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PubMed2026

AI-driven snapshot hyperspectral imaging for on-line sorting systems in food industry: From real-time sensing to intelligent decision-making.

High-throughput food sorting requires rapid, non-destructive detection of external defects, foreign materials, and internal quality attributes in heterogeneous food matrices. Conventional scanning hyperspectral imaging may suffer from motion-induced spatial-spectral mismatches, whereas snapshot hyperspectral imaging (S-HSI) captures spectral images within a single integration time. However, its advantage is limited by trade-offs in resolution, signal-to-noise ratio (SNR), reconstruction uncertainty, and calibration stability, which are further amplified by variable tissue structure, surface reflection, moisture, and fat distribution in foods. This review critically examines artificial intelligence (AI)-driven S-HSI for on-line food sorting within a sensing-representation-decision-execution framework. Compact architectures are compared according to their physical constraints, food-sorting suitability, and ability to support mapping between spectral responses and physicochemical quality attributes. AI strategies are reviewed for spectral reconstruction, image restoration, spatial-spectral representation, band selection, uncertainty-aware decision-making, and edge implementation. AI can partially compensate for snapshot-specific limitations, but current evidence remains largely limited to laboratory or prototype studies. Future work should link system performance to food safety and quality outcomes by reporting throughput, decision latency, calibration drift, missed-detection risk, false-rejection cost, and closed-loop sorting success.

Hyperspectral Imaging↗

PubMed2026

Impact of kangaroo care on circadian rhythm, growth, physiological stability in premature infants, and cortisol and melatonin levels in maternal breast milk: A randomized controlled trial.

PURPOSE: This study aimed to examine the effects of regular kangaroo care (KC) on sleep-wake cycles, growth, physiological stability, and maternal breast milk cortisol and melatonin levels in premature infants. DESIGN: This study was a parallel group, single-blind, pre-test-post-test, randomised controlled trial (RCT). METHODS: This randomized controlled study was conducted in a neonatal intensive care unit (NICU) in Türkiye between September 2024 and September 2025 Thirty-six premature infants were randomized to intervention (n = 28) or control (n = 28). Infants in the intervention group received KC for three consecutive days, twice daily (10:00 a.m. and 10:00 p.m.) for 60 min per session. Data were collected using the Infant Information Form, Physiological Parameters Monitoring Chart, and Premature Infant Sleep-Wake Cycles Tracking Chart. Sleep-wake cycles were monitored using a Bispectral Index device. Breast milk cortisol and melatonin levels were measured at baseline and on day three using the competitive ELISA method. The study was registered at ClinicalTrials.gov (NCT06589349). RESULTS: Regular KC had a statistically significant effect on BIS values, heart rate, respiratory rate, oxygen saturation, and body temperature (p < 0.05). No statistically significant effects were observed on infant body weight or on maternal breast milk cortisol and melatonin levels (p > 0.05). CONCLUSION: The findings indicate that regular KC is associated with improved regulation of the sleep-wake cycle and enhanced physiological stability in premature infants. No significant changes were observed in maternal breast milk cortisol or melatonin levels following KC.

Humans↗

PubMed2026

Formation of environmental persistent free radicals in soil of ammunition demolition site: Roles of 2,4,6-trinitrotoluene and heavy metals.

Environmental Persistent Free Radicals (EPFRs) are a particular type of contaminant present in soil. This study investigated the formation process, environmental behavior, and main influencing variables of EPFRs in soils contaminated with heavy metals and 2,4,6-trinitrotoluene (TNT) from an ammunition demolition site. The results showed that the concentration of total organic carbon (TOC) in the soil was negatively correlated with EPFRs (r = -0.29). In contrast, the content of TNT and copper was significantly positively correlated with EPFRs (r = 0.90 and 0.78, respectively), indicating that TNT acts as a precursor macromolecule in the formation of EPFRs in this type of contaminated soil. Transition metal Cu may be an essential carrier in EPFR production. In order to explore the possible formation mechanism of EPFRs, a simulation experiment was carried out under different temperature and light conditions. The results showed that the photolysis process of TNT was impacted by external energy sources such as heat and light. TNT was firstly adsorbed onto the surface of a transition metal (Cu), and then EPFRs were formed through further electron transfer. This is the first study to detect significant levels of EPFRs in the soil at ammunition demolition sites.

