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OBJECTIVE: To investigate the prognostic significance of DTA (DNMT3A, TET2, ASXL1 ) gene mutations in patients with non-M3 acute myeloid leukemia (AML). METHODS: The clinical data of 180 newly diagnosed AML patients hospitalized in the First People's Hospital of Changzhou from January 2018 to April 2022 were retrospectively analyzed. Next-generation sequencing technology was used to detect 150 gene mutations in the patients, and log-rank tests and Cox regression models were used to analyze the prognostic factors. RESULTS: DTA gene mutations were detected in 83 (46.1%) of 180 AML patients. Compared to patients without DTA mutations, patients with DTA mutations were significantly older (P < 0.001). The median overall survival (OS) time and disease-free survival (DFS) time in the DTA mutation group were significantly shorter than those in the group without DTA mutation (both P < 0.05). Multivariate analysis showed that age ≥ 60 years (P < 0.001), with DTA mutation (P =0.018), and intermediate-risk (relative to favorable-risk) (P =0.005) were independent risk factors for OS in AML patients. CONCLUSION: AML patients with DTA mutations are relatively older, with shorter median OS time and DFS time, and poor prognosis.
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Dioxigenasas , Leucemia Mieloide Aguda , Mutación , Humanos , Leucemia Mieloide Aguda/genética , Pronóstico , Estudios Retrospectivos , Persona de Mediana Edad , Proteínas de Unión al ADN/genética , Proteínas Represoras/genética , Proteínas Proto-Oncogénicas/genética , ADN Metiltransferasa 3A , ADN (Citosina-5-)-Metiltransferasas/genética , Masculino , Femenino , Supervivencia sin Enfermedad , Secuenciación de Nucleótidos de Alto RendimientoRESUMEN
BACKGROUND: Langerhans cell histiocytosis (LCH) is characterized by diabetes insipidus and is an uncommon occurrence. Pathological biopsies still have a certain degree of diagnostic probability. We present a case in which LCH initially affected the pituitary gland. This resulted in a misdiagnosis of chronic inflammation upon pathological examination. CASE SUMMARY: A 25-year-old female exhibited symptoms of diabetes insipidus. Magnetic resonance imaging revealed an enhanced foci in the pituitary gland. After surgical resection of the pituitary lesion, the pathological diagnosis was chronic inflammation. However, the patient later experienced bone destruction in the skull and lower limb bones. After the lower limb bone lesion was compared with the initial pituitary lesion, the final diagnosis was modified to LCH. The patient was treated with multiple chemotherapy courses. However, the patient's condition gradually worsened, and she eventually passed away at home. CONCLUSION: LCH should be considered when patients exhibit diabetes insipidus and absence of high signal intensity in the pituitary gland on sagittal T1-weighted image and abnormal enhancement in the pituitary region.
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OBJECTIVE: To explore the risk factors affecting the survival and efficacy of patients with acute myeloid leukemia with myelodysplasia-related changes (AML-MRC) transformed from myelodysplastic syndrome (MDS). METHODS: The clinical data of 60 patients with AML-MRC transformed from MDS who hospitalized in The Third Affiliated Hospital of Soochow University from January 2010 to December 2021 were retrospectively analyzed. The demographic data and laboratory parameters, cytogenetic karyotypes, target genes of AML detected by next generation sequence, risk stratification, treatment regimen, therapeutic efficacy and survival outcome were documented. Rank sum test and Chi-square test or Fisher exact test were used to compare the survival and efficacy. The effects of clinical parameters, risk stratification and treatment regimens on the survival and efficacy of the AML-MRC patients were analyzed by univariate and multivariate