Objective To explore the value of support vector machine(SVM)model based on gray matter volume(GMV)for identifying amyotrophic lateral sclerosis(ALS),also to analyze the relevant brain regions.Methods MR 3D T1WI data of 60 ALS patients(ALS group)and 60 healthy volunteers(control group)were retrospectively analyzed.Taken GMV of each brain region obtained by voxel-based morphometry as the input features.F-score analysis was used to select feature with the highest classification accuracy to construct SVM model.Receiver operating characteristic curve was drawn to evaluate the efficacy of SVM model for identifying ALS,and top 10％was used as the weight threshold to obtain gray matter brain regions contributed the most to this model.Results SVM model constructed based on the top 40％GMV features had the highest classification accuracy(82.50％),with sensitivity,specificity and area under the curve(AUG)of 85.05％,80.40％and 0.890,respectively.The left precentral gyrus,left anterior cingulate gyrus and paracingulate gyrus,right middle temporal gyrus,opercular part of left inferior frontal gyrus,right dorsolateral superior frontal gyrus,left temporal pole:middle temporal gyrus,right superior occipital gyrus,orbital part of right middle frontal gyrus,right calcarine fissure and surrounding cortex,right fusiform gyrus were the top 1-10 gray matter brain regions contributed to this model.Conclusion ALS had specific GMV change pattern.SVM model based on GMV could be used to effectively identify ALS,while the left precentral gyrus was the most contributive brain region to this model.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

Objective To investigate the ameliorative effects and mechanisms of six types of tea(green tea,cyan tea,red tea,white tea,black tea and yellow tea)on metabolic disorders in obesity mice induced by high-fat diet(HFD).Methods Four-week-old male C57BL/6J mice were randomly divided into 8 groups with 7 mice per group.An HFD-induced obese mouse model was established,and the mice in control group maintained on standard diet followed by intragastric administration of different teas for 5 weeks.The body weight,liver weight ratio,fasting blood glucose,and lipid profile of the mice were measured to assess glucose and lipid metabolism.Serum inflammatory factors including IL-6,tumor necrosis factor-alpha(TNF-α)and oxidative stress markers[malondialdehyde(MDA)and superoxide dismutase(SOD)were measured.Additionally,liver histopathology and the expression of key glycolipid metabolism-related genes,adenosine monophosphate-activated protein kinase(AMPK)and carnitine palmitoyltransferase 1(CPT-1),were analyzed to explore underlying mechanisms.Results Cyan tea significantly suppressed weight gain,demonstrating superior weight control.White tea markedly reduced fasting blood glucose levels and decreased the area under the curve of oral glucose tolerance test(OGTT)and insulin tolerance test(ITT),indicating synergistic improvements in glucose metabolism and insulin sensitivity.Yellow tea exhibited exceptional anti-inflammatory and antioxidant effects,reducing hepatic IL-6 and MDA while enhancing SOD activity.Green tea activated the lipid oxidation pathway by upregulating AMPK/CPT-1 expression.All kinds of tea significantly attenuated hepatic lipid droplet accumulation.Conclusion All six types of tea alleviated metabolic disorders by reducing hepatic fat content in obesity mice.However,different types of tea exert their unique effects on improving metabolic disorders through differential mechanisms such as glucose metabolism regulation,lipid oxidation,and anti-inflammatory and antioxidant actions.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

This study was aimed at understanding the resistance status of dairy cow-derived Streptococcus strains in China,and providing scientific guidance for the rational use of antimicrobials and the development of new antimicrobials.Meta-analysis was used to explore the resistance of Streptococcus strains to 20 antimicrobials between 2000 and 2023.A total of 67 articles de-scribing 3 154 strains were included after a literature search,and a meta-analysis was conducted on the overall collection area according to time subgroups for 20 antimicrobials.Streptococci of dairy origin in China showed varying resistance rates(≥30％),as follows:penicillin(60％,95％CI=0.48-0.72),streptomycin(57％,95％CI=0.46-0.68),cotrimoxazole(56％,95％CI=0.28-0.82),lincomycin(51％,95％CI=0.26-0.76),tetracycline(49％,95％CI=0.40-0.59),doxycyc-line(42％,95％CI=0.24-0.60),clindamycin(41％,95％CI=0.28-0.54),ampicillin(39％,95％CI=0.27-0.52),e-rythromycin(37％,95％CI=0.28-0.45),kanamycin(36％,95％CI=0.20-0.54),and amoxicillin(30％,95％CI=0.10-0.53).On the basis of findings in the collection area,the resistance rates of dairy cow-derived Streptococcus to antimicrobials in Northeast China and Southwest China was generally high.The resistance rates of Streptococcus from dairy cattle to antimi-crobial drugs such as tetracycline,doxycycline,and lincomycin increased significantly over time.However,the resistance rates to antimicrobial drugs such as streptomycin,gentamicin,and enrofloxacin showed a significant decreasing trend.Dairy cow-de-rived Streptococcus had high resistance to some antimicrobials,and the resistance varied by region,because of differences in breeding and management.Monitoring of antimicrobial resistance rates,enhancing research on resistance mechanisms,and reg-ulating the use of antimicrobials remain necessary.

