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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

Extreme Temperature and Incident Diabetes Risk Among Middle-Aged and Older Adults in China: A National Longitudinal Cohort Study.

BACKGROUND AND AIMS: The metabolic consequences of extreme temperature exposure in nondiabetic populations remain poorly understood. This study aimed to examine associations between heatwave and coldwave exposure and incident diabetes mellitus (DM) and impaired glucose tolerance (IGT) in middle-aged and older Chinese adults. METHODS: A total of 1803 China Health and Retirement Longitudinal Study participants aged ≥45 years with normoglycemia at baseline were followed from Wave 1 (2011) to Wave 3 (2015). Eighteen extreme-temperature indicators were derived from city-level fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis data. Outcomes were classified according to American Diabetes Association criteria. Generalized linear mixed-effects models (GLMMs) were pooled across five imputed datasets, with Bonferroni correction for multiple comparisons (α = 0.0028) and sensitivity analysis adjusting for individual follow-up duration. RESULTS: All nine heatwave indicators showed odds ratios (ORs) < 1.0 for DM and IGT. HT9 (≥97.5th percentile, ≥4 consecutive days) was the sole Bonferroni-significant result: OR = 0.845 (95% confidence interval [CI]: 0.802-0.890). Coldwave indicators showed no consistent associations. Age significantly modified the HT9 effect (P-interaction = 0.004): adults aged 65-84 showed a stronger inverse association (OR = 0.616) than those aged < 65 (OR = 0.921). CONCLUSION: Prolonged heatwave exposure was consistently associated with reduced diabetes risk, with pronounced age heterogeneity. Replication in larger prospective studies is warranted.

Humans↗

PubMed2026

Innovation-related perception as a key driver of alternative protein acceptance: evidence from an early-stage model for cultivated meat and algae-/microalgae-based alternative protein products in Italy.

Alternative proteins are increasingly considered part of the transition toward more sustainable food systems, yet their diffusion depends critically on consumer acceptance. This study investigates the early-stage acceptance of two alternative protein categories in Italy-cultivated meat and algae-/microalgae-based alternative protein products. Focusing on the first three phases of acceptance, the analysis examines how innovation-related perception (IRP) shapes consumer perceived value (CPV), consumer perceived risk (CPR), and subsequent affective (AFF), cognitive (COG), and conative (CON) responses. Data were collected through an online survey administered to 238 Italian respondents and analysed using partial least squares structural equation modelling (PLS-SEM). The results show that IRP is the main upstream driver of early-stage acceptance in both product domains: more favourable perceptions strongly increase perceived value and reduce perceived risk. In turn, CPV exerts a much stronger influence than CPR on both affective and cognitive attitudes. A tentative cross-model comparison suggests only a descriptive variation in the final transition toward conative acceptance: affective and cognitive responses were both significant in the two models, with a relatively larger affective coefficient for cultivated meat and more balanced coefficients for algae-/microalgae-based products. Overall, the findings support a process-based interpretation of alternative protein acceptance and highlight the central role of innovation-related perception in shaping early consumer responses. These results provide relevant implications for communication strategies, product positioning, and policy actions aimed at improving the acceptability of alternative proteins in food cultures characterised by strong culinary traditions.

Italy↗

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

From commensal to pathobiont: The emergence of virulence-enhanced Escherichia coli in China's food-animal systems - insights with future implications.

