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	<title>tuberculosis &#8211; Science</title>
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	<title>tuberculosis &#8211; Science</title>
	<link>https://scienmag.com</link>
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		<title>African infectious-disease AI review finds 43 studies, uneven coverage and barriers</title>
		<link>https://scienmag.com/african-infectious-disease-ai-review-finds-43-studies-uneven-coverage-and-barriers/</link>
		
		<dc:creator><![CDATA[Blake Davidson]]></dc:creator>
		<pubDate>Thu, 22 Oct 2026 08:32:54 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[Africa]]></category>
		<category><![CDATA[AI in infectious disease Africa]]></category>
		<category><![CDATA[AI models for HIV]]></category>
		<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[barriers to AI implementation in African health]]></category>
		<category><![CDATA[challenges and gaps in AI infectious disease research Africa]]></category>
		<category><![CDATA[COVID-19]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[deep learning in African infectious disease management]]></category>
		<category><![CDATA[geographic distribution of AI studies Africa]]></category>
		<category><![CDATA[HIV]]></category>
		<category><![CDATA[infectious disease prediction AI Africa]]></category>
		<category><![CDATA[infectious diseases]]></category>
		<category><![CDATA[Machine learning]]></category>
		<category><![CDATA[machine learning for infectious disease surveillance Africa]]></category>
		<category><![CDATA[malaria]]></category>
		<category><![CDATA[opportunities for AI in African disease control]]></category>
		<category><![CDATA[public health surveillance]]></category>
		<category><![CDATA[systematic review]]></category>
		<category><![CDATA[systematic review of AI in African health]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<category><![CDATA[tuberculosis Africa]]></category>
		<category><![CDATA[utilization]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=332683</guid>

					<description><![CDATA[A systematic review found 43 studies applying artificial intelligence to infectious-disease prediction, management, surveillance or outbreak prediction in Africa between 2015 and 2025.]]></description>
										<content:encoded><![CDATA[<p>A systematic review found 43 eligible studies that applied artificial intelligence to infectious-disease prediction, management, surveillance or outbreak prediction in Africa between 2015 and 2025. The studies addressed diseases including HIV, malaria, COVID-19 and tuberculosis. South Africa had the largest number of included studies, followed by Nigeria, Uganda, Ethiopia and Tanzania, showing uneven geographic coverage of the research base.</p>
<p>The review, published in BMC Infectious Diseases , aimed to characterize how artificial intelligence has been used in infectious-disease work across Africa and to examine the opportunities and constraints surrounding that use. It included original, peer-reviewed studies in which machine learning or deep learning was used for management, prediction, surveillance or outbreak prediction. Investigators followed PRISMA 2020 guidelines and registered the review on PROSPERO as CRD420251243329.</p>
<p>They searched PubMed, the African Journals Online platform, Scopus, Google Scholar and ScienceDirect. The searches retrieved 5,050 records: 2,551 from PubMed, 2,000 from ScienceDirect, 102 from African Journals Online, 233 from Scopus and 164 from Google Scholar. Of the 5,006 records screened, 43 met the predefined eligibility criteria.</p>
<p>The researchers systematically extracted information on study characteristics, key findings and the performance metrics reported for the artificial-intelligence models. The geographic breakdown showed 10 included studies from South Africa, eight from Nigeria, six from Uganda, five from Ethiopia and four from Tanzania. These counts place the largest share of the eligible evidence in the five most represented countries.</p>
<p>The review therefore documents activity in several parts of Africa, but it does not establish that AI-based infectious-disease research was evenly distributed across the continent or that the included countries represented every national research setting. Random forest was among the most commonly used machine-learning models, alongside support vector machine, artificial neural network and logistic regression. Among the deep-learning approaches, long short-term memory was the most common.</p>
<p>These measures were tied to the models and outcomes reported in each study. The review does not report from the supplied evidence that any one model produced uniformly superior results across infectious-disease prediction, management, surveillance and outbreak forecasting. The authors nevertheless concluded that artificial intelligence is increasingly used for infectious diseases in Africa while remaining underutilized.</p>
<p>They identified constraints involving policy frameworks, health-data quality, digital infrastructure, funding for health systems and research, and governance. In calling for investment and commitments to address these barriers, the review framed artificial intelligence as a developing capability whose wider use depends on structural conditions in data, infrastructure, financing and oversight. Overall, the review identifies 43 studies and 5,050 database records as the basis for its assessment of AI applications in African infectious-disease research.</p>
<p><strong>Subject of Research:</strong> Systematic review of artificial-intelligence applications for infectious-disease prediction, management and surveillance in Africa</p>
<p><strong>Article Title:</strong> Utilization of artificial intelligence for infectious disease in Africa: a systematic review</p>
<p><strong>Article References:</strong> Anulaobi, C. C., Ogaba, A. K., Udoh, I. O., David, P. W., Ozugha, E. P., Nwadike, P. I., Maduka, Y. O., Miller, O. C., Nnana, M. E., &amp; Ajayi, A. O. (2026). Utilization of artificial intelligence for infectious disease in Africa: a systematic review. <em>BMC Infectious Diseases</em>. <a href="https://doi.org/10.1186/s12879-026-14276-5" rel="noopener noreferrer">https://doi.org/10.1186/s12879-026-14276-5</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12879-026-14276-5" rel="noopener noreferrer">10.1186/s12879-026-14276-5</a></p>
<p><strong>Keywords:</strong> artificial intelligence, infectious diseases, Africa, systematic review, machine learning, deep learning, public health surveillance, HIV, malaria, COVID-19, tuberculosis, Utilization</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">332683</post-id>	</item>
		<item>
		<title>Protonation reshapes MmpL3 to coordinate mycobacterial lipid transport</title>
		<link>https://scienmag.com/protonation-reshapes-mmpl3-to-coordinate-mycobacterial-lipid-transport/</link>
		
		<dc:creator><![CDATA[Drew Townsend]]></dc:creator>
		<pubDate>Thu, 22 Oct 2026 03:53:03 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[allostery]]></category>
		<category><![CDATA[cell-wall biogenesis]]></category>
		<category><![CDATA[membrane transporter]]></category>
		<category><![CDATA[MmpL3]]></category>
		<category><![CDATA[MmpL3 conformational changes and drug targeting]]></category>
		<category><![CDATA[molecular dynamics]]></category>
		<category><![CDATA[Molecular dynamics simulation of mycobacterial membrane proteins]]></category>
		<category><![CDATA[MYC]]></category>
		<category><![CDATA[mycobacteria]]></category>
		<category><![CDATA[Mycobacterial cell wall synthesis and lipid handling]]></category>
		<category><![CDATA[Mycobacterial lipid transport mechanisms]]></category>
		<category><![CDATA[protein conformation]]></category>
		<category><![CDATA[Proton]]></category>
		<category><![CDATA[proton transport]]></category>
		<category><![CDATA[Proton-coupled lipid translocation in mycobacteria]]></category>
		<category><![CDATA[Protonation effects on MmpL3 transporter]]></category>
		<category><![CDATA[Role of Asp256 and Asp645 in MmpL3 function]]></category>
		<category><![CDATA[Structural insights into MmpL3 transporter]]></category>
		<category><![CDATA[transport]]></category>
		<category><![CDATA[trehalose monomycolate]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<category><![CDATA[Tuberculosis drug development targeting MmpL3]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=331731</guid>

					<description><![CDATA[Molecular dynamics simulations show that protonation at two conserved sites in MmpL3 favors distinct conformations and changes how a key mycobacterial cell-wall lipid is positioned.]]></description>
										<content:encoded><![CDATA[<p>Molecular dynamics simulations indicate that adding protons to two conserved sites in the MmpL3 membrane protein can push the transporter toward different conformations, linking proton movement to the handling of a key mycobacterial cell-wall lipid. The study focused on MmpL3 from Mycobacterium smegmatis, a model system for the M. tuberculosis protein, and compared unprotonated protein with states in which either Asp256 or Asp645 was protonated. Asp256 protonation favored an open, more highly hydrated arrangement, whereas Asp645 protonation stabilized a closed and less accessible configuration.</p>