Trinitrotoluene↗

PubMed2026

Reference genome of the Californian trapdoor spider Aptostichus stephencolberti Bond 2008 (Araneae: Mygalomorphae: Euctenizidae).

We present a reference genome assembly for the trapdoor spider Aptostichus stephencolberti. This species, described in 2008, is endemic to the highly fragmented coastal dune habitats of Northern California from Monterey to the San Francisco Bay Area. Trapdoor spiders are ideal taxa for landscape scale genomic studies owing to their extreme site fidelity and limited dispersal capabilities; these same characteristics make them prone to extinction. Genomic studies of species like A. stephencolberti can reveal novel areas of endemism and high conservation value that may not be evident in species with wider ranges and greater dispersal capabilities. As part of the California Conservation Genomics Project, we constructed the A. stephencolberti reference genome from high quality long-read sequences, scaffolded with proximity ligation Omni-C data. The primary assembly comprises 551 scaffolds spanning 3.63 Gbp, a scaffold N50 of 62.2 Mbp and BUSCO completeness of 95.6%. We estimate 52 chromosomes yet find no (TTAGG)n telomer repeats. Expanding the telomeric repeat search finds an ancestral loss of the repeat from all spiders. Automated annotation using the NCBI refseq pipeline and RNAseq data from whole adults finds 14,067 genes with a BUSCO annotation completeness of 95.56%. Repeat annotation identified 77% of the genome to be interspersed repeats. This resource, the first for family Euctenizidae will facilitate future study and resulting conservation actions of A. stephencolberti and other Aptostichus sp. populations associated with the rapidly changing California coastal dune ecosystem.

Aptostichus stephencolberti↗

PubMed2026

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals↗

PubMed2026

Three-dimensional porous nano-hydroxyapatite@gelatin composite as efficient adsorbent for uranyl ion removal from low-level radioactive wastewater.

The contamination of water resources by uranyl (UO22+) ions poses significant environmental and health risks, requiring the development of efficient and sustainable remediation strategies. Adsorption-based techniques have emerged as promising approaches in the field of UO22+ removal, but the design of cost-effective, high-capacity, and environmentally friendly adsorbents remains challenging. In this study, a three-dimensional porous nano-hydroxyapatite@gelatin (nHAP@Ge) composite was synthesized through glutaraldehyde cross-linking, combining the structural stability of Ge with the high uranium affinity of nHAP. The optimized nHAP@Ge, with a nHAP:Ge mass ratio of 1:0.5, exhibited exceptional UO22+ removal efficiency (97 %), along with high adsorption capacity (364.03 mg/g). Systematic characterizations using scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier transform infrared (FT-IR) spectroscopy, and X-ray photoelectron spectroscopy (XPS) methods revealed that the porous structure and surface functional groups (-OH, Ca2+, and PO43-) of the material synergistically contributed to binding UO22+ species. Furthermore, the incorporation of nHAP into the Ge framework resulted in enhanced thermal stability while significantly improving the UO22+ adsorption performance. This work presents a scalable, eco-friendly, and recyclable strategy for the effective treatment of uranium-contaminated water, with potential applications in nuclear wastewater treatment and environmental remediation.

Adsorption↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Psychometric Evaluation of the Breast Inflammatory Symptom Severity Index Versions 2 and 3 Among Lactating Women.

