Background: Influenza A virus (IAV) is a negative-sense RNA virus of the Orthomyxoviridae family and is the etiological agent of a highly contagious acute respiratory disease that can lead to acute lung injury. Objective: To elucidate the molecular mechanisms of IAV infection, an integrative research approach combining gene expression profiling, multinetwork analysis, and in vivo experimental validations was employed. Methods: First, a series of network-based analyses were performed, including protein-protein interaction network construction, weighted gene co-expression network analysis, and subsequent gene set enrichment analysis, to identify the major underlying mechanisms of IAV infection. Following gene expression analysis, core targets, both direct and indirect regulators, were screened. An IAV (H1N1) strain A/PR/8/34-induced acute lung injury mouse model was constructed for in vivo validations. Batch one included two groups to evaluate findings from the multi-network analysis: Mock (n = 10; 5 males and 5 females) and IAV (n = 10; 5 males and 5 females). Batch two included three groups to assess the role of toll-like receptor 3 (TLR3) in IAV infection: Mock (n = 6; 3 males and 3 females), IAV (n = 6; 3 males and 3 females), and TLR3 inhibitor (n = 6; 3 males and 3 females). Body weight was measured on days 0, 3, and 5 after infection. On day 5, lung tissues were collected to assess viral load and histopathological changes. Key targets were examined using enzyme-linked immunosorbent assay, Western blotting, and immunofluorescence staining, both in sera and lung tissues. Results: IAV infection was significantly associated with dysregulation of the immune-inflammation system, such as the LTR, nucle-otide-binding oligomerization domain-(NOD) like receptor, retinoic acid-inducible gene I-like receptor, and nuclear factor kappa-B signaling pathways. Gene set enrichment analysis further indicated that the TLR and necroptosis signaling pathways played crucial roles in the progression of IAV infection (TLR signaling pathway normalized enrichment score = 2.3941, P = 1.00 × 10 ⁻¹⁰; necroptosis normalized enrichment score = 1.9421, P = 6.21 × 10 ⁻⁷). Among the core targets, TLR3 and mixed lineage kinase domain-like protein (MLKL) may regulate gene expression at the transcriptional level (all P < 0.05). In vivo validation using an IAV (PR8) infected acute lung injury mouse model demonstrated increased viral load and lung index, alveolar structural damage, and inflammatory cell infiltration. Immunofluorescence staining exhibited large gaps in Lamin B1 staining and breaches in Emerin signals following IAV-PR8 infection. Expression levels of TLR3, p-receptor-interacting serine/threonine-protein kinase 3 (RIPK3)/RIPK3, and p-mixed lineage kinase domain-like protein (MLKL)/MLKL proteins in lung tissues, as well as proinflammatory factors and mediators in sera, were significantly elevated after IAV infection. Moreover, enhanced neutrophil infiltration (myeloperoxidase) and citrullinated histone H3 (a neutrophil extracellular trap-specific marker), both established indicators of neutrophil extracellular trap formation, were observed. Notably, treatment with a TLR3 inhibitor significantly ameliorated IAV-induced acute lung injury by regulating necroptosis-related targets. Conclusion: Our study provides network-based in vivo evidence that TLR3-receptor-interacting serine/threonine-protein kinase 3-MLKL-mediated necroptosis may underlie IAV-induced acute lung injury and could serve as a potential therapeutic target in severe influenza cases.

Objective To investigate the prevalence of cognitive frailty and its associated factors among middle-aged and elderly patients with chronic obstructive pulmonary disease (COPD) in Gusu District, Suzhou City, to provide a basis for intervention measures. Methods COPD patients managed at Pingjiang New Town Community Health Service Center in Gusu District from January to December 2024 were selected. Data were collected using the Fried Frailty Phenotype, Mini-Mental State Examination, and a general information questionnaire. Chi-square tests, one-way analysis of variance, and multivariate Logistic regression were used for data analysis. Results A total of 1 388 patients were included, with 916 males (65.99%) and 472 females (34.01%). Cognitive frailty was observed in 554 cases (prevalence: 39.91%). Univariate analysis showed significant differences in gender, education, visual impairment, hearing impairment, sleep disorders, and disease duration between the cognitive frailty and non-cognitive frailty groups (all P<0.05). Multivariate Logistic regression indicated that education was negatively associated with cognitive frailty (illiteracy OR=6.969, P<0.001; primary school OR=1.499, P=0.005), while visual impairment (OR=2.347, P<0.001), hearing impairment (OR=1.705, P<0.001), sleep disorders (OR=2.488, P<0.001), and disease duration (≤5 years OR=0.329, P<0.001; 6-10 years OR=0.487, P<0.001) were positively associated with cognitive frailty. Conclusion The prevalence of cognitive frailty among middle-aged and elderly COPD patients in Gusu District, Suzhou City, is high (39.91%). Epositively associated with cognitive frailtyducation, sensory impairments, sleep disorders, and disease duration are associated factors. Clinical attention to high-risk groups and implementation of early screening and targeted interventions are recommended.

