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	<title>Integrative &#8211; Science</title>
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	<title>Integrative &#8211; Science</title>
	<link>https://scienmag.com</link>
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		<title>Multiomic map of methylation in Mycoplasma hyorhinis</title>
		<link>https://scienmag.com/multiomic-map-of-methylation-in-mycoplasma-hyorhinis/</link>
		
		<dc:creator><![CDATA[Drew Townsend]]></dc:creator>
		<pubDate>Thu, 22 Oct 2026 10:06:10 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[Science News]]></category>
		<category><![CDATA[bacterial epigenetics]]></category>
		<category><![CDATA[bacterial epigenetics and DNA methylation patterns]]></category>
		<category><![CDATA[bacterial virulence and host interactions]]></category>
		<category><![CDATA[cytosine methylation in bacterial genomes]]></category>
		<category><![CDATA[DNA Methylation]]></category>
		<category><![CDATA[genomic characterization]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[methyltransferases]]></category>
		<category><![CDATA[multiomic]]></category>
		<category><![CDATA[multiomic genomics of Mycoplasma hyorhinis]]></category>
		<category><![CDATA[Mycoplasma hyorhinis]]></category>
		<category><![CDATA[Mycoplasma hyorhinis methylation mapping]]></category>
		<category><![CDATA[nanopore sequencing]]></category>
		<category><![CDATA[Oxford Nanopore sequencing bacterial methylation]]></category>
		<category><![CDATA[porcine pathogen]]></category>
		<category><![CDATA[Proteomics]]></category>
		<category><![CDATA[restriction enzyme identification in Mycoplasma hyorhinis]]></category>
		<category><![CDATA[restriction-modification system analysis]]></category>
		<category><![CDATA[restriction-modification systems]]></category>
		<category><![CDATA[structural modeling]]></category>
		<category><![CDATA[structural modeling of bacterial methylation proteins]]></category>
		<category><![CDATA[Type III methyltransferase]]></category>
		<category><![CDATA[Type III methyltransferase Mod1 in bacteria]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=333059</guid>

					<description><![CDATA[A multiomic study of Mycoplasma hyorhinis SK76 links specific methyltransferases to genome-wide DNA methylation patterns but does not directly test restriction activity.]]></description>
										<content:encoded><![CDATA[<p>A multiomic analysis of Mycoplasma hyorhinis strain SK76 has identified three classes of restriction-modification systems, while showing that only a subset of the encoded proteins and methylation patterns were detected under the laboratory conditions examined. By integrating comparative genomics, structural modeling, quantitative proteomics and genome-wide Oxford Nanopore sequencing, researchers linked a prominent N6-methyladenine signature to the Type III methyltransferase Mod1, associated cytosine methylation with the Type II Mhy3-End3 module, and connected a weaker, bipartite adenine methylation pattern to the Type I specificity subunit HsdS2. DNA-cleavage activity was not tested, so HsdR1, End3 and Res1 remain putative cognate restriction components rather than experimentally validated restriction enzymes.</p>
<p>The study focused on M. hyorhinis, a wall-less bacterium primarily known as a porcine pathogen and as a frequent contaminant of mammalian cell cultures. Its small, streamlined genome and limited genetic tractability make it difficult to characterize individual epigenetic systems through conventional gene manipulation. Earlier work has implicated M. hyorhinis restriction-modification proteins and helicases in virulence and host interactions, while Type II DNA methyltransferases have been reported to modify cytosine residues in host DNA following invasion. The present research did not examine host modification, infection outcomes or clinical effects; instead, it characterized methylation in SK76 bacterial DNA and inferred links between individual restriction-modification components and genome-wide modification patterns.</p>
<p>Researchers began by searching the SK76 genome for components of Type I, Type II and Type III restriction-modification systems. The Type I locus contained one HsdM methyltransferase, one HsdR restriction subunit and three HsdS specificity subunits. HsdS1 and HsdS2 occupy adjacent, oppositely oriented genes with a 25-base-pair overlap, whereas HsdS3 is located at a distant chromosomal position. Sequence analysis also corrected the predicted start of hsdS1 in two genome annotations: the actual start lies upstream and includes a putative promoter region. All three HsdS proteins contain two N6 DNA methylase target-recognition domains, but their sequence identities and structural completeness differ. HsdS2 retains a complete coiled-coil central helical region, HsdS1 contains a shortened helix, and HsdS3 lacks the second alpha-helix in that region, suggesting reduced functionality or pseudogenization in the latter variants.</p>
<p>Quantitative proteomics supported a hierarchy among the Type I components. HsdS1 and HsdS2 were detected in both exponential- and stationary-phase cultures, although HsdS1 protein intensity was approximately three log2 units lower than that of HsdS2. No unique peptides could be confidently assigned to HsdS3. The HsdM methyltransferase and HsdR restriction subunit were also detected, and HsdS2, HsdM and HsdR each showed lower abundance in stationary phase than in exponential phase. AlphaFold-Multimer models indicated that the HsdM and HsdS variants could form structurally plausible M2S assemblies, but the models did not establish which specificity subunit functions in vivo. HsdS2 was therefore identified as the most likely principal specificity subunit because of its comparatively high abundance, structural integrity and association with the detected bipartite methylation motif.</p>
<p>The three Type II systems in SK76 contain cytosine methyltransferases Mhy1, Mhy2 and Mhy3, each positioned near a putative restriction-associated protein designated End1, End2 or End3. Phylogenetic analyses supported these local pairings: Mhy1 and End1 clustered with a Mycoplasma agalactiae pair, Mhy2 and End2 with Ureaplasma parvum proteins, and Mhy3 and End3 with Sau3AI-related enzymes from Staphylococcus aureus. Proteomics distinguished the Mhy3-End3 pair from the other candidates. Mhy3 and End3 were consistently detected at substantial abundance, whereas Mhy1 and Mhy2 were not detected and End1 was absent from the measurements. End2 produced a low-confidence identification supported by only two peptides, leaving its biological status uncertain. Failure to detect a protein does not exclude expression below the sensitivity of the mass-spectrometry workflow.</p>
<p>Structural and sequence analysis reinforced the evidence for Mhy3-End3. The predicted Mhy3 structure closely resembled the Staphylococcus aureus Sau3AI methyltransferase, with a root-mean-square deviation of 0.4 angstrom, and contained the PCQ catalytic motif characteristic of C5 cytosine methyltransferases plus an FxGxG motif involved in S-adenosyl-L-methionine binding. The End3 model had a 1.7-angstrom RMSD from the corresponding Sau3AI restriction-enzyme structure and retained a PD-(D/E)XK nuclease motif. Together, these findings support predicted competence and the Mhy3-End3 pairing, but they do not demonstrate that End3 cleaves DNA. The absence of detectable Mhy1 and Mhy2 likewise provides no evidence for their methylation activity in this experiment, without ruling out weak expression or modification below the assays’ detection thresholds.</p>
<p>Oxford Nanopore sequencing supplied a genome-wide view of three modified DNA bases: N6-methyladenine, 5-methylcytosine and 4-methylcytosine. At a moderate motif-discovery threshold of 0.5, the dominant adenine signature was centered on GGAT and occurred at 2,333 genomic sites with 77.2% read coverage. Methylation at this motif was distributed across both strands at similar overall levels, with 47.5% on the positive strand and 50.7% on the negative strand, rather than showing a global strand bias. A second, lower-frequency adenine pattern had the bipartite arrangement TA-N6-ATC and appeared at 890 sites with 47.2% coverage. The predominant cytosine signal was centered on the palindromic GATC sequence, found at 2,320 sites with 90.1% coverage. Only seven 4-methylcytosine sites were detected genome-wide, and the proposed CATCC-centered pattern was supported by just two methylated sites with 0.016 coverage, making a robust biological interpretation unlikely.</p>
<p>Integration of the motifs with protein and sequence data yielded specific but inferential assignments. Mod1 was identified as the principal active Type III methyltransferase because it retained the catalytic DPPY and FxGxG motifs, was detected in the proteome and matched the asymmetric GGAT-centered N6-methyladenine pattern. The compact Type III locus also contained Mod2A, Mod2B, Mod3A and Mod3B adjacent to the Res1 restriction subunit. Mod2A and Mod3A were annotated as truncated proteins lacking the catalytic motif, although short sequence repeats could theoretically restore full-length reading frames through frameshifting. Unique peptides were detected for Mod2B and Mod3B, but not for the truncated variants or putative restored products. The investigators consequently described the additional Mod homologues as possible evolutionary remnants or conditionally regulated elements whose activity under other conditions remains unresolved.</p>
<p>The Type II cytosine pattern was assigned to Mhy3, which targets GATC-containing DNA, with End3 retained as its most plausible restriction partner. The lower-frequency bipartite adenine motif was attributed most plausibly to the Type I system, specifically HsdS2, because bipartite recognition is characteristic of Type I systems and the signal was less abundant than the principal GGAT pattern. Across the three classes, gene presence alone therefore overstated the methylome detected under the tested conditions. The best-supported modules were HsdM with HsdS2, Mhy3 with End3, and Mod1 with Res1, whereas several annotated methyltransferases and specificity subunits lacked corresponding protein or methylation evidence. The study demonstrates how genome-wide modification measurements can narrow predictions generated from sequence alone in a genetically intractable organism, but it does not directly establish restriction activity.</p>
<p>Comparative analysis of 22 M. hyorhinis strains indicated that most restriction-modification genes are broadly conserved, with methyltransferases generally more conserved than restriction enzymes. The truncated organization of the mod2-mod3 region was also conserved across multiple strains, supporting the view that it is a stable but potentially regulatable feature rather than an anomaly confined to SK76. Previously published transposon-mutagenesis data from strain JF5820 classified the methyltransferases as essential, along with End2, while End1, End3 and Res1 were classified as non-essential in that assay. Because the present study used SK76 and did not directly assay restriction activity or essentiality, it cannot establish that these functions are interchangeable across strains. Overall, the multiomic map identifies methylation patterns and probable methyltransferase assignments under one set of culture conditions, while phase variation, low-level expression and DNA cleavage remain to be tested directly.</p>
<p><strong>Subject of Research:</strong> Multiomic characterization of DNA methylation and restriction-modification systems in Mycoplasma hyorhinis SK76</p>
<p><strong>Article Title:</strong> Integrative multiomic characterization of the methylome and restriction-modification repertoire of Mycoplasma hyorhinis SK76</p>
<p><strong>Article References:</strong> Frutos-Grilo, E., D’Angelo, M., Anglada-Girotto, M., &amp; Serrano, L. (2026). Integrative multiomic characterization of the methylome and restriction-modification repertoire of Mycoplasma hyorhinis SK76. <em>Frontiers in Microbiology, 17</em>, Article 1950185. <a href="https://doi.org/10.3389/fmicb.2026.1950185" rel="noopener noreferrer">https://doi.org/10.3389/fmicb.2026.1950185</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.3389/fmicb.2026.1950185" rel="noopener noreferrer">10.3389/fmicb.2026.1950185</a></p>
<p><strong>Keywords:</strong> Mycoplasma hyorhinis, DNA methylation, restriction-modification systems, methyltransferases, Nanopore sequencing, proteomics, structural modeling, bacterial epigenetics, Type III methyltransferase, porcine pathogen, Integrative, multiomic</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">333059</post-id>	</item>
		<item>
		<title>Machine Learning Identifies Two Gene Markers of Allergic Rhinitis</title>
		<link>https://scienmag.com/machine-learning-identifies-two-gene-markers-of-allergic-rhinitis/</link>
		
