Objective:This study aimed to analyze the prognostic risk factors for hepatoid adenocarcinoma of the stomach (HAS) and construct two nomogram-based clinical prediction models to predict overall survival (OS) and recurrence-free survival (RFS) in patients with HAS.Methods:Data were retrospectively collected from 82 patients (64 males, 18 females; mean age 60.3 ± 9.4 years) who underwent radical gastrectomy and were pathologically diagnosed with gastric hepatoid adenocarcinoma at the First Medical Center of the PLA General Hospital between February 2006 and September 2023. Statistical analyses were conducted using SPSS 25.0 and R 4.3.2. Survival analyses were performed using the Kaplan-Meier method, and univariate analyses were used to identify clinical and pathological factors associated with prognosis. Variables with P<0.05 in the univariate analysis were included in multivariate Cox regression models to identify independent risk factors for OS and RFS. These factors were incorporated into the prediction models to construct nomograms. The discriminatory power of the models was assessed using the area under the curve (AUC) of receiver operating characteristic (ROC) analyses, while calibration curves, decision curve analysis (DCA), and comparisons with the 8th edition of the TNM staging system of the American Joint Committee on Cancer (AJCC) were employed to evaluate model performance. Results:Among the 82 patients, 36 (43.9%) exhibited vascular infiltration, 61 (74.4%) had nerve infiltration, and lymph node metastasis was observed in 60 cases (73.2%). Pathological stages I, II, III, and IV were distributed as 11 (13.4%), 26 (31.7%), 44 (53.7%), and 1 (1.2%) cases, respectively. Inflammatory markers included neutrophil-to-lymphocyte ratio (NLR) ≥ 4.33 in 22 cases (26.8%), platelet-to-lymphocyte ratio (PLR) ≥ 142.2 in 50 cases (61.0%), monocyte-to-lymphocyte ratio (MLR) ≥ 0.411 in 22 cases (26.8%), α-fetoprotein (AFP) ≥ 2.48 μg/L in 64 cases (78.0%), and C-reactive protein (CRP) ≥ 7.506 mg/L in 12 cases (14.6%). Among the 82 patients, 3 cases (3.6%) were lost to follow-up. The median follow-up time was 52 (range: 8–147) months, with a median OS of 61(2–147) months. The 1-year and 3-year OS rates were 78.5% and 58.5%, respectively, while the 1-year and 3-year RFS rates were 77.3% and 60.3%, respectively. Multivariate analysis identified several independent risk factors influencing OS in patients with HAS: advanced pathological stage, MLR ≥ 0.411, AFP ≥ 2.545 μg/L, and CRP ≥ 7.51 mg/L. The hazard ratios (HRs) and 95% confidence intervals (CIs) were as follows: 5.218 (1.230–22.143), 2.610 (1.287–5.294), 2.950 (1.013–8.589), and 2.594 (1.145–5.877), respectively (all P < 0.05). For RFS, advanced pathological stage, PLR ≥ 152.0, and MLR ≥ 0.411 were independent risk factors, with HRs (95% CIs) of 4.735 (1.080–20.760), 3.759 (1.259–11.226), and 2.714 (1.218–6.048), respectively (all P < 0.05). The AUC values for OS prediction at 1 year, 3 years, and 5 years were 0.7765, 0.7525, and 0.7702, respectively. For RFS, the AUC values were 0.7304, 0.8137, and 0.8307 at 1 year, 3 years, and 5 years, respectively. The calibration curves demonstrated strong agreement between nomogram- predicted outcomes and observed survival data. DCA indicated that both TNM staging and the nomogram-based clinical prediction models provided a net positive benefit in predicting OS and RFS in HAS patients, with the nomogram model demonstrating superior performance. Conclusion:The nomogram-based clinical prediction models developed in this study demonstrated robust performance in predicting long-term OS and RFS in patients with HAS.

Objective To investigate the auditory effects of cochlear implantation in quiet and noisy environ-ments in children with different bilateral intervention modes,as well as the factors influencing these effects.Methods A total of 185 children with bilateral severe to profound sensorineural hearing loss were divided into three groups:bimodal hearing mode group(BIM,n=55),simultaneous bilateral cochlear implantation group(SCI,n=70),and sequential bilateral cochlear implantation group(SBCI,n=60).The Parents' Evaluation of Aural/Oral Performance of Children(PEACH)was used to assess the PEACH scores of the three groups in quiet and noisy environments one year after binaural hearing aid intervention.Additionally,the effects of cochlear implantation age,preoperative residual hearing,hearing aid usage,rehabilitation training mode,family system,and other factors on auditory per-formance in quiet and noisy environments were analyzed.Results The PEACH scores in quiet environments were higher than those in noisy environments for all three groups(all P＜0.05).The SCI group had higher PEACH scores in both quiet and noisy environments compared to the BIM group(P＜0.05).Multifactorial analysis revealed differences in factors influencing auditory performance in quiet and noisy environments among the three groups.First cochlear implantation before 3 years of age,preoperative hearing aid usage,and home-based rehabilitation training mode were common favourable influencing factors for auditory performance in both environments.Preopera-tive residual hearing below 95 dB HL was an favourable influencing factor for auditory performance in quiet environ-ments in the BIM group.The higher the level of parental education,the better auditory performance in both quiet and noisy environments for the SCI and SBCI groups.Implantation interval of 24 months or less and hearing aid usage during the inter-implantation period were favourable influencing factors for auditory performance in both envi-ronments for the SBCI group.Conclusion Children with severe to profound prelingual deafness after simultaneous bilateral CI implantation had better hearing performance than bimodal listening in quiet and noise environments.Ear-ly implantation,preoperative or inter-implantation hearing aid usage are recommended to improve auditory perform-ance in noisy environments,regardless of the bilateral intervention mode.The interval between bilateral cochlear im-plantations should be less than 12 months.

Objective:To explore the neuropathological characteristics of brain tissues from autopsy of patients with schizophrenia.Methods:Forty-two autopsy cases from National Human Brain Bank for Health and Disease, School of Medicine, Zhejiang University from January 2013 to December 2024 were selected as research subjects, among which, 21 were schizophrenia patients(schizophrenia group) and 21 were non-schizophrenia patients (non-schizophrenia group). Clinical data of patients from the two groups were compared. HE staining was used to detect the pathological changes such as infarction, hemorrhage and arteriosclerosis in the brain tissues, silver-nitrate staining was used to detect the amyloid plaques in the brain tissues, Congo red staining was used to detect the pathological changes related to cerebral amyloid angiopathy (CAA) in the brain tissues, modified Gallyas silver staining was used to detect the neurofibrillary tangles in the brain tissues, and immunohistochemical staining was used to detect the expressions of phosphorylated tau protein, β-amyloid protein (Aβ), TAR DNA binding protein 43 (TDP-43), and α-synuclein in the brain tissues. Alzheimer's disease neuropathologic change (ADNC), primary age-related tauopathy (PART), limbic-predominant age-related TDP-43 encephalopathy (LATE), aging-related tau astrogliopathy (ARTAG), Lewy body disease (LBD), and cerebrovascular disease (CVD)-related pathological changes in the brain tissues were evaluated, and differences in positive rates of the above pathological changes were compared.Results:No significant difference in gender, age of death, brain weight, or apolipoprotein E genotype was noted between the schizophrenia group and non-schizophrenia group ( P>0.05). Six schizophrenia patients exhibited low-to-intermediate ADNC, including 4 with low ADNC and 2 with intermediate ADNC. Compared with the non-schizophrenia group, the positive rates of ADNC- and CVD-related pathological changes in the schizophrenia group were significantly higher (0 vs. 28.6%; 9.5% vs. 47.6%, P<0.05). No significant differences in positive rates of PART-, LATE-, ARTAG-, and LBD-related pathological changes were noted between the schizophrenia group and non-schizophrenia group ( P>0.05). Conclusion:Schizophrenia patients show high proportions of ADNC- and CVD-related pathological changes, but relatively low ADNC severity.

