Objective To establish and internally validate a predictive model for poorly differentiated adenocarcinoma based on CT imaging and tumor marker results. Methods Patients with solid and partially solid lung nodules who underwent lung nodule surgery at the Department of Thoracic Surgery, the Affiliated Brain Hospital of Nanjing Medical University in 2023 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. Patients' CT features, including average density value, maximum diameter, pleural indentation sign, and bronchial inflation sign, as well as patient tumor marker results, were collected. Based on postoperative pathological results, patients were divided into a poorly differentiated adenocarcinoma group and a non-poorly differentiated adenocarcinoma group. Univariate analysis and logistic regression analysis were performed on the training set to establish the predictive model. The receiver operating characteristic (ROC) curve was used to evaluate the model's discriminability, the calibration curve to assess the model's consistency, and the decision curve to evaluate the clinical value of the model, which was then validated in the validation set. Results A total of 299 patients were included, with 103 males and 196 females, with a median age of 57.00 (51.00, 67.25) years. There were 211 patients in the training set and 88 patients in the validation set. Multivariate analysis showed that carcinoembryonic antigen (CEA) value [OR=1.476, 95%CI (1.184, 1.983), P=0.002], cytokeratin 19 fragment antigen (CYFRA21-1) value [OR=1.388, 95%CI (1.084, 1.993), P=0.035], maximum tumor diameter [OR=6.233, 95%CI (1.069, 15.415), P=0.017], and average density [OR=1.083, 95%CI (1.020, 1.194), P=0.040] were independent risk factors for solid and partially solid lung nodules as poorly differentiated adenocarcinoma. Based on this, a predictive model was constructed with an area under the ROC curve of 0.896 [95%CI (0.810, 0.982)], a maximum Youden index corresponding cut-off value of 0.103, sensitivity of 0.750, and specificity of 0.936. Using the Bootstrap method for 1000 samplings, the calibration curve predicted probability was consistent with actual risk. Decision curve analysis indicated positive benefits across all prediction probabilities, demonstrating good clinical value. Conclusion For patients with solid and partially solid lung nodules, preoperative use of CT to measure tumor average density value and maximum diameter, combined with tumor markers CEA and CYFRA21-1 values, can effectively predict whether it is poorly differentiated adenocarcinoma, allowing for early intervention.

Objective To analyze the characteristics of adverse drug reactions （ADR） reported in Sixth People’s Hospital South Campus, Shanghai Jiaotong University from 2021 to 2023, to provide reference for promoting rational clinical drug use. Methods ADR data reported in our hospital were collected retrospectively, including patients’ basic information, drugs causing adverse reactions, types of adverse reactions and outcomes. Descriptive analysis methods were used to summarize and analyze the data. Results A total of 979 cases of ADR were reported in our hospital from 2021 to 2023. The highest proportion of patients with ADR occurred in the age range of 31 to 50, and more male patients （63.5%）. The top five drugs involved with adverse reactions were antibiotics （48.8%）, Chinese medicine injections（19.2%）, vitamins（7.5%）, Chinese traditional medicine（7.2%）, equine tetanus immunoglobulin（6.3%）. Among antibiotics, cefuroxime, ceftazidime and cefotiam were the majority. The organs/systems involved in all ADR were mainly skin and accessories damage （55.4%）. The clinical manifestations were rash, itching, and maculopapular rash. Conclusion From 2021 to 2023, the most common drugs causing adverse drug reactions in our hospital were mainly antibacterial drugs, and the rational clinical use of antibacterial drugs still needs to be concerned.