<p>MmpL3 is an essential inner-membrane transporter in mycobacteria. It moves trehalose monomycolate, a precursor of the mycolic acids that form major components of the bacterial cell envelope, between a transmembrane binding pocket and a periplasmic pocket. From the latter site, the lipid can be passed to downstream components involved in cell-wall construction. Because MmpL3 is conserved across mycobacterial species and required for growth and cell-wall biogenesis, understanding how it couples proton transport to lipid movement may inform efforts to develop tuberculosis drugs against this machinery.</p>
<p>The researchers began with a 2.6-ångström crystal structure of M. smegmatis MmpL3 and placed it in a model mycobacterial membrane containing several classes of lipids. They then simulated four fixed-protonation conditions: both conserved aspartates unprotonated, Asp256 protonated, Asp645 protonated, and both aspartates protonated. The first three principal states were each represented by five 2-microsecond replicas, while the dual-protonated state was examined with three replicas. Overall, the project generated 54 microseconds of unrestrained simulations, supplemented by 0.8 microseconds of restrained simulations and further simulations containing the transport substrate.</p>
<p>At the molecular level, the two protonation sites produced contrasting local effects. Protonated Asp256 frequently turned outward from the center of its Asp–Tyr dyad and formed a hydrogen bond with the Ala682 backbone, helping create an open arrangement. It also increased separation between several dyad residues and was associated with a denser water region between the TM4 and TM6 helices. By contrast, protonated Asp645 tended to remain inward-facing, formed fewer contacts with Ser293 and a more variable set of contacts with Tyr257, and reduced the projected area enclosed by the dyad residues. Hydration along TM10 also fell, especially near residue 648.</p>
<p>These local changes were accompanied by movement in the periplasmic domain, which contains the second lipid-binding pocket and interfaces with the transmembrane region containing the first. Protonation increased the variability of periplasmic-domain conformations across replicas, but the two sites biased the motions in different directions. The lower part of the periplasmic C-terminal domain tended to rotate clockwise in the Asp645-protonated simulations and counterclockwise in the Asp256-protonated simulations when viewed from the periplasm. Distance measurements at the narrowest part of the transport channel likewise placed Asp256 protonation toward a wider gate and Asp645 protonation toward a more compact arrangement.</p>
<p>The simulations also suggested that protonation reshapes both substrate pockets. At the entrance to the transmembrane pocket, defined by Leu424 and Glu553, Asp645 protonation biased the pocket toward a narrower state; four of its five replicas fell below the range sampled by the unprotonated system. Asp256 protonation produced greater replica-to-replica variability, with four replicas mainly sampling closed-like distributions and one sampling a distinctly wider configuration. At the periplasmic pocket, the separation between Ser67 and Pro450 tended to increase with Asp256 protonation. Restrained simulations that reproduced selected local hydrogen-bond geometries partially recreated these shifts, supporting an allosteric link between the proton-binding dyads and the distant pockets.</p>
<p>Dynamic network analysis identified candidate routes for that long-range communication. A pathway beginning at Asp256 mainly reached the periplasmic binding pocket through TM2, whereas a pathway beginning at Asp645 was connected to the transmembrane pocket through TM8. These routes provide a plausible physical explanation for the coupled domain movements, although the analysis identifies candidate pathways rather than proving that either route is necessary for transport. The authors also noted that Ser293, corresponding to Ser288 in M. tuberculosis, has been associated with resistance to MmpL3 inhibitors, making the proton-sensitive local network relevant beyond basic transport mechanism.</p>
<p>Adding trehalose monomycolate to the simulations revealed that protonation was associated with changes in how the lipid occupied the two pockets. In the transmembrane pocket, trehalose monomycolate remained bound throughout every trajectory and repeatedly contacted Leu424, Gln554, and His558. In the unprotonated state, its headgroup more often contacted an acidic region containing Asp525, Lys528, Asp531, Asp562, and Pro565. At least one hydrogen bond with that region occurred in 28% of unprotonated frames, compared with 6% in the Asp256-protonated and 9% in the Asp645-protonated simulations. The protonated states instead tended to position the headgroup approximately 2.3 ångströms closer to the central channel.</p>
<p>At the periplasmic pocket, trehalose monomycolate also remained bound but sampled two recurring sub-sites. One was beside a loop formed by residues 442–456; the other was on the Tyr44/Asp144 side of the pocket. The loop-side position placed the lipid headgroup closer to the periplasm, 26.7 ± 1.5 ångströms from the protein’s center of mass, compared with 22.4 ± 1.6 ångströms for the other position. All three Asp645-protonated replicas predominantly sampled the loop-side sub-site, as did two of three Asp256-protonated replicas and one of three unprotonated replicas. Because the individual trajectories rarely exchanged positions, the authors treated these counts as descriptive preferences rather than converged equilibrium populations.</p>
<p>Taken together, the results support a sequential model in which Asp256 protonation opens and hydrates the dyad region while favoring movement of trehalose monomycolate toward the central channel. Subsequent Asp645 protonation favors a more compact protein and lipid configurations closer to the periplasmic side, consistent with forward progress through the transport cycle. The work is a computational mechanistic study, not a demonstration of transport or therapeutic benefit in living bacteria. Its fixed-protonation simulations cannot define complete free-energy landscapes or transition barriers, establish the proton-to-lipid stoichiometry, or show whether the conserved tyrosins directly participate in proton transfer. Experiments directly measuring proton flux alongside lipid transport, together with reactive or constant-pH simulations, will be needed to test the proposed cycle.</p>
<p><strong>Subject of Research:</strong> How protonation at conserved sites alters MmpL3 conformation and trehalose monomycolate binding in molecular dynamics simulations.</p>
<p><strong>Article Title:</strong> Proton transport drives allosteric conformational changes in the MmpL3 transporter</p>
<p><strong>Article References:</strong> Yang, L., North, E. J., Zgurskaya, H. I., Jackson, M., &amp; Gumbart, J. C. (2026). Proton transport drives allosteric conformational changes in the MmpL3 transporter. <em>PLOS Computational Biology, 22</em>(10), e1014880. <a href="https://doi.org/10.1371/journal.pcbi.1014880" rel="noopener noreferrer">https://doi.org/10.1371/journal.pcbi.1014880</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1371/journal.pcbi.1014880" rel="noopener noreferrer">10.1371/journal.pcbi.1014880</a></p>
<p><strong>Keywords:</strong> MmpL3, mycobacteria, tuberculosis, proton transport, molecular dynamics, membrane transporter, trehalose monomycolate, cell-wall biogenesis, allostery, protein conformation, Proton, transport</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">331731</post-id>	</item>
		<item>
		<title>Clinical predictors of tracheobronchial tuberculosis and airway stenosis in pulmonary tuberculosis</title>
		<link>https://scienmag.com/clinical-predictors-of-tracheobronchial-tuberculosis-and-airway-stenosis-in-pulmonary-tuberculosis/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Thu, 22 Oct 2026 03:24:20 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[acid-fast smear]]></category>
		<category><![CDATA[age under 50]]></category>
		<category><![CDATA[airway complication risk]]></category>
		<category><![CDATA[airway stenosis]]></category>
		<category><![CDATA[bronchoscopy]]></category>
		<category><![CDATA[bronchoscopy diagnosis]]></category>
		<category><![CDATA[China]]></category>
		<category><![CDATA[clinical]]></category>
		<category><![CDATA[clinical predictors]]></category>
		<category><![CDATA[female sex risk factors]]></category>
		<category><![CDATA[logistic regression analysis]]></category>
		<category><![CDATA[Predictors]]></category>
		<category><![CDATA[pulmonary tuberculosis]]></category>
		<category><![CDATA[retrospective study]]></category>
		<category><![CDATA[southwestern China]]></category>
		<category><![CDATA[sputum acid-fast smear]]></category>
		<category><![CDATA[tracheobronchial]]></category>
		<category><![CDATA[tracheobronchial tuberculosis]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=331609</guid>

