Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Objective To predict the radiation impact of discharging wastewater containing uranium within the specified limit generated during the normal operation of a new production line at a nuclear fuel plant on the receiving water body and its downstream, and to provide a reference for the management of radioactive liquid effluent discharge from nuclear facilities. Methods Based on the technical guidelines for environmental impact assessment, literature on radiation environmental impact assessment, and data collected from on-site investigations, appropriate hydrological parameters and prediction models were selected to analyze and predict the variation pattern of radioactive nuclide uranium along the receiving water body and the radiation exposure of nearby residents. Results The maximum increase in uranium concentration in the receiving water body and its downstream caused by the discharge of uranium-containing wastewater was 1.14 μg/L. The maximum predicted concentration was 2.75 μg/L after adding the background data of the water body. The resulting maximum individual annual effective dose for the public was 1.49 × 10⁻⁴ mSv/a. Conclusion The maximum predicted uranium concentration in the receiving water body and its downstream is lower than the uranium concentration limit of 30 μg/L specified in the Standards for Drinking Water Quality (GB 5749-2022). The maximum individual annual effective dose for the public is much lower than the control value of 0.2 mSv/a specified in the Radiation Protection Regulations for Uranium Processing and Fuel and Fuel Manufacturing Facilities (EJ 1056-2018). The radiation impact is acceptable.

ObjectiveBased on functional near-infrared spectroscopy (fNIRS), we investigated the brain activity characteristics of gross motor tasks in children with autism spectrum disorder (ASD) and motor dysfunctions (MDs) to provide a theoretical basis for further understanding the mechanism of MDs in children with ASD and designing targeted intervention programs from a central perspective. MethodsAccording to the inclusion and exclusion criteria, 48 children with ASD accompanied by MDs were recruited into the ASD group and 40 children with typically developing (TD) into the TD group. The fNIRS device was used to collect the information of blood oxygen changes in the cortical motor-related brain regions during single-handed bag throwing and tiptoe walking, and the differences in brain activation and functional connectivity between the two groups of children were analyzed from the perspective of brain activation and functional connectivity. ResultsCompared to the TD group, in the object manipulative motor task (one-handed bag throwing), the ASD group showed significantly reduced activation in both left sensorimotor cortex (SMC) and right secondary visual cortex (V2) (P<0.05), whereas the right pre-motor and supplementary motor cortex (PMC&SMA) had significantly higher activation (P<0.01) and showed bilateral brain region activity; in terms of brain functional integration, there was a significant decrease in the strength of brain functional connectivity (P<0.05) and was mainly associated with dorsolateral prefrontal cortex (DLPFC) and V2. In the body stability motor task (tiptoe walking), the ASD group had significantly higher activation in motor-related brain regions such as the DLPFC, SMC, and PMC&SMA (P<0.05) and showed bilateral brain region activity; in terms of brain functional integration, the ASD group had lower strength of brain functional connectivity (P<0.05) and was mainly associated with PMC&SMA and V2. ConclusionChildren with ASD exhibit abnormal brain functional activity characteristics specific to different gross motor tasks in object manipulative and body stability, reflecting insufficient or excessive compensatory activation of local brain regions and impaired cross-regions integration, which may be a potential reason for the poorer gross motor performance of children with ASD, and meanwhile provides data support for further unraveling the mechanisms underlying the occurrence of MDs in the context of ASD and designing targeted intervention programs from a central perspective.

OBJECTIVE: To explore the clinical characteristics and prognostic factors of patients with extranasal NK/T-cell lymphoma (NKTCL). METHODS: The clinical data of 138 patients with NKTCL diagnosed in 10 medical centers of Huaihai Lymphoma Working Group from June 2015 to April 2021 were collected and analyzed retrospectively. The differences in clinicopathological characteristics of patients with different involvement and efficacy of pegaspargase regimen were compared, as well as perform survival analysis. RESULTS: A total of 138 extranasal NKTCL patients were included, with a median age of 46 years, and the ratio of males to females was approximately 2∶1. There were 39 patients with gastrointestinal involvement, 32 patients with oropharyngeal involvement, 17 patients with skin involvement, 11 patients with lymph node involvement, 11 patients with orbital involvement, and 28 patients with other parts involvement. Patients with skin involvement had a higher proportion of advanced disease and a lower proportion of CD56 positive rate compared to those with oropharyngeal involvement. Among the patients with gastrointestinal involvement, the survival rate of patients who received pegaspargase regimen was significantly higher than those who were treated without pegaspargase (P < 0.01). Multivariate analysis showed that serum creatinine was an independent prognostic factor for patients with skin involvement ( HR =1.027, 95%CI : 1.001-1.054, P =0.040), ECOG PS and EBV DNA were independent prognostic factors for patients with gastrointestinal involvement ( HR =2.635, 95%CI : 1.096-6.338, P =0.030; HR =4.772, 95% CI : 1.092-20.854, P =0.038), and ECOG PS and CA stage were independent prognostic factors for patients with oropharyngeal involvement ( HR =13.875, 95%CI : 2.517-76.496, P =0.002; HR =20.261, 95%CI : 2.466-166.470, P =0.005). CONCLUSION The clinicopathological characteristics of extranasal NKTCL patients with different sites of involvement are vary, and effective individualized treatment need to be further explored.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Asparaginase/therapeutic use* ; Lymphoma, Extranodal NK-T-Cell/pathology* ; Prognosis ; Retrospective Studies ; Survival Rate ; Polyethylene Glycols