Objective To explore the polymorphism of tyrosinase (TYR) and melanocortin 1 receptor (MC1R) genes and their mRNA expression levels in relation to coat-color phenotypes in guinea pigs, providing genetic markers for locating dominant traits in guinea pigs. Methods A total of 57 self-bred ordinary-level guinea pigs were selected and divided into three groups based on coat color: white (n=22), variegated (n=22) and black (n=13). The guinea pigs were euthanized with an overdose of pentobarbital sodium via intraperitoneal injection. DNA was then extracted from the dorsal skin tissue. Polymorphism in the coding sequence (CDS) of the exons of the TYR and MC1R genes in each group was detected by cloning and sequencing. The mRNA expression of the two genes in skin tissues was detected by real-time fluorescent quantitative PCR to investigate the relationship between these genes and guinea pig coat color. Results A single nucleotide polymorphism (SNP) site was found in the CDS region of TYR exon Ⅰ, where the base A was replaced by G. All white guinea pigs had the G/G genotype for TYR, while no deep-colored (variegated and black) guinea pigs exhibited the G/G genotype for TYR. Most deep-colored guinea pigs had the A/A genotype, and a few had A/G genotype. The A/A genotype frequency in black guinea pigs was higher than in variegated guinea pigs. A 2 760 bp sequence deletion was identified in the exon of the MC1R gene, marked as the - gene, with non-deleted samples marked as N gene. Most white guinea pigs had the -/- genotype for MC1R, variegated guinea pigs mainly had the -/N genotype, and black guinea pigs mainly had the N/N genotype, with a few showing the -/N. The TYR gene expression level was higher in white guinea pigs, lower in variegated guinea pigs, and intermediate in black guinea pigs, but there was no significant difference among the three groups (P>0.05). The MC1R gene expression level in white guinea pigs was extremely low, while both variegated and black guinea pigs showed significantly higher levels than white guinea pigs (P<0.01). Black guinea pigs showed significantly higher levels than variegated guinea pigs (P<0.05). ConclusionThe TYR and MC1R genes synergistically regulate coat color of guinea pigs. The G-site mutation in the TYR gene may lead to albinism, and the change of N-site in the MC1R gene affects the depth of the coat color.

OBJECTIVE: This study aimed to evaluate the association between susceptibility genes and non-alcoholic fatty liver disease (NAFLD) in children with obesity. METHODS: We conducted a two-step case-control study. Ninety-three participants were subjected to whole-exome sequencing (exploratory set). Differential genes identified in the small sample were validated in 1,022 participants using multiplex polymerase chain reaction and high-throughput sequencing (validation set). RESULTS: In the exploratory set, 14 genes from the NAFLD-associated pathways were identified. In the validation set, after adjusting for sex, age, and body mass index, ECI2 rs2326408 (dominant model: OR = 1.33, 95% CI: 1.02-1.72; additive model: OR = 1.22, 95% CI: 1.01-1.47), C6orf201 rs659305 (dominant model: OR = 1.30, 95% CI: 1.01-1.69; additive model: OR = 1.21, 95% CI: 1.00-1.45), CALML5 rs10904516 (pre-ad dominant model: OR = 1.36, 95% CI: 1.01-1.83; adjusted dominant model: OR = 1.40, 95% CI: 1.03-1.91; and pre-ad additive model: OR = 1.26, 95% CI: 1.04-1.66) polymorphisms were significantly associated with NAFLD in children with obesity ( P < 0.05). Interaction analysis revealed that the gene-gene interaction model of CALML5 rs10904516, COX11 rs17209882, and SCD5 rs3733228 was optional ( P < 0.05), demonstrating a negative interaction between the three genes. CONCLUSION In the Chinese population, the CALML5 rs10904516, C6orf201 rs659305, and ECI2 rs2326408 variants could be genetic markers for NAFLD susceptibility.
Humans ; Non-alcoholic Fatty Liver Disease/genetics* ; Child ; Male ; Female ; Genetic Predisposition to Disease ; Case-Control Studies ; Exome Sequencing ; Adolescent ; Polymorphism, Single Nucleotide ; Obesity/complications* ; Pediatric Obesity/complications* ; China