					<description><![CDATA[A retrospective study of 1,999 bronchoscopy-selected pulmonary tuberculosis patients found that 22.0% had tracheobronchial tuberculosis and 49.7% of those affected developed airway stenosis.]]></description>
										<content:encoded><![CDATA[<p>Among 1,999 patients with pulmonary tuberculosis who underwent bronchoscopy at West China Hospital in southwestern China, 439 were diagnosed with tracheobronchial tuberculosis, and 218 of those affected patients—49.7%—also developed airway stenosis. The single-centre retrospective study reports that female sex, age below 50 years and a positive sputum acid-fast smear were independently associated with tracheobronchial tuberculosis in this selected clinical population.</p>
<p>The researchers reviewed patients treated at West China Hospital between September 2013 and June 2019. Patients were eligible if they had confirmed pulmonary tuberculosis, underwent bronchoscopy and had complete baseline clinical data available. Of the 1,999 included patients, 439, or 22.0%, were assigned to the tracheobronchial tuberculosis case group, while 1,560, or 78.0%, had no bronchoscopic evidence of the condition. The analysis evaluated both the presence of tracheobronchial tuberculosis and the occurrence of associated tracheobronchial stenosis.</p>
<p>Multivariable logistic regression identified three independent predictors of tracheobronchial tuberculosis. Female sex carried an odds ratio of 5.726, with a 95% confidence interval of 1.913 to 17.133 and a p-value of 0.002. Patients younger than 50 years had an odds ratio of 4.144, with a 95% confidence interval of 1.791 to 9.588 and a p-value of 0.001. A positive sputum acid-fast smear was associated with an odds ratio of 2.494, with a 95% confidence interval of 0.998 to 6.636 and a p-value of 0.050. These estimates describe associations within the retrospective analysis, rather than proving that the characteristics caused the disease. The confidence interval for the smear result also included values close to 1, reflecting greater uncertainty around that estimate.</p>
<p>Airway stenosis was common among the 439 patients identified with tracheobronchial tuberculosis: 218, or 49.7%, developed tracheobronchial stenosis. The supplied results do not report the corresponding number among patients with pulmonary tuberculosis who did not have tracheobronchial involvement, so they do not establish a risk contrast between the groups. The abstract also does not specify the timing of stenosis development or the clinical outcomes associated with it. Although the findings describe demographic and laboratory characteristics associated with bronchoscopic identification of tracheobronchial disease, the retrospective design and the requirement for bronchoscopy limit direct extrapolation to people with pulmonary tuberculosis who were not referred for the procedure.</p>
<p>The 22.0% proportion should not be interpreted as the prevalence of tracheobronchial tuberculosis among all patients with pulmonary tuberculosis. Every participant in the analysed cohort had undergone bronchoscopy, making the sample different from an unselected pulmonary tuberculosis population. The wide confidence intervals for several predictors, particularly female sex and age below 50 years, also indicate substantial uncertainty in the estimated effect sizes. The results instead provide a clinical profile observed in a hospital cohort: young to middle-aged women with pulmonary tuberculosis and positive sputum acid-fast smears were more likely to receive a bronchoscopic diagnosis of tracheobronchial tuberculosis than the comparison patients.</p>
<p><strong>Subject of Research:</strong> Clinical predictors of tracheobronchial tuberculosis and associated airway stenosis in patients with pulmonary tuberculosis</p>
<p><strong>Article Title:</strong> Clinical predictors of tracheobronchial tuberculosis and associated airway stenosis among patients with pulmonary tuberculosis: a study from Southwestern China</p>
<p><strong>Article References:</strong> Ding, X.-J., Yu, M., Ji, G.-Y., &amp; He, J.-Q. (2026). Clinical predictors of tracheobronchial tuberculosis and associated airway stenosis among patients with pulmonary tuberculosis: a study from Southwestern China. <em>BMC Infectious Diseases</em>. <a href="https://doi.org/10.1186/s12879-026-14262-x" rel="noopener noreferrer">https://doi.org/10.1186/s12879-026-14262-x</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12879-026-14262-x" rel="noopener noreferrer">10.1186/s12879-026-14262-x</a></p>
<p><strong>Keywords:</strong> tracheobronchial tuberculosis, airway stenosis, pulmonary tuberculosis, bronchoscopy, acid-fast smear, clinical predictors, retrospective study, southwestern China, Clinical, predictors, tracheobronchial, tuberculosis</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">331609</post-id>	</item>
		<item>
		<title>Tuberculosis bacterium resists innate immune clearance in mouse models</title>
		<link>https://scienmag.com/tuberculosis-bacterium-resists-innate-immune-clearance-in-mouse-models/</link>
		
		<dc:creator><![CDATA[Morgan Morrow]]></dc:creator>
		<pubDate>Thu, 22 Oct 2026 00:16:06 +0000</pubDate>
				<category><![CDATA[Biology]]></category>
		<category><![CDATA[Medicine]]></category>
		<category><![CDATA[adaptive immunity development in tuberculosis]]></category>
		<category><![CDATA[bacterial clearance]]></category>
		<category><![CDATA[diverse]]></category>
		<category><![CDATA[early immune control of tuberculosis]]></category>
		<category><![CDATA[in vivo tuberculosis immunity]]></category>
		<category><![CDATA[infection]]></category>
		<category><![CDATA[innate immune activation in tuberculosis]]></category>
		<category><![CDATA[innate immunity]]></category>
		<category><![CDATA[innate immunity and tuberculosis]]></category>
		<category><![CDATA[Legionella pneumophila]]></category>
		<category><![CDATA[Legionella pneumophila pre-infection]]></category>
		<category><![CDATA[low-dose tuberculosis infection]]></category>
		<category><![CDATA[macrophage response to Mtb]]></category>
		<category><![CDATA[macrophages]]></category>
		<category><![CDATA[microbial environment and TB susceptibility]]></category>
		<category><![CDATA[mouse models]]></category>
		<category><![CDATA[Mouse models of tuberculosis]]></category>
		<category><![CDATA[Mycobacterium tuberculosis]]></category>
		<category><![CDATA[Mycobacterium tuberculosis infection models]]></category>
		<category><![CDATA[myeloid cells]]></category>
		<category><![CDATA[Single-Cell RNA Sequencing]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<category><![CDATA[Tuberculosis innate immune resistance]]></category>
		<category><![CDATA[ultra-low-dose infection]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=331199</guid>

					<description><![CDATA[Mouse infection experiments show that Mycobacterium tuberculosis remains difficult for innate immunity to clear across ultra-low-dose, microbiota-primed, and Legionella-primed models.]]></description>
										<content:encoded><![CDATA[<p><em>Mycobacterium tuberculosis</em> (Mtb) replicated in mice even after extremely low-dose infection and lung pre-infection with <em>Legionella pneumophila</em> (Lp), a bacterium that induces a strong antibacterial innate immune response. Across the infection models tested, the findings indicate that Mtb remained resistant to control by innate immunity before the onset of adaptive immunity.</p>
<p>Mtb is a robust activator of innate immunity, and innate immune activation of macrophages can affect its replication in vitro. However, the researchers noted that there had been little in vivo evidence that innate immunity controls Mtb before adaptive immunity develops. Earlier studies generally used specific-pathogen-free mouse models and relatively large infectious doses, potentially obscuring the ability of innate defenses to restrict infection.</p>
<p>To test whether smaller infectious doses revealed stronger early control, the investigators performed ultra-low-dose Mtb infections in mice. The initial innate immune response was unable to curb even the minimal infectious doses tested. Thus, the experiments did not find evidence that innate mechanisms established control of Mtb at the lowest challenge levels examined, although the result applies to the mice and experimental conditions used.</p>
<p>The researchers also examined whether prior exposure to a more diverse microbial environment changed susceptibility. They primed the immune systems of C57BL/6 mice by co-housing them with “pet shop” mice before Mtb exposure. The co-housed animals were as susceptible to Mtb infection as specific-pathogen-free mice, indicating that this form of immune priming did not provide measurable protection in the model.</p>
<p>A more targeted test involved infecting the lungs with Lp before Mtb exposure. Innate immunity alone can clear large Lp doses—more than 100,000 colony-forming units (CFU)—from the lung within a few days. Yet Lp pre-infection only modestly reduced Mtb CFU in mice subsequently infected with Mtb alone compared with those receiving Mtb without prior Lp infection. Single-cell RNA sequencing showed that Lp priming induced measurable changes in myeloid cells responding to Mtb, but those changes had little effect on innate control of the bacterium. Together, the results distinguish immune activation from effective bacterial clearance: a response capable of eliminating large amounts of Lp, and detectable changes in myeloid cells, did not substantially restrict Mtb replication. The study was limited to mouse infection models and did not determine how innate immunity contributes to tuberculosis in people or to the later course of infection involving adaptive immunity.</p>
<p><strong>Subject of Research:</strong> Experimental assessment of innate immune control of Mycobacterium tuberculosis in mouse infection models</p>
<p><strong>Article Title:</strong> Diverse infection models demonstrate robust resistance of Mycobacterium tuberculosis to innate immunity</p>
<p><strong>Article References:</strong> Fairgrieve, M. R., Brydon, E. C., Chavez, R. A., Kotov, D. I., &amp; Vance, R. E. (2026). Diverse infection models demonstrate robust resistance of Mycobacterium tuberculosis to innate immunity. <em>PLOS Pathogens, 22</em>(10), e1014713. <a href="https://doi.org/10.1371/journal.ppat.1014713" rel="noopener noreferrer">https://doi.org/10.1371/journal.ppat.1014713</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1371/journal.ppat.1014713" rel="noopener noreferrer">10.1371/journal.ppat.1014713</a></p>
<p><strong>Keywords:</strong> Mycobacterium tuberculosis, innate immunity, mouse models, ultra-low-dose infection, Legionella pneumophila, macrophages, myeloid cells, single-cell RNA sequencing, bacterial clearance, tuberculosis, Diverse, infection</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">331199</post-id>	</item>
		<item>
		<title>Retrospective Ethiopian hospital study finds no detectable five-year TB trend</title>
		<link>https://scienmag.com/retrospective-ethiopian-hospital-study-finds-no-detectable-five-year-tb-trend/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 07:07:51 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[detection]]></category>
		<category><![CDATA[diagnostic testing]]></category>
		<category><![CDATA[Ethiopia]]></category>
		<category><![CDATA[Factors associated with rifampicin resistance in Ethiopian TB cases]]></category>
		<category><![CDATA[hospital records]]></category>
		<category><![CDATA[Impact of COVID-19 on TB detection in Ethiopian hospital]]></category>
		<category><![CDATA[Laboratory-based TB surveillance in northeastern Ethiopia]]></category>
		<category><![CDATA[Limitations of hospital-based TB]]></category>
		<category><![CDATA[Longitudinal assessment of TB diagnostics in healthcare settings]]></category>
		<category><![CDATA[Mycobacterium]]></category>
		<category><![CDATA[Mycobacterium tuberculosis]]></category>
		<category><![CDATA[No significant change in TB prevalence over five years]]></category>
		<category><![CDATA[retrospective study]]></category>
		<category><![CDATA[Retrospective study of MTB using Xpert MTB/RIF in Ethiopia]]></category>
		<category><![CDATA[rifampicin]]></category>
		<category><![CDATA[rifampicin resistance]]></category>
		<category><![CDATA[Rifampicin resistance analysis in TB patients]]></category>
		<category><![CDATA[Statistical analysis of TB and drug resistance data]]></category>
		<category><![CDATA[Trends]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<category><![CDATA[Tuberculosis detection trends in Ethiopian hospital]]></category>
		<category><![CDATA[Xpert MTB/RIF]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=327923</guid>

					<description><![CDATA[A retrospective analysis of 4,351 Ethiopian hospital records found no statistically significant five-year trend in MTB detection or rifampicin resistance, while previous TB treatment was strongly associated with both outcomes.]]></description>
										<content:encoded><![CDATA[<p>A five-year retrospective analysis of routine Xpert MTB/RIF records from Woldia Comprehensive Specialized Hospital in northeastern Ethiopia found no statistically significant temporal trend in the detection of Mycobacterium tuberculosis (MTB) or rifampicin resistance between 2020 and 2024. MTB was detected in 504 records, or 11.6%. Among 498 MTB-detected records with determinate rifampicin-resistance results, 28, or 5.6%, showed rifampicin resistance.</p>
<p>Neither outcome had a significant annual difference or linear trend across the study period. The study, published in BMC Infectious Diseases , examined laboratory records generated from January 2020 through December 2024. The investigators used descriptive statistics and logistic regression to assess MTB detection, rifampicin resistance and associated factors.</p>
<p>Chi-square tests evaluated annual proportions, while continuous-year logistic regression assessed whether calendar year was associated with either outcome. A case-mix-adjusted sensitivity analysis examined temporal changes in MTB detection after accounting for age, sex, previous TB treatment, specimen type and referring facility. Firth-penalized logistic regression was used to assess the robustness of associations with rifampicin resistance in the presence of sparse resistant cases.</p>
<p>The records represented a hospital testing population rather than a population-based sample, so the results describe facility-level testing patterns and cannot directly establish trends in community TB incidence or drug resistance. Calendar year was not significantly associated with MTB detection in the continuous-year model. The estimated odds ratio was 1.007 per year, with a 95% confidence interval of 0.946 to 1.071.</p>
<p>Year was likewise not significantly associated with rifampicin resistance, for which the odds ratio was 1.089 and the 95% confidence interval was 0.848 to 1.399. Adjustment for the measured case-mix factors did not change the finding for MTB detection: the adjusted odds ratio per year was 1.025, with a 95% confidence interval of 0.957 to 1.097 and a p value of 0.481. The lack of a statistically detectable trend does not demonstrate that the underlying burden or resistance level remained constant.</p>
<p>Previous TB treatment had strong associations with both outcomes in the adjusted analyses. Compared with people without a reported history of prior TB treatment, those previously treated had an adjusted odds ratio of 13.99 for MTB detection, with a 95% confidence interval of 7.85 to 24.95. For rifampicin resistance, the corresponding adjusted odds ratio was 49.72, with a 95% confidence interval of 18.60 to 132.90.</p>
<p>These retrospective estimates represent associations among the tested records rather than causal effects or direct measures of individual risk. Male sex was also associated with rifampicin resistance, with an adjusted odds ratio of 4.59 and a 95% confidence interval of 1.32 to 16.00. HIV positivity was associated with MTB detection in univariable analysis, yielding a crude odds ratio of 7.03 and a 95% confidence interval of 1.99 to 24.77, but extensive missing HIV data constrained the interpretation of that result.</p>
<p>Only 28 rifampicin-resistance events were identified, contributing to wide confidence intervals, particularly for the association between previous TB treatment and resistance. The findings are also limited to one hospital, its recorded testing population and the five-year period from 2020 through 2024. A null temporal association in these records does not establish the absence of trends in other settings or at other times.</p>
<p>Overall, the analysis identified MTB in approximately one in nine tested records and rifampicin resistance in 5.6% of MTB-detected records with determinate results. Previous TB treatment was the factor most strongly associated with both outcomes, while the study detected no significant year-to-year shift in either MTB detection or Xpert-detected rifampicin resistance during the study period.</p>
<p><strong>Subject of Research:</strong> Temporal patterns in tuberculosis detection and rifampicin resistance among Xpert-tested records at a northeastern Ethiopian hospital</p>
<p><strong>Article Title:</strong> Trends in Mycobacterium tuberculosis detection and rifampicin resistance using Xpert MTB/RIF assay at Woldia comprehensive specialized hospital, Northeastern Ethiopia: a 5-year retrospective study</p>
<p><strong>Article References:</strong> Tamrat, E., Kassanew, B., Mollaw, N. G., Girma, T., Asfaw, T., Habtamu, T., Jemal, A., Gashaw, M., Bazezew, A., Damtie, A. A., Gedfie, S., Gashaw, Y., Asmare, Z., Biset, S., &amp; Reta, M. A. (2026). Trends in Mycobacterium tuberculosis detection and rifampicin resistance using Xpert MTB/RIF assay at Woldia comprehensive specialized hospital, Northeastern Ethiopia: a 5-year retrospective study. <em>BMC Infectious Diseases</em>. <a href="https://doi.org/10.1186/s12879-026-14670-z" rel="noopener noreferrer">https://doi.org/10.1186/s12879-026-14670-z</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12879-026-14670-z" rel="noopener noreferrer">10.1186/s12879-026-14670-z</a></p>
