Annals of Translational Medicine

Background The high mortality of septic shock demands novel adjunctive therapies. Shenfu Injection (SFI), a traditional Chinese medicine, shows potential but its mechanism remains unclear. Method s We conducted an open-label, randomized trial in 80 patients with septic shock. Patients received standard care with or without adjunctive SFI for 7 days. The primary outcome was 28-day mortality. Key secondary outcomes included inflammatory markers, lactate clearance, and vasopressor duration. Concurrently, network pharmacology analyzed SFIs bioactive components, predicted targets, and enriched pathways, with validation by molecular docking. Results The 28-day mortality was significantly lower in the SFI group (20.0% vs. 42.5%, P=0.030). SFI accelerated clinical improvement, evidenced by greater reductions in IL-6 and procalcitonin, higher 6-hour lactate clearance (35.2% vs. 18.5%, P<0.001), shorter vasopressor duration (48 vs. 72 hours, P<0.001), and more rapid SOFA score decline. Network pharmacology identified 145 SFI-septic shock common targets, with IL-6, SRC, and MAPK3 as central hubs. Pathway analysis revealed significant enrichment in TNF, PI3K-Akt, and IL-17 signaling pathways. Molecular docking confirmed strong binding of key SFI components (e.g., Ginsenoside Rh2) to core targets like IL-6. Conclusion s Adjunctive Shenfu Injection reduces mortality and improves clinical recovery in septic shock, potentially through a multi-target mechanism involving modulation of inflammatory and cellular signaling pathways. This integrative study provides both clinical evidence and a mechanistic framework supporting SFI's use. Clinical Trial Registration: Chinese Clinical Trial Registry, ChiCTR1800020435.

ObjectivesAmong surgically resected non-small cell lung cancer (NSCLC) patients with similar stage and histopathological characteristics, there is variability in patient outcomes which highlights urgency of identifying biomarkers to predict recurrence. The goal of this study was to systematically develop a pre-surgical CT-based habitat-based radiomics classifier to predict recurrence-of-risk in NSCLC. MethodsThis study included 293 NSCLC patients with surgically resected stage IA-IIIA disease that were randomly divided into a training (n = 195) and test cohorts (n = 98). From pre-surgical CT images, tumor habitats were generated using two-level unsupervised clustering and then radiomic features were calculated from the intratumoral region and habitat-defined subregions. Using ridge-regularized logistic regression, separate classifiers were developed to predict 3-year recurrence using intratumoral radiomics, habitat-based radiomics, and a combined model (intratumoral and habitat) which was generated using a stacked learning framework. For each classifier, probability of recurrence was calculated for each patient then numerous statistical and machine learning approaches were utilized to stratify patients for recurrence-free survival. ResultsThe combined radiomics classifier yielded a superior AUC (0.82) compared to the intratumoral (AUC = 0.75) and habitat radiomics (AUC = 0.81) models. When the classifiers were used to stratify high- versus low-risk patients utilizing a cut-point identified by decision tree analysis, high-risk patients were yielded the largest risk estimate (HR = 8.43; 95% CI 2.47 - 28.81) compared to the habitat (HR = 5.41; 95% CI 2.08 - 14.09) and intratumoral radiomics (HR = 3.54; 95% CI 1.45 - 8.66) models. SHAP analyses indicated that habitat-derived information contributed most strongly to recurrence prediction. ConclusionsThis study revealed that habitat-based radiomics provided superior statistical performance than intratumoral radiomics for predicting recurrence in NSCLC.

BackgroundTo investigate the safety and efficacy of CT-guided lung nodule localization needles for the preoperative localization of small pulmonary nodules. MethodsA retrospective study was conducted on 102 patients with a total of 113 small pulmonary nodules who underwent preoperative localization at Jinan Fourth Peoples Hospital from January 2024 to December 2025. Nodule diameter and depth, localization time, the number of pleural punctures, the localization success rate, and postoperative complications (hook dislodgement, hemorrhage, and pneumothorax) were recorded. All patients underwent video-assisted thoracoscopic surgery (VATS) after localization. ResultsThe mean nodule diameter was 0.97{+/-}0.36 cm, the mean depth was 1.26{+/-}0.48 cm, and the mean localization time was 9.8{+/-}3.65 minutes. The hook dislodgement rate was 0.98% (1/102), the intrapulmonary hemorrhage rate was 14.71% (15/102), and the pneumothorax rate was 16.67% (17/102). All pulmonary nodules were successfully resected by VATS at 73.82{+/-}13.83 minutes after localization, and no severe complications occurred. ConclusionsThe use of a CT-guided lung nodule localization needle for the preoperative localization of small pulmonary nodules decreases the time needed for intraoperative nodule detection and operation time. This strategy is a simple, safe, and accurate preoperative localization method that is worthy of increased clinical use.

PurposeIn this study, we aimed to develop and evaluate an artificial intelligence-based diagnostic model for the diagnosis of acute cholecystitis (AC) using non-contrast CT images and clinical data. Materials and MethodsThis retrospective study included 199 patients (100 AC, 99 non-AC) treated between January 2016 and December 2025 at a single center. Patients were randomly divided into training (n=139) and test (n=60) datasets. Three models were constructed: an imaging-based deep learning model, a clinical data-based machine learning model, and a hybrid machine learning model integrating deep learning-derived imaging features with clinical data. CT images were preprocessed, and gallbladder regions were segmented. Clinical variables included white blood cell counts and levels of C-reactive protein and liver function markers. Model performance was evaluated using accuracy, precision, recall, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). Statistical comparisons were performed using Welchs t-test and Chi-square test. ResultsThe imaging-based model achieved accuracy 0.883, precision 0.848, recall 0.933, specificity 0.833, and AUC 0.916. The blood-based model achieved accuracy 0.917, precision 0.931, recall 0.900, specificity 0.933, and AUC 0.949. The hybrid model showed the highest performance, with accuracy 0.950, precision 0.909, recall 1.000, specificity 0.900, F1 score 0.952, and AUC 0.986. ConclusionA hybrid model integrating CT imaging and clinical data improved diagnostic performance for AC compared with single-modality models.

PurposeTo identify the ocular biometric parameters associated with refractive outcomes in Chinese Primary angle closure glaucoma (PACG) patients receiving phacoemulsification and intraocular lens (IOL) implantation (PEI) surgery. Methods165 Chinese PACG patients receiving PEI and goniosynechialysis (GSL) and 53 cataract patients as controls only receiving PEI surgery were recruited. The prediction accuracy of IOL power calculation was assessed by the prediction error (PE), mean absolute error (MAE), median absolute error (MedAE), and proportions of eyes with a PE within {+/-} 0.25 diopters (D), {+/-} 0.50 D, {+/-} 0.75 D, and {+/-} 1.00 D. The association of different ocular biometric parameters with the PE of IOL calculation were evaluated. ResultsThe PACG patients had significantly higher absolute of PE as compared to the control subjects, especially the acute PACG patients. The axial length (AL), changes in aqueous depth pre- and post-surgery ({bigtriangleup}AD), and the ratio of {bigtriangleup}AD/AL were significantly associated with the PE in acute PACG patients. The association of {bigtriangleup}AD with the PE of IOL power calculation was found in PACG patients with AL [&ge;] 22 mm. ConclusionsThis study revealed the association of AL and {bigtriangleup}AD with the PE of IOL calculation in Chinese PACG patients. Precisely predict the {bigtriangleup}AD is necessary for acute PACG patients, especially for those with AL [&ge;] 22 mm, to improve the refractive outcomes.

After rejection, resubmission of scientific manuscripts often requires substantial journal-specific reformatting. We compared systematic review submission policies across high-impact ophthalmology journals and quantified policy similarity to support resubmission planning. We identified the top 50 ophthalmology journals by SCImago Journal Rank that publish systematic reviews and are not invite-only, extracted policies from author instructions using an a priori data dictionary, and computed pairwise similarity on a 0 to 1 scale using the Gower coefficient across mixed policy variables with available-case denominators for unstated fields. Policies were heterogeneous and frequently unstated. Only 29 of 50 journals (58%) stated a main-text word limit; among journals with numeric limits, the median was 4000 words (interquartile range 3500 to 5500; n = 23). Preferred Reporting Items for Systematic Reviews and Meta-Analyses compliance was explicitly required by 35 of 50 journals (70%), and prospective registration by 6 of 50 journals (12%). Across 1225 journal pairs, similarity was modest, with a median of 0.64 (interquartile range 0.57 to 0.71; range 0.05 to 0.98). Similarity among the top 5 highest-ranking journals ranged from 0.62 to 0.90 (median 0.75). Systematic review submission policies vary widely across high-impact ophthalmology journals, and most journal pairs show only modest similarity. Similarity-based guidance may help identify policy-aligned resubmission targets while anticipating common sources of reformatting burden.