		<dc:creator><![CDATA[Juliet Wilcox]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 22:27:16 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[allergic rhinitis]]></category>
		<category><![CDATA[allergic rhinitis gene markers]]></category>
		<category><![CDATA[CD83]]></category>
		<category><![CDATA[cell adhesion]]></category>
		<category><![CDATA[computational identification of allergy-related genes]]></category>
		<category><![CDATA[diagnostic biomarkers]]></category>
		<category><![CDATA[gene expression-based disease separation]]></category>
		<category><![CDATA[immune heterogeneity]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[limitations of retrospective gene studies]]></category>
		<category><![CDATA[Machine learning]]></category>
		<category><![CDATA[machine learning in allergy diagnostics]]></category>
		<category><![CDATA[microarray analysis of allergic rhinitis]]></category>
		<category><![CDATA[nasal tissue gene expression analysis]]></category>
		<category><![CDATA[network]]></category>
		<category><![CDATA[potential molecular targets for allergy diagnosis]]></category>
		<category><![CDATA[public gene-expression datasets]]></category>
		<category><![CDATA[ROC curve performance in gene classifiers]]></category>
		<category><![CDATA[T-cell profiling]]></category>
		<category><![CDATA[TNFSF14]]></category>
		<category><![CDATA[TNFSF14 and CD83 allergy biomarkers]]></category>
		<category><![CDATA[Transcriptomics]]></category>
		<category><![CDATA[two-gene classifier for allergic rhinitis]]></category>
		<category><![CDATA[validation of gene markers in external datasets]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=330869</guid>

					<description><![CDATA[A cross-algorithm analysis of public nasal-tissue data identified TNFSF14 and CD83 as a two-gene panel that distinguished allergic-rhinitis samples from controls, while computational immune profiling revealed T-cell remodeling and two exploratory molecular groups.]]></description>
										<content:encoded><![CDATA[<p>A computational analysis of public nasal-tissue expression data found that the genes TNFSF14 and CD83, when assessed together, separated samples from people with allergic rhinitis from healthy controls. The study used one discovery cohort and two external validation datasets, identifying a two-gene classifier that reached an area under the receiver operating characteristic curve, or AUC, of 0.968 in the training set, 1.000 in the smaller validation set GSE46171 and 0.758 in GSE40037. These results position the pair as a promising candidate panel for further development, although the authors caution that the analysis is retrospective, based on modest numbers of stored samples, and does not establish that the genes cause disease or are ready for clinical diagnosis.</p>
<p>The research team began with a microarray discovery cohort, GSE75011, containing 15 samples from people with allergic rhinitis and 25 healthy controls. Using a deliberately inclusive screening threshold of p below 0.05 and an absolute log2 fold change above 0.585, the authors identified transcripts that differed between cases and controls. They intersected these differentially expressed genes with a curated set of 1,542 cell-adhesion-related genes from the Molecular Signatures Database, producing 38 differentially expressed adhesion-related genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses associated this group with leukocyte adhesion, cell activation, cytokine-receptor binding, focal adhesion and immunoglobulin-superfamily cell-adhesion-molecule signaling. The researchers emphasize that the strategy was designed to capture immune-regulatory programs involved in cell-cell interaction rather than to restrict attention to structural adhesion proteins alone.</p>
<p>Protein-interaction mapping provided a second layer of prioritization. The investigators queried the STRING database, retained interactions with confidence scores of at least 0.15, visualized the network in Cytoscape and used the MCODE plug-in to identify densely connected modules. MCODE detected two modules, and the highest-scoring module contained 13 candidate hub genes. All 13 showed statistically significant expression differences between allergic-rhinitis and control samples in the discovery cohort. CX3CR1 and CADM1 were elevated in allergic rhinitis, whereas NR4A3, PDCD1, MAP3K8, TNFSF14, ZC3H12A, DUSP1, NLRP3, SMAD7, TBX21, CD83 and ICOSLG were reduced. Functional annotation linked the hub candidates to CD4-positive alpha-beta T-cell differentiation, T-cell activation and leukocyte cell-cell adhesion, extending the analysis from adhesion-associated expression toward the immune circuitry in which those signals sit.</p>
<p>The 13 hub candidates were then screened in parallel by least absolute shrinkage and selection operator regression, random forest and support vector machine recursive feature elimination. LASSO retained five genes at its cross-validated penalty, random forest ranked six above a MeanDecreaseGini threshold of 1, and SVM-RFE achieved its lowest classification error with three features. The overlap across all three algorithms consisted of TNFSF14 and CD83. In the discovery cohort, TNFSF14 alone produced an AUC of 0.931 and CD83 an AUC of 0.845; the combined model reached 0.968. The authors also incorporated the two markers into a nomogram for estimating sample-level probability, examined calibration between predicted and observed status and used decision-curve analysis to assess performance across probability thresholds.</p>
<p>External testing produced variable but encouraging results. The two-gene classifier achieved an AUC of 1.000 in GSE46171, which included six allergic-rhinitis samples and three controls, but the authors explicitly warn that such a small cohort warrants cautious interpretation. Its AUC was 0.758 in GSE40037, a dataset comprising 10 cases and 12 controls, indicating that discrimination persisted but was less than in the discovery set. At the individual-marker level, CD83 retained moderate diagnostic value in both validation cohorts, whereas TNFSF14 performance varied. Both genes tended to be lower in allergic-rhinitis samples overall, yet their group differences were not identical across datasets: TNFSF14 remained significantly reduced in GSE46171 but not GSE40037, while CD83 was significantly reduced in GSE40037 but not GSE46171. The combined panel therefore appeared more reproducible than either gene alone in this analysis.</p>
<p>Both markers are embedded in immune pathways relevant to allergic inflammation. TNFSF14 encodes a TNF-superfamily ligand that binds herpesvirus entry mediator and lymphotoxin-beta receptors to stimulate lymphocyte proliferation and modulate immune responses. Its reduced expression in allergic rhinitis is not straightforward to interpret because the gene has been associated with immune activation in other settings; the authors say altered immune-cell composition, disease stage or compensatory responses could account for the observation. CD83 is associated with dendritic-cell maturation and regulation, and both membrane-bound and soluble forms can influence T- and B-cell responses. Lower bulk-tissue expression may likewise reflect differences in dendritic-cell abundance or composition rather than reduced regulation within individual cells. The researchers therefore interpret both signals as immune-associated transcriptional features, not direct evidence of impaired molecular pathways or causal contributions to disease.</p>
<p>Immune deconvolution suggested that the expression differences sat within a remodeled T-cell environment. Single-sample gene set enrichment analysis showed lower activated dendritic-cell and T follicular-helper signatures in allergic-rhinitis samples, alongside a moderate increase in a general T-helper signature and a reduction in T-cell co-stimulation scores. CIBERSORT produced a complementary view, with lower inferred levels of resting memory CD4 T cells and higher levels of naive CD4 T cells in cases. Pearson correlations showed that TNFSF14 and CD83 had distinct but overlapping relationships with multiple immune-cell estimates. These computational results are consistent with a changed cellular and functional context in the nasal samples, but they do not establish which immune populations cause the expression shifts. Bulk transcriptomics can make changes in cell abundance or composition resemble altered regulation within particular cell types.</p>
<p>Expression-based clustering further divided the allergic-rhinitis samples in the training cohort into two exploratory groups. Non-negative matrix factorization indicated a two-group structure, and principal component analysis placed the groups in different transcriptomic regions. TNFSF14 expression was higher in Subtype 2, whereas CD83 was higher in Subtype 1. The groups also differed in single-sample estimates of plasmacytoid dendritic cells, helper T cells and tumor-infiltrating lymphocyte-related signals, as well as in antigen-presenting-cell co-stimulation, checkpoint activity, cytolytic activity and T-cell co-stimulation. MCP-counter indicated broader differences in inferred immune-cell composition. Genes distinguishing the groups were enriched for depyrimidination, ketone catabolism and small-molecule catabolic processes, pointing to possible metabolic differences alongside immune variation. Because clustering was based on only the samples in the discovery cohort, the authors describe these groups as exploratory molecular patterns rather than definitive clinical subtypes.</p>
<p>The study also mapped possible regulatory influences, but these results remain hypothesis-generating. NetworkAnalyst predictions connected both markers to candidate transcription factors, including members of the NF-kappa-B, STAT and IRF families, while experimentally supported miRNA interactions from miRTarBase were combined with lncRNA-miRNA relationships to construct a putative competing endogenous RNA network. TNFSF14 occupied a more central position and was linked to more predicted non-coding RNA regulators than CD83. Enrichment against DSigDB associated the expression signatures with compounds including puromycin, menadione, sanguinarine and betamethasone valerate, but database similarity does not establish that any compound treats allergic rhinitis or alters these markers in patients. The analysis also lacks protein measurements, functional experiments, detailed severity and treatment information, control for comorbid asthma or conjunctivitis, and broad representation across regions and populations.</p>
<p>Taken together, the findings offer a two-gene computational signature and a possible framework for understanding molecular variation within allergic rhinitis. TNFSF14 and CD83 warrant experimental validation in independent nasal-tissue or blood samples, assessment of whether their RNA levels correspond to protein abundance, and testing of whether manipulating either gene changes dendritic-cell or T-cell behavior. Prospective studies with larger and clinically annotated cohorts would also be needed to test whether the panel retains accuracy in people receiving different treatments, those with different symptom burdens and those with coexisting allergic disease. For now, the strongest conclusion is that a cross-algorithm analysis of adhesion-associated immune expression consistently selected TNFSF14 and CD83, with functional and clinical relevance still awaiting direct evaluation.</p>
<p><strong>Subject of Research:</strong> Transcriptomic and immune-signature analysis of candidate diagnostic biomarkers in allergic rhinitis</p>
<p><strong>Article Title:</strong> Integrative Network Analysis and Machine Learning Identify Cell Adhesion‐Related Biomarkers and Immune Heterogeneity in Allergic Rhinitis</p>
<p><strong>Article References:</strong> He, G., &amp; Zhang, L. (2026). Integrative Network Analysis and Machine Learning Identify Cell Adhesion‐Related Biomarkers and Immune Heterogeneity in Allergic Rhinitis. <em>Immunity, Inflammation and Disease, 14</em>(10), Article e70562. <a href="https://doi.org/10.1002/iid3.70562" rel="noopener noreferrer">https://doi.org/10.1002/iid3.70562</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1002/iid3.70562" rel="noopener noreferrer">10.1002/iid3.70562</a></p>
<p><strong>Keywords:</strong> allergic rhinitis, TNFSF14, CD83, diagnostic biomarkers, machine learning, transcriptomics, immune heterogeneity, cell adhesion, T-cell profiling, public gene-expression datasets, Integrative, Network</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">330869</post-id>	</item>
		<item>
		<title>South Indian Parkinson’s study links gut microbes to inflammation</title>
		<link>https://scienmag.com/south-indian-parkinsons-study-links-gut-microbes-to-inflammation/</link>
		