Objective:To establish a pure water direct dilution-inductively coupled plasma mass spectrometry (ICP-MS) detection method for rapid determination of urinary iodine.Methods:Pure water was used to directly dilute the urine samples. The washing solution was 5.0 g/L ascorbic acid, the internal standard solution was 5.0 g/L ascorbic acid and 100 μg/L 128Te, the standard solution was prepared with the solution of lyophilized urine iodine biological component analysis reference material. The method was evaluated in terms of linear range, detection limit, quantification limit, precision and method comparision experiment. Results:The linear correlation coefficient of the standard curve for iodine concentration range from 0 to 50.0 μg/L was 0.999 7, with a detection limit of 0.2 μg/L and a quantification limit of 0.6 μg/L. The spiked recovery rates of low, medium, and high concentration iodine standard solutions added to actual urine samples were 100.8%, 99.1% and 99.7%, respectively, with relative standard deviations of 0.8%, 1.3% and 1.6%, respectively. There was no statistically significant difference ( t = - 0.14, P = 0.890) between the results of measuring actual urine and assessment urine using this method and "Determination of Iodine in Urine-Part 2: Inductively Coupled Plasma Mass Spectrometry (WS/T 107.2-2016)". Conclusions:We have successfully established a pure water direct dilution-ICP-MS method for determining urinary iodine. This method provides accurate and highly sensitive results, making it suitable for sudden public health emergencies and large-scale clinical measurement of urinary iodine.

This study was aimed at understanding the resistance status of dairy cow-derived Streptococcus strains in China,and providing scientific guidance for the rational use of antimicrobials and the development of new antimicrobials.Meta-analysis was used to explore the resistance of Streptococcus strains to 20 antimicrobials between 2000 and 2023.A total of 67 articles de-scribing 3 154 strains were included after a literature search,and a meta-analysis was conducted on the overall collection area according to time subgroups for 20 antimicrobials.Streptococci of dairy origin in China showed varying resistance rates(≥30％),as follows:penicillin(60％,95％CI=0.48-0.72),streptomycin(57％,95％CI=0.46-0.68),cotrimoxazole(56％,95％CI=0.28-0.82),lincomycin(51％,95％CI=0.26-0.76),tetracycline(49％,95％CI=0.40-0.59),doxycyc-line(42％,95％CI=0.24-0.60),clindamycin(41％,95％CI=0.28-0.54),ampicillin(39％,95％CI=0.27-0.52),e-rythromycin(37％,95％CI=0.28-0.45),kanamycin(36％,95％CI=0.20-0.54),and amoxicillin(30％,95％CI=0.10-0.53).On the basis of findings in the collection area,the resistance rates of dairy cow-derived Streptococcus to antimicrobials in Northeast China and Southwest China was generally high.The resistance rates of Streptococcus from dairy cattle to antimi-crobial drugs such as tetracycline,doxycycline,and lincomycin increased significantly over time.However,the resistance rates to antimicrobial drugs such as streptomycin,gentamicin,and enrofloxacin showed a significant decreasing trend.Dairy cow-de-rived Streptococcus had high resistance to some antimicrobials,and the resistance varied by region,because of differences in breeding and management.Monitoring of antimicrobial resistance rates,enhancing research on resistance mechanisms,and reg-ulating the use of antimicrobials remain necessary.