Objective:To analyze risk factors for early trauma-induced coagulopathy (TIC) in pediatric patients with moderate-to-severe traumatic brain injury (msTBI), develop a predictive model and evaluate its predictive performance.Methods:A retrospective cohort study was conducted to analyze the clinical data of 290 pediatric patients with msTBI who were admitted to Children′s Hospital of Soochow University between January 2016 and December 2024, including 188 boys and 102 girls, aged 0.2-15.7 years [5.2(2.8, 9.3)years]. Based on the coagulation test results at admission, the patients were divided into TIC group ( n=162) and non-TIC group ( n=128). The patients were randomly allocated into training set ( n=203) and validation set ( n=87) at a ratio of 7∶3. Demographic characteristics, clinical data, vital signs, imaging findings, arterial blood gas analysis results, and coagulation profiles of the patients were collected. Univariate analysis and Lasso regression analysis were used to identify risk factors associated with early TIC in children with msTBI and multivariate Logistic regression analysis was performed to determine independent risk factors and construct a predictive model. The model′s discrimination and calibration were evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), Hosmer-Lemeshow (H-L) test, and calibration curve. Its clinical utility was assessed through decision curve analysis (DCA). Results:Significant differences were observed between the TIC group and non-TIC group in terms of age, weight, time from injury to admission, child′s Glasgow coma scale (CGCS) score, pediatric trauma score (PTS), shock index, heart rate, respiratory rate, systolic blood pressure, Rotterdam CT score, intraventricular hemorrhage, cerebral contusion, brain herniation, long bone fracture, pelvic fracture, hemopneumothorax, pulmonary contusion, intra-abdominal organ injury, actual bicarbonate, base excess, base excess in the extracellular fluid, blood glucose, hemoglobin (Hb), osmolarity, blood calcium, anion gap, blood lactate, prothrombin time, activated partial thromboplastin time, international normalized ratio, and platelet count ( P<0.05). With coagulation-related variables excluded, the following features were identified with Lasso regression including CGCS score, PTS, heart rate, systolic blood pressure, long bone fracture, blood glucose, and Hb. Multivariate Logistic regression analysis revealed that CGCS score≤8 points ( OR=3.05, 95% CI 1.65, 5.63), PTS>5 points ( OR=0.45, 95% CI 0.23, 0.89), systolic blood pressure ( OR=0.98, 95% CI 0.97, 0.99), blood glucose ( OR=1.09, 95% CI 1.01, 1.17), and long bone fracture ( OR=2.47, 95% CI 1.13, 5.42) were influencing factors for early TIC in children with msTBI ( P<0.05). The regression equation of the predictive model was established as follows: Logit[ P/(1- P)]=1.01×"CGCS score≤8 points"-0.69×"PTS>5 points"- 0.02×"systolic blood pressure"+0.89×"long bone fracture"+0.08×"blood glucose"+1.32. The ROC curve analysis showed that the training set had an AUC of 0.86 (95% CI 0.78, 0.94), with sensitivity and specificity of 76.6% and 92.5%, while the AUC was 0.80 (95% CI 0.74, 0.86), with sensitivity and specificity of 75.7% and 79.6% in the validation set. H-L test results showed a χ2 value of 8.18 ( P=0.416) in the training set and 5.30 ( P=0.216) in the validation set. The calibration curves for both sets demonstrated good agreement with the actual curves, indicating that the predicted probabilities closely matched the observed probabilities. The DCA results indicated that both the training set and validation set demonstrated positive net benefits within threshold probabilities ranges of 10%-100% and 15%-96%. Conclusions:Independent risk factors for early TIC in pediatric msTBI patients include CGCS score≤ 8 points, PTS≤5 points, low systolic blood pressure, long bone fracture, and high blood glucose. The predictive model constructed based on these factors demonstrates favorable predictive performance and clinical application value.

Objective:To evaluate preoperative high-resolution thin-layer cervical enhanced CT used to predict the venous route of the submental flap reflux vein and its relationship with adjacent structures in order to guide the anatomical understanding and protection of submental flap in pharyngeal cancer surgery.Methods:Sixty consecutive patients with pharyngeal cancer who underwent submental flap repair surgery in our department from March 2022 to December 2024, as well as 60 patients who were accepted neck dissection suffering other cancers, were selected. Before surgery, high-resolution cervical enhanced CT scans were performed, and the position of the transverse section of the facial vein in the venous phase horizontal image gradually variation tendency was focused layer by layer. The direction and adjacent relationship of the submental flap reflux veins were determined and recorded. Combined with 60 patients with other head and neck tumors who underwent neck dissection in our department during the same period (a total of 120 cases, 240 sides), the classification and management of the draining veins of Fang′s mental flap were conducted. Type Ⅰ mainly drains into the internal jugular vein; Type Ⅱ mainly drains into the external jugular vein and Type Ⅲ mainly drains into the anterior jugular vein (often accompanied by an external jugular draining branch). The status and proportion of venous drainage were analyzed.Results:Vascular predictive coincidence rate was 98.3% (59/60) among the 60 patients with pharyngeal cancer. Only one patient was predicted to have a simple return to the external jugular vein. However, during the operation, in addition to the main return to the external jugular vein, a small portion also returned to the internal jugular vein. Submental flap reflux vessels were classified into three types based on intraoperative submental flap venous return in 60 cases of laryngopharyngeal cancer, in conjunction with the analysis of venous return patterns from 240 cervical CT scans. Type Ⅰ mainly refluxed to the internal jugular vein, accounting for 42.1%. Type Ⅱ mainly refluxed to the external jugular vein (47.9%). Type Ⅲ mainly refluxed to the anterior jugular vein (10.0%). The total detection rate of CT reading of 240 venous reflux was 98.7% (237/240). Vascular predictive coincidence rate was 97.9%(235/240).Conclusion:The detailed analysis of submental venous return vessels can accurately predict the direction of reflux veins and its surrounding areas by preoperative high-resolution enhanced CT scan. This provides reliable guidance for the anatomy and protection of the submental flap reflux veins during surgery.