Objective To investigate the auditory effects of cochlear implantation in quiet and noisy environ-ments in children with different bilateral intervention modes,as well as the factors influencing these effects.Methods A total of 185 children with bilateral severe to profound sensorineural hearing loss were divided into three groups:bimodal hearing mode group(BIM,n=55),simultaneous bilateral cochlear implantation group(SCI,n=70),and sequential bilateral cochlear implantation group(SBCI,n=60).The Parents' Evaluation of Aural/Oral Performance of Children(PEACH)was used to assess the PEACH scores of the three groups in quiet and noisy environments one year after binaural hearing aid intervention.Additionally,the effects of cochlear implantation age,preoperative residual hearing,hearing aid usage,rehabilitation training mode,family system,and other factors on auditory per-formance in quiet and noisy environments were analyzed.Results The PEACH scores in quiet environments were higher than those in noisy environments for all three groups(all P＜0.05).The SCI group had higher PEACH scores in both quiet and noisy environments compared to the BIM group(P＜0.05).Multifactorial analysis revealed differences in factors influencing auditory performance in quiet and noisy environments among the three groups.First cochlear implantation before 3 years of age,preoperative hearing aid usage,and home-based rehabilitation training mode were common favourable influencing factors for auditory performance in both environments.Preopera-tive residual hearing below 95 dB HL was an favourable influencing factor for auditory performance in quiet environ-ments in the BIM group.The higher the level of parental education,the better auditory performance in both quiet and noisy environments for the SCI and SBCI groups.Implantation interval of 24 months or less and hearing aid usage during the inter-implantation period were favourable influencing factors for auditory performance in both envi-ronments for the SBCI group.Conclusion Children with severe to profound prelingual deafness after simultaneous bilateral CI implantation had better hearing performance than bimodal listening in quiet and noise environments.Ear-ly implantation,preoperative or inter-implantation hearing aid usage are recommended to improve auditory perform-ance in noisy environments,regardless of the bilateral intervention mode.The interval between bilateral cochlear im-plantations should be less than 12 months.

Objective:This study aimed to analyze the prognostic risk factors for hepatoid adenocarcinoma of the stomach (HAS) and construct two nomogram-based clinical prediction models to predict overall survival (OS) and recurrence-free survival (RFS) in patients with HAS.Methods:Data were retrospectively collected from 82 patients (64 males, 18 females; mean age 60.3 ± 9.4 years) who underwent radical gastrectomy and were pathologically diagnosed with gastric hepatoid adenocarcinoma at the First Medical Center of the PLA General Hospital between February 2006 and September 2023. Statistical analyses were conducted using SPSS 25.0 and R 4.3.2. Survival analyses were performed using the Kaplan-Meier method, and univariate analyses were used to identify clinical and pathological factors associated with prognosis. Variables with P<0.05 in the univariate analysis were included in multivariate Cox regression models to identify independent risk factors for OS and RFS. These factors were incorporated into the prediction models to construct nomograms. The discriminatory power of the models was assessed using the area under the curve (AUC) of receiver operating characteristic (ROC) analyses, while calibration curves, decision curve analysis (DCA), and comparisons with the 8th edition of the TNM staging system of the American Joint Committee on Cancer (AJCC) were employed to evaluate model performance. Results:Among the 82 patients, 36 (43.9%) exhibited vascular infiltration, 61 (74.4%) had nerve infiltration, and lymph node metastasis was observed in 60 cases (73.2%). Pathological stages I, II, III, and IV were distributed as 11 (13.4%), 26 (31.7%), 44 (53.7%), and 1 (1.2%) cases, respectively. Inflammatory markers included neutrophil-to-lymphocyte ratio (NLR) ≥ 4.33 in 22 cases (26.8%), platelet-to-lymphocyte ratio (PLR) ≥ 142.2 in 50 cases (61.0%), monocyte-to-lymphocyte ratio (MLR) ≥ 0.411 in 22 cases (26.8%), α-fetoprotein (AFP) ≥ 2.48 μg/L in 64 cases (78.0%), and C-reactive protein (CRP) ≥ 7.506 mg/L in 12 cases (14.6%). Among the 82 patients, 3 cases (3.6%) were lost to follow-up. The median follow-up time was 52 (range: 8–147) months, with a median OS of 61(2–147) months. The 1-year and 3-year OS rates were 78.5% and 58.5%, respectively, while the 1-year and 3-year RFS rates were 77.3% and 60.3%, respectively. Multivariate analysis identified several independent risk factors influencing OS in patients with HAS: advanced pathological stage, MLR ≥ 0.411, AFP ≥ 2.545 μg/L, and CRP ≥ 7.51 mg/L. The hazard ratios (HRs) and 95% confidence intervals (CIs) were as follows: 5.218 (1.230–22.143), 2.610 (1.287–5.294), 2.950 (1.013–8.589), and 2.594 (1.145–5.877), respectively (all P < 0.05). For RFS, advanced pathological stage, PLR ≥ 152.0, and MLR ≥ 0.411 were independent risk factors, with HRs (95% CIs) of 4.735 (1.080–20.760), 3.759 (1.259–11.226), and 2.714 (1.218–6.048), respectively (all P < 0.05). The AUC values for OS prediction at 1 year, 3 years, and 5 years were 0.7765, 0.7525, and 0.7702, respectively. For RFS, the AUC values were 0.7304, 0.8137, and 0.8307 at 1 year, 3 years, and 5 years, respectively. The calibration curves demonstrated strong agreement between nomogram- predicted outcomes and observed survival data. DCA indicated that both TNM staging and the nomogram-based clinical prediction models provided a net positive benefit in predicting OS and RFS in HAS patients, with the nomogram model demonstrating superior performance. Conclusion:The nomogram-based clinical prediction models developed in this study demonstrated robust performance in predicting long-term OS and RFS in patients with HAS.

