Objective:To evaluate the clinical utility of machine learning model based radiomics in predicting high-risk molecular subtypes of lower-grade gliomas(LrGGs).Methods:This was a cross-sectional study. A total of 287 patients diagnosed with LrGGs in the First Hospital of Shanxi Medical University, Shanxi Provincial People′s Hospital, and the Third Hospital of Shanxi Medical University from January 2011 to September 2023 were retrospectively collected, including 166 males and 121 females; 114 cases of high-risk molecular subtypes and 173 cases of non-high-risk molecular subtypes. All patients were divided into 201 cases in the training set and 86 cases in the test set according to 7∶3 in simple randomized grouping method. All patients underwent contrast-enhanced T 1WI (CE-T 1WI) and T 2-weighted fluid-attenuated inversion recovery sequence imaging (T 2-FLAIR), and the imaging features of high-risk and non-high-risk molecular subtypes were analyzed. Analysis of variance, recursive feature elimination, and Kruskal-Wallis were used for radiomics feature screening, and a support vector machine (SVM) classifier was used to construct a radiomics-based classifier model. Univariate and multivariate logistic regression were used to analyze clinical variables independently influencing high-risk molecular subtypes of LrGGs to construct a clinical model; a combined model was developed by integrating radiomics labels and clinical variables. Receiver operating characteristic curve and area under the curve (AUC), calibration curve, and decision curve were used to compare the predictive performance of different models. Results:The patient′s age ( OR=1.042, 95% CI 1.018-1.068, P=0.001), pathological grade ( OR=2.270, 95% CI 1.212-4.311, P=0.011), MGMT methylation status ( OR=0.456, 95% CI 0.238-0.866, P=0.017), and ependymal involvement ( OR=7.335, 95% CI 2.929-18.370, P<0.001) were independent influencing factors for the high-risk molecular subtype of LrGGs, and a clinical model was developed based on these factors. An SVM model was constructed based on 12 radiomics features (3 radiomics features based on CE-T 1WI and 9 radiomics features based on T 2-FLAIR). The radiomics score of the probability output by the SVM model was combined with age, pathological grade, MGMT methylation status, and ependymal involvement to develop a combined model. The AUC values of the SVM model for predicting the high-risk molecular subtype of LrGGs were 0.824 and 0.859 in the training set and test set, respectively; the AUC values of the clinical model in the training set and test set were 0.759 and 0.721, respectively; and the AUC values of the combined model in the training set and test set were 0.823 and 0.815, respectively. The combined model had a high clinical net benefit. Conclusion:The machine learning MRI radiomics model can preoperatively predict high risk molecular subtypes of LGGrs, assist in individualized treatment decisions.

Cancer is a group of chronic diseases caused by a combination of genetic and environmental factors.Immune cells play a vital role in the regulation of tumor diseases.Recently,innate lymphoid cells(ILCs)have been found to have an important regu-latory role in the tumor microenvironment.ILCs are tissue resident immune cells located mainly in the mucosa and first barrier organs and have been extensively studied for defense against pathogenic invasion,lymphatic development and tissue repair.The role of ILCs in tumor immunity has received increasing attention in recent years.Among the various subpopulations of ILCs cells,the regulation of ILC3s in tumor immunity is the most controversial.Therefore,we summarized the role of ILC3s in tumor immunity by combining rele-vant studies on the involvement of ILC3s in tumor immune regulation in recent years.

Autophagy is a conserved physiological phenomenon commonly found in all eukaryotic cells,which promotes cell survival by degrading intracellular proteins and organelles during starvation or nutrient deficiency.Dysfunc-tion autophagy is closely related to various diseases.Soluble N-elthylmaleimide-sensitive factor attachment protein recep-tor(SNARE)complex is a protein complex that mediates membrane fusion and plays a key role in the fusion process of au-tophagosomes and lysosomes.The aberrant assembly of the SNARE complex results in the arrest of autophagic flow,there-by leading to cellular dysfunction and the occurrence of diseases.In this review,we summarized the roles of SNARE pro-teins in the autophagosome-lysosome fusion and the latest research in related diseases,providing a reference for studying the mechanism of autophagy and diseases targeting the SNARE complex.