<p><strong>Keywords:</strong> tuberculosis, rifampicin resistance, Xpert MTB/RIF, Ethiopia, retrospective study, hospital records, Mycobacterium tuberculosis, diagnostic testing, Trends, Mycobacterium, detection, rifampicin</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">327923</post-id>	</item>
		<item>
		<title>TB sputum smear positivity rose during Taiwan’s COVID-19 transition, study finds</title>
		<link>https://scienmag.com/tb-sputum-smear-positivity-rose-during-taiwans-covid-19-transition-study-finds/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 03:27:55 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[acid-fast]]></category>
		<category><![CDATA[acid-fast bacilli]]></category>
		<category><![CDATA[acid-fast bacilli smear results]]></category>
		<category><![CDATA[bacilli]]></category>
		<category><![CDATA[cavitary pulmonary disease]]></category>
		<category><![CDATA[COVID-19 transition]]></category>
		<category><![CDATA[epidemiology of TB during pandemic transition]]></category>
		<category><![CDATA[impact of COVID-19 on TB diagnostics]]></category>
		<category><![CDATA[increased TB sputum smear positivity]]></category>
		<category><![CDATA[public health surveillance]]></category>
		<category><![CDATA[pulmonary tuberculosis diagnosis trends]]></category>
		<category><![CDATA[radiographic findings in TB]]></category>
		<category><![CDATA[retrospective cross-sectional TB study]]></category>
		<category><![CDATA[retrospective study]]></category>
		<category><![CDATA[smear]]></category>
		<category><![CDATA[sputum]]></category>
		<category><![CDATA[sputum smear]]></category>
		<category><![CDATA[Taiwan]]></category>
		<category><![CDATA[Taiwan COVID-19 transition]]></category>
		<category><![CDATA[TB and COVID-19 pandemic comparison]]></category>
		<category><![CDATA[TB diagnostic markers during COVID-19]]></category>
		<category><![CDATA[TB disease presentation without cavitary lung lesions]]></category>
		<category><![CDATA[TB disease severity during pandemic]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=326927</guid>

					<description><![CDATA[A retrospective study of 789 adults in southern Taiwan found higher sputum acid-fast bacilli smear positivity during the COVID-19 transition period, without a significant parallel increase in cavitary pulmonary disease.]]></description>
										<content:encoded><![CDATA[<p>Sputum acid-fast bacilli smear positivity was higher among adults newly diagnosed with pulmonary tuberculosis during Taiwan’s COVID-19 transition period than before the pandemic, according to a retrospective cross-sectional study conducted at a medical center in southern Taiwan. The increase was not accompanied by a corresponding rise in radiographically documented cavitary pulmonary disease.</p>
<p>Researchers analyzed 789 consecutive adults diagnosed with pulmonary tuberculosis from 2017 through 2024 and divided them into three time periods: the pre-pandemic period of 2017–2019, the pandemic period of 2020–2022, and the COVID-19 transition period of 2023–2024. The cohort included 341 patients diagnosed before the pandemic, 270 during it and 178 during the transition. Sputum smear results were available for 738 patients, or 93.5% of the cohort.</p>
<p>Acid-fast bacilli smear positivity was 34.4% in the pre-pandemic period, 32.0% during the pandemic and 48.6% during the COVID-19 transition. The difference across the three periods was statistically significant, with a p-value of 0.001. Multivariable logistic regression showed that the transition period was independently associated with smear positivity compared with the pre-pandemic period, yielding an adjusted odds ratio of 1.92 and a 95% confidence interval of 1.28–2.87; the association had a p-value of 0.002.</p>
<p>The pattern for cavitary disease differed. Its prevalence was 10.3% before the pandemic, 12.6% during the pandemic and 14.0% during the COVID-19 transition, but the differences across periods were not statistically significant, with a p-value of 0.412. Neither the pandemic nor transition period was independently associated with cavitation in the multivariable analysis. Diabetes mellitus and recurrent tuberculosis, however, were independently associated with cavitary pulmonary disease.</p>
<p>Taken together, the findings show a temporal change in one laboratory measure of pulmonary tuberculosis without a parallel statistical difference in the prevalence of radiographic cavitation. Because the study was retrospective, cross-sectional and based at a single medical center in southern Taiwan, it cannot establish that pandemic-era conditions caused the higher smear positivity or that the same pattern occurred nationwide. The data nevertheless identify the COVID-19 transition period as a period associated with an increase in positive sputum smears among newly diagnosed pulmonary tuberculosis patients, while also showing that the rise was not mirrored by a significant change in cavitary disease prevalence.</p>
<p><strong>Subject of Research:</strong> Temporal changes in sputum acid-fast bacilli smear positivity and cavitary pulmonary disease among adults with tuberculosis in Taiwan</p>
<p><strong>Article Title:</strong> Sputum acid-fast bacilli smear positivity and cavitary pulmonary disease across COVID-19 pandemic phases in Taiwan</p>
<p><strong>Article References:</strong> Hsieh, C.-J., Weng, T.-P., Lu, M.-Y., Lu, C.-L., &amp; Lee, N.-Y. (2026). Sputum acid-fast bacilli smear positivity and cavitary pulmonary disease across COVID-19 pandemic phases in Taiwan. <em>BMC Infectious Diseases</em>. <a href="https://doi.org/10.1186/s12879-026-14631-6" rel="noopener noreferrer">https://doi.org/10.1186/s12879-026-14631-6</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12879-026-14631-6" rel="noopener noreferrer">10.1186/s12879-026-14631-6</a></p>
<p><strong>Keywords:</strong> tuberculosis, COVID-19 transition, acid-fast bacilli, sputum smear, cavitary pulmonary disease, Taiwan, public health surveillance, retrospective study, Sputum, acid-fast, bacilli, smear</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">326927</post-id>	</item>
		<item>
		<title>HIV prevalence fell among Tanzanian children with tuberculosis, surveillance analysis shows</title>
		<link>https://scienmag.com/hiv-prevalence-fell-among-tanzanian-children-with-tuberculosis-surveillance-analysis-shows/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 01:01:54 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[age differences]]></category>
		<category><![CDATA[age-related differences in TB/HIV co-infection]]></category>
		<category><![CDATA[decline of HIV among children with TB]]></category>
		<category><![CDATA[factors]]></category>
		<category><![CDATA[HIV]]></category>
		<category><![CDATA[HIV prevalence among children with tuberculosis in Tanzania]]></category>
		<category><![CDATA[impact of HIV prevention measures in Tanzania]]></category>
		<category><![CDATA[national tuberculosis surveillance data Tanzania]]></category>
		<category><![CDATA[pediatric co-infection]]></category>
		<category><![CDATA[prevalence]]></category>
		<category><![CDATA[prevalence trends]]></category>
		<category><![CDATA[Public health]]></category>
		<category><![CDATA[regional disparities in HIV/TB co-infection]]></category>
		<category><![CDATA[regional variation]]></category>
		<category><![CDATA[relapse tuberculosis]]></category>
		<category><![CDATA[retrospective analysis of HIV/TB co-infection]]></category>
		<category><![CDATA[statistical methods for HIV prevalence analysis]]></category>
		<category><![CDATA[surveillance data]]></category>
		<category><![CDATA[Tanzania]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<category><![CDATA[tuberculosis and HIV co-infection trends]]></category>
		<category><![CDATA[tuberculosis relapse and HIV co-infection risk]]></category>
		<category><![CDATA[use of DHIS2-eTL in HIV/TB surveillance]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=326622</guid>

					<description><![CDATA[A retrospective analysis of Tanzanian surveillance data found that HIV prevalence among children with tuberculosis and documented HIV status fell from 28.5% in 2018 to 8.9% in 2023.]]></description>
										<content:encoded><![CDATA[<p>HIV prevalence among children with tuberculosis in Tanzania’s 10 high-burden regions fell from 28.5% in 2018 to 8.9% in 2023, according to a retrospective analysis of national surveillance records. The study included 25,449 children younger than 15 years who were registered with tuberculosis and had a documented HIV status between January 2018 and December 2023. Of these children, 3,667 were HIV-positive, giving an overall prevalence of 14.4% with a 95% confidence interval of 14.0% to 14.8%. Although the annual decline was substantial, the analysis found that co-infection remained more common among older children, children registered with relapse tuberculosis and children in several regions.</p>
