The study was a secondary analysis of cross-sectional initial-visit data from the publicly available Get SET Early dataset. After complete-case analysis, it included 1,502 children diagnosed with autism spectrum disorder and 570 typically developing children. The autism group included 1,171 boys and 331 girls and had a mean age of 26.2 months; the typically developing group included 332 boys and 238 girls and had a mean age of 25.2 months. In the original study, legal guardians provided informed consent and the University of California, San Diego ethics committee approved the protocol.

The researchers constructed Gaussian graphical models from ten variables measured with three standardized assessments. The Autism Diagnostic Observation Schedule supplied social affect and restricted and repetitive behaviors. The Vineland Adaptive Behavior Scales contributed communication, socialization, daily living skills and motor skills, while the Mullen Scales of Early Learning supplied fine motor, visual reception, receptive language and expressive language. The models were estimated with EBICglasso regularization, and the researchers examined network topology, node centrality, descriptive sex-specific patterns and conditional-dependence structures.

The two groups differed in global strength and in their prominent estimated edges. In the typically developing network, communication had strong associations with expressive language and daily living skills, with edge weights of 0.31 and 0.30. In the autism network, the largest edges linked fine motor with visual reception at 0.45 and receptive with expressive language at 0.37. The negative association between fine motor and restricted and repetitive behaviors was also estimated at −0.12 in the autism network, compared with −0.01 in the typically developing network. These values describe conditional associations and do not demonstrate causal relationships.

Communication had the highest strength centrality in the typically developing network, whereas receptive language had the highest strength in the autism network. A Network Comparison Test based on 1,000 permutations found greater global strength in the autism network, with a difference of 1.79 and p<0.001. Global strength is the sum of absolute edge weights and is not equivalent to network density. Exploratory bridge-centrality calculations identified receptive language and communication as the leading cross-domain connectors in the autism network, with bridge-strength values of 0.661 and 0.655. Because these raw statistics were not tested with a normalized inferential comparison, they do not establish reduced inter-domain integration in autism.

Case-dropping bootstrap analyses with 1,000 resamples indicated good stability for the autism network’s strength, closeness and betweenness indices, each with a CS coefficient of 0.75. For the typically developing group, the corresponding coefficients were 0.672 for strength and 0.595 for closeness. These results concern stability within the submitted EBICglasso specification and resampling procedure; the study did not examine whether the network remained similarly stable under alternative estimators, tuning parameters or node sets.

The researchers also estimated directed acyclic graphs to summarize conditional-dependence structures. In the typically developing model, communication was connected to daily living skills, socialization, receptive language and expressive language. In the autism model, social affect and restricted and repetitive behaviors were connected to receptive language. The authors did not interpret these orientations as temporal order, developmental cascades or causal effects. With cross-sectional data, statistically equivalent graphs can represent the same distribution, so arrow directions cannot resolve causal or developmental mechanisms.

Exploratory comparisons by sex found that none of the ten variables differed between boys and girls in the autism group after Benjamini-Hochberg false-discovery-rate correction; all q values were at least 0.228. Eight variables differed in the typically developing group after correction, with girls scoring higher on communication, socialization, daily living skills, visual reception, receptive language and expressive language, and boys scoring higher on social affect and restricted and repetitive behaviors. Network comparisons found higher global strength in autism among both boys and girls, with differences of 2.03 and 1.56, respectively, both with p<0.001. The much smaller female autism subgroup, 331 compared with 1,171 males, and the absence of sample-size-balanced sensitivity analyses limit these exploratory findings.

Several limitations constrain the proposed model. Structural vulnerability was an interpretive network descriptor rather than a validated scalar index, and no normalized formal comparison of inter-domain integration was performed. Edge-level Network Comparison Test p values were unadjusted, age was not included as a covariate, and unmeasured clinical, socioeconomic and contextual characteristics may have influenced the estimates. The selected nodes did not include executive functioning, sensory processing or play skills, which could affect the estimated topology and centrality ordering. The model has also not been tested in an independent autism cohort. The authors therefore characterize receptive language and communication as candidate central and bridging nodes and state that longitudinal, covariate-adjusted, externally replicated and sensitivity-tested studies are required before developmental, clinical or intervention implications can be established.

Subject of Research: Cross-sectional symptom-ability network analysis of a provisional autism structural vulnerability model in preschool children

Article Title: A structural vulnerability model of autism derived from symptom-ability network analysis

Article References: Li, H.-M., & Chen, Z. (2026). A structural vulnerability model of autism derived from symptom-ability network analysis. Frontiers in Psychiatry, 17, Article 1837552. https://doi.org/10.3389/fpsyt.2026.1837552

Image Credits: AI Generated

DOI: 10.3389/fpsyt.2026.1837552

Keywords: autism spectrum disorder, network analysis, receptive language, adaptive communication, preschool children, cross-sectional study, centrality, conditional dependence, sex differences, hypothesis-generating research, structural, vulnerability

Researchers used the Livelihood Vulnerability Index and the Intergovernmental Panel on Climate Change framework to examine livelihood vulnerability among tribal communities in the Lohardaga and Khunti districts. The evidence summarized in the article abstract comes from a primary survey of 400 tribal households, supplemented by focus group discussions. Because only the abstract and publisher preview were supplied, the full questionnaire, analytical procedures and underlying results cannot be assessed here.

The abstract identifies higher vulnerability in livelihood strategies, health, assets and climate variability. Under the LVI-IPCC analysis, the reported exposure, sensitivity and adaptive-capacity values were 0.392, 0.479 and 0.485, respectively. These findings describe measured index results rather than forecasts of future vulnerability or evidence that any particular intervention would improve outcomes.

The tribal comparison did not follow the apparent level of district development. The abstract reports that the Oraon tribe, residing in a more developed district, showed greater vulnerability, largely due to climate variability. By contrast, the Munda tribe, residing in a less developed district, had comparatively lower vulnerability, although the abstract notes constraints associated with limited asset ownership and inadequate infrastructure. This cross-sectional geographic comparison does not establish change over time or a causal relationship between district development and vulnerability.

The study’s scope was limited to 400 tribal households in two districts of rural Jharkhand, and the abstract does not provide uncertainty intervals, demographic breakdowns or evidence that the results represent every tribal community in the region. The authors’ abstract concludes that the findings point toward targeted interventions to strengthen adaptive capacity and improve livelihood security, but it does not report implementation or outcome data for such measures.

Subject of Research: Measured livelihood vulnerability among 400 tribal households in rural Jharkhand

Article Title: Livelihood vulnerability among tribal communities: empirical evidence from rural Jharkhand, India

Article References: Ankita, K., & Kumar, M. (2026). Livelihood vulnerability among tribal communities: empirical evidence from rural Jharkhand, India. SN Social Sciences, 6(9), Article 378. https://doi.org/10.1007/s43545-026-01672-6

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01672-6

Keywords: tribal communities, livelihood vulnerability, Jharkhand, Lohardaga, Khunti, climate variability, adaptive capacity, household survey, mixed-methods study, Livelihood, vulnerability, tribal

Verbal harassment was the most frequently reported experience. A total of 69.67% of surveyed operators said enforcement personnel had made them feel less than human, while most reported being shouted at, sworn at or insulted. Physical assault was reported by 24.6% of respondents, and sexual harassment by 4.1%. Demands for bribes were also widespread, with 78.69% reporting such demands. These figures describe the experiences recorded in the operator survey; the abstract does not provide details about survey dates, recruitment, question wording or statistical uncertainty around the percentages.

The authors interpret the survey alongside the officers’ accounts as showing that roadside enforcement cannot be characterized simply as interactions between powerful officers and powerless drivers. The focus-group material indicated that harassment could run in both directions, while bribery could range from a coerced toll to a transaction chosen by the operator. The researchers also report repeated bending of enforcement through elite interference. Drawing on theories of state-produced informality, street-level discretion and political economy, they propose a “discretion in exception” model to explain how unaccountable discretion within a weakly regulated environment may contribute to these outcomes.