A fundamental shift in Escherichia coli epidemiology is being driven by convergence of virulence determinants and antimicrobial resistance within linked human-animal-environment systems. In China, the rapid growth of food-animal production, extensive antimicrobial use, and complex food networks are accelerating the emergence and dissemination of virulence-enhanced E. coli pathobionts. This review synthesizes recent epidemiological, genomics, and outbreak data to characterize China's evolving landscape of food-animal-associated E. coli. We highlight a significant shift from classical pathotypes to hybrid lineages that simultaneously carry virulence factors and last-resort antibiotic resistance determinants, including mcr-1, tet(X4), and blaNDM. These traits disseminate rapidly via plasmid-mediated horizontal gene transfer, facilitating rapid adaptation and enabling cross-sectoral One Health transmission. National surveillance, foodborne outbreak investigations, and whole-genome sequencing data show that food-animal reservoirs are active evolutionary niches that drive pathogen diversity and fitness, rather than serving merely as contamination sources. Whole-genome sequencing also pinpoints high-risk clones (e.g., ST394) and plasmid-mediated co-selection of virulence and AMR. The emergence of hybrid pathotypes (e.g., STEC/ETEC) and AMR-virulence co-selection challenges traditional classification and limits the effectiveness of conventional surveillance approaches. The 2017 colistin ban reduced mcr-1, yet ongoing resistance and emerging tet(X4) demand integrated surveillance. Collectively, these findings call for reconceptualizing E. coli as a dynamic genomic entity embedded within a unified ecological network. Addressing this threat requires an integrated One Health strategy including genomic surveillance, agricultural antimicrobial stewardship, and coordinated food-environment-clinical monitoring to prevent high-risk clone emergence and global spread.

Animals↗

PubMed2026

Rational design of high-productivity perfusion processes for CHO Cells: From growth inhibitory strategies to model-driven optimization.

While perfusion culture for Chinese hamster ovary (CHO) cells offers advantages such as continuous operation and flexibility, it suffers from product loss through cell bleeding and difficulties in reaching high productivity due to sustained rapid cell growth. Growth inhibitory strategies are widely used to enhance productivity in fed‑batch processes; however, their practical implementation and comparative effectiveness in perfusion processes remain insufficiently explored. Meanwhile, process development often relies on costly trial‑and‑error approaches. Here, we systematically compared three growth inhibitory strategies in perfusion culture-low cell‑specific perfusion rate (CSPR), sodium butyrate, and mild hypothermia-with respect to cell growth, metabolism, productivity, and product quality. Genome‑scale metabolic flux sampling analysis revealed that low‑CSPR and sodium butyrate induce a convergent up‑regulation of energy metabolism, correlating with greater gains in specific productivity (qp). Building on this insight, we developed a growth‑kinetic model for the combined low‑CSPR + butyrate strategy, incorporating parameter uncertainty. This model‑guided framework enabled the rational design of two distinct high‑productivity perfusion processes: a sustained mode that achieved robust long‑term stability alongside substantial productivity gains, and a high‑intensity mode that pushed qp and daily volumetric titer to their maxima, with increases of up to 108.94% and 190.36%, respectively, in a model CHO cell line with a moderate baseline productivity. Our study provides a proof‑of‑concept framework for perfusion intensification, from strategy selection to rational process design.

Animals↗

PubMed2026

Cefoxitin versus cefotaxime as empirical treatment of spontaneous bacterial peritonitis in liver cirrhotic patients: randomized controlled clinical trial.

BACKGROUND: Spontaneous bacterial peritonitis (SBP) is a severe complication of cirrhosis requiring immediate empirical antibiotic therapy. Third-generation cephalosporins are the traditional agents of choice; however, increasing clinical failure rates necessitate the evaluation of alternative antibiotics to ensure optimal therapeutic outcomes. The aim was to investigate the efficacy of cefoxitin versus cefotaxime for SBP treatment. METHODS: A randomized clinical trial was conducted on 140 cirrhotic patients with community-acquired SBP at Al-Rajhy Liver University Hospital, Assiut, Egypt. Patients were randomized to receive either cefotaxime (n = 70) or cefoxitin (n = 70), 2 g every 8 h for 5 days. Polymorphonuclear neutrophil (PMN) counts were measured upon admission, on Day 2 and on Day 5. Clinical response rates at Days 2 and 5, development of hepatorenal syndrome, length of stay and mortality were assessed. RESULTS: According to intention-to-treat analysis, clinical response rates at Day 2 were 74.2% in the cefotaxime group and 80% in the cefoxitin group, while at Day 5, they were 71.4% and 74.3%, respectively (P = 0.704). The PMN counts at Days 0, 2 and 5 showed no significant differences between the cefotaxime and cefoxitin groups (P = 0.889, 0.909 and 0.360, respectively). The incidence of hepatorenal syndrome was 7.1% in the cefotaxime group compared with 8.6% in the cefoxitin group (P = 0.753), and mortality was 15.7% and 12.9%, respectively (P = 0.629). CONCLUSIONS: Cefoxitin showed comparable effectiveness to cefotaxime but may be utilized in selected clinically stable SBP patients.

