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Comparing the efficacy of chlorhexidine and povidone-iodine for surgical site disinfection: a systematic review and meta-analysis from randomized controlled trials.

BACKGROUND: Randomized controlled trials report conflicting evidence on the efficacy of different skin disinfectants for preventing surgical site infection (SSI). METHODS: We systematically searched PubMed, Web of Science, Cochrane Library, and Embase for RCTs published up to February 2025 comparing preoperative skin disinfection with povidone-iodine (PVI) versus chlorhexidine (CH). Primary outcomes were overall, superficial, deep, and organ/space SSI rates. Secondary outcomes included hospital stay, readmission, and reoperation. RESULTS: CH was superior to PVI in preventing overall SSI (26 studies, n = 29,356; RR: 0.89; 95% confidence interval [CI]: 0.80 to 0.99). The overall SSI incidence rate in the CH group was 7.1% (1,045/14,677), compared with 7.8% (1,152/14,679) in the PVI group, equating to an 11% reduction in relative risk and a 0.7% reduction in absolute risk. The number needed to treat to prevent one SSI was 143. CH demonstrated superiority over PVI in preventing superficial SSI (13 studies, n = 16,867; RR: 0.77; 95% CI: 0.64 to 0.92), but not for deep SSI (11 studies, n = 15,842; RR: 1.00; 95% CI: 0.77 to 1.29) or organ SSI (9 studies, n = 9,471; RR: 1.17; 95% CI: 0.89 to 1.53). No significant differences were found in hospital stay, readmission, or reoperation rates between the two groups. CONCLUSION: CH demonstrates statistical superiority over PVI in preventing overall and superficial SSI, though the absolute clinical benefit is modest. No significant differences were observed for deep or organ/space SSI, nor for secondary outcomes including hospital length of stay, readmission, or reoperation rates.

Humans

Efficacy and Safety of the Dual Glucagon-Like Peptide-1 and Glucagon Receptor Agonist Mazdutide in Predominantly Chinese Adults With Obesity and/or Type 2 Diabetes: A Systematic Review and Meta-Analysis.

AIM: To assess the effects of mazdutide on body weight, HbA1c, metabolic outcomes, and adverse events in adults with overweight/obesity and/or type 2 diabetes (T2D). METHODS: This systematic review and meta-analysis included randomized controlled trials (RCTs) comparing mazdutide with placebo or active comparators in adults with overweight/obesity and/or T2D, identified through PubMed, Scopus, Web of Science, and ClinicalTrials.gov to 20 February 2026. Co-primary outcomes were percent change in body weight and change in HbA1c. Secondary outcomes included other weight-related and metabolic outcomes, as well as safety. Random-effects models were used to generate pooled mean differences (MDs) or risk ratios with 95% confidence intervals, and the certainty of the evidence (COE) was assessed using GRADE. RESULTS: Nine RCTs (N = 2292; most with low risk of bias) were included. In overweight/obesity without diabetes, mazdutide 3, 4, and 6 mg reduced body weight more than placebo (MDs -6.56%, -9.92%, and -11.1%, respectively; very low COE due to substantial heterogeneity and few trials). In T2D, mazdutide 4 and 6 mg reduced body weight and HbA1c versus placebo (moderate COE) and also outperformed dulaglutide for both outcomes. Mazdutide also improved waist circumference, lipids, liver enzymes, and uric acid levels. Gastrointestinal adverse events were more frequent, but serious adverse events and treatment discontinuation rates were comparable with those of the comparators. CONCLUSIONS: Mazdutide was associated with dose-dependent reductions in body weight and HbA1c, with broader metabolic benefits in predominantly Chinese adults with obesity and/or T2D. Longer-term, multi-ethnic studies are needed to confirm durability, generalizability, and cardiovascular safety.

Humans

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

Humans

Do wound protectors reduce contamination in total shoulder arthroplasty? A randomized controlled trial.

