BackgroundPatients with depressive episode and schizophrenia have a high risk of suicide. The sleep electroencephalogram power spectral density characteristics of patients with depressive episode accompanied by suicidal behavior and those with schizophrenia may be different， but there is currently a lack of direct comparative studies on these two groups of patients. ObjectiveTo compare the sleep electroencephalogram power spectral density between depressive episode and schizophrenic patients with suicidal behavior， in order to provide references for exploring predictive indicators of suicidal behavior. MethodsFrom June 2018 to December 2020， 20 patients with depressive episode and 20 patients with schizophrenia who had committed suicide within the past month and were treated at the outpatient department of Shenzhen Kangning Hospital were selected. All of them met the diagnostic criteria for depressive episode or schizophrenia as defined in the International Classification of Diseases， tenth edition （ICD-10）. Using a random sampling method， 20 volunteers with matching gender and age to the patient groups were selected from the Cuiping community in Shenzhen as the control group. The subjective sleep of the patients was evaluated using the Insomnia Severity Index （ISI）， the Dysfunctional Belief and Attitude about Sleep （DBAS）， the Disturbing Dreams and Nightmare Severity Index （DDNSI）， and the Epworth Somnolence Scale （ESS）. The objective sleep of the patients was assessed using polysomnography. The sleep electroencephalogram was filtered and the power spectral density of the brain wave was analyzed and processed for all the subjects. The subjective and objective sleep conditions of the two patient groups were compared， and the sleep electroencephalogram power spectral density of the patient groups and the control group were also compared. ResultsA comparison of subjective and objective sleep conditions between patients with depressive episode accompanied by suicidal behavior and patients with schizophrenia accompanied by suicidal behavior showed no statistically significant differences （P>0.05）. Comparisons of sleep electroencephalogram power spectral density in the W stage （average power of α wave， total power of δ wave， average power of δ wave， average power of θ wave）， N1 stage （average power of β wave， total power of α wave， total power of δ wave）， N2 stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave）， N3 stage （average power of α wave， average power of δ wave）， and R stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave） between patients with depressive episode accompanied by suicidal behavior， patients with schizophrenia accompanied by suicidal behavior， and the control group showed statistically significant differences （P<0.05 or 0.01）. The total power of δ wave in the W stage and the average power of β wave and δ wave in the N1 stage were higher in two patient groups were higher than those of the control group. The total power of α wave and the average power of α wave in the N2 stage were lower than those of the control group， while the average power of δ wave was higher than that of the control group. The average power of α wave in the N3 stage of both patient groups were lower than that of the control group， while the average power of δ wave was higher than that of the control group. The total power and average power of α wave in the R stage were lower than those of the control group， while the total power and average power of δ wave were higher than those of the control group. All the differences were statistically significant. Patients with depressive episode accompanied by suicidal behavior had higher average powers of α wave， δ wave， and θ wave in the W stage compared with the control group， while the total power of α wave in the N1 stage was lower in the former group. All these differences were statistically significant （P<0.05）. ConclusionThe depressive episode patients accompanied by suicidal behavior have highly overlapping sleep electroencephalogram abnormal patterns with those of schizophrenia patients， mainly manifested as a general decrease in α wave power （N2， N3， R stage） and a general increase in δ wave power （W， N1， N2， N3， R stage） as well as β wave power in N1 stage. At the same time， patients with depressive episode accompanied by suicidal behavior also show specific changes， including an increase in the average power of α and θ waves during the wakefulness period （W stage）， and a decrease in the total power of α wave in N1 stage. ［Funded by Guangdong Province High-level Clinical Key Specialty （with supporting funds from Shenzhen City） （number， SZGSP013）； Shenzhen Key Medical Discipline （number， SZXK041）； Shenzhen Clinical Medicine Research Center Project （number， 20210617155253001）］

Objective: To explore the influencing factors of anxiety symptoms and to construct a predictive model based on machine learning algorithms, so as to provide support for the prevention and management of anxiety symptoms among junior high school students. Methods: From April to May 2023, a stratified random cluster sampling method was adopted to select 8 176 junior high school students from Zhengzhou and Shangqiu citys. All participants completed the Adolescent Self rating Life Events Checklist, the 10item Connor-Davidson Resilience Scale, the School Connectedness Scale, the Parent-Child Cohesion Questionnaire, and the 7 item Generalized Anxiety Disorder Scale. Logistic regression analysis identified the associated factors of anxiety symptoms among junior high school students. Predictive models were constructed using Logistic regression, Random Forest, and eXtreme Gradient Boosting (XGBoost) algorithms, with SHapley Additive exPlanations analysis explaining the optimal model. Results: The detection rate of anxiety symptoms among junior high school students was 16.3%. Logistic regression analysis showed that junior high school students who were female ( OR =1.22), in the ninth grade ( OR =1.27), living in urban areas ( OR =1.37), having a father with a college education or above ( OR =1.26), having a mother with a senior high school education ( OR =1.26), and experiencing higher levels of negative life events ( OR =1.05) reported a higher risk of anxiety symptoms(all P <0.05). In contrast, those with moderate family economic status ( OR =0.71), moderate academic burden ( OR =0.59), low academic burden ( OR =0.54), moderate sleep quality ( OR =0.46), good sleep quality ( OR =0.26), excellent sleep quality ( OR =0.15), higher levels of psychological resilience ( OR =0.96), higher levels of school connectedness ( OR =0.96), and higher levels of parent-child cohesion ( OR =0.98) reported a lower risk of anxiety symptoms (all P <0.05). Three machine learning models demonstrated good predictive performance for anxiety symptoms among junior high school students (all AUC>0.8), with the XGBoost model achieving the best predictive performance. SHAP analysis revealed that negative life events, sleep quality, school connectedness, psychological resilience and parent-child cohesion were the top five relevant factors for predicting anxiety symptoms. Conclusions The detection rate of anxiety symptoms among junior high school students is relatively high. The XGBoost model is the optimal predictive model for anxiety symptoms in the population. Negative life events, sleep quality, school connectedness, psychological resilience, and parent-child cohesion are significant correlates of anxiety symptoms among junior high school students.

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.

ObjectiveTo investigate the inhibitory effect of gingerol， an active component of ginger， on Staphylococcus aureus （S. aureus） infection， and to preliminarily explore its mechanism related to extracellular vesicles （EVs）. MethodsS.aureus infection models were established in human umbilical vein endothelial cell （HUVECs）， Vero E6 cells， and C57BL/6 mice. Experimental groups included control， infection， and gingerol-treated groups. Bacterial load and VE-cadherin protein expression were detected using immunofluorescence and Western blot. EVs were isolated by size exclusion chromatography and characterized by transmission electron microscopy and nanoparticle tracking analysis. miRNA sequencing was performed on EVs. ResultsGingerol treatment significantly reduced the bacterial load in both in vitro and in vivo infection models and upregulated VE-cadherin expression. miRNA sequencing of EVs revealed that S. aureus infection upregulated the expression of hsa-miR-320c， while gingerol treatment reversed this abnormal expression. Bioinformatic analysis further predicted that the target genes of hsa-miR-320c were significantly enriched in cell junction-related pathways. ConclusionGingerol exhibits clear antibacterial and host-protective effects， by regulating hsa-miR-320c in EVs to maintain endothelial barrier integrity.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

ObjectiveTo investigate the screen exposure situation and its determinants among children aged 0‒3 years, so as to offer insights for intervening in children’s screen exposure. MethodsA total of 1 797 children who received routine physical examinations in Shaoxing Maternal and Child Health Care Hospital from January 2024 to December 2024 were enrolled. A self-designed screen exposure questionnaire was used to collect demographic information for children, educational attainment of parents and main caregivers, contents of video screen exposure, and video devices. The screen exposure rate among children was analyzed, and a multivariable logistic regression model was used to analyze its influencing factors. ResultsAmong the 1 797 children aged 0‒3 years, 935 were boys (52.03%), and 862 were girls (47.97%). The mean age was (21.81±9.97) months old. A total of 335 infants and toddlers had an average daily cumulative screen exposure >1 hour over the past week, with a screen exposure rate of 18.64%. Multivariable logistic regression analyses showed that the risk of screen exposure was higher with each one-year increase in the child’s age (OR=1.90, 95%CI: 1.58‒2.28), with cartoons or nursery rhymes as the main video content (OR=2.09, 95%CI: 1.27‒3.44; OR=1.75, 95%CI: 1.02‒2.97, respectively), and with watching videos during the period for meals or for parents doing housework, or before bedtime (OR=3.51, 95%CI: 2.08‒5.92; OR=2.92, 95%CI: 1.75‒4.88; OR=2.01, 95%CI: 1.16‒3.49, respectively). In contrast, higher maternal educational levels (OR=0.67, 95%CI:0.49‒0.92) were associated with a reduced rate of screen exposure. ConclusionAmong children aged 0‒3 years, their screen exposure is associated with their age, maternal educational level, screen content, and time of video watching. The departments should strengthen the education on screen exposure for older children and the mothers with lower education, while advocating for parents to scientifically and normatively manage screen content and time.

Objective: To present the plotting of trend analysis charts and the application of multi-rule trend analysis method for monitoring the quality of whole blood, washed red blood cells, and leukocyte-depleted suspended red blood cells. Methods: Samples of whole blood, washed red blood cells, and leukocyte-depleted suspended red blood cells were collected in accordance with relevant protocols and requirements. The results of blood quality testing were compiled. The trend line charts were plotted for the deviation rates of volume, hemoglobin (Hb) content, supernatant protein content, and leukocyte residual count. In addition, the trend line chart were plotted for hematocrit and post-storage hemolysis rate. Results: The trend analysis rules for the deviation rate of volume from the standard were: 1 categorized as out-of-control, (3 of 4) as warning, R as warning, 8 as alert, and 12 as alert. For Hb content deviation rate, the rules were: <0% categorized as out-of-control; <20% but ≥0% (for whole blood) or <10% but ≥0% (for washed red blood cells and leukocyte-depleted suspended red blood cells) as a warning. For supernatant protein content deviation rate, the rules were: ≥0.0% as out-of-control, and >-10% but <0.0% as a warning. For hematocrit, the rules were: 1 as out-of-control and (3 of 4) as warning. For leukocyte residual count deviation rate, the rules were: >0.0% as out-of-control, and >-10% but ≤0.0% as a warning. For post-storage hemolysis rate, the rule was: ≥0.8% out-of-control. Conclusion: The application of multi-rule trend analysis facilitates the timely identification of trend abnormalities and factors causing deviations in the collection and preparation processes of whole blood, washed red blood cells, and leukocyte-depleted suspended red blood cells, thereby providing reliable numerical evidence for their correction and adjustment.

Gastric cancer remains a highly prevalent malignancy worldwide, with surgical resection currently constituting the cornerstone of treatment aimed at improving long-term patient survival. Owing to their notable advantages, including reduced surgical trauma and accelerated postoperative recovery, minimally invasive procedures are progressively supplanting conventional open surgery and have become the mainstream approach in gastric cancer management. Concurrently, the rapid advancement of artificial intelligence (AI) technologies has enabled real-time intraoperative monitoring of surgical scenes, thereby furnishing novel technical support for adjunctive decision-making, surgical navigation, and skill assessment during gastrectomy. This article provides a systematic review of the current status of AI applications in minimally invasive gastric cancer surgery, with a particular focus on research progress pertaining to instrument recognition, surgical phase identification, delineation of normal anatomical structures, detection of metastatic foci, and early warning of intraoperative adverse events. Furthermore, we discuss the potential value of AI in enhancing surgical efficiency, ensuring patient safety, and optimizing surgical education. On this basis, we further analyze the principal challenges and inherent risks confronting current AI systems, with the aim of informing future technological innovation and facilitating clinical translation.

OBJECTIVE To provide a reference for clinical pharmacists to participate in the treatment of rare and complex cases of CTLA-4 haploid deficiency combined with severe malnutrition. METHODS The clinical pharmacist participated in the diagnosis and treatment of a complex case of CTLA-4 haploid deficiency with severe malnutrition， type 1 diabetes， blood coagulation abnormalities with gastrointestinal bleeding and virus infection， assisted the doctor to develop an individualized parenteral nutrition program， and dynamically adjusted the ratio of glucose and insulin （from 3.9∶1 to 15.6∶1）. When patient had severe coagulation abnormalities and gastrointestinal bleeding， the clinical pharmacist recommended discontinuing fat emulsion and switching to glucose amino acid dual energy supply； when the patient had a high fever accompanied by a sudden drop in platelets， the clinical pharmacist recommended to improve the second-generation sequencing of plasma metagenomics. Based on positive results for both EB virus and cytomegalovirus， the clinical pharmacist recommended to discontinue meropenem and switch to ganciclovir for antiviral treatment； when the patient experienced systemic itching and mental excitement， the clinical pharmacist quickly diagnosed as an adverse reaction of ganciclovir and recommended to switch to acyclovir for antiviral treatment. The clinical pharmacist simultaneously carried out parenteral nutrition medication education， and standardized infusion speed， and continuously monitored bleeding-related indicators. RESULTS The physician adopted the advice of the clinical pharmacist. After comprehensive intervention， the patient’s body temperature returned to normal， gastrointestinal bleeding stopped， coagulation indicators significantly improved， blood sugar control reached the standard， and the condition improved and the patient was discharged. CONCLUSIONS Clinical pharmacists rely on comprehensive pharmaceutical services to balance the benefits and risks of treatment for rare and complex cases. They play a key role in individualized nutrition planning， refined blood glucose control， infection identification and anti-infection optimization， and identification and treatment of adverse drug reactions to ensure patient medication safety and efficacy.