Humans↗

PubMed2026

Evidence-based insights into medial pedicle reduction mammaplasty: A systematic review and meta-analysis.

BACKGROUND: Breast reduction relieves the physical and psychosocial burden of macromastia. Medial pedicle reduction mammaplasty may enhance vascular reliability, preserve nipple-areola complex (NAC) sensation, and sustain upper pole fullness, even in large-volume reductions. The purpose of this study was to assess the outcomes of medial pedicle breast reduction. METHODS: A search across ScienceDirect, Cochrane, and PubMed was conducted. Included studies reported on perioperative outcomes and complications of medial pedicle breast reduction. Data on demographics, surgical variables, complications, sensory recovery, volumetric changes, and patient satisfaction were extracted. Proportion meta-analysis was performed, and odds ratios were calculated for comparison with inferior pedicle breast reduction. RESULTS: Twenty-five studies comprising 1033 patients met the inclusion criteria. Mean BMI ranged from 27 to 42 kg/m2, with mean resection weights between 412 and 3828 g. Mean surgical times ranged from 104 to 204 min. Pooled complication rates were low: infection 1%, seroma 1%, hematoma 1%, fat necrosis 2%, NAC necrosis 1%, dehiscence 8%, and reintervention 5%. Odds of complications did not differ significantly from inferior pedicle reductions. NAC sensation typically recovered by 6-12 months, with no long-term deficits. Volumetric analyses demonstrated stable breast shape after the first postoperative year, with superior upper pole tissue maintained. Patient satisfaction ranged 75-100%, with higher ratings for scar appearance and overall aesthetics in medial pedicle reductions. CONCLUSION: Medial pedicle breast reduction is a well-established and reproducible technique, preserving NAC sensation, achieving stable long-term shape, and enhancing upper pole fullness. It offers satisfactory aesthetic outcomes compared to other traditional methods, even in large-volume reductions.

Humans↗

PubMed2026

New Evidence in Heart Failure: 2026 Update.

Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of HF continues to increase due to population aging, improved survival, and the growing prevalence of cardiovascular, renal, and metabolic comorbidities. Simultaneously, the pace of scientific progress in HF has accelerated considerably. Recent advances have refined our understanding of HF epidemiology, prognosis, and disease trajectories, including emerging concepts of HF improvement, remission, and recovery. The Second Universal Definition of HF has also updated the classification framework, moving beyond the traditional ejection fraction-based categories. HF is now broadly classified into two major phenotypes: heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Novel mechanistic insights highlight the role of inflammation, immune activation, metabolic dysfunction, mitochondrial biology, and multisystem interactions in HF progression. There has also been significant progress in the characterization and management of major comorbidities, including chronic kidney disease (CKD), diabetes, obesity, atrial fibrillation (AF), pulmonary hypertension, frailty, malnutrition, and cancer. Diagnostic innovations include novel biomarkers, multi-omics technologies, artificial intelligence-based approaches, advanced imaging techniques, congestion assessment tools, and emerging digital health solutions. Important advances have occurred in specific HF aetiologies, including cardiomyopathies, cardiac amyloidosis (CA), myocarditis, arrhythmia-induced cardiomyopathy (AiCM), and Chagas cardiomyopathy. Therapeutic developments continue to reshape HF management across the spectrum of left ventricular ejection fraction. Recent evidence has focused on optimization of guideline-directed medical therapy in HFrEF, expansion of evidence-based therapies in HFpEF, and growing roles for sodium-glucose cotransporter-2 inhibitors, finerenone, incretin-based therapies, and transcatheter valve interventions. Collectively, these advances support the transition from a predominantly phenotype-based approach towards a more personalized and biologically informed model of HF care, with the potential to further improve outcomes across the entire HF spectrum.

