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PubMed2026

Comparison of black carbon measurements using filter-specific reference transmittance to those using lab blanks or an average of unloaded filters.

Filter-based optical techniques compare light transmission intensities between loaded (I) and unloaded (I0) filters as a measure of light-absorbing mass for subsequent estimations of equivalent black carbon (eBC). We analyzed 5,379 15 mm Teflon filters from the Household Air Pollution Intervention Network (HAPIN) trial to assess the influence that different methods of I0 estimations have on eBC measures. We compared eBC measurements using filter-specific I0 values (Method 1) to those using three other methods of I0 estimation: the lab blank scan from a given session (Method 2), the average of all pre-sample filter scans (Method 3), and the average of all lab blank filter scans (Method 4). We assessed the agreement between Method 1 and the alternative methods using Bland-Altman analysis. We also assessed the relationship between Method 1 and the alternative methods across the complete measurement range and after stratifying exposure data into quartiles according to Method 1 eBC exposures. The mean (SD) personal eBC exposure for Method 1 was 7.8 μg/m3 (5.9), and exposures ranged from 1.3 to 46.8 μg/m3. Compared to Method 1, eBC using Methods 2, 3, and 4 were higher by 0.7 μg/m3, 0.1 μg/m3, and 0.7 μg/m3, respectively. The performances of linear regression models between Method 1 and all other methods were moderate to strong (R2 range: 0.42-0.93) in the second, third, and fourth quartiles; however, the models in the first quartile (eBC range: 1.3-2.9 μg/m3) performed poorly (R2 = 0.25-0.26), with error approximately 25% of the mean. Our findings suggest that, in most instances, conventional methods for obtaining I0 values can be used to sufficiently characterize eBC; however, analyzing filters before sampling adds appreciably to the accuracy of eBC estimations in lower concentration settings.Implications: Filter-based optical techniques compare light transmission intensities between loaded (I) and unloaded (I0) filters as a measure of light-absorbing mass for subsequent estimations of equivalent black carbon (eBC). To assess the influence that different methods of I0 estimations have on eBC measures, we analyzed 5,379 15 mm Teflon filters from the Household Air Pollution Intervention Network (HAPIN) trial. Our findings suggest that, in most instances, conventional methods for obtaining I0 values can be used to sufficiently characterize eBC; however, analyzing filters before sampling adds appreciably to the accuracy of eBC estimations in lower concentration settings.

Soot↗

PubMed2026

Mining Stored-Specimen Studies for Information about Cancer Natural History.

The advent of new multicancer early detection tests and publication of early diagnostic results have generated expectations of clinical benefit from multicancer screening. The clinical benefit of a cancer screening test depends critically on disease natural history, which is typically learned from prospective screening studies. Retrospective studies of stored blood specimens are important in learning about a test's preclinical diagnostic performance but have rarely been used to infer natural history. The extent to which these studies might be harnessed to also learn natural history is discussed in the context of an article in this issue that infers the combined natural history of a range of cancers targeted by a multicancer early detection test using a case-control subsample of specimens from a large cohort study. The critical question concerns the identifiability of key transition rates in multistate models of natural history alongside state-specific sensitivities. The article suggests that these parameters are estimable within a Bayesian framework that leverages prior information about test sensitivity from diagnostic studies. We offer a heuristic discussion of identifiability in this setting and encourage formal study to determine the extent to which models with varying degrees of complexity may be learned from stored-specimen studies. See related article by Dai et al., p. 1535.

Humans↗

PubMed2026

Syndemics, violence and injury: exploring historical relationships between infectious disease epidemics and violent crime in South Africa.

This paper explores historical and contemporary intersections between mass-mortality epidemics and violent crime in South Africa, focusing on four major epidemics - Spanish Flu, tuberculosis, HIV, and Covid-19. The study integrates epidemiological data and contextual historical information such as crime statistics, archival records, and secondary scholarship to explore whether epidemic-driven mortality crises are associated with subsequent changes in violence and injury profiles. With the possible exception of gendered violence, the study finds little evidence that earlier epidemics directly contributed to rapid or sustained increases in violent crime, despite causing substantial adult mortality and long-term social and economic disruption. A comparison between epidemic and socio-economic profiles strongly suggests that the significant increases in violent crime recorded after the Covid-19 pandemic are highly localised, and may be more strongly related to lockdown responses, including alcohol restrictions, rather than the effects of disease itself.

Humans↗

PubMed2025

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↗

PubMed2026

Gastrointestinal digestion governs insect protein hydrolysis and predicted bioactive peptide release: Species-dependent implications for functional food applications.

