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The present study reveals that all crowders, regardless of their architecture, favor a compact enzyme conformation while modulating conformational dynamics and substrate binding through distinct mechanisms. These findings provide valuable insights into protein stabilization strategies and may facilitate the rational design of therapeutics targeting modular enzymes.
Recycling polymers with solvents requires removing additives efficiently-yet for most of the hundreds of additives used industrially, the efficiency of various solvents to dissolve them is unknown, particularly due to the scarcity of experimental solubility data. This work proposes a systematic computational approach using the quantum mechanics-aided open-source COSMO-SAC model to screen solvents and requires only the fusion data of the additive as external input, or even no empirical input. To validate the method, we compiled solubility measurements for five representative additives across diverse solvent classes. Quantitatively, predictions typically fall within 0.5 log units of measured values (in mole fraction) and, more importantly, qualitatively correctly identify both the best and worst solvent types for each additive. Furthermore, we examined how different modeling choices affect predictions: for instance, values of fusion properties, molecular conformation and σ-profile of the additive, and dispersive interactions. When fusion data are unavailable, the infinite-dilution activity coefficient provides rankings comparable to those obtained from calculated equilibrium solubilities, particularly for poorly soluble additives. Minor limitations of the approach were observed in cases where solvents are structurally very similar-here, fine distinctions between them can be affected by interference from other effects or model simplifications. However, for choosing between different solvent classes-the decision that matters most in practice-the rankings prove robust. We additionally benchmarked COSMO-SAC against HANNA, a machine-learning activity-coefficient model: the two yield comparable solvent rankings. To facilitate reproducibility and extension of this work, we provide COSMOSol, a Python toolset containing all workflows and data. The method offers a practical, first-principles route to solvent screening-not only for polymer additives, but potentially for other compound classes where experimental data are lacking.
Heterozygote carriers of Gaucher's disease mutations and other polymorphisms in the glucocerebrosidase (GBA) gene show an increased incidence of Parkinson's disease. We hypothesized that common GBA polymorphisms would be associated with subtle parkinsonian features, mild cognitive impairment, and "silent" Lewy body (LB) pathology in aging individuals without a clinical diagnosis of parkinsonism. The most prevalent GBA variants, T369M and E326K, appear in the general population at rates of approximately 0.6% and 1%, respectively. We evaluated 845 participants from the Oregon Alzheimer's Disease Research Center (OADRC) with SNP data generated by the National Centralized Repository of Alzheimer's Disease (NCRAD). Twenty-one subjects were E326K carriers and eighteen were T369M carriers. Clinical measures and postmortem neuropathology were compared between each SNP group and non-carriers. Although there were no statistically significant clinical differences related to synucleinopathy across groups, neuropathological analyses revealed a significantly higher prevalence of LB pathology in E326K carriers compared to T369M carriers. When stratifying each genetic group by LB status (LB+ or LB-), LB+ E326K carriers demonstrated a significant reduction in Mini-Mental State Examination (MMSE) scores compared with LB- non-carriers and a modest decrease compared with T369M carriers. These preliminary findings from a small, uni-center cohort suggest that the E326K GBA polymorphism may predict LB pathology and subtle cognitive decline in aging individuals who lack overt parkinsonian symptoms. Further validation in a larger cohort is warranted. Identifying at-risk individuals through targeted genetic screening may ultimately support earlier intervention and preventative care strategies. Understanding How Two Common GBA Gene Variants Affect Brain Aging in People Without Parkinson's Disease: What We Learned by Comparing Thinking Abilities and Brain Changes in Older AdultsThis study explored whether two common changes in the GBA gene, called E326K and T369M, influence how the brain ages in people who never developed Parkinson's disease during life. We wanted to learn whether these genetic differences affect thinking or memory and whether they are linked to changes in the brain that are usually seen only after symptoms appear. This question matters because many people now learn about their genetic risks through medical or consumer testing, yet doctors often do not have clear information about what these results mean for older adults who have no symptoms. To study this, we followed a large group of older adults who completed yearly thinking and movement tests and then donated their brains for research. This approach allowed us to compare their everyday functioning with the actual brain changes seen under the microscope. We found that people with the E326K variant showed more of the protein buildup typically linked to Parkinson's disease, even though they never showed the disease in life. They also tended to have lower memory scores. This suggests that E326K may contribute to “silent” brain changes long before symptoms appear. In contrast, people with the T369M variant did not show these harmful changes. They had no signs of Parkinson's-related protein buildup and tended to have fewer Alzheimer's-related changes as well, along with slightly better memory performance. These findings show that not all GBA variants act the same way. One variant may increase risk for early, hidden brain changes, while another may be neutral or even somewhat protective. Understanding these differences can help doctors better explain genetic test results, guide decisions about monitoring and follow-up, and support future research aimed at early prevention of brain diseases.
