Objective To explore the value of the Transformer model based on multi-sequence MRI to predict isocitrate dehydrogenase(IDH)mutation status in patients with glioma.Methods The multi-sequence MRI data of 500 glioma patients(103 mutation-type and 397 wild-type)were analyzed retrospectively from the publicly available dataset Cancer Imaging Archive.The prediction model was constructed through the Transformer deep learning algorithm.Area under the curve(AUC)of the receiver operating characteristic(ROC)curve was used to evaluate the predictive performance,and the five-fold crossover was used for validation of the predictive model.Results The clinical,multi-sequence MRI,and combined clinical+multi-sequence MRI models based on the Transformer deep learning algorithm could be used to predict the IDH mutation status of patients with glioma,and the combined clinical+multi-sequence MRI model had the highest diagnostic efficacy compared with the former two,with an AUC of 0.904[95％confidence interval(CI)0.875-0.928],and the sensitivity and specificity of 86.41％and 86.40％,respectively.DeLong's test showed that the difference in AUC between the combined clinical+multi-sequence MRI model and the clinical model was statistically significant(Z=3.327,P＜0.001).Conclusion The Transformer model based on multi-sequence MRI can effectively identify patients with IDH mutation-type glioma and IDH wild-type glioma.

Objective To explore the value of the Transformer model based on multi-sequence MRI to predict isocitrate dehydrogenase(IDH)mutation status in patients with glioma.Methods The multi-sequence MRI data of 500 glioma patients(103 mutation-type and 397 wild-type)were analyzed retrospectively from the publicly available dataset Cancer Imaging Archive.The prediction model was constructed through the Transformer deep learning algorithm.Area under the curve(AUC)of the receiver operating characteristic(ROC)curve was used to evaluate the predictive performance,and the five-fold crossover was used for validation of the predictive model.Results The clinical,multi-sequence MRI,and combined clinical+multi-sequence MRI models based on the Transformer deep learning algorithm could be used to predict the IDH mutation status of patients with glioma,and the combined clinical+multi-sequence MRI model had the highest diagnostic efficacy compared with the former two,with an AUC of 0.904[95％confidence interval(CI)0.875-0.928],and the sensitivity and specificity of 86.41％and 86.40％,respectively.DeLong's test showed that the difference in AUC between the combined clinical+multi-sequence MRI model and the clinical model was statistically significant(Z=3.327,P＜0.001).Conclusion The Transformer model based on multi-sequence MRI can effectively identify patients with IDH mutation-type glioma and IDH wild-type glioma.

Objective To investigate the prevalence of Cryptosporidium infection and the distribution of parasite species and genotypes among HIV-positive individuals in Jiangxi Province. Methods HIV-positive individuals' sociodemographic and clinical data were collected from three AIDS designated hospitals in Jiangxi Province from January 2022 to March 2023. Subjects' stool samples were collected, and genomic DNA was extracted from stool samples. Nested PCR assay was performed based on the small subunit ribosomal RNA (SSU rRNA) gene of Cryptosporidium, and Cryptosporidium gp60 gene was amplified in stool samples positive for the SSU rRNA gene. The second-round PCR amplification product was checked with 1.5% agarose gel electrophoresis, and the products of suspected positive amplifications were sequenced, followed by sequence alignment. The phylogenetic tree was created using the Neighbor-Joining method with the software MEGA 11.0, to characterize the species, genotypes and sub-genotypes of Cryptosporidium. Results A total of 382 HIV-positive individuals were enrolled, with two cases identified with Cryptosporidium infection (0.52% prevalence), and both cases had no abdominal pain or diarrhea. Following sequencing and sequence alignment, the gene sequences of these two Cryptosporidium isolates shared 99.76% and 99.88% similarity with the gene sequence of C. meleagridis isolates. Phylogenetic analysis based on the Cryptosporidium SSU rRNA gene sequence identified the species of these two Cryptosporidium-positive stool samples as C. meleagridis. Following nested PCR amplification of the Cryptosporidium gp60 gene, sequencing and sequence alignment, the two C. meleagridis isolates were characterized as III eA17G2R1 and III bA25G1R1a sub-genotypes, and the sub-genotype III bA25G1R1a was firstly described in humans. Conclusion The prevalence of Cryptosporidium is low among HIV-positive individuals in Jiangxi Province. The likelihood of Cryptosporidium infection cannot be neglected among HIV-positive individuals without diarrhea.

Objective To establish a clinical-CT model,and to observe its value for evaluating lymphovascular invasion(LVI)and/or perineural invasion(PNI)in esophageal squamous cell carcinoma(ESCC).Methods Data of 156 ESCC patients were retrospectively analyzed.The patients were divided into positive group(n=58,LVI[+]and/or PNI[+])and negative group(n=98,LVI[-]and PNI[-])according to postoperative pathological results.Clinical and CT data were compared between groups.Logistic regression analysis was performed to establish a model,and its efficacy of evaluating ESCC LVI and/or PNI was analyzed.Results Significant differences of carcinoembryonic antigen(CEA),carbohydrate antigen 199(CA199),tumor thickness,tumor volume and CT venous phase value(CTV),the difference between CTV and CT plain phase value(CTP)(△CTV-P)and venous phase enhancement rate(V％)were found between groups(all P＜0.05),and the area under the curve(AUC)of the above parameters for evaluating ESCC LVI and/or PNI was 0.702,0.690,0.731,0.744,0.621,0.631 and 0.599,respectively.CEA,CA199,tumor thickness,tumor volume and CTV were all independent predictive factors for ESCC LVI and/or PNI.A combined model was established based on the above features,and its accuracy,sensitivity and specificity for evaluating ESCC LVI and/or PNI was 82.05％,65.52％and 91.84％,respectively,with AUC of 0.838,higher than that of each single parameter(all P＜0.05).Conclusion The established clinical-CT model could effectively evaluate ESCC LVI and/or PNI.

Objective To observe the value of intratumoral and peritumoral CT radiomics for evaluating KRAS gene status in patients with colorectal adenocarcinoma.Methods Totally 245 patients with colorectal adenocarcinoma were retrospectively enrolled and divided into mutant group(n=139)and wild group(n=106)according to KRAS gene status,also divided into training set(n=171)and test set(n=74)at a ratio of 7∶3.Clinical data were compared between groups,and clinical factors were screened with logistic regression analysis to establish a clinical model.Based on enhanced venous phase CT images,intratumoral volume of interest(VOI),peritumoral VOI,and intratumoral+peritumoral VOI were delineated,radiomics features were extracted,and radiomics models were constructed.The combination model was constructed based on the best radiomics model combined with clinical factors.The value of each model for evaluating KRAS gene status in patients with colorectal adenocarcinoma was analyzed.Results Significant differences of patients’gender and carcinoembryonic antigen(CEA)were found between mutant group and wild group(both P＜0.05),which were independent impact factors of KRAS gene status in patients with colorectal adenocarcinoma(both P＜0.05).The area under the curve(AUC)of clinical model for evaluating KRAS gene status in patients with colorectal adenocarcinoma in training set and test set was 0.633 and 0.658,respectively.Intratumoral+peritumoral 3 mm model was the best radiomics model,with AUC of 0.921 and 0.894 in training set and test set,respectively.AUC of the combination model in training set and test set was 0.949 and 0.956,respectively.In training set,significant differences of AUC were found between clinical model and intratumoral+peritumoral 3 mm model,also between clinical model and combination model(both P＜0.001),while in test set,significant differences of AUC were found between each two models(all P＜0.05).Conclusion Intratumoral+peritumoral 3 mm radiomics based on enhanced venous phase CT could help to evaluate KRAS gene status in patients with colorectal adenocarcinoma.Combining with patients’gender and CEA could further improve efficacy of this model.

Circadian disruption is being increasingly recognized as a critical factor in the development and progression of Parkinson’s disease (PD). This review aims to provide an in-depth overview of the relationship between circadian disruption and PD by exploring the molecular, cellular, and behavioral aspects of this interaction. This review will include a comprehensive understanding of how the clock gene system and transcription–translation feedback loops function and how they are diminished in PD. The article also discusses the role of clock genes in the regulation of circadian rhythms, as well as the impact of clock gene dysregulation on mitochondrial function, oxidative stress, and neuroinflammation, including the microbiota-gut-brain axis, which have all been proposed as being crucial mechanisms in the pathophysiology of PD. Finally, this review highlights potential therapeutic strategies targeting the clock gene system and circadian rhythm for the treatment of PD.

Objectives: Bipolar hemiarthroplasty is commonly performed to treat displaced femoral neck fractures in osteo porotic patients. This study aimed to assess the occurrence and outcomes of unplanned return visits to the emergency department (ED) within 90 days following bipolar hemiarthroplasty for displaced femoral neck fractures. Methods: The clinical data of 1322 consecutive patients who underwent bipolar hemiarthroplasty for osteoporotic femoral neck fractures at a tertiary medical center were analyzed. Data from the patients’ electronic medical records, including demographic information, comorbidities, and operative details, were collected. The risk factors and mortality rates were analyzed. Results: Within 90 days after surgery, 19.9% of patients returned to the ED. Surgery-related reasons accounted for 20.2% of the patient’s returns. Older age, a high Charlson comorbidity index score, chronic kidney disease, and a history of cancer were identified as significant risk factors for unplanned ED visits. Patients with uncemented implants had a significantly greater risk of returning to the ED due to periprosthetic fractures than did those with cemented implants (P = 0.04). Patients who returned to the ED within 90 days had an almost fivefold greater 1-year mortality rate (15.2% vs 3.1%, P < 0.001) and a greater overall mortality rate (26.2% vs 10.5%, P < 0.001). Conclusions This study highlights the importance of identifying risk factors for unplanned ED visits after bipolar hemiarthroplasty, which may contribute to a better prognosis. Consideration should be given to the use of cemented implants for hemiarthroplasty, as uncemented implants are associated with a greater risk of peri prosthetic fractures.