<p>Researchers analyzed Tanzania’s national electronic tuberculosis surveillance system, DHIS2-eTL. Eligibility was limited to children below 15 years with documented HIV status, and HIV positivity was confirmed at tuberculosis registration. The investigators used a chi-square test for linear trend to assess annual changes in prevalence. They also used modified Poisson regression with robust variance to estimate adjusted prevalence ratios for factors associated with HIV co-infection. As a result, the estimates describe children encountered through the tuberculosis surveillance system who had an HIV status recorded; they do not represent every child with tuberculosis or every child living with HIV in Tanzania.</p>
<p>HIV positivity declined in each successive year covered by the analysis. It was 28.5% in 2018, with a 95% confidence interval of 26.8% to 30.2%, and 8.9% in 2023, with an interval of 8.1% to 9.8%. The test for linear trend yielded a chi-square statistic of 719.7 with one degree of freedom and a p-value below 0.001. This corresponds to a roughly two-thirds proportional reduction over the six-year observation period. The surveillance analysis documents a marked change in the prevalence of co-infection among notified children, but it does not establish which interventions or changes in health services produced that change.</p>
<p>Prevalence increased across the three pediatric age groups. HIV positivity was 9.0% among children younger than five years, with a 95% confidence interval of 8.5% to 9.5%; 17.7% among those aged 5 to 9 years, with an interval of 16.8% to 18.6%; and 22.6% among those aged 10 to 14 years, with an interval of 21.6% to 23.7%. The chi-square statistic for this pattern was 684.3 with one degree of freedom and a p-value below 0.001. In the adjusted model, registration at ages 10 to 14 was associated with an adjusted prevalence ratio of 2.40, compared with the reference category, with a 95% confidence interval of 2.22 to 2.59. There was no statistically significant difference in prevalence between boys and girls, for which the reported p-value was 0.814.</p>
<p>Regional variation was also pronounced. Prevalence was highest in Njombe, at 29.7%, and lowest in Ruvuma, at 6.7%, with the overall regional difference reported at p below 0.001. After adjustment, registration in Njombe was associated with an adjusted prevalence ratio of 1.46, with a 95% confidence interval of 1.30 to 1.64. The study’s conclusion also identified Njombe, Mbeya and Iringa as places where co-infection remained concentrated. Relapse tuberculosis was associated with an adjusted prevalence ratio of 2.30, with a 95% confidence interval of 1.92 to 2.76. These are adjusted associations rather than evidence that age, region or relapse status directly caused HIV co-infection, and the surveillance records do not identify the mechanisms behind the observed patterns.</p>
<p>The retrospective design provides population-scale program data but carries important limitations. Results depend on the completeness and accuracy of routine records, while excluding children whose HIV status was not documented. The analysis also cannot directly determine the incidence of tuberculosis among children living with HIV or fully measure differences in access to testing, care-seeking and health services. Although the six-year trend and multivariable analysis add information beyond descriptive reporting, the findings should be interpreted as measured prevalence and modeled associations within notified cases. Children living with HIV who develop tuberculosis are described in the study background as having higher case fatality and lower treatment success than their HIV-negative peers; the present surveillance analysis did not directly compare those clinical outcomes. The authors concluded that Tanzania’s National Tuberculosis and Leprosy Programme should prioritize repeat HIV testing for children aged five years and above and for tuberculosis retreatment cases, with geographically intensified attention in Njombe, Mbeya and Iringa.</p>
<p><strong>Subject of Research:</strong> HIV prevalence and associated factors among Tanzanian children with tuberculosis</p>
<p><strong>Article Title:</strong> Prevalence and factors associated with HIV among children with tuberculosis in ten high-burden regions of Tanzania, 2018–2023: a retrospective analysis of national surveillance data</p>
<p><strong>Article References:</strong> Mgeyi, E. N., Kalabamu, F. S., Onduru, O. G., Riziki, K. M., Balama, R. F., Sililo, G. A., Shimba, P., Kwesiga, J. B., Rose, A., Wafula, S. T., Nsubuga, D., &amp; Kimuli, D. (2026). Prevalence and factors associated with HIV among children with tuberculosis in ten high-burden regions of Tanzania, 2018–2023: a retrospective analysis of national surveillance data. <em>BMC Infectious Diseases</em>. <a href="https://doi.org/10.1186/s12879-026-14459-0" rel="noopener noreferrer">https://doi.org/10.1186/s12879-026-14459-0</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12879-026-14459-0" rel="noopener noreferrer">10.1186/s12879-026-14459-0</a></p>
<p><strong>Keywords:</strong> HIV, tuberculosis, pediatric co-infection, Tanzania, surveillance data, prevalence trends, age differences, regional variation, relapse tuberculosis, public health, Prevalence, factors</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">326622</post-id>	</item>
		<item>
		<title>Descriptive field investigation finds three new tuberculosis cases after outreach screening at an informal settlement in Badalona, Spain</title>
		<link>https://scienmag.com/descriptive-field-investigation-finds-three-new-tuberculosis-cases-after-outreach-screening-at-an-informal-settlement-in-badalona-spain/</link>
		
		<dc:creator><![CDATA[Phoebe Ingram]]></dc:creator>
		<pubDate>Wed, 21 Oct 2026 00:18:39 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[Science News]]></category>
		<category><![CDATA[active TB]]></category>
		<category><![CDATA[Badalona]]></category>
		<category><![CDATA[challenges of TB control in informal urban housing]]></category>
		<category><![CDATA[community]]></category>
		<category><![CDATA[community screening]]></category>
		<category><![CDATA[community-based TB screening in Spain]]></category>
		<category><![CDATA[contact tracing]]></category>
		<category><![CDATA[health inequalities]]></category>
		<category><![CDATA[impact of overcrowding on TB transmission]]></category>
		<category><![CDATA[informal housing]]></category>
		<category><![CDATA[outreach]]></category>
		<category><![CDATA[outreach screening effectiveness in informal settlements]]></category>
		<category><![CDATA[public health response to TB clusters]]></category>
		<category><![CDATA[public health surveillance]]></category>
		<category><![CDATA[role of community engagement in TB detection]]></category>
		<category><![CDATA[screening]]></category>
		<category><![CDATA[social determinants of TB in vulnerable populations]]></category>
		<category><![CDATA[TB surveillance and containment strategies in Spain]]></category>
		<category><![CDATA[transmission]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<category><![CDATA[tuberculosis case detection among vulnerable populations]]></category>
		<category><![CDATA[tuberculosis epidemiology in immigrant communities]]></category>
		<category><![CDATA[Tuberculosis outbreak investigation in informal settlement]]></category>
		<category><![CDATA[urban health assessment in Badalona]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=326413</guid>

					<description><![CDATA[A descriptive field investigation in Badalona, Spain, found three new tuberculosis cases after outreach screening reached 81 of an estimated 150 people connected to an informal urban settlement.]]></description>
										<content:encoded><![CDATA[<p>A descriptive public health field investigation in an informal urban settlement in Badalona, Spain, found that community-based outreach screening identified three new active tuberculosis cases among 81 people screened between October 2024 and February 2025. The target population was an estimated 150 residents and non-resident community members connected to a former school building that had been occupied for five years. Overall, 11 tuberculosis cases were epidemiologically linked to the settlement: 10 were bacteriologically confirmed and one was clinically diagnosed.</p>
<p>The investigation followed the detection in late 2023 of a small cluster of tuberculosis cases among men of sub-Saharan origin living in Badalona. Several cases were linked to the occupied building, and another resident was subsequently hospitalized with disseminated tuberculosis and died during admission. The field investigation was coordinated by the Epidemiological Surveillance Service of Barcelonès Nord and Maresme with primary care, hospital and community teams, and was designed to identify undiagnosed active disease and assess the feasibility of outreach screening in a structurally vulnerable population.</p>
<p>Conditions in the building included overcrowding, poor ventilation, makeshift partitions, and limited access to water and electricity. In addition to people residing there, the building served as a social, religious and community gathering place, so the eligible population included regular non-resident users. Population estimates were uncertain and changed between visits; women and children were initially not known to be present, while people who used cannabis and alcohol were present in both sections of the building.</p>
<p>Three sequential on-site interventions combined health education, symptom-based screening and clinical assessment. Recruitment involved posters, word of mouth, visits by community health workers and support from trusted community representatives. The symptom questionnaire covered unexplained cough, unexplained fever lasting more than three weeks, night sweats, dyspnea, chest pain, unintentional weight loss and unexplained fatigue. People reporting symptoms and close contacts of cases were assessed clinically, while asymptomatic close contacts were referred for chest radiography. Referrals for suspected tuberculosis included chest radiography, sputum smear microscopy, culture and Xpert MTB/RIF Ultra testing under national protocols. Transportation cards and community-worker support were provided to facilitate access.</p>
<p>Across the three visits, 81 people were screened, equivalent to 54% of the estimated eligible population. Forty-five completed symptom questionnaires and clinical examinations, among whom 12 were classified as presumptive tuberculosis cases, a positivity of 27%. All 12 completed diagnostic evaluation, producing 100% retention in testing. Three were diagnosed with tuberculosis, giving a number needed to screen of 27 and a number needed to test of 4. Two began treatment, completed it and were cured; the third, a probable lymph node tuberculosis case, never started treatment and was lost to follow-up. Treatment outcomes were assessed through April 2026.</p>
<p>The October 2024 intervention reached 55 male participants, of whom 19 completed full clinical assessments. Two new smear-positive pulmonary tuberculosis cases were diagnosed after all seven people evaluated for suspected disease had received radiography, with one evaluated at primary care after missing a hospital appointment. The November intervention included 25 participants and 13 asymptomatic close contacts, resulting in one additional probable lymph node tuberculosis diagnosis. A February 2025 outreach effort identified 12 women and seven children linked to the settlement, but only one woman attended evaluation; no children were screened. She had previously received tuberculosis treatment and had a normal chest X-ray.</p>
<p>Beyond the three cases detected through screening, surveillance and hospital records identified six additional linked cases, bringing the total to 11. These included the index case, the fatal disseminated case, the two pulmonary cases found in the first intervention, the probable lymph node case found in the second, and six additional cases. During the ascertainment period, another 66 residents who had not been screened for tuberculosis and had no previous public health system record registered with and attended the Sant Roc Primary Care Center following community engagement and referral activities. Three children were also linked to pediatric primary care for health needs unrelated to tuberculosis screening.</p>
<p>Participation was limited by population mobility, incomplete enumeration, institutional mistrust, weak coordination with social services and limited transport and accompaniment support. Women and children were markedly underrepresented, and field professionals informally reported concerns that some women feared contact with public health services could draw the attention of social services. Site identification was delayed by six months after the initial reported cases, and incomplete mapping required another four months before the first intervention. An eviction notice issued during the campaign prompted residents to leave or relocate, contributing to loss to follow-up and unscreened people.</p>
<p>The investigation was descriptive and limited to one occupied building and its connected community. It did not include on-site chest radiography, so symptomatic participants and close contacts were referred to healthcare facilities, although all 12 presumptive cases completed diagnostic evaluation. The estimated eligible population remained uncertain, coverage differed across the three visits, and the findings cannot establish the effectiveness or cost-effectiveness of screening in comparable settlements. The authors nevertheless observed that coordinated community outreach detected active disease and linked residents with healthcare services, while concluding that such screening remains operationally fragile in the presence of housing instability, mobility, mistrust and limited institutional support.</p>
<p><strong>Subject of Research:</strong> Descriptive field investigation of community tuberculosis screening in an informal urban settlement in Badalona, Spain.</p>
<p><strong>Article Title:</strong> Tuberculosis transmission and community outreach screening in an informal urban settlement in a low-incidence European setting</p>
<p><strong>Article References:</strong> Flamarich-Gol, C., Bosch-Arís, M., Blázquez, G., Garcia-Circuns, A., Thiaw, B. E., Essadek, H. O., Roure, S., Stojanovic, Z., Bellido-Calduch, S., Lovera, M., García-Delgado, A., Segura, A., Carreres-Molas, A., Guasch-Arriaga, I., Antuori, A., Llop, A., Pillado, P., Romero, Y., Antolín, O., &#8230; Vilaplana, C. (2026). Tuberculosis transmission and community outreach screening in an informal urban settlement in a low-incidence European setting. <em>Frontiers in Public Health, 14</em>, Article 1907926. <a href="https://doi.org/10.3389/fpubh.2026.1907926" rel="noopener noreferrer">https://doi.org/10.3389/fpubh.2026.1907926</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.3389/fpubh.2026.1907926" rel="noopener noreferrer">10.3389/fpubh.2026.1907926</a></p>
<p><strong>Keywords:</strong> tuberculosis, community screening, active TB, outreach, informal housing, Badalona, public health surveillance, health inequalities, contact tracing, transmission, community, screening</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">326413</post-id>	</item>
		<item>
		<title>Cross-sectional study identifies seven predictors of stated willingness to accept TB preventive treatment among Xinjiang close contacts</title>
		<link>https://scienmag.com/cross-sectional-study-identifies-seven-predictors-of-stated-willingness-to-accept-tb-preventive-treatment-among-xinjiang-close-contacts/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Tue, 20 Oct 2026 21:08:26 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[accept]]></category>
		<category><![CDATA[close contacts]]></category>
		<category><![CDATA[cross-sectional study]]></category>
		<category><![CDATA[cross-sectional TB research China]]></category>
		<category><![CDATA[determinants]]></category>
		<category><![CDATA[health education]]></category>
		<category><![CDATA[health education influence on TB treatment]]></category>
		<category><![CDATA[logistic regression in TB studies]]></category>
		<category><![CDATA[nomogram development for TB prevention]]></category>
		<category><![CDATA[prediction nomogram]]></category>
		<category><![CDATA[predictive modeling for TB treatment acceptance]]></category>
		<category><![CDATA[predictors of TB treatment acceptance]]></category>
		<category><![CDATA[TB contact tracing and intervention]]></category>
		<category><![CDATA[TB contact willingness factors]]></category>
		<category><![CDATA[TB treatment adherence predictors]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<category><![CDATA[tuberculosis infection]]></category>
		<category><![CDATA[tuberculosis knowledge]]></category>
		<category><![CDATA[tuberculosis knowledge impact]]></category>
		<category><![CDATA[tuberculosis preventive treatment]]></category>
		<category><![CDATA[Tuberculosis preventive treatment willingness]]></category>
		<category><![CDATA[willingness]]></category>
		<category><![CDATA[Xinjiang]]></category>
		<category><![CDATA[Xinjiang tuberculosis contact study]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=323407</guid>

					<description><![CDATA[A cross-sectional study of 460 tuberculosis infection-positive close contacts in Xinjiang found that 80.9% stated willingness to accept preventive treatment and identified seven associated factors, while the internal prediction model requires external validation before implementation.]]></description>
										<content:encoded><![CDATA[<p>A cross-sectional study in Xinjiang, China, found that 372 of 460 close contacts with tuberculosis infection expressed willingness to accept tuberculosis preventive treatment during a face-to-face structured interview, representing 80.9% of participants. The study enrolled these participants between January 1 and December 31, 2023; they were close contacts of 87 people with bacteriologically confirmed pulmonary tuberculosis. Willingness was defined as a self-reported affirmative response to a standardized survey question, so the outcome measured stated intention rather than actual treatment initiation.</p>
<p>According to the study abstract, the investigators screened variables with least absolute shrinkage and selection operator regression using 10-fold cross-validation and then used multivariable logistic regression to identify independent statistical predictors. They developed and internally evaluated a predictive nomogram, assessing discrimination, calibration, the Brier score, sensitivity, specificity and decision curve analysis. Analyses were performed in R version 4.3.2 using the rms package.</p>
<p>Five factors were positively associated with willingness to accept preventive treatment. High tuberculosis-related knowledge had the strongest reported association, with an adjusted odds ratio of 6.00 and a 95% confidence interval of 3.30 to 10.91. Health education by healthcare workers was associated with willingness at an adjusted odds ratio of 3.65 (95% confidence interval, 1.90 to 7.00). Participants reporting a history of smoking had an adjusted odds ratio of 3.59 (95% confidence interval, 1.43 to 9.06), and those reporting alcohol consumption had an adjusted odds ratio of 3.10 (95% confidence interval, 1.02 to 9.41). Cohabitation with a person with tuberculosis was also associated with willingness, with an adjusted odds ratio of 2.09 (95% confidence interval, 1.14 to 3.84).</p>
<p>Two factors were inversely associated with stated willingness: higher annual household income, for which the reported adjusted odds ratio was 0.076 (95% confidence interval, 0.030 to 0.193), and frequent exercise. The abstract does not specify the income unit or the change represented by the income estimate, so the odds ratio should not be interpreted as applying to each individual increase in income. The investigators cautioned that the counterintuitive associations involving smoking and alcohol history warrant careful interpretation and may reflect perceived health vulnerability or residual confounding rather than direct causal pathways. They also noted that small subgroup sizes substantially limited the numerical precision of some estimates.</p>
<p>The nomogram showed good discrimination in internal evaluation, with an area under the curve of 0.861 (95% confidence interval, 0.817 to 0.902), a Brier score of 0.099 and satisfactory calibration; the reported Hosmer–Lemeshow result was χ² = 4.41, P = 0.819. The study authors described the model as a structured visual aid for predicting willingness and supporting individualized counseling by frontline healthcare workers, but stated that external validation in independent Chinese settings is required before clinical implementation. As a cross-sectional study conducted in one high-burden region, the research establishes associations in the enrolled sample rather than causal effects. It does not demonstrate actual treatment uptake, clinical benefit or the effectiveness of a counseling intervention.</p>
<p><strong>Subject of Research:</strong> Cross-sectional analysis of stated willingness to accept tuberculosis preventive treatment among infected close contacts in Xinjiang, China</p>
<p><strong>Article Title:</strong> Determinants of willingness to accept Tuberculosis Preventive Treatment (TPT) among close contacts with Tuberculosis Infection (TBI) in Xinjiang, China</p>
<p><strong>Article References:</strong> Wang, S., Peng, B., Wang, M., Jingesi, J., Wufuer, K., Liu, N., Wang, L., Wang, X., Wang, X., Xu, Y., Zhao, Y., Wang, J., Simayi, A., Ou, X., &amp; Cao, M. (2026). Determinants of willingness to accept Tuberculosis Preventive Treatment (TPT) among close contacts with Tuberculosis Infection (TBI) in Xinjiang, China. <em>BMC Public Health</em>. <a href="https://doi.org/10.1186/s12889-026-29457-9" rel="noopener noreferrer">https://doi.org/10.1186/s12889-026-29457-9</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12889-026-29457-9" rel="noopener noreferrer">10.1186/s12889-026-29457-9</a></p>
<p><strong>Keywords:</strong> tuberculosis preventive treatment, tuberculosis infection, willingness, close contacts, Xinjiang, cross-sectional study, prediction nomogram, health education, tuberculosis knowledge, Determinants, accept, Tuberculosis</p>
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		<title>Persistent tinnitus preceded diagnosis of multifocal tuberculosis in a 32-year-old patient: case report</title>
		<link>https://scienmag.com/persistent-tinnitus-preceded-diagnosis-of-multifocal-tuberculosis-in-a-32-year-old-patient-case-report/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Tue, 20 Oct 2026 20:40:40 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[atypical presentation of tuberculosis in young adult]]></category>
		<category><![CDATA[case]]></category>
		<category><![CDATA[case report]]></category>
		<category><![CDATA[complex case of tuberculosis with ENT and nervous system involvement]]></category>
		<category><![CDATA[disseminated tuberculosis presenting with neurological signs]]></category>
		<category><![CDATA[GeneXpert]]></category>
		<category><![CDATA[hearing loss]]></category>
		<category><![CDATA[miliary tuberculosis]]></category>
		<category><![CDATA[miliary tuberculosis with multi-organ dissemination]]></category>
		<category><![CDATA[multifocal]]></category>
		<category><![CDATA[multifocal tuberculosis]]></category>
		<category><![CDATA[neurological manifestations of tuberculosis]]></category>
		<category><![CDATA[otomastoid abscess]]></category>
		<category><![CDATA[positive sputum GeneXpert MTB/RIF test]]></category>
		<category><![CDATA[Revealing]]></category>
		<category><![CDATA[tinnitus]]></category>
		<category><![CDATA[tinnitus as initial symptom of multifocal tuberculosis]]></category>
		<category><![CDATA[tuberculomas]]></category>
		<category><![CDATA[tuberculosis]]></category>
		<category><![CDATA[tuberculosis involving middle ear and otomastoid abscess]]></category>
		<category><![CDATA[tuberculosis with cranial nerve involvement]]></category>
		<category><![CDATA[tuberculosis-related hearing loss and paresthesia]]></category>
		<category><![CDATA[use of MRI and CT imaging in tuberculosis diagnosis]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=322782</guid>

					<description><![CDATA[A case report describes persistent isolated tinnitus preceding the diagnosis of multifocal tuberculosis affecting the lungs, nervous system, ear, nose and throat, and adrenal glands in a 32-year-old patient with diabetes.]]></description>
										<content:encoded><![CDATA[<p>A 32-year-old patient with diabetes and no known history of tuberculosis sought care for three months of isolated, persistent tinnitus without associated respiratory signs, according to a case report in BMC Infectious Diseases. The initial ear, nose and throat examination was unremarkable, but the condition later progressed to include left-sided hearing loss, facial and upper-limb paresthesia, nocturnal fever and deterioration in general condition.</p>
<p>Diagnostic imaging identified several affected anatomical sites. Brain MRI showed a left otomastoid abscess alongside necrotic thalamic and mesencephalic lesions considered suggestive of tuberculomas. Chest, abdominal and pelvic CT revealed diffuse pulmonary miliary tuberculosis, mediastinal lymphadenopathy and enlarged adrenal glands. A sputum GeneXpert MTB/RIF test was positive for <em>Mycobacterium tuberculosis</em>, leading to a diagnosis of multifocal tuberculosis involving the lungs, nervous system, ear, nose and throat, and adrenal glands.</p>
<p>The authors described the case as an unusual presentation of disseminated tuberculosis. The abstract notes that tinnitus is an uncommon manifestation and reports that there were no previously described cases in which persistent isolated tinnitus was the initial symptom of multifocal tuberculosis. In this case, tinnitus preceded the appearance of other neurological, sensory and systemic findings, including left-sided hearing loss, paresthesia, fever and worsening general condition.</p>
<p>Following diagnosis, the patient received four-drug antituberculosis therapy, and the report stated that clinical progress was favorable. Because the evidence comes from a single case report, the observation does not establish how frequently multifocal tuberculosis presents with tinnitus or whether the same clinical course can be expected in other patients. The authors concluded that persistent unexplained tinnitus may warrant consideration of a systemic infectious cause, particularly in settings where tuberculosis is endemic, and emphasized the role of molecular testing in early diagnosis.</p>
<p><strong>Subject of Research:</strong> A case report of multifocal tuberculosis initially revealed by persistent tinnitus</p>
<p><strong>Article Title:</strong> Tinnitus revealing a multifocal tuberculosis: a case study</p>
<p><strong>Article References:</strong> Qadiri, K., Belhajou, L., Azouzou, K., Lahlou, Y. B., Benaissa, E. M., &amp; chadli, M. (2026). Tinnitus revealing a multifocal tuberculosis: a case study. <em>BMC Infectious Diseases</em>. <a href="https://doi.org/10.1186/s12879-026-14239-w" rel="noopener noreferrer">https://doi.org/10.1186/s12879-026-14239-w</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1186/s12879-026-14239-w" rel="noopener noreferrer">10.1186/s12879-026-14239-w</a></p>
<p><strong>Keywords:</strong> tinnitus, multifocal tuberculosis, case report, miliary tuberculosis, tuberculomas, otomastoid abscess, hearing loss, GeneXpert, revealing, multifocal, tuberculosis, case</p>
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