The optimal systemic treatment for node-negative, human epidermal growth factor receptor 2 (HER2)-positive breast cancer with tumors >2 cm remains unclear. De-escalation is commonly used for smaller tumors, but evidence supporting the neoadjuvant dual-targeted pathway in high tumor burden disease is limited. To compare pathological response and exploratory disease-free survival (DFS) between the neoadjuvant dual-targeted and adjuvant single-targeted treatment pathways, focusing on tumors >2 cm. Retrospective, single-center cohort study. We identified 518 consecutive patients treated from 2015 to 2023 at a tertiary academic center. In a guideline-recommended cohort (N = 426), patients managed via the neoadjuvant dual-targeted pathway were compared with those managed via the adjuvant single-targeted pathway. Propensity scores were estimated using logistic regression and applied via overlap weighting to balance covariates. DFS was assessed using overlap-weighted Cox regression, including a tumor-size interaction (⩽2 vs >2 cm). Sensitivity analyses addressed calendar-time confounding, truncation at 24 months with bootstrapped risk differences, and surgery-date landmark analysis. Reporting followed Strengthening the Reporting of Observational Studies in Epidemiology guidelines. Overlap weighting achieved good balance (all standardized mean differences <0.10). In the guideline-recommended cohort (18 DFS events), the neoadjuvant dual-targeted pathway was not significantly associated with DFS (hazard ratio (HR) 0.26; 95% confidence interval (CI): 0.04-1.55; p = 0.138), and the size-by-treatment interaction was not significant (p = 0.123). In tumors >2 cm (N = 247), the neoadjuvant dual-targeted pathway was associated with a pathological complete response rate of 56.9% (58/102) and an exploratory DFS signal (HR 0.08; 95% CI: 0.01-0.59). At 24 months, 0 versus 5 DFS events resulted in an absolute risk difference of 7.0% (95% CI: 1.1%-14.0%). Sensitivity analyses yielded consistent results, though estimates for tumors ⩽2 cm were imprecise. In this exploratory real-world cohort, the neoadjuvant dual-targeted treatment pathway for node-negative, HER2-positive breast cancer with tumors >2 cm was associated with high pathological response rates and an exploratory DFS signal, though sparse events and observational biases limit survival conclusions. Size-informed, risk-adapted strategies are needed. Trial registration: Not applicable. Comparing two treatment strategies for node-negative HER2-positive breast cancer: is it better to give two targeted drugs before surgery for tumors larger than 2 cm? Why was this study done? Patients with HER2-positive breast cancer that has not spread to the lymph nodes (node-negative) generally have excellent outcomes. For small tumors, surgery followed by one HER2-targeting drug works well. However, doctors are unsure if patients with tumors larger than 2 cm need a stronger approach. We investigated whether giving two targeted drugs before surgery works better for these patients than the standard approach. What did the researchers do? We reviewed the medical records of 518 patients with node-negative, HER2-positive breast cancer treated at a single hospital. We compared patients who received the standard treatment (surgery first, then one targeted drug) with those who received the stronger approach (two targeted drugs before surgery). What did the researchers find? For patients with tumors larger than 2 cm, the stronger approach (two drugs before surgery) was highly effective. It completely cleared the cancer before surgery in more than half of these patients, and early results suggest it might better prevent the cancer from returning. However, for patients with smaller tumors, this stronger treatment did not show a clear extra benefit. What do these findings mean? Tumor size matters when choosing treatments for node-negative, HER2-positive breast cancer. Patients with tumors larger than 2 cm might benefit from two targeted drugs before surgery. Because this study looked back at past medical records and the number of returning cancer events was very low, longer follow-up is needed to confirm these findings before changing standard medical guidelines.