analysis. RESULTS: The median overall survival (OS) of the AML-MRC patients was 4.5 months, the 1-year OS rate was 28.3%, and the complete remission (CR) rate after treatment was 33.3%. The univariate analysis showed that age≥60 years, leukocytosis, severe thrombocytopenia, poor-risk group and only accepted hypomethylating agents(HMAs) or supportive therapy were the risk factors affecting OS. COX multivariate analysis showed that thrombocytopenia ( HR=4.46), HMAs therapy (compared to transplantation, HR=10.47), supportive therapy (compared to transplantation, HR=25.80) and poor-risk group (compared to medium-risk group, HR=13.86) were independent hazard factors for median OS of patients with AML-MRC. The univariate analysis showed that the risk factors affecting 1-year OS in patients with AML-MRC were age≥60 years, thrombocytopenia, time of transformation from MDS to AML (TTA)≥3 months, fibrinogen-albumin ratio index (FARI)≥0.07, CONUT score≥5, poor-risk group and supportive therapy. Binary logistic regression analysis showed that the independent risk factors for 1-year OS in AML-MRC patients were age≥60 years ( HR=11.23), thrombocytopenia ( HR=8.71), FARI≥0.07 ( HR=5.19) and poor-risk group ( HR=14.00). The risk factors affecting CR of AML-MRC patients in univariate analysis were age≥60 years, thrombocytopenia, FARI≥0.1, CONUT score≥5, poor-risk group and supportive therapy, while binary logistic regression analysis showed that age≥60 years( HR=7.35), CONUT score≥5 ( HR=9.60), thrombocytopenia ( HR=12.05) and poor-risk group ( HR=32.5) were independent risk factors affecting CR of the patients. CONCLUSION: The OS of AML-MRC patients is poor, old age(≥60 years old), supportive therapy, HMA therapy, poor-risk, thrombocytopenia, FARI≥0.07 and CONUT score≥5 may be associated with poor prognosis.
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Leucemia Mieloide Aguda , Síndromes Mielodisplásicos , Humanos , Síndromes Mielodisplásicos/complicaciones , Pronóstico , Tasa de Supervivencia , Factores de Riesgo , Persona de Mediana Edad , Progresión de la Enfermedad , Trombocitopenia/etiología , Femenino , Inducción de Remisión , MasculinoRESUMEN
Diagnosing posttraumatic stress disorder (PTSD) using only single-modality images is controversial. We aimed to use multimodal magnetic resonance imaging (MRI) combining structural, diffusion, and functional MRI to possibly provide a more comprehensive viewpoint on the decisive characteristics of PTSD patients. Typhoon-exposed individuals with (n = 26) and without PTSD (n = 32) and healthy volunteers (n = 30) were enrolled. Five MRI features from three modalities, including two resting-state functional MRI (rs-fMRI) features (amplitude of low-frequency fluctuation, ALFF; and regional homogeneity, ReHo), one structural MRI feature (gray matter density, GM), and two diffusion tensor imaging (DTI) features (fractional anisotropy, FA; and mean diffusivity, MD) were investigated simultaneously with a multimodal canonical correlation analysis + joint independent component analysis model to identify abnormalities in the PTSD brain. We identified statistical differences between PTSD patients and healthy controls in terms of 1 rs-fMRI (ALFF, ReHo) alterations in the superior frontal gyrus, precuneus, inferior parietal lobule (IPL), anterior cingulate cortex (ACC), and posterior cingulate cortex (PCC), 2 DTI (FA, MD) changes in the pons, genu, and splenium of the corpus callosum, and 3 Structural MRI abnormalities in the precuneus, IPL, ACC, and PCC. A novel ReHo component was found to distinguish PTSD and trauma-exposed controls, including the precuneus, IPL, middle frontal gyrus, middle occipital gyrus, and cerebellum. This study reveals that PTSD individuals exhibit intertwined functional and structural anomalies within the default mode network. Some alterations within this network may serve as a potential marker to distinguish between PTSD patients and trauma-exposed controls.