		<dc:creator><![CDATA[Cassandra Pierce]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 15:24:45 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[16S rRNA gene sequencing in Parkinson’s]]></category>
		<category><![CDATA[16S rRNA sequencing]]></category>
		<category><![CDATA[functional]]></category>
		<category><![CDATA[gut microbes and neuroinflammation]]></category>
		<category><![CDATA[Gut microbiome]]></category>
		<category><![CDATA[gut-brain axis and Parkinson's]]></category>
		<category><![CDATA[inflammation]]></category>
		<category><![CDATA[inflammation-linked gut bacteria]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[Kerala]]></category>
		<category><![CDATA[metabolic pathways]]></category>
		<category><![CDATA[microbial diversity in Parkinson’s patients]]></category>
		<category><![CDATA[microbial signatures in Parkinson’s]]></category>
		<category><![CDATA[microbiome]]></category>
		<category><![CDATA[microbiome dysbiosis]]></category>
		<category><![CDATA[microbiota and neurodegeneration]]></category>
		<category><![CDATA[multi-omics]]></category>
		<category><![CDATA[Parkinson's disease]]></category>
		<category><![CDATA[Parkinson’s disease gut microbiome]]></category>
		<category><![CDATA[population-specific microbiome analysis]]></category>
		<category><![CDATA[regional microbiota differences in disease]]></category>
		<category><![CDATA[regional variations in gut microbiota]]></category>
		<category><![CDATA[South India]]></category>
		<category><![CDATA[South Indian microbiome study]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=329641</guid>

					<description><![CDATA[A Kerala cohort study linked Parkinson’s disease with distinct gut microbial communities and predicted changes in inflammatory, neurotransmitter and energy-related metabolic pathways.]]></description>
										<content:encoded><![CDATA[<p>A study of people with Parkinson’s disease in Kerala, India, has identified gut microbiome patterns associated with the disorder, including increased abundance of several microbial groups linked by the researchers to inflammation and reduced abundance of groups associated with anti-inflammatory activity. The findings, based on 16S rRNA gene amplicon sequencing, provide a population-specific snapshot of the gut microbiome in South Indian patients and highlight candidate microbial signatures that may help guide broader multi-omics investigations into Parkinson’s disease.</p>
<p>Parkinson’s disease is a progressive neurodegenerative disorder characterized by aggregation of alpha-synuclein in dopaminergic neurons. The new study examined the gut microbiomes of people with Parkinson’s disease and healthy controls from Kerala, a region where the microbial composition of the population may differ from that studied in other parts of the world. Researchers said the design was motivated in part by geographic variation in gut microbial communities, which makes local evidence important when evaluating proposed links among microbiota, inflammation and neurodegeneration.</p>
<p>The investigators found significant differences in both microbial diversity and taxonomic composition between the Parkinson’s disease and control groups. The microbial community in the Parkinson’s group contained higher relative abundances of Akkermansia, Bifidobacterium, Escherichia-Shigella, Collinsella, an unclassified Eggerthellaceae genus, an unclassified Enterobacterales group and Intestinimonas. At the same time, Bacteroides, Lachnospira, Agathobacter, Prevotella and Erysipelotrichaceae UCG-003 were reduced. These are comparative observations from this cohort; they do not establish that any particular organism causes Parkinson’s disease or that changing the microbiome would alter clinical outcomes.</p>
<p>The team then used predictive functional profiling to estimate which metabolic capabilities might be associated with the observed microbial communities. The analysis pointed to differences in pathways involved in neurotransmitter-related processes, including dopaminergic, glutamatergic and GABAergic metabolism. Predicted shifts also extended to amino acid, polyamine, nucleotide and energy metabolism. An integrative network analysis connected Parkinson’s-enriched taxa with dysregulated metabolic pathways, suggesting that taxonomic changes and predicted functional potential may form coordinated biological patterns rather than isolated microbial differences.</p>
<p>Because the work was based on amplicon sequencing and computational functional prediction, it cannot directly measure microbial metabolites, inflammatory molecules or the brain. The study therefore identifies associations and testable candidates rather than demonstrating a gut-microbiome mechanism for Parkinson’s disease. Larger studies incorporating metabolomics, metagenomics, host inflammatory measurements and longitudinal clinical data will be needed to determine whether the reported signatures are reproducible, causally relevant or capable of distinguishing Parkinson’s disease in other populations. Within those limits, the research offers an exploratory regional baseline and a framework for future multi-omics studies of inflammation-related microbiome patterns in Parkinson’s disease.</p>
<p><strong>Subject of Research:</strong> Gut microbiome composition and predicted metabolic functions in South Indian patients with Parkinson’s disease</p>
<p><strong>Article Title:</strong> Integrative microbiome and functional profiling decodes pro-inflammatory gut microbiome signatures in South Indian patients with Parkinson’s disease</p>
<p><strong>Article References:</strong> Painadath Alikunju, A., Jose, D., Venkatachalam, S., Tajudeen, J., Azhchath Vasu, D., K K, D., Raman, G., L, G. T., Thomas, F., K P, D., Manoj, N., Krishnan, S., &amp; P S, B. C. (2026). Integrative microbiome and functional profiling decodes pro-inflammatory gut microbiome signatures in South Indian patients with Parkinson’s disease. <em>npj Parkinson&#x27;s Disease</em>. <a href="https://doi.org/10.1038/s41531-026-01547-w" rel="noopener noreferrer">https://doi.org/10.1038/s41531-026-01547-w</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1038/s41531-026-01547-w" rel="noopener noreferrer">10.1038/s41531-026-01547-w</a></p>
<p><strong>Keywords:</strong> Parkinson’s disease, gut microbiome, microbiome dysbiosis, inflammation, 16S rRNA sequencing, metabolic pathways, South India, Kerala, multi-omics, Integrative, microbiome, functional</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">329641</post-id>	</item>
		<item>
		<title>TIMP1 linked to anoikis resistance and metastasis in esophageal cancer</title>
		<link>https://scienmag.com/timp1-linked-to-anoikis-resistance-and-metastasis-in-esophageal-cancer/</link>
		
		<dc:creator><![CDATA[Nathaniel Bowman]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 10:57:38 +0000</pubDate>
				<category><![CDATA[Cancer]]></category>
		<category><![CDATA[anoikis resistance]]></category>
		<category><![CDATA[bulk]]></category>
		<category><![CDATA[cancer metastasis]]></category>
		<category><![CDATA[cancer metastasis models]]></category>
		<category><![CDATA[esophageal squamous cell carcinoma]]></category>
		<category><![CDATA[gene co-expression network analysis]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[metastasis mechanisms]]></category>
		<category><![CDATA[prognostic gene signature]]></category>
		<category><![CDATA[prognostic modeling]]></category>
		<category><![CDATA[single-cell]]></category>
		<category><![CDATA[Single-Cell RNA Sequencing]]></category>
		<category><![CDATA[single-cell RNA sequencing in cancer]]></category>
		<category><![CDATA[targeted therapy development]]></category>
		<category><![CDATA[TIMP1]]></category>
		<category><![CDATA[TIMP1 gene regulation]]></category>
		<category><![CDATA[Transcriptomics]]></category>
		<category><![CDATA[tumor cell survival pathways]]></category>
		<category><![CDATA[tumor invasion]]></category>
		<category><![CDATA[tumor invasion and spread]]></category>
		<category><![CDATA[tumor microenvironment in esophageal cancer]]></category>
		<category><![CDATA[xenograft models]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=328876</guid>