The study offers an empirical account of what enforcement encounters can look like for informal transport workers in one Nigerian city, while also presenting a framework for examining relationships between police authority, discretion and informality. Its stated contribution includes documenting the bidirectional and elite-influenced character of Nigerian roadside enforcement and demonstrating how complementary data can be used to study a population that the authors describe as previously unmapped. However, this report is based only on the accessible abstract rather than the full article. The limited information available prevents assessment of the instruments, analytical procedures, subgroup patterns and broader generalizability, and the reported associations do not by themselves establish the causes of harassment, bribery or assault.

Subject of Research: Mixed-methods analysis of law-enforcement encounters experienced by informal transport operators in Ibadan, Nigeria

Article Title: The dynamics of power and vulnerability: an analysis of law enforcement interactions with informal transport operators in Ibadan, Nigeria

Article References: Akogun, O., & Popoola, A. (2026). The dynamics of power and vulnerability: an analysis of law enforcement interactions with informal transport operators in Ibadan, Nigeria. SN Social Sciences, 6(9), Article 381. https://doi.org/10.1007/s43545-026-01673-5

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01673-5

Keywords: informal transport, road enforcement, harassment, bribery, police, Nigeria, Ibadan, mixed methods, street-level discretion, dynamics, power, vulnerability

The species is an endemic reptile occupying isolated high-elevation habitats in the Coastal and Andean mountain ranges of central Chile, from southern Coquimbo to northern O’Higgins. It generally occurs between 2,000 and 2,800 metres above sea level. Such sky-island populations are separated from one another by warmer, drier valleys and have progressively less connected habitat as temperature and precipitation patterns change. The International Union for Conservation of Nature lists L. nigroviridis as Least Concern, although earlier work has identified potential risks from climate change and anthropization. The new analysis examined how the species’ climate envelope might change and where human occupation could constrain movement between mountain areas.

For the analysis, researchers used 199 georeferenced presence records from 53 localities, compiled from literature, museum catalogues, GBIF and iNaturalist and filtered for geographic precision. They generated 597 pseudoabsences with the BIOMOD2 package. A preliminary sensitivity analysis using the True Skill Statistic indicated that this number maintained accuracy without overfitting. The final modelling used a Random Forest algorithm in five repeated runs, dividing the records into 80% training and 20% testing sets in each run. The best-performing model achieved a True Skill Statistic of 0.86 and a receiver operating characteristic value of 0.98, metrics interpreted in the study as indicating good discrimination between presence and absence.

Six variables from WorldClim 2 were retained: mean diurnal temperature range, temperature seasonality, minimum temperature of the coldest month, annual precipitation, precipitation during the driest quarter and precipitation during the warmest quarter. Their selection combined the species’ thermal ecology, previous modelling work on Liolaemus, tests of multicollinearity through the Variance Inflation Factor, and Random Forest importance scores. Future layers came from the CMIP6 MPI-ESM1-2-HR model under RCP 4.5 and RCP 8.5 for 2040 and 2080. High-suitability areas were defined as those with a predicted presence probability greater than 0.6. The analysis then compared their area and mapped projected gains and losses across the study region.

The range contraction varied markedly among scenarios. The high-probability area was 3,538.2 square kilometres under 2040 RCP 4.5, 3,465.7 under 2040 RCP 8.5, 3,336.3 under 2080 RCP 4.5 and 2,058.0 under 2080 RCP 8.5. Relative to current conditions, the corresponding total changes were −1.1%, −3.1%, −6.7% and −42.5%. In the most severe scenario, 59.1% of the current area was projected to be lost and 16.6% gained. The sharp contrast between the 2080 scenarios indicates that the model outcome depended strongly on the greenhouse-gas pathway used to generate the future climate layers.

Geographically, the 2080 RCP 8.5 projection contained no high-probability climate envelope in Coquimbo, where the species is currently present. A small area around the mountains near Coltauco remained in the Coastal Range, limiting southward expansion in that part of the distribution. In the Andes, however, the southern limit shifted toward Chimbarongo–Las Peñas, north of the Alto Huemul nature sanctuary. The maximum southward displacement was 33.8 kilometres in the 2040 RCP 8.5 projection and 60.6 kilometres in the 2080 RCP 8.5 projection. The model therefore supported the study’s expectation of a southward movement and reduced geographic range, but it did not project the anticipated shift to higher elevations through 2080.

The absence of an altitudinal displacement may reflect both the species’ biology and the limits of the modelled period and scenarios. In the Coastal Range, the available habitat already reaches 2,281 metres, leaving limited space for an uphill move. The Andes contain many peaks above 4,000 metres, but the model did not identify high-probability conditions there under the scenarios examined. The authors suggest that the magnitude of climatic change through 2080 may be insufficient to reveal a significant altitudinal shift for this species. They also note that the timing of such movements varies among taxa and can extend from decades to centuries, with rapid shifts more readily observed in highly mobile organisms.

Land-use information was added after the climate models were produced, using a WorldCover layer that mapped croplands and built environments. It was not a forecast of future urban expansion and therefore represented a conservative account of the barriers the species could encounter. The mapped human footprint was greater in the Coastal Range than in the Andes. This contrast matters for the projected difference between the two mountain systems: Andean populations had a potential route toward newly suitable southern areas without the same concentration of croplands and buildings, while Coastal populations would face a denser network of human land uses if suitable conditions eventually shifted beyond Coltauco. River basins can also impede dispersal among Andean populations, although the study did not identify a comparable concentration of cropland and buildings along that route.

The climate variables used in the model point toward warming and drying in the study area. Under 2080 RCP 8.5, minimum temperature of the coldest month increased by 70.97%, annual precipitation decreased by 28.90%, and precipitation during the driest and warmest quarters remained unchanged. The authors connect these patterns with reduced humidity in central Chile and potential changes in the shrub habitats used by Liolaemus for thermoregulation. Field observations cited in the study describe lizards basking in the morning and retreating into shaded vegetation to avoid overheating and dehydration. The projections do not directly demonstrate changes in plant recruitment, activity time or population survival, but they identify climatic variables that could affect the conditions on which the species depends.

Humidity may also influence the insect prey of this mainly insectivorous lizard. The evidence reviewed by the authors links humidity with insect survival, reproduction, movement and migration, while low humidity can constrain some insect species. For the lizard, these relationships provide a possible route by which climatic drying could affect food resources in addition to direct thermal stress. The study did not measure prey abundance, feeding success or reproduction, however, so these remain ecological mechanisms discussed in relation to the model rather than quantified outcomes. The robust findings are the projected contraction and southward movement of the climate envelope, the regional disappearance of high-probability conditions in Coquimbo, and the differing land-use constraints facing Coastal and Andean populations.

The authors present assisted migration as a possible future option, particularly for Coastal populations that may be unable to cross human barriers while tracking shifting climate conditions. Human-assisted translocation is generally discussed for species with limited dispersal capacity, but it may also be considered when otherwise mobile species cannot reach newly suitable habitat because of anthropogenic barriers. The modelling study did not implement or evaluate a translocation, establish that one would be necessary or safe, or test possible ecological and genetic consequences. Its broader contribution is to show how climate projections and land-use maps can be combined to identify differing vulnerability among populations of the same species. The authors suggest that this approach could also inform research on other central Chilean reptiles with similar habitat requirements, including Liolaemus bellii, Liolaemus leopardinus and Pristidactylus volcanensis, for which additional ecological and physiological work would be needed.

