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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

Comparing trajectories of cognitive functioning in treatment-resistant and non-resistant depression: a multicentre linear mixed-effects analysis.

BACKGROUND: Impaired cognitive functioning is a severe symptom in major depressive disorder (MDD). Recent evidence suggests it may be a central characteristic in its treatment resistant form (TRD), potentially constituting a clinical marker for treatment resistance and a target amenable to intervention. To date, cognitive functioning in TRD remains poorly understood and longitudinal investigations are scarce. METHODS: This observational prospective cohort study, including 320 patients diagnosed with MDD from the multicentre PROMPT study, examined differences in cognitive functioning between 118 TRD and 202 non-TRD patients over a period of twelve weeks in a real-world setting, using linear mixed modelling. Patients that failed to respond to at least two prior antidepressants trials at baseline were classified as TRD. RESULTS: TRD patients showed significantly poorer baseline performances than non-TRD patients in attention/processing speed (β = -0.45; 95%CI[-0.70, -0.19]; FDR-p = 0.003) and verbal memory (β = -0.45; 95%CI[-0.72, -0.18]; FDR-p = 0.003). Significant time × group interactions were observed in motor speed and verbal fluency tasks. Post-hoc-analyses revealed stagnation in TRD patients and significant improvement in non-TRD patients. Across all other tasks improvement was observed in both groups, and random effects showed large heterogeneity between patients, indicating notable individual differences in cognitive performances. CONCLUSIONS: The results suggest distinct recovery patters between non-TRD and TRD patients, and diminished functioning in TRD patients at the domain level. However, intact and diminished performances likely occur in both groups, warranting further investigation of cognitive heterogeneity. These short-term findings highlight the need for more comprehensive longitudinal research on cognition in TRD.

Humans↗

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

Viral replication through phase separation: Cytosolic and nuclear condensates.

Replication of many RNA and DNA viruses occurs within specialized intracellular hubs organized as membraneless biomolecular condensates (BCs) driven by liquid-liquid phase separation. As obligate intracellular parasites, viruses depend on the host cell machinery to complete their replication cycles and therefore actively remodel the intracellular environment to favor viral genome replication, transcription, and assembly. Cytosolic and nuclear phase-separated replication compartments (RC) provide concentrated and dynamic platforms that promote efficient interactions between viral genomes and viral or host proteins essential for infection. The formation of viral replication BCs is typically facilitated by viral proteins enriched in intrinsically disordered regions and low-complexity domains, which enable multivalent interactions with viral nucleic acids and cellular factors. These interactions are mediated by diverse biophysical forces, including hydrophobic and π interactions, hydrogen bonding, molecular crowding, and osmotic effects. Throughout infection, viral BCs remain highly dynamic, allowing continuous exchange of components and functional maturation of replication hubs. Their properties and activities are further regulated by post-translational modifications of viral and host proteins, such as phosphorylation, acetylation, and methylation. In this review, we summarize current evidence supporting liquid-liquid phase separation as a central organizing principle of viral RCs. We focus on representative RNA and DNA viruses that replicate in the cytosol or nucleus, highlighting virus-specific strategies, conserved mechanisms, and the consequences of BC formation for viral replication efficiency, host antiviral responses, and therapeutic intervention.

Phase Separation↗

PubMed2026

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans↗

PubMed2026

Temporal redistribution of control reveals age-related differences in task switching at the level of preparation.

Task-switching studies often report minimal age-related differences in switch costs, leading to the conclusion that switching-related control processes are relatively preserved in aging. However, this conclusion is based on paradigms that confound preparatory and execution processes. This study examined whether age-related differences in semantic task-set reconfiguration may be underestimated due to this confound. In Experiment 1 (36 young and 30 older adults), participants performed an externally paced task-switching paradigm without control over preparation. In Experiment 2 (28 young and 28 older adults), a self-paced paradigm allowed participants to initiate stimulus onset, enabling measurement of preparation time. Across both experiments, reaction time (RT) and error rate (ER) showed reliable age effects but no interactions between age and condition, whereas switching-related condition effects varied across measures and experiments. The expression of switching-related costs differed across measures and task structures. Local switch costs were expressed in ER in Experiment 1 but in RT in Experiment 2. Global switch costs (all-switch vs. all-repeat) were observed in execution measures only in Experiment 1. In Experiment 2, preparation time showed reliable mixing, local, and global switching effects, with age-related amplification emerging specifically for global switching. These findings indicate that switching-related costs are redistributed across processing stages and behavioral measures. The results suggest that age-related modulation of semantic task-set reconfiguration may emerge more clearly during preparation than task execution, particularly under continuous switching demands. Preparation time is interpreted cautiously as reflecting participant-regulated preparatory processes rather than a pure measure of preparation efficiency.

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

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

Three-Dimensional Fracture Mapping of the Terrible Triad of the Elbow: Morphological Characteristics and Clinical Implications.