Objective:To explore the neuropathological characteristics of brain tissues from autopsy of patients with schizophrenia.Methods:Forty-two autopsy cases from National Human Brain Bank for Health and Disease, School of Medicine, Zhejiang University from January 2013 to December 2024 were selected as research subjects, among which, 21 were schizophrenia patients(schizophrenia group) and 21 were non-schizophrenia patients (non-schizophrenia group). Clinical data of patients from the two groups were compared. HE staining was used to detect the pathological changes such as infarction, hemorrhage and arteriosclerosis in the brain tissues, silver-nitrate staining was used to detect the amyloid plaques in the brain tissues, Congo red staining was used to detect the pathological changes related to cerebral amyloid angiopathy (CAA) in the brain tissues, modified Gallyas silver staining was used to detect the neurofibrillary tangles in the brain tissues, and immunohistochemical staining was used to detect the expressions of phosphorylated tau protein, β-amyloid protein (Aβ), TAR DNA binding protein 43 (TDP-43), and α-synuclein in the brain tissues. Alzheimer's disease neuropathologic change (ADNC), primary age-related tauopathy (PART), limbic-predominant age-related TDP-43 encephalopathy (LATE), aging-related tau astrogliopathy (ARTAG), Lewy body disease (LBD), and cerebrovascular disease (CVD)-related pathological changes in the brain tissues were evaluated, and differences in positive rates of the above pathological changes were compared.Results:No significant difference in gender, age of death, brain weight, or apolipoprotein E genotype was noted between the schizophrenia group and non-schizophrenia group ( P>0.05). Six schizophrenia patients exhibited low-to-intermediate ADNC, including 4 with low ADNC and 2 with intermediate ADNC. Compared with the non-schizophrenia group, the positive rates of ADNC- and CVD-related pathological changes in the schizophrenia group were significantly higher (0 vs. 28.6%; 9.5% vs. 47.6%, P<0.05). No significant differences in positive rates of PART-, LATE-, ARTAG-, and LBD-related pathological changes were noted between the schizophrenia group and non-schizophrenia group ( P>0.05). Conclusion:Schizophrenia patients show high proportions of ADNC- and CVD-related pathological changes, but relatively low ADNC severity.

Objective:To evaluate the clinical value of a capillary electrophoresis-based method for gene diagnosis of hyperphenylalaninemia.Methods:In this single-center prospective study, 40 newborns with suspected hyperphenylalaninemia detected by neonatal liquid chromatography-tandem mass spectrometry screening at Nanjing Maternity and Child Health Care Hospital from February 2021 to February 2023 were included, with 22 males, 18 females and a mean age at diagnosis of 21.93 days.Capillary electrophoresis was used to detect 85 variants of the phenylalanine hydroxylase ( PAH) gene in 40 newborns with suspected hyperphenylalaninemia.The PAH gene of undiagnosed patients was further analyzed by Sanger sequencing.The detection rate, sensitivity and specificity of capillary electrophoresis were calculated. Results:Among these 40 newborns with suspected hyperphenylalaninemia, 71 PAH variants were detected by capillary electrophoresis, 32 patients were clearly diagnosed, only 1 pathogenic variant was found in 5 patients, and no pathogenic variant was found in the last 3 patients.Therefore, the detection rate, sensitivity and specificity of capillary electrophoresis for analysis of the PAH gene were 80.00%, 88.75% and 100%, respectively. Conclusions:The capillary electrophoresis-based method can rapidly, efficiently and accurately detect PAH gene variants at lower cost and is a promising gene detection method for hyperphenylalaninemia in clinical practice.