Abdominal binders have been studied as an adjunctive device for colonoscopy, but trial-level evidence is heterogeneous and existing meta-analyses have either not stratified by body-mass index (BMI) or used only linear meta-regression, leaving BMI dependence of binder benefit unresolved. To quantify the effect of abdominal binders on cecal intubation time (CIT), post-procedural pain, manual pressure, and position change during adult colonoscopy and to examine BMI dependence using a pre-specified stratified approach. Systematic review and meta-analysis of randomized controlled trials. Seven academic databases plus ClinicalTrials.gov were searched (primary April 30, 2025; updated February 28, 2026). Two reviewers screened records and assessed risk of bias (Cochrane RoB 2) independently. Effects were pooled with random-effects (DerSimonian-Laird) models: mean difference (CIT), Hedges's g (pain), and risk ratio (manual pressure, position change). BMI was a pre-specified stratified subgroup across three study-level tertiles (<26, 26-28, >28 kg/m²); robustness was assessed by leave-one-out sensitivity analyses. Fourteen RCTs (n = 2834) were included after two post hoc exclusions (predatory publication; unverifiable randomization). Abdominal binders significantly reduced CIT (MD -1.576 min; p < 0.001; k = 14), pain (Hedges's g -0.853; p < 0.001; k = 8), manual pressure (RR 0.522; p < 0.001; k = 11), and position change (RR 0.569; p < 0.001; k = 11). BMI-stratified analysis revealed a non-monotonic pattern for CIT and manual pressure (with a parallel pattern for pain whose intermediate stratum rests on a single trial): lean (<26) and obese (>28) strata showed benefit while the intermediate stratum (26-28) did not. Position-change benefit reached significance only in the lean stratum. Effects were robust on leave-one-out. Abdominal binders consistently improve four colonoscopy-related outcomes; the non-monotonic BMI response pattern suggests two distinct mechanistic pathways and is hypothesis-generating, warranting confirmation in BMI-stratified randomized trials. Prospectively registered with International Platform of Registered Systematic Review and Meta-Analysis Protocols on May 15, 2025 (registration number INPLASY202550043; DOI: 10.37766/inplasy2025.5.0043). Do abdominal binders help during colonoscopy? A study on how patient body weight (BMI) changes the results What is this study about? Colonoscopy is the best way to screen for colon cancer, but the procedure can be difficult if the colonoscope “loops” or stretches the bowel, causing pain and longer procedure times. Abdominal binders—elastic belts worn around the waist—are used to apply steady pressure to the belly to prevent these loops from forming. This study looked at data from 14 clinical trials involving 2,834 patients to see if these binders truly improve the experience for both patients and doctors. Key Findings: The research found that using an abdominal binder during a colonoscopy provides four main benefits: Faster Procedures: It shortened the time it took to reach the end of the colon by about 1.6 minutes on average. Less Pain: Patients reported significantly less discomfort after the procedure. Easier for Staff: Doctors didn’t have to manually push on the patient’s belly as often. Fewer Position Changes: Patients didn’t need to be rolled into different positions as frequently to help the scope move forward. Why Body Weight (BMI) Matters: The most important discovery was that the binder’s success depends on the patient’s Body Mass Index (BMI). The benefit followed a “U-shaped” pattern: Lean Patients (BMI < 26): Saw significant benefits because the binder helps stabilize “loose” internal organs. Obese Patients (BMI > 28): Saw significant benefits because the binder helps support the abdominal wall. Intermediate Patients (BMI 26–28): These patients saw the least benefit, likely because their internal anatomy is already naturally stable enough that the binder adds little extra help. Conclusion: Abdominal binders are a helpful, low-cost tool for improving colonoscopy outcomes. They are especially effective for thinner patients and heavier patients, helping to make the life-saving procedure quicker and more comfortable. For patients in the middle weight range, doctors may decide whether to use one based on the specific case.
A growing number of studies suggest that exposure to particulate matters with aerodynamic diameters < 2.5 μm (PM2.5) below air quality standards still increases the risk of death from cardiovascular disease (CVD), and the risk of death from ischemic heart disease (IHD) and stroke, the largest cause of CVD death. The aim of this study was to investigate the effect of PM2.5 exposure at lower levels on years of life lost (YLL) and potential life expectancy benefits for IHD and stroke. We investigated the relationship between daily PM2.5 and YLL for IHD and stroke using a generalized additive model (GAM) based on Poisson distribution. Furthermore, we extended our analysis to estimate the Potential Gain in Life Expectancy (PGLE) and the Attributable Fraction (AF) under the current Chinese air quality standards and more stringent World Health Organization (WHO) air quality guidelines. Findings reveal that for each 10 µg/m3 increase in PM2.5, YLL rose by 1.69 years for IHD and 1.34 years for stroke, with the most significant effects observed on the day of exposure for IHD and three days post-exposure for stroke. The impact was more pronounced among women and those aged ≥ 65 years. If PM2.5 levels met the 2021 WHO air quality guidelines, PGLE of 0.22 years for IHD and 0.16 years for stroke could be achieved. The study highlights the need for stricter PM2.5 control measures to enhance cardiovascular health and reduce mortality, even in regions with relatively low pollution levels.