This study investigates the digestion of insect proteins and the release of predicted bioactive peptides during human gastrointestinal digestion. Using the Infogest in vitro model, mealworm, cricket, and black soldier fly larvae (BSFL) proteins were digested and analyzed through discovery proteomics and bioinformatics to identify predicted bioactive peptides. Sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) quantified insect proteins including predicted bioactive peptide precursor proteins, the precursors of predicted bioactive peptides. Results indicated that gastrointestinal digestion strongly influences peptide release, with the gastric phase exhibiting a richer predicted bioactive peptide profile than the small intestinal phase. Many predicted bioactive peptides were rapidly hydrolysed under small intestine conditions, which may lead to reduced stability or diminished activity in vivo, potentially explaining why certain peptides show strong bioactivity in vitro but limited effects in vivo. Additionally, predicted bioactive peptide release varied by insect species, influenced by genetic factors and peptide abundance. These findings highlight the importance of species selection and consideration of proteolytic digestion patterns in optimizing insect-derived bioactive peptides for functional foods and nutraceutical applications.

Animals↗

PubMed2026

Retinal microstructural alterations as early phenotypes of depression in radiogenomics analysis.

BACKGROUND: With the increasing prevalence of depression, there is an urgent clinical need for early screening in depression. The retina offers a promising window for early screening in depression due to its rapid, non-invasive, objective, eye-brain correlated characteristics, but previous research has yielded conflicting alterations in retinal microstructure in depression. METHODS: We screened retinal optical coherence tomography and brain magnetic resonance imaging data in the UK Biobank to enroll 23,225 participants for retinal study of depression occurrence, and 1475 participants for the eye-brain association study. We also used genetic data (ID: ebi-a-GCST90014267 and ukb-d-20,448) from the Integrative Epidemiology Unit Open Genome-Wide Association Study for Mendelian randomization analysis. We used Cox regression to assess the association between retinal microstructure and depression risk, Mendelian randomization to infer causality, and mediation analysis to explore retina-brain pathway association. RESULTS: The Cox regression analysis showed that retinal ganglion cell-inner plexiform layer (GCIPL) thickness remained a significant predictor of depression. The Mendelian randomization analysis indicated a positive statistical association between GCIPL thickness and depression. Moreover, there was a significant positive correlation (all p < 0.001) between the volume of specific depression-related brain regions and the GCIPL thickness. Adjusting for age, sex, and head size, the mediation analysis provided preliminary evidence for a potential anatomical pathway linking retinal GCIPL thickness to depression-related brain regions through primary visual cortex and secondary visual cortex volumes. CONCLUSION: Thickened retinal GCIPL is a potential early phenotype of depression and has a potential association pathway with depression-related brain regions using a radiogenomics approach.

Humans↗

PubMed2026

Effects of apple phenolics on the human metabolome: modulation of key metabolic pathways.

Apples are widely recognized for their potential health benefits, partly attributed to their phenolic compounds. However, their impact on human metabolism remains incompletely understood. This study investigated metabolic effects of apple-derived phenolic compounds using untargeted metabolomics approach across multiple biofluids. In a crossover intervention study, 30 healthy men consumed a phenolic-rich apple juice or a placebo for two weeks. Blood, urine and saliva samples were collected before and after each intervention and analyzed by direct infusion ultra-high resolution mass spectrometry. Consumption of apple phenolic compounds resulted in significant alterations of the human metabolome, including increased levels of phenolic-derived degradation products and microbial-associated metabolites across all biofluids. Pathway enrichment analysis revealed pronounced effects on phenylalanine and tyrosine metabolism, as well as linoleic and arachidonic acid metabolism, Overall, these findings demonstrate that apple phenolic compounds induce measurable, microbiota-associated and systemic metabolic changes, providing new insights into their metabolic fate and biological relevance.

Humans↗

PubMed2026

Integrated genomic and biochemical diagnosis of a novel homozygous start-loss variant in AKR1D1 associated with neonatal cholestasis.