Objective:To understand the status of intestinal helminth infections in Lunan area of Shandong Province (Jining City, Rizhao City, Linyi City, Heze City, and Zaozhuang City), and provide scientific basis for formulating parasitic disease prevention and control strategies.Methods:From 2016 to 2023, a stratified sampling method was used to conduct surveillance in 33 counties (cities, districts, hereinafter referred to as counties) in Lunan area of Shandong Province. Each county was divided into five areas (east, south, west, north, and center), with one administrative village (community) selected from each area. And ≥200 permanent residents (aged ≥3 years old, having lived locally for ≥6 months) were sampled from each village (community), and one stool sample was collected from each participant. The Kato-Katz method (two slides per sample) was used for parasite detection, and the results were analyzed.Results:From 2016 to 2023, a total of 49 436 people were surveyed, including 23 861 males and 25 575 females, with an age range of 3 - 105 years old. The testing identified 687 intestinal helminth infections, with an overall infection rate of 1.39%. The predominant infection was whipworm (582 cases), with an infection rate of 1.18%; followed by roundworm and hookworm, with infection rates of 0.13% (62 cases) and 0.05% (23 cases) respectively; other types of helminths ( Clonorchis sinensis and pinworm) totaled 20 cases, with an infection rate of 0.04%. From 2016 to 2023, the annual intestinal helminth infection rates were 2.76% (201/7 292), 0.90% (56/6 327), 0.84% (52/6 200), 1.70% (124/7 282), 1.23% (88/7 133), 1.45% (104/7 150), 0.34% (17/5 058), and 1.46% (45/3 084), showing an overall downward trend (χ 2trend = 42.40, P < 0.001). The ≥60 age group had the highest intestinal helminth infection rate (2.39%, 323/13 489), while the 30 - 39 age group had the lowest rate (0.68%, 48/7 016). There was statistically significant difference in infection rates among different age groups (χ 2 = 172.25, P < 0.001). There was no statistically significant difference in infection rates between genders (χ 2 = 0.03, P = 0.862). Farmers had the highest infection rate (1.69%, 560/33 118), with statistically significant differences among different occupational groups (χ 2 = 64.88, P < 0.001). Those with primary school education or below had the highest infection rate (1.82%, 445/24 469), with statistically significant differences among different education levels (χ 2 = 64.93, P < 0.001). Conclusions:In Lunan area of Shandong Province, whipworm is the predominant intestinal helminth infection, with elderly people being the high-risk group. Although the intestinal helminth infection rate in this region remains at a low level, there is still a risk of transmission. Continuous surveillance is needed, along with strengthened prevention and control measures for key populations.

Objective:To evaluate the clinical utility of machine learning model based radiomics in predicting high-risk molecular subtypes of lower-grade gliomas(LrGGs).Methods:This was a cross-sectional study. A total of 287 patients diagnosed with LrGGs in the First Hospital of Shanxi Medical University, Shanxi Provincial People′s Hospital, and the Third Hospital of Shanxi Medical University from January 2011 to September 2023 were retrospectively collected, including 166 males and 121 females; 114 cases of high-risk molecular subtypes and 173 cases of non-high-risk molecular subtypes. All patients were divided into 201 cases in the training set and 86 cases in the test set according to 7∶3 in simple randomized grouping method. All patients underwent contrast-enhanced T 1WI (CE-T 1WI) and T 2-weighted fluid-attenuated inversion recovery sequence imaging (T 2-FLAIR), and the imaging features of high-risk and non-high-risk molecular subtypes were analyzed. Analysis of variance, recursive feature elimination, and Kruskal-Wallis were used for radiomics feature screening, and a support vector machine (SVM) classifier was used to construct a radiomics-based classifier model. Univariate and multivariate logistic regression were used to analyze clinical variables independently influencing high-risk molecular subtypes of LrGGs to construct a clinical model; a combined model was developed by integrating radiomics labels and clinical variables. Receiver operating characteristic curve and area under the curve (AUC), calibration curve, and decision curve were used to compare the predictive performance of different models. Results:The patient′s age ( OR=1.042, 95% CI 1.018-1.068, P=0.001), pathological grade ( OR=2.270, 95% CI 1.212-4.311, P=0.011), MGMT methylation status ( OR=0.456, 95% CI 0.238-0.866, P=0.017), and ependymal involvement ( OR=7.335, 95% CI 2.929-18.370, P<0.001) were independent influencing factors for the high-risk molecular subtype of LrGGs, and a clinical model was developed based on these factors. An SVM model was constructed based on 12 radiomics features (3 radiomics features based on CE-T 1WI and 9 radiomics features based on T 2-FLAIR). The radiomics score of the probability output by the SVM model was combined with age, pathological grade, MGMT methylation status, and ependymal involvement to develop a combined model. The AUC values of the SVM model for predicting the high-risk molecular subtype of LrGGs were 0.824 and 0.859 in the training set and test set, respectively; the AUC values of the clinical model in the training set and test set were 0.759 and 0.721, respectively; and the AUC values of the combined model in the training set and test set were 0.823 and 0.815, respectively. The combined model had a high clinical net benefit. Conclusion:The machine learning MRI radiomics model can preoperatively predict high risk molecular subtypes of LGGrs, assist in individualized treatment decisions.