On August 4th, 2020, Beirut witnessed the largest non-nuclear explosion in modern history. The explosion resulted in the release of large amounts of gases and particulate matters (PM) including ammonia and nitrogen oxides (NOx), as well as pure oxygen (O2) (1). NO2 conversion into nitric and nitrous acids has been shown to damage the alveolar structure in distal airways (2). The goal of this study is to investigate the early and late, subjective and objective, effects of the explosion and particulate matter exposure on the upper airway, specifically chronic rhinitis.
This study explores older adults' perceptions of the ageing experience in Trinidad and Tobago, and gains insight into their self-perceptions of ageing. A concurrent mixed-methods approach was utilized, targeting older adults living in Trinidad or Tobago. For this paper, only the qualitative component of the study will be discussed. Thirty-eight (38) participants engaged in six focus group discussions about their physical, mental, and social health and ageing experiences. The focus groups were audio-recorded and transcribed verbatim. The data were analyzed with MAXQDA software and themes found. Participants lived experiences were garnered from various aspects of their lives, including personal matters and cultural and societal influences with major themes such as ageism and disrespect, undesirable cultural norms, and fear of crime. Most themes reflected positive perceptions, including positive outlook on ageing, positive perceptions of one's health, enjoying retirement, satisfaction with available resources, and spirituality/religion. Negative experiences focused on the health system and in navigating financial challenges. The findings of our study show the need for a change in the framing of age and ageing at both the individual and societal level and shows the relevance of continued societal participation and adequate health care among older adults for a healthy ageing society. Multilevel and multisector efforts are required to reduce everyday ageism and promote positive beliefs, practices, and policies related to aging and older adults.
Hydrogel-based photocatalytic systems have emerged as a transformative platform at the interface of soft matter chemistry, catalysis, and sustainable energy conversion. Unlike conventional particulate photocatalysts, embedding semiconductor materials within three-dimensional, water-rich polymer networks creates a highly hydrated and tunable microenvironment that regulates mass transport, light-matter interactions, and interfacial charge dynamics. This review critically examines the rational design principles of multifunctional photocatalytic hydrogels, emphasizing how gelation chemistry, network topology, and interfacial engineering synergistically govern catalytic performance. Recent advances in defect engineering, heterojunction construction, functionalization and hybridization with conductive and plasmonic components are discussed as key strategies to tailor band structures and suppress charge recombination within confined hydrogel architectures. The hydrogel matrix plays a key role in coupling adsorption with photocatalysis, stabilizing reactive intermediates, and enabling spatially confined redox pathways, thereby enhancing efficiencies in photocatalytic hydrogen evolution, hydrogen peroxide production, ammonia synthesis, carbon dioxide reduction, organic pollutant degradation, biomass conversion, and advanced oxidation processes, including (self-)Fenton and peroxymonosulfate and persulfate activation for environmental remediation. Beyond material design, this review addresses challenges related to photon transport, interfacial charge migration, reactor configuration, and scalability, linking microscale engineering with macroscale performance. A comparative assessment against conventional photocatalysts highlights their strengths, limitations, and translational potential. Finally, future directions are outlined through a structured strengths, weaknesses, opportunities, and threats (SWOT) analysis, guiding the development of next-generation hydrogel photocatalytic systems for sustainable solar-to-chemical energy conversion and environmental remediation.
To synthesize recent evidence on how environmental exposures influence stroke risk, with emphasis on air pollution, thermal stress, circadian and occupational disruption, built and social environments, and selected toxicants. Long-term and episodic air pollution, especially fine particulate matter with aerodynamic diameter ≤ 2.5 μm (PM₂.₅) and wildfire smoke, remain most consistently associated with stroke risk. Extreme heat combined with heat-humidity metrics is emerging as an important acute stroke trigger. Noise, artificial light at night, shift work, and long working hours show smaller but plausible associations, while greener and more walkable environments may be modestly protective. Social and structural disadvantage clusters, multiple exposures and inequities play an integrated role in risk and prevention. Environmental determinants are increasingly relevant to stroke risk. The strongest current links are realted to pollution, heat, sleep, and work disruption, as well as environmental inequity. Future research should move beyond single-exposure models toward combined-exposure as well as intervention-focused approaches.
