Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Recent data suggest that vascular endothelial growth factor receptor inhibitor (VEGFRi) can enhance the anti-tumor activity of the anti-programmed cell death-1 (anti-PD-1) antibody in colorectal cancer (CRC) with microsatellite stability (MSS). However, the comparison between this combination and standard third-line VEGFRi treatment is not performed, and reliable biomarkers are still lacking. We retrospectively enrolled MSS CRC patients receiving anti-PD-1 antibody plus VEGFRi (combination group, n=54) or VEGFRi alone (VEGFRi group, n=32), and their efficacy and safety were evaluated. We additionally examined the immune characteristics of the MSS CRC tumor microenvironment (TME) through single-cell and spatial transcriptomic data, and an MSS CRC immune cell-related signature (MCICRS) that can be used to predict the clinical outcomes of MSS CRC patients receiving immunotherapy was developed and validated in our in-house cohort. Compared with VEGFRi alone, the combination of anti-PD-1 antibody and VEGFRi exhibited a prolonged survival benefit (median progression-free survival: 4.4 vs. 2.0 months, P=0.0024; median overall survival: 10.2 vs. 5.2 months, P=0.0038) and a similar adverse event incidence. Through single-cell and spatial transcriptomic analysis, we determined ten MSS CRC-enriched immune cell types and their spatial distribution, including naive CD4⁺ T, regulatory CD4⁺ T, CD4⁺ Th17, exhausted CD8⁺ T, cytotoxic CD8⁺ T, proliferated CD8⁺ T, natural killer (NK) cells, plasma, and classical and intermediate monocytes. Based on a systemic meta-analysis and ten machine learning algorithms, we obtained MCICRS, an independent risk factor for the prognosis of MSS CRC patients. Further analyses demonstrated that the low-MCICRS group presented a higher immune cell infiltration and immune-related pathway activation, and hence a significant relation with the superior efficacy of pan-cancer immunotherapy. More importantly, the predictive value of MCICRS in MSS CRC patients receiving immunotherapy was also validated with an in-house cohort. Anti-PD-1 antibody combined with VEGFRi presented an improved clinical benefit in MSS CRC with manageable toxicity. MCICRS could serve as a robust and promising tool to predict clinical outcomes for individual MSS CRC patients receiving immunotherapy.
Humans ; Colorectal Neoplasms/drug therapy* ; Male ; Female ; Immunotherapy ; Middle Aged ; Aged ; Tumor Microenvironment/immunology* ; Retrospective Studies ; Microsatellite Instability ; Transcriptome ; Single-Cell Analysis ; Programmed Cell Death 1 Receptor/immunology* ; Gene Expression Profiling ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; Receptors, Vascular Endothelial Growth Factor/antagonists & inhibitors*

