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.

This study analyzed the genetic evolutionary characteristics of sandflies and their effects on the spread of kala-azar in various environments in endemic provinces in China,to provide a scientific basis for kala-azar disease prevention and control.Sand-flies were collected in kala-azar endemic areas such as southern Xinjiang,the large hilly areas of southern Gansu,the northern Sich-uan and Taihang Mountains,and surrounding small hills.The cytochrome c oxidase subunit I and cytochrome b gene fragments of mito-chondrial DNA were amplified to identify sandfly species.The COI and Cytb gene sequences of sandflies from southern Xinjiang and Si-chuan recorded in NCBI were also collected.The intraspecific and interspecific genetic differences of sandflies were calculated in MEGA11.0,and a phylogenetic tree was constructed through the neighbor-joining method,for analysis of the genetic and evolutionary characteristics of sandfly populations and their effects on disease transmission.A total of 155 sandflies were collected from nine sam-pling sites in seven provinces of China;the species included Phlebotomus chinensis,Phlebotomus wui,and Sergentomyia squamirostris.Five sandfly species belonging to two genera were collected:P.chinensis,P.wui,and Phlebotomus alexandri in the genus Phleboto-mus,and S.squamirostris in the genus Sergentomyia.Genetic evolution analysis based on COI and Cytb gene sequences indicated intra-specific genetic distances of 0-0.062 and 0-0.056,respectively,and interspecific genetic distances of 0.126-0.176 and 0.110-0.171,respectively.The phylogenetic tree indicated that P.wui,P.alexandri,Phlebotomus longiductus,and S.squamirostris clus-tered into one branch.The sequences of P.chinensis in the large and small hilly areas clustered into two geographical clades.In the small hilly areas,the sequences of P.chinensis aggregates showed small genetic differences,the pathogen infection was consistent,and the cases showed an epidemic spread trend.Large genetic differences at the molecular level were observed among sandflies in dif-ferent ecological regions,thus indicating key effects on leishmaniasis transmission.On the basis of these findings,prevention and con-trol strategies should be adapted to local conditions,and precise and effective prevention and control measures should be formulated according to the genetic evolution characteristics of sandflies in different regions,to better control the transmission of Kala-azar.

Objective:To evaluate the relationship between postoperative changes in femoral head coverage (FHC) after S 2-Alar-Iliac (S 2AI) screw fixation and the development of sagittal imbalance during follow-up in patients with adult spinal deformity (ASD), providing insights for clinical assessment and treatment strategies. Methods:A consecutive cohort of 98 ASD patients who underwent S2AI fixation between September 2019 and September 2021 was retrospectively analyzed. Patients were divided into two groups based on changes in femoral head coverage (ΔFHC): the FHC-C group (upper quartile ΔFHC, 25 cases) and the FHC-NC group (lower quartile ΔFHC, 24 cases). Additionally, patients were classified into proximal junctional kyphosis (PJK) and non-PJK groups based on their clinical outcomes at the last follow-up. Standing full-spine anteroposterior and lateral X-rays were taken preoperatively, postoperatively, and at the two-year follow-up to measure and document the following spinal parameters: Cobb angle, proximal lumbar lordosis (PLL), distal lumbar lordosis (DLL), lumbar lordosis (LL), lordosis distribution index (LDI), sagittal vertical axis (SVA), coronal balance distance (CBD), thoracic kyphosis (TK), T 1 pelvic angle (T 1PA), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), PI-LL, and proximal junctional angle (PJA). Parameters related to hip joint coverage included: femoral head coverage (FHC), lateral center-edge angle (LCE angle), acetabular index (AI), Sharp angle, and extrusion index (EI). Comparisons of radiographic indicators between the two groups were performed at preoperative, postoperative, and final follow-up assessments. The visual analogue scale (VAS) was used to evaluate the hip pain and back pain. Results:At final follow-up, the incidence of PJK was significantly higher in the FHC-NC group [37.5% (9/24)] compared to the FHC-C group [16.0% (4/25)] (χ 2=3.952, P=0.042). Moreover, the increase in sagittal vertical axis (ΔSVA) was significantly greater in the FHC-NC group (35.9±44.7 mm vs. 14.6±31.8 mm, t=2.216, P=0.031). Patients with PJK had significantly higher preoperative T 1PA (36.8°±10.8° vs. 31.9°±18.4°, t=2.150, P=0.034) and lower immediate postoperative ΔFHC (1.7%±1.5% vs. 3.3%±2.5%, t=2.987, P=0.004), as well as lower changes in lateral center-edge angle during follow-up (0.3°±3.0° vs. 1.1°±8.9°, t=2.334, P=0.022). Pearson correlation analysis revealed significant negative correlations between postoperative ΔFHC and both ΔSVA ( r=-0.374, P=0.008) and proximal junctional angle changes (ΔPJA, r=-0.429, P=0.006). Additionally, increases in VAS leg pain scores correlated negatively with immediate postoperative FHC ( r=-0.314, P=0.025) and ΔFHC ( r=-0.298, P=0.031). Logistic regression indicated that immediate postoperative ΔFHC was a protective factor against PJK [ OR=0.722, 95% CI (0.541, 0.963), P=0.009), with a ROC-determined optimal ΔFHC cut-off of 3.90% (AUC=0.723, Youden index=0.847). Conclusions:Postoperative evaluation of femoral head coverage is clinically important for ASD patients undergoing S2AI screw fixation. A pre-to-post ΔFHC below 3.90% may indicate reduced hip compensation capacity, increasing risks for hip pain, sagittal imbalance progression, and PJK postoperatively.