BackgroundRetinal structural and microvascular alterations detected by optical coherence tomography (OCT) and OCT angiography (OCTA) have emerged as promising biomarkers of Alzheimer's disease (AD). However, the extent to which retinal changes reflect cerebral neurodegenerative and vascular pathology and contribute to cognitive impairment remains incompletely characterized.ObjectiveTo investigate the relationships among retinal OCT/OCTA metrics, cerebral neuroimaging markers, and global cognitive performance in patients with AD.Methods115 AD and 101 cognitively unimpaired controls underwent OCT/OCTA imaging, 3.0T brain magnetic resonance imaging, and neuropsychological assessment. Retinal structural measures, including peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell-inner plexiform layer (GCIPL) thicknesses, and retinal microvascular densities of the superficial vascular complex (SVC) and deep vascular complex were analyzed alongside white matter hyperintensity (WMH) volume, hippocampal volume, and cerebral small vessel disease (SVD) burden.ResultsCompared with controls, patients with AD exhibited significantly thinner pRNFL and GCIPL and lower SVC density (all p < 0.01). Retinal structural and microvascular alterations were associated with greater WMH burden, hippocampal atrophy, increased SVD burden, and lower Mini-Mental State Examination and Montreal Cognitive Assessment scores (all p < 0.05). Significant interactions were observed between GCIPL thickness and periventricular WMH volume in relation to cognitive performance. Mediation analyses demonstrated that WMH volume and SVD burden partially mediated the association between reduced SVC density and cognitive impairment.ConclusionsRetinal OCT/OCTA metrics are associated with cerebral neurodegenerative and vascular abnormalities and reflect cognitive dysfunction in AD, supporting their potential utility as accessible, noninvasive biomarkers for disease assessment and monitoring.
Quantitative MRI (qMRI) might detect subtle changes in recurrent high-grade glioma earlier than conventional imaging. The purpose of this study was to investigate whether WHO grade 4 glioma patients demonstrate alterations in multiparameter mapping (MPM) and diffusion tensor imaging (DTI)-derived measures within radiologically normal-appearing brain regions that subsequently exhibit tumor recurrence in follow-up scans. For 16 WHO grade 4 glioma patients with confirmed recurrence at follow-up, qMRI parametric maps [proton density (PD), longitudinal relaxation rate (R1), transverse relaxation rate (R2*)] were generated using an MPM protocol. Additionally, diffusion tensor imaging (DTI)-derived free water (FW) and FW-corrected tissue fractional anisotropy (FAt) were evaluated. We mapped recurrent tumor areas onto baseline scans to identify regions that subsequently progressed to contrast-enhancing tumor (CET) or FLAIR-hyperintense areas. Normal-appearing gray matter (NAGM) that progressed into FLAIR-hyperintense areas in follow-up scans showed significantly lower median PD values, while median FW was significantly elevated across all subregions compared to their reference regions. This potentially reflects an early redistribution of water from bound tissue compartments into the extracellular space, most evident in gray matter. R1 demonstrated significantly lower median values in NAGM progressing to tumor compared to stable NAGM. Variance was significantly increased for PD, R2*, and FW in multiple subregions, consistent with heterogeneous tumor infiltration. MPM and DTI-derived metrics reveal subtle alterations in radiologically normal-appearing brain tissue months before recurrence becomes visible on conventional imaging. This could support earlier identification of subclinical progression and allow for personalized surveillance strategies.
