AIM: To investigate the mechanism of Hexue Mingmu Tablets(HXMMT)in improving diabetic retinopathy(DR)based on transcriptomics.METHODS: Zebrafish DR models were established by 3-day glucose induction(130 mmol/L)starting at 3 days post-fertilization(dpf). Larvae were randomized into four groups: control group(CG; aquaculture water), model group(MG; 130 mmol/L glucose), low-dose HXMMT treatment group(L-HX; 130 mmol/L glucose +7.5 mg/L HXMMT), and high-dose HXMMT treatment group(H-HX; 130 mmol/L glucose +75 mg/L HXMMT), with a 3-day intervention period until 6 dpf. The area and length of eyes, and body length of zebrafish were observed by stereomicroscopy, retinal morphology was observed by hematoxylin-eosin staining(HE), and retinal vessel diameter was observed under fluorescence microscope. Differentially expressed genes(DEGs)were identified by RNA-sequencing(RNA-seq)technology to further elucidate the molecular mechanism of HXMMT in improving DR in zebrafish, and the sequencing accuracy was validated through quantitative real-time polymerase chain reaction(qRT-PCR).RESULTS: HE staining demonstrated that the intervention with HXMMT significantly improved the disordered cell arrangement, widened gaps, and thickened inner nuclear layer(INL)in ganglion cell layer GCL); retinal vascular diameter quantification revealed that the retinal vessel diameter of the MG significantly increased compared with the CG, and it was significantly changed after the intervention of HXMMT, with significant efficacy in the H-HX(P<0.05); transcriptomics profiling identified 1 470 reversed DEGs, predominantly enriched in the AMPK signaling pathway, FoxO signaling pathway, retinal developmental processes, and tight junction regulation. Technical validation confirmed strong correlation between qRT-PCR and RNA-seq data(R2=0.8571, P<0.05).CONCLUSION: HXMMT may improve retinal vascular microcirculation disorders in DR by regulating core targets including vsx1, pde6c, arr3a, plk1, fbp1b, foxo1a, pcna, and cdk1, as well as synergistically modulating processes such as retinal development in camera-type eyes, visual perception, microtubule cytoskeletal organization, tight junctions, and the AMPK signaling pathway, Foxo signaling pathway.

AIM: To investigate the relationship between Apelin and δ-like ligand 4(DLL4)expression levels and clinical stage and efficacy in patients with neovascular glaucoma(NVG).METHODS: A total of 96 NVG patients(96 eyes)who were admitted to our hospital from January 2022 to March 2024(NVG group)and 96 cataract patients(96 eyes)who underwent cataract surgery in our hospital during the same period(control group)were selected. NVG patients were divided into stage Ⅰ group(22 eyes), stage Ⅱ group(47 eyes)and stage Ⅲ group(27 eyes)according to the clinical stage; furthermore, patients were divided into ineffective group(20 eyes)and effective group(76 eyes)according to efficacy. Aqueous humor Apelin and DLL4 levels were detected by enzyme-linked immunosorbent assay. The influencing factors of the efficacy in NVG patients were analyzed by multivariate unconditional Logistic regression analysis, the evaluation efficiency of aqueous humor Apelin and DLL4 levels on the efficacy in NVG patients was analyzed by receiver operating characteristic(ROC)curve.RESULTS: Compared with the control group, aqueous humor Apelin and DLL4 levels in the NVG group were increased(all P<0.001). Aqueous humor Apelin and DLL4 levels in the stage Ⅰ, stage Ⅱ and stage Ⅲ groups increased in turn(all P<0.001). The effective rate of 96 NVG patients was 79.2%(76/96). Compared with the effective group, aqueous humor Apelin and DLL4 levels in the ineffective group increased(all P<0.001). Clinical stage III, high intraocular pressure, high Apelin and DLL4 were independent risk factors for ineffective treatment in NVG patients(all P<0.05). The area under the curve of the combined evaluation of aqueous humor Apelin and DLL4 levels in evaluating the efficacy of NVG patients was 0.874, which was greater than 0.790 and 0.786 of aqueous Apelin and DLL4 levels alone(all P<0.05).CONCLUSION: Aqueous humor Apelin and DLL4 levels in NVG patients increase, which relate to the increase of clinical stage and poor efficacy, and the combination of aqueous humor Apelin and DLL4 levels is more effective in evaluating the efficacy of NVG patients.