Subject of Research: Modelled climate and land-use vulnerability of the Chilean sky island lizard Liolaemus nigroviridis

Article Title: Assessing the vulnerability of a sky island lizard to climate and land-use change

Article References: Mella-Romero, J., Maya-Miranda, S., Véliz, D., & Simonetti, J. A. (2024). Assessing the vulnerability of a sky island lizard to climate and land-use change. Herpetozoa, 37, 257-267. https://doi.org/10.3897/herpetozoa.37.e125163

Image Credits: AI Generated

DOI: 10.3897/herpetozoa.37.e125163

Keywords: Liolaemus nigroviridis, species distribution modelling, climate change, land-use change, sky islands, central Chile, Andean Range, Coastal Range, Random Forest, conservation, Assessing, vulnerability

The idea arrives at a critical moment. Oxidative stress has been implicated in virtually every major neurodegenerative disorder, from Alzheimer’s and Parkinson’s diseases to amyotrophic lateral sclerosis (ALS) and peripheral neuropathies. Damaged proteins, oxidized lipids, and injured nucleic acids accumulate in diseased neural tissue, and more than 30 causative genes have been identified for ALS alone. Yet mutations in any single gene explain only a small fraction of cases, and clinical trials of broad-spectrum antioxidants have repeatedly disappointed. Wakatsuki and Araki argue that this failure reveals a fundamental truth: the biological consequences of ROS are determined not merely by their abundance, but by the molecular architecture that interprets and transduces redox signals within neurons.

At the heart of the new framework is a distinction that has often been blurred in the literature. ROS themselves are not simply toxic byproducts; they are physiological signaling molecules that regulate cell proliferation, immunity, autophagy, metabolism, and tissue repair. Oxidative stress, by contrast, denotes a condition in which ROS production exceeds the cellular capacity for detoxification. The presence of ROS therefore does not by itself specify whether a neuron will adapt, degenerate, or die. What matters is the threshold—an emergent property of a signaling network shaped by signal amplitude, duration, subcellular location, prior priming, feedback, and the simultaneous engagement of independent pathways.

The authors organize this threshold logic into four partially overlapping layers. The first is ROS generation and oxidative input, driven by the intense mitochondrial activity required to meet neurons’ high energy demands and by NADPH oxidase (NOX) activity. The second is antioxidant buffering and adaptation, mediated by pyridine nucleotide systems (NAD/NADH and NADP/NADPH) and thiol-based redox couples such as glutathione (GSH/GSSG) and cysteine/cystine. The third is redox-sensitive signal detection and molecular gating, in which oxidative modifications of proteins alter enzymatic activity, interactions, localization, and stability. The fourth comprises cellular outcomes—degeneration, survival and adaptation, or repair and regeneration. Crucially, downstream commitment mechanisms need not themselves be directly redox-sensitive; rather, they help set the effective threshold by determining whether an oxidative perturbation is tolerated, amplified, converted into structural degeneration, or followed by successful clearance and repair.

Threshold logic of this kind is well established in other biological systems. In the DNA-damage response, the duration and temporal pattern of p53 activity can direct recovery, arrest, senescence, or apoptosis even when cumulative signal exposure is similar. Individual p53 target promoters decode amplitude, duration, and frequency using different threshold and filtering properties. In T cells, distinct pathways downstream of the same antigen receptor show different activation thresholds, allowing signal strength to be translated into graded and digital outputs. The parallels do not imply that neuronal oxidative signaling uses the same molecular circuitry, but they illustrate a general design principle: biological specificity can reside in the architecture and dynamics of signal processing rather than solely in the identity or amount of the initiating stimulus. Neurons are especially suitable for such regulation because signals must be integrated across long distances, highly specialized compartments, and long lifetimes—meaning that local redox events in an axon, synapse, mitochondrion, or glial contact may be interpreted differently even within the same cell.

The buffering layer reveals why antioxidant capacity cannot be reduced to a single variable. In the CNS, mature forebrain neurons can exhibit epigenetic repression of the transcription factor NRF2, whereas astrocytes retain strong NRF2-dependent transcriptional responses, and neuronal activity can induce NRF2-dependent glutathione metabolism genes in astrocytes—illustrating that antioxidant protection in the brain is dynamically distributed across cell types. Genome-wide CRISPR interference and activation screens in human induced pluripotent stem cell-derived neurons have identified glutathione peroxidase 4, selenocysteine metabolism, lysosomal function, iron handling, and autophagy as major determinants of survival under chronic oxidative stress. Prosaposin, a lysosomal precursor protein required for sphingolipid degradation, proved particularly important: its deficiency produced a neuron-selective pathway leading from lysosomal failure and iron trapping to lipid peroxidation and ferroptosis. Antioxidant capacity, in other words, is a coupled network linking thiol metabolism, organelle quality control, iron homeostasis, and lipid composition.

The PNS, meanwhile, is not simply biased toward antioxidant protection. Schwann cells can support axons and adopt repair-promoting states after injury, but they can also generate spatially restricted oxidative signals that amplify neuroinflammation—a Schwann cell TRPA1–NOX1 circuit sustains macrophage-dependent oxidative signaling after peripheral nerve injury. NRF2 activation can be protective in experimental peripheral neuropathy, yet these observations do not establish that basal NRF2 activity is globally stronger in every PNS neuron or glial state. CNS and PNS tissues may instead utilize different combinations of neuronal and glial redox-buffering mechanisms that vary according to the type and temporal stage of injury.

The gating layer provides some of the most mechanistically detailed examples. Oxidation of catalytic cysteine residues in protein phosphatases can reversibly suppress their activity, prolonging receptor- and MAPK-dependent signaling; in neurons, reversible oxidation of ERK-directed phosphatases can convert oxidative stress into sustained ERK activity and toxicity. Redox modifications can also activate, rather than inhibit, signaling enzymes: glutathione S-transferase pi 1-mediated S-glutathionylation of Aurora-A at Cys290 promotes its dimerization and autophosphorylation, coupling localized redox fluctuations to MEK–ERK signaling and postsynaptic maturation. The ubiquitin system is similarly regulated by redox-mediated modification—nitrosative or oxidative modification of the cysteine-rich E3 ligase parkin can alter and subsequently impair its activity, linking redox stress to defective protein quality control in models of Parkinson’s disease. These gates filter out weak, transient, or spatially inappropriate signals through priming phosphorylation, scaffold assembly, compartmental recruitment, relief of autoinhibition, or loss of an inhibitory metabolite. The number, order, and subcellular localization of required events may be as important as the absolute abundance of ROS.

Among the pathways linking oxidative stress to neuroaxonal degeneration, the E3 ubiquitin ligase ZNRF1 provides a particularly clear worked example. ZNRF1 is expressed in neurons in both the CNS and PNS and participates in axonal degeneration in response to oxidative stress, ischemic injury, and axon severance. ROS-dependent activation of EGFR promotes phosphorylation of ZNRF1, inducing its ubiquitin ligase activity. Activated ZNRF1 ubiquitinates AKT and promotes its proteasomal degradation, releasing GSK3β from AKT-mediated inhibition and activating GSK3β-dependent pathways that destabilize microtubules and drive neurite fragmentation. The events upstream of ZNRF1, however, are not identical in the experimental CNS and PNS paradigms examined. In cultured central neurons exposed to oxidative stress, ROS-dependent EGFR activation seems directly coupled to ZNRF1 phosphorylation. In injured peripheral axons, by contrast, ZNRF1 activation additionally requires p38 MAPK-dependent phosphorylation of p47phox at Ser345, which promotes NOX-dependent ROS signaling. The authors interpret this additional requirement as a two-step gate: injury-associated p38 signaling supplies a permissive state, whereas NOX-derived ROS supplies the activating redox signal. This two-step architecture may reduce inappropriate pathway activation by requiring coincident signals before Wallerian degeneration proceeds.