					<description><![CDATA[Single-cell and bulk transcriptomic analyses linked TIMP1 to anoikis resistance in esophageal squamous cell carcinoma, while cell and mouse experiments showed that lowering TIMP1 reduced malignant behaviors and lung colonization.]]></description>
										<content:encoded><![CDATA[<p>Researchers have identified TIMP1 as a candidate regulator of anoikis resistance in esophageal squamous cell carcinoma, a cancer type in which tumor cells can survive after detaching from surrounding tissue and acquire traits associated with invasion and distant spread. Integrated single-cell and bulk RNA analyses produced a seven-gene prognostic model, while laboratory experiments showed that reducing TIMP1 levels suppressed several malignant behaviors in esophageal cancer cells and diminished tumor growth and lung colonization in nude mice.</p>
<p>Anoikis is a form of programmed cell death triggered when cells lose contact with the extracellular matrix. The researchers began by calculating anoikis-related signatures across cell types in single-cell RNA-sequencing data from esophageal squamous cell carcinoma, or ESCC. These scores revealed differences among cell populations, allowing the team to identify differentially expressed genes associated with the process. The investigators then used weighted gene co-expression network analysis on the GSE53625 bulk-transcriptomics cohort and intersected its results with the single-cell findings. This integration narrowed the search to 428 candidate anoikis-related genes.</p>
<p>The researchers next developed a risk model intended to estimate patient prognosis. Univariate Cox regression and least absolute shrinkage and selection operator, or LASSO, Cox regression were used to construct a seven-gene model comprising ATP8B3, KIF18B, TIMP1, BCAT1, SLC39A6, CLEC6A and TNS3. The model showed prognostic value in both the GSE53625 cohort and an independent cohort from The Cancer Genome Atlas. A nomogram was also created by integrating the gene-based risk score with clinicopathological features. The study therefore links molecular patterns of anoikis to outcome estimates in ESCC, but the risk model remains a research tool rather than a clinically validated test.</p>
<p>Among the model’s genes, TIMP1 was selected for functional testing. In vitro assays indicated that knocking down TIMP1 reduced ESCC cell proliferation, migration, invasion and colony formation. The same treatment reduced resistance to anoikis and increased apoptosis, supporting the hypothesis that TIMP1 helps tumor cells tolerate detachment from their substrate. In vivo experiments in nude mice provided a complementary result: TIMP1 knockdown suppressed growth of subcutaneous ESCC xenografts and reduced experimental pulmonary colonization. These findings are consistent with a role for TIMP1 in maintaining anoikis-resistant, metastatic phenotypes, although the experiments do not establish the full molecular route through which it acts.</p>
<p>The work points to TIMP1 as both a component of an ESCC prognostic signature and a biologically relevant candidate regulator, but several limitations remain. The downstream signaling mediators and direct molecular interactions connecting TIMP1 to anoikis resistance were not characterized. The clinical cohorts establish associations and prognostic performance rather than showing that the seven-gene model improves care, and the functional evidence comes from cultured cells and mouse xenograft models rather than human interventional studies. The researchers accordingly describe the results as a rationale for further mechanistic and translational investigation, not as an immediate basis for treatment selection or clinical decision-making.</p>
<p><strong>Subject of Research:</strong> TIMP1 regulation of anoikis resistance and metastatic potential in esophageal squamous cell carcinoma</p>
<p><strong>Article Title:</strong> Integrative single-cell and bulk transcriptomic analyses identify timp1 as a candidate regulator of anoikis resistance and metastatic potential in esophageal squamous cell carcinoma</p>
<p><strong>Article References:</strong> Li, S., Liu, J., Wang, N., Tao, Z., Xie, K., Jiang, W., &amp; Ma, H. (2026). Integrative single-cell and bulk transcriptomic analyses identify timp1 as a candidate regulator of anoikis resistance and metastatic potential in esophageal squamous cell carcinoma. <em>BMC Cancer</em>. <a href="https://doi.org/10.1186/s12885-026-17208-3" rel="noopener noreferrer">https://doi.org/10.1186/s12885-026-17208-3</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12885-026-17208-3" rel="noopener noreferrer">10.1186/s12885-026-17208-3</a></p>
<p><strong>Keywords:</strong> esophageal squamous cell carcinoma, TIMP1, anoikis resistance, single-cell RNA sequencing, transcriptomics, cancer metastasis, prognostic modeling, tumor invasion, xenograft models, Integrative, single-cell, bulk</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">328876</post-id>	</item>
		<item>
		<title>Coriander metabolites linked to activity against drug-resistant urinary bacteria</title>
		<link>https://scienmag.com/coriander-metabolites-linked-to-activity-against-drug-resistant-urinary-bacteria/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 07:39:25 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[analysis]]></category>
		<category><![CDATA[antibacterial activity against multidrug-resistant E. coli]]></category>
		<category><![CDATA[antibiofilm activity]]></category>
		<category><![CDATA[Apiaceae herbs antimicrobial properties]]></category>
		<category><![CDATA[biofilm formation inhibition]]></category>
		<category><![CDATA[chemometric]]></category>
		<category><![CDATA[chemometric analysis of herbal extracts]]></category>
		<category><![CDATA[coriander]]></category>
		<category><![CDATA[Coriander metabolites]]></category>
		<category><![CDATA[drug-resistant urinary bacteria]]></category>
		<category><![CDATA[fatty acids]]></category>
		<category><![CDATA[herbal extracts against uropathogenic bacteria]]></category>
		<category><![CDATA[identification of bioactive plant metabolites]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[metabolite profiling of coriander]]></category>
		<category><![CDATA[Metabolomics]]></category>
		<category><![CDATA[multidrug resistance]]></category>
		<category><![CDATA[natural alternatives to antibiotics]]></category>
		<category><![CDATA[plant extracts]]></category>
		<category><![CDATA[plant-derived compounds for urinary tract infections]]></category>
		<category><![CDATA[quercetin]]></category>
		<category><![CDATA[untargeted liquid chromatography mass spectrometry]]></category>
		<category><![CDATA[urinary tract infections]]></category>
		<category><![CDATA[uropathogenic E. coli]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=328003</guid>

