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Operationalizing Local Ecological Knowledge for Aquatic Biodiversity Conservation: A Systematic Review and Management Framework.

Effective conservation and management of aquatic biodiversity is severely constrained by the absence of long-term ecological data in small-scale, tropical, and data-poor fisheries, where roughly one-quarter to one-third of freshwater fish species and 37.5% of elasmobranchs are threatened with extinction once Data Deficient species are accounted for. Conventional monitoring and stock-assessment tools are often financially and technically inaccessible in these systems, leaving managers without the evidence needed to prioritize conservation action or implement precautionary governance. Local Ecological Knowledge (LEK) is a largely underutilized resource for natural resource management that can provide temporal depth, spatial resolution, and species-specific ecological insights unavailable from scientific records. We conducted a systematic review and bibliometric synthesis of 60 peer-reviewed studies (1997-2025) applying LEK to assess fish conservation status, examining how, where, and through what methods this knowledge has been used. Our analysis identifies four complementary pathways through which LEK informs conservation management: reconstructing multi-decadal population changes, documenting spatial contraction and habitat loss, detecting extreme rarity and local extirpation, and characterizing intrinsic sensitivity to exploitation based on life-history traits. Despite growing methodological rigor, freshwater systems and African fisheries remain critically underrepresented, and formal integration of LEK into fisheries governance and biodiversity assessment remains the exception rather than the rule. We propose a practical three-stage framework to operationalize LEK within existing management and conservation systems. Recognizing fishing communities as legitimate co-producers of ecological knowledge is both scientifically necessary and an equity imperative for achieving global biodiversity commitments under the Kunming-Montreal Global Biodiversity Framework.

Biodiversity

Redox Rewiring in Nicotine-Driven Gastric Carcinogenesis: Uncovering ROS-Dependent Oncogenic Circuits.

SIGNIFICANCE: Nicotine from tobacco products, secondhand smoke, and emerging delivery systems remains a major but underappreciated driver of gastric carcinogenesis (GC). Although reactive oxygen species (ROS) have long been implicated in tumor biology, current models incompletely explain how chronic nicotine selectively reprograms gastric epithelial signaling. This review advances the concept of redox rewiring, whereby nicotine establishes a persistent oxidative state that orchestrates multiple oncogenic programs via spatially compartmentalized NOX signaling. RECENT ADVANCES: We synthesize evidence for a unified model wherein nicotine activates nAChR/β-AR signaling, Ca2+ influx, PKC, and compartmentalized NOX-derived ROS to generate distinct oncogenic outputs. Beyond the established NOX/ROS/NF-κB/MAPK-driven IL-8 and MMP-9 axes, we integrate emerging evidence into three interconnected modules governing EMT/metastasis (ABL1/STAT3/COX-2/periostin), survival/chemoresistance (ERK/GLI1/Bcl-2), and invasion/immune evasion (miR-21/PDCD4). Collectively, these circuits suggest that ROS function not merely as damaging byproducts but as spatially organized signaling mediators dictating tumor behavior. CRITICAL ISSUES: A major challenge is distinguishing established mechanisms from incompletely validated models. The three proposed axes are testable hypotheses requiring experimental validation. Most data derive from in vitro studies with nonphysiologic nicotine concentrations, and artifacts from nonspecific ROS probes are common. Compensatory pathway activation and multi-target effects of natural products remain underexplored. FUTURE DIRECTIONS: We outline a precision-redox oncology roadmap linking pathway-specific biomarkers, mechanistically matched natural products, and biomarker-enriched trials. Priorities include genetic validation of the three axes, time-resolved ROS imaging, and pulsed natural product regimens. By reframing nicotine-driven GC as adaptive redox network remodeling, this review provides a framework for prevention, stratification, and next-generation therapy. Antioxid. Redox Signal. 00, 000-000.

gastric cancer

Getting to the Core of the Matter-Assessing the Role of Replication in Metabarcoding-Based sedaDNA.

Replication is central to most experimental and sampling designs, increasing inferential power and capturing fine-scale data heterogeneity. However, its importance remains poorly evaluated in some ecological and evolutionary settings. This is the case of metabarcoding studies using DNA recovered from sedimentary archives, in which biological signals integrate ecological information through depositional and burial processes, yet are commonly inferred from a single sediment core per site. Here, we evaluated the effect of different types of replication using sedimentary DNA metabarcoding data from two genetic markers (mitochondrial COI and nuclear 18S) using a nested sampling design. The design included three intertidal sites, three spatially separated sediment cores per site (biological replicates), two sediment horizons per core, and eight PCR (technical) replicates per sediment sample. Variance partitioning showed that site identity and sediment age group together explained > 70% of the variation in beta diversity, indicating that among-site spatial and stratigraphic differences were the dominant drivers of community composition. PERMANOVA likewise identified non-significant effects of biological replication. Among PCR replicates from the same sediment sample, richness varied substantially, whereas Shannon diversity was more consistent. Despite this variability, differences in community composition among technical replicates remained smaller than those associated with biological replication or site identity, indicating a limited influence on broader ecological patterns. Community composition was highly similar among replicate cores within sites, consistent with stratigraphic coherence. These results indicate limited within-site heterogeneity and suggest that, under stratigraphically coherent conditions, increasing biological replication may provide little additional information, whereas enhancing technical replication and stratigraphic resolution can improve ecological inference from sedimentary DNA metabarcoding datasets.

DNA Barcoding, Taxonomic

A system-level metastable model of cancer evolution: integrating replication stress, cell cycle deregulation and chromosomal instability.

INTRODUCTION: Cancer cell proliferation occurs within the context of persistent genomic instability. In this review, we propose the RS-CCD-CIN axis as a systems-level framework in which replication stress (RS), cell cycle deregulation (CCD) and chromosomal instability (CIN) form an interdependent triad that shapes tumour evolution. This axis represents a constrained metastable state in which genomic instability is tolerated and buffered. The objective of this review is to synthesize the current understanding of how the RS-CCD-CIN axis contributes to tumour heterogeneity, adaptability and therapy response. DISCUSSION: Evidence indicates that RS, CCD and CIN operate as a dynamic, interconnected network rather than as independent processes. Replication stress induces DNA damage and mutagenesis, while partial checkpoint disruption permits cells with unresolved lesions to proliferate. Chromosomal instability generates both structural and numerical alterations, contributing to intratumoural heterogeneity. Together, these processes facilitate adaptation to environmental and therapeutic pressures. Extrachromosomal DNA, micronuclei formation and cytosolic DNA signalling, including the cGAS-STING pathway, connect genomic instability to adaptive responses and immune modulation. Single-cell and spatial profiling reveal temporal and spatial variability in RS, CCD and CIN states, highlighting the limitations of static biomarkers. Therapeutically, targeting individual components often yields limited durability, whereas approaches that simultaneously perturb multiple aspects of the RS-CCD-CIN axis may improve clinical outcomes. CONCLUSIONS: This review highlights the RS-CCD-CIN axis as a fragile and metastable architecture that supports cancer evolution, while also being susceptible to collapse. A deeper understanding of this interconnected framework may inform the development of therapeutic strategies and enhance the management of resistance.

Humans

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5​ concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon

Experimental evolution reveals contrasting adaptive landscapes in lab and field environments.

Experimental evolution is widely used to infer microbial responses to environmental change, yet most laboratory studies impose constant, well-mixed conditions that differ fundamentally from fluctuating, spatially structured field environments. We compared genomic evolution in the leaf litter-associated bacterium Curtobacterium strain MMLR14_002 under control and warming treatments in laboratory culture and in a complementary field experiment. Laboratory-derived isolates accumulated more mutations per genome and exhibited stronger locus-level parallelism, with mutations recurring in a small number of coding loci. Field-derived isolates accumulated fewer mutations per genome, and these mutations rarely occurred in the same coding loci across replicate populations. Instead, field isolates exhibited a higher proportion of intergenic mutations, with mutations recurring in the same intergenic regions across independent field deployments. When coding mutations were detected in the field, they were distributed across functionally diffuse targets and more often involved metabolic pathways than the core cellular processes repeatedly targeted during laboratory evolution. Warming itself did not consistently influence mutation accumulation or the genomic distribution of mutations; instead, laboratory and field contexts primarily shaped the accumulation, targets, and repeatability of genomic change. These results suggest that laboratory thermal evolution identifies adaptive routes favored under sustained selection but may overestimate coding-level parallelism under heterogeneous field conditions. Bridging laboratory and field evolution will likely require experimental designs that incorporate temporal variability and spatial heterogeneity characteristic of natural systems.IMPORTANCEA central goal of experimental evolution is to infer how microbes evolve in nature from laboratory studies. Here, we evaluate this assumption by comparing genomic evolution of a leaf litter-associated Curtobacterium strain in laboratory and field warming experiments to identify broad patterns rather than isolate the contribution of any single environmental factor. We find that the strong parallelism at coding loci observed under laboratory conditions is reduced in the field, while mutations recurring in the same intergenic regions across field deployments suggest that parallel evolution in nature may more often involve regulatory noncoding regions rather than coding targets. These results show that environmental context reshapes adaptive landscapes and may limit the parallelism of coding-level genomic responses inferred from homogeneous laboratory conditions.

experimental evolution

Extended Long-Term Effects of Cognitive and Aerobic Training on Cognitive Function in Patients With Stress-Related Exhaustion Disorder: A 4.5-Year Follow-Up of a Randomized Controlled Trial.