HYPOTHESIS: Cutibacterium acnes is the most frequent cause of shoulder prosthetic joint infection with skin edges as a source of wound contamination. The primary purpose of this study was to determine if the use of a wound protector device decreases the deep wound bacterial colonization in primary shoulder arthroplasty. The secondary purpose was to assess the effect of device usage on deltopectoral muscle and cephalic vein injury. METHODS: This was a prospective, randomized controlled trial. A total of 100 patients undergoing primary total shoulder arthroplasty were enrolled and randomized into 2 groups: a wound protector group and a control group. Five patients withdrew from the study, leaving 48 patients in the wound protector group and 47 controls. Three deep wound culture swabs were taken after final arthroplasty implantation. The surgeon also graded deltoid, pectoralis major, and cephalic vein injury on a 0-3 scale based on modification to the Tscherne classification of soft tissue injury. The primary outcome of this study was positive culture results for C acnes. Secondary outcomes included total bacterial culture positivity as well as soft tissue injury grades. A subanalysis removing likely contaminant positive cultures (growth >7 days and 1 colony only) was also performed. Comparisons between groups were made using Fisher exact test for categorical outcomes and t tests and Mann-Whitney U tests for continuous variables. RESULTS: The use of a wound protector did not result in any significant differences compared with controls in the rate of positive cultures for C acnes (15% vs. 21%, P = .593) or all bacteria (15% vs. 26%, P = .304). Removing likely contaminant positive cultures did not demonstrate any significant difference in culture positivity (9% vs. 17%, P = .355, for C acnes; 9% vs. 19%, P = .231, for all bacterial species). The wound protector group had better soft tissue injury scores for the deltoid muscle (P < .001) and pectoralis muscle (P < .001). No difference in cephalic vein injury was noted between the 2 groups (P > .05). No difference in surgical time was noted. CONCLUSION: The use of a surgical wound protector device in total shoulder arthroplasty did not significantly decrease bacterial colonization of the deep wound. However, soft tissue damage to the deltoid and pectoralis muscle was less severe in the wound protector group. These findings suggest that this device reduces iatrogenic soft tissue injury.

Humans

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence

Effect of knee and hip joint positions on passive stiffness of the rectus femoris and vastus lateralis in healthy individuals.

Passive muscle stiffness is a key determinant of musculoskeletal function and is influenced by structural components such as titin, connective tissue, and fascia. However, the effects of joint position, muscle depth, and sex on quadriceps passive stiffness remain unclear. To investigate the passive stiffness of the rectus femoris (RF) and vastus lateralis (VL) under different joint configurations, muscle depths, and between sexes using shear wave elastography (SWE). Thirty-six healthy young adults (18 men and 18 women) participated in this randomized crossover study. Passive stiffness was assessed in four positions of knee flexion: supine with 60&#xb0; (SUP60), supine with 20&#xb0; (SUP20), sitting with 60&#xb0; (SIT60), and sitting with 20&#xb0; (SIT20). SWE measurements (m/s) were obtained from 30 regions of interest (ROIs) per muscle, categorized into superficial, intermediate, and deep levels. Data were analyzed using Generalized Estimating Equations (GEE). A significant effect of position was observed, with higher stiffness values in the SUP60 condition for both RF and VL (p&#x2009;<&#x2009;0.001). Superficial regions consistently exhibited greater stiffness compared to intermediate and deep regions across all positions (p&#x2009;<&#x2009;0.001). Additionally, men demonstrated significantly higher stiffness values than women (p&#x2009;<&#x2009;0.001). Significant interactions were found between position and muscle, as well as position and depth. Quadriceps passive stiffness is influenced by joint position, muscle depth, and sex. The SUP60 position elicits the highest stiffness, while superficial muscle regions are consistently stiffer. These findings highlight the non-uniform mechanical behavior of the quadriceps and may have implications for clinical assessment, rehabilitation, and exercise prescription. Clinical trial registration: This study was registered at Clinicaltrials.gov in June 06th, 2023. Register number NCT05905406. Link to access https//clinicaltrials.gov/study/NCT05905406.

Humans

The efficacy of non-invasive brain stimulation interventions in obsessive-compulsive disorder management: A network meta-analysis of randomized controlled trials.