INTRODUCTION: Congenital bile acid synthesis defects are rare autosomal recessive disorders that typically present in early infancy with cholestasis, progressive liver dysfunction, and, in severe cases, acute liver failure. These conditions may mimic other metabolic diseases detected in newborn screening, complicating early diagnosis. The AKR1D1 gene encodes Δ4-3-oxosteroid 5β-reductase, a key enzyme in primary bile acid synthesis, and pathogenic variants cause bile acid synthesis defect type 2 (OMIM #235555). CASE DESCRIPTION: We report a 3-month-old male infant with severe neonatal cholestasis and a history of elevated tyrosine levels in newborn screening. Pregnancy was high risk and unmonitored, with birth outside a hospital. Parental consanguinity was first-degree. Early metabolic evaluation showed transient normalization of tyrosine levels, but subsequent analyses revealed recurrent hyper-tyrosinemia. Urinary organic acids showed increased 4-hydroxyphenyl metabolites, with absent succinylacetone, excluding tyrosinemia type I. Progressive cholestasis developed, accompanied by coagulopathy, hyperbilirubinemia, hyperammonemia, and markedly elevated alpha-fetoprotein. Imaging revealed no structural liver abnormalities. Clinical exome sequencing identified a novel homozygous start-loss variant in AKR1D1, likely abolishing functional enzyme production. Metabolic studies confirmed increased urinary excretion of 3-oxocholenoic acids consistent with abnormal bile acid synthesis and supporting a diagnosis of bile acid synthesis defect type 2. Oral cholic acid therapy led to stabilization and improvement in clinical and biochemical parameters. DISCUSSION/CONCLUSION: This case illustrates the diagnostic complexity of neonatal cholestasis, particularly when initial metabolic findings suggest alternative etiologies. It highlights the importance of newborn screening as a tool for broader diagnostic suspicion and the critical role of early molecular diagnosis and multidisciplinary care. Timely recognition and targeted therapy can improve outcomes, prevent liver transplantation, and enable accurate genetic counseling, especially in consanguineous families.

Humans↗

PubMed2026

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans↗

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

Thrombus Metabolism-Based Molecular Subtyping for Prognostic Risk Stratification in Acute Ischemic Stroke: A Preliminary Study.

AIMS: To preliminarily characterize metabolic molecular subtypes of cerebral thromboemboli and evaluate their clinical significance in anterior circulation acute ischemic stroke due to large vessel occlusion (AIS-LVO). METHODS: Untargeted metabolomics was performed on thromboemboli retrieved from 36 patients with anterior circulation AIS-LVO using ultra-performance coupled liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Unsupervised hierarchical clustering was employed to identify distinct metabolic molecular subtypes, and their associations with stroke etiology, radiographic severity, and functional outcomes were analyzed. RESULTS: Two distinct thrombus metabolic molecular subtypes (C1 and C2) were identified based on 12 metabolites significantly associated with both short-term (7-day ∆NIHSS) and long-term (90-day mRS) functional outcomes. The C1 subtype, predominantly cardioembolic, exhibited enhanced lipid metabolism, whereas the C2 subtype, primarily atherothrombotic, demonstrated increased folate metabolism. Patients with C1 thromboemboli presented more severe admission ischemic lesions (as indicated by ASPECTS) and experienced poorer short-term and long-term outcomes. A six-metabolite signature derived from LASSO regression was identified for exploratory discrimination of thrombus metabolic subtypes, etiological subtypes, and 90-day outcomes. CONCLUSION: This preliminary exploratory study identifies two metabolically distinct thrombus molecular subtypes with clinical implications in anterior circulation AIS-LVO, providing a novel basis for risk stratification and personalized secondary prevention and warrants further investigation.

Humans↗

PubMed2026

Vortex-assisted liquid-liquid microextraction based on natural deep eutectic solvents for the determination of pyrethroid pesticides in urine.

A novel, facile, and environmentally friendly analytical method was developed based on vortex-assisted liquid-liquid microextraction and high-performance liquid chromatography with diode-array detection for detecting pyrethroid pesticides (PPs) in urine. Natural deep eutectic solvents (NADESs) were prepared using plant essential oil-derived monoterpenoids (thymol, carvacrol, and menthol) combined with aromatic primary alcohols (benzyl alcohol, phenethyl alcohol, and phenylpropyl alcohol) as hydrogen bond donors and acceptors. These solvents served as environmentally benign extraction media, thereby avoiding the use of conventional volatile, toxic organic solvents. NADESs are naturally derived, easy to prepare, biodegradable, and environmentally friendly solvents. Hydrophobic and π-π interactions between the NADESs and PPs may contribute to enhancing the affinity of PPs toward the NADESs phase. Vortex technology, accelerating mass transfer between the sample and extractant phases, enables fast extraction of PPs. Under optimized conditions, the method achieved a low detection limit (0.002 mg L-1), satisfactory precision with relative standard deviations (0.3%-2.4%), and acceptable recovery (80.7%-86.2%). The method demonstrated excellent performance in urine analysis and was feasible as a facile and green strategy for monitoring the content of PPs in biological matrices and assessing exposure risk.

