Advancing Open Science

Dynamic membrane bioreactors (DMBRs) are promising systems for continuous biohydrogen production because they enable effective biomass retention under short hydraulic retention time (HRT) conditions. In this study, a dynamic membrane bioreactor coupled with electro-fermentation (DMBR-EF) was operated for 59 days to investigate the effect of applied voltage on biohydrogen production and metabolic flux regulation. The reactor was sequentially operated at 0 (no applied voltage), 0.2, 0.4, 0.6, 0.8, and 1.0 V using glucose as a model substrate. The highest hydrogen production rate (HPR) and hydrogen yield (HY) were achieved at 0.2 V, reaching 15.35 ± 0.48 L H₂/L/d and 1.54 ± 0.05 mol H₂/mol glucose_added, respectively, which were 33.71% and 33.91% higher than those of the 0 V control. At 0.2 V, residual glucose and effluent volatile suspended solids (VSS) were minimized, while butyric acid (HBu) formation was enhanced and lactic acid (HLa) accumulation was suppressed. In contrast, voltages above 0.4 V reduced hydrogen recovery by shifting metabolic flux toward HLa, propionic acid (HPr), formic acid (HFo), and homoacetogenic pathways. Microbial analysis showed that Clostridium dominated under all conditions, but voltage application selectively altered the relative abundance and metabolic output of Clostridium-related amplicon sequence variants (ASVs). These results indicate that mild electrochemical stimulation at 0.2 V effectively enhances continuous biohydrogen production by promoting butyric acid-type fermentation, suppressing lactic acid accumulation, and reducing hydrogen loss through competing metabolic pathways in DMBR-EF systems.

Recurrent urinary tract infection (rUTI) continues to pose a formidable clinical challenge, largely owing to the rapid clearance of therapeutic agents from the bladder caused by short intravesical residence time and periodic urinary voiding. Although intravesical drug delivery has emerged as a promising local therapeutic strategy, conventional liquid instillations and physically crosslinked hydrogels frequently fail to sustain structural integrity and prolonged drug release within the dynamically changing bladder microenvironment. Herein, we develop a photocrosslinkable, pH-responsive intravesical floating drug delivery system (iFDDS) for sustained antimicrobial delivery. This system is fabricated using diacrylated Pluronic F127 (F127DA) as the core network-building component. The covalently crosslinked F127DA network confers superior mechanical stability while preserving amphiphilic micellar domains that enable efficient loading of hydrophobic drugs. A tertiary amine-based pH-responsive crosslinker (CLMA) is further integrated into the hydrogel matrix, endowing iFDDS with enhanced swelling capacity under the mildly acidic microenvironment. Additionally, lyophilization-induced porous architecture reduces the apparent density of the iFDDS below that of urine, achieving stable flotation for over 48 h and effectively mitigating the risk of urinary tract obstruction. The optimized iFDDS exhibits favorable catheter deliverability, shear-thinning rheological behavior adaptable to dynamic fluid conditions, and excellent biocompatibility with bladder epithelial cells. Upon loading with rifampicin, the iFDDS demonstrates potent and sustained antibacterial efficacy against Escherichia coli. This study establishes a robust, environment-adaptive platform for intravesical therapy, offering a viable strategy to address the short residence time limitation of conventional formulations and improve the therapeutic management of rUTI.

Background/Objectives: The paper aimed to synthesize the diagnostic performance of artificial intelligence (AI) methods for classifying breast lesions on contrast-enhanced breast MRI and to estimate a pooled area under the receiver operating characteristic curve (AUC). Methods: This targeted evidence synthesis and meta-analysis was informed by PRISMA 2020 reporting principles where applicable. Eligible studies were drawn from an investigator-supplied corpus of 12 primary manuscripts and assessed against predefined criteria. MEDLINE/PubMed, Embase, and Web of Science were consulted through October 2025 to contextualize the literature and verify bibliographic and study details; additional database records were not screened for eligibility. We included studies applying machine learning or deep learning to contrast-enhanced breast MRI for benign-versus-malignant lesion classification and reporting an AUC on an independent test set, external validation set, or patient-wise cross-validation. AUCs were pooled on the logit scale using an inverse-variance DerSimonian–Laird random-effects model, and heterogeneity was quantified using I². Results: Nine studies met the criteria for quantitative synthesis (evaluation-set sizes, 60–3936). The pooled random-effects AUC was 0.898 (95% CI, 0.875–0.918), with substantial heterogeneity (I² = 88.1%) and a 95% prediction interval of 0.824–0.943, indicating that performance may vary meaningfully across settings. Conclusions: AI models showed promising discriminative performance within this targeted corpus, but substantial heterogeneity, differences in unit of analysis, approximated variance estimates, and limited external institutional validation temper confidence in generalizability. The pooled AUC should be interpreted descriptively, and future studies should prioritize rigorous multi-institutional external validation, transparent reporting, and prospective reader- or workflow-impact evaluation before routine clinical deployment.