Background: and Purpose Vertebrobasilar fusiform aneurysms (VBFAs) carry substantial morbidity and mortality, but optimal management for unruptured VBFAs remains unclear. We compared the safety and efficacy of conservative management (CM), stent-assisted coiling (SAC), and flow diverters (FDs) in patients with unruptured VBFAs, focusing on long-term prognosis. Methods: This study included data from a nationwide Chinese cohort of patients with vertebrobasilar dissecting aneurysms. Inverse probability of treatment weighting (IPTW) balanced confounders across groups. The primary outcome was poor prognosis (modified Rankin Scale score >2). Secondary outcomes included aneurysm rupture, ischemic stroke, compression symptoms, and VBFA-related deaths. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup and sensitivity analyses were performed. Results: Among 1,115 patients with unruptured VBFAs, 838 (median age, 54 years; 655 men) were included. After IPTW, baseline characteristics were balanced. Median follow-up was 54 months. FD was associated with a lower risk of poor prognosis than CM (OR, 0.48 [95% CI, 0.30 to 0.77]; p=0.002), with no difference between CM and SAC. FD also reduced aneurysm rupture (OR, 0.20 [95% CI, 0.07 to 0.60]; p=0.004) and compression symptoms (OR, 0.30 [95% CI, 0.13 to 0.68]; p=0.004) versus CM. Time-to-event analyses further revealed significant differences in vertebral artery lesions and Type I–II VBFAs, whereas no significant differences were observed in basilar or vertebrobasilar junction lesions or in Type III–IV VBFAs. Conclusions Compared with CM, FD was associated with improved long-term outcomes in unruptured VBFAs, particularly in vertebral artery lesions and Type I–II VBFAs, although residual confounding cannot be excluded.

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.

ObjectiveTo investigate the association between insulin resistance （IR） and cardiovascular metabolic indicators， including blood pressure， blood lipids， and serum uric acid， in a middle-aged population. MethodsBased on the baseline survey of the Hong Sifang cohort of China National Salt Industry Group， a total of 575 participants were included. According to the homeostasis model assessment of insulin resistance， the participants were divided into an IR group （n=116） and a non-IR group （n=459）. Differences between the two groups were compared using the t-test and chi-square test. Multivariate logistic regression analysis was performed to evaluate the associations between IR and abnormalities in metabolic indicators. ResultsA total of 575 participants were included， including 390 men and 185 women， with a mean age of （48.58 ± 5.14） years and a mean body mass index （BMI） of （24.16 ± 2.97） kg/m². Blood pressure， serum uric acid， and blood lipid levels were significantly higher in the IR group than in the non-IR group （P<0.001）. After adjusting for potential confounders including age， sex， and BMI， IR was independently associated with hypertension， dyslipidemia， and hyperuricemia， with odds ratios （OR） and 95% confidence intervals （CI） of 2.57 （1.61-4.09）， 3.81 （2.36-6.17）， and 2.68 （1.53-4.71）， respectively （all P<0.001）. ConclusionInsulin resistance is significantly associated with multiple cardiovascular metabolic risk factors in the middle-aged population. Monitoring IR may contribute to the early prevention and control of cardiovascular diseases.

ObjectiveTo investigate the intervention effects of Suanzaoren Tang on depression model rats induced by isolation combined with chronic unpredictable mild stress （CUMS）， and to examine its influence on the c-Jun N-terminal kinase （JNK）/proto-oncogene protein （c-Myc）/tumor suppressor protein 53 （p53） signaling pathway， thereby revealing its potential functional mechanism. MethodsA total of 72 male SD rats were randomly divided into six groups using a strict random number table： blank group， model group， fluoxetine group （3.6 mg·kg^-1）， and high-， medium-， and low-dose Suanzaoren Tang groups （10， 5， 2.5 g·kg^-1），with 12 rats in each group. A depression model was established using isolation combined with CUMS. Fluoxetine and different doses of Suanzaoren Tang were administered continuously for 28 days. Behavioral indicators such as sucrose water consumption and open field test scores were recorded. Western blot and immunohistochemistry （IHC） were employed to analyze the expression of key proteins in the JNK/c-Myc/p53 signaling pathway， and the terminal deoxynucleotidyl transferase dUTP nick end labeling （TUNEL） assay was used to evaluate the number of apoptotic cells in the hippocampus. ResultsCompared with the blank group， the model group exhibited a significantly reduced sucrose preference index （P<0.01）， a lower total score of horizontal and vertical movements in the open field test （P<0.01）， significantly increased expression of JNK， c-Myc， and p53 proteins in the hippocampus （P<0.01）， and a higher number of TUNEL-positive cells in the hippocampus （P<0.01）. Compared with the model group， the sucrose preference index and the total score of horizontal and vertical movements in the open field test significantly increased in the high- and medium-dose Suanzaoren Tang groups and the fluoxetine group （P<0.05， P<0.01）. The expression of JNK， c-Myc， and p53 proteins significantly decreased in all Suanzaoren Tang groups （high， medium， and low doses） and the fluoxetine group （P<0.05， P<0.01）. The number of TUNEL-positive cells in the hippocampus also significantly decreased in these groups （P<0.01）. ConclusionSuanzaoren Tang can regulate the expression of JNK/c-Myc/p53 proteins in the hippocampus of depression model rats， and its antidepressant mechanism may be related to its protective effect on hippocampal neurons.