					<description><![CDATA[An integrated metabolomics and laboratory study links coriander’s chemical profile with the strongest antibacterial activity against multidrug-resistant uropathogenic E. coli, while all three tested herbs reduced biofilm formation.]]></description>
										<content:encoded><![CDATA[<p>In a laboratory study of methanolic extracts from three edible Apiaceae herbs, coriander showed the strongest antibacterial activity against clinical multidrug-resistant uropathogenic Escherichia coli, while extracts of all three herbs significantly reduced biofilm formation. The comparative investigation combined untargeted liquid chromatography–quadrupole time-of-flight tandem mass spectrometry, multivariate chemometrics, antimicrobial testing and biofilm assays. A total of 167 metabolites were tentatively annotated, allowing researchers to connect distinct chemical signatures with observed biological effects. These findings identify candidate compounds for further testing, but they do not establish that any herb or metabolite is safe or effective for treating urinary tract infections in people.</p>
<p>Celery (Apium graveolens L.), coriander (Coriandrum sativum L.) and parsley (Petroselinum crispum) were purchased from a commercial market in Alexandria, Egypt, and their aerial parts were extracted separately with methanol. Each methanolic extract was then partitioned into a methylene chloride fraction and an aqueous mother liquor. The biological tests used 20 uropathogenic E. coli isolates obtained from private laboratories in Alexandria. Susceptibility testing showed that every isolate was resistant to amoxicillin-clavulanic acid, doxycycline and nalidixic acid, while all were susceptible to ertapenem, imipenem and meropenem. Twelve isolates were classified as strong biofilm formers, four as intermediate formers and four as non-biofilm formers.</p>
<p>The antibacterial results varied markedly among the herbs and fractions. Coriander’s total methanolic extract and aqueous mother liquor each produced a minimum inhibitory concentration of 3.75 micrograms per millilitre, the lowest value reported for the plant preparations. Its methylene chloride fraction required 100 micrograms per millilitre. Celery was less active: the total methanolic extract had a minimum inhibitory concentration of 50 micrograms per millilitre, while its aqueous mother liquor reached 25 micrograms per millilitre and its methylene chloride fraction showed no detectable activity under the tested conditions. Parsley’s total extract and aqueous mother liquor likewise had no detectable activity, although its methylene chloride fraction inhibited growth at 100 micrograms per millilitre. Ciprofloxacin and norfloxacin had minimum inhibitory concentrations between 0.9 and 1.9 micrograms per millilitre alone. When combined with coriander extract, the effects were described as additive, with no evidence of synergism or antagonism in the tested combinations.</p>
<p>Untargeted metabolomics produced markedly different profiles for the three herbs. Analyses were run in positive and negative electrospray ionization modes and incorporated retention time, accurate mass, predicted molecular formulas and tandem mass-spectrometry fragmentation patterns. Compound detection and processing initially yielded 4,861 features in negative mode and 3,155 in positive mode; after peak detection, deisotoping, chromatographic alignment and filtering, 580 and 512 aligned features, respectively, remained for chemometric analysis. The final annotation included flavonoids and glycosides, isoflavones, phenolic acids, coumarins, amino-acid derivatives, fatty acids and lipids, chlorins and a lignan. All 167 annotations were assigned level 2 confidence, meaning they were tentative identifications supported by library or literature spectral matches rather than confirmed with authentic standards.</p>
<p>Coriander had the richest and most diverse flavonoid and phenolic profile in this analysis. Its extracts contained quercetin, multiple quercetin conjugates, apigenin glucuronide, luteolin-7-O-glucoside, kaempferol-3-O-glucorhamnoside, several caffeoylquinic-acid derivatives, ferulic acid and assorted coumarins. Celery was distinguished by compounds including apiin, luteolin and apigenin conjugates, 4,5-dicaffeoylquinic acid and the coumarin marmesin. Parsley contained numerous furanocoumarins, including cnidilin, 5-hydroxyxanthotoxin, pinnatin, bergaptol and isoimperatorin, as well as rhamnetin and isorhamnetin conjugates. The researchers also detected chlorin-related molecules in all three herbs and the lignan eucommicin A in celery and coriander.</p>
<p>Principal component analysis, hierarchical cluster analysis and partial least squares discriminant analysis separated the three samples according to their metabolite profiles. In negative-ion mode, the first two principal components accounted for 95% of the observed variability, and the samples formed three distinct clusters. Coriander was associated with high levels of quercetin 3-O-rutinoside, eucommicin A and several hydroxylated C18 fatty acids, including three trihydroxy-octadecaenoic-acid features and hydroxy-octadecatrienoic- and hydroxy-octadecadienoic-acid features. Celery was associated with apiin, luteolin 7-O-apiosylglucoside, pyroglutamic acid, lunularic acid and a glycerophosphoinositol. Parsley was distinguished by fructose-phenylalanine and features including bergaptol. Supervised models separating celery from parsley reported R² and Q² values of 0.99 in both ionization modes, although the limited set of triplicate samples means these internal performance values should not be confused with independent validation.</p>
<p>Partial least squares regression then related metabolite abundance to the measured minimum inhibitory concentrations. The negative-ion model had cumulative R² of 0.92 and Q² of 0.87, while the positive-ion model had R² of 0.94 and Q² of 0.83. In both models, coriander’s metabolite pattern was inversely positioned relative to minimum inhibitory concentration, whereas parsley lay closest to the values associated with inactivity. Prominent variables associated with antibacterial activity included quercetin 3-O-rutinoside, trihydroxy-octadecaenoic-acid isomers, hydroxy-octadecatrienoic acid, hydroxy-octadecadienoic acid and eucommicin A. Positive-ion analysis additionally highlighted furanocoumarin hexosides, a methoxy-ethoxycarbonyl coumarin and a chlorin-related compound, 132-hydroxypheophorbide-A methyl ester. These are statistical associations within extract-level data, not demonstrations that any individual metabolite caused the observed inhibition.</p>
<p>All tested plant preparations also inhibited biofilm formation, whether used alone or in combinations with ciprofloxacin or norfloxacin. Biofilm mass was measured after 24 hours by fixing the attached biomass with methanol, staining it with crystal violet, releasing the dye with acetic acid and measuring absorbance at 630 nanometres. The study reported significant reductions in biofilm mass across the extract and antibiotic-combination conditions, including tests with sub-minimum-inhibitory-concentration levels of the plant extracts. The researchers discussed several possible contributors, including quercetin derivatives, phenolic compounds and coumarins that have activity against cell membranes, quorum sensing, extracellular polymeric substances and other biofilm-maintenance processes in earlier studies. Those mechanisms remain hypotheses for the herb extracts tested here, which were not separated into constituent compounds during the assays.</p>
<p>The bacterial collection also displayed several virulence-associated genes, adding context to the laboratory model. The fimH gene was present in 80% of the isolates, afa genes in 90%, papC in 76% and hly genes in 76%; the cytotoxic necrotizing factor gene occurred in 35%. These findings characterize the tested isolates but do not show that the herbal preparations affect the corresponding virulence traits. Moreover, the experiments were performed in vitro with commercial plant material, methanol-derived fractions and an artificial biofilm assay. They did not examine pharmacokinetics, host toxicity, urinary concentrations, treatment outcomes or the possibility of interactions with conventional drugs in patients.</p>
<p>For that reason, the results are best understood as a chemical and activity map for future research. The strongest candidates identified for isolation include quercetin 3-O-rutinoside, trihydroxy-octadecaenoic acid, hydroxy-octadecatrienoic acid, hydroxy-octadecadienoic acid and eucommicin A, together with selected coumarins and chlorin-related metabolites. The authors propose purifying these compounds, confirming their structures with authentic standards and complementary analytical methods, and testing them individually and in combinations against multidrug-resistant uropathogenic E. coli. Mechanistic work, cytotoxicity and selectivity assessments, and testing in appropriate in-vivo urinary tract infection models would still be required before any therapeutic or preventive application could be considered.</p>
<p><strong>Subject of Research:</strong> Metabolite profiles associated with antibacterial and antibiofilm activity of celery, coriander and parsley against multidrug-resistant uropathogenic E. coli</p>
<p><strong>Article Title:</strong> Integrative metabolomics and chemometric analysis reveal metabolites associated with antibacterial and antibiofilm activities of celery, Coriander, and parsley against multidrug-resistant uropathogenic Escherichia coli</p>
<p><strong>Article References:</strong> Abdel-dayem, S. I. A., El Gedaily, R. A., Eltanany, B. M., Seiffein, N. L., Hani, G. A., Afifi, S. M., &amp; Ali, D. E. (2026). Integrative metabolomics and chemometric analysis reveal metabolites associated with antibacterial and antibiofilm activities of celery, Coriander, and parsley against multidrug-resistant uropathogenic Escherichia coli. <em>BMC Complementary Medicine and Therapies, 26</em>(1), Article 313. <a href="https://doi.org/10.1186/s12906-026-05610-0" rel="noopener noreferrer">https://doi.org/10.1186/s12906-026-05610-0</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12906-026-05610-0" rel="noopener noreferrer">10.1186/s12906-026-05610-0</a></p>
<p><strong>Keywords:</strong> Uropathogenic E. coli, Multidrug resistance, Antibiofilm activity, Coriander, Metabolomics, Plant extracts, Quercetin, Fatty acids, Urinary tract infections, Integrative, chemometric, analysis</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">328003</post-id>	</item>
		<item>
		<title>Morphology and DNA analysis identify two new Cortinarius section Telamonia species from southwestern China</title>
		<link>https://scienmag.com/morphology-and-dna-analysis-identify-two-new-cortinarius-section-telamonia-species-from-southwestern-china/</link>
		
		<dc:creator><![CDATA[Drew Townsend]]></dc:creator>
		<pubDate>Tue, 20 Oct 2026 23:34:02 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[Science News]]></category>
		<category><![CDATA[biodiversity assessment in Chinese forests]]></category>
		<category><![CDATA[Cortinarius]]></category>
		<category><![CDATA[Cortinarius species discovery]]></category>
		<category><![CDATA[DNA-based fungal identification]]></category>
		<category><![CDATA[fungal phylogenetics]]></category>
		<category><![CDATA[fungal taxonomy]]></category>
		<category><![CDATA[herbarium specimen collection]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[integrative taxonomic methods]]></category>
		<category><![CDATA[ITS sequencing]]></category>
		<category><![CDATA[macrofungal fieldwork Yunnan and Xizang]]></category>
		<category><![CDATA[morphology and molecular analysis]]></category>
		<category><![CDATA[mushroom morphology]]></category>
		<category><![CDATA[new mushroom species China]]></category>
		<category><![CDATA[new species]]></category>
		<category><![CDATA[nrLSU sequencing]]></category>
		<category><![CDATA[phylogenetics]]></category>
		<category><![CDATA[section Telamonia fungi]]></category>
		<category><![CDATA[spore ornamentation microscopy]]></category>
		<category><![CDATA[taxonomy]]></category>
		<category><![CDATA[Telamonia]]></category>
		<category><![CDATA[Xizang]]></category>
		<category><![CDATA[Yunnan]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=325695</guid>