Stress-related conditions like clinical burnout and exhaustion disorder (ED) are associated with enduring cognitive problems. We have previously demonstrated that the addition of computerised cognitive training (CCT) and aerobic training (AT) to a multimodal rehabilitation programme (MMR) yielded greater improvements in cognitive function compared to MMR alone in patients with ED. These effects were maintained at the 1-year follow-up for CCT, but not for AT. Building on these findings, the present study examined the extended long-term effects of CCT and AT on cognitive function, psychological health, and work ability, 4.5 years after the interventions. Participants were recruited from a stress-rehabilitation clinic and 56 of the initial 132 participants returned for the 4.5-year follow-up. Assessments were conducted before (T1), immediately after (T2), 1-year after (T3) and 4.5-years after (T4) the interventions. Mixed model analyses assessed changes in the intervention groups relative to the control group from T1 to T4, with follow-up comparisons examining within-group stability of outcomes between T3 to T4. The primary outcome was cognitive performance on a global cognitive score. Secondary outcomes included domain-specific cognitive functioning, self-reported cognitive function, psychological health (burnout, depression, anxiety, and fatigue), and work ability. The analysis revealed sustained long-term effects on the global cognitive score, a trained updating task and episodic memory in the CCT group, with stable performance between one- and 4.5-year follow-up. The addition of AT did not yield any extended long-term effects on cognitive performance. Both groups showed extended long-term improvements in self-reported memory problems, although findings were mixed. Extended long-term improvements were observed on burnout for both groups, with additional effects on anxiety and work ability in the AT group. Notably, these effects were not present at the 1-year follow-up and are more plausibly explained by selective attrition rather than a delayed intervention effect. In conclusion, the result indicates that cognitive interventions such as CCT can have lasting positive effects on cognitive function in patients with ED, whereas the long-term psychological effects should be interpreted with caution. TRIAL REGISTRATION: ClinicalTrials.gov: NCT0073772.

Adult

Breastfeeding Outcomes After Radiofrequency Ablation and Surgical Excision of Fibroadenomas Compared to Natural History: A Retrospective Cohort Study.

BACKGROUND: Fibroadenomas, common benign breast tumors in women of reproductive age, are increasingly managed with minimally invasive radiofrequency ablation (RFA) or surgical excision. However, their impact on breastfeeding outcomes remains underexplored. We aimed to assess breastfeeding ability and breast tissue changes in women treated with RFA or surgery compared to those with untreated fibroadenomas. METHODS: In this retrospective cohort study, we evaluated 153 women with biopsy-confirmed fibroadenomas across five groups: RFA with prior breastfeeding (RFA-PreBF; n = 26), RFA with posttreatment breastfeeding (RFA-PostBF; n = 22), surgical excision with prior breastfeeding (Surgical-PreBF; n = 30), surgical excision with posttreatment breastfeeding (Surgical-PostBF; n = 20), and noninterventional with breastfeeding (Observation-BF; n = 55). Breastfeeding ability was assessed using a 5-point scale, and breast tissue changes were evaluated via ultrasound at 18 months, and all breastfeeding attempts occurred at a minimum of 12 months postprocedure. Fisher's exact test compared complete lactation failure rates, and a power analysis validated the study design (Fig. 1). FINDINGS: The combined RFA group (n = 48) had a higher complete lactation failure rate (14.6%) than the Observation-BF group (3.6%; Fisher's exact test, p = 0.045). Similarly, the combined surgical group (n = 50) had a higher complete lactation failure rate (16.0%) than the Observation-BF group (p = 0.034). When pooled, the combined intervention group (n = 98) showed a complete lactation failure rate of 15.3% versus 3.6% in the Observation-BF group. Residual tissue correlated with lactation impairment in the RFA group (Spearman's &#x3c1;, p < 0.05). Ultrasound showed no tumor recurrence, with cystic changes in some cases not linked to breastfeeding impairment. Power analysis confirmed 80% power to detect a medium effect size (f = 0.25, Fig. 1), supporting the study's robustness.7 RFA-PreBF (n = 26), RFA-PostBF (n = 22), Surgical-PreBF (n = 30), Surgical-PostBF (n = 20), and Observation-BF (n = 55). Breastfeeding ability was assessed using a 5-point scale, and breast tissue changes were evaluated via ultrasound at 18 months. Fisher's exact test compared complete lactation failure rates, and a power analysis validated the study design (Fig. 1).[Figure: see text]Interpretation:RFA and surgical excision are effective for fibroadenoma management but increase the risk of complete lactation failure compared to untreated fibroadenomas. Careful patient selection, precise procedural techniques, and vigilant posttreatment monitoring are essential to optimize breastfeeding outcomes, particularly for women planning future pregnancies.

