ObjectiveTo establish a risk recognition model for coronary artery stenosis by using a machine learning method and to identify the key causative factors. MethodsPatients aged ≥18 years，diagnosed with coronary heart disease through coronary angiography from January 2013 to May 2020 in two prominent hospitals in Shanxi Province， were continuously enrolled. Logistic regression，back propagation neural network （BPNN）， and random forest（RF）algorithms were used to construct models for detecting the causative factors of coronary artery stenosis. Sensitivity （TPR）， specificity （TNR）， accuracy （ACC）， positive predictive value （PV+）， negative predictive value （PV-）， area under subject operating characteristic curve （AUC）， and calibration curve were used to compare the discrimination and calibration performance of the models. The best model was then employed to predict the main risk variables associated with coronary stenosis. ResultsThe RF model exhibited superior comprehensive performance compared to logistic regression and BPNN models. The TPR values for logistic regression，BPNN，and RF models were 75.76%， 74.30%， and 93.70%， while ACC values were 74.05%， 72.30%， and 79.49%， respectively. The AUC values were：logistic regression 0.739 9； BPNN 0.723 1； RF 0.752 2. Manifestations such as chest pains，abnormal ST segments on ECG，ventricular premature beats with hypertension， atrial fibrillation， regional wall motion abnormalities（RWMA） by color echocardiography， aortic regurgitation（AR）， pulmonary insufficiency （PI）， family history of cardiovascular diseases，and body mass index（BMI）were identified as top ten important variables affecting coronary stenosis according to the RF model. ConclusionsRandom forest model shows the best comprehensive performance in identification and accurate assessment of coronary artery stenosis. The prediction of risk factors affecting coronary artery stenosis can provide a scientific basis for clinical intervention and help to formulate further diagnosis and treatment strategies so as to delay the disease progression.

Objective To investigate the effect of pneumoperitoneum pressure during robotic-assisted kidney transplantation (RAKT) on the function of the transplant kidney. Methods The data of 243 kidney transplant recipients were retrospectively analyzed and divided into open kidney transplantation (OKT) group (n=105) and RAKT group (n=138). The RAKT group was further divided into 13 mmHg group (n=67) and 7 mmHg group (n=71) based on pneumoperitoneum pressure. The donor information, recipient's preoperative general data, intraoperative data, and postoperative recovery of the three groups were compared. In the RAKT group, the renal artery, segmental artery, interlobar artery, and venous flow velocity of the transplant kidney were measured using laparoscopic ultrasound. Results There was a statistically significant difference in donor types among the groups (P<0.05), while other donor information and recipient's preoperative general data showed no statistically significant differences (all P>0.05). There were no statistically significant differences in serum creatinine and complications at 30 days and 1 year postoperatively among the groups (all P>0.05). The OKT group and 7 mmHg group had more intraoperative urine output than the 13 mmHg group. Both RAKT groups had less intraoperative blood loss and shorter hospital stays than the OKT group, and longer operation times than the OKT group (all P<0.05). There were no statistically significant differences in operation time, intraoperative blood loss, and hospital stay between the two RAKT groups (all P>0.05). The vascular flow velocity of the transplant kidney decreased at 13 mmHg compared to 7 mmHg pneumoperitoneum pressure, but the differences were not statistically significant (all P>0.05). Conclusions Controllable pneumoperitoneum pressure has a limited impact on the vascular flow velocity of the transplanted kidney. RAKT is a safe and effective surgical method under appropriate pneumoperitoneum pressure, and choosing a lower pneumoperitoneum pressure is more conducive to the early recovery of renal function postoperatively.