Objective To investigate the ameliorative effects and mechanisms of six types of tea(green tea,cyan tea,red tea,white tea,black tea and yellow tea)on metabolic disorders in obesity mice induced by high-fat diet(HFD).Methods Four-week-old male C57BL/6J mice were randomly divided into 8 groups with 7 mice per group.An HFD-induced obese mouse model was established,and the mice in control group maintained on standard diet followed by intragastric administration of different teas for 5 weeks.The body weight,liver weight ratio,fasting blood glucose,and lipid profile of the mice were measured to assess glucose and lipid metabolism.Serum inflammatory factors including IL-6,tumor necrosis factor-alpha(TNF-α)and oxidative stress markers[malondialdehyde(MDA)and superoxide dismutase(SOD)were measured.Additionally,liver histopathology and the expression of key glycolipid metabolism-related genes,adenosine monophosphate-activated protein kinase(AMPK)and carnitine palmitoyltransferase 1(CPT-1),were analyzed to explore underlying mechanisms.Results Cyan tea significantly suppressed weight gain,demonstrating superior weight control.White tea markedly reduced fasting blood glucose levels and decreased the area under the curve of oral glucose tolerance test(OGTT)and insulin tolerance test(ITT),indicating synergistic improvements in glucose metabolism and insulin sensitivity.Yellow tea exhibited exceptional anti-inflammatory and antioxidant effects,reducing hepatic IL-6 and MDA while enhancing SOD activity.Green tea activated the lipid oxidation pathway by upregulating AMPK/CPT-1 expression.All kinds of tea significantly attenuated hepatic lipid droplet accumulation.Conclusion All six types of tea alleviated metabolic disorders by reducing hepatic fat content in obesity mice.However,different types of tea exert their unique effects on improving metabolic disorders through differential mechanisms such as glucose metabolism regulation,lipid oxidation,and anti-inflammatory and antioxidant actions.

Objective:To establish a pure water direct dilution-inductively coupled plasma mass spectrometry (ICP-MS) detection method for rapid determination of urinary iodine.Methods:Pure water was used to directly dilute the urine samples. The washing solution was 5.0 g/L ascorbic acid, the internal standard solution was 5.0 g/L ascorbic acid and 100 μg/L 128Te, the standard solution was prepared with the solution of lyophilized urine iodine biological component analysis reference material. The method was evaluated in terms of linear range, detection limit, quantification limit, precision and method comparision experiment. Results:The linear correlation coefficient of the standard curve for iodine concentration range from 0 to 50.0 μg/L was 0.999 7, with a detection limit of 0.2 μg/L and a quantification limit of 0.6 μg/L. The spiked recovery rates of low, medium, and high concentration iodine standard solutions added to actual urine samples were 100.8%, 99.1% and 99.7%, respectively, with relative standard deviations of 0.8%, 1.3% and 1.6%, respectively. There was no statistically significant difference ( t = - 0.14, P = 0.890) between the results of measuring actual urine and assessment urine using this method and "Determination of Iodine in Urine-Part 2: Inductively Coupled Plasma Mass Spectrometry (WS/T 107.2-2016)". Conclusions:We have successfully established a pure water direct dilution-ICP-MS method for determining urinary iodine. This method provides accurate and highly sensitive results, making it suitable for sudden public health emergencies and large-scale clinical measurement of urinary iodine.

Objective To explore the value of support vector machine(SVM)model based on gray matter volume(GMV)for identifying amyotrophic lateral sclerosis(ALS),also to analyze the relevant brain regions.Methods MR 3D T1WI data of 60 ALS patients(ALS group)and 60 healthy volunteers(control group)were retrospectively analyzed.Taken GMV of each brain region obtained by voxel-based morphometry as the input features.F-score analysis was used to select feature with the highest classification accuracy to construct SVM model.Receiver operating characteristic curve was drawn to evaluate the efficacy of SVM model for identifying ALS,and top 10％was used as the weight threshold to obtain gray matter brain regions contributed the most to this model.Results SVM model constructed based on the top 40％GMV features had the highest classification accuracy(82.50％),with sensitivity,specificity and area under the curve(AUG)of 85.05％,80.40％and 0.890,respectively.The left precentral gyrus,left anterior cingulate gyrus and paracingulate gyrus,right middle temporal gyrus,opercular part of left inferior frontal gyrus,right dorsolateral superior frontal gyrus,left temporal pole:middle temporal gyrus,right superior occipital gyrus,orbital part of right middle frontal gyrus,right calcarine fissure and surrounding cortex,right fusiform gyrus were the top 1-10 gray matter brain regions contributed to this model.Conclusion ALS had specific GMV change pattern.SVM model based on GMV could be used to effectively identify ALS,while the left precentral gyrus was the most contributive brain region to this model.