					<description><![CDATA[A morphology-and-DNA taxonomic study of four fungal specimens from Xizang and Yunnan identified Cortinarius linzhiensis and Cortinarius pallidomarginatus as two new species in section Telamonia.]]></description>
										<content:encoded><![CDATA[<p>An integrative taxonomic study combining detailed fungal morphology with DNA sequence analysis has identified two new species in <em>Cortinarius</em> section <em>Telamonia</em>: <em>Cortinarius linzhiensis</em> and <em>Cortinarius pallidomarginatus</em>. The investigation was based on four specimens collected in July and August 2025 from forests in the Xizang Autonomous Region and Yunnan Province, China, and was not a comprehensive survey of <em>Cortinarius</em> diversity in either region.</p>
<p>The specimens were gathered during macrofungal fieldwork in the Yarlung Zangbo Grand Canyon National Nature Reserve in Xizang and border counties of Yunnan. Researchers examined macroscopic and microscopic features, including the cap, gills, stem, basidiospores, basidia, marginal elements and pileipellis. Dried material was mounted in 5% potassium hydroxide for microscopy, with Congo red used to facilitate observation, while scanning electron microscopy was used to examine spore ornamentation. The specimens were deposited in the Herbarium of Cryptogams of the Kunming Institute of Botany, Chinese Academy of Sciences.</p>
<p>DNA was extracted from the fruiting bodies, and the nuclear ribosomal internal transcribed spacer region, ITS, and nuclear ribosomal large subunit region, nrLSU, were amplified and sequenced. The dataset contained 64 sequences representing 22 species: eight newly generated sequences and 56 sequences downloaded from other sources. It included 54 ITS and 10 nrLSU sequences and produced a combined alignment of 1,555 characters, including gaps.</p>
<p>Maximum-likelihood and Bayesian phylogenetic analyses yielded similar tree topologies, and both new species clustered within section <em>Telamonia</em>. Section <em>Tragani</em> was selected as the outgroup. The authors considered the placements consistent with several diagnostic section-level traits, including weakly hygrophanous caps with dense fibrillose squamules, fibrous-scaly stems, white to dirty-white veils that can form a ring, moderately verrucose ellipsoid to amygdaliform spores, and a duplex pileipellis. Some placements had relatively low bootstrap support.</p>
<p><em>Cortinarius linzhiensis</em> was represented by a holotype collected at 3,420 meters in a mixed forest of <em>Quercus aquifolioides</em> and <em>Picea likiangensis</em> var. <em>linzhiensis</em> in Lulang Town, Linzhi City, and by an additional specimen from <em>Picea</em>-dominated forest at 3,815 meters. Its medium-sized fruiting bodies have caps 40–90 millimeters wide that are light brown to dark brown, wrinkled, weakly hygrophanous and densely covered with fibrillose squamules. The cap margin can crack halfway up the cap and bears grayish-white, spiderweb-like veil remnants.</p>
<p>The <em>C. linzhiensis</em> stem is dirty white, sometimes with a pale purple tint at the apex, and bears brown fibrillose squamules and a pale yellow ring. Its basidiospores measured (8–)8.5–10(–11) × 5.5–7(–7.5) micrometers, with a mean length-to-width ratio of 1.47 ± 0.08. The pileipellis has a weakly developed epicutis 15–45 micrometers thick. Phylogenetic analysis placed the species as sister to <em>C. lijiangensis</em>, although with moderate bootstrap support. By comparison, <em>C. lijiangensis</em> has a maroon cap and stem, an evanescent arachnoid annulus and a thicker epicutis of 140–230 micrometers.</p>
<p>The two <em>C. linzhiensis</em> collections differed by two nucleotide substitutions and insertion–deletion sites in their ITS sequences, as well as in cap color and pigmentation of the stem apex. The authors interpreted these differences as intraspecific variation associated with differences in altitude and host-forest environment rather than as diagnostic characters, and therefore treated the collections as conspecific.</p>
<p><em>Cortinarius pallidomarginatus</em> was collected at 1,770 meters in a broad-leaved forest dominated by <em>Castanopsis</em>, <em>Lithocarpus</em> and <em>Cyclobalanopsis</em> in Houqiao Town, Tengchong City, Yunnan. Its 40–60-millimeter cap is weakly hygrophanous and reddish brown, with a white margin, reddish-brown spiderweb-like veil remnants and dense fibrillose squamules. Its gills are reddish brown, and its stem is light reddish brown. Basidiospores measured (8–)8.5–10 × (5.5–)6–7 micrometers, with a mean length-to-width ratio of 1.43 ± 0.06, and were brown in potassium hydroxide with moderately verrucose ornamentation.</p>
<p>Phylogenetic analysis placed <em>C. pallidomarginatus</em> in a sister clade to a misidentified <em>C. torvus</em>-like lineage, with low bootstrap support, and showed it as closely related to <em>C. subionophyllus</em> and <em>C. ultimiionophyllus</em>. Morphologically, its reddish-brown cap with a white margin distinguishes it from those two species, which have grayish-purplish-brown to ochraceous-brown caps without white margins. The analysis also exposed unresolved taxonomy within <em>Telamonia</em>: some sequences labeled <em>C. torvus</em> formed separate clades, including one clustering with <em>C. tigrinipes</em>, indicating possible misidentification or misapplication of the name.</p>
<p>Because many published reference species of section <em>Telamonia</em> lack publicly available sequences for the protein-coding loci RPB1, RPB2 and TEF1-α, the researchers selected ITS plus nrLSU for the primary reconstruction to maximize taxon coverage. Newly obtained sequences for the three protein-coding loci provided supplementary evidence for the independent evolutionary status of the new species. The conclusions remain bounded by a sample of only four specimens, relatively low bootstrap support for some placements, and limited availability of high-resolution reference sequences.</p>
<p><strong>Subject of Research:</strong> Integrative taxonomy of two new Cortinarius section Telamonia species from southwestern China</p>
<p><strong>Article Title:</strong> Integrative taxonomy reveals two new species of Cortinarius section Telamonia ( Cortinariaceae , Agaricales ) from southwestern China</p>
<p><strong>Article References:</strong> Li, T.-S., Zhang, Y., Yang, Y.-Y., Guan, H.-B., Wu, F., &amp; Zhao, Q. (2026). Integrative taxonomy reveals two new species of Cortinarius section Telamonia (Cortinariaceae, Agaricales) from southwestern China. <em>MycoKeys, 138</em>, 149-162. <a href="https://doi.org/10.3897/mycokeys.138.186765" rel="noopener noreferrer">https://doi.org/10.3897/mycokeys.138.186765</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.3897/mycokeys.138.186765" rel="noopener noreferrer">10.3897/mycokeys.138.186765</a></p>
<p><strong>Keywords:</strong> Cortinarius, Telamonia, fungal taxonomy, new species, mushroom morphology, ITS sequencing, nrLSU sequencing, phylogenetics, Xizang, Yunnan, Integrative, taxonomy</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">325695</post-id>	</item>
		<item>
		<title>METTL1–NSUN1 axis linked to malignant progression and immune features in kidney clear cell carcinoma</title>
		<link>https://scienmag.com/mettl1-nsun1-axis-linked-to-malignant-progression-and-immune-features-in-kidney-clear-cell-carcinoma/</link>
		
		<dc:creator><![CDATA[Nathaniel Bowman]]></dc:creator>
		<pubDate>Tue, 20 Oct 2026 22:07:16 +0000</pubDate>
				<category><![CDATA[Cancer]]></category>
		<category><![CDATA[cancer cell growth inhibition]]></category>
		<category><![CDATA[CRISPR screening]]></category>
		<category><![CDATA[epigenetic modifications in cancer]]></category>
		<category><![CDATA[functional]]></category>
		<category><![CDATA[gene expression analysis]]></category>
		<category><![CDATA[immune microenvironment]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[Kidney clear cell carcinoma]]></category>
		<category><![CDATA[kidney renal clear cell carcinoma]]></category>
		<category><![CDATA[macrophages]]></category>
		<category><![CDATA[METTL1]]></category>
		<category><![CDATA[METTL1–NSUN1 axis]]></category>
		<category><![CDATA[molecular mechanisms of oncogenesis]]></category>
		<category><![CDATA[N7-methylguanosine]]></category>
		<category><![CDATA[neutrophils]]></category>
		<category><![CDATA[NSUN1]]></category>
		<category><![CDATA[potential therapeutic targets]]></category>
		<category><![CDATA[prognosis]]></category>
		<category><![CDATA[prognostic biomarkers]]></category>
		<category><![CDATA[single-cell transcriptomics]]></category>
		<category><![CDATA[tumor microenvironment]]></category>
		<category><![CDATA[tumor progression]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=324338</guid>

					<description><![CDATA[A study combining clinical-data analysis, functional cell experiments and single-cell transcriptomics linked the METTL1–NSUN1 axis to malignant progression and immune-microenvironment features in kidney renal clear cell carcinoma.]]></description>
										<content:encoded><![CDATA[<p>A study combining clinical-data analysis, functional cell experiments and single-cell transcriptomics found that the METTL1–NSUN1 axis is associated with malignant progression and immune-microenvironment features in kidney renal clear cell carcinoma (KIRC). The available report is the abstract of an open-access BMC Cancer article published online on 17 October 2026; the publisher states that the version is subject to further edits and will be replaced by the final Version of Record. The abstract does not provide sample sizes, detailed statistical results or full methodological specifications.</p>
<p>According to the abstract, METTL1 messenger RNA and protein levels were significantly elevated in KIRC tumors and correlated with advanced progression and poor prognosis. NSUN1 was significantly co-expressed with METTL1, was also increased, and correlated with unfavorable prognosis. CRISPR screening gene-effect scores indicated that METTL1 knockout inhibited cell growth across renal, esophageal, gastric and colorectal cancer cell lines. In the functional experiments, METTL1 overexpression increased NSUN1 expression, while NSUN1 knockdown partially rescued the oncogenic effects attributed to METTL1 overexpression. These findings support a functional contribution from NSUN1 to METTL1-associated effects, but the abstract does not quantify the extent of the rescue or establish that all METTL1 activity depends on NSUN1.</p>
<p>Mechanistically, the experimental results indicated that METTL1 installed N7-methylguanosine modifications on NSUN1 messenger RNA and increased its expression. Single-cell sequencing data showed progressive upregulation of METTL1 and NSUN1 during epithelial-to-malignant transformation, accompanied by coordinated activation of RNA-modification genes and epithelial–mesenchymal transition-related transcription factors, including ZEB1, KLF4 and TBX3. The analysis also identified intensive crosstalk between cancer cells and basal cells in the tumor microenvironment. High METTL1 expression correlated with increased infiltration of pro-tumor M0 macrophages and neutrophils, which the authors linked with an immunosuppressive microenvironment. The reported immune findings are correlations in the analyzed data, rather than direct evidence that METTL1 caused the infiltration or suppression.</p>
<p>Taken together, the abstract reports associations between METTL1/NSUN1 expression, tumor progression, prognosis and tumor-microenvironment features, alongside mechanistic findings from cancer-cell models. The scope of the evidence described here does not demonstrate clinical utility or therapeutic benefit in people with KIRC, and the underlying paper remains a research article rather than a clinical treatment study.</p>
<p><strong>Subject of Research:</strong> Mechanistic and single-cell analysis of the METTL1–NSUN1 axis in kidney renal clear cell carcinoma</p>
<p><strong>Article Title:</strong> Integrative functional experiments and single-cell transcriptomics reveal the METTL1/NSUN1 axis drives malignant progression in kidney renal clear cell carcinoma</p>
<p><strong>Article References:</strong> Cui, Y., Qin, T., Wu, X., &amp; Zhang, C. (2026). Integrative functional experiments and single-cell transcriptomics reveal the METTL1/NSUN1 axis drives malignant progression in kidney renal clear cell carcinoma. <em>BMC Cancer</em>. <a href="https://doi.org/10.1186/s12885-026-17194-6" rel="noopener noreferrer">https://doi.org/10.1186/s12885-026-17194-6</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12885-026-17194-6" rel="noopener noreferrer">10.1186/s12885-026-17194-6</a></p>
<p><strong>Keywords:</strong> kidney renal clear cell carcinoma, METTL1, NSUN1, N7-methylguanosine, single-cell transcriptomics, tumor progression, prognosis, tumor microenvironment, macrophages, neutrophils, Integrative, functional</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">324338</post-id>	</item>
		<item>
		<title>Morphological and genetic study describes new Acrossocheilus species in Hunan</title>
		<link>https://scienmag.com/morphological-and-genetic-study-describes-new-acrossocheilus-species-in-hunan/</link>
		
		<dc:creator><![CDATA[Juliet Wilcox]]></dc:creator>
		<pubDate>Tue, 20 Oct 2026 21:48:57 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[Science News]]></category>
		<category><![CDATA[Acrossocheilus]]></category>
		<category><![CDATA[Acrossocheilus genus]]></category>
		<category><![CDATA[biodiversity assessment in Lishui River]]></category>
		<category><![CDATA[DNA barcoding]]></category>
		<category><![CDATA[DNA barcoding in fish]]></category>
		<category><![CDATA[fish morphological diagnostics]]></category>
		<category><![CDATA[fish taxonomy]]></category>
		<category><![CDATA[freshwater fish diversity in Hunan]]></category>
		<category><![CDATA[Hunan Province]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[integrative taxonomy]]></category>
		<category><![CDATA[Lishui River]]></category>
		<category><![CDATA[mitochondrial genome]]></category>
		<category><![CDATA[mitochondrial genome sequencing]]></category>
		<category><![CDATA[morphological measurements in ichthyology]]></category>
		<category><![CDATA[new fish species description]]></category>
		<category><![CDATA[new species]]></category>
		<category><![CDATA[reveals]]></category>
		<category><![CDATA[species delimitation]]></category>
		<category><![CDATA[species delimitation analysis]]></category>
		<category><![CDATA[specimen preservation and deposition]]></category>
		<category><![CDATA[taxonomy]]></category>
		<category><![CDATA[vertebral counts by X-ray]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=324067</guid>