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Tormentas Ciclónicas , Trastornos por Estrés Postraumático , Humanos , Imagen de Difusión Tensora , Trastornos por Estrés Postraumático/patología , Mapeo Encefálico , Encéfalo/patología , Imagen por Resonancia Magnética/métodosRESUMEN
The endophytic fungal diversity of Cirsium kawakamii, a herb indigenous to Taiwan, was analyzed in this study. In addition, some fungal isolates were evaluated for the risk they pose as plant pathogens. In total, 1836 endophytic fungi were isolated from C. kawakamii from Hehuanjian, Puli Township, and Tatachia. They were classified into 2 phyla, 8 classes, 40 families, and 68 genera. Colletotrichum, Fusarium, Phomopsis, and Xylaria, (Ascomycota, Sordariomycetes) were the dominant genera. The genus accumulation curve (based on the bootstrap estimator) was non-asymptotic, with estimated richness significantly exceeding the richness captured by our sampling to date. Considering the collection time, the data indicated significant differences in the proportions of the C. kawakamii endophyte genus from Hehuanjan, Puli Township (across two seasons), and Tatachia. The Shannon and Gini-Simpson indices revealed variations in diversity, with C. kawakamii endophytes (Puli Township in winter) significantly reducing alpha diversity compared with other seasons and locations. Meanwhile, the Gini-Simpson index suggested that there were no significant differences in richness among the four sampling sites. The PCA results unveiled distinct community structures across different locations and seasons, explaining 46.73% of the total variation in fungal community composition significantly affected diversity and richness. In addition, a considerable number of Fusarium isolates exhibited harmful properties towards wheat, potatoes, and apples. It is postulated that these fungi belong to the Fusarium tricinctum species complex (FTSC).
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OBJECTIVE: To explore the clinical characteristics and prognostic factors of patients with primary parotid gland lymphoma, and construct a prognostic model nomogram for patients with primary diffuse large B-cell lymphoma (DLBCL) of parotid gland. METHODS: Primary parotid gland lymphoma and primary DLBCL of parotid gland patients from 1984 to 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analysis were conducted to determine the independent prognostic factors of primary parotid gland lymphoma and primary DLBCL of parotid gland, respectively. According to the established independent prognostic factors of primary DLBCL of parotid gland, nomogram was built to predict 3- and 5-year survival, and the discrimination and calibration of the model were evaluated by concordance index (C-index) and calibration plots. RESULTS: A total of 2 610 patients with primary parotid gland lymphoma were identified. Their median age was 66(15-99) years old, the male to female ratio was 1â¶1.8, and 20.5% of them was primary DLBCL of parotid gland, which was the most common histological subtype in aggressive lymphomas. Multivariate Cox regression analysis showed that sex, age, Ann Arbor stage, years of diagnosis, marital status, histological subtype, surgery, and radiation were the independent prognostic factors of primary parotid gland lymphoma, while age, marital status, surgery, and chemotherapy were the independent prognostic factors of primary DLBCL of parotid gland. The C-index of the prediction model was 0.702(95%CI: 0.696-0.768), reflecting a good discrimination ability. The predicted value probability of the calibration plots was close to the actual value probability, reflecting a good accuracy ability. CONCLUSIONS: Sex, age, Ann Arbor stage, years of diagnosis, marital status, histological subtype, surgery, and radiation were the independent prognostic factors of primary parotid gland lymphoma. The nomogram survival prediction model for primary DLBCL of parotid gland patients can assist clinical decision effectively.
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BACKGROUND: Abnormal white matter has been reported in patients with end-stage renal disease (ESRD). However, few studies have investigated the relationship between specific damage segments and cognition in ESRD. This study aimed to delineate white matter alterations in ESRD and its relationship with cognition. METHODS: A total of 36 patients undergoing hemodialysis and 25 healthy controls underwent diffusion tensor imaging (DTI) and a series of neuropsychiatric tests. Automated fiber quantification was used to extract distinct DTI indices, and the relationship between the specific segment of the white matter and clinical properties was investigated. Furthermore, a support vector machine was applied to differentiate patients with ESRD from healthy controls. RESULTS: Fractional anisotropy values decreased in multiple fiber bundles, including bilateral thalamic radiata, cingulum cingulate, inferior fronto-occipital fasciculus (IFOF), uncinate, Callosum_Forceps_Major/Callosum_Forceps_Minor (CFMaj/CFMin), and left uncinate from the tract level in patients with ESRD. Specific damaged segments were detected in 8 fiber bundles, including bilateral thalamic radiation, cingulum cingulate, IFOF, CFMin, and left corticospinal tract. Few alterations in these fiber bundles were correlated with cognition impairment and hemoglobin levels. The tract profiles of the left thalamic radiata and left cingulum cingulate could be used to differentiate hemodialysis patients from healthy controls, with an accuracy of 76.9% and 67.6%, respectively. CONCLUSIONS: This study revealed white matter damage in hemodialysis patients. This damage occurred in specific segments of the tract, especially in the left thalamic radiata and left cingulum cingulate, which might become a new biomarker for patients with ESRD and cognition impairment.
