Climate change is altering the Earth's water cycle system. The resulting three extreme weather events—heatwaves, droughts, and extreme precipitation—impacts urban and rural water security through multi-layered mechanisms. A primary structural disparity exists between urban and rural systems: while urban areas benefit from comprehensive and standardized pipe networks that ensure terminal water quality, rural areas often suffer from "last mile" vulnerability due to inadequate infrastructure and outdated purification facilities. Extreme weather can directly alter the microbial community structure, concentrations of chemical pollutants and physicochemical properties of source water. These alterations interfere with the efficiency of water treatment processes and ultimately compromise the integrity of distribution systems. Because distribution networks often lack real-time monitoring and adaptive response capabilities, they have emerged as the most vulnerable link in the "water source-water treatment-distribution system" chain. Based on a systematic analysis of these chain-wide impacts, this paper proposed a series of control strategies, including security frameworks based on multi-model coupling and water source protection measures, improvement of water treatment technologies, optimization of distribution systems, and development of new water quality monitoring methods. These strategies aim to enhance the climate adaptability of urban and rural drinking water systems through multi-dimensional intervention, providing a theoretical basis for constructing climate-resilient water infrastructure.

Objective:To explore the clinical characteristics and genetic etiology of a child with Neurofibromatosis-Noonan syndrome (NFNS).Methods:A child with NFNS who was treated at the Department of Endocrinology of Hangzhou Children′s Hospital in January 2024 was selected as the study subject. Clinical data of the child was collected by retrospective analysis method. Peripheral venous blood samples (2 mL each) were collected from the child and his parents. Genomic DNA was extracted, and trio whole exome sequencing (Trio-WES) of the family was carried out. Sanger sequencing was used to perform family verification on the candidate variants. The identified variants were classified for pathogenicity according to the Standards and Guidelines for the Interpretation of Sequence Variants established by the American College of Medical Genetics and Genomics (ACMG) (hereafter referred to as the " ACMG guidelines" ). This study has been approved by the Medical Ethics Committee of Hangzhou Children′s Hospital (Ethics No. 2021-06).Results:The child was a 7-year and 4-month-old male. He has short stature, numerous café-au-lait spots on the neck and trunk, and special facial features such as a full forehead, wide interpupillary distance, a low nasal bridge, and low-set ears.The results of Trio-WES showed that he has harbored a NF1 gene c. 3773G>T (p.W1258L) mutation, which was verified by Sanger sequencing to be de novo in origin. The NF1 gene child was associated with NFNS, which was an autosomal dominant inheritance. According to the ACMG guidelines, this variant was judged to be a likely pathogenic variant (PS2+ PM2+ PP3+ PP2). No pathogenic variant in genes associated with Noonan syndrome, such as those in PTPN11, SOS1, RAF1, RIT1, and KRAS, was found. Conclusion:The child with NFNS has clinical features such as short stature, special facial features, and café-au-lait spots. The c. 3773G>T (p.W1258L) variation in the NF1 gene may be the genetic etiology of the NFNS child in this study. The results of this study has enriched the variation spectrum of the NF1 gene.

Objective:To investigate the denoising performance of different deep learning (DL) strategies on low-dose brain 18F-FDG PET images. Methods:This retrospective methodological study was conducted on brain PET/CT images of 50 patients (35 males, 15 females, age 20-87 years) who received 3.7MBq/kg 18F-FDG at the Fifth Affiliated Hospital of Sun Yat-sen University between May 2023 and January 2024. Full-dose PET data were acquired with 2min scan. CT scans were acquired before PET scanning. Low-dose PET sinograms were generated by down-sampling the full-dose list mode data to 1/2, 1/4, and 1/20 of full-dose count level. Both full-dose and low-dose sinograms were reconstructed with random, CT-based attenuation and scatter corrections using the three-dimensional (3D) ordered-subsets expectation maximization (OSEM) algorithm (2 iterations, 20 subsets). A total of 4 DL denoising methods were established: (1) 3D conditional generative adversarial networks (GAN) using only low-dose PET as input (GAN-1); (2) 3D attention-based GAN (AttGAN) with low-dose PET input (AttGAN-1); (3) 3D AttGAN with low-dose PET and CT inputs (AttGAN-2); (4) 3D AttGAN with frequency-separation using low-dose PET and CT inputs (AttGAN-FS-2). For AttGAN-FS-2, during the frequency division process, high- and low-frequency components were extracted from the PET reconstructed images via Fourier transform, then inversed Fourier transform, denoised separately, and finally combined to produce the final denoised images. The dataset was separated into training (70%), validation (10%) and testing (20%) sets using simple random sampling without replacement with a fixed random seed. A 5-fold cross-validation scheme was then applied to test all 50 patients. Performance was evaluated against full-dose PET using normalized mean square error (NMSE), structural similarity (SSIM), peak signal-to-noise ratio (PSNR), contrast-to-noise ratio (CNR), SUV mean and SUV max bias of selected brain ROIs. Wilcoxon signed rank test was used to analyze the differences between the denoising methods. Results:AttGAN-FS-2 showed the best performance among all dose levels, with statistical difference as compared by low-dose PET and GAN-1 denoised images for NMSE, SSIM, PSNR, and CNR ( Z values: 2.92-6.15, all P<0.005). NMSE, SSIM quantitative evaluation results (median) of each model at 1/20 dose were: GAN-1: 0.08, 0.87, AttGAN-1: 0.08, 0.88, AttGAN-2: 0.07, 0.89, AttGAN-FS-2: 0.06, 0.91, respectively ( Z values: 3.24-5.77, all P<0.005). Conclusion:The DL-based method combined with multiple strategies AttGAN-FS-2 shows improved denoising performance for low-dose brain PET images.