					<description><![CDATA[A morphological and mitochondrial study of 11 fish specimens from Hunan Province described Acrossocheilus zhangjiajiensis as a new species and reported its complete mitochondrial genome.]]></description>
										<content:encoded><![CDATA[<p>A study combining anatomical measurements, DNA barcoding, species-delimitation analysis and mitochondrial genome sequencing formally described a new fish species, <em>Acrossocheilus zhangjiajiensis</em>, from the upper Lishui River in Zhangjiajie City, Hunan Province, China. The authors examined 11 specimens collected in Bamaoxi Village, Sangzhi County, between 2021 and 2024, and increased the number of recognized species in the genus to 25.</p>
<p>The researchers designated specimen JWS2024296, measuring 120.4 millimetres in standard length, as the holotype and deposited 10 paratypes collected at the same locality. The specimens were preserved in 85% ethanol and deposited in the Molecular Ecology Laboratory at Zhangjiajie Campus, Jishou University. Measurements were recorded with a digital caliper to the nearest 0.1 millimetre and expressed as percentages of standard length or head length, while vertebral counts for two specimens were examined by X-radiography.</p>
<p>The new species has an elongated, laterally compressed body, an inferior mouth, two pairs of barbels and a complete lateral line with 37 to 38 scales. Its diagnosis combines six vertical black bars on the flanks, which remain present through adulthood, with black markings on the dorsal-fin membranes, a slightly hardened last unbranched dorsal-fin ray with a smooth posterior margin, and a maxillary barbel extending to the midpoint of the eye. In living individuals, the bars are distinct in juveniles and become shorter and fainter in adults.</p>
<p>Morphological comparisons involved 11 <em>A. zhangjiajiensis</em> and 11 <em>A. jishouensis</em> specimens of comparable size. Although many measured ranges overlapped, Mann–Whitney U tests found significant differences in 11 of 26 characters at P ≤ 0.05, including eye diameter, rostral-barbel length, postdorsal length, dorsal-fin length, pelvic-fin length, pectoral-fin length, caudal-fin length and pelvic-to-anal distance. X-radiography also found 4+33 vertebrae in two new-species specimens, compared with 4+35 vertebrae in two <em>A. jishouensis</em> specimens examined in the study.</p>
<p>For the mitochondrial cytochrome oxidase I analysis, the researchers extracted DNA from fin tissue of three <em>A. zhangjiajiensis</em> individuals. The COI haplotype network identified two haplotypes in the new species and eight in 23 <em>A. jishouensis</em> individuals. The overall COI genetic distance between the two species was 3.1%, and the haplotype groups were clearly separated. Maximum-likelihood and Bayesian analyses based on both COI and 13 mitochondrial protein-coding genes placed the new species as the sister taxon of <em>A. jishouensis</em>.</p>
<p>The researchers also applied the Bayesian Poisson Tree Processes model to the COI tree. It identified 10 putative species groups among the <em>Acrossocheilus</em> species included in the analysis. The lineage containing <em>A. zhangjiajiensis</em> had a branch length of 0.063, above the model’s automatically estimated threshold of 0.034, and was treated as an independent group. This molecular analysis did not include every recognized species in the genus, so the reported species-delimitation result applies to the sampled taxa rather than providing a comprehensive revision of <em>Acrossocheilus</em>.</p>
<p>Analysis of the 13 protein-coding genes gave genetic distances of 3.3% between <em>A. zhangjiajiensis</em> and <em>A. jishouensis</em> and as much as 11.4% between the new species and <em>A. longipinnis</em>. Within the comparison with its closest sampled relative, the ND4L gene showed the lowest distance at 1.0%, while ND6 showed the highest at 6.6%. A Jinping, Guizhou, population assigned to <em>A. jishouensis</em> also showed divergence from other populations of that species, but the study retained its identification because no physical specimens were available for examination.</p>
<p>A separate specimen provided the first complete mitochondrial genome reported for <em>A. zhangjiajiensis</em>. The assembled sequence was 16,592 base pairs long and contained 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes and a D-loop region. The authors assembled and annotated the sequence, manually verified the annotation and deposited it in GenBank. The COI sequences and mitochondrial genome were likewise deposited as GenBank records PV200282–PV200284 and PV200285, respectively.</p>
<p>The description places <em>A. zhangjiajiensis</em> in the barred group, whose members bear vertical black bars. Its combination of coloration, barbel length, dorsal-fin anatomy, bar position and scale count distinguishes it from the other barred species examined by the authors, while molecular evidence separates it from <em>A. jishouensis</em>, a related species also recorded in Zhangjiajie but from a different drainage. At present, the new species is known only from the type locality in shallow, clear, gently flowing water with a gravel bottom in the upper reaches of the northern branch of the Lishui River.</p>
<p><strong>Subject of Research:</strong> Integrative taxonomic description of a new Acrossocheilus fish species from Hunan, China</p>
<p><strong>Article Title:</strong> Integrative taxonomy reveals a new species of Acrossocheilus ( Cypriniformes , Cyprinidae ) from Hunan Province, China</p>
<p><strong>Article References:</strong> Cao, J., Deng, Z., Xiang, H., Xie, Y., Wang, C., Li, H., Hu, Y., Wei, Y., &amp; Jiang, W. (2026). Integrative taxonomy reveals a new species of Acrossocheilus (Cypriniformes, Cyprinidae) from Hunan Province, China. <em>Zoosystematics and Evolution, 102</em>(3), 869-883. <a href="https://doi.org/10.3897/zse.102.195486" rel="noopener noreferrer">https://doi.org/10.3897/zse.102.195486</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.3897/zse.102.195486" rel="noopener noreferrer">10.3897/zse.102.195486</a></p>
<p><strong>Keywords:</strong> Acrossocheilus, new species, fish taxonomy, integrative taxonomy, Hunan Province, Lishui River, species delimitation, mitochondrial genome, DNA barcoding, Integrative, taxonomy, reveals</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">324067</post-id>	</item>
		<item>
		<title>Integrative study identifies three new Dugesia planarian species in Henan, China</title>
		<link>https://scienmag.com/integrative-study-identifies-three-new-dugesia-planarian-species-in-henan-china/</link>
		
		<dc:creator><![CDATA[Margaret Porter]]></dc:creator>
		<pubDate>Tue, 20 Oct 2026 21:30:24 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[Science News]]></category>
		<category><![CDATA[asexual reproduction in freshwater flatworms]]></category>
		<category><![CDATA[biodiversity]]></category>
		<category><![CDATA[chromosome analysis in planarians]]></category>
		<category><![CDATA[copulatory anatomy]]></category>
		<category><![CDATA[description]]></category>
		<category><![CDATA[Dugesia]]></category>
		<category><![CDATA[Dugesia planarian species discovery]]></category>
		<category><![CDATA[freshwater invertebrate biodiversity]]></category>
		<category><![CDATA[freshwater planarians]]></category>
		<category><![CDATA[freshwater planarians taxonomy]]></category>
		<category><![CDATA[genetic distance]]></category>
		<category><![CDATA[Henan Province]]></category>
		<category><![CDATA[histological studies of Dugesia]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[integrative species identification methods]]></category>
		<category><![CDATA[integrative taxonomy]]></category>
		<category><![CDATA[karyology]]></category>
		<category><![CDATA[molecular phylogeny]]></category>
		<category><![CDATA[molecular phylogeny of Dugesia]]></category>
		<category><![CDATA[morphological characterization of Dugesia]]></category>
		<category><![CDATA[new species description in China]]></category>
		<category><![CDATA[reproductive anatomy of planarians]]></category>
		<category><![CDATA[species description]]></category>
		<category><![CDATA[species diversity in Henan Province]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=323777</guid>