OBJECTIVE: To evaluate the psychometric properties of Versions 2 and 3 of the Breast Inflammatory Symptom Severity Index (BISSI). DESIGN: Secondary data analysis of clinical trial data. SETTING: Private physiotherapy practices, a public tertiary hospital, and a community in Melbourne, Australia. PARTICIPANTS: Women more than 7 days after birth with inflammatory conditions of the lactating breast (N = 43). METHODS: We performed confirmatory factor analysis of the BISSI Version 2 to examine item loading, which informed development of the BISSI Version 3 (V3). We assessed convergent validity by comparing total BISSI V3 scores with human milk sodium to potassium ratio (Na+:K+) at Trial Days 1, 3, and 10 using Bland-Altman plots. We compared item-level scores for size of affected area with objective receiver operating characteristic curve analysis to assess discriminant validity for symptom severity and Cronbach's alpha for internal reliability. RESULTS: After confirmatory factor analysis, we removed two items, resulting in a six-item BISSI V3. All retained items demonstrated comparable loading on the overall scale. Limits of agreement for total BISSI V3 scores and item-level scores for size of affected area were acceptable at all time points, with more than 90% of observations falling within 2 standard deviations of the mean difference, supporting convergent validity. Discriminant validity of the BISSI V3 was supported. We found high internal reliability at both time points CONCLUSION: Our findings provide evidence for the validity and reliability of the BISSI V3 and support its continued development and for clinical use of the BISSI V3 and human milk Na+:K+ analysis to enhance management of inflammatory conditions of the lactating breast.

breastfeeding↗

PubMed2026

Efficacy and Safety of GLP-1 Receptor Agonists for the Management of Antipsychotic-Induced Weight Gain.

OBJECTIVE: The objective of this systematic review and meta-analysis was to compare the efficacy and safety of glucagon-like peptide-1 (GLP-1) receptor agonists for the management of antipsychotic-induced weight gain. DATA SOURCES: A systematic review was conducted following PRISMA methodology through July 2025 that evaluated the efficacy and safety of GLP-1 agonists for the management of antipsychotic-induced weight gain. STUDY SELECTION AND DATA EXTRACTION: Efficacy endpoints were change in body weight (kg), change in body mass index (BMI) (kg/m2), and change in HbA1c (%). The safety endpoint was gastrointestinal (GI) adverse effects. A P-value of 0.05 was considered statistically significant, and heterogeneity was reported as I2. DATA SYNTHESIS: Six studies were included in this systematic review, of which 4 trials were included in the meta-analysis. The difference found between GLP-1 agonists and placebo was a change in weight of -5.85 kg (P = 0.0622, 95% CI = -9.72 to -1.97), a change in BMI of -2.11 kg/m2 (P = 0.7692, 95% CI = -5.51 to 1.29), and a change in HbA1c of -1.58 (P = 0.6659, 95% CI = -4.75 to 1.58). The overall risk ratio for a patient to experience a GI-related adverse effect when taking a GLP-1 agonist compared to placebo was 1.83 (95% CI = 1.42 to 2.37). RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE: While the efficacy endpoints did not reach significance, this meta-analysis shows that select GLP-1 receptor agonists may be used to promote weight loss in patients taking antipsychotics. Controlling antipsychotic-induced weight gain helps patients remain adherent to therapeutic doses of their antipsychotic medications. CONCLUSION: The use of certain GLP-1 agonists may be considered to help promote weight loss in patients experiencing antipsychotic-induced weight gain.

Humans↗

PubMed2026

Assessing the public health impact of routinely collected electronic healthcare record data in NICE guidelines: A systematic review of CPRD research.

OBJECTIVES: Evidence used in NICE guidance has traditionally prioritised randomised controlled trials, but increasing availability of electronic health record (EHR) data has expanded opportunities for real-world evidence. The Clinical Practice Research Datalink (CPRD) is a commonly used UK primary care EHR resource, yet the extent to which CPRD studies have informed NICE guidelines in the past decade is unclear. STUDY DESIGN: The systematic review was conducted in accordance with PRISMA guidelines. METHODS: We conducted a systematic review of CPRD studies in PubMed, MEDLINE, and Embase published between 04/16-09/25. For each eligible CPRD study, targeted searches of NICE guidelines were performed to identify explicit citations in NICE guidelines. Two reviewers screened and extracted data independently, resolving disagreements by consensus or third reviewer. Guideline information, number of guidelines over time, type of guidelines, and disease area guidelines (using British National Formulary (BNF) chapters) were described. RESULTS: 7181 records were identified. After de-duplication, 2704 unique CPRD studies were screened against NICE guidelines. Of these, 92 CPRD-based studies met inclusion criteria and were cited across 67 NICE documents. The annual number of NICE guidelines citing CPRD studies increased between 2016 and 2025; 1.5% of identified guidelines published in 2016 and 27.7% in 2025. The guideline citing the most CPRD studies was cancer related. The most common types of guidelines included clinical guidelines (49.3%) and technology appraisals (32.8%). Guidelines made up 12 different BNF categories, most frequently central nervous system related (23.9%; n = 16). CONCLUSION: Observational CPRD studies are increasingly referenced in NICE guidelines across multiple disease areas, supporting the growing role of EHR data in national guideline development.