ObjectiveTo analyze the factors influencing meropenem-related liver injury （MRLI） and to explore their clinical predictive value. MethodsA retrospective case-control study was conducted， and the Chinese Hospital Pharmacovigilance System （CHPS） was used to establish a retrieval scheme. A total of 1 625 hospitalized cases using meropenem from January 2018 to December 2022 were collected. Patients were divided into case group （n=62） and control group （n=1 563） based on the presence or absence of liver injury. Clinical data and laboratory indicators from both groups were collected and analyzed. The t-test was used for comparison of normally distributed continuous data between the two groups， while the Mann-Whitney U test was used for comparison of continuous data not conforming to a normal distribution. The chi-square test was used for comparison of categorical data between the two groups. A multivariate Logistic regression analysis was performed to identify the influencing factors for MRLI. A Logistic regression equation was established， and the predictive value of these factors was assessed using the receiver operating characteristic （ROC） curve. ResultsThe results of univariate analysis indicated that the rates of male patients， hypoproteinemia， shock， intensive care unit （ICU） admissions， sepsis， and liver， gallbladder， and cardiovascular diseases， the levels of alanine aminotransferase （ALT）， alkaline phosphatase （ALP）， gamma-glutamyl transpeptidase （GGT）， aspartate aminotransferase （AST）， creatinine （CREA）， and procalcitonin （PCT）， and the number of hospitalization days were significantly higher in the case group than in the control group （P<0.05）， and that the platelet levels in the case group were significantly lower than those in the control group （P<0.05）. The multivariate Logistic regression analysis showed that male sex （odds ratio ［OR］=2.080， 95% confidence interval ［CI］： 1.050 — 4.123， P=0.036）， admission to the ICU （OR=8.207， 95%CI： 4.094‍ ‍—‍ ‍16.453， P<0.001）， comorbidity with gallbladder disease （OR=8.240， 95%CI： 3.605‍ ‍—‍ ‍18.832， P<0.001）， ALP （OR=1.012， 95%CI： 1.004‍ ‍—‍ ‍1.019， P=0.004）， GGT （OR=1.010， 95%CI： 1.005‍ ‍—‍ ‍1.015， P<0.001）， and PLT （OR=0.997， 95%CI： 0.994‍ ‍—‍ ‍0.999， P=0.020） were the influential factors for MRLI. The areas under the ROC curve of ALP， GGT， and PLT were 0.589， 0.637， and 0.595， respectively， and the AUC of them combined was 0.837. ConclusionMale sex， ICU admission， comorbidity with gallbladder disease， increased ALP， increased GGT， and decreased PLT were influencing factors for MRLI， and a combination of factors has a better predictive value for the occurrence of MRLI.

Objective:To investigate key genes and cellular communication involved in spinal cord injury (SCI) repair using transcriptome sequencing and single-cell sequencing analysis.Methods:Two transcriptome sequencing datasets related to SCI and one single-cell sequencing dataset were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in the two transcriptome sequencing datasets were analyzed using the limma package in R, followed by cross-analysis to identify common DEGs. Functional enrichment analysis of DEGs was performed using the DAVID database for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Hub genes in the protein-protein interaction (PPI) network were identified using the cytoHubba plugin in Cytoscape. Single-cell sequencing data were analyzed using the Seurat package in R. Principal Component Analysis (PCA) was applied for dimensionality reduction, and t-distributed Stochastic Neighbor Embedding (t-SNE) was used for visualization. Cellular communication between different cell groups was analyzed using the CellChat package.Results:Differential analysis of transcriptome sequencing data identified 98 common DEGs. GO and KEGG enrichment analysis highlighted biological processes such as wound healing, macrophage activation, and immune response-related cell activation. The PPI network predicted 10 hub genes: ITGAM, TGFB1, CCL2, ICAM1, CD44, FN1, TIMP1, TLR2, ITGB2, and LGALS3. Single-cell sequencing analysis identified six distinct cell populations, including astrocytes, neurons, and fibroblasts. Cellular communication analysis revealed key signaling pathways between cell subpopulations, including SPP1- (ITGAV+ITGB1), SPP1- (ITGA5+ITGB1), TNF-TNFRSF1A transmission pathway, etc.Conclusions:During SCI repair, astrocytes receive signals from fibroblasts, monocytes, and neurons via the SPP1 pathway, while astrocytes and neurons receive signals from monocytes through the TNF pathway. These findings provide critical insights into the molecular mechanisms underlying SCI repair and offer a foundation for future research.