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Objective:To analyze the clinical features and risk factors for renal injury in children with antineutrophil cytoplasmic antibody (ANCA)-positive IgA vasculitis (IgAV).Methods:A case-control study was conducted. Seventy-two ANCA-positive IgAV children hospitalized at the Children′s Hospital of Chongqing Medical University from January 2017 to October 2022 were enrolled as the ANCA-positive group. Propensity score matching (1∶4) using the nearest neighbor was performed with age and gender as covariate, and 288 cases ANCA-negative IgAV children were included as the ANCA-negative group. Patients with renal injury were named ANCA-positive IgAV nephritis (IgAVN) group and ANCA-negative IgAVN group, respectively. The ANCA-positive IgAVN group was further divided into myeloperoxidase (MPO) group and proteinase 3 (PR3) group based on the type of ANCA. Clinical data including manifestations, laboratory tests, renal injury, and prognosis were collected. Comparisons between groups were performed using independent sample t-tests, Mann-Whitney U tests, χ2 tests, or Fisher′s exact tests. Kaplan-Meier curves were used to assess differences in the time to renal injury onset, and multivariate logistic regression was performed to identify independent risk factors for renal injury. Results:Among the 72 ANCA-positive IgAV children (41 males, 31 females, age of 7.7 (5.3, 11.2) years), no significant difference in age or gender was observed compared to the ANCA-negative group (both P>0.05). The ANCA-positive group had higher IgM levels, a higher incidence of recurrent rash, and shorter thrombin time (all P<0.05). Among children with renal injury, the ANCA-positive group showed significant differences in the incidence of hematuria, clinical classification, and grade A prognosis compared to the ANCA-negative group (all P<0.05), but no difference was found in the time to renal involvement onest or renal pathology (all P>0.05). The MPO group had higher rates of microscopic hematuria, gross hematuria, acute renal insufficiency, glomerular sclerosis, and grade B prognosis compared to the ANCA-negative IgAVN group (all P<0.05), with a later onset of renal involvement ( P<0.05). Elevated serum creatinine ( OR=1.08, 95% CI 1.03-1.14) and shortened thrombin time ( OR=0.71, 95% CI 0.55-0.92) were independent risk factors for renal injury in ANCA-positive IgAV children (all P<0.05). Conclusions:Children with ANCA-positive IgAV are more likely to experience recurrent rash. MPO-ANCA-positive IgAVN children have higher risks of hematuria, acute kidney injury and glomerular sclerosis, with later-onset but poorer renal prognosis compared to ANCA-negative IgAVN children. Higher serum creatinine levels and shorter thrombin time may be associated with renal injury in children with ANCA-positive IgAV.

Objective:This study investigated the expression of C-X-C motif chemokine receptor 3 (CXCR3) on CD45RO? T cells in the peripheral blood of patients with Alzheimer′s disease (AD) and its association with clinical features.Methods:A total of 41 AD patients and 30 age-and sex-matched healthy controls (HCs) were recruited from the Department of Neurology at the Medical Division of PLA General Hospital between September 2022 and March 2024. Flow cytometry was used to quantify CXCR3 expression on CD45RO? T cell subsets in peripheral blood. Dementia severity in AD patients was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Spearman correlation analysis examined the relationship between CD45RO?CXCR3? T cell levels and cognitive function in the AD group. Receiver operating characteristic (ROC) curve analysis determined the predictive utility of CD45RO?CXCR3? T cells for AD, quantified by the area under the curve (AUC).Results:Compared to healthy controls, AD patients exhibited significantly elevated levels of CD8?CD45RO?CXCR3? T cells [17.8% (7.2%, 40.3%) vs. 8.2% (5.1%, 12.3%), Z=-2.59, P<0.05]. However, no significant differences were observed for CD4?CD45RO?CXCR3? T cells, CD4?CD45RO?CXCR3? T cells, or CD8?CD45RO?CXCR3? T cells ( P>0.05). Spearman correlation analysis revealed a negative correlation between CD8?CD45RO?CXCR3? T cell levels and cognitive scores (MMSE: r=-0.72, P<0.05; MoCA: r=-0.70, P<0.05). ROC analysis demonstrated an AUC of 0.81 for CD8?CD45RO?CXCR3? T cells in predicting AD, with a sensitivity of 59.0% and specificity of 93.3%. Conclusions:CXCR3 expression is significantly upregulated on CD8?CD45RO? T cells in AD patients, and its levels correlate with cognitive impairment severity. These findings suggest that CD8?CD45RO?CXCR3? T cells may serve as a potential biomarker for AD diagnosis and progression monitoring.