OBJECTIVE: To explore the clinical characteristics and genetic etiology of a child with Neurofibromatosis-Noonan syndrome (NFNS). METHODS: A child with NFNS who was treated at the Department of Endocrinology of Hangzhou Children's Hospital in January 2024 was selected as the study subject. Clinical data of the child was collected by retrospective analysis. Peripheral venous blood samples (2 mL each) were collected from the child and his parents. Genomic DNA was extracted, and trio-whole exome sequencing (Trio-WES) of the family was carried out. Sanger sequencing was used to perform family verification on the candidate variants. The identified variants were classified for pathogenicity according to the Standards and Guidelines for the Interpretation of Sequence Variants established by the American College of Medical Genetics and Genomics (ACMG) (hereafter referred to as the "ACMG guidelines"). This study has been approved by the Medical Ethics Committee of Hangzhou Children's Hospital (Ethics No. 2021-06). RESULTS: The child was a 7-year and 4-month-old male. He has short stature, numerous café-au-lait spots on the neck and trunk, and special facial features such as a full forehead, wide interpupillary distance, a low nasal bridge, and low-set ears. The results of Trio-WES showed that the he had harbored the NF1 gene c.3773G>T (p.W1258L) mutation, which was verified by Sanger sequencing to be de novo in origin. The NF1 gene was associated with NFNS, which has an autosomal dominant inheritance. According to the ACMG guidelines, this variant was judged to be a likely pathogenic variant (PS2+PM2+PP3+PP2). No pathogenic variant in genes associated with Noonan syndrome, such as PTPN11, SOS1, RAF1, RIT1, and KRAS, was found. CONCLUSION The child with NFNS has clinical features such as short stature, special facial features, and café-au-lait spots. The c.3773G>T (p.W1258L) variation in the NF1 gene may be the genetic etiology of the NFNS child in this study. The results of this study has enriched the variation spectrum of the NF1 gene.
Child ; Humans ; Male ; Exome Sequencing ; Mutation ; Neurofibromatosis 1/genetics* ; Neurofibromin 1/genetics* ; Noonan Syndrome/genetics*

AIM:To explore the causal association between the counts of five types of white blood cells—neutrophils,monocytes,eosinophils,baso-phils,and lymphocytes—and venous thromboem-bolism(VTE).METHODS:Mendelian randomization(MR)analysis method was used,with genetic vari-ants associated with the five types of white blood cells as instrumental variables,and venous throm-boembolism occurrence risk as the outcome vari-able,inverse variance-weighted(IVW)method was employed as the primary analysis method,with MR-Egger regression,weighted median(WM),sim-ple model,and weighted mode methods used as supplements,to analyze the causal association be-tween the counts of five types of white blood cells and VTE,followed by reverse MR analysis.RE-SULTS:Neutrophil and lymphocyte counts are caus-ally associated with the risk of VTE.For neutrophil count,the IVW estimate(OR=0.867,95%CI:0.761-0.981,P=0.031),MR-Egger estimate(OR=0.754,95%CI:0.571-0.996,P=0.048),weighted median es-timate(OR=0.846,95%CI:0.729-0.981,P=0.027),and weighted model estimate(OR=0.748,95%CI:0.595-0.942,P=0.014)were calculated.For lympho-cyte count,the IVW estimate(OR=0.838,95%CI:0.741-0.949,P=0.005)and weighted median esti-mate(OR=0.024,95%CI:0.718-0.977,P=0.024)were calculated.Reverse MR analysis showed a causal association between the risk of VTE and neu-trophil count,the IVW estimate(OR=0.989,95%CI:0.980-0.999,P=0.024).CONCLUSION:Neutrophil and lymphocyte counts are related to the risk of VTE,and decrease in neutrophil and lymphocyte numbers may increase the risk of VTE.VTE occur-rence risk is associated with neutrophil count,and reducing the risk of VTE occurrence may increase neutrophil count.Further research is needed to un-derstand the underlying biological mechanisms be-hind this relationship.