Objective:To investigate key genes and cellular communication involved in spinal cord injury (SCI) repair using transcriptome sequencing and single-cell sequencing analysis.Methods:Two transcriptome sequencing datasets related to SCI and one single-cell sequencing dataset were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in the two transcriptome sequencing datasets were analyzed using the limma package in R, followed by cross-analysis to identify common DEGs. Functional enrichment analysis of DEGs was performed using the DAVID database for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Hub genes in the protein-protein interaction (PPI) network were identified using the cytoHubba plugin in Cytoscape. Single-cell sequencing data were analyzed using the Seurat package in R. Principal Component Analysis (PCA) was applied for dimensionality reduction, and t-distributed Stochastic Neighbor Embedding (t-SNE) was used for visualization. Cellular communication between different cell groups was analyzed using the CellChat package.Results:Differential analysis of transcriptome sequencing data identified 98 common DEGs. GO and KEGG enrichment analysis highlighted biological processes such as wound healing, macrophage activation, and immune response-related cell activation. The PPI network predicted 10 hub genes: ITGAM, TGFB1, CCL2, ICAM1, CD44, FN1, TIMP1, TLR2, ITGB2, and LGALS3. Single-cell sequencing analysis identified six distinct cell populations, including astrocytes, neurons, and fibroblasts. Cellular communication analysis revealed key signaling pathways between cell subpopulations, including SPP1- (ITGAV+ITGB1), SPP1- (ITGA5+ITGB1), TNF-TNFRSF1A transmission pathway, etc.Conclusions:During SCI repair, astrocytes receive signals from fibroblasts, monocytes, and neurons via the SPP1 pathway, while astrocytes and neurons receive signals from monocytes through the TNF pathway. These findings provide critical insights into the molecular mechanisms underlying SCI repair and offer a foundation for future research.

Objective:To explore the clinical manifestations and pathogenic variant in a family with epilepsy, developmental delay and brain deformity.Methods:Clinical data of the child and his family members who had visited the Department of Pediatrics, Linyi People's Hospital on July 2, 2022 were collected. The child, his sister and parents were subjected to high-throughput sequencing, and the result was verified by Sanger sequencing.Results:The child was a 6-year-old boy with developmentally delay and had epileptic seizures with fever sensitivity for four years. Cranial imaging showed brain dysplasia, while the video electroencephalogram showed abnormal discharge. High-throughput sequencing showed the child has harbored a heterozygous c. 5G>T (p.Arg2Leu) variant of TUBB2A gene, which was unreported previously. His sister also carried the variant and had similar clinical manifestations, whilst his parents were of the wild-type and had normal clinical phenotypes. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was classified as pathogenic (PS2+ PM2_Supporting+ PM5+ PP1+ PP2+ PP3). Conclusion:The heterozygous c. 5G>T (p.Arg2Leu) variant of the TUBB2A gene, in the form of gonadal mosaicism, probably underlay the disorders in this family.

Objective:To explore the clinical features and genetic etiology of a child with SPONASTRIME dysplasia (SD).Methods:A 9-month-old female who had presented at the Linyi People′s Hospital in August 2022 for short stature was selected as the study subject. Clinical data of the child were collected, and whole exome sequencing (WES) was carried out. Sanger sequencing was used for validating the candidate variants.Results:The child has manifested short stature, mid-face hypoplasia, joint laxity, internal knee rotation, irregularities in the metaphysis of long bones, and flat and concave lumbar vertebrae. WES revealed that she has harbored compound heterozygous variants of the TONSL gene, namely c.3088G>T (p.Glu1030*) and c. 3053G>A (p.Arg1018His), which were inherited from her phenotypically normal parents. Neither variant was reported previously. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the c. 3088G>T variant was classified as likely pathogenic (PVS1+ PM2_Supporting), whilst the c. 3053G>A was classified as a variant of uncertain significance (PM2_Supporting+ PM3+ PP3). Conclusion:The c. 3088G>T and c. 3053G>A compound heterozygous variants of the TONSL gene probably underlay the pathogenesis in this patient. Above finding has facilitated the clinical diagnosis and genetic counseling for her family.