Liquid Phase Microextraction↗

PubMed2026

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins↗

PubMed2026

Cochlear Implantation in Sickle Cell Disease: A Systematic Review of Feasibility and Outcomes.

INTRODUCTION: Sickle cell disease (SCD) is associated with systemic complications, including sensorineural hearing loss (SNHL) from microvascular occlusion and chronic inflammation. Although reports link SCD to higher rates of SNHL, current evidence is limited by small sample size, varied audiologic methods, and lack of standardized screening. This systematic review summarizes available literature on SNHL and cochlear implantation (CI) in SCD. METHODS: A literature search of PubMed MEDLINE, Embase, Scopus, Web of Science, and CINAHL identified 79 citations. After removal of duplicates, 35 records were screened in Rayyan. Studies published between January 1, 2000, and June 30, 2025, were eligible if they reported patients with SCD who developed hearing loss and underwent CI. Nine full texts were reviewed, and 4 met the inclusion criteria. Screening and review were performed independently by 2 authors per PRISMA guidelines. RESULTS: Across 4 case reports, a total of 5 patients with SCD underwent CI, ranging in age from 2 to 42 years. Four presented with bilateral severe-to-profound SNHL and one with unilateral loss. Implantation was technically feasible in all cases, including patients with cochlear fibrosis or ossification requiring modified insertion techniques. Postoperative outcomes were favorable: all patients demonstrated reliable device function and low impedances. Only 60% showed meaningful auditory benefit, characterized by improved functional speech perception in 2 patients (40%) and access to the speech frequency range with hearing testing going from moderate/profound hearing loss to mild hearing loss in 3 patients (60%). Complications occurred in 2 patients (40%): one developed unilateral middle ear infection leading to meningitis, and another experienced a postoperative pulmonary embolism requiring anticoagulation. The remaining 3 patients (60%) had uncomplicated recoveries with reported improved hearing from moderate/profound hearing loss to mild hearing loss post implantation. CONCLUSION: While CI appears feasible in SCD, our findings suggest that additional data are needed to assess its effectiveness in this patient population. However, evidence is limited to case reports, and complications such as thromboembolism and rapid cochlear fibrosis highlight the need for close perioperative management. More comprehensive studies with larger sample size are required to define surgical risk, optimize management, and establish best practices for timely implantation in this population.

Humans↗

PubMed2026

Sitosterolemia: evolving strategies for earlier diagnosis.

PURPOSE OF REVIEW: Sitosterolemia is a rare autosomal recessive lipid disorder caused by biallelic pathogenic variants in ABCG5 or ABCG8 , resulting in excessive intestinal absorption and impaired biliary excretion of plant sterols. Although historically considered exceptionally rare, recent genetic studies suggest the disorder is substantially underdiagnosed, with marked phenotypic heterogeneity ranging from xanthomas and premature atherosclerosis to hematologic abnormalities, and frequently mimics familial hypercholesterolemia. This review summarizes recent advances in the clinical, biological, and genetic diagnosis of sitosterolemia, with a focus on strategies that may facilitate earlier detection. RECENT FINDINGS: Phytosterol quantification, particularly sitosterol, campesterol, and stigmasterol, remains indispensable for accurate diagnosis. Hematologic abnormalities, including hemolytic anemia, stomatocytosis, and macrothrombocytopenia, are increasingly recognized as valuable diagnostic clues complementing the biochemical approach. Expanded variant catalogs for ABCG5/ABCG8 and genome-wide association studies have revealed potentially polygenic contributions to phytosterol metabolism extending beyond these two genes. However, no specific guidelines have yet been established for cascade screening. SUMMARY: Earlier diagnosis requires integration of clinical, biochemical, hematologic, and genetic data. Plasma phytosterol measurement remains the diagnostic cornerstone. Improved disease awareness, broader access to sterol testing, and expanded genetic screening may reduce diagnostic delays and enable timely management, including ezetimibe and dietary phytosterol restriction.

Humans↗

PubMed2026

Weight Loss without Food Intake Suppression through Size-Dependent Retention of Anti-Inflammatory Nanomedicines.