AIM:To identify transcriptional differences between the ocular surface ectoderm(OSE)and surface ectoderm(SE)using RNA-seq, and elucidate the OSE transcriptome landscape and the regulatory networks involved in its development.METHODS:OSE and SE cells were differentiated from human embryonic stem(hES)cells. Differentially expressed genes(DEGs)between OSE and SE were analyzed using RNA-seq. Based on the DEGs, we performed gene ontology(GO)analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis, and protein-protein interaction(PPI)network analysis. Transcription factors(TFs)and hub genes were screened. Subsequently, TF-gene and TF-miRNA regulatory networks were constructed using the NetworkAnalyst platform.RESULTS:A total of 4 182 DEGs were detected between OSE and SE cells, with 2 771 up-regulated and 1 411 down-regulated genes in OSE cells. GO-BP analysis revealed that up-regulated genes in OSE were enriched in the regulation of ion transmembrane transport, axon development, and modulation of chemical synaptic transmission. Down-regulated genes were primarily involved in nuclear division, chromosome segregation, and regulation of cell cycle phase transition. KEGG analysis indicated that up-regulated genes in OSE cells were enriched in signaling pathways such as cocaine addiction, axon guidance, and amphetamine addiction, while down-regulated genes were enriched in proteoglycans in cancer, ECM-receptor interaction, protein digestion and absorption, and cytokine-cytokine receptor interaction. Additionally, compared with SE, 204 TFs(including FOS, EGR1, POU5F1, SOX2, and PAX6)were up-regulated, and 80 TFs(including HAND2, HOXB6, HOXB5, HOXA5, and HOXB8)were down-regulated in OSE cells. Furthermore, we identified 6 up-regulated and 9 down-regulated hub genes in OSE cells, and constructed TF-gene and TF-miRNA regulatory networks based on these hub genes.CONCLUSIONS:The transcriptome characteristics of OSE and SE cells were elucidated through RNA-seq analysis. These findings may provide a novel insight for studies on the development and in vitro directed induction of OSE and corneal epithelial cells.

Objective To evaluate the factors affecting urinary stone detection rate using virtual unenhanced(VUE)images obtained from triphasic dual-energy CT urography(DECTU)based on Logistic regression analysis.Methods For this study,150 patients who had suspected urinary stone and underwent triphasic DECTU were included.The true unenhanced(TUE)images were reconstructed as 120 kVp-like images,and VUE images at the portal venous phase[VUE(VP)]and excretory phase[VUE(EP)]were obtained using iodine removal technique from portal venous and excretory phase DECTU images,respectively.Two readers independently evaluated the above three types of images,and recorded the number of urinary stones,their anatomical locations,and whether there was residual iodine on the VUE images.Stone size and CT number were recorded only on the TUE images.Stone size,CT number,anatomical location,and iodine contrast agent were included in univariate and multivariate Logistic regression analyses to evaluate the factors affecting urinary stone detection rate using VUE images.Thresholds for detecting urinary stones on VUE images were determined using receiver operating characteristics(ROC)analysis.Results We detected 304 stones on TUE images,while the detection rates were 92.4％and 71.4％when using VUE(VP)and VUE(EP)images,respectively.Stone size and CT number were important factors influencing urinary stone detection rate using VUE(VP)and VUE(EP)images(P＜0.01).The area under curve(AUC)of using stone size and CT number for detecting stones using the VUE(VP)images was up to 0.96,and as threshold values,stones with size larger than 3.52 mm and CT number greater than 469 HU were found to have high accuracy.However,the AUC decreased to 0.88 when we combined stone size,CT number and anatomical location using the VUE(EP)images.In addition,different contrast agents did not affect the detection rate of stones on the VUE(EP)images(P=0.57).The stone detection rate in the kidney was significantly lower than those on the VUE(EP)images(P＜0.001).Conclusion VUE(VP)images provide better stone detection.Stone size and CT number have significant impacts on the stone detection rate using VUE images.The lower stone detection rate in the kidney on the VUE(EP)images is related to the residual iodine.