Objective:To compare the survival outcomes of different subsequent treatment regimens in patients with locally advanced hypopharyngeal squamous cell carcinoma (HPSCC) who achieved partial response (PR) after neoadjuvant chemotherapy based on the gross tumor volume regression rate (GTVRR).Methods:This retrospective study included patients with locally advanced HPSCC treated at the Department of Head and Neck Surgery, Beijing Tongren Hospital, from January 2011 to December 2023. The cohort included 135 males and 3 females, aged from 35 to 77 years. All patients received 2-3 cycles of TPF regimen (paclitaxel+cisplatin+5-fluorouracil) neoadjuvant chemotherapy. Subsequent treatments included concurrent chemoradiotherapy or surgery combined with postoperative adjuvant radiotherapy. The impacts of different subsequent treatment modalities on the survivals and prognoses of patients were compared based on GTVRR thresholds of 50% and 70%. The χ 2 test was used to analyze influencing factors; survival analysis and intergroup comparisons were performed using the Kaplan-Meier method and Log-rank test; prognostic factors were assessed using univariate and multivariate Cox regression analyses. Results:The 5-year OS and PFS rates were 56.5% and 47.9%, respectively, while, the 10-year OS and PFS rates were 25.8% and 21.2%, respectively. The median OS was 75 months, and the median PFS was 48 months. The laryngeal function preservation rate for the entire cohort was 83.3%. The patients who underwent surgery combined with postoperative radiotherapy had significantly better OS and PFS outcomes than those treated with concurrent chemoradiotherapy ( P<0.05). Stratification based on GTVRR revealed that the surgery plus postoperative radiotherapy regimen was particularly effective for PR patients with a GTVRR of 30%-70%, showing significantly better OS and PFS compared to the concurrent chemoradiotherapy group ( P<0.05). Conclusion:The optimal subsequent treatment for PR-HPSCC may be surgery-based comprehensive treatment, particularly for patients with a GTVRR of 30%-70%. This study offers valuable insights for the stratified treatment of HPSCC, which could contribute to improving overall patient prognosis.

Objective: To analyze the disease burden of chronic obstructive pulmonary disease (COPD) and changes in its risk factors among residents in Zhejiang Province from 1990 to 2021, so as to identify key priorities for COPD prevention and control. Methods: Data on COPD mortality and disability-adjusted life years (DALY) for residents in Zhejiang Province from 1990 to 2021 were collected from the Global Burden of Disease (GBD) 2021 database. Standardized mortality and standardized DALY rate were calculated using the GBD 2021 world population standard structure. Premature mortality was computed via the life table method. The average annual percent change (AAPC) was applied to analyze trends in COPD mortality, DALY rate, and premature mortality. Changes in deaths of COPD risk factors were evaluated using population attributable fraction (PAF). Results: From 1990 to 2021, the standardized COPD mortality in Zhejiang Province decreased from 272.40/100 000 to 70.56/100 000 (AAPC=-4.395%), and the standardized DALY rate declined from 4 167.37/100 000 to 1 071.89/100 000 (AAPC=-4.396%). Similar downward trends were observed in both males (AAPC=-3.933%, -4.173%) and females (AAPC=-4.785%, -4.480%), all P<0.05. Crude mortality and DALY rates increased with age, and the crude mortality and DALY rates of various age groups in Zhejiang Province showed decreasing trends from 1990 to 2021 (all P<0.05). The premature mortality declined from 4.37% to 0.60% from 1990 to 2021 (AAPC=- 6.206%), with consistent trends across males and females (AAPC=- 6.144%, - 6.379%, all P<0.05). From 1990 to 2021, particulate matter pollution showed the largest reduction in PAF (- 56.76%), while ambient ozone pollution had the largest increase (103.07%) in Zhejiang Province. By 2021, smoking became the leading risk factor for deaths of COPD (PAF=43.32%). Conclusions The standardized mortality, standardized DALY rate, and premature mortality for COPD show consistent declining trends in Zhejiang Province from 1990 to 2021. However, risk factors such as smoking and ambient ozone pollution require intensified focus to further reduce disease burden of COPD.

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control