Journal Article↗

PubMed2026

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence↗

PubMed2026

Reported exposure to news portrayals about mental health problems and their impact: Findings from the 2025 National Survey of Stigma and Discrimination.

OBJECTIVE: Media portrayals of people with mental illness have the power to mitigate or perpetuate stigma related to mental health. This study aimed to investigate reported real-world exposure to news media portrayals about people with mental health problems in the past 12 months and the impact of these. METHODS: Data were from a nationally representative survey of 6032 Australians exploring attitudes towards people with mental health problems. Participants were asked about their exposure to positive news stories about a person with a mental health problem, as well as negative portrayals, in which someone was harmed by a person with a mental health problem. Further questions covered the sources (traditional or social media) and impact of these exposures. RESULTS: Regression models were used to explore sociodemographic predictors of impact. Most participants reported exposure to negative news portrayals (68.4%, 95% confidence interval = [66.9, 69.8]), while fewer reported exposure to positive news stories (33.7%, 95% confidence interval = [32.3, 35.2]). Most people exposed to the negative news stories reported a negative impact (69.0%, 95% confidence interval = [67.2, 70.7]), and most exposed to positive news stories reported a positive impact (80.2%, 95% confidence interval = [77.6, 82.5]). Age and gender were associated with reported impact but not lived experience of mental illness. CONCLUSIONS: Exposure to negative news stories about mental health problems was prevalent. Given their impact on news audiences broadly, negative news stories need to be accurate and responsible to mitigate negative impacts. A renewed focus on generating and promoting positive and stigma-challenging news stories is needed to increase subsequent positive impacts.

Humans↗

PubMed2026

Health bill beneath the plastic feast: A phthalate contamination alert from takeout food containers.

The rapid growth of takeout food consumption in China has raised concerns regarding exposure to phthalic acid esters (PAEs) from food packaging. This study investigated the presence, source, contribution, and health risk of PAEs in commonly used takeout containers. Widespread contamination was observed, with total PAE concentrations ranging from below the limit of detection to 222,000 ng/g. Diisobutyl phthalate (DIBP), dibutyl phthalate (DBP), and bis(2-ethylhexyl) phthalate (DEHP) were identified as the predominant compounds, accounting for 7.50 %, 14.7 %, and 18.7 % of the total concentration, respectively. These PAEs may originated from additives during manufacturing and potential contamination of raw materials. Human exposure assessment showed that daily exposure doses of DIBP, DBP, and DEHP via container ranged from 0.00 to 2340 ng/(kg·day) among frequent takeout consumers, contributing substantially to overall PAE body burdens. To further assess exposure and associated risks, a nationwide online questionnaire survey was conducted across China. Based on this national-scale behavioral dataset, the health risks among Chinese residents were evaluated. Although the modeled non-carcinogenic risks of DIBP, DBP, and DEHP remained within acceptable limits, the simulation suggested that approximately 70 % of participants may experience potential exceedance of the carcinogenic risk threshold for DEHP. The frequency of takeout food consumption was identified as the most important factor affecting PAE exposure. These findings underscore the importance of limiting takeout frequency and reducing reliance on plastic containers to mitigate health risks. This study provides scientific evidence to support the development of safer packaging materials and informs public health strategies.

Phthalic Acids↗

PubMed2026

The potential of clustering methods for pre-test triage in sleep medicine: A systematic review.

Sleep disorders exhibit substantial heterogeneity, and traditional classifications may not fully capture clinically relevant subtypes. Clustering techniques can identify patient subgroups that improve phenotypic characterization and may support personalized management. This systematic review evaluated the application of clustering in sleep medicine, with particular focus on its potential use as a pre-test triage tool prior to formal sleep testing. PubMed/MEDLINE, Embase, Web of Science, and Scopus were searched to February 2025. Eligible studies applied clustering to classify sleep disorders in adults. Two reviewers independently conducted screening, data extraction, and risk-of-bias assessment using QUADAS-2. The protocol was registered on PROSPERO. Fifty-one studies (1983-2025) were included, predominantly focused on obstructive sleep apnea (OSA) (n = 38, 74%). Hierarchical clustering (n = 20) and K-means clustering (n = 14) were the most frequently used techniques. Internal validation was reported in only 18% of studies, and external validation was reported in only 1 study. Seven studies relied exclusively on baseline clinical, demographic, or questionnaire data, representing pre-test scenarios, whereas most incorporated polysomnography-derived variables, limiting their applicability to early clinical stratification. Hierarchical clustering was the most commonly applied method; however, the overall lack of validation limits confidence in the robustness and clinical applicability of identified phenotypes. The potential role of clustering as a pre-test triage strategy remains largely unexplored, as most studies focused on post-diagnostic phenotyping and were affected by incorporation bias. Future research should prioritize pre-test clinical variables, rigorously validate internally and externally, and adopt standardized methodological and reporting practices to facilitate clinical translation.

Humans↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

A 12-week, double-blind, quasi-randomized, placebo-controlled study to evaluate the efficacy and safety of Coleus forskohlii (Forcslim) on body weight loss.

BACKGROUND: Overweight and obesity have emerged as a global epidemic, significantly impacting human health. Traditional usage and growing scientific evidence suggest that Coleus forskohlii extract (Forcslim) may aid in reducing excess body weight and fat. This study aimed to evaluate the efficacy and safety of Forcslim supplementation in overweight individuals. METHODS: A quasi-randomized, double-blind, placebo-controlled clinical trial was conducted in 60 overweight subjects aged 20-70 years over a period of 12 weeks. The participants were assigned to receive either Forcslim or placebo. The key outcome measures included body weight, body mass index (BMI), body composition, and anthropometric parameters. Additionally, lipid profile parameters and safety markers (including metabolic, hepatic, and cardiovascular indicators) were assessed throughout the study duration. RESULTS: Compared to the placebo group, the Forcslim group showed significant reductions in waist circumference (-1.83 cm; p < 0.01) and body weight (-1.93 kg; p < 0.001). Significant improvements in anthropometric parameters were observed exclusively in the Forcslim group. Furthermore, triglyceride (TG) levels were significantly reduced (p < 0.01), while high-density lipoprotein (HDL) levels showed a significant increase (p = 0.001). No clinically significant changes were observed in metabolic markers, liver and muscle enzyme levels, heart rate, blood pressure, or reported adverse effects, indicating a favorable safety profile. CONCLUSIONS: Forcslim demonstrated significant anti-obesity effects, including reductions in body weight, waist circumference, and improvements in the lipid profile. These findings suggest that C. forskohlii extract supplementation may serve as a safe and effective alternative to synthetic anti-obesity drugs.

Humans↗

PubMed2026

Angiotensin II regulates anxiety and social-affective top-down and bottom-up attention control in a sex-dependent manner.

BACKGROUND: The renin-angiotensin system (RAS) has been increasingly recognized as potent modulator of cognitive and affective functions, with angiotensin II type 1 receptor (AT1R) antagonists emerging as repurposing candidate for anxiety and stress-related disorders. However, it remains unclear whether transient AT1R blockade modulates emotional attentional control and whether these effects are sex-dependent. METHODS: We conducted a preregistered, randomized, double-blind, placebo-controlled pharmacological eye-tracking study in 79 healthy adults (males and females) and determined effects of transient AT1R blockade via losartan (50 mg) on emotional attention control using a validated anti-saccade paradigm with social (emotional faces) and non-social stimuli. Treatment effects on state anxiety and oculomotor responses were characterized using traditional metrics and a novel trial-history informed dynamic control framework. RESULTS: Losartan reduced state anxiety irrespective of sex but induced sexually dimorphic effects on attentional control. In females, losartan enhanced performance by reducing endpoint error without altering latency. Conversely, in males, losartan increased endpoint error and prolonged latency of the first correct saccade. Trial-history analyses revealed losartan reduced error probabilities following errors and repeat trials in both sexes. Yet, following correct trials, females receiving losartan maintained lower error probabilities, while males exhibited higher errors, potentially reflecting failure to disengage from effortful control. CONCLUSIONS: The RAS modulates anxiety and attentional control, the latter sex-dependently. AT1R blockade reconfigures attentional processing and adaptive control, suggesting sex-specific therapeutic potential in disorders characterized by excessive anxiety and attentional dysregulation. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov; https://clinicaltrials.gov/;NCT06329050.

Humans↗

PubMed2026

Cross-kingdom dynamics of the subgingival bacteriome and mycobiome: A pilot study on the effects of a novel HA-H₂O₂-Glycine formulation to treat periodontitis.

OBJECTIVES: Traditional periodontal therapy primarily focuses on bacterial biofilm control; however, recent evidence also suggests a critical role for the oral mycobiome. This study evaluated the clinical and ecological impact of a novel mouthwash formulation containing hyaluronic acid (HA), hydrogen peroxide (H2O2), and glycine on periodontal patients METHODS: This prospective, randomized split-mouth trial included 13 adult participants with periodontitis treated with HA-H2O2-glycine formula (BMG0703A) used twice a day for seven days. Subgingival plaque samples were collected from periodontal pocket and healthy control sites at baseline (T0) and one-week post-treatment (T1). Microbial and fungal communities were characterized using Next-Generation Sequencing (NGS) of the 16S rRNA and ITS2 regions. Linear Mixed Models (LMM) and Spearman correlation were used to assess taxonomic shifts and cross-kingdom relationships. RESULTS: Sequencing revealed a promising ecological shift: the bacteriome shifted from anaerobic dominance (Olsenella, Peptostreptococcus) toward a health-associated aerobic profile, with Rothia near-doubling (11.91% to 22.68%). The mycobiome underwent a "normalization" effect: Candida abundance decreased significantly (22.8% to 9.1%), while fungal Shannon diversity in pockets returned to healthy-site levels. Inter-kingdom analysis identified antagonistic relationships between expanding commensal bacteria and opportunistic fungi, suggesting that the intervention may help re-establish a protective bacterial niche. CONCLUSIONS: The HA-H2O2-glycine formulation seems to facilitate a rapid, cross-kingdom modulation of the subgingival niche. By reducing anaerobic pathogens and normalizing the mycobiome it appear to induce short-term changes, suggesting potential as adjunctive strategy in periodontal management. CLINICAL SIGNIFICANCE: The present work underlines the possible cross-Kingdom effects of a novel compound.

Humans↗

PubMed2026

The Potential Role of Mesenchymal Stem Cell Therapy for Moderate-to-Severe Atopic Dermatitis: A Systematic Review and Meta-Analysis of Human Clinical Trials.

Despite currently available treatment options for moderate-to-severe atopic dermatitis (AD), some patients fail to achieve adequate disease control. Emerging evidence suggests that mesenchymal stem cells (MSCs) may represent a promising therapeutic option. This systematic review and meta-analysis included four randomized controlled trials (RCTs) and one non-randomized clinical trial. Eligible studies evaluated patients with moderate-to-severe AD treated with MSCs derived from human umbilical cord blood, autologous adipose tissue, and allogeneic bone marrow. PubMed, Embase, and Cochrane were searched from inception to December 2025. Primary outcomes included the proportion of patients achieving ≥50% and ≥75% improvement from baseline in the Eczema Area and Severity Index (EASI) and safety outcomes. The meta-analysis included 236 participants. The pooled EASI-50 response rate at week 12 was 46.76% (95% confidence interval [CI]: 32.36% to 61.72%). EASI-75 response rates were 17.41% (95% CI: 5.56% to 43.03%) at week 12 and 23.97% (95% CI: 16.48% to 33.50%) at week 16. The pooled incidence of treatment-emergent adverse events was 26.86% (95% CI: 19.56% to 35.68%), with infections and infestations 7.97% (95% CI: 4.11% to 14.88%) and gastrointestinal disorders 3.52% (95% CI: 1.33% to 9.01%) being the most frequently reported. MSC-based therapy shows early promise as a potential treatment for moderate-to-severe AD, offering a possible alternative to traditional therapies. However, the current evidence is largely based on small clinical trials, underscoring the necessity for large-scale RCTs to establish the efficacy and safety of MSC-based therapy in broader patient populations.

Humans↗