Objective:X-linked non-syndromic hearing loss is an extremely rare type of hearing impairment. This study conducted a phenotypic and genetic analysis of a family with X-linked dominant inheritance to explore the causes of hearing loss. Methods:Clinical data were collected from a patient with non-syndromic hearing loss who visited the Otorhinolaryngology Department of the First Affiliated Hospital of Zhengzhou University in June 2023. Phenotypic and genetic analyses were performed on family members, including audiometric tests, whole-exome sequencing, and PCR-Sanger sequencing verification. Audiological assessments comprised pure-tone audiometry, impedance audiometry, auditory brainstem response, and otoacoustic emission tests. Results:The affected individuals in this pedigree have X-linked dominant non-syndromic deafness caused by mutations in the SMPX gene. The proband, along with their mother and maternal grandmother, exhibit varying degrees of sensorineural hearing loss. Whole-exome sequencing revealed a novel pathogenic variant, NM_014332.3: c. 133-2A>C, in the SMPX gene in the proband. Sanger sequencing confirmed that the proband, proband's mother, and grandmother all carried this pathogenic variant. Conclusion:This study reports a novel pathogenic variant in the SMPX gene, providing additional medical evidence for the diagnosis and treatment of X-linked dominant inherited non-syndromic hearing loss. It enriches the mutation spectrum of the SMPX gene.
Humans ; Pedigree ; Mutation ; Phenotype ; Male ; Hearing Loss, Sensorineural/genetics* ; Exome Sequencing ; Female ; Adult ; Hearing Loss/genetics* ; Evoked Potentials, Auditory, Brain Stem ; Muscle Proteins

Objective:The aim of this study is to analyze the clinical characteristics and genetic variants of a late-onset auditory neuropathy pedigree caused by maternally inherited- mitochondrial mutation.Methods:A male proband who presented with bilateral sensorineural hearing loss at Henan Children′s Hospital in September 2023 was chosen, along with his family members (4 generations, 20 individuals) as the study subjects. Data from this pedigree were collected, organized, and analyzed for clinical genetic characteristics. Medical histories were obtained from family members, pedigree charts were drawn, audiological, imaging, and physical examinations were conducted. Pathogenic genes and mutations were screened using high-throughput sequencing. Sanger sequencing was employed for variant confirmation and segregation validation in the family.Results:In this family, a total of 12 members (10 members collected) had sensorineural hearing loss, characterized by late-onset hearing impairment with an onset age ranging from 9 to 30 years. The patients exhibited poor speech recognition rates, and audiometric examinations are consistent with auditory neuropathy. There was no history of ototoxic drug use. High-throughput sequencing identified the variant NC_012920.1:m.7471dup in the mitochondrial MT-TS1 gene as the pathogenic variant. Sanger sequencing results confirmed that the pathogenic gene mutation site perfectly co-segregated with the auditory neuropathy phenotype in this family. According to the classification criteria and guidelines for genetic variations by the American College of Medical Genetics and Genomics, the variant was classified as a pathogenic mutation. Conclusion:The mitochondrial MT-TS1 gene mutation m.7471dup is considered to be the pathogenic cause in this late-onset auditory neuropathy pedigree.