Downstream of these gates lie commitment mechanisms that determine whether an upstream perturbation becomes irreversible. The dual leucine zipper kinase (DLK) pathway can serve as a signaling mediator for both protective and degenerative responses—supporting regenerative transcription after axonal injury, but also activating JNK–JUN-dependent degeneration and neuronal death. Stress-induced recruitment of DLK to palmitoylated, sphingomyelin-rich vesicular assemblies is required for local kinase activation, illustrating how subcellular organization creates a regulated signaling checkpoint. The NMNAT2–SARM1 system provides an even clearer commitment threshold: mitochondrial impairment can deplete axonal NMNAT2 and increase the NMN/NAD+ ratio, which SARM1 senses through its autoinhibitory armadillo repeat domain; once activated, its NAD+ hydrolase activity triggers a feed-forward metabolic catastrophe that commits the axon to degeneration. These pathways also demonstrate that degeneration and regeneration are not simply opposite ends of a single linear scale—a neuron may have a high threshold for somatic death but a low threshold for local axon degeneration, or it may undergo rapid Wallerian degeneration while retaining robust axonal regenerative capacity.

The therapeutic implications are profound. The limited clinical success of broad antioxidant therapies suggests that simply lowering ROS levels may be insufficient—and may also interfere with physiological redox signaling. The threshold framework instead identifies several possible intervention levels: increasing buffering in a vulnerable cell type, preventing pathological priming or scaffold assembly, inhibiting conversion of a redox signal into a degenerative program, or blocking the execution step after upstream stress has occurred. The DLK and SARM1 fields illustrate both the promise and the risk of this strategy. Pharmacological SARM1 inhibition protects axon structure and function in preclinical models, including chemotherapy-induced peripheral neuropathy. By contrast, a phase 1 study of the DLK inhibitor GDC-0134 in ALS identified dose-limiting sensory and ocular adverse events, emphasizing that chronic cell-wide inhibition of a multifunctional stress pathway may have unintended consequences. More selective interference with stimulus-dependent axonal DLK palmitoylation and localization has recently been shown to suppress pro-degenerative signaling while avoiding cytoskeletal effects associated with direct kinase inhibition—supporting the targeting of a disease-relevant gating event rather than eliminating an entire signaling system.

Wakatsuki and Araki are careful to bound their claims. The available ZNRF1 studies used different neuronal preparations and stress paradigms and did not generate matched ROS dose–response curves in CNS and PNS neurons; they support a model of distinct activation requirements but do not yet establish a quantitatively higher ZNRF1 activation threshold throughout the PNS. The relevant unit of comparison, the authors insist, is not the CNS neuron versus the PNS neuron, but a defined neuronal subtype in a defined compartment and injury context, together with its associated glia and immune cells. Single-cell profiling of dorsal root ganglia after peripheral and central axon injury has shown that neuronal and non-neuronal populations engage distinct transcriptional and intercellular programs, while spatial transcriptomic studies of human neurodegenerative tissue reveal region- and cell-state-specific molecular programs associated with selective vulnerability.

The next step for the field will be quantitative comparison. Experiments that measure input-output relationships at single-cell and subcellular resolution, under matched CNS and PNS conditions and in the presence of relevant glia, will help determine whether proposed gates truly alter the threshold for degeneration. If manipulation of p38 MAPK or p47phox Ser345 alters ROS production but does not change the relationship between local ROS levels and ZNRF1 activation, the pathway would be better regarded primarily as a mechanism controlling ROS production; if the pathway status alters ZNRF1 activation at comparable local ROS levels, this would support a genuine gating mechanism. Separating ROS generation from the molecular decisions that interpret ROS may ultimately reveal why apparently similar oxidative burdens produce divergent outcomes—and may help identify therapeutic targets that preserve physiological redox signaling while preventing pathological commitment to neurodegeneration.

Subject of Research: Oxidative signaling thresholds shape vulnerability in the central and peripheral nervous systems

Article Title: Oxidative signaling thresholds shape vulnerability in the central and peripheral nervous systems

Article References: Wakatsuki, S., & Araki, T. (2026). Oxidative signaling thresholds shape vulnerability in the central and peripheral nervous systems. PLOS Biology, 24(10), e3004032. https://doi.org/10.1371/journal.pbio.3004032

Image Credits: AI Generated

DOI: 10.1371/journal.pbio.3004032

Keywords: Oxidative, signaling, thresholds, shape, vulnerability, central, peripheral, nervous, systems, scientific research

The research, led by Li Sun and colleagues at Beijing University of Civil Engineering and Architecture, integrates three complementary methodological strands: hydrological simulation, machine learning, and spatial statistics. The team employed the SCS-CN model, a widely used rainfall-runoff framework developed by the United States Soil Conservation Service, to simulate how precipitation is converted into surface runoff across the basin’s varied landscapes. The model’s core logic hinges on a curve number, a parameter that captures how readily land produces runoff depending on soil type, land cover, and antecedent moisture. Paved, compacted, or otherwise impervious surfaces generate far more runoff than forested slopes, and the SCS-CN approach translates those differences into spatially explicit estimates of flood hazard for every corner of the basin.

On top of that hydrological foundation, the researchers deployed XGBoost, a gradient-boosted decision tree algorithm prized for its ability to capture complex, nonlinear relationships among many environmental variables. Flood risk is rarely the product of a single factor in isolation; instead, rainfall depth, elevation, slope, drainage density, vegetation cover, and the extent of impervious surfaces interact in ways that traditional linear models struggle to represent. XGBoost excels at learning these multi-factor couplings from data, but its predictions can be opaque. To open the black box, the team applied SHAP, or SHapley Additive exPlanations, a technique borrowed from cooperative game theory that quantifies each variable’s contribution to every individual prediction. The result is a risk model that is not only accurate but interpretable, revealing exactly how and where each driver pushes risk up or down for the historic buildings in question.

The third pillar of the framework is spatial autocorrelation analysis, a family of statistical methods that tests whether high or low risk values cluster geographically more than random chance would predict. This matters because heritage protection decisions are inherently spatial: resources for flood defenses, drainage improvements, and emergency planning must be allocated to places, and knowing that risk concentrates in identifiable hotspots is far more actionable than a list of individual buildings. By combining hazard, the probability and severity of flooding, with vulnerability, the susceptibility of buildings and their settings to damage, the researchers produced an integrated risk assessment for every one of the 5,482 historic structures in the dataset.

The findings paint a strikingly patterned picture of heritage flood risk across the Minjiang River Basin. Flood hazard, the team found, decreases from downstream to upstream, forming belt-like aggregations that trace the river network itself. This geometry makes intuitive sense once the underlying hydrology is considered: downstream reaches accumulate runoff from the entire upstream catchment, water levels rise higher, and floodplains widen, so the hazard envelope hugs the main channels most heavily in the lower basin. Historic buildings sited along these lowland waterways, often deliberately, since rivers were the arteries of trade and settlement, therefore sit squarely within the zones of greatest hydraulic exposure.

Vulnerability, however, tells the opposite story. The study reveals a spatial mismatch: vulnerability is higher upstream and lower downstream. That inversion matters because risk is not simply hazard; it is the product of how likely a flood is and how much damage it can do. A modest flood striking fragile, poorly protected upstream structures may cause more harm than a larger flood reaching resilient downstream buildings. The mismatch means that hazard maps alone, however sophisticated, cannot guide heritage protection. Planners who prioritized only downstream floodplains would leave the vulnerable upstream clusters, where steep terrain, constrained evacuation routes, and building characteristics may amplify damage, comparatively unguarded.

When hazard and vulnerability are integrated, the resulting risk map follows a southeast-high to northwest-low gradient across the basin, with strong clustering in the estuarine zone and the midstream valleys. These hotspots are precisely where high hydraulic exposure coincides with concentrations of vulnerable historic fabric, making them the natural focal points for intervention. The spatial autocorrelation analysis confirms that these high-risk zones are statistically significant clusters rather than scattered accidents of individual building locations, which strengthens the case for basin-scale, coordinated management rather than building-by-building measures.