Artificial active particles provide a powerful platform to investigate non-equilibrium collective behavior. Here, we use Hexbugs equipped with embedded magnetic dipoles as macroscopic realizations of magnetic self-propelled particles (MSPPs) to study active matter under confinement. By combining experiments and simulations, we analyze their dynamics within a parabolic domain modeled as a symmetric external harmonic potential. We uncover a rich landscape of metastable and dynamically evolving configurations, including climbing chains, polarized orbiting clusters, and rotating ring-like states, arising from the competition between dipolar interactions, confinement, and activity. While orbiting states are recovered at the single-particle level, we show that self-alignment alone does not determine the collective dynamics, which instead emerge from magnetic interactions. We demonstrate that the number of particles and the relative strength of magnetic interactions and harmonic confinement control the structure and stability of these states. Our experimental observations are quantitatively reproduced by a minimal model of disk-like magnetic active Brownian particles with inertial translational dynamics and overdamped orientation. These results provide a unified framework for understanding structure formation and dynamical states in confined active systems with dipolar interactions.
Active matter systems exhibit unique nonequilibrium phenomena that bridge the fields of soft condensed matter and biological physics. In this study, we investigate the structural and dynamical behaviors of a six-armed star copolymer immersed in a dense bath of active Brownian particles (ABPs) via Langevin dynamics simulations. Our results reveal a universal scaling relation for rotational dynamics: ω ∼ Pe 1.2, which is independent of the copolymer's bending rigidity κ, thereby confirming the Péclet number (Pe) as the key variable governing nonequilibrium kinetics. Through a torque balance analysis to rotational dissipation, we derive theoretical bounds on the scaling exponent and relate the observed value n ≈ 1.2 to the weakly nonlinear regime where activity-driven accumulation competes with self-propelled escape. We find that interaction potential parameters finely tune the system's behavior: stronger and longer-range interactions promote compact conformations at low ABP densities, while enhancing rotational dynamics. At higher ABP densities, crowding effects dominate, leading to non-monotonic structural and dynamical responses. The effective diffusivity follows D eff/D 0 ∼ 1 + αPe 2 at moderate Pe and transitions to a different scaling regime (Pe 1.3) at high Pe. Our analysis reveals that rotational motion is a finite-range phenomenon: for short arm lengths, the polymer arms sustain bent conformations enabling ABP collection and persistent rotation; other active-particle-induced arm collapse causes rotation to cease. These findings provide a theoretical framework for the quantitative design of active polymer composites and have important implications for intelligent soft materials and micro-nano robotics.
The rapid expansion of rice processing mills in agriculturally rich regions, such as Khajanagar, Kushtia, has resulted in elevated concentrations of particulate matter (PM), posing serious environmental and public health risks. The close proximity of rice mills to residential areas necessitates evaluating particulate matter dispersion to assess neighbourhood-level health risks. This study examines the spatial distribution, dispersion behaviour, and health impacts of PM₂.₅ and PM₁₀ across industrial and adjacent residential zones. A total of 69 sampling points were monitored using optical particle counters (OPCs) at 0-100 m (industrial) and 101-300 m (residential) distances, along with meteorological observations. PM₂.₅ concentrations in industrial areas exceeded all regulatory limits in Bangladesh, the WHO, and the U.S. EPA, while PM₁₀ exceeded WHO standards only within industrial zones; both fractions exceeded all benchmarks in residential areas. The Kruskal-Wallis test (p < 0.05) confirmed significant interzonal variation. Spatial mapping identified PM hotspots in the western and eastern industrial belts and the western residential cluster, providing empirical evidence of localized emission intensity and downwind accumulation driven by mill density and prevailing wind patterns. PM₂.₅ and PM₁₀ were highly correlated, though their relationships with humidity and temperature were weak. Gaussian plume modelling indicated that PM₁₀ dispersed and deposited over greater distances than PM₂.₅ due to its size-dependent transport under prevailing winds, increasing exposure in residential zones. AirQ⁺ health risk analysis revealed that PM₂.₅ exposure contributed to 39.78% of ALRI-related mortality in children under five, while in adults (≥ 30 years), it accounted for 48.01% of Chronic Obstructive Pulmonary Disease (COPD), 56.25% of Ischemic Heart Disease (IHD), and 65.05% of stroke deaths. PM₁₀ posed additional risks for IHD and lung cancer, with 34.16% of lung cancer mortality linked to PM₂.₅ exposure. By integrating spatial monitoring, dispersion modelling, and health risk assessment, this study identifies high-risk micro-environments and underscores the need for stricter emission control in rice-processing regions.
