Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

ObjectiveCerebral ischemic injury triggers a complex pathological cascade characterized by excessive reactive oxygen species (ROS) accumulation, persistent oxidative stress, and sustained neuroinflammation in the injured brain microenvironment. These events collectively drive mitochondrial dysfunction, microglial overactivation, pro-inflammatory cytokine release, and progressive neuronal apoptosis, ultimately leading to severe and irreversible neurological deficits. However, conventional therapeutic strategies face critical limitations, including poor blood-brain barrier penetration, insufficient local drug concentration, uncontrolled drug release, and off-target systemic side effects. To address this pathological process, we rationally designed and fabricated an injectable ROS-responsive hydrogel loaded with polydopamine nanoparticles (PDA NPs) for spatiotemporally controlled antioxidation, anti-inflammation, and neuroprotection in the ischemic injury microenvironment. The present study aimed to systematically characterize the physicochemical properties, ROS-responsive drug release behavior, biocompatibility, and neuroprotective efficacy of this composite hydrogel system in vitro. MethodsPDA NPs were fabricated via oxidative self-polymerization. The ROS-responsive hydrogel was cross-linked using N1-(4-boronobenzyl)-N3-(4-boronophenyl)-N1,N1,N3,N3-tetramethylpropane-1, 3-diaminium (TSPBA) and polyvinyl alcohol (PVA). Morphology, particle size, Zeta potential, and structure of PDA NPs were characterized by dynamic light scattering (DLS), Zeta potential analysis, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Microstructure, rheological properties, shear-thinning behavior, and ROS-triggered release profiles of the hydrogel were examined by SEM and rheometry. Biocompatibility was evaluated using HT22 mouse hippocampal neurons with CCK-8 and live/dead staining. An oxygen-glucose deprivation/reoxygenation (OGD/R) model was established to simulate ischemic injury in vitro. ROS levels and neuronal apoptosis were detected by DHE staining and TUNEL assay. Microglial polarization and pro-inflammatory cytokine expression were analyzed using immunofluorescence and RT-qPCR in BV-2 microglia. Transwell co-culture was used to verify the indirect neuroprotection mediated by modulated microglia. ResultsCharacterization results confirmed that the as-prepared PDA NPs were monodispersed spherical nanoparticles with uniform diameter and negative surface potential, demonstrating favorable dispersibility and robust ROS-scavenging activity. The TSPBA-PVA hydrogel exhibited a highly porous interconnected network, suitable mechanical strength, and obvious shear-thinning behavior, supporting its application as an injectable implant. More importantly, the hydrogel displayed typical ROS-responsive degradation and on-demand PDA NP release in a ROS-concentration-dependent manner. In vitro cellular experiments demonstrated that the PDA NP-loaded hydrogel possessed excellent biocompatibility with HT22 cells. In the OGD/R model, the hydrogel significantly reduced intracellular ROS accumulation and markedly suppressed neuronal apoptosis. Furthermore, the composite hydrogel effectively redirected BV-2 microglia from the pro-inflammatory M1 toward the anti-inflammatory M2 phenotypes, downregulated the expression of pro-inflammatory cytokines including TNF-α, IL-1β, and IL-6, and reduced inflammatory damage. Transwell co-culture assays further validated that M2-polarized microglia mediated by the hydrogel significantly enhanced the survival of OGD/R-injured HT22 neurons and attenuated apoptosis. ConclusionIn this study, we successfully developed a novel injectable ROS-responsive hydrogel loaded with PDA NPs for synergistic antioxidative and anti-inflammatory neuroprotection. This intelligent hydrogel system enables ROS-triggered on-demand release of PDA NPs, efficiently scavenges excessive ROS, inhibits oxidative stress injury, modulates microglial polarization, and suppresses neuroinflammation, thereby exerting robust neuroprotective effects in vitro. This biomaterial platform provides a promising strategy for the targeted and controlled delivery of bioactive nanomaterials in the central nervous system diseases and establishes a solid experimental foundation for the development of in situ injectable therapies for ischemic brain injury.

ObjectiveTo investigate the mechanism of liver injury induced by tripterygium glycosides tablets （TG） and the molecular mechanism of compound glycyrrhizin tablets （CG） in alleviating the abnormalities of cholesterol metabolism caused by TG via cholesterol metabolism. MethodsAccording to the body weights， male Sprague-Dawley （SD） rats were randomly grouped as follows： control （pure water）， low-dose TG （TG-L， 189.0 mg·kg^-1·d^-1）， high-dose TG （TG-H， 472.5 mg·kg^-1·d^-1）， TG-L+CG （189.0 mg·kg^-1·d^-1 TG + 20.25 mg·kg^-1·d^-1 CG）， and TG-H+CG （472.5 mg·kg^-1·d^-1 TG + 20.25 mg·kg^-1·d^-1 CG）， with 6 rats in each group. Rats were administrated with corresponding drugs once daily for 3 weeks. At the end of the last administration， the mRNA and protein levels of liver X receptor-alpha （LXR-α）， low-density lipoprotein receptor （LDLR）， adenosine triphosphate-binding cassette transporter A1 （ABCA1）， adenosine triphosphate-binding cassette transporter G1 （ABCG1）， 3-hydroxy-3-methylglutaryl coenzyme A reductase （HMGCR）， cholesterol 7α-hydroxylase （CYP7A1）， cholesterol 12α-hydroxylase （CYP8B1）， and sterol 27-hydroxylase （CYP27A1） in the liver tissue were determined by Real-time PCR and Western blotting， respectively. The level of 3-hydroxy-3-methylglutaryl coenzyme A reductase （HMG-CoAR）， a regulatory enzyme of cholesterol synthesis， was measured by enzyme-linked immunosorbent assay （ELISA）. HepG2 cells were used to observe the effect of TG on the cell proliferation in vitro. Specifically， HepG2 cells were grouped as follows： Low-dose TG （TG-l， 15 mg·L^-1）， medium-dose TG （TG-m， 45 mg·L^-1）， high-dose TG （TG-h， 135 mg·L^-1）， fenofibrate （FB， 10 μmol·L^-1）， CG extract， TG-h+FB （135 mg·L^-1 TG + 10 μmol·L^-1 FB）， TG-m+FB （45 mg·L^-1 TG + 10 μmol·L^-1 FB）， TG-l+FB （15 mg·L^-1 TG + 10 μmol·L^-1 FB）， TG-h+CG （135 mg·L^-1 TG + 60 μmol·L^-1 CG）， TG-m+CG （45 mg·L^-1 TG + 60 μmol·L^-1 CG）， and TG-l+CG （15 mg·L^-1 TG + 60 μmol·L^-1 CG）. The mRNA and protein levels of LXR-α， ABCG1， LDLR， CYP7A1， CYP8B1， and CYP27A1 in HepG2 cells were determined by Real-time PCR and Western blotting， respectively. ResultsThe rat experiment showed that compared with the control group， the TG-H group showed down-regulated mRNA levels of CYP7A1， CYP8B1， and CYP27A1 in the liver tissue （P<0.05， P<0.01）， which were up-regulated by the application of CG （P<0.05， P<0.01）， and the TG-H+CG group showed up-regulated mRNA level of LDLR （P<0.01）. Compared with the control group， the TG-L and TG-H groups showed down-regulated protein levels of LDLR， CYP7A1， and CYP8B1 in the liver tissue （P<0.05， P<0.01）. In addition， the protein levels of ABCG1 and LXR-α were down-regulated in the TG-H and TG-L groups， respectively （P<0.05）. Compared with TG alone， TG+CG up-regulated the protein levels of ABCG1 and LDLR （P<0.05， P<0.01）， and the protein levels of CYP7A1 and CYP8B1 in the TG-H+CG group were up-regulated （P<0.05， P<0.01）. The cell experiment showed that compared with the control group， the TG-h group presented up-regulated mRNA level of LXR-α （P<0.01）， and the TG-m and TG-h groups showcased down-regulated mRNA levels of LDLR and CYP7A1 （P<0.01） and up-regulated mRNA level of CYP27A1 （P<0.01） in HepG2 cells. The combination of CG with TG restored the above changes （P<0.01）. Western blotting results showed that compared with the control group， the TG-m and TG-h groups showed down-regulated protein levels of LXR-α， ABCG1， LDLR， CYP7A1， CYP8B1， and CYP27A1 in HepG2 cells （P<0.01）. Compared with the TG-h group， the TG-h+CG group showed up-regulated protein level of LDLR （P<0.05）. Compared with the TG-m group， the TG-m+CG group showcased up-regulated protein levels of LDLR， ABCG1， CYP7A1， and CYP27A1 （P<0.05， P<0.01）. ConclusionThe administration of TG at 189.0， 472.5 mg·kg^-1 for 3 weeks could modulate the signaling pathways associated with cholesterol efflux， endocytosis， and cholesterol biotransformation in hepatocytes， leading to the accumulation of cholesterol and subsequent liver injury in rats. CG could ameliorate the liver injury induced by lipid metabolism disorders caused by TG by up-regulating the expression of LXR-α， LDLR， ABCG1， CYP7A1， CYP8B1， and CYP27A1 to promote cholesterol biotransformation.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective To explore the effect of Xiongcan Yishen Formula on ferroptosis in testicular tissue of male rats with late-onset hypogonadism(LOH).Methods A total of 48 male Sprague-Dawley rats aged 6 months were randomly divided into model group,low-dose and high-dose Xiongcan Yishen Formula groups and propionate testosterone group,with 12 rats in each group.An additional 6 male Sprague-Dawley rats aged 8 weeks were set as the normal group.Except for the normal group,the rats were intraperitoneally injected with Cyclophosphamide at a dose of 20 mg/(kg·d)for 5 consecutive days to establish the LOH model,while the normal group received an equal volume of physiological saline for 5 days.The normal group and model group were given equal volumes of distilled water by gavage,while the low-dose and high-dose Xiongcan Yishen Formula groups were administered concentrated decoction at doses of 10.4 g and 41.6 g/kg/d respectively,and the propionate testosterone group received intramuscular injections of 5.21 mg/kg/d propionate testosterone,all for 28 consecutive days.ELISA was used to detect serum testosterone levels in rats,HE staining and transmission electron microscopy were used to observe the gross morphology of testicular tissue and the ultrastructure of Leydig cells,and RT-qPCR and Western blotting were used to detect the expression of ferroptosis-related genes and proteins in testicular tissue.Results The LOH model rats exhibited pathological changes such as atrophy of seminiferous tubules,structural disorder,and reduced spermatocytes in the lumen,as well as ultrastructural changes in Leydig cells including altered nuclear morphology,increased mitochondrial density,and reduced cristae.After intervention with Xiongcan Yishen Formula and propionate testosterone,the pathological changes in testis and the ultrastructure of Leydig cells were improved.Compared with the normal group,serum testosterone levels in the model group were significantly decreased(P＜0.05),the expression of ROS,ACSL4 mRNA and protein in testicular tissue was significantly increased,while the expression of FTH1,GPX4,and SLC7A11 mRNA and protein was significantly decreased(P＜0.05).Compared with the model group,ser-um testosterone levels in the low-dose and high-dose Xiongcan Yishen Formula groups and the propionate testosterone group were significantly increased(P＜0.05),and the expression of ROS,ACSL4 mRNA and protein was significantly decreased(P＜0.05);the high-dose Xiongcan Yishen Formula group showed significantly increased expression of FTH1,GPX4,and SLC7A11 mRNA and protein(P＜0.05).Conclusion Ferroptosis in testicular tissue is increased in LOH rats,and Xiongcan Yishen For-mula can elevate serum testosterone levels and improve pathological changes and ultrastructure in testicular tissue of LOH rats,possibly related to the inhibition of ferroptosis in testicular tissue of LOH rats.

Objective:To develop a rapid assessment scale for healthy aging suitable for the Chinese population.Methods:Based on existing healthy aging assessment scales, national standards, and expert consensus, an initial Healthy Aging Rapid Assessment Scale was drafted through two rounds of expert consultation. A pre-survey was conducted with 3 220 subjects recruited from Guangzhou between July 2023 and July 2024. Items were screened through item analysis and exploratory factor analysis to form the final scale. Reliability and validity of the final scale were validated across five cities: Guangzhou, Dongguan, Shenzhen, Baoding, and Chuxiong.Results:The initial version comprised 36 items, while the finalized scale contained 18 items across three dimensions: metabolic health, mental health, and cognitive health. Test-retest reliability ranged from 0.71 to 0.81 across all study sites. The Spearman-Brown coefficient varied between 0.91-0.96, Cronbach′s α between 0.77-0.83, comparative fit index (CFI) between 0.90-0.98, goodness-of-fit index (GFI) between 0.90-0.99, and root-mean-square error of approximation (RMSEA) between 0.03-0.09. For the three dimensions, reliability and validity metrics demonstrated consistency: Spearman-Brown coefficients 0.87-0.99, Cronbach′s α 0.77-0.83, CFI 0.90-0.98, GFI 0.90-0.99, and RMSEA 0.03-0.09 across four regions.Conclusion:The developed Healthy Aging Rapid Assessment Scale for the Chinese population exhibits robust reliability and validity.

Patients suffering from nerve injury often experience exacerbated pain responses and complain of memory deficits. The dorsal hippocampus (dHPC), a well-defined region responsible for learning and memory, displays maladaptive plasticity upon injury, which is assumed to underlie pain hypersensitivity and cognitive deficits. However, much attention has thus far been paid to intracellular mechanisms of plasticity rather than extracellular alterations that might trigger and facilitate intracellular changes. Emerging evidence has shown that nerve injury alters the microarchitecture of the extracellular matrix (ECM) and decreases ECM rigidity in the dHPC. Despite this, it remains elusive which element of the ECM in the dHPC is affected and how it contributes to neuropathic pain and comorbid cognitive deficits. Laminin, a key element of the ECM, consists of α-, β-, and γ-chains and has been implicated in several pathophysiological processes. Here, we showed that peripheral nerve injury downregulates laminin β1 (LAMB1) in the dHPC. Silencing of hippocampal LAMB1 exacerbates pain sensitivity and induces cognitive dysfunction. Further mechanistic analysis revealed that loss of hippocampal LAMB1 causes dysregulated Src/NR2A signaling cascades via interaction with integrin β1, leading to decreased Ca²⁺ levels in pyramidal neurons, which in turn orchestrates structural and functional plasticity and eventually results in exaggerated pain responses and cognitive deficits. In this study, we shed new light on the functional capability of hippocampal ECM LAMB1 in the modulation of neuropathic pain and comorbid cognitive deficits, and reveal a mechanism that conveys extracellular alterations to intracellular plasticity. Moreover, we identified hippocampal LAMB1/integrin β1 signaling as a potential therapeutic target for the treatment of neuropathic pain and related memory loss.
Animals ; Laminin/genetics* ; Hippocampus/metabolism* ; Neuralgia/metabolism* ; Cognitive Dysfunction/etiology* ; Male ; Peripheral Nerve Injuries/metabolism* ; Extracellular Matrix/metabolism* ; Integrin beta1/metabolism* ; Pyramidal Cells/metabolism* ; Signal Transduction

OBJECTIVE: The objective of this study was to analyse fungal composition and exploit application potential in the Bantou (BT) agarwood-forming trunk of Aquilaria sinensis. METHODS: BT agarwood is a naturally formed agarwood that was collected after cutting. Total genomic DNA of the fungi in BT agarwood was extracted by the hexadecyltrimethy ammonium bromide (CTAB) method, followed by PCR amplification and library construction. The effective tags were obtained by the HiSeq2500 platform, and the data were subjected to bioinformatics and statistical analyses. RESULTS: A total of 7 850 040 effective tags were obtained, Ascomycota was the most abundant fungus at the phylum level, with a relative abundance of 56.36%-61.44%, followed by Basidiomycota, with a relative abundance of 10.49%-20.39%. Dothideomycetes, Agaricomycetes and Sordariomycetes were dominant at the class level, accounting for 26.21%-33.88%, 8.40%-17.66%, and 18.41%-24.11%, respectively. Lignosphaeria, Phaeoacremonium and Hermatomyces were dominant at the genus level, with relative abundances of 6.25%-7.64%, 1.95%-9.05% and 1.5%-5.4%, respectively. Diversity and richness analysis showed that the fungal composition in the agarwood formation sites (agarwood layer, upper agarwood layer and lower agarwood layer) were significantly lower than those in the decomposing layer and the healthy layer. That is, the fungal diversity and richness were significantly reduced during agarwood formation by the action of open wounds. The fungal community structure in the decomposing layer and agarwood formation sites obviously differed from that in the healthy layer. The number of Aspergillus taxa in agarwood formation sites decreased significantly (healthy layer is 0.5%, decomposing layer is 0.022%, upper agarwood layer is 0.012%, agarwood layer is 0.01%, and lower agarwood layer is 0.013%), indicating that agarwood may contain potential substances to inhibit the growth of Aspergillus. CONCLUSION Agarwood from agarwood formation sites contains potential substances that inhibit Aspergillus, which provides valuable information for the control of the genus of Aspergillus.