Clinical studies↗

PubMed2026

Evaluating a coaching intervention for Dementia Care Practice Recommendations in care communities: a cluster randomized controlled trial.

BACKGROUND AND OBJECTIVES: Within care communities, including nursing home and assisted living settings, person-centered dementia care, outlined by the 2018 Alzheimer's Association Dementia Care Practice Recommendations (DCPR), is foundational to quality care and improving staff outcomes. This study evaluates the effectiveness of a 6-month Care Community Coaching Program in enhancing person-centered dementia care and staff outcomes in alignment with the DCPR. RESEARCH DESIGN AND METHODS: A cluster randomized controlled trial was conducted with 77 care communities and 434 staff members-227 from 38 intervention communities and 207 from 39 control communities. Outcomes included employee satisfaction (areas: job satisfaction, team building and communication, scheduling and staffing, training, and management and leadership), person-centered care practices (areas: workplace practices, individualized care and services, caregiver-resident relationships), and dementia care confidence, measured pre- and post-intervention and at 3-month follow-up. A generalized Estimating Equations model was used to estimate intervention effects. RESULTS: Care communities assigned to the coaching intervention showed statistically significant improvements in employee satisfaction and staff perceptions of workplace practices and individualized care. No statistically significant effects on staff perceptions of caregiver-resident relationships or on dementia care confidence were noted. DISCUSSION AND IMPLICATIONS: Findings provide direction for future research and intervention development, including examining coaching's impact on resident quality outcomes, and incorporating skills training into future models. Collectively, findings provide evidence of the effectiveness of a Care Community Coaching Program in improving staff outcomes and person-centered practices, offering a practical path towards improving the lived experience of residents and staff in care communities.

Humans↗

PubMed2026

Impact of neoprene wetsuits on lung volumes and work of breathing: implications for military diver safety and performance.

INTRODUCTION: Neoprene wetsuits may impose mechanical constraints on the chest wall, potentially altering respiratory function. This study investigated the impact of neoprene wetsuits on lung volumes, airway mechanics, and work of breathing (WOB) in healthy male divers. METHODS: A randomised crossover trial was conducted with 31 male divers at the Royal Netherlands Navy Diving Medical Centre. Participants underwent pulmonary function testing, including spirometry, body plethysmography, the forced oscillation technique (FOT), and diffusion capacity measurements, both with and without a hoodless standardised 5 mm neoprene full body wetsuit with a neoprene neck seal. Primary outcomes included changes in forced vital capacity (FVC), functional residual capacity (FRC), airway resistance (Raw), reactance (Xrs), and WOB. RESULTS: Wearing a neoprene wetsuit led to statistically significant reductions in FVC (2.8%, P < 0.05), forced expiration in one second (2.9%, P < 0.05), FRC (4.0%, P < 0.05), and expiratory reserve volume (10.9%, P < 0.05), alongside increases in inspiratory capacity and tidal volume. Raw increased significantly (P < 0.05), while the FOT revealed altered airway mechanics, evidenced by increased Xrs at multiple frequencies (P < 0.05). Diffusion capacity remained unchanged, suggesting preserved alveolar-capillary function. CONCLUSIONS: Neoprene wetsuits induce mechanically restrictive effects on the chest wall, reducing static and dynamic lung volumes and increasing WOB. While these changes may not be clinically relevant at rest, their impact needs to be determined during strenuous or prolonged dives, particularly when combined with other equipment that limits thorax excursions. Future research should explore the effects of the military 5 mm wetsuit under immersed conditions to better understand their operational impact on diver performance and safety.

Male↗

PubMed2026

Modulating sentence comprehension in people with aphasia through anodal tDCS: A double-blind randomized cross-over study.