The global surge in Autism Spectrum Disorder (ASD) cases, coupled with evidence linking prenatal Particulate Matter (PM) exposure to developmental disruption, demands a comprehensive review to design targeted health interventions. This systematic review and meta-analysis aim to evaluate the strength and consistency of evidence linking prenatal PM exposure to ASD across studies, quantifying this relation to identify actionable environmental risk thresholds. This study employed PRISMA protocols to systematically extract and evaluate evidence from PubMed, Web of Science, Scopus, and ScienceDirect (2010-2024), and screened 4,013 articles to identify qualified case-control and cohort studies (n=29). Data synthesis employed random-effects modeling, accompanied by comprehensive assessment through I2 statistics, Q-tests, funnel plots, Duval and Tweedie's trim-and-fill analysis, and Egger's regression, to ensure validity. A meta-analysis of 16 case-control studies revealed a 34 % increased risk of ASD associated with prenatal PM exposure (pooled OR=1.34; 95 % CI: 1.13-1.54), despite substantial between-study heterogeneity (I2=94.02 %, p<0.001). Publication bias was not significant (Egger's test p value=0.114). Critical trimester-specific analysis uncovered that third-trimester exposure significantly increased ASD risk (OR=1.17; 95 % CI: 1.01-1.34), while first-trimester (OR=1.02; 95 % CI: 0.92-1.11; I2=49.18 %, p<0.10) and second-trimester exposures (OR=1.13; 95 % CI: 0.88-1.38; I2=92.59 %, p<0.001) showed non-significant associations. This review identified prenatal and early life exposure to PM as a risk factor for ASD, indicating a trimester-specific vulnerability. It highlighted the necessity of focused air quality interventions and targeted guidance to reduce prenatal PM exposure to alleviate ASD risk during the critical-window.
Dengue-associated liver injury is common, prognostically significant, and associated with high mortality at severe thresholds. Oxidative stress is a key, potentially modifiable mechanism. N-acetylcysteine has strong biological plausibility and supportive preclinical data, but clinical evidence remains limited, underscoring the need for well-designed randomized trials to inform practice and policy.
Lithographic patterning of semiconductor materials is essential for most modern optoelectronic devices. However, traditional inorganic and nanocrystal derived resists exhibit low electron-dose sensitivity, weak solubility contrast, and limited chemical compatibility, restricting high resolution functional lithography. Here, we present a molecular complex platform that converts ordinary metal halides (MXn; nine compositions) into intrinsically electron beam responsive, solution processable resists for direct write electron beam lithography. Coordination of MXn with oleylamine yields metal-ligand complexes with comparatively low dose sensitivity among additive-free inorganic resists (0.81 mC cm-2), high contrast (γ = 3.1), and sub-30 nm resolution. Across the tested metal halide library, resist sensitivity shows an exponential dependence on molecular weight, establishing the first universal scaling relationship for molecular resist energetics. Mechanistic studies reveal that electron irradiation induces bond cleavage and coordination network collapse, generating metal halide domains with high structural fidelity. The patterned nanostructures retain optical functionality, nanodots displaying super linear PL excitation (α > 1) characteristics. Furthermore, sequential multilayer writing enables deterministic RGB nano-pixel architectures, exemplified by registered 3.9 × 104 pixel full color parrot micrograph. This additive free, tunable molecular resist system provides a high-resolution lithography route for scalable quantum photonic and optoelectronic fabrication.
Two experiments were conducted to establish the prediction equations of growth performance and apparent metabolizable energy (AME) on chemical composition and enzymatic hydrolysate gross energy (EHGE) of corn, soybean meal (SBM), corn gluten meal (CGM), and wheat bran (WB) in chickens. Experiment 1 established the prediction equations of EHGE of four ingredients on chemical composition. In experiment 2, prediction equations of growth performance and AME based on EHGE of diets in chickens was developed. The variation was high for ether extract (EE) and crude protein (CP) of corn (6.78, 9.56) and WB (15.42, 10.41). The coefficient of variation of EE was higher than those of other ingredients in SBM and CGM. Two, seven, and eight equations for predicting the EHGE of corn, CGM, and WB based on dry matter (DM), GE, CP, and EE were established, respectively. However, statistical analysis showed that prediction equations of SBM were not significant. The prediction equations of ADFI, F/G and AME on EHGE of diets were ADFI = -2.143 * EHGEd + 54.066 (R2 = 0.955), F/G = -0.256 * EHGEd + 5.935 (R2 = 0.954), AME = 0.719 * EHGEd + 3.547 (R2 = 0.937), respectively. These results indicated that chemical compositions and the EHGE of corn, CGM, and WB could predict the growth performance and AME for chickens.