Objective:To investigate the clinical phenotype and genetic characteristics of developmental epileptic encephalopathy 18 (DEE18) caused by SZT2 gene variants. Methods:Clinical data of 2 children with SZT2 related DEE18 who visited the Department of Pediatric Neurology, Linyi People′s Hospital in March 2020 and July 2023 were collected. The whole exome sequencing (WES) and Sanger sequencing were applied to verify the child and their parents. SWISS-MODEL software was used to perform protein 3D modeling for the selected SZT2 gene variants. Results:Both of the 2 cases showed severe global developmental delay, epileptic seizures, autism, megacephaly, facial deformity, hypotonia, corpus callosum malformation, persistent cavum septum pellucidum, and slow background activity and focal discharge in video electroencephalography. Case 1 was easy to startle and thin in stature; case 2 had immune deficiency and clustered seizures. WES results showed that case 1 carried a compound heterozygous variant of c.5811G>A (p.W1937X) (paternal) and c.9269delG (p.S3090Ifs *94) (maternal), while case 2 carried a compound heterozygous variant of c.6302A>C(p.H2101P) (paternal) and c.7584dupA (p.E2529Rfs *20) (maternal), the parents of both patients with normal clinical phenotypes. The 4 mutations mentioned above were novel variations that had not yet been reported domestically or internationally. According to the American College of Medical Genetics and Genomics variant classification criteria and guidelines, the p.S3090Ifs *94 variant was interpreted as pathogenic; p.W1937X variant was interpreted as pathogenic; p.E2529Rfs *20 variant was interpreted as likely pathogenic; p.H2101P variant was interpreted as uncertain significance. 3D modeling showed that the variant of p.H2101P resulted in a significant change in the hydrogen bond around the 2 101st amino acid encoded, leading to a decrease in protein stability. The other 3 variants led to early truncation of peptide chain and obvious changes in protein structure. Conclusions:DEE18 caused by SZT2 gene mutation is mainly an autosome recessive genetic disease, and its clinical manifestations include global developmental delay, epileptic seizures, autism, craniofacial malformation, hypotonia, epileptic discharge, corpus callosum malformation, persistent cavum septum pellucidum, shock, small and thin stature, and immune deficiency. Four novel variants related to the SZT2 gene may be the genetic etiology of DEE18 patients in this study.