This double-blind randomized cross-over study investigated the effects of perilesional anodal transcranial direct current stimulation (AtDCS) combined with speech-language therapy on sentence comprehension in eight individuals with chronic nonfluent agrammatic aphasia. The behavioral therapy consisted of an intensive comprehension treatment including drilling in sentence-to-picture matching and Mapping Therapy. Each participant underwent both the anodal tDCS and sham stimulation conditions (five received sham first followed by real stimulation, and the remaining three the reverse sequence), with each condition paired with the same behavioral treatment and separated by a four-month washout period. Stimulation was applied over the perilesional area (left BA6) for 20 min during daily 40-min therapy sessions over four consecutive weeks. Sentence comprehension was assessed with the RiComprendo battery and functional communication with the Communicative Effectiveness Index (CETI). Data were analyzed using paired t-tests, Bayesian analyses, and linear mixed-effects models to control for baseline performance and individual variability. Both stimulation conditions produced significant pre-to-post improvements in sentence comprehension, particularly for syntactically complex structures such as passives and center-embedded object relatives. However, gains were overall greater following AtDCS, as reflected in larger effect sizes, stronger Bayes factors, and a significant treatment effect in the mixed-effects models. Only the AtDCS condition yielded significant improvements in self-perceived comprehension abilities on the CETI. These findings suggest that AtDCS over perilesional cortical areas may boost the effects of traditional language therapy on sentence comprehension, supporting its feasibility and potential as an adjuvant intervention in post-stroke aphasia rehabilitation.

Humans↗

PubMed2026

How Do Climatic Factors Directly Influence the Incidence and Risk of Meningococcal Meningitis Across the African Meningitis Belt? A Narrative Literature Review.

Globally, the highest incidence of meningococcal meningitis occurs within the African meningitis belt, spanning 26 countries across sub-Saharan Africa. Meningococcal meningitis incidence is highly seasonal in this region specifically, with outbreaks mostly occurring during the dry season, characterized by low rainfall and atmospheric humidity, high temperature, and increased dust and wind speed. The strong seasonality of meningococcal outbreaks coincides with seasonal variation in climatic factors. This multicollinearity can make it difficult to identify environmental drivers of disease and the mechanisms by which they operate. This review aims to collate existing evidence to better clarify the mechanisms by which climatic variables influence meningococcal meningitis incidence. We examined the impact of dust, wind speed, temperature, rainfall, and land cover on meningococcal meningitis outbreaks. Within the literature, atmospheric dust and wind speed had the strongest statistical association with meningococcal outbreaks and demonstrated greater predictive probability than other climatic variables. However, several climatic factors have demonstrable influences on one another, reflected in the seasonality of meningococcal meningitis. Atmospheric dust can reduce precipitation levels in part through its radiative properties. Decreased rainfall and increasing temperatures can dry out soil, increasing its availability to be uplifted as dust. Alongside, this lower atmospheric humidity increases evaporative demand, leading to faster soil moisture loss and enhanced surface drying. We argue that rainfall, temperature, and land cover variability may act as part of a broader climatic mechanism, increasing atmospheric dust. This increases the incidence and risk of meningococcal meningitis.

Africa↗

PubMed2026

Elucidating the evolution of meat quality, water distribution, microstructure, and protein structure during sous-vide and micro-pressure cooking.

This study investigated the evolution of eating quality (colour, texture and volatile flavour compounds), water status, microstructure and protein structure of pork meat under different cooking methods. The methods analysed included traditional cooking (TC: 10, 20, 30 and 40 min, 100 °C), sous-vide cooking (SV: 1, 2, 3 and 4 h, 60 °C) and micro-pressure cooking (MC: 10, 20, 30 and 40 min, 120 °C). Across the three cooking processes, as cooking time increased, cooking loss, lightness, yellowness, P23, β-sheet, random coil and surface hydrophobicity of the meat samples increased. By contrast, redness, P22, hydrogen proton density, esters content, α-helix, β-turn and sulfhydryl group content decreased. Moreover, the Warner-Bratzler shear force (WBSF), adhesiveness, hardness, springiness, gumminess, chewiness, alcohols, aldehydes, ketones and fluorescence intensity of the meat samples, initially increased and then decreased as cooking progressed. SV resulted in higher water-holding capacity (WHC), improved redness and increased alcohol and ester levels, whereas MC produced softer meat and greater water mobility. Furthermore, MC enhanced the degree of microstructural damage and protein structural unfolding in the meat. MC requires less time to achieve textures and flavours similar to those obtained using the TC and SV methods. Thus, MC is an efficient cooking method for the catering industry to obtain desired meat quality rapidly.