Objective:To investigate the tissue methylation features of adenocarcinoma patients presenting as pulmonary nodules on CT scans.Methods:A retrospective analysis was conducted on 70 adenocarcinoma patients with pulmonary nodules diagnosed at the Shanghai General Hospital from June 1, 2022 to January 20, 2024. Participants were assigned to two groups using the random number table, with 40 in the discovery group and 30 in the validation group. In the discovery group, tissue samples were analyzed using reduced representation bisulfite sequencing (RRBS) technology to compare the average methylation levels between cancer tissues and paired adjacent non-cancerous tissues. Differentially methylated regions (DMRs) were screened for analysis of their distribution across various genomic functional elements, and hierarchical clustering was plotted. GO and KEGG pathway enrichment analyses were further conducted on the DMRs. Subsequently, candidate DMRs associated with lung adenocarcinoma were validated using TCGA lung adenocarcinoma cohort and targeted bisulfite sequencing technology in the validation group. The comparison of methylation levels between groups was conducted using t-tests or non-parametric tests, while rates and composition ratios were analyzed using chi-square tests or Fisher′s exact test.Results:In discovery cohort, the average methylation level in cancer tissues was lower compared to adjacent normal tissues [(42.369±4.627) vs (44.370±4.046), t=?2.059, P=0.043]. A total of 37 995 DMRs were identified, including 16 889 upregulated regions and 21 106 downregulated regions, predominantly locating in promoter regions (48.917%), introns (36.457%), and exons (10.812%). The DMR clustering heatmap revealed two distinct clusters corresponding to cancer tissues and adjacent non-cancerous tissues. GO analysis showed that DMRs associated genes were mainly located in the cell membrane and nuclear chromatin, and were primarily involved in RNA polymerase Ⅱ-related transcription and regulation. KEGG pathway enrichment analysis indicated that DMRs associated genes were mainly involved in neuroactive ligand-receptor interaction, cancer pathways, calcium signaling pathway, cAMP signaling pathway, and MAPK signaling pathway. Validation in the TCGA cohort confirmed 11 potential characteristic DMRs. In the validation group, TBS confirmed that the methylation levels of DMRs associated with MIR10B, DMRTA2, HOPX, TFAP2B and MARCH11 in cancer tissues were significantly higher than those in adjacent non-cancerous tissues [11.200(4.305, 27.088) vs 2.650(1.298, 4.645), Z=?4.539, P<0.05; 18.610(13.600, 33.025) vs 8.675(5.488, 13.085), Z=?4.554, P<0.05; 17.600(2.183, 76.015) vs 1.085(0.898, 1.835), Z=?5.131, P<0.05; 5.250(3.220, 7.693) vs 3.495(2.165, 4.383), Z=?2.861, P<0.05; 11.515(7.525, 21.033) vs 7.830(5.518, 11.488), Z=?2.440, P<0.05 ], and the differences were statistically significant. Conclusions:Lung adenocarcinoma tissue exhibits different methylation patterns compared with adjacent normal lung tissue. The identified DMRs are involved in the regulation of several key pathways. Results from the TCGA cohort and an independent validation group support the potential diagnostic value of DMRs such as MIR10B, DMRTA2, HOPX, TFAP2B, and MARCH11 in lung adenocarcinoma, though their clinical application requires further validation.

Objective:To analyze the relationship between dietary composition of residents in endemic fluorosis areas and skeletal fluorosis.Methods:A case-control study was used to analyze the difference of dietary composition between patients with skeletal fluorosis (case group) and residents without skeletal fluorosis (control group). In August 2019, taking the drinking water-borne endemic fluorosis area in Wenshui County, Lvliang City, Shanxi Province as the survey site, a cluster sampling method was adopted to select local residents aged over 18 years old, and a questionnaire survey was conducted by face-to-face interview. The survey contents included gender, age and consumption frequency of various foods. Binary logistic regression was used to analyze the relationship between food consumption frequency and skeletal fluorosis. The diagnosis of skeletal fluorosis was made by using portable digital radiography (DR) to take X-ray films of forearm and lower leg, combining with clinical signs, and according to the Diagnostic Standard for Endemic Skeletal Fluorosis (WS/T 192-2008) to determine.Results:A total of 1 061 subjects were included in this study, including 376 in the case group and 685 in the control group. The age composition of patients in the case group (≤60, > 60 years old: 162, 214 cases) was significantly different from that in the control group (≤60, > 60 years old: 423, 261 cases, χ 2 = 34.52, P < 0.001). There was no statistically significant difference in gender ratio (χ 2 = 1.37, P = 0.251). The proportion of patients in the case group who ate meat and eggs > 1 time/week was lower than that in the control group (χ 2 = 8.06, 5.46, P < 0.05), the proportion of patients who ate milk > 1 time/week was higher than that in the control group (χ 2 = 4.01, P = 0.046), and the proportion of patients who ate seafood ≥1 time/week was lower than that in the control group (χ 2 = 4.16, P = 0.046). The results of binary logistic regression analysis showed that after adjusting for age, sex, and urinary fluoride, the frequency of eating meat, eggs or milk > 1 time/week and the frequency of eating seafood ≥1 time/week were not related to the risk of skeletal fluorosis ( P > 0.05); however, in the group ≤60 years old, the frequency of eating eggs > 1 time/week was associated with the risk of skeletal fluorosis [odds ratio ( OR) = 0.59, 95% confidence interval ( CI): 0.39, 0.88]. Conclusions:The consumption frequency of meat, milk, eggs and seafood is significantly different between the skeletal fluorosis patients and the control people. In the population ≤60 years old, consumption frequency of eggs > 1 time/week may reduce the risk of skeletal fluorosis.

Osteonecrosis of the femoral head (ONFH) is one of the common and difficult-to-treat orthopedic diseases caused by a variety of factors that lead to abnormal blood flow to the femoral head, which in turn leads to deformation and collapse of the femoral head and eventually results in severe hip joint dysfunction. The key to the treatment is early diagnosis and correct treatment according to the stage classification and active prevention of further aggravation of ONFH aiming to delay or avoid hip replacement surgery in young and middle-aged patients. At present, there are various non-surgical and surgical hip-preserving modalities for early ONFH, designed to slow down the progression of the disease, prevent the femoral head from collapsing and stop the mild collapse. In recent years, with the emergence and development of bone reconstruction biomaterials, artificial bone reconstruction after scraping of ONFH lesions has shown great potential in the treatment of early ONFH. The authors review the research progress in hip-preserving modalities for early ONFH in young and middle-aged patients from non-surgical and surgical perspectives, hoping to provide a reference for clinical treatment of early ONFH.

With the determination of the whole genome sequence of varicella-zoster virus (VZV) virus, the successful breakthrough of infectious cloning technology of VZV, and the emergence of effective preventive vaccines, which have been proven to be effective and safe, varicella has become a disease preventable by specific immunity. This article will review the genomic structure, epidemiological characteristics, and research application progress of varicella vaccine and herpes zoster vaccine of varicella zoster virus to provide reference for primary prevention of the disease.
Humans ; Herpesvirus 3, Human/genetics* ; Herpes Zoster/prevention & control* ; Herpes Zoster Vaccine ; Chickenpox Vaccine ; Genomics

ObjectiveTo analyze the characteristics of death and premature death of 4 major chronic diseases （cardiovascular and cerebrovascular diseases， malignant tumors， chronic respiratory diseases and diabetes） in Taizhou City from 2011 to 2018，and provide data basis for the government to formulate chronic disease prevention planning. MethodsThe death data of household registration residents in Taizhou City from 2011 to 2018 were derived from the Chronic Disease Surveillance Information Management System in Zhejiang Province. The death toll ratio of chronic diseases， the mortality rate of chronic diseases， the probability of premature death of chronic diseases were analyzed. The standardization rate was calculated six times in 2010. Population composition of the census. The Joinpoint Regression Program 4.2 software was used for calculating annual percent change （APC） and its statistical test results. ResultsFrom 2011 to 2018， there were 231 724 chronic disease deaths in Taizhou City， with a mortality rate of 486.52/10⁵ and a standardized mortality rate of 381.55/10⁵. The proportion of chronic disease deaths to total deaths was 79.89%， of which males were higher than females and rural areas were higher than urban areas.From 2011 to 2018， the standardized mortality and early death probability of cardiovascular and cerebrovascular diseases， malignant tumors and chronic respiratory diseases in Taizhou showed a downward trend （P<0.05）， the standardized mortality of diabetes （P=0.46） and the early death probability （P=0.22） did not decline， and the mortality of all age groups of the above four types of chronic diseases in rural areas was higher than that in urban areas. The mortality of the four types of chronic diseases from high to low are cardiovascular and cerebrovascular diseases， malignant tumors， chronic respiratory diseases and diabetes， and the mortality tends to increase with age. From 2011 to 2018， the probability of premature death from four types of chronic diseases in Taizhou City showed a downward trend， from 13.49% in 2011 to 10.49% in 2018， with an average annual decrease of 2.97%. The difference was statistically significant （t=‒5.83，P<0.05）. ConclusionChronic disease death is the main cause of death in Taizhou City. In order to reduce the mortality rate of chronic diseases， effective prevention and control measures for chronic diseases should be carried out， especially the prevention and control of diabetes and male chronic diseases.

Objective:To explore the effect of group cognitive behavior therapy (GCBT) on anxiety, depression and quality of life in patients with chronic obstructive pulmonary disease (COPD) in community.Methods:From August to November 2019, patients with moderate COPD in 18 communities in Xuzhou City were randomly divided into the intervention group ( n=240) and the control group ( n=223). The control group received routine management and the intervention group received group cognitive behavioral therapy intervention for 8 weeks on the basis of routine management.Before and after the intervention, FEV 1% predicted value and FEV 1/FVC were measured by pulmonary function tester.Hospital Anxiety and Depression Scale (HADS) was used to evaluate the anxiety and depression of patients.St.George's respiratory questionnaire (SGRQ), COPD assessment test (CAT) and modified medical research council dyspnea (mMRC) were used to evaluate the quality of life of patients.SPSS 20.0 software was used for analysis.The χ 2 test, independent sample t-test, paired sample t-test were used for statistical analysis. Results:After 8 weeks of intervention, the anxiety and depression scores of the intervention group were lower than those of the control group (anxiety: (8.23±4.02) vs (10.71±3.60); depression: (7.87±3.73) vs (10.20±3.72)( t=6.415, 6.185, both P<0.01). After the intervention, there was no significant difference in FEV 1%((51.7±12.3)% vs (52.0±12.6)%) predicted value and FEV 1/FVC((57.3±10.8)% vs (56.9±10.7)%) between the two groups( t=-0.259, 0.400, both P>0.05). The scores of CAT, mMRC and SGRQ in the intervention group were lower than those in the control group((17.35±5.78) vs (20.90±8.00), (1.55±0.82) vs (2.30±1.21), (41.78±21.56) vs (57.08±24.46))( t=-5.061, -7.227, -6.580, all P<0.01). Conclusion:Group cognitive behavioral therapy can relieve the anxiety and depression and improve the quality of life of patients with COPD.

Background: The influencing factors of diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus (T2DM) were explored to develop and validate a DKD diagnostic tool based on nomogram approach for patients with T2DM. Methods: A total of 2,163 in-hospital patients with diabetes diagnosed from March 2015 to March 2017 were enrolled. Specified logistic regression models were used to screen the factors and establish four different diagnostic tools based on nomogram according to the final included variables. Discrimination and calibration were used to assess the performance of screening tools. Results: Among the 2,163 participants with diabetes (1,227 men and 949 women), 313 patients (194 men and 120 women) were diagnosed with DKD. Four different screening equations (full model, laboratory-based model 1 [LBM1], laboratory-based model 2 [LBM2], and simplified model) showed good discriminations and calibrations. The C-indexes were 0.8450 (95% confidence interval [CI], 0.8202 to 0.8690) for full model, 0.8149 (95% CI, 0.7892 to 0.8405) for LBM1, 0.8171 (95% CI, 0.7912 to 0.8430) for LBM2, and 0.8083 (95% CI, 0.7824 to 0.8342) for simplified model. According to Hosmer-Lemeshow goodness-of-fit test, good agreement between the predicted and observed DKD events in patients with diabetes was observed for full model (χ2=3.2756, P=0.9159), LBM1 (χ2=7.749, P=0.4584), LBM2 (χ2=10.023, P=0.2634), and simplified model (χ2=12.294, P=0.1387). Conclusion LBM1, LBM2, and simplified model exhibited excellent predictive performance and availability and could be recommended for screening DKD cases among Chinese patients with diabetes.

Background: The influencing factors of diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus (T2DM) were explored to develop and validate a DKD diagnostic tool based on nomogram approach for patients with T2DM. Methods: A total of 2,163 in-hospital patients with diabetes diagnosed from March 2015 to March 2017 were enrolled. Specified logistic regression models were used to screen the factors and establish four different diagnostic tools based on nomogram according to the final included variables. Discrimination and calibration were used to assess the performance of screening tools. Results: Among the 2,163 participants with diabetes (1,227 men and 949 women), 313 patients (194 men and 120 women) were diagnosed with DKD. Four different screening equations (full model, laboratory-based model 1 [LBM1], laboratory-based model 2 [LBM2], and simplified model) showed good discriminations and calibrations. The C-indexes were 0.8450 (95% confidence interval [CI], 0.8202 to 0.8690) for full model, 0.8149 (95% CI, 0.7892 to 0.8405) for LBM1, 0.8171 (95% CI, 0.7912 to 0.8430) for LBM2, and 0.8083 (95% CI, 0.7824 to 0.8342) for simplified model. According to Hosmer-Lemeshow goodness-of-fit test, good agreement between the predicted and observed DKD events in patients with diabetes was observed for full model (χ2=3.2756, P=0.9159), LBM1 (χ2=7.749, P=0.4584), LBM2 (χ2=10.023, P=0.2634), and simplified model (χ2=12.294, P=0.1387). Conclusion LBM1, LBM2, and simplified model exhibited excellent predictive performance and availability and could be recommended for screening DKD cases among Chinese patients with diabetes.