Objective To investigate the changes in serum levels of claudin-5 and Apelin-13 in patients with depression and their relationship with disease progression and sleep disorders.Methods A total of 128 patients with depression admitted to our hospital from June 2021 to July 2023 were selected as the study group,and another 128 patients who underwent physical examinations during the same period were selected as the control group.The correlation between the expression levels of serum claudin-5 and Apelin-13 in patients with depression and the Hamilton Depression Rating Scale(HAMD)score,as well as the diagnostic value of serum claudin-5 and Apelin-13 for the severity of depression in patients were analyzed.Results The expression level of claudin-5 in the serum of patients in study group was higher than that of the control group,which increased with the severity of the disease(P<0.05)and was positively correlated with the HAMD score(r=0.713,P<0.05).In addition,the expression level of claudin-5 in the serum of patients with sleep disorders was higher than that of those without sleep disorders(P<0.05),and the trend of changes in the expression level of Apelin-13 was opposite;Age,age at onset of depression,and claudin-5 were factors for sleep disorders in patients with depression,while Apelin-13 was a protec-tive factor(P<0.05);The combined detection of serum claudin-5 and Apelin-13 is superior to their individual detection(Z combined detection-claudin-5=2.393,Z combined detection-Apelin-13=1.964,P=0.016,0.044).Conclusion The expression levels of claudin-5 and Apelin-13 in serum of patients with depression were related to the progression of disease and the sleep disorders and the combined detection has high diagnostic value for severe depression.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective To construct a visual intelligent recognition model for Oncomelania hupensis robertsoni in Yunnan Province based on the EfficientNet-B4 model, and to evaluate the impact of data augmentation methods and model hyperparameters on the recognition of O. hupensis robertsoni. Methods A total of 400 O. hupensis robertsoni and 400 Tricula snails were collected from Yongsheng County, Yunnan Province in June 2024, and snail images were captured following identification and classification of 300 O. hupensis robertsoni and 300 Tricula snails. A total of 925 O. hupensis robertsoni images and 1 062 Tricula snail images were collected as a dataset and divided into a training set and a validation set at a ratio of 8:2, while 352 images captured from the remaining 100 O. hupensis robertsoni and 354 images from the remaining 100 Tricula snails served as an external test set. All acquired images were subjected to preprocessing, including cropping and resizing. Three data augmentation approaches were employed, including baseline, Mixup and Gaussian blurring, and model hyperparameters included two optimization algorithms of adaptive moment estimation (Adam) and stochastic gradient descent (SGD), two loss functions of focal loss and cross entropy loss, and two learning rate decay strategies of cosine annealing and multi-step. The intelligent recognition models of O. hupensis robertsoni and Tricula snails were constructed based on the EfficientNet-B4 model, and 7 training strategy groups were generated by combinations of different data augmentation approaches and hyperparameters. The performance of intelligent recognition models was tested with external test sets, and evaluated with accuracy, precision, recall, F1 score, loss, Youden’s index, and the area under the receiver operating characteristic curve (AUC) under different training strategies. Results The variation of loss values was comparable among intelligent recognition models with different data augmentation approaches. The Group 4 model constructed with Mixup and Gaussian blurring data augmentation approaches showed the optimal performance, with an accuracy of 90.38%, precision of 90.07%, F1 score of 89.44%, Youden’s index of 0.81 and AUC of 0.961 in the external test set. The accuracy of models using the SGD optimizer reduced by 29.16% as compared to those using the Adam optimizer (χ² = 81.325, P < 0.001), and the accuracy of models using the cross entropy loss function reduced by 0.80% as compared to the Group 4 model (χ² = 3.147, P > 0.05), while the accuracy of models using the multi-step learning rate decay strategy increased by 0.65% as compared to the Group 4 model (χ² = 0.208, P > 0.05). In addition, the model with the baseline + Mixup + Gaussianblurring data augmentation approach and hyperparameters of Adam optimizer, focal loss function and multi-step learning rate decay strategy showed the highest performance, with an accuracy of 91.03%, precision of 91.97%, recall of 88.11%, F1 score of 90.00%, Youden’s index of 0.82 and AUC values of 0.969 in external test set, respectively. Conclusions The intelligent recognition model of O. hupensis robertsoni based on EfficientNet-B4 model is accurate for identification of O. hupensis robertsoni and Tricula snails in Yunnan Province.