BACKGROUND: Lung cancer is currently the most prevalent malignancy and the leading cause of cancer deaths worldwide. Although the early stage non-small cell lung cancer (NSCLC) presents a relatively good prognosis, a considerable number of lung cancer cases are still detected and diagnosed at locally advanced or late stages. Surgical treatment combined with perioperative multimodality treatment is the mainstay of treatment for locally advanced NSCLC and has been shown to improve patient survival. Following the standard methods of neoadjuvant therapy, perioperative management, postoperative adjuvant therapy, and other therapeutic strategies are important for improving patients' prognosis and quality of life. However, controversies remain over the perioperative management of NSCLC and presently consensus and standardized guidelines are lacking for addressing critical clinical issues in multimodality treatment. METHODS: The working group consisted of 125 multidisciplinary experts from thoracic surgery, medical oncology, radiotherapy, epidemiology, and psychology. This guideline was developed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. The clinical questions were collected and selected based on preliminary open-ended questionnaires and subsequent discussions during the Guideline Working Group meetings. PubMed, Web of Science, Cochrane Library, Scopus, and China National Knowledge Infrastructure (CNKI) were searched for available evidence. The GRADE system was used to evaluate the quality of evidence and grade the strengths of recommendations. Finally, the recommendations were developed through a structured consensus-building process. RESULTS: The Guideline Development Group initially collected a total of 62 important clinical questions. After a series of consensus-building conferences, 24 clinical questions were identified and corresponding recommendations were ultimately developed, focusing on neoadjuvant therapy, perioperative management, adjuvant therapy, postoperative psychological rehabilitation, prognosis assement, and follow-up protocols for NSCLC. CONCLUSIONS This guideline puts forward reasonable recommendations focusing on neoadjuvant therapy, perioperative management, adjuvant therapy, postoperative psychological rehabilitation, prognosis assessment, and follow-up protocol of NSCLC. It standardizes perioperative multimodality treatment and provides guidance for clinical practice among thoracic surgeons, medical oncologists, and radiotherapists, aiming to reduce postoperative recurrence, improve patient survival, accelerate recovery, and minimize postoperative complications such as atelectasis.
Humans ; Carcinoma, Non-Small-Cell Lung/therapy* ; Lung Neoplasms/therapy* ; Combined Modality Therapy ; Perioperative Care

OBJECTIVES: Lymph node metastasis in papillary thyroid cancer (PTC) is closely associated with tumor recurrence and patient survival. However, current technologies have limited sensitivity in detecting occult cervical lymph node metastases. Identifying accurate molecular markers for predicting PTC metastasis holds significant clinical value. This study aims to analyze WNT10A expression in PTC and its clinical significance, and to explore the role of WNT10A gene knockdown in PTC cell proliferation, invasion, and metastasis. METHODS: The expression of WNT10A in thyroid carcinoma was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) and University of Alabama at Birminghara Cancer data analysis Portal (UALCAN) databases. Real-time RT-PCR was used to measure WNT10A mRNA levels in tumor and adjacent normal tissues from 32 PTC patients. Immunohistochemistry was conducted on 158 PTC specimens to assess WNT10A protein expression and its correlation with clinicopathological features. In vitro experiments were performed using K1 and TPC-1 cell lines. Cell proliferation was assessed using the Celigo system and methyl thiazolyl tetrazolium (MTT) assays; apoptosis was measured via flow cytometry; invasion and metastasis were evaluated using scratch and Transwell assays. A xenograft model was established in nude mice to observe tumor growth, and tumor weight and volume were compared between cell lines. Differentially expressed genes regulated by WNT10A were identified via mRNA sequencing, followed by Gene Ontology (GO) and ingenuity pathway analysis (IPA). Real-time PCR and Western blotting were used to validate the effects of WNT10A on key downstream mRNA and protein in the Tec kinase signaling pathway. RESULTS: WNT10A mRNA expression was significantly higher in thyroid cancer tissues compared to adjacent normal tissues according to GEPIA and UALCAN (both P<0.01). The real-time RT-PCR result showed that WNT10A mRNA expression in PTC tissues was high than that in adjacent tissues (P<0.01). Immunohistochemistry revealed significantly higher WNT10A protein expression in PTC tissues compared to adjacent tissues (P<0.01), and its expression correlated with multifocality, extrathyroidal invasion, and lymph node metastasis. WNT10A knockdown significantly inhibited proliferation, altered cell cycle distribution, and increased apoptosis in K1 and TPC-1 cells (all P<0.01). WNT10A silencing also reduced migration and invasion abilities in both cell lines. In vivo, WNT10A knockdown in TPC-1 cells suppressed tumor formation in nude mice. GO analysis and IPA suggested that the Tec kinase signaling pathway was a key downstream target of WNT10A. RT-PCR and Western blotting confirmed that WNT10A knockdown downregulated the expression of key genes (STAT3, MAPK8, TNFRSF21, and AKT2) in this pathway. CONCLUSIONS WNT10A is highly expressed in PTC and is associated with tumor proliferation, invasion, and metastasis. Its tumor-promoting effects may be mediated through suppression of the Tec kinase signaling pathway.
Humans ; Cell Proliferation ; Thyroid Cancer, Papillary/pathology* ; Thyroid Neoplasms/metabolism* ; Animals ; Wnt Proteins/metabolism* ; Neoplasm Invasiveness ; Mice ; Cell Line, Tumor ; Female ; Male ; Mice, Nude ; Apoptosis ; Lymphatic Metastasis ; Middle Aged ; Cell Movement ; Adult