					<description><![CDATA[An integrative animal study combining anatomy, chromosome analysis, molecular phylogeny and genetic distances identified three new Dugesia species from three sites in Henan Province, China.]]></description>
										<content:encoded><![CDATA[<p>An integrative taxonomic study of freshwater planarians collected from three sites in Henan Province has identified three new species of the genus Dugesia: D. tongbaiensis, D. fangchengensis and D. lushanensis. The animal study combined external and internal anatomy, histology, chromosome analysis, molecular phylogeny and genetic-distance estimates, with copulatory-apparatus anatomy providing the principal morphological evidence for species identification.</p>
<p>The researchers collected planarians in 2020 from a river in Sidaohe Village, Tongbai County; a stream in Yindian Village, Fangcheng County; and a stream in the Huameigu Scenic Area, Lushan County. Specimens were transported in habitat water and maintained in autoclaved tap water at 18 ± 1 °C in darkness. They were fed fresh beef liver once a week and starved for at least one week before karyological, histological and DNA analyses. None was sexually mature when collected, and the animals reproduced asexually by fission in culture. Sexual maturity appeared only after approximately two years of laboratory rearing.</p>
<p>D. tongbaiensis, represented by a holotype and additional specimens from Sidaohe Village, has asymmetrical openings of the oviducts into the bursal canal, with the right opening dorsal to the left. A long connecting duct separates the slender saclike seminal vesicle from two adjacent diaphragms in the penis papilla, and the second diaphragm is larger than the first. Its ejaculatory duct follows a central course through the papilla and terminates at its tip. Sixteen individuals became sexual after approximately two years in the laboratory, but they had not produced cocoons when the study was published.</p>
<p>D. fangchengensis, described from Yindian Village, is characterized by two asymmetric bumps around the middle of the penis papilla, giving the structure an approximately gyroscopic shape. It also has a kidney-shaped seminal vesicle, a pointed diaphragm at mid-length of the papilla, and a short ventrally displaced ejaculatory duct with a terminal opening. After nearly two years in culture, 12 specimens became sexual and produced cocoons 40–45 days later. Each observed cocoon yielded 7–12 juveniles measuring 1.25–4.01 mm in length and 0.45–0.70 mm in width.</p>
<p>D. lushanensis, collected from the Huameigu Scenic Area at 430 m above sea level, has a large asymmetrical parenchymatic penial valve at the base of the penis papilla, with the dorsal portion distinctly larger. Its diagnostic structures include an ellipsoidal seminal vesicle separated from an inverted V-shaped ejaculatory duct by a well-developed diaphragm, plus a subterminal opening through the ventral wall of the papilla. The papilla is markedly asymmetrical, with a thicker and longer dorsal lip, and bears a bump at mid-length. Sexually mature individuals were first observed on October 1, 2022, although no cocoons had been detected by publication.</p>
<p>Karyological observations provided partial support for the taxonomic distinctions, but did not separate all three species. D. tongbaiensis and D. fangchengensis both had mixoploid karyotypes containing diploid complements of 2n = 2x = 16 and triploid complements of 2n = 3x = 24, with all chromosomes classified as metacentric. Of 213 examined metaphase plates from six D. tongbaiensis specimens, 130 showed the diploid complement and 56 the triploid complement. For D. fangchengensis, 88 of 122 plates from six specimens were diploid and 21 were triploid. Some plates in both samples could not be classified because chromosomes were poorly dispersed or over-spread.</p>
<p>D. lushanensis differed in showing only the diploid complement of 2n = 2x = 16 among 99 classifiable metaphase plates from 122 examined across six specimens; the other 23 plates could not be assessed accurately. Its first chromosome pair was 2.71 times the length of the shortest chromosome, compared with ratios of 2.21 in D. tongbaiensis and 2.11 in D. fangchengensis. Thus, the chromosome evidence distinguished D. lushanensis from the other two new taxa, whereas the first two could not be separated from each other by karyotype because both contained diploid and triploid complements.</p>
<p>For the molecular analysis, the researchers obtained DNA from three individuals of each new species, amplified the mitochondrial COI and nuclear ITS-1 markers and found no sequence variation among the three specimens within each species. A concatenated 1,403-base-pair alignment, comprising 797 base pairs of COI and 606 of ITS-1, was analyzed by Bayesian inference and maximum likelihood. The resulting trees had nearly identical topologies. All 16 Chinese species included in the analysis were placed within the Eastern Palearctic/Oriental/Australasian clade. D. tongbaiensis and D. fangchengensis were fully supported sister species and clustered with D. japonica and D. umbonata, whereas D. lushanensis grouped in another subclade with D. ryukyuensis and D. batuensis.</p>
<p>Genetic distances supported the recognition of three independent lineages. The lowest COI distances to known congeners were 6.2% for D. tongbaiensis, 6.1% for D. fangchengensis and 6.2% for D. lushanensis. Pairwise COI distances among the three new species ranged from 9.2% to 11.5%, with D. tongbaiensis and D. fangchengensis the closest pair. The authors proposed that differences in local environmental conditions, including temperature, precipitation, lithology and slope, might have contributed to the separation of D. lushanensis from the other two species. That explanation remains a hypothesis: the study sampled three collection sites and used laboratory-reared material, so it did not directly test geographic or ecological causes of speciation.</p>
<p><strong>Subject of Research:</strong> Integrative taxonomy of three newly described Dugesia freshwater planarians from Henan Province, China</p>
<p><strong>Article Title:</strong> Integrative description of three new species of Dugesia ( Platyhelminthes , Tricladida , Dugesiidae ) from Henan Province, central China</p>
<p><strong>Article References:</strong> Zhang, H.-C., He, J.-H., Zhang, Y.-Y., Sun, X.-J., Shi, C.-Y., Chen, G.-W., &amp; Liu, D.-Z. (2026). Integrative description of three new species of Dugesia (Platyhelminthes, Tricladida, Dugesiidae) from Henan Province, central China. <em>Zoosystematics and Evolution, 102</em>(4), 893-909. <a href="https://doi.org/10.3897/zse.102.185506" rel="noopener noreferrer">https://doi.org/10.3897/zse.102.185506</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.3897/zse.102.185506" rel="noopener noreferrer">10.3897/zse.102.185506</a></p>
<p><strong>Keywords:</strong> Dugesia, freshwater planarians, species description, integrative taxonomy, Henan Province, molecular phylogeny, genetic distance, karyology, copulatory anatomy, biodiversity, Integrative, description</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">323777</post-id>	</item>
		<item>
		<title>Integrative mapping of chloroplast rRNA modifications reveals conserved and lineage-specific features and stepwise modification during plastid ribosome biogenesis</title>
		<link>https://scienmag.com/integrative-mapping-of-chloroplast-rrna-modifications-reveals-conserved-and-lineage-specific-features-and-stepwise-modification-during-plastid-ribosome-biogenesis/</link>
		
		<dc:creator><![CDATA[Alan Morgan]]></dc:creator>
		<pubDate>Tue, 20 Oct 2026 20:54:52 +0000</pubDate>
				<category><![CDATA[Agriculture]]></category>
		<category><![CDATA[16S and 23S rRNA methylation]]></category>
		<category><![CDATA[16S rRNA]]></category>
		<category><![CDATA[23S rRNA]]></category>
		<category><![CDATA[Arabidopsis thaliana]]></category>
		<category><![CDATA[Chloroplast rRNA modifications]]></category>
		<category><![CDATA[chloroplasts]]></category>
		<category><![CDATA[conserved bacterial rRNA modifications]]></category>
		<category><![CDATA[direct RNA sequencing in chloroplasts]]></category>
		<category><![CDATA[effects of rRNA methylation on photosynthesis]]></category>
		<category><![CDATA[Integrative]]></category>
		<category><![CDATA[KsgA]]></category>
		<category><![CDATA[lineage-specific rRNA modifications]]></category>
		<category><![CDATA[mapping]]></category>
		<category><![CDATA[PFC1]]></category>
		<category><![CDATA[photosynthesis]]></category>
		<category><![CDATA[plant plastid ribosome assembly]]></category>
		<category><![CDATA[post-transcriptional rRNA modification mapping]]></category>
		<category><![CDATA[ribosome biogenesis]]></category>
		<category><![CDATA[RNA sequencing]]></category>
		<category><![CDATA[role of PFC1 in rRNA maturation]]></category>
		<category><![CDATA[rRNA modifications]]></category>
		<category><![CDATA[stepwise rRNA processing]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=323127</guid>

					<description><![CDATA[An integrative Arabidopsis study mapped chloroplast rRNA modifications and linked stepwise modification during ribosome biogenesis to rRNA maturation, chloroplast ribosome assembly and photosynthetic performance in young leaves.]]></description>
										<content:encoded><![CDATA[<p>An integrative analysis in Arabidopsis thaliana identified seven confidently modified sites in chloroplast 16S rRNA and ten in 23S rRNA, according to the study abstract. Most corresponded to conserved bacterial modifications, while a methylated cytosine at position C1940 in 23S rRNA appeared to be conserved within the plant lineage but absent from bacteria. These findings provide a map of chloroplast rRNA modifications and link their installation to ribosome maturation and assembly in plant chloroplasts.</p>
<p>For the research study, the authors combined direct RNA sequencing with complementary cDNA-based approaches and meta-analysis of publicly available RNA-seq datasets. The researchers assessed post-transcriptional modifications in the chloroplast 16S and 23S rRNAs of Arabidopsis thaliana. They also examined the plastid counterpart PFC1 of the bacterial dimethyltransferase KsgA and used single-molecule direct RNA sequencing to analyze defined 16S and 23S rRNA processing states. The reported detection of stage-specific modification-associated signatures was consistent with modifications being installed stepwise during plastid ribosome biogenesis.</p>
<p>Functional analysis of PFC1 indicated that loss of N6,N6-dimethyladenosine formation impaired 16S rRNA maturation, delayed chloroplast ribosome assembly and affected photosynthetic performance in young leaves. The study therefore associates this RNA modification with rRNA maturation and ribosome assembly while providing experimental evidence for a functional effect in young leaf tissue. The authors described the overall pattern as showing that plastid ribosomes retain a prokaryotic-type functional core, alongside the plant-lineage-associated C1940 modification that was not found in bacteria.</p>
<p>The work is a plant molecular-biology study centered on Arabidopsis, with comparative sequence evidence used to examine conservation across bacteria and plant lineages. Its functional experiments focused on one modification-related protein and the reported photosynthetic effect was specific to young leaves, so the abstract does not establish effects across all tissues, developmental stages or plant species. Only the supplied abstract and publisher metadata were available for this report; the source also notes that the accessible accepted version may undergo further edits before replacement by the final Version of Record.</p>
<p><strong>Subject of Research:</strong> Mapping chloroplast rRNA modifications associated with ribosome maturation and assembly in Arabidopsis thaliana</p>
<p><strong>Article Title:</strong> Integrative mapping of chloroplast rRNA modifications reveals conserved and lineage-specific features and stepwise modification during plastid ribosome biogenesis</p>
<p><strong>Article References:</strong> Gołębiewska, K., Duszyn, M., Piątkowski, J., &amp; Gawroński, P. (2026). Integrative mapping of chloroplast rRNA modifications reveals conserved and lineage-specific features and stepwise modification during plastid ribosome biogenesis. <em>BMC Plant Biology</em>. <a href="https://doi.org/10.1186/s12870-026-09896-7" rel="noopener noreferrer">https://doi.org/10.1186/s12870-026-09896-7</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12870-026-09896-7" rel="noopener noreferrer">10.1186/s12870-026-09896-7</a></p>
<p><strong>Keywords:</strong> Arabidopsis thaliana, chloroplasts, rRNA modifications, ribosome biogenesis, 16S rRNA, 23S rRNA, PFC1, KsgA, photosynthesis, RNA sequencing, Integrative, mapping</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">323127</post-id>	</item>
	</channel>
</rss>