Objective:To evaluate the role of whole exome sequencing（WES）in the etiological diagnosis and precision medicine management of patients with urolithiasis.Methods:We conducted a retrospective review of 21 patients with urolithiasis and pathogenic gene mutations identified by WES at The Second Affiliated Hospital of Zhengzhou University between April 2019 and March 2025. The cohort included 13 males and 8 females，with a mean age of（18.9 ± 11.1）years；18 patients were under 25 years old. Clinical presentations included nephrocalcinosis（8 patients）and urinary tract calculi（13 patients），with five patients exhibiting extra-renal manifestations such as renal tubular acidosis and hyperaldosteronism. Stone composition analysis identified calcium oxalate（16 patients），cystine（4 patients），and carbonate apatite（1 patient）. Metabolic abnormalities were prevalent，including hypocitraturia（11 patients），hyperoxaluria（8 patients），and hypercalciuria（7 patients），with eight patients presenting two or more concurrent disorders. All patients underwent WES and comprehensive metabolic evaluation. Sequencing was performed on an Illumina Hiseq4000 platform，achieving a mean depth of > 100× and coverage of > 98% in target regions. Variants were classified according to the American College of Medical Genetics and Genomics（ACMG）guidelines.Results:WES identified 12 distinct genes across autosomal recessive（9 genes： AGXT， GRHPR， ATP6V1B1， SLC12A1， KCNJ1， SLC3A1， SLC7A9， SLC34A3， WFS1），autosomal dominant（2 genes： CASR， ADCY10），and X-linked recessive（1 gene： CLCN5）inheritance patterns. Genotype-phenotype correlations revealed mutations associated with primary hyperoxaluria（8 patients），hypercalciuria（7 patients），and renal malformation due to a WFS1 mutation（1 patient）. A positive genetic diagnosis was achieved in 100% of patients with either urinary oxalate > 1 000 μmol/24 h or cystine stones. 8 patients received a diagnosis of hereditary stone disease at their first presentation（non-delayed group），while 13 experienced a mean diagnostic delay of（9.6 ± 3.9）years. The delayed diagnosis group had a significantly older age at initial stone onset［（10.2 ± 5.3）years vs.（6.8 ± 3.1）years， P = 0.03］and a higher incidence of impaired renal function（6 patients vs. 1 patient， P = 0.04）. Analysis of diagnostic delay by gene subgroup showed delays in 2/4 patients with cystinuria［ SLC3A1/ SLC7A9；（8.2 ± 3.5）years］，5/8 with primary hyperoxaluria［ AGXT/ GRHPR；（10.5 ± 4.1）years］，5/7 with hypercalciuria-related genes［ CASR/ ADCY10/ SLC12A1/ KCNJ1/ SLC34A3；（9.8 ± 3.8）years］，and 1/2 with other genes［ ATP6V1B1/ WFS1/ CLCN5；（7.6 ± 2.2）years］. Among 32 mutation sites detected，21 were classified as pathogenic/likely pathogenic and 11 as variants of uncertain significance. Four novel mutations were identified： ATP6V1B1（presenting with renal tubular acidosis，nephrocalcinosis，and hypocitraturia）， WFS1（presenting with renal malrotation，hydronephrosis，and stones without metabolic abnormalities）， SLC12A1（presenting with Bartter syndrome type 1，chronic renal insufficiency，hypercalciuria，hypocitraturia，alkalosis，and hyperaldosteronism），and SLC3A1（presenting with bilateral renal stones and cystinuria）. Conclusions:WES is crucial in identifying the underlying etiology of urolithiasis and can guide targeted treatment. We recommend early WES for patients with an initial stone presentation before age 25，those with nephrocalcinosis，or those with abnormal metabolic workups to facilitate precise diagnosis and preventive care.

Multiple sclerosis(MS)is a complex autoimmune disorder characterized by inflammatory demyelination in the central nervous system.Prominent symptoms include damage to myelin sheaths in the brain,optic nerve,and spinal cord,as well as axonal dysfunction;however,the exact causes and mechanisms of MS remain unclear.Genetic and environmental factors are thought to interact via autoimmune mechanisms,potentially triggering the disease.Recent studies suggest that abnormal activation of the NOD-like receptor thermal protein domain associated protein 3(NLRP3)inflammasome may play a critical role in the pathogenesis of MS.In this context,this review summarizes the molecular mechanisms underlying NLRP3 activation and its connection to MS,considering relevant literature from the past decade.The findings aim to provide insights into the progression of MS and to identify potential therapeutic strategies by elucidating the underlying mechanisms.

Multiple sclerosis(MS)is a complex autoimmune disorder characterized by inflammatory demyelination in the central nervous system.Prominent symptoms include damage to myelin sheaths in the brain,optic nerve,and spinal cord,as well as axonal dysfunction;however,the exact causes and mechanisms of MS remain unclear.Genetic and environmental factors are thought to interact via autoimmune mechanisms,potentially triggering the disease.Recent studies suggest that abnormal activation of the NOD-like receptor thermal protein domain associated protein 3(NLRP3)inflammasome may play a critical role in the pathogenesis of MS.In this context,this review summarizes the molecular mechanisms underlying NLRP3 activation and its connection to MS,considering relevant literature from the past decade.The findings aim to provide insights into the progression of MS and to identify potential therapeutic strategies by elucidating the underlying mechanisms.