Humans

A black soybean yoghurt fermented with a reusable probiotic cellulose gel: beneficial effects and metabolic characteristics.

The demand for plant-based yoghurts is continuously increasing. However, achieving stable physicochemical properties and acceptable flavor of the plant-based yoghurts remains challenging. In our previous work, we encapsulated Lactiplantibacillus plantarum (L. plantarum) LCC-605 biofilm into bacterial cellulose (BC), obtaining a LP605@BC gel. LP605@BC gel exhibited excellent harsh-environment resistance abilities and storage stability, and is very suitable as a starter culture. In this work, we used LP605@BC as a starter culture to prepare the fermented plant-based yoghurt (e.g., black soybean yoghurt, BSY-LP605@BC). After fermentation, the inverted nonflowing yoghurt was formed due to the strong interaction between protein and exopolysaccharide (EPS) produced by LCC-605 during fermentation. In addition, the water holding capacity (67.2%) of BSY-LP605@BC was also greatly improved. The viable bacterial counts in BSY-LP605@BC reached 11.2 log CFU/mL after 21&#xa0;days of storage. BSY-LP605@BC showed increased antioxidant, cholesterol-lowering abilities, and hypoglycemic potential compared with the unfermented black soybean milk. Interestingly, LP605@BC could be reused at least 5 times, demonstrating excellent sustainability. Significant metabolomic differences between BSY-LP605@BC and the black soybean milk were observed via untargeted metabolomic analysis, further proving the beneficial effects of BSY-LP605@BC. Overall, our work developed an effective reusable starter culture for preparing the plant-based yoghurt in a sustainable manner, providing a new design direction and form of starter culture.

Yogurt

Evaluating the Efficacy of Electronic Screening, Brief Intervention, and Referral to Treatment (e-SBIRT) for Gambling: An Online Pilot Randomised Trial.

OBJECTIVES: To investigate the efficacy of electronic screening, brief intervention, and referral to treatment (e-SBIRT) at improving gambling outcomes and increasing help-seeking. METHODS: We conducted a two-arm, randomised online pilot trial (n&#x2009;=&#x2009;83) comparing an e-SBIRT intervention with an active control over 12 weeks. The brief intervention was informed by motivational interviewing and incorporated personalised normative feedback, information provision, and relapse-prevention components. Eligible participants were aged 18 or older, resided in the UK and had scores indicating at least moderate severity gambling. RESULTS: Participants (54 [65.1%] male; mean [SD] age&#x2009;=&#x2009;40.58 [12.75] years, mean [SD] PGSI&#x2009;=&#x2009;7.16 [5.58]) in the e-SBIRT and control conditions showed improvements in gambling harms (p&#x2009;=&#x2009;0.033) and perceived ability to control gambling (p&#x2009;=&#x2009;0.029). No significant effects of condition assignment or condition x time interactions were observed. However, exploratory analyses of individual model coefficients suggested greater improvement in perceived ability to control gambling among participants receiving e-SBIRT at 12 weeks (p&#x2009;=&#x2009;0.043). Exploratory analyses also suggested higher rates of help-seeking at 12-week follow-up among participants receiving e-SBIRT. CONCLUSION: Overall, e-SBIRT did not demonstrate clear advantages over assessment and information provision alone. Further research should prioritise refining intervention components and evaluating SBIRT approaches in settings that better reflect its opportunistic delivery model.

Humans

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

Humans

Multi&#x2011;omics approaches to decipher the molecular mechanisms of exercise&#x2011;mediated bone protection: From mechanistic insights to personalized exercise prescription (Review).