Non-invasive brain stimulation (NIBS) has been widely used as an alternative treatment for obsessive compulsive disorder (OCD). However, the most effective NIBS parameters are unclear. To compare the efficacy of NIBS in OCD. We conducted a systematic review and network meta-analyses (NMA) to combine direct and indirect comparisons of NIBS.Systematic searches were conducted in Cochrane CENTRAL, EMBASE, PubMed, and Web of Science from inception to June 20, 2025. Forty-two randomized sham-controlled trials (n = 1456) were included. All statistical analyses were conducted with R statistical software. Bayesian NMAs mainly using the BUGSnet package and gemtc package. Five NIBS protocols produced statistically significant reductions in Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores compared with sham stimulation: high-frequency rTMS over the FzFCz (Hf-rTMS-FzFCz; MD -11.77, 95% CrI -20.62 to -3.09), low-frequency rTMS over F3F4 (Lf-rTMS-F3F4; MD -9.93, 95% CrI -18.07 to -1.65), low-frequency rTMS over FCz (Lf-rTMS-FCz; MD -3.25, 95% CrI -6.06 to -0.40), high-frequency deep TMS over FzFC (Hf-dTMS-FzFC; MD -6.48, 95% CrI -12.32 to -0.50), and 2 mA anodal tDCS over F3 with cathodal over Fp2 (MD -9.34, 95% CrI -16.01 to -3.03).For secondary outcomes, high-frequency deep rTMS over FzFCz produced the largest reduction both in depressive symptoms (SMD -1.24, 95% CrI -1.92 to -0.55) and anxiety scores (SMD -1.88, 95% CrI -2.62 to -1.11), but had no effect on Clinical Global Impression-Severity (CGI-S) scores.Specific NIBS protocols are safe and effective adjunctive treatments for OCD, with promising yet inconclusive improvements in comorbid depressive symptoms. Further high-quality, head-to-head trials are needed.

Humans

Utility of monocyte-derived cells to investigate immune-mediated drug-induced liver injury.

Immune-mediated drug-induced liver injury (DILI) is triggered or exacerbated by the immune system mounting an attack against the drug or its metabolites. The array of in vitro assays for evaluating drug immune liability is limited, highlighting a significant gap in effectively predicting and understanding immune-mediated hepatotoxicity. We aimed to investigate whether monocytes differentiated with the Metaheps (MH) protocol could provide insights into the molecular mechanisms of immune-mediated DILI. MH were generated from monocytes of healthy volunteers (HV) and DILI patients. MH phenotypic characterization was performed by proteomics and qPCR. MH sensitivity to drugs associated with immune-mediated DILI was assessed by lactate dehydrogenase (LDH) assay. Drug-induced LDH release by DILI-derived MH was compared to the upper limit of the 95% CI calculated from HV-derived MH cells treated with the same drug. The 95% CI determined in HV-derived MH was set as the sensitivity threshold for the specific drug. MH cells retain the expression of several immune-related proteins of the parental monocytes and activate a pro-inflammatory response upon exposure to lipopolysaccharide. For all MH (6 out of 6) generated from patients with penicillin-induced DILI, the LDH release upon re-challenge was above the threshold. The sensitivity of MH generated from seven patients with immune checkpoint inhibitor (ICI)-induced hepatotoxicity was ICI-dependent, responding to nivolumab and/or ipilimumab (4 out of 5), but not to pembrolizumab (0 out of 2). Additionally, DILI-derived MH were not sensitive to non-DILI drugs. In conclusion, monocyte-derived cells may serve as an additional tool for drug-specific mechanistic studies of immune-mediated DILI.

Humans

Phenotypic and transcriptomic characterization of biallelic RNU2-2 developmental and epileptic encephalopathy.