Perhaps the most technically interesting contribution lies in what the SHAP analysis uncovered about the drivers of risk. Key factors including impervious surfaces, vegetation cover, and topography exhibit significant nonlinear threshold effects, meaning their influence on flood risk does not increase smoothly but jumps once certain critical values are crossed. Below a threshold of impervious cover, additional paving may contribute only modestly to runoff generation; beyond it, the landscape’s hydrological response can shift abruptly, sharply elevating flood hazard downstream. Vegetation cover operates in the opposite direction, buffering risk, but its protective effect also shows threshold behavior, so incremental loss of canopy in already degraded areas may trigger disproportionate increases in exposure. These nonlinearities are exactly the kind of relationships that linear risk indices miss and that interpretable machine learning is uniquely positioned to reveal.

The study also emphasizes multi-factor coupling, the observation that risk drivers interact rather than act independently. Topography shapes where water collects, but the severity of inundation in any given valley depends on how much of the upstream surface is sealed by development and how much remains vegetated. A steep, forested headwater may shed water quickly yet harmlessly, while the same slope cleared and paved becomes a runoff engine. Understanding these couplings is essential for anticipating how future land-use change and urbanization, layered on top of intensifying rainfall, could redraw the basin’s heritage risk map in ways that static assessments would never foresee.

Beyond its specific findings for the Minjiang, the framework carries broader implications for heritage science and disaster resilience worldwide. River basins across monsoon Asia, and indeed across the globe, host historic buildings whose survival increasingly depends on anticipating climate-driven flood extremes. The study’s combination of physically grounded hydrological simulation, accurate yet interpretable machine learning, and rigorous spatial statistics offers a transferable template: it delivers basin-scale coverage, respects the nonlinear reality of flood mechanisms, and produces outputs that heritage managers can act on directly, from prioritizing estuarine and midstream clusters for protective works to targeting upstream vulnerability reduction. For the thousands of historic buildings lining the Minjiang’s waters, and for countless others in similar basins, the message is clear: effective protection begins with knowing precisely where risk lives, and why.

Subject of Research: Flood risk assessment of historic buildings in the Minjiang River Basin using hydrological simulation, machine learning and spatial analysis

Article Title: Spatial identification and assessment of flood risk for historic buildings in the Minjiang River Basin

Article References: Sun, L., Wang, S., Hu, W., Yun, X., Deng, Q., Zeng, S., Wang, M., & Yang, Z. (2026). Spatial identification and assessment of flood risk for historic buildings in the Minjiang River Basin. npj Heritage Science. https://doi.org/10.1038/s40494-026-03047-9

Image Credits: AI Generated

DOI: 10.1038/s40494-026-03047-9

Keywords: flood risk, historic buildings, heritage science, Minjiang River Basin, SCS-CN model, XGBoost, SHAP, spatial autocorrelation, vulnerability, machine learning, cultural heritage, disaster resilience

The technical achievement underlying the study is considerable. Boil water notices are issued and revoked in real time by the Mississippi State Department of Health and are not routinely archived in a form suitable for spatial analysis. The researchers obtained the historical records through a formal data request, but the dataset consisted of little more than street names and notice dates in plain text. To convert this textual archive into something a geographic information system could interrogate, the team built a multistep geospatial workflow combining Python programming, OpenStreetMap, the U.S. Census Bureau TIGER/Line road network, and ArcGIS Pro. Street addresses were standardized, matched to road segments, cross-validated against multiple map sources, and buffered to identify nearby buildings drawn from a 2022 statewide building-footprint dataset. The census blocks containing those buildings were then classified as notice-affected. In total, 97.44 percent of the records were successfully matched to road segments; the remaining 2.56 percent, for which no reliable spatial match could be established, were excluded.

That conversion mattered because of a persistent mismatch in environmental justice research: the notices describe exposure at the scale of a street, while most socioeconomic data from the American Community Survey are published only at the coarser census block-group level. To harmonize the two, the researchers employed building-footprint-based dasymetric mapping, a technique that redistributes block-group demographic values to individual census blocks in proportion to the number of building footprints each block contains. The approach assumes that buildings reasonably represent where people actually live within a neighborhood, producing finer and more spatially representative population estimates than conventional areal weighting. Using this method, the team compiled 230 variables spanning ten dimensions of social vulnerability, including age and sex, income, race, poverty, employment, marital status, health insurance coverage, relocation status, building age, and building value, all resolved to the census block.

With the exposure and demographic layers aligned, the analysis turned to the Getis-Ord Gi* statistic, a local indicator of spatial association designed to detect statistically significant concentrations of high or low values. Unlike global measures such as Moran’s I, which summarize clustering for an entire study area with a single number, the Gi* statistic pinpoints where significant hot spots and cold spots actually occur. The researchers input annual boil water notice frequency for each census block, constructed a spatial weight matrix using the ten nearest neighbors with row-standardized weights, and generated standardized z-scores and p-values for every block. Positive, significant z-scores marked hot spots of recurring advisories; negative ones marked cold spots. The same procedure was applied to population counts and to each demographic variable, producing parallel hot spot layers that could be compared directly.

The comparison itself relied on the Hot Spot Analysis Comparison tool in ArcGIS Pro, run with 9,999 permutations and fuzzy similarity weighting. Two complementary statistics quantified the spatial correspondence between notice hot spots and demographic hot spots. The Similarity Value, ranging from 0 to 1, measures how often corresponding blocks fall into the same significance category, while the Spatial Fuzzy Kappa, ranging from -1 to 1, controls for chance agreement and tolerates uncertainty in the exact correspondence of neighboring locations. Crucially, the researchers excluded pairs of blocks where both layers were statistically nonsignificant, ensuring the similarity measures were conditional on significant clusters rather than dominated by the many blocks where neither notices nor a given demographic group clustered. The output classified each block into categories such as Hot-to-Hot, meaning a demographic hot spot coinciding with a notice hot spot, or Cold-to-Hot, meaning a group concentrated in areas the advisories avoided.

The results reveal a clear hierarchy of vulnerability. Older adults aged sixty and older exhibited the strongest and most persistent spatial association with recurring notice hot spots of any group examined. In 2017, 12,203 older adults lived within Hot-to-Hot clusters; by the partial 2024 observation period, covering January through August, that figure had risen to 17,997. Children under five also showed recurring clustering, particularly in southern Jackson, with the greatest spatial extent in 2020 and the largest Hot-to-Hot population in 2017 at 6,978 individuals. But across the study period, the older population demonstrated greater temporal persistence and spatial overlap with notice hot spots, making them the most consistently associated age group in the analysis.

Economic and educational gradients followed a similar pattern. Residents living below the poverty line consistently represented the most affected income group, and their numbers within affected blocks increased over time, reaching their highest level in 2024 despite the dataset covering only eight months of that year. Hot-to-Hot clusters of poverty concentrations and notice hot spots recurred in southern and central Jackson, with the largest populations observed in 2018 and 2022. Individuals with a high school diploma, GED, or incomplete college education likewise showed recurring Hot-to-Hot clustering, while doctoral and professional degree holders were the least affected groups. High-income populations, concentrated primarily in northeastern Jackson, displayed a contrasting profile: their significant Hot-to-Hot clusters were intermittent, and Cold-to-Hot categories occurred more frequently in northern portions of the city, indicating concentrations of affluent residents in areas comparatively spared by the advisories.

Racial patterns demand careful interpretation, and the authors are explicit about the distinction between spatial coincidence and disproportionate exposure. Black residents constitute approximately 81.8 percent of Jackson’s population, so larger absolute numbers of Black residents within Hot-to-Hot areas partly reflect their overall representation in the city. Recurring Hot-to-Hot clusters between Black population hot spots and notice hot spots were concentrated in southern Jackson and persisted across multiple years, with the largest counts in 2017, 2023, and the partial 2024 period, while White population hot spots, concentrated in the northeast, showed greater temporal variability. Among smaller groups, multiracial residents represented the largest minority population within Hot-to-Hot areas in selected years, and Hispanic residents, largely captured by the Other Race Alone category, demonstrated the most temporally persistent clustering among minorities, recurring in most years except 2018. When the researchers normalized exposure by each group’s total population, Black residents’ proportional affected rates were not consistently the highest, underscoring that the findings indicate recurring coincidence rather than proven racial disparity.