BackgroundEpidermal Growth Factor Receptor (EGFR) inhibitors, while effective in oncology, are associated with under-characterized ocular adverse events (AEs). Prior studies have been limited in scope, lacking a comprehensive, class-wide analysis of the full spectrum of ocular toxicity, particularly for newer agents. MethodsWe conducted a disproportionality analysis of the FDA Adverse Event Reporting System (FAERS) (2001-2025). Twelve EGFR-targeted agents were evaluated against a pre-specified set of ocular MedDRA Preferred Terms. To ensure robust signal detection, a significant association was defined by [&ge;]3 co-reported cases, a Proportional Reporting Ratio (PRR) [&ge;]2.0, and a false-discovery-rate adjusted p-value <0.05. ResultsAmong 6,976,462 drug-event combinations, 20 met all signal criteria for Eyelash Abnormalities, Ocular Surface Disease, or Vision-Threatening and Intraocular Events. Trichomegaly demonstrated extreme disproportionality (e.g., panitumumab PRR= 465.3, 95% Confidence Interval [CI], 247.7-874.3). A consistent pattern of ocular surface toxicity (conjunctivitis, keratitis, blepharitis) was observed across multiple tyrosine kinase inhibitors and monoclonal antibodies, indicating a class-wide effect. Signals for serious events included corneal perforation (erlotinib, n= 7, PRR=13.9, 95% CI= 6.6-29.4) and optic neuropathy (erlotinib, n= 6, PRR= 2.9, 95% CI= 1.3-6.4). ConclusionThis analysis confirms a strong, class-wide signal for ocular toxicity across the spectrum of EGFR inhibitors, from characteristic eyelid changes to sight-threatening complications. These findings underscore the necessity for proactive ophthalmologic monitoring, including baseline assessment, in patients receiving these therapies to preserve vision and maintain quality of life during cancer treatment.

Malignant pleural effusion (MPE) frequently complicates advanced cancer and impairs quality of life. Chemical pleurodesis with agents such as bleomycin or povidone iodine is widely used, but comparative efficacy and safety remain uncertain. Bleomycin is an established agent but is costly and less available, whereas povidone iodine is affordable and easily accessible. This study aimed to systematically compare the efficacy and safety of bleomycin versus povidone iodine for pleurodesis in patients with malignant pleural effusions. We conducted a systematic review and meta-analysis following PRISMA guidelines. PubMed, Semantic Scholar, and the Google Scholar were searched through May 20th 2025. Studies included randomized controlled trials and cohort studies comparing bleomycin and povidone iodine for pleurodesis in patients with MPE. Seven studies with 392 patients (174 in the povidone iodine group, 218 in the bleomycin group) were included. Success rates for pleurodesis ranged from 71.1% to 100% for povidone iodine and 66.7% to 95.2% for bleomycin. Meta-analysis showed no significant difference in efficacy (RR = 1.04, 95% CI: 0.94-1.15, p = 0.50; I2 = 43%). Both agents were well tolerated, with similar rates of mild adverse events. This study showed no significant bias. Povidone iodine and bleomycin are equally effective and safe for pleurodesis in MPE. Given its lower cost and greater accessibility, povidone iodine may be preferred, especially in resource-limited settings.

Abstract Background: Pediatric respiratory infections are a leading cause of morbidity and mortality globally, representing a major health challenge in children. Research Gap: Despite extensive studies on epidemiology, clinical management, and specific pathogens, no bibliometric analysis has systematically evaluated the most influential research in this field. Objectives: This study aimed to evaluate the characteristics of the top 50 most-cited articles on pediatric respiratory infections and to identify emerging research trends. Methods: The Web of Science database was searched without publication year restrictions. Independent reviewers screened studies based on predefined inclusion and exclusion criteria. Data were extracted using a standardized form, including study details. Results: The 50 most-cited articles ranged from 34 to 384 citations and showed a right-skewed distribution with a sharp drop after the top ten. Publication years ranged from 1978 to 2021, with over half published in the 2010s. Articles appeared in 31 journals, with Pediatrics contributing five. Leading countries were the United States (18%), China (12%), and Canada (10%), with research largely concentrated in high-income regions and limited multicenter collaboration. Cohort studies dominated (66%), while randomized trials (12%) and reviews/meta-analyses (16%) were less common. Research clustered around three themes: clinical outcomes (e.g., pneumonia, bronchiolitis); viral etiology/diagnostics (e.g., RSV, SARS-CoV-2); and antimicrobial stewardship. Conclusion: Over the past decades, pediatric respiratory infection research has developed but remains unbalanced, relying heavily on observational evidence from high-income countries, with limited randomized trials, systematic reviews, multicenter collaborations, and LMIC-led studies. These findings provide insights that may direct researchers to identify potential focal points and guide future research in the field.

Background. Lung metastases in osteosarcoma (OS) are the main cause of the death. The accuracy of the diagnosis of nodules by computed tomography (CT) of the lungs is critically important for determining the disseminated stage of the disease and planning surgical treatment. The use of artificial intelligence (AI) in the search for lung nodules increases the accuracy of diagnosis and reduces the chance of missing metastases. Objective: to evaluate the accuracy of lung nodules diagnosis in adolescents with OS using AI. Methods. A retrospective assessment of CT scans of adolescents with OS was performed. A pathological nodule with an average size of [&ge;]4 mm was considered a target finding. The diagnostic accuracy of an AI algorithm previously trained on an adult dataset was evaluated, and the number of false positives (FP) and false negatives (FN) was determined. Sensitivity, specificity, accuracy, area under the ROC curve (AUC), positive predictive value, negative predictive value, and F1-measure were calculated. Based on the obtained results, the effectiveness of the algorithm was assessed. Results. 248 CT scans of adolescents with OS were evaluated. The following results were obtained: in 5 cases, the AI algorithm showed a FP result (2.02%), in 34 cases, it showed a FN result (13.71%), and in 209 cases, a correct result (both true positive and true negative) (84.27%). The diagnostic accuracy of the algorithm was 0.843 (95% CI 0.794-0.887). The application of the AI algorithm in the practice of an X-ray doctor in a specific clinical task would allow to increase the sensitivity from 0.805 to 0.891, while ensuring an absolute decrease in the number of FN results by 8.59% and a relative decrease by 44%. Conclusion. The obtained results confirm the practical value of the application of the AI algorithm and justify the implementation of AI-assisted systems in the diagnostic protocols for lung metastases in adolescents with OS.

Bubble continuous positive airway pressure (bCPAP) is a low-cost respiratory support device that has demonstrated different outcomes for children with severe pneumonia in different settings. Some differences in outcomes may be attributable to implementation factors (e.g., patient monitoring and feeding practices). We aimed to characterize bCPAP reach, implementation fidelity, and safety outcomes for children with severe pneumonia in Pakistan. We conducted a prospective cohort study at Aga Khan University Hospital and Abbasi Shaheed Hospital from February through May 2025. We enrolled children 1-59 months who met WHO criteria for severe pneumonia within 24 hours of presentation to the emergency department. Participants were followed daily via chart review, caregiver survey, and physical exam through discharge, transfer, or death. We reported the proportion of children receiving bCPAP ("reach") and constructed a mixed-effects, multinomial logistic regression model with robust standard errors to report: fidelity (child location in a highly monitored area, continuous monitoring, avoidance of unplanned disruptions to bCPAP, and avoidance of oral feeding); safety (aspiration events and pneumothorax); bCPAP failure (death, respiratory support escalation, or leaving against medical advice); and in-hospital mortality. Of 165 children with severe pneumonia, 88 (53%) received bCPAP over 141 bCPAP days. The average predicted probabilities (95% CI) of our fidelity measures were: 85% (78-92%) for location in a highly monitored area; 56% (51-60%) for continuous monitoring; 66% (57-75%) for continuous bCPAP without disruptions; 46% (36-55%) for avoidance of oral feeding while on bCPAP. Among children receiving bCPAP, 9 (10%) experienced an aspiration event, 1 (2.2%) experienced a pneumothorax; 19 (22%) experienced bCPAP treatment failure. One child (1.1%) died; 6 (6.8%) required respiratory support escalation; 14 (16%) left against medical advice. We identified several gaps in bCPAP reach and fidelity. These may be modifiable by individual-and team-targeted strategies to reduce bCPAP-related complications and pneumonia-related child deaths.

Background: Anemia is an established marker of cardiovascular disease severity and risk which leads to elevations in resting myocardial blood flow (MBF) and impaired myocardial flow reserve (MFR) in patients without obstructive coronary artery disease (CAD). Anemia can potentially be detected opportunistically from blood pool density changes on computed tomography (CT) imaging. Objectives: We evaluated relationships between chamber density measurements with hemoglobin, positron emission tomography (PET) findings, and cardiovascular events. Methods: We included 33460 patients from 13 sites in the REFINE-PET who underwent PET and 24368 patients undergoing lung cancer screening chest CT. A deep learning model segmented cardiac chambers from CT images, then quantified chamber density. We evaluated the relationship between chamber density measures with resting MBF and MFR, as well as associations with death or myocardial infarction (MI). Results: We included a total of 57,828 patients. A higher density in myocardium compared to left ventricle blood pool was associated with reduced MFR (adjusted odds ratio 3.02 per SD increase, 95% confidence interval[CI] 2.72 - 3.38) and an increased risk of death or MI in (adjusted hazard ratio[HR] 1.38 per SD increase, 95% CI 1.26-1.51). Having myocardial density higher than blood pool density was also associated with cardiovascular death in patients undergoing low-dose chest CT (adjusted HR 1.73, 95% CI 1.20-2.52). Conclusions: In a large multimodality dataset, lower cardiac chamber density is associated with impaired MFR and independently associated with cardiovascular events. These biomarkers can be automatically extracted from CT to provide physiologic insights and potentially guide patient care.

BackgroundA critical radiologist shortage exists in India, leading to delayed chest radiograph (CXR) interpretation. This leads to disease progression, higher morbidity, and mortality. Artificial intelligence-based CXR interpretation by Lenek Intelligent Radiology Assistant (LIRA) is a promising solution. This study aims to establish the screening and triaging capabilities of LIRA by assessing its accuracy in detecting abnormalities and pathologies in CXRs from geographically diverse institutions. MethodsWe conducted a retrospective multi-source validation of the diagnostic accuracy of LIRA for the detection of general abnormalities, tuberculosis, consolidation, pleural effusion, pneumothorax, and cardiomegaly. De-identified chest radiographs were input into LIRA models. The obtained interpretations were compared to the established ground truth reporting for the calculation of sensitivity, specificity, and AUROC with 95% CI for individual pathologies across varying probability thresholds. ResultsLIRA demonstrated high sensitivity for general abnormality detection (AUROC 0.93-0.986, 84.4-97.1% sensitivity, 88.9-92.4% specificity) and tuberculosis triaging (Shenzhen & Montgomery: 88.5-89.7% sensitivity, 89.9-90.5% specificity; Jaypee: 98.7% sensitivity, 63.6% specificity). For consolidation (AUROC 0.884-0.895, 96.4-96.9% sensitivity, 70.8-77.1% specificity), pleural effusion (AUROC 0.942-0.967, 79.7-99.1% sensitivity, 81.2-87.7% specificity), pneumothorax (AUROC 0.87, 90.6-94.8% sensitivity, 79.5-82.7% specificity) and cardiomegaly (AUROC 0.883, 95.1% sensitivity, 81.6% specificity), the model exhibited commendable accuracy as well. ConclusionsThe diagnostic performance of LIRA was consistent across various pathologies and chest radiographs from diverse geographic locations, with particular strengths in abnormality detection and tuberculosis screening. The risk-stratified triaging and high sensitivity of LIRA make it a reliable adjunct solution to address radiologist shortages, reduce turnaround times, and support Indias tuberculosis elimination goals.

BackgroundLymphangiogenesis plays a critical role in various liver diseases, yet its function in liver fibrosis remains controversial. This study aimed to explore the role of lymphangiogenesis in liver fibrogenesis and its underlying regulatory mechanisms. MethodsLiver fibrotic mice were established by carbon tetrachloride (CCl4) or Thioacetamide (TAA)-induced injection or bile duct ligation. Lymphatic vessels were marked by podoplain (Pdpn) staining in mice and D2-40 staining in clinical samples. Lymphatic vessels area and density were measured to indicate lymphangiogenesis. Multiplexing immunohistochemistry was used to detect co-localization of proteins. ResultsIn the present study, we first verified increased lymphangiogenesis in human and murine fibrotic livers. Afterwards, we identified VEGFC rather than VEGFD as the primary driver of lymphangiogenesis in liver fibrosis. Furthermore, we demonstrated that M1 macrophages serve as the major source of VEGFC. Founctional studies revealed that VEGFC-mediated lymphangiogenesis exacerbates hepatic fibrosis, while its inhibition alleviated fibrosis. Bioinformatic analysis uncovered Midkine (MDK) as a key downstream of lymphangiogenesis. Both in vivo and in vitro studies confirmed that exogenous MDK promotes liver fibrosis via activating hepatic stellate cells (HSCs), whereas MDK inhibition counteracts the profibrotic effects of VEGFC-induced lymphangiogenesis. Importantly, we discovered that MDK activates HSCs through the Hippo/YAP signaling pathway. ConclusionsM1 macrophage-mediated lymphangiogenesis aggravates liver fibrosis via MDK secretion, which activates HSCs. These findings provide novel insights into coordinated crosstalk between macrophages, lymphatic endothelial cells and HSCs in liver fibrosis and suggest lymphangiogenesis and MDK as potential therapeutic targets for fibrotic liver diseases.

ObjectiveTo describe the clinical characteristics of term neonates with neonatal bacterial meningitis (NBM) and explore the association between different pathogens and imaging complications, providing clinical evidence for early identification and individualized management. MethodsA retrospective study was conducted on 531 term neonates diagnosed with NBM admitted to the Capital Institute of Pediatrics from 2013 to 2025. Demographics, clinical manifestations, laboratory parameters, etiological results, imaging complications and treatment measures were collected. Patients were divided into favorable/adverse discharge outcome groups and pathogen-positive/negative groups. Statistical analyses were performed using appropriate tests, and Cramers V coefficient was used to analyze the association between pathogens and imaging complications. ResultsO_LIThe most common clinical manifestations were abnormal body temperature (79.85%), altered consciousness (55.18%) and jaundice (46.52%). CSF/blood culture was positive in 133 cases (25.05%), with Escherichia coli (27.07%), group B streptococcus (17.29%) and Staphylococcus species (16.54%) as predominant pathogens. The overall incidence of imaging complications was 22.22%, mainly hydrocephalus (5.84%), subdural effusion (4.90%) and encephalomalacia (2.64%). C_LIO_LIAdverse discharge outcomes occurred in 107 cases (20.15%). Compared with the favorable group, the adverse group had higher incidences of convulsions, altered consciousness, anterior fontanelle bulging, abnormal muscle tone and primitive reflexes (all P<0.001), more obvious laboratory abnormalities (higher CRP, CSF leukocytes and protein, lower CSF glucose, all P<0.05), higher culture positive rates and greater need for adjuvant therapy (all P<0.001). C_LIO_LIPathogen-positive patients had higher imaging complication rates. Gram-negative infections were associated with higher hydrocephalus and subdural effusion rates, while Gram-positive infections had higher brain abscess risk. Specifically, Escherichia coli correlated with hydrocephalus and subdural effusion; group B streptococcus with cerebral infarction and encephalomalacia; LMs with intracranial hemorrhage and brain abscess; negative cultures correlated with no imaging complications (all P<0.05). C_LI ConclusionTerm NBM neonates have non-specific manifestations, mainly abnormal body temperature and altered consciousness. Predominant pathogens areEscherichia coli, group B streptococcus and Staphylococcus species, with hydrocephalus and subdural effusion as common imaging complications. Adverse outcomes are associated with severe symptoms, obvious laboratory abnormalities and higher pathogen positivity. Specific pathogens correlate with distinct imaging complications.

This study investigates the therapeutic potential of secretomes derived from Adipose-derived Mesenchymal Stem Cells (ADMSC-CM) and Limbal-derived Mesenchymal Stem Cells (LMSC-CM) against oxidative stress-induced damage in Retinal Pigment Epithelium (RPE-1) cells. RPE dysfunction, often triggered by oxidative stress, is a hallmark of various retinal degenerations. Here, we induced RPE-1 injury using H2O2 and evaluated the restorative effects of both MSC-conditioned media (CM). Our results demonstrated that both ADMSC-CM and LMSC-CM significantly enhanced cell viability and successfully reversed H2O2-induced G2/M phase cell cycle arrest. While oxidative stress triggered a pro-inflammatory response characterized by elevated IL-1{beta}, IL-6, and IL-10 expression, MSC-CM treatment, particularly ADMSC-CM, effectively modulated these levels and suppressed the p38 MAPK signaling pathway. Furthermore, MSC-CM reduced the Bax/Bcl-2 ratio, indicating an anti-apoptotic effect, and appeared to stabilize autophagic flux. To investigate the impact of oxidative-stress induced alterations in retinal pigment epithelial cells on angiogenesis, the effects of RPE-derived secreted factors on endothelial cell function were evaluated. Crucially, in terms of safety and secondary complications, neither secretome exhibited pro-angiogenic tendencies; instead, they significantly inhibited HUVEC migration and invasion compared to the H2O2 damaged group. These findings suggest that both ADMSC and LMSC secretomes provide a potent multi-targeted therapeutic effect, making them promising candidates for cell-free therapies in retinal diseases.

BackgroundTransfer of Streptococcus agalactiae, or Group B Streptococcus (GBS) from parent to newborn during delivery can produce life-threatening infections in neonates. Probiotics could potentially prevent GBS colonization in pregnant individuals. We conducted a systematic review and meta-analysis to evaluate the effectiveness of probiotic administration in treating Group B Streptococcus colonization. MethodsMEDLINE, ClinicalTrials.gov, PROSPERO, and the Cochrane, Wild Card, Central Register of Controlled Trials were searched from the July 2015 of each database until July 2025 that completed a randomized controlled trial which compared Probiotic versus control. We utilized the Cochrane Risk of Bias 2.0 (RoB 2) tool to assess bias in the systematic review. Results14 randomized controlled clinical trials met our inclusion criteria. The trials used oral probiotic administration compared to either a placebo or a control group. A meta-analysis showed that probiotic administration produced a statistically significant decrease in the rate of GBS colonization in pregnant individuals. The individual studies ranged from four showing great effectiveness, while the other 10 studies showed a range of effectiveness, from partially effective to no effectiveness in preventing GBS colonization. ConclusionOverall, probiotics were effective in lowering infection rates of GBS, but individual studies showed great variability. Probiotics show promise in decreasing GBS colonization in pregnant people, but more studies need to be performed in order to use them effectively and decrease antibiotic usage.

BackgroundVertebral artery calcification (VAC), a critical indicator of cerebrovascular disease, is often overlooked in head-and-neck imaging. Manual detection is time-consuming and prone to inter-observer variability. This study aimed to develop and validate a deep learning model for automated detection and quantitative risk assessment of VAC in non-contrast head-and-neck computed tomography (CT) images, bridging the diagnostic gap between dentistry and vascular medicine. MethodsWe developed a deep learning model based on the ResNet-18 architecture, designated as Grayscale ResNet, optimized for single-channel CT images. The development followed a two-phase strategy: initial training on 539 axial images from head-and-neck CT image followed by iterative refinement (fine-tuning) using a targeted dataset of clinically significant cases to ensure generalizability. The models performance was evaluated using patient-level Receiver Operating Characteristic (ROC) analysis and saliency map visualization for clinical interpretability. ResultsThe optimized model demonstrated a robust performance in distinguishing between cases with and without VAC. In the independent cohort, the model achieved an area under the curve (AUC) of 0.846. At a specific threshold value (98.6%), the system yielded a sensitivity of 80.0% and a specificity of 90.6%. A saliency map analysis confirmed that the model consistently focused on anatomically relevant vascular regions. ConclusionsThe proposed automated system provides an accurate and reliable method for VAC screening using routine head-and-neck CT scans. By transforming incidental imaging findings into a quantifiable risk index, this tool can serve as a vital decision-support system for dentists and radiologists, facilitating early patient referrals and contributing to global stroke prevention.

Background and aimTrauma healing with low-intensity ultrasound is effective for different types of injuries affecting both soft tissues and bones. The work aimed to disclose the healing potential of a new type of ultrasound, ultra-wideband low-intensity mechanical waves (UMUS), and to compare its effects with those of low-intensity pulsed ultrasound (LIPUS) in a model of trauma. Material and methodsThe work was performed on 2-to 3-month-old male Wistar rats. The model of tail amputation was created, and a transducer emitting UMUS (1-7 MHz, 0.22 mW/cm2) was applied daily for 10 days to the surface of the trauma site in animals that were timely immobilized. LIPUS (1.5 mHz, 30.0 mW/cm2) was used in a separate group of animals. Sham-stimulated rats were used as a control. The intensity of collagen expression in the subdermal tissue was assessed in van Gieson-stained sections, whereas in the UMUS group, expression of CD31, CD34, VEGF, and Ki67 was analyzed. ResultsStarting on the 20th day after trauma, UMUS-treated animals demonstrated a statistically significant decrease in the surface area of the traumatic zone compared to the control, whereas LIPUS-treated rats showed this difference on the 30th day of observation. Starting from the 30th day, a significantly greater reduction in the surface of trauma was observed in UMUS, with complete closure achieved in 6 out of 9 rats (P=0.019 vs control), whereas in LIPUS-treated animals, a similar result was observed in 2 out of 8 rats (P>0.05). In UMUS-treated rats, heightened expression of collagen in animals with LIPUS exceeded control data by 7.84% (P=0.034), while the expression in rats with UMUS exceeded data in LIPUS-treated rats by 14.71% (P=0.013). Increased expression of CD31, CD34, VEGF, and Ki67 was observed in UMUS-treated rats. ConclusionsUMUS treatment accelerated healing and reduced wound size, and increased the expression of collagen, CD31, VEGF, CD34, and Ki67, supporting angiogenesis and collagen formation. Effects are more pronounced compared to LIPUS treatment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=176 HEIGHT=200 SRC="FIGDIR/small/717366v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@936775org.highwire.dtl.DTLVardef@16d505eorg.highwire.dtl.DTLVardef@1b75d7dorg.highwire.dtl.DTLVardef@15ae99c_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundPa4ediatric pneumonia is a major cause of childhood morbidity and mortality. Chest X-rays (CXR) are central to diagnosis, but shortages of specialist radiologists can delay reporting. Multimodal large language models (MLLMs) may assist clinical workflows by analysing images and communicating findings, although their diagnostic performance remains below state-of-the-art classifiers. ObjectiveTo evaluate whether ensemble strategies improve MLLM diagnostic performance for paediatric radiological pneumonia detection on CXRs. MethodsIn this retrospective study, paediatric CXRs from two datasets (balanced and real-world) at KK Womens and Childrens Hospital were analysed. Images were independently reviewed by two board-certified radiologists, with pneumonia severity assigned to three classes using a predefined consensus algorithm. Fifteen MedGemma-4B-it agents classified each CXR into five likelihood categories, which were mapped to the three severity classes for evaluation. Majority voting, soft voting and GPTOSS-20B aggregation were compared with baseline average agent performance. The primary outcome was One-vs-Rest (OvR) AUROC. Secondary metrics included accuracy, sensitivity, specificity, F1-score, Cohens {kappa} and One-vs-One (OvO) AUROC. ResultsThe balanced dataset contained 900 CXRs and the real-world dataset 1300 CXRs. Soft voting significantly improved OvR-AUROC compared with baseline in both datasets (Balanced: 0.829>0.764; 95%CI=0.752-0.779; P=0.0002. Real-world: 0.728>0.655; 95%CI=0.638-0.679; P=0.0003). Soft voting also improved accuracy, Cohens {kappa}, OvO-AUROC in both datasets and F1-score in the balanced dataset. ConclusionSoft voting enhances MedGemmas diagnostic discriminatory performance for paediatric radiological pneumonia detection. Our system enables privacy-preserving, near real-time clinical decision support with explainable outputs, having potential for integration into emergency departments. Our systems high specificity supports triage by flagging high-risk radiological pneumonia cases. Clinical ImpactO_LIPaediatric CXRs often face reporting delays exceeding 24 hours due to radiologist shortages. C_LIO_LIOur proposed MLLM ensemble framework achieves better than average MLLM diagnostic discrimination for radiological pneumonia without requiring cloud-based systems. C_LIO_LISoft-voting aggregation enhances diagnostic discriminatory effectiveness for paediatric pneumonia severity, while preserving explainable outputs. C_LIO_LIOur system acts as a decision support tool that identifies higher-risk pneumonia cases for urgent review, supporting safer triage. C_LI