Autophagy is a conserved physiological phenomenon commonly found in all eukaryotic cells,which promotes cell survival by degrading intracellular proteins and organelles during starvation or nutrient deficiency.Dysfunc-tion autophagy is closely related to various diseases.Soluble N-elthylmaleimide-sensitive factor attachment protein recep-tor(SNARE)complex is a protein complex that mediates membrane fusion and plays a key role in the fusion process of au-tophagosomes and lysosomes.The aberrant assembly of the SNARE complex results in the arrest of autophagic flow,there-by leading to cellular dysfunction and the occurrence of diseases.In this review,we summarized the roles of SNARE pro-teins in the autophagosome-lysosome fusion and the latest research in related diseases,providing a reference for studying the mechanism of autophagy and diseases targeting the SNARE complex.

Objective:To understand the status of intestinal helminth infections in Lunan area of Shandong Province (Jining City, Rizhao City, Linyi City, Heze City, and Zaozhuang City), and provide scientific basis for formulating parasitic disease prevention and control strategies.Methods:From 2016 to 2023, a stratified sampling method was used to conduct surveillance in 33 counties (cities, districts, hereinafter referred to as counties) in Lunan area of Shandong Province. Each county was divided into five areas (east, south, west, north, and center), with one administrative village (community) selected from each area. And ≥200 permanent residents (aged ≥3 years old, having lived locally for ≥6 months) were sampled from each village (community), and one stool sample was collected from each participant. The Kato-Katz method (two slides per sample) was used for parasite detection, and the results were analyzed.Results:From 2016 to 2023, a total of 49 436 people were surveyed, including 23 861 males and 25 575 females, with an age range of 3 - 105 years old. The testing identified 687 intestinal helminth infections, with an overall infection rate of 1.39%. The predominant infection was whipworm (582 cases), with an infection rate of 1.18%; followed by roundworm and hookworm, with infection rates of 0.13% (62 cases) and 0.05% (23 cases) respectively; other types of helminths ( Clonorchis sinensis and pinworm) totaled 20 cases, with an infection rate of 0.04%. From 2016 to 2023, the annual intestinal helminth infection rates were 2.76% (201/7 292), 0.90% (56/6 327), 0.84% (52/6 200), 1.70% (124/7 282), 1.23% (88/7 133), 1.45% (104/7 150), 0.34% (17/5 058), and 1.46% (45/3 084), showing an overall downward trend (χ 2trend = 42.40, P < 0.001). The ≥60 age group had the highest intestinal helminth infection rate (2.39%, 323/13 489), while the 30 - 39 age group had the lowest rate (0.68%, 48/7 016). There was statistically significant difference in infection rates among different age groups (χ 2 = 172.25, P < 0.001). There was no statistically significant difference in infection rates between genders (χ 2 = 0.03, P = 0.862). Farmers had the highest infection rate (1.69%, 560/33 118), with statistically significant differences among different occupational groups (χ 2 = 64.88, P < 0.001). Those with primary school education or below had the highest infection rate (1.82%, 445/24 469), with statistically significant differences among different education levels (χ 2 = 64.93, P < 0.001). Conclusions:In Lunan area of Shandong Province, whipworm is the predominant intestinal helminth infection, with elderly people being the high-risk group. Although the intestinal helminth infection rate in this region remains at a low level, there is still a risk of transmission. Continuous surveillance is needed, along with strengthened prevention and control measures for key populations.