Objective To investigate the survival time of patients diagnosed with sporadic Creutzfeldt-Jakob disease in China between 2020 and 2022 and explore the associated factors influencing survival.Methods A retrospective analysis was conducted on clinically diagnosed cases with complete information on sporadic Creutzfeldt-Jakob dis-ease diagnosed by the China Creutzfeldt-Jakob disease surveillance network from 2020 to 2022,baseline information of patients was obtained from the case files,telephone follow-up was used to obtain the treatment and survival status of the patients after the diagnosis,life-table method was used for estimating the survival rate,Kaplan-Meier method was used for calculating the median survival time and the 95％CI,Cox regression model was used for univariate and multivariate analyses were used to screen for factors influencing survival time.Results The median survival time of the 300 patients was 5 months(95％CI:4.165-5.835).Univariate analysis revealed that factors such as age at onset,regional distribution,presence of corticobasal or extrapyramidal symptoms as initial manifestations,number of initial symptoms,presence of corticobasal or extrapyramidal functional abnormalities,number of major clinical manifestations,presence of typical electroencephalogram findings,and use of nasal feeding during the course of the disease were potential factors influencing survival time(P＜0.1).Multivariate analysis showed that the risk of death in patients with onset age＞65 years was 1.350 times higher than in patients with onset age ≤65 years(P=0.021,95.0％CI:1.046-1.742).Patients without pyramidal or extrapyramidal dysfunction had a 0.674-fold lower risk of death compared to those with these symptoms(P=0.020,95.0％CI:0.483-0.939).Patients who did not receive nasal feeding had a 1.817-fold higher risk of death compared to those who did(P＜0.001,95.0％CI:1.406-2.349).Conclusion Age at onset,the presence of pyramidal or extrapyramidal functional abnormalities,and the use of nasal feeding during the disease course are factors influencing the survival time of pa-tients clinically diagnosed with sCJD.

Objective:To explore the overall survival and prognostic factors of patients over 50 years old with acute myeloid leukemia(AML).Methods:The clinical data of 222 AML patients aged over 50 years in our hospital from January 2016 and June 2021 were retrospectively analyzed.Kaplan-Meier method was used to evaluate the overall survival(OS)rate,and Cox regression model to evaluate the prognostic factors.Results:The 1-year and 3-year OS rates of all patients were 46.8％and 28.8％,respectively.The recurrence rate of patients who achieved remission during follow-up time was 57％.Both univariate and multivariate analysis showed that advanced age,MLL family fusion gene,PHF6 gene mutation,TP53 gene mutation,intolerance to standard chemotherapy,incomplete remission,complex karyotype,+mar karyotype and inv(3)karyotype were significantly correlated with prognosis(all P＜0.05).Negative fusion gene and positive AML-ETO fusion gene had no obvious survival advantage in this population.In patients with complete remission,there was no significant survival advantage in those who achieved minimal residual disease negative.Conclusion:AML patients aged over 50 years have a poor outcome and high recurrence rate.The prognosis is affected by multiple factors and has its own characteristics.

Objective:To investigate the clinical value immature granulocyte percentage(IG％)and other inflammatory indicators in the severity of acute appendicitis.Methods:A total of 201 pediatric patients undergoing appendicitis surgery admitted to Zhoukou Central Hospital from June 2022 to August 2023 were included.Patients with pathologically confirmed actue appendici-tis were divided two subgroups:actue simple appendicitis(ASA)group and actue complicated ap-pendicitis(ACA)group,The variables that included IG％,white blood cell(WBC)count,absolute neutrophil count(ANC),absolute lymphocyte count(ALC),neutrophil to lymphocyte ratio(NLR),pro-calcitonin(PCT),C-reactive protein(CRP),platelet to lymphocyte(PLR)and other indexes were ana-lyzed between ASA and ACA group.The logistic regression model for diagnosis of ACA was es-tablished,and the diagostic value of this model and other inflammtory indicators for ACA was evaluated by receiver operating characteristic(ROC)curve analysis.Results:The levels of IG％,WBC,ANC,ALC,NLR,PCT and PLR were higher and the level of ALC was lower in ACA group than those in ASA group(all P＜0.05).Logistic regression analysis showed that IG％,NLR and CRP were three diagnostic determinants of ACA(all P＜0.05).The AUC of the established logistic model and IG％,NLR,CRP were 0.868,0.821,0.691 and 0.790(all P＜0.001).The logistic model was vali-dated by independent cohorts,and the AUC was 0.872,the sensitivity was 90.0％and the speci-ficity was 75.6％.Conlusions:The IG％value can early indicator for pediatric ACA,and the es-tablished logistic regression model based on biomarkers including IG％,NLR and CRP has clinical value in diagnosing ACA in children.