Objective:To evaluate the role of whole exome sequencing（WES）in the etiological diagnosis and precision medicine management of patients with urolithiasis.Methods:We conducted a retrospective review of 21 patients with urolithiasis and pathogenic gene mutations identified by WES at The Second Affiliated Hospital of Zhengzhou University between April 2019 and March 2025. The cohort included 13 males and 8 females，with a mean age of（18.9 ± 11.1）years；18 patients were under 25 years old. Clinical presentations included nephrocalcinosis（8 patients）and urinary tract calculi（13 patients），with five patients exhibiting extra-renal manifestations such as renal tubular acidosis and hyperaldosteronism. Stone composition analysis identified calcium oxalate（16 patients），cystine（4 patients），and carbonate apatite（1 patient）. Metabolic abnormalities were prevalent，including hypocitraturia（11 patients），hyperoxaluria（8 patients），and hypercalciuria（7 patients），with eight patients presenting two or more concurrent disorders. All patients underwent WES and comprehensive metabolic evaluation. Sequencing was performed on an Illumina Hiseq4000 platform，achieving a mean depth of > 100× and coverage of > 98% in target regions. Variants were classified according to the American College of Medical Genetics and Genomics（ACMG）guidelines.Results:WES identified 12 distinct genes across autosomal recessive（9 genes： AGXT， GRHPR， ATP6V1B1， SLC12A1， KCNJ1， SLC3A1， SLC7A9， SLC34A3， WFS1），autosomal dominant（2 genes： CASR， ADCY10），and X-linked recessive（1 gene： CLCN5）inheritance patterns. Genotype-phenotype correlations revealed mutations associated with primary hyperoxaluria（8 patients），hypercalciuria（7 patients），and renal malformation due to a WFS1 mutation（1 patient）. A positive genetic diagnosis was achieved in 100% of patients with either urinary oxalate > 1 000 μmol/24 h or cystine stones. 8 patients received a diagnosis of hereditary stone disease at their first presentation（non-delayed group），while 13 experienced a mean diagnostic delay of（9.6 ± 3.9）years. The delayed diagnosis group had a significantly older age at initial stone onset［（10.2 ± 5.3）years vs.（6.8 ± 3.1）years， P = 0.03］and a higher incidence of impaired renal function（6 patients vs. 1 patient， P = 0.04）. Analysis of diagnostic delay by gene subgroup showed delays in 2/4 patients with cystinuria［ SLC3A1/ SLC7A9；（8.2 ± 3.5）years］，5/8 with primary hyperoxaluria［ AGXT/ GRHPR；（10.5 ± 4.1）years］，5/7 with hypercalciuria-related genes［ CASR/ ADCY10/ SLC12A1/ KCNJ1/ SLC34A3；（9.8 ± 3.8）years］，and 1/2 with other genes［ ATP6V1B1/ WFS1/ CLCN5；（7.6 ± 2.2）years］. Among 32 mutation sites detected，21 were classified as pathogenic/likely pathogenic and 11 as variants of uncertain significance. Four novel mutations were identified： ATP6V1B1（presenting with renal tubular acidosis，nephrocalcinosis，and hypocitraturia）， WFS1（presenting with renal malrotation，hydronephrosis，and stones without metabolic abnormalities）， SLC12A1（presenting with Bartter syndrome type 1，chronic renal insufficiency，hypercalciuria，hypocitraturia，alkalosis，and hyperaldosteronism），and SLC3A1（presenting with bilateral renal stones and cystinuria）. Conclusions:WES is crucial in identifying the underlying etiology of urolithiasis and can guide targeted treatment. We recommend early WES for patients with an initial stone presentation before age 25，those with nephrocalcinosis，or those with abnormal metabolic workups to facilitate precise diagnosis and preventive care.

Objective:The aim of this study is to analyze the clinical characteristics and genetic variants of a late-onset auditory neuropathy pedigree caused by maternally inherited- mitochondrial mutation.Methods:A male proband who presented with bilateral sensorineural hearing loss at Henan Children′s Hospital in September 2023 was chosen, along with his family members (4 generations, 20 individuals) as the study subjects. Data from this pedigree were collected, organized, and analyzed for clinical genetic characteristics. Medical histories were obtained from family members, pedigree charts were drawn, audiological, imaging, and physical examinations were conducted. Pathogenic genes and mutations were screened using high-throughput sequencing. Sanger sequencing was employed for variant confirmation and segregation validation in the family.Results:In this family, a total of 12 members (10 members collected) had sensorineural hearing loss, characterized by late-onset hearing impairment with an onset age ranging from 9 to 30 years. The patients exhibited poor speech recognition rates, and audiometric examinations are consistent with auditory neuropathy. There was no history of ototoxic drug use. High-throughput sequencing identified the variant NC_012920.1:m.7471dup in the mitochondrial MT-TS1 gene as the pathogenic variant. Sanger sequencing results confirmed that the pathogenic gene mutation site perfectly co-segregated with the auditory neuropathy phenotype in this family. According to the classification criteria and guidelines for genetic variations by the American College of Medical Genetics and Genomics, the variant was classified as a pathogenic mutation. Conclusion:The mitochondrial MT-TS1 gene mutation m.7471dup is considered to be the pathogenic cause in this late-onset auditory neuropathy pedigree.