OBJECTIVE: A significant proportion of individuals with suspected genetic developmental and epileptic encephalopathies (DEEs) remain unsolved following whole genome sequencing (WGS). Here we describe biallelic RNU2-2 variants causing a recently reported, severe, recessive DEE. METHODS: We screened individuals who have received WGS analyses at the Genomic Medicine Centre Karolinska for Rare Diseases for biallelic RNU2-2 variants. Deep phenotyping was performed through reviewing entire medical histories and phenotypic traits were transcribed to their corresponding Human Phenotype Ontology (HPO) term. HPO terms were used to generate pairwise phenotypic similarity scores and assess for significantly shared phenotype enrichment in the RNU2-2 sub-cohort. RNA sequencing analyses were performed in fibroblast and blood tissues to compare splicing events between RNU2-2 individuals and two independent control groups. RESULTS: We identified 14 individuals from nine families with 12 ultra-rare biallelic RNU2-2 variants clustering in the conserved 5' domains. Genotype data from 13 of 14 individuals has been reported previously as part of a larger cohort. All individuals presented with a highly concordant, severe DEE, characterized by severe to profound intellectual disability, inability to walk or communicate, hyperkinesia, and refractory seizures. Infantile spasms and tonic seizures were the predominant seizure types and a Lennox-Gastaut syndrome-like phenotype was common. These individuals had a significantly similar phenotypic signature when compared with 703 individuals with complex pediatric epilepsies (two-sided Monte Carlo permutation test, p&#x2009;=&#x2009;.005). RNA sequencing analyses showed aberrant splicing, with the most pronounced effects in fibroblast tissues in mutually exclusive exon and alternate 3' splice-site events, which were not detectable in blood. SIGNIFICANCE: We present deep phenotyping data and transcriptomic analyses that provide support for rare, 5' clustering biallelic RNU2-2 variants causing this novel, severe DEE. We propose an RNA sequencing methodology on fibroblast tissue for future validation of RNU2-2 variants.

autosomal recessive disease

Inducible flocculation in Komagataella phaffii enables enhanced biomass separation for biopharmaceutical production.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50&#x202f;% create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (ScFLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation or gravity sedimentation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY&#xae; VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

Flocculation

Mitophagy-mediated ferroptosis involved in 2,5-hexanedione-induced neurotoxicity in rats.

n-Hexane, a widespread environmental and industrial pollutant, poses serious health risks, particularly neurotoxicity. Chronic exposure primarily induces sensorimotor neuropathy via its metabolite 2,5-hexanedione (HD), yet the mechanisms underlying HD-induced neuronal injury remain unclear. Recent evidence implicates ferroptosis, an iron-dependent form of regulated cell death, in neurodegenerative processes. In this study, Sprague-Dawley (SD) rats were exposed to HD to establish a neuropathy model. Ferroptosis involvement was assessed using the iron chelator deferoxamine (DFO) and the ferroptosis inhibitor Ferrostatin-1. The potential role of mitophagy in HD-induced ferroptosis was evaluated by monitoring mitophagy markers and by autophagy inhibition with chloroquine (CQ). In vitro, SH-SY5Y cells were transfected with PINK-1 siRNA to explore mitophagy-mediated regulation of ferroptosis. HD exposure led to iron accumulation, lipid peroxidation, mitochondrial abnormalities, and decreased GPX4 in rat spinal neurons. DFO or ferrostatin-1 treatment ameliorated these changes and preserved mitochondrial integrity. Mechanistic analyses revealed HD-induced activation of mitophagy, as shown by upregulation of Beclin-1, LC3II, Drp-1, and PINK-1, with concomitant downregulation of P62 in spinal mitochondria. CQ suppressed mitophagy, reduced iron deposition and lipid peroxidation, and improved motor function. Similarly, PINK-1 knockdown in SH-SY5Y cells mitigated HD-induced mitophagy and ferroptosis. These findings demonstrate that HD induces neuronal ferroptosis via mitophagy activation. Inhibition of ferroptosis or mitophagy effectively attenuates HD-induced neurotoxicity, suggesting potential therapeutic strategies to reduce neural damage from environmental n-hexane exposure.

Animals

A novel urease-producing strain effectively induces cadmium biomineralization under low-temperature stress.

Microbially induced carbonate precipitation (MICP) has been widely used to immobilize Cadmium (Cd) in contaminated soils in mining-affected regions. However, its remediation efficacy under low-temperature stress, as well as the nucleation process that regulates Cd biomineralization via carbonate precipitation by psychrophilic bacteria, has yet to be investigated. Here, we isolated Pseudomonas sp. J-6, a novel urease-producing strain from tailings in high-altitude cold regions, exhibiting unparalleled cold adaptability at 5 &#xb0;C and achieving 95.85 % Cd removal efficiency by MICP at 10 &#xb0;C. Furthermore, the coprecipitation process of Ca1-xCdxCO3 was clarified through the continuous observation of the precipitates after the low-temperature MICP reaction. The crystal morphology transitioned from loose vaterite in the early stage to a dense square-block morphology in the middle stage. Cd2+ progressively shifted from a surface-bound state to lattice incorporation, ultimately resulting in the formation of stable Cd-substituted calcite crystals. In this process, low temperatures led to the formation of larger, highly ordered Cd-substituted calcite crystals, thereby strengthening Cd sequestration and its long-term stability. In addition, under low-temperature stress, Pseudomonas sp. J-6 induced MICP reaction decreased the bioavailable Cd in alpine slag soil by 44.85 % and enhanced physical properties. In the freeze-thaw cycles, the remediation efficiency remained stable. This study clarified the biomineralization potential in high-altitude cryogenic environments and the nucleation process of Cd biomineralization by psychrophilic bacteria-induced carbonate precipitation, filling a critical research gap in its application under extreme conditions and highlighting its promise for sustainable remediation of heavy metal pollution under low-temperature stress.

Cadmium

Transient acoustic stimulation induces time-dependent synaptic remodeling and enhancement of auditory nerve output after threshold recovery.

BACKGROUND: Acoustic stress can alter cochlear function even in the absence of permanent threshold elevation; however, synaptic consequences of transient acoustic stimulation remain incompletely understood. OBJECTIVE: This study aimed to investigate whether transient acoustic stimulation induces changes in the auditory nerve output and cochlear ribbon synapse morphology following hearing threshold recovery. METHODS: Young adult CBA/CaJ mice were exposed to band-limited acoustic stimulation (45-2,000&#xa0;Hz, 95&#xa0;dB SPL, 2&#xa0;h). Auditory brainstem responses (ABRs), hair cell and spiral ganglion neuron survival, and synaptic morphology were evaluated before exposure and up to 2&#xa0;weeks post-exposure. RESULTS: ABR thresholds were transiently elevated immediately after exposure but largely recovered by 1&#xa0;day post-exposure. In contrast, ABR wave I amplitudes significantly increased after threshold recovery across multiple test frequencies. Ribbon-associated puncta in both inner and outer hair cell regions exhibited biphasic temporal changes, with an initial decrease immediately after exposure followed by an increase at 1&#xa0;day post-exposure. The ribbon-associated punctal area also increased after exposure and remained elevated at later post-exposure time points. No significant loss of hair cells or spiral ganglion neurons was observed. Exploratory genomic analysis suggested enrichment of pathways related to metabolic defense and cellular stress responses. CONCLUSIONS: Transient acoustic stimulation induces time-dependent synaptic remodeling and enhancement of peripheral auditory nerve output without overt cellular degeneration. These findings support a model in which early cochlear responses to acoustic perturbation include adaptive synaptic plasticity and gain regulation, extending current concepts of noise-induced cochlear change beyond irreversible synaptic loss.

Animals

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals

Mitigating pH-induced instability in deruxtecan-based ADCs: an onboard-mixing icIEF approach for robust charge heterogeneity characterization.

Accurate charge variant analysis of antibody-drug conjugates (ADCs) is essential for understanding product heterogeneity and ensuring quality control. However, Deruxtecan (DXd)-based ADCs present a unique analytical challenge due to the intrinsic instability of the payload, where the lactone ring readily undergoes hydrolysis under alkaline conditions, resulting in time-dependent shifts in charge distribution during imaged capillary isoelectric focusing (icIEF). In this study, we describe the development of an onboard-mixing icIEF method designed to minimize pH-induced degradation during sample preparation. By separating ADC samples from carrier ampholytes (CAs) prior to injection and enabling real-time mixing within the instrument, this approach effectively suppresses premature lactone ring opening and stabilizes charge variant profiles. Comparative studies between conventional premixing and onboard-mixing approach demonstrated that the latter significantly enhances reproducibility, particularly for acidic variants that are highly sensitive to structural conversion. Comprehensive method validation confirmed excellent precision, linearity, and sensitivity, with consistent performance across run-to-run and intra-day analyses. The results underscore the importance of controlling microenvironmental pH exposure in the analysis of chemically instable ADCs. The proposed onboard-mixing strategy provides a robust and efficient solution for icIEF-based characterization, reducing analytical artifacts while simplifying method development. This approach is broadly applicable to ADCs and other biotherapeutics containing pH-sensitive functional groups.

Hydrogen-Ion Concentration