AIM:To explore the causal association between the counts of five types of white blood cells—neutrophils,monocytes,eosinophils,baso-phils,and lymphocytes—and venous thromboem-bolism(VTE).METHODS:Mendelian randomization(MR)analysis method was used,with genetic vari-ants associated with the five types of white blood cells as instrumental variables,and venous throm-boembolism occurrence risk as the outcome vari-able,inverse variance-weighted(IVW)method was employed as the primary analysis method,with MR-Egger regression,weighted median(WM),sim-ple model,and weighted mode methods used as supplements,to analyze the causal association be-tween the counts of five types of white blood cells and VTE,followed by reverse MR analysis.RE-SULTS:Neutrophil and lymphocyte counts are caus-ally associated with the risk of VTE.For neutrophil count,the IVW estimate(OR=0.867,95%CI:0.761-0.981,P=0.031),MR-Egger estimate(OR=0.754,95%CI:0.571-0.996,P=0.048),weighted median es-timate(OR=0.846,95%CI:0.729-0.981,P=0.027),and weighted model estimate(OR=0.748,95%CI:0.595-0.942,P=0.014)were calculated.For lympho-cyte count,the IVW estimate(OR=0.838,95%CI:0.741-0.949,P=0.005)and weighted median esti-mate(OR=0.024,95%CI:0.718-0.977,P=0.024)were calculated.Reverse MR analysis showed a causal association between the risk of VTE and neu-trophil count,the IVW estimate(OR=0.989,95%CI:0.980-0.999,P=0.024).CONCLUSION:Neutrophil and lymphocyte counts are related to the risk of VTE,and decrease in neutrophil and lymphocyte numbers may increase the risk of VTE.VTE occur-rence risk is associated with neutrophil count,and reducing the risk of VTE occurrence may increase neutrophil count.Further research is needed to un-derstand the underlying biological mechanisms be-hind this relationship.

Objective:To explore the clinical characteristics and genetic etiology of a child with Neurofibromatosis-Noonan syndrome (NFNS).Methods:A child with NFNS who was treated at the Department of Endocrinology of Hangzhou Children′s Hospital in January 2024 was selected as the study subject. Clinical data of the child was collected by retrospective analysis method. Peripheral venous blood samples (2 mL each) were collected from the child and his parents. Genomic DNA was extracted, and trio whole exome sequencing (Trio-WES) of the family was carried out. Sanger sequencing was used to perform family verification on the candidate variants. The identified variants were classified for pathogenicity according to the Standards and Guidelines for the Interpretation of Sequence Variants established by the American College of Medical Genetics and Genomics (ACMG) (hereafter referred to as the " ACMG guidelines" ). This study has been approved by the Medical Ethics Committee of Hangzhou Children′s Hospital (Ethics No. 2021-06).Results:The child was a 7-year and 4-month-old male. He has short stature, numerous café-au-lait spots on the neck and trunk, and special facial features such as a full forehead, wide interpupillary distance, a low nasal bridge, and low-set ears.The results of Trio-WES showed that he has harbored a NF1 gene c. 3773G>T (p.W1258L) mutation, which was verified by Sanger sequencing to be de novo in origin. The NF1 gene child was associated with NFNS, which was an autosomal dominant inheritance. According to the ACMG guidelines, this variant was judged to be a likely pathogenic variant (PS2+ PM2+ PP3+ PP2). No pathogenic variant in genes associated with Noonan syndrome, such as those in PTPN11, SOS1, RAF1, RIT1, and KRAS, was found. Conclusion:The child with NFNS has clinical features such as short stature, special facial features, and café-au-lait spots. The c. 3773G>T (p.W1258L) variation in the NF1 gene may be the genetic etiology of the NFNS child in this study. The results of this study has enriched the variation spectrum of the NF1 gene.

Objective:To investigate the denoising performance of different deep learning (DL) strategies on low-dose brain 18F-FDG PET images. Methods:This retrospective methodological study was conducted on brain PET/CT images of 50 patients (35 males, 15 females, age 20-87 years) who received 3.7MBq/kg 18F-FDG at the Fifth Affiliated Hospital of Sun Yat-sen University between May 2023 and January 2024. Full-dose PET data were acquired with 2min scan. CT scans were acquired before PET scanning. Low-dose PET sinograms were generated by down-sampling the full-dose list mode data to 1/2, 1/4, and 1/20 of full-dose count level. Both full-dose and low-dose sinograms were reconstructed with random, CT-based attenuation and scatter corrections using the three-dimensional (3D) ordered-subsets expectation maximization (OSEM) algorithm (2 iterations, 20 subsets). A total of 4 DL denoising methods were established: (1) 3D conditional generative adversarial networks (GAN) using only low-dose PET as input (GAN-1); (2) 3D attention-based GAN (AttGAN) with low-dose PET input (AttGAN-1); (3) 3D AttGAN with low-dose PET and CT inputs (AttGAN-2); (4) 3D AttGAN with frequency-separation using low-dose PET and CT inputs (AttGAN-FS-2). For AttGAN-FS-2, during the frequency division process, high- and low-frequency components were extracted from the PET reconstructed images via Fourier transform, then inversed Fourier transform, denoised separately, and finally combined to produce the final denoised images. The dataset was separated into training (70%), validation (10%) and testing (20%) sets using simple random sampling without replacement with a fixed random seed. A 5-fold cross-validation scheme was then applied to test all 50 patients. Performance was evaluated against full-dose PET using normalized mean square error (NMSE), structural similarity (SSIM), peak signal-to-noise ratio (PSNR), contrast-to-noise ratio (CNR), SUV mean and SUV max bias of selected brain ROIs. Wilcoxon signed rank test was used to analyze the differences between the denoising methods. Results:AttGAN-FS-2 showed the best performance among all dose levels, with statistical difference as compared by low-dose PET and GAN-1 denoised images for NMSE, SSIM, PSNR, and CNR ( Z values: 2.92-6.15, all P<0.005). NMSE, SSIM quantitative evaluation results (median) of each model at 1/20 dose were: GAN-1: 0.08, 0.87, AttGAN-1: 0.08, 0.88, AttGAN-2: 0.07, 0.89, AttGAN-FS-2: 0.06, 0.91, respectively ( Z values: 3.24-5.77, all P<0.005). Conclusion:The DL-based method combined with multiple strategies AttGAN-FS-2 shows improved denoising performance for low-dose brain PET images.

Objective To investigate the difference of facial soft tissue changes in patients with different vertical bone facial types after orthodontic treatment.Methods A total of 137 female patients with class Ⅱ malocclusion aged 18 to 30 years old were selected for retrospective analysis using facial soft tissue 3D model data.According to the mandibular plane angle(FH-MP)angle,they were divided into high angle group,average angle group and low angle group.The EinScan Pro 2X 2020 handheld high-precision 3D scanner was used to capture facial soft tissue images of patients before treatment(T0)and at 6 months during treatment(T1)and after treatment(T2).The patients'facial images were overlapped using reverse engineering software Geomagic Wrap 2021,and the differ-ences within and between groups were statistically analyzed using SPSS 26.0 statistical software.Results Before and after orthodontic treatment,the average overall facial changes in the high angle group were(-3.25±0.22)mm,in the average angle group was(-3.28±0.30)mm,and in the average low angle group was(-3.69±0.36)mm.Compared with the other two groups,the changes in the low angle group decreased more,and the difference was statistically significant(P＜0.05).The mandibular angle area and temporal area decreased the most in the low angle group,which were(-2.78±0.18)mm and(-2.27±0.35)mm,respectively,and the differ-ence was statistically significant compared with the other two groups(P＜0.05),while there was no statistically significant difference among the other groups(P＞0.05).Conclusion The whole face and all facial regions of the three groups had some negative changes,but the collapse in the mandibular angle area and the temporal muscle ar-ea of the low angle group was more obvious than that of the other two groups.

Platelet-aggregation receptor 1 (PEAR1) is a transmembrane receptor identified in 2005 and expressed mainly on platelets and endothelial cells. PEAR1 is a receptor protein that contacts platelets with each other and plays an important role in platelet activation and aggregation. Endothelial cells play an important role in maintaining vascular tone and vascular repair, and PEAR1 regulates the process of tumourigenesis and development by affecting their proliferation and associated neovascularisation. In recent years, PEAR1 has gradually been recognized as a potential target for antithrombotic drugs. This review focuses on elucidating the mechanisms of platelet endothelial aggregation receptor 1 and related signaling pathways in platelets and endothelial cells, and provides new ideas for the study of drug therapy for tumour-associated thrombosis.