Background/Objectives: Pain intensity and depressive symptoms are closely associated in adults with chronic pain (CP), contributing to greater disability, poorer treatment outcomes, and increased healthcare costs. However, the mechanisms underlying this symptom-level relationship remain incompletely understood. This systematic review and meta-analysis aimed to (i) identify all candidate factors mediating the effect of pain intensity on depressive symptoms, or vice versa, in adults with CP and (ii) estimate the magnitude of indirect, direct and total effects reported across eligible studies. Methods: Seven databases were searched in May–July 2023 and updated in May–June 2024. Observational studies and randomized controlled trials evaluating mediators of the relationship between pain intensity and depressive symptoms, or vice versa, in adults with CP were eligible. Data extraction and methodological appraisal were performed independently by three reviewers. Findings were synthesized narratively using vote counting and displayed using harvest plots. When appropriate, meta-analyses were conducted using regression coefficients, standard errors and sample sizes to estimate pooled indirect, direct and total effects. Results: The search identified 6826 studies, of which 34 (47 mediation models) met the inclusion criteria. Twenty-nine studies (combined n = 13,587) examined the effect of pain intensity on depressive symptoms, identifying 24 candidate mediators. Exploratory meta-analyses were feasible only for pain catastrophizing (indirect effect [IE]: β = 0.150; 95% confidence interval [CI]: 0.066, 0.233) and helplessness (IE: β = 0.101; CI: 0.066, 0.137). The pooled estimate for pain catastrophizing showed substantial heterogeneity and was highly influenced by a single study. Sleep quality, pain self-efficacy and pain interference showed preliminary evidence of mediation in narrative synthesis. Nine studies (combined n = 1359) investigated the effect of depressive symptoms on pain intensity, identifying 12 candidate mediators. Pain catastrophizing was the most consistently supported mediator, although quantitative synthesis was not feasible. Conclusions: Several potentially modifiable mediators of the pain–depression relationship were identified and may represent targets for multidisciplinary interventions. However, quantitative findings remain preliminary because of the limited number of studies, substantial heterogeneity for some mediators, and the predominance of cross-sectional evidence. Robust three-wave longitudinal mediation studies with adequate statistical power, standardized measures and reporting, and theory-driven models are needed to establish the temporal validity of candidate mediators and strengthen causal inferences.

Chlorophenylacetonitriles are known as one of the emerging nitrogenous disinfection byproducts (N-DBPs) in chlorinated drinking water due to their concerned cytotoxicity and genotoxicity compared to regulated carbonaceous DBPs. However, under low-dose exposure, the in vivo pathological consequences of chlorophenylacetonitriles remain largely unresolved. Here, C57BL/6J mice were exposed to 2-chlorophenylacetonitrile (2-CPAN) via drinking water (100 ug/L) for six months, and an integrated histopathological and genome-wide transcriptomic approach was employed to mechanistically characterize its multi-organ toxicological consequences. 2-CPAN ingestion significantly suppressed body weight (35.9 ± 2.0 g vs. 47.6 ± 11.6 g, p < 0.05) and induced severe gastroenteropathy—including gastric lamina propria inflammatory infiltration, intestinal villous blunting, crypt disorganization, transmural mononuclear infiltration, and abrogating epithelial barrier integrity. Intestinal barrier failure drove portal translocation of luminal PAMPs, potentially triggering splenic white pulp atrophy, red/white pulp boundary dissolution, and parenchymal changes consistent with fibrotic remodeling. Splenic RNA sequencing revealed a bipartite transcriptomic reprogramming: upregulated pathways were enriched in the ribosome, MAPK signaling, cytokine–cytokine receptor interaction, and chemokine signaling pathways. A proteotoxic stress module (Hspa1a, 9.4-fold; Hspa1b, 10.2-fold) and a chemokine effector hub (Ccl2, 3.43-fold; Ccl5, 2.9-fold; Ccl19, 2.58-fold; Ccl21a, 2.15-fold) were identified by the STRING network. Downregulated pathways converged on cell cycle suppression, with concurrent loss of Ccne1/Ccne2 and Cdc6 (G1/S block), Ccnb1 and Plk1 (G2/M arrest), and Rrm2/Tars3/TrnM (dNTP and aminoacyl-tRNA starvation), collectively forcing splenic lymphocytes into irreversible proliferative failure. These findings provide the first mechanistically resolved in vivo evidence that chronic 2-CPAN exposure drives a potential gut–spleen toxicological axis, underscoring the urgent need to incorporate organ endpoints by long-term exposure into N-DBP risk assessment.

This paper proposes a governance-aware methodological framework for the integration of Cognitive Artificial Intelligence into marine CAD environments. Unlike existing approaches that focus on isolated optimization or prediction tasks, the proposed framework introduces a structured architecture combining engineering knowledge corpora, hybrid AI reasoning, and CAD-based interaction within a traceable and regulatory-aware workflow. The contribution of this work is methodological rather than domain-exhaustive. The framework is illustrated through a conceptual pipe routing use case, selected as a representative high-constraint design subsystem involving spatial reasoning, compliance verification, and iterative coordination. A normalized performance evaluation model is defined to estimate improvements in design efficiency, convergence, compliance validation and rework reduction. Although the validation is conceptual, the results are consistent with reported improvements in AI-assisted engineering workflows. The proposed framework gives a basis for integrating AI into marine CAD environments, aligned with newer digital ship design and Shipyard 4.0 approaches.

Vancomycin-resistant enterococci (VRE) have emerged as major nosocomial pathogens worldwide, primarily due to the acquisition of the vanA gene, which confers high-level resistance to vancomycin. Rapid detection of the vanA gene, which is associated with vancomycin resistance, is crucial for timely clinical management and infection control. Through this research, we aimed to develop an assay combining loop-mediated isothermal amplification and a lateral flow Dipstick (LAMP-LFD) for the rapid detection of the vanA gene in VRE. Genomic DNA was extracted and amplified from 100 clinical urine samples by LAMP targeting vanA under optimized, constant-temperature conditions, with the amplified product then detected using a lateral flow Dipstick assay based on probe pairing. The diagnostic performance of the LAMP-LFD method was evaluated and compared with a conventional PCR reference method. The LAMP-LFD assay successfully detected the vanA gene in all positive samples, with negative samples showing no assay cross-reactivity with 12 species of bacteria commonly found in clinical settings. The developed LAMP–LFD assay showed promising diagnostic performance for detecting the vanA gene in Enterococcus isolates, demonstrating complete agreement with the reference PCR method in this study. Owing to its rapid turnaround time, simplicity, and visual readout, the assay has potential as a molecular screening tool for VRE. However, further validation in larger, multicenter studies and comparison with phenotypic antimicrobial susceptibility testing are required before routine clinical implementation.

Objectives: The importance of sleep disturbance as a component of supportive care in pediatric oncology has recently been recognized, but the characteristics of sleep for this particular disease category have yet to be elucidated. Methods: This cross-sectional study included 54 pediatric patients diagnosed with leukemia or lymphoma and 56 age- and sex-matched clinically stable children attending routine pediatric hematology outpatient follow-up for benign hematological conditions. Sleep was assessed using the Children’s Sleep Habits Questionnaire (CSHQ). Global and domain-specific sleep scores were compared. Multivariable linear regression was used to identify correlates of global sleep disturbance, including parental educational attainment. Within the patient group, recent hospitalization and corticosteroid exposure were modeled separately because of strong collinearity. Results: Patients had higher global CSHQ scores than the comparison group (53.56 ± 8.28 vs. 49.07 ± 8.09, p = 0.005; Cohen’s d = 0.55). Differences were most evident in sleep anxiety and parasomnias (exploratory subscale findings), whereas sleep duration did not differ significantly. In the whole-sample model, patient status (B = 4.16, p = 0.006) and higher parental educational attainment (B = −2.13, p < 0.001) were independently associated with global sleep disturbance. Within the patient group, recent hospitalization was the strongest clinical correlate of sleep burden (B = 11.18, p < 0.001; R² = 0.433). Corticosteroid exposure was associated with higher sleep disturbance only in models excluding hospitalization. Conclusions: Children with leukemia and lymphoma showed a selective parent-reported sleep disturbance pattern characterized mainly by sleep anxiety and parasomnias rather than reduced sleep duration. Recent hospitalization and parental educational attainment appear to be important correlates of sleep burden in pediatric hematology-oncology care.