To accurately capture and effectively integrate the spatiotemporal features of electroencephalogram (EEG) signals for the purpose of improving the accuracy of EEG-based emotion recognition, this paper proposes a new method combining independent component analysis-recurrence plot with an improved EfficientNet version 2 (EfficientNetV2). First, independent component analysis is used to extract independent components containing spatial information from key channels of the EEG signals. These components are then converted into two-dimensional images using recurrence plot to better extract emotional features from the temporal information. Finally, the two-dimensional images are input into an improved EfficientNetV2, which incorporates a global attention mechanism and a triplet attention mechanism, and the emotion classification is output by the fully connected layer. To validate the effectiveness of the proposed method, this study conducts comparative experiments, channel selection experiments and ablation experiments based on the Shanghai Jiao Tong University Emotion Electroencephalogram Dataset (SEED). The results demonstrate that the average recognition accuracy of our method is 96.77%, which is significantly superior to existing methods, offering a novel perspective for research on EEG-based emotion recognition.
Electroencephalography/methods* ; Emotions ; Humans ; Signal Processing, Computer-Assisted ; Principal Component Analysis ; Algorithms ; Convolutional Neural Networks

Background::Growth retardation is a common complication of chronic kidney disease in children, which can be partially relieved after renal transplantation. This study aimed to develop and validate a predictive model for growth patterns of children with end-stage renal disease (ESRD) after kidney transplantation using machine learning algorithms based on genomic and clinical variables.Methods::A retrospective cohort of 110 children who received kidney transplants between May 2013 and September 2021 at the First Affiliated Hospital of Zhengzhou University were recruited for whole-exome sequencing (WES), and another 39 children who underwent transplant from October 2021 to March 2022 were enrolled for external validation. Based on previous studies, we comprehensively collected 729 height-related single-nucleotide polymorphisms (SNPs) in exon regions. Seven machine learning algorithms and 10-fold cross-validation analysis were employed for model construction.Results::The 110 children were divided into two groups according to change in height-for-age Z-score. After univariate analysis, age and 19 SNPs were incorporated into the model and validated. The random forest model showed the best prediction efficacy with an accuracy of 0.8125 and an area under curve (AUC) of 0.924, and also performed well in the external validation cohort (accuracy, 0.7949; AUC, 0.796). Conclusions::A model with good performance for predicting post-transplant growth patterns in children based on SNPs and clinical variables was constructed and validated using machine learning algorithms. The model is expected to guide clinicians in the management of children after renal transplantation, including the use of growth hormone, glucocorticoid withdrawal, and nutritional supplementation, to alleviate growth retardation in children with ESRD.

Objective:To investigate the computed tomography (CT)-based integrated deep learning model for qualitative and quantitative classification of hepatic portal vein.Methods:The retrospective study was conducted. The CT imaging data of 291 patients undergoing upper-abdomen enhanced CT examination in the Beijing Tsinghua Changgung Hospital of Tsinghua University from October 2017 to January 2019 were collected. There were 195 males and 96 females, aged (51±12)years. The hepatic portal vein was reconstructed using the three-dimensional reconstruction system. Three-dimensional point cloud was input to the encoder model to obtain the three-dimen-sional reconstructed vectorized representation, which was used for qualitative classification and quantitative representation classification. Measurement data with normal distribution were repre-sented as Mean± SD, and comparison between groups was conducted using the paired t test. Count data were repre-sented as percentages or absolute numbers, and comparison between groups was analyzed using the paired chi-square test. Results:(1) Three-dimensional reconstruction of portal vein and anatomical classification. Three-dimensional structure was reconstructed in the 291 patients. Classification of main hepatic portal vein showed 211 cases of Akgul type A, 29 cases of Akgul type B, 16 cases of Akgul type C, 10 cases of Akgul type D, and 25 cases of unclassifiable. (2) Prediction of qualitative classification of main hepatic portal vein. Of the 291 patient samples, 25 unclassifiable or poor quality samples were excluded, 266 samples were used for automated qualitative classification of the main portal vein by machine model. There were 211 cases of Akgul type A, 29 cases of Akgul type B, 26 cases of Akgul type C&D. The Macro-F1 of 266 patients was 61.93%±40.50% and the accuracy was 84.99%, versus 32.38%±19.81% and 61.65% of Random classifier, showing significant differ-ences between them ( t=7.85, χ2=62.89, P<0.05). (3) Quantitative representation of portal vein classification. The probabilities of quantitative classification for Akgul qualitative classification of similar samples included P@1 as 73%±45%, P@3 as 70%±37%, P@5 as 69%±35%, P@10 as 67%± 32%, mean reciprocal rank(MRR) as 80%±34%, versus 57%±50%, 58%±35%, 58%±32%, 58%± 30%, 70%±37% of the baseline model, showing significant differences between the two analytical methods ( t=5.22, 5.11, 5.00, 4.99, 3.47, P<0.05). Conclusion:The automated classification model for the hepatic portal vein structure was constructed using CT-based three-dimensional reconstruc-tion and deep learning technology, which can achieve automatic qualitative classification and quanti-tatively describe the hepatic portal vein structure.