Objective:To investigate the current application status of prophylactic anti-infective drugs during the perioperative period in liver transplantation centers and provide data references for further standardizing prophylactic regimens.Methods:A questionnaire comprising 53 questions across 5 dimensions was designed and released using the WJX platform. The dimensions included basic information about medical institutions, perioperative pathogenic microorganisms, current status of empirical antibacterial prophylaxis, adjustments to prophylactic anti-infective strategies, and an overview of prophylactic measures against other pathogens. Based on the survey results, the types of common perioperative pathogens in liver transplantation, types of prophylactic antibacterial drugs, timing and duration of administration, upgraded prophylaxis strategies (such as escalation of antibiotic classes or extension of drug application duration), and prevention strategies for other pathogens were summarized.Results:A total of 13 completed questionnaires from pharmacists at liver transplantation centers were collected. The most common pathogens during the perioperative period were Gram-negative bacilli, including Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii. The most frequently used prophylactic antibacterial drugs were cefoperazone/sulbactam and piperacillin/tazobactam. Regarding the timing of administration, 9 centers administered drugs 0.5 to 1.0 hour before surgery, 3 within 0.5 hour, and 1 within 1 hour preoperatively. The prophylactic duration was within 7 days postoperatively for living donor liver transplantation in 10 centers, while for cadaveric donor liver transplantation, only 6 centers adhered to the 7-day duration. When donors had infections with sensitive bacteria, 9 centers upgraded prevention strategies: 2 centers escalated the antibiotic class or adjusted regimens, 5 centers extended the duration of prophylaxis, 2 centers implemented donor-specific susceptibility-guided antibacterial treatments regardless of colonization or infection, and 5 centers administered prophylaxis only in cases of colonization based on donor susceptibility results. When donors had multi-drug resistance bacterial infections, 11 centers upgraded prevention strategies: 7 escalated the antibiotic class or adjusted regimens, 4 extended prophylaxis duration, 6 implemented susceptibility-guided treatments irrespective of colonization or infection, 1 administered prophylaxis only for colonization based on donor susceptibility results, and 2 abandoned transplantations. 7 centers routinely applied antifungal prophylactic measures, including 1 for preoperative prophylaxis and 6 for postoperative prophylaxis, using caspofungin (4 centers), fluconazole (2 centers), posaconazole (1 center), and micafungin (1 center). 6 centers initiated antifungal prophylaxis in cases with donor or recipient fungal infection history or active fungal infections detected during liver procurement. Most antifungal prophylaxis was administered within 72 hours postoperative (11 centers), with durations mostly within 14 days (12 centers). For viral infections, 6 centers adopted routine postoperative prophylactic measures. Conclusions:Currently, the perioperative prophylactic anti-infective strategies in 13 liver transplantation centers are not standardized. High-quality multicenter clinical studies are needed to compare the effectiveness of different prophylactic regimens, aiming to further standardize the types and durations of prophylactic drug use.

Cancer is a group of chronic diseases caused by a combination of genetic and environmental factors.Immune cells play a vital role in the regulation of tumor diseases.Recently,innate lymphoid cells(ILCs)have been found to have an important regu-latory role in the tumor microenvironment.ILCs are tissue resident immune cells located mainly in the mucosa and first barrier organs and have been extensively studied for defense against pathogenic invasion,lymphatic development and tissue repair.The role of ILCs in tumor immunity has received increasing attention in recent years.Among the various subpopulations of ILCs cells,the regulation of ILC3s in tumor immunity is the most controversial.Therefore,we summarized the role of ILC3s in tumor immunity by combining rele-vant studies on the involvement of ILC3s in tumor immune regulation in recent years.