Objective:To analyze the clinical phenotypes and TSC1/TSC2 gene variations in 52 children with tuberous sclerosis complex. Methods:The clinical data of 59 children with tuberous sclerosis complex hospitalized in Linyi People′s Hospital between January 2017 and October 2022 were collected. The analysis of TSC1 and TSC2 gene variations on main family members was performed, and then bioinformatics analysis followed. The positive children were divided into TSC1 gene group and TSC2 gene group, and the difference of clinical characteristics between the two groups was analyzed. Results:Among 59 children, 52 cases were detected TSC1/ TSC2 gene variations (17 cases in the TSC1 gene group and 35 cases in the TSC2 gene group). Of the 52 children, 28 (53.8%) were male, 24 were female (46.2%); 17 (32.7%) were familial cases (10 with TSC1 gene variations and 7 with TSC2 gene variations), 35 (67.3%) were sporadic cases; 46 (88.5%) had hypomelanotic macules, 13 (25.0%) had facial angiofibromas, 5 (9.6%) had shagreen patches, 49 (94.2%) had subependymal nodules/calcifications, 47 (90.4%) had cortical nodules, 2 (3.8%) had subependymal giant cell astrocytomas, 39 (75.0%) had intellectual/developmental disabilities, 49 (94.2%) had epileptic seizures, 8 (15.4%) had cardiac rhabdomyomas, 9 (17.3%) had renal angiomyolipomas, and 4 (7.7%) had retinal hamartomas. Of the 52 children, 49 variations were detected, including 4 large fragment deletion/duplication variations, and 45 point variations; 41 pathogenic variations, 7 likely pathogenic variations, and 1 variation of uncertain significance. In this study, 16 point mutations and 1 large fragment duplication mutation which had not been reported at home and abroad, and 3 high-frequency mutation sites (p.Arg692 *, p.Arg228 *, and p.Arg1200Try) were found. There was a statistically significant difference in the proportion of familial cases [10/17 vs 7/35(20%), χ2=7.838, P=0.005], median onset age of epilepsy [38.0(0.5-134.0) months vs 8.0(0.1-63.0) months, Z=3.506 , P<0.001] and the incidence of developmental retardation/intellectual impairment [8/17 vs 31/35(88.6%), χadj2=8.423, P=0.004] between the TSC1 gene and TSC2 gene groups. Conclusions:Tuberous sclerosis compiex has widespread phenotypes, can affect every body system, especially the skin and nervous system. The pathogenic gene is TSC1/ TSC2. The TSC1 gene group has more familial cases. The TSC2 gene group has an earlier onset age of epilepsy and a higher incidence of developmental retardation/intellectual impairment. In this study, 16 novel point mutations, 1 novel large fragment duplication mutation, and 3 hotspot mutations were identified, expanding the gene variation spectrum of tuberous sclerosis complex.

Objective:To explore the developmental characteristics of event-related potential(ERP) in cognitive function of recognition memory in children aged 6-12.Methods:A total of 130 normal children were divided into seven age groups (6 ( n=20), 7 ( n=17), 8 ( n=23), 9 ( n=24), 10 ( n=19), 11 ( n=15), and 12 years old ( n=12)) to perform a picture study-recognition task and record the reaction time, accuracy, and ERP components of all participants. SPSS 22.0 software was used for data analysis. Single factor analysis of variance and trend of variance were used to compare the response time and accuracy of 7 groups of children during the recognition stage. Pearson correlation analysis was used to study the correlation between the amplitude of the central midline N2 component and age. Paired t-test was used to examine the old/new effects of the amplitude of midfrontal N2 and midparietal P3 waves. Results:(1) The differences of recognition ability ( F(6, 123)=2.476, P<0.05), old picture reaction time ( F(6, 123)=6.461, P<0.001), and new picture reaction time ( F(6, 123)=4.163, P<0.001) among 7 age groups of children were statistically significant. Recognition ability of children aged 6 (0.61±0.24) was lower than those of 8-12 years old children((0.76±0.27), (0.76±0.10), (0.73±0.11), (0.75±0.10), (0.70±0.17) respectively)(all P<0.05). The reaction time of the old picture showed no difference among the children aged 6-9 (all P>0.05), and the reaction time of old picture of children aged 12 was shorter than those of 6-10 years old children (all P<0.01). There was no significant difference in the reaction time of new pictures among the children aged 6-10 (all P>0.05), and which in children aged 12 was shorter than those in 6-10 years old children(all P<0.01). (2) Age was positively correlated with the amplitude of the N2 component in the central region under the new ( r=0.488, P<0.001) and old picture( r=0.452, P<0.001) conditions. (3)At 6 years old, children showed old/new effects on the mid-frontal electrodes. At 7 years old, there were no old/new effects in either the mid-frontal or mid-parietal regions. From 8 to 9 years old, old/new effects appeared in the mid-parietal lobe. At 10 years old, old/new effects were present in both the mid-frontal and mid-parietal regions. At 11 years old, the mid-parietal lobe showed old/new effects. Finally, at 12 years old, negative old/new effects could be observed in both the mid-frontal and mid-parietal regions. Conclusion:There are three periods of changes in the behavior of picture recognition memory in school-age children. At ages 6-7, the accuracy rate is relatively low; at ages 8-9, it improves; and between ages 10-12, the accuracy rate stabilizes while also enabling faster judgments.Children's recognition memory retrieval process is more complex than their behavioral performance. Children have different tendencies toward strategies, but strategic transitions in recognition processing are not always beneficial for performance.