Obesity is a risk factor for high-mortality health conditions, including cardiovascular diseases and type 2 diabetes, which makes the advancement of efficacious and safe weight loss therapies a high priority in pharmacology. The causal link between obesity and its comorbid conditions is believed to be a chronic state of inflammation originating within adipose tissue, with macrophages playing central roles, an axis that is not targeted directly by current therapies. Here, we use nanocarriers to deliver an anti-inflammatory glucocorticoid receptor agonist to adipose tissue macrophages and report the impact of size on therapeutic effect. Three dextran nanocarriers between 4-30 nm in hydrodynamic diameter released molecular drug cargo at equivalent rates and exhibited similar biological potency in vitro. In vivo in a mouse model of obesity, body weight and body fat were reduced in a size-dependent manner after 2-4 weeks of treatment. Unlike current clinical pharmacotherapies for weight loss, these body composition changes were not associated with changes in food intake. Greater retention of larger dextran nanocarriers in visceral adipose tissue appears to elicit a local change to promote browning by increasing mitochondrial abundance and lipid droplet fragmentation. Further development of this platform may result in a safe and potent modulator of adipose tissue in the state of obesity without direct action on nutrient intake to address malnutrition and lean body mass deficiencies observed with current weight loss pharmacotherapies.

Animals↗

PubMed2026

Associations between multiple essential trace metal concentrations and risk of hyperuricemia: insights from a central Chinese population.

Previous studies have indicated that levels of individual essential trace metals are related to hyperuricemia (HUA), but evidence on their combined effects is limited. To address this gap, the associations of individual and joint levels of 12 essential trace metals (manganese, selenium, nickel, chromium, cobalt, tin, iron, molybdenum, zinc, strontium, vanadium, and copper) with the risk of HUA were investigated in 2,021 adults recruited from Hunan Province, China. Inductively coupled plasma mass spectrometry (ICP-MS) was employed to determine urinary metal concentrations. Logistic regression, Bayesian kernel machine regression (BKMR), and quantile g calculation (Qgcomp) were applied to evaluate the associations of single and mixture metal concentrations with HUA. Of the participants, 516 (25.53%) were diagnosed with HUA. Inverse associations were found between vanadium, chromium, manganese, iron, cobalt, selenium, strontium, and molybdenum levels and HUA, with ORs ranging from 0.63 to 0.91. Conversely, a positive association was observed between zinc concentration and HUA [OR (95% CI): 1.17 (1.01, 1.37)]. Both BKMR and Qgcomp models showed a negative overall effect of essential trace metals on HUA risk, with strontium (- 43.6%) and vanadium (- 27.8%) being the main contributors. In addition, formal interaction tests revealed significant effect modification by age for tin and by BMI for zinc. In conclusion, the levels of essential trace metals were linked to a decreased risk of HUA, and these associations were modified by age and BMI only for specific metals.

Humans↗

PubMed2026

Towards microplastic bioremediation: Fungal degradation of pristine and pretreated high-density polyethylene and polystyrene.

Microplastic (MP) contamination has become a significant ecological issue because of its enduring existence in the ecosystem and its possible negative impacts. Therefore, using degrading strategies to eliminate these stubborn polymers has been a subject of scientific research. However, the currently used degradation methods are relatively inefficient. Given the pervasiveness of High-Density Polyethylene (HDPE) and Polystyrene (PS) and their resistance to biodegradability, disposal strategies are critical and must be addressed. This manuscript examines the biodegradation of pristine and UV-treated HDPE and PS MPs by Aspergillus flavus species in minimal growth media over 70 days. The maximum weight loss observed at 70 days for pristine HDPE and PS in sole carbon source (SCS) media was (29.33 ± 0.28) % and (17.67 ± 0.35) %, respectively. Whereas, for UV-treated HDPE and PS MPs, the % weight reduction was (33 ± 0.21) % and (25 ± 0.19) %, respectively. UV-treated MPs exhibited greater weight reduction, as UV induced oxygenated functional groups enhance polymer susceptibility to enzymes, thereby promoting biodegradation. HDPE MPs typically show a higher proportion of particles in the lower size range compared to PS MPs. This assertion was based on the weight loss, particle size distribution, and SEM analysis. Furthermore, chemical changes were evaluated using Fourier transform Infrared Spectroscopy (FTIR) analysis, which also displayed chemical oxidation occurring during biodegradation. Liquid Chromatography-Mass Spectrometry (LC-MS) results indicate that UV pretreatment enhances biodegradability by promoting chain scission. These findings further suggest that this fungus's natural and ubiquitous occurrence in terrestrial and marine environments may actively contribute to MP biodegradation while requiring few nutrients.

Microplastics↗