Venous system diseases mainly include varicose veins and venous malformations of lower limbs and the genital system. Most of them are chronic diseases that cause serious clinical symptoms to patients and affect their health and quality of life. Sclerotherapy has become the first-line therapy for venous system diseases. However, there are problems such as incomplete fibrosis and vascular recanalization after sclerotherapy, and improper operation will cause serious adverse consequences. Therefore, exploring a safe and effective sclerotherapy strategy is essential for developing clinically successful sclerotherapy. To solve the above problems, we proposed a new sclerotherapy strategy with a dual mechanism of "vascular damage and plasmin (PLA) system inhibition." We intended to construct a novel cationic surfactant (AEO_x-TA) by reacting tranexamic acid (TA), a parent structure, with fatty alcohol polyoxyethylene ether (AEO_x) by ester bonds. AEO_x-TA could damage vascular endothelium and initiate a coagulation cascade effect to induce thrombus. Furthermore, AEO_x-TA could be degraded by esterase and release the parent drug, TA, which could inhibit the PLA system to inhibit the degradation of thrombus and extracellular matrix and promote the process of vascular fibrosis. In addition, such surfactant-based sclerosants have foam-forming properties, and they can be blended with polyvinyl alcohol (PVA) to prepare a highly stable foam formulation (AEO_x-TA/P), which can achieve a precise drug delivery and prolonged drug retention time, thereby improving drug efficacy and reducing the risk of ectopic embolism. Overall, the novel cationic surfactant AEO_x-TA provides a new avenue to resolve the bottleneck: surfactant sclerosants' efficiency is relatively low in the current sclerotherapy.

Acute lung injury (ALI) has been a kind of acute and severe disease that is mainly characterized by systemic uncontrolled inflammatory response to the production of huge amounts of reactive oxygen species (ROS) in the lung tissue. Given the critical role of ROS in ALI, a Fe₃O₄ loaded bovine serum albumin (BSA) nanocluster (BF) was developed to act as a nanomedicine for the treatment of ALI. Combining with NIR irradiation, it exhibited excellent ROS scavenging capacity. Significantly, it also displayed the excellent antioxidant and anti-inflammatory functions for lipopolysaccharides (LPS) induced macrophages (RAW264.7), and Sprague Dawley rats via lowering intracellular ROS levels, reducing inflammatory factors expression levels, inducing macrophage M2 polarization, inhibiting NF-κB signaling pathway, increasing CD4⁺/CD8⁺ T cell ratios, as well as upregulating HSP70 and CD31 expression levels to reprogram redox homeostasis, reduce systemic inflammation, activate immunoregulation, and accelerate lung tissue repair, finally achieving the synergistic enhancement of ALI immunotherapy. It finally provides an effective therapeutic strategy of BF + NIR for the management of inflammation related diseases.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