Objective:To clarify the safety, repair rate, durability, and risk factors for recurrent mitral regurgitation(MR) in patients with Barlow disease(BD) who total thoracoscopic minimally invasive mitral valvuloplasty(TMVP).Methods:Clinical data, mid-term and long-term outcomes of BD patients who underwent TMVP at Guangdong Provincial People's Hospital from January 2009 to June 2022 were retrospectively analyzed. Patients were divided into a group with no MR recurrence(group A) and a group with MR recurrence(group B) according to whether recurrent MR appeared in the postoperative period, and the data of the two groups of patients were compared with each other for the risk factor analysis.Results:The repair rate of TMVP was 98.4%, and no patient died perioperatively. The median follow-up time was 3.1(1.7, 5.2) years, the follow-up rate was 95.8%, and there was no patient died. As of March 2023, 112 patients developed no recurrent MR(group A), 11 patients developed recurrent MR(group B), and 2 patients in group B underwent repeated mitral valve surgery. The left atrial diameter(LAD) and left ventricular end-systolic diameter(LVESD) were higher in group B than in group A patients[LAD: (50.9±7.7)mm vs.(43.7±8.7)mm, P=0.009; LVESD: (37.1±5.5)mm vs.(33.2±4.7)mm, P=0.011], and the percentage of tendon cord rupture was higher in group B than in group A( P=0.022), while the rest of the baseline data were not statistically significant. There was no statistically significant difference between two groups in terms of the use of different surgical techniques, aortic cross-clamp time, cardiopulmonary bypass time, and operative time. Postoperative LAD, postoperative LVESD, and postoperative left ventricular end-diastolic diameter of group B patients were higher than those of group A( P<0.05). There was no statistically significant difference in perioperative and long-term complication rates between the two groups. Multifactorial Cox regression analysis revealed that advanced age( HR=1.049, 95% CI: 0.997-1.103, P=0.066) and large preoperative LVESD( HR=1.168, 95% CI: 1.053-1.295, P=0.003) were the risk factors for postoperative recurrence MR. Conclusion:Total thoracoscopic minimally invasive BD repair is safe, which has a high success rate and good long-term results. Advanced age and large preoperative LVESD are risk factors for recurrent MR in the long term.

Objective:To explore the clinical symptoms, imaging characteristics, cerebrospinal fluid (CSF) features, as well as the treatment and prognosis of autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy.Methods:Sixty-one patients with anti-GFAP astrocyte antibody (GFAP-IgG) single-positive autoimmune encephalitis who were treated at the Third Affiliated Hospital, Sun Yat-sen University between January 2017 and September 2023 were retrospectively collected. The demographic characteristics (age at onset, sex), clinical symptoms (core symptoms, neurological deficits, psychiatric behavioral abnormalities, and autonomic dysfunction), imaging features [brain/spinal cord/optic nerve magnetic resonance imaging (MRI) lesion distribution and enhancement patterns], and CSF parameters were analyzed. Acute-phase treatments, including methylprednisolone pulse therapy, intravenous immunoglobulin (IVIG), etc, along with the follow-up outcomes [modified Rankin Scale (mRS) score] were recorded.Results:The onset age was 40 (30, 55) years, and 68.9% (42/61) of the patients were male. The most common clinical manifestations were fever (65.6%, 40/61), headache (60.7%, 37/61), and urinary/defecatory abnormalities (45.9%, 28/61). Brain MRI revealed lesions predominantly in the cerebral cortex and subcortical white matter (57.4%, 35/61), periventricular white matter (50.8%, 31/61), and basal ganglia (36.1%, 22/61). Periventricular linear-radiating enhancement was the predominant MRI enhancement pattern (55.7%, 34/61). Spinal MRI showed lesions mainly in the cervical (42.6%, 26/61) and thoracic spinal cord (32.8%, 30/61), with leptomeningeal enhancement (31.1%, 19/61) and scattered punctate/patchy enhancements (21.3%, 13/61). Optic neuropathy was observed in 6 cases (9.8%). CSF analysis demonstrated a pressure of 180 (133, 240) mmH 2O (1 mmH 2O=0.009 8 kPa), white blood cell count of 29 (4, 156)×10?/L, and protein level of 0.72 (0.40, 1.44) g/L. Nineteen patients (31.1%) experienced rapid progression of meningoencephalitis or myelitis within 3 days of admission. All patients received methylprednisolone pulse therapy, with 47.5% (29/61) additionally treated with IVIG. At a follow-up of 12 (3, 28) months, 12 cases (19.7%) relapsed, and 75.4% (46/61) had favorable outcomes (mRS score 0-2). Poor prognosis (mRS score>2) was observed in 4 cases, including 3 with cervical spinal cord involvement and status epilepticus, 1 elderly patient with lung cancer. Conclusions:GFAP astrocytopathy predominantly affects young adults, with a male predominance. Spinal cord involvement is common, manifesting as myelitis and myelopathy. Rapid progression of meningoencephalitis or myelitis may occur early in the disease course. Periventricular linear-radiating enhancement on brain MRI is a key diagnostic clue. Leukocyte and protein levels in the cerebrospinal fluid are generally mildly to moderately elevated. Most patients respond well to corticosteroids and immunotherapy, with favorable outcomes. However, advanced age and cervical spinal cord involvement are associated with poor prognosis.

Objective:To evaluate the relationship between postoperative changes in femoral head coverage (FHC) after S 2-Alar-Iliac (S 2AI) screw fixation and the development of sagittal imbalance during follow-up in patients with adult spinal deformity (ASD), providing insights for clinical assessment and treatment strategies. Methods:A consecutive cohort of 98 ASD patients who underwent S2AI fixation between September 2019 and September 2021 was retrospectively analyzed. Patients were divided into two groups based on changes in femoral head coverage (ΔFHC): the FHC-C group (upper quartile ΔFHC, 25 cases) and the FHC-NC group (lower quartile ΔFHC, 24 cases). Additionally, patients were classified into proximal junctional kyphosis (PJK) and non-PJK groups based on their clinical outcomes at the last follow-up. Standing full-spine anteroposterior and lateral X-rays were taken preoperatively, postoperatively, and at the two-year follow-up to measure and document the following spinal parameters: Cobb angle, proximal lumbar lordosis (PLL), distal lumbar lordosis (DLL), lumbar lordosis (LL), lordosis distribution index (LDI), sagittal vertical axis (SVA), coronal balance distance (CBD), thoracic kyphosis (TK), T 1 pelvic angle (T 1PA), pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), PI-LL, and proximal junctional angle (PJA). Parameters related to hip joint coverage included: femoral head coverage (FHC), lateral center-edge angle (LCE angle), acetabular index (AI), Sharp angle, and extrusion index (EI). Comparisons of radiographic indicators between the two groups were performed at preoperative, postoperative, and final follow-up assessments. The visual analogue scale (VAS) was used to evaluate the hip pain and back pain. Results:At final follow-up, the incidence of PJK was significantly higher in the FHC-NC group [37.5% (9/24)] compared to the FHC-C group [16.0% (4/25)] (χ 2=3.952, P=0.042). Moreover, the increase in sagittal vertical axis (ΔSVA) was significantly greater in the FHC-NC group (35.9±44.7 mm vs. 14.6±31.8 mm, t=2.216, P=0.031). Patients with PJK had significantly higher preoperative T 1PA (36.8°±10.8° vs. 31.9°±18.4°, t=2.150, P=0.034) and lower immediate postoperative ΔFHC (1.7%±1.5% vs. 3.3%±2.5%, t=2.987, P=0.004), as well as lower changes in lateral center-edge angle during follow-up (0.3°±3.0° vs. 1.1°±8.9°, t=2.334, P=0.022). Pearson correlation analysis revealed significant negative correlations between postoperative ΔFHC and both ΔSVA ( r=-0.374, P=0.008) and proximal junctional angle changes (ΔPJA, r=-0.429, P=0.006). Additionally, increases in VAS leg pain scores correlated negatively with immediate postoperative FHC ( r=-0.314, P=0.025) and ΔFHC ( r=-0.298, P=0.031). Logistic regression indicated that immediate postoperative ΔFHC was a protective factor against PJK [ OR=0.722, 95% CI (0.541, 0.963), P=0.009), with a ROC-determined optimal ΔFHC cut-off of 3.90% (AUC=0.723, Youden index=0.847). Conclusions:Postoperative evaluation of femoral head coverage is clinically important for ASD patients undergoing S2AI screw fixation. A pre-to-post ΔFHC below 3.90% may indicate reduced hip compensation capacity, increasing risks for hip pain, sagittal imbalance progression, and PJK postoperatively.