The theoretical framing situates these patterns within environmental justice and urban political ecology. Environmental justice scholarship has long emphasized the unequal distribution of environmental burdens across racial and socioeconomic groups, while urban political ecology examines how political, economic, and institutional processes, including historical investment and disinvestment, shape uneven urban environments. From this perspective, recurring boil water notices are not isolated infrastructure failures but manifestations of broader socio-spatial inequality, the product of decades of underinvestment, aging infrastructure, population decline, a shrinking municipal revenue base, workforce shortages, and deferred maintenance. Jackson issued more than 750 boil water notices between 2016 and 2020 alone, and the widely publicized 2022 crisis, when failures at the O.B. Curtis Water Treatment Plant left more than 150,000 residents without reliable drinking water, was the culmination of a long-term process rather than a singular event.

The practical implications extend beyond Jackson. The authors argue that historical notice patterns could help utilities identify neighborhoods for infrastructure inspection, pipe-condition assessment, preventive maintenance, and capital improvements, shifting water service management from reactive crisis response toward proactive, geographically targeted planning. Where persistent notice clustering overlaps with vulnerable populations, physical interventions could be complemented by targeted risk communication, accessible emergency water distribution, and assistance obtaining alternative water. The framework is explicitly transferable: any city with archived advisory records could reconstruct its own geography of water hardship and identify the communities disproportionately affected. The authors caution that their statistics measure spatial agreement, not causation, and that future work incorporating pipe age, material, maintenance history, pressure conditions, and failure records would clarify the mechanisms producing these patterns. But as climate change, urbanization, and deferred infrastructure investment intensify water insecurity in cities worldwide, the study demonstrates that the question of who endures recurring water hardship has an answer, and that answer can be mapped, measured, and acted upon.

Subject of Research: A geospatial study of boil water notices in Jackson, Mississippi, shows recurring water service disruptions spatially coincide with demographic vulnerability.

Article Title: Spatiotemporal analytics of demographic vulnerability to urban water hardship

Article References: Malaker, T., & Meng, Q. (2026). Spatiotemporal analytics of demographic vulnerability to urban water hardship. Discover Cities, 3(1), Article 203. https://doi.org/10.1007/s44327-026-00382-1

Image Credits: AI Generated

DOI: 10.1007/s44327-026-00382-1

Keywords: urban water insecurity, environmental justice, geospatial analysis, boil water notices, Jackson Mississippi, hot spot analysis, dasymetric mapping, water infrastructure, Spatiotemporal, analytics, demographic, vulnerability

The research team, led by Rasha H. Ramadan of Egypt’s National Authority for Remote Sensing and Space Sciences and Mona S. Ramadan of United Arab Emirates University, set out to answer a deceptively simple question: which neighborhoods of Greater Cairo are most vulnerable, in a relative sense, to the constellation of urban conditions that make lung cancer more likely? To do so, they assembled twenty-nine spatial criteria organized into four domains: socioeconomic, residential, environmental, and physical. Each criterion layer was oriented so that larger standardized values represented greater relative vulnerability, reclassified onto an ordinal 1-to-8 scale, and then weighted using the Analytic Hierarchy Process, a structured mathematical technique for converting expert judgment into consistent numerical weights.

Technically, the framework relies on weighted linear combination, a cornerstone of multi-criteria decision analysis. Under this approach, every pixel of the city receives a vulnerability score computed as the sum of its reclassified criterion values multiplied by their assigned weights. The researchers ran the combination under four domain-priority scenarios, in which one domain at a time received the largest weight, and one equal-weight scenario in which all domains contributed equally. Every Analytic Hierarchy Process matrix met the prespecified consistency ratio threshold of less than 0.10, with a maximum observed value of 0.0216, indicating that the expert judgments encoded in the weights were internally coherent rather than arbitrary.

Because the weights themselves are analyst-defined assumptions, the team stress-tested them with 1,000 Monte Carlo perturbations, randomly shifting criterion weights by up to 15 percent and recomputing the maps. The result was striking stability: under equal-domain weighting, the rank order of criterion weights held with a mean Spearman correlation of 0.9912. In plain terms, the relative importance the framework assigns to each indicator barely budged even when the numbers were shaken. The authors are careful to note that this quantifies weight-rank stability, not spatial or outcome validation, a distinction that matters for how the maps should be read.

The resulting vulnerability surfaces show higher relative vulnerability concentrated in parts of western, northwestern, and southern Greater Cairo, with the exact pattern shifting depending on which domain was prioritized. The environmental domain alone classified 118.087 square kilometers of the city as low vulnerability, 626.825 square kilometers as medium, and 660.491 square kilometers as high. The physical domain, which includes terrain and built-form indicators derived from digital elevation models and satellite missions such as SRTM, produced 140.073, 635.396, and 629.935 square kilometers across the same three classes. These are not small margins; they cover hundreds of square kilometers of one of Africa’s largest urban agglomerations.

But the researchers did not stop at mapping. In a complementary hospital-based case-control analysis, they recruited 511 lung-cancer cases and 256 controls between 2022 and 2024 at the National Cancer Institute of Cairo University, a national oncology referral center drawing patients from governorates across Egypt and from diverse socioeconomic backgrounds. Controls consisted of patients with malignancies other than lung cancer, as well as visitors or accompanying persons with no known lung-cancer diagnosis. Residence codes were used strictly as nominal keys for an exact district-score lookup, ensuring that the geographic index could be joined to individual records without treating the GIS output as a causal estimate.

The individual-level findings are compelling. In a complete ten-predictor logistic model, smoking, proximity to pollution sources, and the residential-area vulnerability score carried the largest positive coefficients, meaning that these three factors were most strongly associated with lung-cancer case status in the sample. The logistic model achieved an area under the receiver-operating-characteristic curve of 0.82, with a 95 percent confidence interval of 0.78 to 0.86, indicating good discriminative ability. A machine-learning counterpart, an internally cross-validated radial-basis-function support vector machine, reached 79 percent accuracy, 81 percent sensitivity, and 76 percent specificity. Neither model, the authors emphasize, constitutes external validation of the GIS index; they provide complementary associations within a referral-hospital sample.

What makes the study unusual, and likely to spark debate, is its methodological candor. Composite GIS maps of disease vulnerability are often interpreted more strongly than their data support, and the authors explicitly warn against this. The GIS outputs, they write, identify relative vulnerability under explicit weighting assumptions; they do not estimate lung-cancer incidence or individual probability. The framework is most appropriately used for environmental surveillance, hypothesis generation, and prioritization of future population-based validation, not for clinical prediction or policy mandates based on a single map layer.

Still, the implications for sustainable health planning are considerable. Greater Cairo, home to more than twenty million people, faces chronic air-quality challenges, rapid informal urban growth, and stark socioeconomic gradients. By making the weighting assumptions transparent, testing them with Monte Carlo perturbation, and pairing the spatial index with individual-level correlates, the researchers have produced a template that other rapidly urbanizing regions could adapt. The study received no external funding and was approved by the Ethics Committee of the National Cancer Institute, Cairo University, with written informed consent obtained from all participants in accordance with the Declaration of Helsinki.

For now, the maps of Greater Cairo stand as a carefully hedged but powerful piece of evidence: a relative vulnerability atlas built from twenty-nine indicators, four domains, and thousands of perturbed weight combinations, pointing planners toward the neighborhoods where environmental and social conditions converge most sharply. Whether those neighborhoods see targeted interventions, from air-quality monitoring to screening outreach, will depend on the population-based validation studies the authors say must come next. But the framework itself, open access and fully documented, offers cities from Lagos to Jakarta a rigorous starting point for asking where vulnerability lives, and what to do about it.