The global burden of bone metabolic disorders necessitates a shift from generic exercise recommendations toward personalized prescription strategies. Exercise confers skeletal protection through mechanotransduction, yet the underlying molecular networks remain incompletely understood. Multi&#x2011;omics technologies, including transcriptomics, proteomics, metabolomics and single&#x2011;cell spatial approaches, have revolutionized the capacity to decode exercise&#x2011;mediated bone adaptation at the systems level. The present review synthesizes current single&#x2011;omics landscapes and integrative multi&#x2011;omics analyses that elucidate the core regulatory networks, mechanobiological coupling mechanisms and multiorgan crosstalk that are implicated in the bone response to mechanical loading. Translational applications across clinical scenarios such as osteoporosis, osteoarthritis and disuse bone loss are evaluated, and the technical, analytical and translational challenges limiting clinical implementation are addressed. Finally, the present review provides a framework for translating multi&#x2011;omics molecular signatures into personalized exercise prescriptions for optimized skeletal health.

Humans

Executive function in alcohol use disorder with low psychiatric comorbidity: Comparison with a non-clinical sample and predictive value for treatment outcome.

BACKGROUND: Executive functions (EF) encompass abilities such as planning, decision-making, and inhibitory control, critical for learning, establishing and maintaining behavioral change. The association between alcohol use disorder (AUD) and impairments in EF are well established. However, prior research is dominated by studies on convenience samples including individuals with severe AUD with high levels of psychiatric comorbidity, which limits generalizability. The present study therefore aimed to investigate the degree of impairment and predictive ability of EF, on alcohol consumption, among individuals with moderate AUD with low levels of psychiatric comorbidity. METHODS: Adults with moderate AUD (n&#x2009;=&#x2009;147) were recruited at three specialized addiction outpatient clinics in Stockholm, to a randomized controlled trial investigating the efficacy of two psychological treatments. Participants underwent neuropsychological testing before treatment. Eight tests from the CANTAB&#xae; battery were administered at baseline, assessing mental flexibility, sustained attention, visuospatial working memory, response inhibition, and delay discounting. Assessments of alcohol use and related symptoms were conducted at baseline, the 12- and 26-weeks follow-up. A non-clinical reference sample (n&#x2009;=&#x2009;72) completed corresponding CANTAB&#xae; tests. The two groups were compared regarding EF using descriptive statistics and t-tests, and the predictive value of EF for reduction in alcohol consumption, was investigated using multiple regression models. RESULTS: Individuals with AUD did not perform worse on any of the tests on executive function (CANTAB&#xae;) as compared to the non-clinical reference sample. Measures of EF were not significant predictors for reduction in alcohol use for the 12-week, or the 26-week follow-up. CONCLUSIONS: EFs were not impaired and were not a clinically relevant predictor of treatment outcomes in this population with AUD. Future research on EF as a predictor in AUD treatment, needs to corroborate the present findings, and include other populations, e.g., with different socio-economic backgrounds and by including other methodologies for measuring EF.

Humans

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000&#xa0;cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT&#xa0;>&#xa0;2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared

Morphology-Encoded Colorimetric Hydrogen Sensing Using Embedded Reactive Pd Absorbers in Fabry-Perot Cavities.

Chemical reactions offer a powerful strategy for generating visible optical responses through localized changes in absorption, dielectric environment, and interfacial wetting. A palladium (Pd)-embedded Fabry-Perot cavity is introduced as a reaction-active optical platform in which structural color is governed by intracavity absorption coupled with reaction-induced dielectric perturbation. Positioning Pd within the dielectric spacer creates a spatially controllable reactive absorber whose vertical location relative to the standing-wave field dictates wavelength-selective absorption within the cavity. The morphology of the embedded Pd layer provides an additional design parameter by modulating both optical loss and interfacial wetting. Under hydrogen exposure in the presence of oxygen, catalytic water formation at the Pd/polymer interface generates localized dielectric heterogeneity and interfacial water droplets, thereby perturbing the optical path length and amplifying the visible response. As a result, the cavity exhibits pronounced, morphology-dependent color transitions that are inaccessible through dielectric-layer engineering or Pd/PdH refractive-index changes alone, enabling direct visual hydrogen sensing under ambient light, as well as flexible optical devices capable of large-area patterning. These findings establish a design framework for reaction-active optical cavities that translate localized chemistry into a colorimetric hydrogen sensing mechanism.

Fabry&#x2013;Perot resonator

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics