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.

Bronchial asthma （abbreviated as asthma） is one of the common chronic airway inflammatory diseases in the respiratory system， which is difficult to cure. Airway mucus hypersecretion （AMH） is an important factor leading to acute asthma attacks. Traditional Chinese medicine （TCM） possesses therapeutic advantages characterized by multiple pathways， multiple targets， and multiple links， and its mechanism of action in intervening in AMH has gradually drawn attention. TCM can effectively alleviate the symptoms of patients by intervening in asthma through methods such as eliminating phlegm and eliminating fluid retention. This review finds that the pathogenesis of asthma-associated AMH is correlated with decreased mucociliary clearance function and enhanced mucus secretion function； single TCM （such as Platycodon grandiflorum）， effective components of TCM （such as pinellia polysaccharides）， and compound prescriptions （mainly heat-clearing and phlegm-resolving prescriptions， etc.） can improve asthma-associated AMH by regulating the PI3K/Akt and JAK/STAT signaling pathways， inhibiting airway inflammatory responses， oxidative stress， and recovering the water-salt ratio of the mucus layer itself.

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: 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.

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: To investigate the potential efficacy and safety of Lutai Danshen Baishao granules (LDBG) for treating female melasma associated with kidney deficiency and blood stasis patterns. Methods: A randomized, double-blind, placebo-controlled trial was conducted at the Third Central Hospital of Tianjin, China from March to December 2023. A total of 110 female patients with melasma linked to kidney deficiency and blood stasis were enrolled and treated with either LDBG or a placebo twice daily for 60 days. Efficacy was assessed through measures such as the total melasma area, reduced melasma area, reduction rate of melasma area, melasma color score, Melasma Area and Severity Index (MASI) score, and traditional Chinese medicine (TCM) symptom score scale. Safety assessments included routine blood and biochemical tests. Results: Participants in both groups were aged 52–63 years, with no significant differences. After the 2-month intervention, the total melasma area decreased in both groups; however, a greater reduction was observed in the test group [462.50 mm2 (12.81%) vs. 100.00 mm2 (3.11%), P < .001]. Moreover, LDBG treatment significantly reduced the MASI and melasma color scores in the test group (P < .05). The total TCM symptom evaluation score significantly decreased (test group: 6.00 vs. placebo group: 7.00, P = .001), with significant relief in symptoms such as improvement in dark lips, nails, and waist soreness in the test group, compared with that in the placebo group (P < .05). Within-group comparisons revealed that TCM syndrome was significantly alleviated in the test group (P < .05). Conclusion LDBG intervention shows promising effectiveness in reducing female melasma and alleviating TCM syndromes.

OBJECTIVE To compare the clinical efficacy and safety of remimazolam and propofol in general anesthesia induction and maintenance for elderly patients undergoing thoracoscopic lobectomy. METHODS A total of 86 elderly lung cancer patients who underwent thoracoscopic lobectomy at Chongqing University Three Gorges Hospital from February to July 2024 were selected and divided into the propofol group and the remimazolam group according to the randomized numerical table method， with 43 cases in each group. During anesthesia induction， patients in the propofol group and the remimazolam group were intravenously administered 2 mg/kg of Propofol medium- and long-chain fat emulsion injection or 0.25 mg/kg of Remimazolam tosilate for injection， respectively； during anesthesia maintenance， the two groups received intravenous infusion of 6-10 mg/（kg·h） of Propofol medium- and long- chain fat emulsion injection or 1-3 mg/（kg·h） of Remimazolam tosilate for injection， respectively. The anesthesia effects， anesthesia-related indicators， intraoperative opioid and muscle relaxant dosages， Ramsay sedation score， numerical rating scale （NRS） score， and hemodynamic parameters were compared between the two groups， and the occurrence of adverse drug reactions was recorded. RESULTS A total of 41 patients in the propofol group and 43 patients in the remimazolam group completed the trial. The proportion of patients with grade Ⅰ anesthesia effect in the remimazolam group was significantly higher than that in the propofol group， while the proportion of patients with grade Ⅱ anesthesia effect was significantly lower than that in the propofol group （P＜0.05）. In this group， the disappearance time of eyelash reflex， the time taken for the bispectral index to drop to 60， and the Ramsay sedation scores （2 and 6 hours after operation） were all significantly prolonged or increased， while the recovery time， NRS scores （2 and 6 hours after operation）， and the incidence of intraoperative hypotension were all significantly shortened or reduced； moreover， the improvements of the above sedation/NRS scores exhibited a time-dependent pattern within 2 to 24 hours after operation （P＜0.05）. Compared with before anesthesia induction （T0）， the heart rate [except at 2 min after medication （T1）， 60 min after anesthesia （T4）， and at the end of surgery （T5） in the remimazolam group] and mean arterial pressure [except at T1 in the remimazolam group] of patients in both groups significantly decreased at T1， 5 min after medication （T2）， at the start of surgery （T3）， T4， and T5 （P＜0.05）. Meanwhile， regional cerebral oxygen saturation significantly increased in both groups. Furthermore， the heart rate and mean arterial pressure of patients in the remimazolam group were significantly higher than those in the propofol group at T1， T2 and T4 （P＜0.05）. No statistically significant differences were observed between the two groups in terms of postanesthesia care unit stay time， dosage of opioids and muscle relaxants， regional cerebral oxygen saturation， or peripheral oxygen saturation at various time points （P＞0.05）. CONCLUSIONS Compared to propofol， remimazolam demonstrates superior anesthesia effects when used for the induction and maintenance of general anesthesia in elderly patients undergoing thoracoscopic lobectomy. It not only provides more stable intraoperative hemodynamics and shortens the postoperative recovery time but also effectively reduces the incidence of intraoperative hypotension.