Subject of Research: Environmental health and spatial epidemiology of lung cancer in Greater Cairo

Article Title: Urban environmental vulnerability to lung cancer in greater Cairo: a GIS-based multi-indicator assessment for sustainable health planning

Article References: Ramadan, R. H., Ramadan, M. S., Saleh, A. B., Elemam, A. A., Emam, M., & Khairy, N. (2026). Urban environmental vulnerability to lung cancer in greater Cairo: a GIS-based multi-indicator assessment for sustainable health planning. BMC Public Health. https://doi.org/10.1186/s12889-026-29985-4

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29985-4

Keywords: lung cancer, GIS, Greater Cairo, spatial vulnerability, public health, environmental health, multi-criteria decision analysis, case-control study, Urban, environmental, vulnerability, lung

Anillochlamys tropica is a Leptodirini beetle, a member of a tribe of highly specialized cave dwellers in the family Leiodidae. Like many subterranean lineages, it has evolved a life cycle with two larval stages before adulthood, an arrangement known as an intermediary cycle. The species is endemic to the southeastern Iberian Peninsula, and the adults used in the study were collected from Meravelles cave near Alzira in Valencia in February 2024. The animals were transported to the laboratory under cool, humid, and dark conditions to minimize stress, then randomly divided into two groups: one of 48 adults for thermal tolerance testing and one of 15 adults for breeding.

Subterranean ecosystems are among the most stable environments on Earth. Temperatures in caves barely fluctuate across daily, seasonal, or annual cycles, closely mirroring the mean annual surface temperature above. This stability, combined with permanent darkness and simplified ecological interactions, makes caves ideal natural laboratories for testing how species respond to warming. Yet despite extending beneath at least 19 percent of Earth’s land surface, subterranean habitats have been largely overlooked in conservation and climate change agendas. Recent work has begun to change that, revealing that subterranean beetles generally possess low upper thermal limits and a limited capacity for thermal acclimation compared with most surface-dwelling invertebrates.

What has been missing from nearly all of this research is any consideration of life stages other than adults. In surface-dwelling invertebrates, it is well established that early developmental stages are often more sensitive to environmental stressors, including temperature. But collecting larvae in caves is notoriously difficult, and rearing them under laboratory conditions presents significant logistical challenges. The Spanish team overcame these obstacles by breeding adults in Petri dishes lined with clay and moss, feeding them baker’s yeast, and monitoring eggs every two days. The first-instar larvae that hatched were then used for the thermal tolerance experiments, providing the first empirical estimate of thermal tolerance for the larval stage of any subterranean species.

The experimental design was straightforward but rigorous. Adults and larvae were exposed to constant temperatures of 17, 20, 23, 25, and 27.5 degrees Celsius for seven days, with relative humidity above 90 percent and in complete darkness. These values represent both natural and extreme conditions for subterranean Leptodirini, according to previous studies with Pyrenean relatives of the study species. Each treatment included 8 to 10 adults or 13 to 20 larvae, and the animals were monitored daily for survival while environmental conditions were continuously recorded with data loggers. Survival was analyzed using Kaplan-Meier curves and Cox models to test the effects of temperature, life cycle stage, and their interaction, and the upper thermal limit was estimated as the temperature causing 50 percent mortality after seven days, known as the LT50.

The results were striking. Adults maintained high survival, between 90 and 100 percent, at temperatures from 17 to 25 degrees Celsius for the full seven days, but all died within a single day at 27.5 degrees Celsius. Larvae told a very different story. While they survived well at 17 degrees Celsius, with 100 percent survival, mortality rose to 27 percent at 20 degrees Celsius, and exposure to 23 and 25 degrees Celsius caused progressive mortality reaching roughly 80 percent by day seven. No larvae survived beyond one day at 27.5 degrees Celsius. The estimated LT50 after seven days was 26.1 plus or minus 0.73 degrees Celsius for adults but only 21.47 plus or minus 0.53 degrees Celsius for larvae, a gap of nearly five degrees.

Statistical analysis confirmed that the difference was real and significant. Temperature, life cycle stage, and their interaction all significantly affected survival in the Cox model, with p-values below 0.001 for stage and temperature and 0.003 for the interaction. Post-hoc analyses showed that the mean probability of mortality did not differ between stages at 17 and 20 degrees Celsius, but larvae showed significantly higher mortality than adults at 23 and 25 degrees Celsius. In other words, the two life stages are equally comfortable in cool conditions, but as temperatures climb toward the upper end of the natural range, larvae begin to falter while adults remain largely unscathed.

Why would larvae be so much more heat-sensitive than adults? The researchers suggest several non-mutually-exclusive explanations. Larvae are smaller and invest heavily in growth, which raises their metabolic demands and may limit their ability to activate energetically costly thermal regulation mechanisms, such as the production of heat stress proteins. Their thinner cuticle compared with adults may also imply higher sensitivity to desiccation and heat stress. Such ontogenetic differences in thermal sensitivity are likely widespread among subterranean insects, and the study’s authors argue that assessing all life stages is essential when evaluating vulnerability to climate change.

The most alarming implication concerns the thermal safety margin, the difference between an organism’s upper thermal limit and its habitat temperature. The cave where Anillochlamys tropica lives currently sits at around 17 degrees Celsius, meaning that the larvae’s LT50 is only a few degrees above the temperature they experience today. Unlike most surface-dwelling species, subterranean beetles cannot avoid heat through migration because of their limited dispersal capacity. Nor can they synchronize development with seasonal climate patterns, as some surface larvae do to avoid the warmest periods of the year, because deep caves have minimal seasonal temperature fluctuation. Behavioral thermoregulation by microhabitat selection is equally infeasible in the homogeneous and stable cave environment. Projected temperature increases in the Mediterranean region, which is warming faster than many other areas, could further threaten the species’ persistence.

The study has limitations that the authors acknowledge. They focused solely on first-instar larvae, leaving the responses of eggs, second-instar larvae, and pupae unexplored, because logistical constraints made it impossible to obtain enough reproducing adults to rear sufficient numbers of later stages. The assays also measured only lethal effects, whereas sublethal impacts such as reduced growth or delayed development may occur at lower, non-lethal temperatures. Thermal sensitivity often operates hierarchically, so processes most sensitive to environmental change can limit overall fitness even when survival is possible over a wider range of temperatures. The study did not account for interactions with other key environmental stressors, such as ambient humidity, which is highly constant and near saturation in subterranean habitats but could influence survival and thermal tolerance. Notably, a recent report documented a decline in Anillochlamys tropica populations, suggested to be related to a drop in relative humidity, with records in the cave reaching as low as 75 percent, conditions that may no longer constitute a suitable refuge. Future research, the authors advocate, should investigate sublethal effects on fitness-related traits, examine all developmental stages, incorporate multiple interacting environmental variables, and integrate laboratory data with detailed cave microclimate modeling to better predict species persistence under climate change.

Subject of Research: Ontogeny shapes vulnerability to climate change underground: Larvae of a subterranean beetle are more sensitive to temperature increase than adults

Article Title: Ontogeny shapes vulnerability to climate change underground: Larvae of a subterranean beetle are more sensitive to temperature increase than adults

Article References: Colado, R., Sendra, A., Pallarés, S., Plaza-Buendía, J., Velasco, J., & Sánchez-Fernández, D. (2025). Ontogeny shapes vulnerability to climate change underground: Larvae of a subterranean beetle are more sensitive to temperature increase than adults. Subterranean Biology, 54, 23-33. https://doi.org/10.3897/subtbiol.54.174031

Image Credits: AI Generated

DOI: 10.3897/subtbiol.54.174031

Keywords: climate change, subterranean ecosystems, cave beetles, thermal tolerance, ontogeny, Anillochlamys tropica, Leptodirini, LT50, Iberian Peninsula, conservation, shapes, vulnerability

The stakes of this argument become visible in clinical training, where trainees encounter death, uncertainty, suffering, and systemic injustice at a stage when their professional identities are still forming. Research cited in the article shows how these encounters evoke vulnerability—stepping beyond one’s comfort zone into situations of risk and limited control. Trainees in end-of-life care, for example, are shocked by the physical realities of death while navigating a culture that treats dying as taboo and values emotional distance as the appropriate professional response. Junior doctors entering clinical practice report that uncertainty, responsibility, and fear of being judged incompetent make vulnerability inevitable. In Brazil, daily encounters with structural inequities leave trainees feeling powerless as they witness the suffering of marginalized populations. Yet trainees are implicitly expected to manage these experiences alone, through individual emotional restraint.

When emotionally charged experiences cannot be openly acknowledged, the authors argue, they may give rise to shame. Shame transforms emotional distress into negative judgments about the self, leading trainees to interpret vulnerability as evidence that they are inadequate or do not belong in medicine rather than as a natural response to complex clinical practice. Medical education can become an environment fruitful for shame, where hierarchical relationships, psychologically unsafe learning environments, perfectionism, and experiences of underrepresentation increase the likelihood and intensity of shame experiences. In this context, many trainees adopt what researchers call a cloak of competence, hiding their emotions and struggles to avoid being perceived as unprofessional. Instead of supporting reflection and growth, shame reinforces emotional suppression, identity dissonance, and isolation—shaping how trainees come to understand themselves as future physicians.

The consequences extend beyond individual distress. Trainees frequently hold the implicit assumption that being a good doctor requires suppressing emotions, a process that progressively reduces their awareness of their own feelings and those of others. When professionalism privileges emotional distance, it reflects perspectives largely rooted in Western societies of the Global North, where cultural norms shape how emotions are experienced, expressed, and discussed in everyday life. Trainees may struggle to reconcile their own emotions and values with expectations of detachment, creating identity dissonance—the distress of being unable to align one’s personal values with a detached professional role. Over time, these unresolved tensions can lead to isolation, burnout, cynicism, and a diminished sense of purpose. Innovative initiatives, such as music-based pedagogical activities, have successfully promoted emotional education in medical training by normalizing emotions within medical practice and strengthening trainees’ emotional awareness, but such interventions remain the exception rather than the norm.

To counter this dominant model, the authors adopt a decolonial perspective that questions whose values, ways of knowing, and ways of relating have been privileged in medical professionalism, and whose have been marginalized or excluded. From this standpoint, professionalism becomes a culturally situated and negotiated social contract that can be reimagined through multiple ways of knowing, relating, and becoming a physician. The article draws on three complementary perspectives—queer epistemologies, the South African philosophy of Ubuntu, and Freirean critical pedagogy—to broaden current understandings of professionalism, then turns to transformative learning theory to explain how vulnerability and emotional tension can become catalysts for learning.

The first perspective comes from research on queer identities in medical education, which illustrates how trainees act as care weavers, drawing on lived experiences of marginalization to transform personal vulnerability into a relational capacity for empathy and clinical insight. For these trainees, marginalization acts as a lifelong disorienting dilemma that prompts a transformative rejection of dehumanizing professional norms in favor of radical connection. Queer epistemologies hold that knowledge is produced through embodied and affective experience, and that the feelings generated by living athwart a norm—discomfort, disorientation, shame—disclose how that norm operates in ways not available from within it. The authors are careful not to treat marginalization as productive in a way that would justify its harms: their claim is not that exclusion is educative, but that knowledge generated under conditions of exclusion should be recognized as knowledge rather than discounted as personal experience. This capacity resonates with bell hooks’ understanding of the margin as more than a place of deprivation—a space of resistance, creativity, and transformation where new ways of knowing and being can emerge.

The second perspective, Ubuntu, is a South African relational ontology that understands personhood through the principle I am because we are. Human beings become who they are through their relationships with others, making identity an ongoing and collective process of becoming—one that extends to professional identity, positioning the process of becoming a physician as inseparable from relationships with patients, colleagues, communities, and society. In Ubuntu, emotions are not private inner states belonging to an isolated individual but relational forces that disclose, sustain, and repair the bonds through which people connect and care for one another. Compassion, empathy, kindness, and emotional presence allow physicians to recognize their shared humanity with patients and colleagues. Epistemologically, clinical truth and personhood are not objective facts extracted by an isolated observer but relational understandings co-constructed through communal interdependence—knowing a patient requires going beyond disease pathology to listen to their story within their communal context. Emotions also create the conditions for solidarity, positioning professionalism as a collective practice grounded in compassion, mutual responsibility, and shared humanity.

If Ubuntu locates professionalism in relationship, critical pedagogy locates it in structure. According to Freire’s critical pedagogy, in which dialogue and the reading of one’s social world are the conditions for critical consciousness, learners are encouraged to connect their emotional experiences to the historical, social, and institutional contexts that shape healthcare. Inspired by this tradition and drawing on the Brazilian context, researchers have proposed a Pedagogy of Connection that emerged from the close integration between medical education and the country’s public healthcare system. From the beginning of their training, Brazilian students participate in community and primary care settings, encountering the complexity of patients’ lives, the realities of social inequality, and the challenges of delivering equitable healthcare. These early patient encounters can evoke uncertainty, frustration, and a sense of powerlessness as learners recognize that many health problems are rooted in broader social and structural conditions. The Pedagogy of Connection responds by creating educational spaces where these experiences can be explored collectively through dialogue and critical reflection. Presence—an emotional, rational, and spiritual openness to patients’ suffering—allows emotions to inform decision-making, and feelings of frustration or moral outrage can make systemic problems visible, contributing to the development of critical consciousness and positioning the physician as an agent of social justice.

Together, these perspectives reframe professionalism as a process that develops across emotional, relational, and structural dimensions of medical education. Transformative learning theory provides the framework for understanding how emotionally significant experiences can challenge existing assumptions and become opportunities for learning. Transformative learning begins with a disorienting dilemma—an experience that challenges previously held assumptions and frames of reference, prompting critical reflection that engages both cognitive and affective dimensions. Clinical settings provide a unique context for this process, as trainees routinely encounter emotionally and ethically complex situations. Experiences such as first encounters with end-of-life care or reaching the limits of one’s own capabilities can leave trainees feeling overwhelmed, powerless, uncertain, and alone, unsettling their assumptions about care and their professional role. Rather than representing signs of incompetence, these emotional responses can become disorienting dilemmas that prompt critical reflection and shifts in perspective when learners are supported in acknowledging, making sense of, and expressing their emotions.

The authors propose reconnecting professionalism with emotions by recognizing vulnerability as a source of learning, relationships as central to professional identity, educational spaces as sites for dialogue and critical reflection, and transformative learning as a process of collective meaning-making. Crucially, they do not offer this as a new universal standard to replace the old one. They argue instead that emotional engagement is constitutive of professional identity formation, while the meanings, expressions, and legitimate forms of that engagement are shaped by the cultural, structural, and historical contexts in which physicians learn and practice. By positioning emotion as a legitimate way of knowing, feelings are recognized not as subjective distractions from clinical practice but as perceptual tools that deepen understanding. Relational professionalism calls for educational spaces where emotionally challenging experiences are explored collectively rather than carried individually—spaces of radical openness where vulnerability, uncertainty, and emotional tension are recognized as shared opportunities for reflection rather than personal shortcomings, enabling learners to cultivate professional identities grounded in connection, solidarity, and social responsibility.

Subject of Research: Decolonial reframing of emotions in medical professionalism and professional identity formation

Article Title: Can emotions be professional? A decolonial reframing of professional identity formation

Article References: Camargo Collet, S., Ribeiro, L. M. C., van der Goot, W. E., de Carvalho Filho, M. A., & Olmos-Vega, F. M. (2026). Can emotions be professional? A decolonial reframing of professional identity formation. Frontiers in Medicine, 13, Article 1952561. https://doi.org/10.3389/fmed.2026.1952561

Image Credits: AI Generated

DOI: 10.3389/fmed.2026.1952561

Keywords: medical professionalism, professional identity formation, emotions, decolonialism, medical education, Ubuntu, queer theory, critical pedagogy, transformative learning, vulnerability, health professions education, clinical training