Cooking↗

PubMed2026

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans↗

PubMed2026

Regional and statewide hysterectomy-corrected endometrial cancer incidence and five-year relative survival in Texas.

BACKGROUND: Rising endometrial cancer (EC) incidence nationwide, particularly among Hispanic women, and high prevalence of risk factors such as obesity and comorbidities in Texas, motivated us to estimate EC incidence rates (IRs) and survival by age (<50 years/ early-onset, ≥50 years/late-onset), race-ethnicity (Non-Hispanic-White [NHW], -Black [NHB], Hispanic), histology (endometrioid, non-endometrioid), and area-based socioeconomic (SES) factors across Texas Health Service Regions (HSRs). STUDY DESIGN: Between 2000 and 2019, a total of 42,571 women (20-79 years) with EC were reported from Texas within the Surveillance, Epidemiology, and End Results Program. IRs and 5-year relative survival were calculated using SEER*Stat. IRs were corrected for hysterectomy using Behavioral Risk Factor Surveillance System data. RESULTS: Statewide EC IRs rose from 38.5 (2000-2009) to 44.5 (2010-2019), with the highest increase in the Upper-South (42.6 to 53.8). Across HSRs, Upper-South consistently had higher IRs among women < 50 (13.9) and ≥ 50 years (112.7). Among those < 50 years, Hispanics had the highest IRs (12.4), predominantly endometrioid tumors, whereas in women ≥ 50 years, NHB had the highest IRs (119.2) with a large proportion of non-endometrioid tumors. IRs were higher in areas with lower poverty, and higher education, income, and urbanization. Associations with unemployment were mixed. Worse survival outcomes were observed among NHBs, non-endometrioid, advanced-stage, and lower SES. Central Texas had more favorable survival outcomes compared to other HSR. CONCLUSION: EC IRs and survival rates in Texas largely mirror national trends, with regional differences likely reflecting sociodemographic and histologic distributions.

Humans↗

PubMed2026

Biomonitoring of industrial heavy metal pollution via enzymatic and metabolic responses in desert ants (Cataglyphis savignyi) and beetles (Tentyrum sp) as bioindicators.

The current work seeks to evaluate the effectiveness of Cataglyphis saviginyi and Tentyrum sp as indicators of pollution in the city's main industrial regions by analyzing their enzymatic activity and primary metabolites. Soil samples were collected at each site under investigation to analyze soil characteristics and heavy metal content. C. saviginyi and Tentyrum sp were collected across four consecutive seasons (2023-2024) to investigate enzymatic (GPT, GOT, ALP, ACP, LDH) and metabolic (lipid, protein, carbohydrate) biomarkers. The physicochemical properties of the soil differed substantially between the industrial areas and the control site. Soil heavy metal buildup was highest at industrial sites (1 and 4) compared to the control site, with the order being Zn > Cr > Cd > Cu. Heavy metal pollution indices were determined. Increased industrial activity from metal industries, ceramics, and chemical painting companies defines this area, as seen by the high Cdeg, mCd, PI, and PLI values derived for industrial sites 1 and 4. While C. saviginyi and Tentyrum sp deconcentrated and released Cr, Cd, and Zn into the soil via the biological accumulation factor (BAF), Cu acted as a macro-concentrator. Compared with the control site, industrial environments were shown to increase levels of GPT, GOT, LDH, ACP, protein, and carbohydrates in C. saviginyi. However, lipid and ALP activity was suppressed. at industrial sites, Tentyrum sp carbohydrate content was higher than at control sites, but GPT, GOT, ALP, ACP, LDH, protein, and lipid activities were all suppressed. Consequently, enzymatic and metabolic biomarkers proved to be sensitive indicators for assessing industrial heavy metal pollution in desert ecosystems.

Animals↗