Objective:To describe the epidemiological characteristics and trends of leukemia incidence in Qidong between 1972 and 2021, and provide guidelines for prevention and control measures and strategies.Methods:The cancer registry data was collected and analyzed on leukemia incidence during 1972—2021 in Qidong by sex, age and time. Crude incidence rate (CR), China age-standardized rate (ASRC), world age-standardized rate (ASRW), and average annual change percentage (AAPC) was calculated by Joinpoint software. Age-period-cohort (APC) model was used to analyze the influence of age, period and birth cohort on the changes in the incidence trend of leukemia patients.Results:From 1972 to 2021, there were 2 948 patients with leukemia in Qidong, accounting for 2.00% of all cancer new cases, CR of leukemia was 5.26/10 5, ASRC was 4.34/10 5, ASRW was 4.35/10 5. The truncated incidence of 35—64 years old was 5.29/10 5, the cumulative incidence rate between the ages of 0 and 74 years old was 0.40%, the cumulative risk was 0.40%. There were 1 608 male patients, the CR, ASRC, and the ASRW were 5.81/10 5, 4.88/10 5 and 4.85/10 5. The number of female patients were 1 340, and the CR, ASRC, and the ASRW were 4.71/10 5, 3.86/10 5 and 3.91/10 5, respectively. Temporal trends indicated significant upward trends in ASRC among both gender, males and females with AAPC values of 1.41% ( P＜0.001), 1.15% ( P＜0.001), and 1.73% ( P＜0.001), respectively. The results of the APC model showed that the average net drift value of leukemia incidence in all age groups was 1.57% (95% CI, 1.24%-1.89%), and the highest value of local drift was 3.20% (95% CI, 1.63%-4.78%) in the 80~ years old group. The incidence of leukemia increased with age. With the passage of time, the risk of leukemia incidence increased gradually compared with the rate ratio of leukemia incidence (risk ratio [ RR], 1.00) in 1992—1996, the RR of leukemia incidence increased from 0.70 during 1972—1976 to 1.57 during 2017—2021. The later the cohort was born, the greater the risk of leukemia incidence compared with the relative risk of leukemia incidence ( RR, 1.00) in 1952—1956 cohort, the RR of leukemia incidence increased from 0.24 in the 1892—1896 cohort to 2.73 in the 2017—2021 cohort. Conclusions:The incidence of the leukemia has presented a rising trend in the past fifty years. Leukemia incidence increased with age, and the period and cohort effects on the risk of incidence increase. Further research is needed to investigate the risk factors related to leukemia.

Objective:To assess the value of serum alpha-fetoprotein(AFP),protein induced by vitamin K absence or antagonist-Ⅱ(PIVKA-Ⅱ)and glypican-3(GPC-3)in the diagnosis of hepatocellular carcinoma(HCC).Methods:Studies of AFP,PIVKA-Ⅱ,GPC-3 or in combination for the diagnosis of HCC since 2002 were searched in PubMed,Web of Science and Embase databases.The literature was screened according to the inclusion and exclusion criteria,the quality of the included articles was evaluated by QUADAS checklist,and relevant data were extracted by Meta DiSc,Review Manager 5.4 and Stata 15.1.The diagnostic values of AFP,PIVKA-Ⅱ and GPC-3 alone or in combination for HCC were assessed with receiver operating characteristic(ROC)curve.Results:A total of 32 articles were included in the study.Meta-analysis showed that when a single marker was used to diagnose HCC,the area under the ROC curve(AUC)of PIVKA-Ⅱ was the highest(0.88,95%CI:0.85-0.91),followed by GPC-3 and AFP.The AUC of combination of serum markers was higher than that of a single marker,and the AUC of PIVKA-Ⅱ combined with GPC-3 was the highest(0.90,95%CI:0.87-0.92).When a single marker was used for diagnosis,the sensitivity of PIVKA-Ⅱ and GPC-3 were relatively high(0.75 and 0.76),while the specificity of PIVKA-Ⅱ(0.88)and AFP(0.87)were higher than that of GPC-3(0.81).The sensitivity of the combination of serum markers was higher than that of a single marker,while the specificity was not significantly improved.When a single marker is used to diagnose HCC,the diagnostic odds ratio(DOR)of PIVKA-Ⅱ was the highest(22,95%CI:13-36),followed by GPC-3 and AFP.The DOR of the combination of two markers in the diagnosis of HCC was higher than that of a single marker,and the DOR of AFP combined with GPC-3 was the highest(25,95%CI:9-67).The DOR of the combination of the three markers was significantly reduced to 10(95%CI:7-45).Conclusions:When a single marker is used,PIVKA-Ⅱhas a higher diagnostic value for HCC.The combination of two markers can significantly improve the diagnostic sensitivity,and AFP combined with PIVKA-Ⅱ is recommended for the diagnosis of HCC.The combination of all three markers failed to further improve the diagnostic value.