BACKGROUND: The morphology of fractures in the terrible triad of the elbow (TTE) is complex, and precise management relies on a profound understanding of this morphology. This study aims to systematically analyze, for the first time, the distribution and morphological characteristics of TTE fracture lines using three-dimensional (3D) imaging technology. METHODS: Clinical data and thin-slice CT scans of 112 patients with TTE from January 2021 to December 2024 were retrospectively included. 3D fracture models were reconstructed using Mimics software. Virtual reduction and standardized alignment were performed using 3-matic software. Fracture lines were mapped onto standard ulnar and radial templates, and 3D fracture heat maps were generated using the E-3D software to demonstrate the high-frequency distribution zones of the fracture lines visually. Statistical analysis was performed using SPSS software (version 21.0, IBM Corp., Armonk, NY, USA). Continuous variables were compared using one-way analysis of variance (ANOVA), and categorical variables were compared using the chi-square test (χ2 test). A two-tailed p < 0.05 was considered statistically significant. RESULTS: The study revealed distinct patterns in the distribution of TTE fracture lines. In the coronoid process, the fracture "hot zone" presented as an annular high-density band extending from the lateral middle aspect to the tip. In the radial head, an oblique high-density band was observed in the anterolateral quadrant of the articular surface. The radial neck exhibited a circumferential high-density zone, which was most prominent in the anterolateral aspect. Statistical analysis indicated a significant correlation between age and fracture complexity; the proportion of Regan-Morrey type III coronoid fractures and Mason type III radial head fractures was significantly higher in elderly patients (> 60 years) (p < 0.05), suggesting that advanced age is a significant risk factor for complex fractures. CONCLUSION: This study is the first to visually reveal the Collaborative Distribution Patterns of TTE fracture lines using 3D fracture mapping technology. This model provides morphological evidence for understanding the injury mechanism of TTE and offers an anatomical framework that may assist surgeons in individualizing surgical approaches and fixation strategies.

Humans↗

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

A STORM-based protocol for nanoscale imaging and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber.

Stochastic Optical Reconstruction Microscopy (STORM) enables nanoscale mapping of molecular components beyond the diffraction limit; however, its reproducible implementation in hydrophobic polymer matrices remains challenging because fluorescence-labeling specificity, fluorophore photoswitching, three-dimensional localization, chromatic registration, and quantitative image analysis must be carefully controlled. This protocol presents a standardized experimental workflow for dual-color labeling, astigmatism-based three-dimensional STORM acquisition, and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber (NR). The workflow covers sample pretreatment, Cy5 NHS ester labeling of protein-associated primary amines, DiI labeling of phospholipid-rich domains, STORM imaging-buffer preparation, three-dimensional single-molecule localization, dual-channel registration, generation of standardized xy projections, aggregate-size analysis, and projected lateral spatial correlation assessment. Reproducibility is supported by defined acquisition and localization criteria, three independent sample preparations with at least five fields of view analyzed per condition, and unlabeled, single-color, dye-only matrix, and processing-associated Cy5 controls. Mean lateral localization precisions of 11.8 ± 2.3 nm for Cy5 and 13.5 ± 2.9 nm for DiI were obtained, while two-dimensional Fourier ring correlation analysis of the xy projections yielded effective lateral image resolutions of approximately 25 and 28 nm, respectively. Image-based particle segmentation and localization-coordinate-based density-based spatial clustering of applications with noise (DBSCAN) were applied to standardized xy projections as complementary quantitative approaches. Application of the protocol to untreated, centrifuged, and protease-treated NR samples demonstrated treatment-associated changes in the detected abundance and projected size distributions of protein- and phospholipid-associated aggregates, together with a non-monotonic change in their projected lateral spatial correlation. These observations describe alterations in nanoscale organization but do not, by themselves, establish stable protein-phospholipid complex formation. Unlike previous studies that primarily demonstrated the feasibility of STORM imaging in rubber materials, the principal contribution of this work is an end-to-end, step-by-step protocol incorporating defined controls, three-dimensional localization, image-quality metrics, chromatic-registration procedures, and complementary quantitative-analysis pipelines for non-expert users. The workflow may be adaptable to other hydrophobic polymers and soft-material systems after appropriate optimization and validation.

Rubber↗

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

Acupuncture improves depressive symptoms and prefrontal cortical function in mild to moderate depressive disorder: A randomized sham-controlled trial and fNIRS study.

BACKGROUND: Depressive disorder is a common mental illness associated with substantial functional impairment. Although pharmacotherapy is widely used, its effectiveness is often limited by adverse effects and poor adherence. Acupuncture has been increasingly applied as a complementary treatment for depression, and its neurobiological characteristics remain unclear. OBJECTIVE: This randomized, sham-controlled trial aimed to evaluate the clinical efficacy of acupuncture for mild to moderate depressive disorder and to investigate its effects on prefrontal cortical function using functional near-infrared spectroscopy (fNIRS). METHODS: Patients with mild to moderate depressive disorder were randomly assigned to a real acupuncture (RA) group or a sham acupuncture (SA) group and received standardized treatment for 8 weeks. Clinical outcomes were assessed using the Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), Short Form-36 Health Survey (SF-36), and a traditional Chinese medicine syndrome score. A subset of participants underwent fNIRS assessment during resting-state and task-based conditions to evaluate prefrontal cortical activation and functional connectivity. RESULTS: Compared with baseline, the RA group showed significant reductions in SDS and SAS scores and significant improvements in SF-36 emotional domains, with effects emerging at Week 4 and persisting up to 12 weeks after treatment. Improvements were greater and more stable in the RA group than in the SA group. fNIRS analyses revealed enhanced activation in dorsolateral and medial prefrontal regions and strengthened prefrontal functional connectivity following acupuncture, whereas neural changes in the SA group were limited. CONCLUSION: Acupuncture is effective for improving depressive and anxiety symptoms and quality of life in patients with mild to moderate depressive disorder. Modulation of prefrontal cortical activation and connectivity may underlie its antidepressant effects.

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↗

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↗