Objective To observe the clinical efficacy of mind-regulating and meridians-dredging acupuncture combined with rehabilitation training in treating limb dysfunction in recovery period of cerebral infarction(CI).Methods A total of 110 cases of patients with limb dysfunction in recovery period of CI were randomly divided into observation group and control group,55 cases in each group,the control group was given routine rehabilitation training,and the observation group was treated with mind-regulating and meridians-dredging acupuncture on the basis of intervention of the control group,the course of treatment covered two consecutive weeks.After two weeks of treatment,the clinical efficacy of the two groups was evaluated,and the changes of scores of traditional Chinese medicine(TCM)syndrome,Fugl-Meyer Assessment(FMA),Berg Balance Scale(BBS)and Modified Barthel Index(MBI)before and after treatment of patients in the two groups were observed.The changes of electromyographic signal before and after treatment were compared between the two groups.And the safety and the occurrence of adverse reactions in the two groups were evaluated.Results(1)The total effective rate was 98.18%(54/55)in the observation group and 87.27%(48/55)in the control group.The efficacy of the observation group was superior to that of the control group,the difference being statistically significant(P<0.05).(2)After treatment,the TCM syndrome scores of patients in the two groups were significantly improved(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,with a statistically significant difference(P<0.05).(3)After treatment,the FMA scores of patients in the two groups improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(4)After treatment,the BBS scores and MBI scores of the patients in the two groups improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(5)After treatment,the root mean square value(RMS)of biceps brachii muscle elbow flexion and triceps brachii muscle elbow extention of the two groups of patients improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(6)During the treatment,there were no obvious adverse reactions occurred in both groups.Conclusion Mind-regulating and meridians-dredging acupuncture combined with rehabilitation training in treating limb dysfunction in recovery period of CI can significantly improve the motor ability of patients,and adjust the electromyographic signals of the affected limbs,with high safety.

Objective To evaluate the predictive value of dose-surface histogram(DSH)for radiation proctitis(RP)in prostate cancer(PCa)patients undergoing radiotherapy.Methods This prospective randomized controlled clinical trial included 380 PCa patients who underwent image-guided radiotherapy in the First Affiliated Hospital of Hebei Northern University from January 2018 to January 2023.Patients were randomly divided into observation group(n=200)and control group(n=180).The rectal dose distribution of patients in the two groups was evaluated by using DSH and dose-volume histogram(DVH),respectively.The receiver operating characteristic(ROC)curve was utilized to evaluate the predictive value of DSH for acute RP,with DVH serving as a reference.Results The difference was not statistically significant in clinical information such as age,KPS score,and body mass index(BMI)between the observation and control groups(P＞0.05),as well as in acute RP incidence(P＞0.05).There were significant differences in S40 and V40,S50 and V50,S60 and V60,S70 and V70,and S78 and V78 between the two groups(P＜0.05).S40,S50,V40,and V50 showed low efficacy(P＜0.001)in predicting acute RP at each level,with AUC≤0.700.S60 and V60 showed moderate efficacy(P＜0.001)in predicting acute RP at each level,with AUC 0.700-0.900.S70,S78,V70 and V78 showed high efficacy(P＜0.001)in predicting acute RP at each level,with AUC＞0.900.Conclusions The predictive value of DSH for rectal toxicity in patients with PCa is basically consistent with that of DVH.It is expected to become a novel and valuable tool for evaluating radiotherapy plans in the future.

Non-functioning pituitary adenomas(NFPAs)are relatively common.Apart from hyperprolactinemia caused by pituitary compression,they typically lack overt hormonal hypersecretion and usually present with clinical symptoms due to mass effects.Previously considered a uniform entity,NFPAs are actually a highly heterogeneous group of tumors,including aggressive subtypes like silent corticotroph adenomas(SCA)and null cell adenomas.The 2022 WHO new classification of pituitary tumors employs transcription factors[e.g.,pituitary-specific transcription factor 1(PIT-1),T-box transcription factor 19(TBX19,also known as TPIT),steroidogenic factor 1(SF-1)]for detailed categorization,allowing precise subclassification of NFPAs into multiple subtypes derived from distinct cell lineages,including silent gonadotroph adenomas,SCA,and plurihormonal PIT-1-positive adenomas.This helps identify highly invasive subtypes with high recurrence risk,guiding clinical diagnosis and treatment,prognostic assessment,and individualized management.The new classification also provides a theoretical basis for targeted therapies of NFPAs(e.g.,somatostatin analogs and temozolomide).This review comprehensively discusses the latest pathological classification of NFPAs and its clinical implications,aiming to enhance understanding of this disease and offer valuable insights for precise diagnosis,treatment,and prognostic assessment.

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome