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.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective: To explore the correlation between parent-child separation experience and non suicidal self injury (NSSI) behavior among junior and senior high school students, so as to provide a reference for the prevention and improvement of NSSI behavior among junior and senior high school students. Methods: Using a stratified cluster random sampling method, 3 114 junior and senior high school students aged 11-19 years were recruited from Chenzhou and Jishou cities in Hunan Province between November 2024 and September 2025. A self designed questionnaire and the Functional Self injury Behavior Assessment Scale were used to collect information on parental labor migration and adolescents NSSI behavior status. Binary Logistic regression model was used to analyse the association between parent-child separation experiences and NSSI behavior among junior and senior high school students, with further stratified analysis by gender. Results: The prevalence rate of NSSI behavior among junior and senior high school students was 9.9%, and the overall incidence of parent-child separation was 48.9%, comprising 17.1% separated from their father only, 5.5% separated from their mother only, and 26.3% separated from both parents. After adjusting for variables such as age, gender, and ethnicity, the results of binary Logistic regression analyses indicated that adolescents with parent-child separation experiences had a higher risk of NSSI behavior ( OR =1.31, 95% CI =1.01-1.69, P <0.05). Compared with those without parent-child separation experiences, adolescents who were separated from their mother only ( OR =1.68, 95% CI =1.03-2.74) or from both parents ( OR =1.41, 95% CI =1.04-1.92) showed significantly increased risks of NSSI behavior (both P <0.05). Conclusions Parent-child separation experiences are associated with an increased risk of NSSI behavior among junior and senior high school students. Strengthened attention should be paid to left behind senior high school students to reduce the occurrence of NSSI in adolescents.

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 To explore the correlation between thyroid hormones and massive proteinuria in patients with type 2 diabetes mellitus (T2DM). Methods A total of 308 patients with T2DM admitted to 3201 Hospital between June 2020 and June 2025 were selected as the observation group, and another 250 healthy individuals who underwent physical examinations during the same period served as the control group. The thyroid hormones levels [free triiodothyronine (FT₃), thyroid stimulating hormone (TSH), and free thyroxine (FT₄)] were measured and compared between the two groups. Based on whether 24-hour urinary protein quantification was ≥ 3.5 g, the patients in the observation group were divided into a massive proteinuria group and a non-massive proteinuria group. Multivariate logistic regression analysis was used to analyze the factors influencing the occurrence of massive proteinuria in T2DM patients. Pearson method was applied to analyze the relationship of thyroid hormone indicators with severity indicators of massive proteinuria. Results Compared with the control group and the non-massive proteinuria group, FT₃ and FT₄ in the massive proteinuria group were lower, while TSH was higher (P<0.05). Multivariate logistic regression analysis suggested that glycosylated hemoglobin (OR=1.113, 95%CI: 1.045-1.185), TSH (OR=1.123, 95%CI: 1.006-1.253), eGFR (OR=0.894, 95%CI: 0.822-0.973), and FT₃ (OR=0.898, 95%CI: 0.828-0.973) were related factors for the occurrence of massive proteinuria in T2DM patients (P<0.05). Pearson correlation analysis revealed that FT3 and FT4 levels in T2DM patients were significantly negatively correlated with 24-hour urinary protein quantification (r=-0.514, -0.502), while the level of TSH was positively correlated with 24-hour urinary protein quantification (r=0.486) (P<0.001). Conclusion In T2DM patients, low FT3 and eGFR levels and high TSH and glycosylated hemoglobin levels are related factors for the occurrence of massive proteinuria, and thyroid hormone levels are significantly associated with the severity of massive proteinuria.

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.

Primary female genital system lymphoma(PFGSL)is a rare subtype of extranodal lymphoma and patients commonly present in the department of gynecology.At present,there is a lack of uniform standards for the treatment of PFGSL.Although the classification of lymphoid neoplasmas was updated by the World Health Organization classification of haematolymphoid tumors in 2016,PFGSL was still not elaborated in sufficient detail.Most cases of PFGSL are non-Hodgkin lymphoma,involving the ovary and cervix.In some cases,involvement of uterine corpus,vagina,and vulva is reported.In this article,we report two cases of non-Hodgkin lymphoma in the female genital system,one from the uterus and the other from the ovary.By presenting the diagnosis and treatment of the two cases and reviewing the literature,we aim to provide a reference for clinicians in recognizing and treating rare cases.
Female ; Humans ; Genital Neoplasms, Female/diagnosis* ; Lymphoma, Non-Hodgkin/diagnosis* ; Ovarian Neoplasms

Objective To investigate the efficacy of the ultraviolet A-riboflavin cross-linking corneal stromal lenticule punctal plug for the treatment of dry eyes in rabbits.Methods Thirty-two New Zealand white rabbits(64 eyes)were se-lected and randomly divided into a normal group,a model group,a conventional plug group and a cross-linking plug group,with 8 rabbits(16 eyes)in each group.Rabbits in the normal group were not treated.In the model group,moderate-to-se-vere dry eye rabbit models were constructed but no treatment was given.Rabbits in the conventional and cross-linking plug groups were implanted with conventional and cross-linking plugs after model construction,respectively.The tear film func-tions of the experimental rabbits,including tear secretion volume(SIT),corneal fluorescein sodium staining,tear film break-up time(BUT),and tear meniscus height(TMH),were detected before the intervention,1 day,1 week,2 weeks,and 4 weeks after the intervention.In addition,the corneas of each group were collected for hematoxylin and eosin(HE)staining to observe the changes of the corneal epithelium 4 weeks after the intervention.Finally,the non-cross-linking and cross-linking corneal stromal lenticules were placed separately in 1 g·L-1 of type Ⅰ collagenase to observe the change of the lenticule diameter over time.Results In the cross-linking plug group,the SIT,BUT and TMH values 2 and 4 weeks after the intervention were significantly higher than those before the intervention(all P＜0.01).In the conventional plug group,the SIT,BUT and TMH values 4 weeks after intervention were significantly higher than those before the intervention(all P＜0.01).After 4 weeks of intervention,the corneal staining of rabbits in the cross-linking plug group was better than that in the conventional plug group and model group.The HE staining results showed that in the cross-linking plug group,the corneal epithelial thickness of rabbits was basically normal,epithelial cells were basically arranged in order,and a single layer of columnar epithelial cells was observed on the basal layer.The dissolution time of the corneal stromal lenticule after cross-linking was significantly increased,compared with that of the non-cross-linking one.Conclusion The ultraviolet A-riboflavin cross-linking corneal stromal lenticule punctal plug has a more stable therapeutic effect on the rabbit dry-eye model than the conventional one,so it is expected to provide a novel approach for the clinical treatment of dry eyes.

Aim To investigate the effect of tetrameth-ylpyrazine(TMP)on neuroinflammation after cerebral ischemia and hypoxia via mannose-binding lectin(MBL).Methods Patients diagnosed with ischaemic stroke at Shanxi Provincial People's Hospital were in-cluded in the study,and their clinicopathological data,as well as blood and urine samples,were collected with the consent of the patients and their families.Using these biological samples,differential proteins and tar-gets were identified by proteomic analysis and subse-quently verified with animal experiments.The mice were divided into the sham,dMCAO,and TMP(10,20,40 mg·kg-1)treatment groups.After seven days of drug administration,the modified neurological sever-ity score(mNSS)was used to assess the neurological function.TTC staining was used to detect the volume of cerebral infarction.Motor function was evaluated be-haviourally,and ELISA was used to detect MASP1,sC5b-9,TNF-α,IL-6,and IL-1β.Western blot was used to determine the expression of relevant proteins,such as MBL2,MASP2,and C3.Results Compared with the sham group,the dMCAO group exhibited in-creased neurological impairment,which was signifi-cantly ameliorated by TMP treatment.The expression levels of MBL2,C3 and MASP2 were elevated in the dMCAO group and were reduced following TMP treat-ment.Additionally,the dMCAO group showed elevat-ed expression of inflammatory factors IL-1 β,IL-6 and TNF-α,which were then suppressed by TMP treat-ment.Conclusion TMP inhibits the inflammatory re-sponse after ischemia and hypoxia by regulating MBL,thus attenuating brain injury.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.