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Fallo Renal Crónico , Sustancia Blanca , Humanos , Sustancia Blanca/diagnóstico por imagen , Imagen de Difusión Tensora/métodos , Cuerpo Calloso , Diálisis Renal/efectos adversos , Fallo Renal Crónico/complicaciones , Fallo Renal Crónico/diagnóstico por imagen , Fallo Renal Crónico/terapia , Encéfalo/diagnóstico por imagen , AnisotropíaRESUMEN
China has implemented a series of long-term measures to control the spread of COVID-19, however, the effects of these measures on other chronic and acute respiratory infectious diseases remain unclear. Tuberculosis (TB) and scarlet fever (SF) serve as representatives of chronic and acute respiratory infectious diseases, respectively. In China's Guizhou province, an area with a high prevalence of TB and SF, approximately 40,000 TB cases and hundreds of SF cases are reported annually. To assess the impact of COVID-19 prevention and control on TB and SF in Guizhou, the exponential smoothing method was employed to establish a prediction model for analyzing the influence of COVID-19 prevention and control on the number of TB and SF cases. Additionally, spatial aggregation analysis was utilized to describe spatial changes in TB and SF before and after the COVID-19 outbreak. The parameters of the TB and SF prediction models are R2 = 0.856, BIC = 10.972 and R2 = 0.714, BIC = 5.325, respectively. TB and SF cases declined rapidly at the onset of COVID-19 prevention and control measures, with the number of SF cases decreasing for about 3-6 months and the number of TB cases remaining in decline for 7 months after the 11th month. The spatial aggregation of TB and SF did not change significantly before and after the COVID-19 outbreak but exhibited a marked decrease. These findings suggest that China's COVID-19 prevention and control measures also reduced the prevalence of TB and SF in Guizhou. These measures may have a long-term positive impact on TB, but a short-term effect on SF. Areas with high TB prevalence may continue to experience a decline due to the implementation of COVID-19 preventive measures in the future.
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COVID-19 , Enfermedades Transmisibles , Escarlatina , Tuberculosis , Humanos , ChinaRESUMEN
Background: Altered resting-state functional connectivity has been found in patients with post-traumatic stress disorder (PTSD). However, the alteration of resting-state functional connectivity at whole-brain level in typhoon-traumatized individuals with PTSD remains largely unknown. Objectives: To investigate changes in whole-brain resting-state functional connectivity and brain network topology in typhoon-traumatized subjects with and without PTSD. Design: Cross-sectional study. Methods: Twenty-seven patients with typhoon-related PTSD, 33 trauma-exposed controls (TEC), and 30 healthy controls (HC) underwent resting-state functional MRI scanning. The whole brain resting-state functional connectivity network was constructed based on the automated anatomical labeling atlas. The graph theory method was used to analyze the topological properties of the large-scale resting-state functional connectivity network. Whole-brain resting-state functional connectivity and the topological network property were compared by analyzing the variance. Results: There was no significant difference in the area under the curve of γ, λ, σ, global efficiency, and local efficiency among the three groups. The PTSD group showed increased dorsal cingulate cortex (dACC) resting-state functional connectivity with the postcentral gyrus (PoCG) and paracentral lobe and increased nodal betweenness centrality in the precuneus relative to both control groups. Compared with the PTSD and HC groups, the TEC group showed increased resting-state functional connectivity between the hippocampus and PoCG and increased connectivity strength in the putamen. In addition, compared with the HC group, both the PTSD and TEC groups showed increased connectivity strength and nodal efficiency in the insula. Conclusion: Aberrant resting-state functional connectivity and topology were found in all trauma-exposed individuals. These findings broaden our knowledge of the neuropathological mechanisms of PTSD.
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OBJECTIVE: To investigate the biological effects and its relative mechanism of decitabine combined with anlotinib on multiple myeloma cells. METHODS: The human MM cell lines and primary cells were treated with different concentrations of decitabine, anlotinib, and decitabine+anlotinib, respectively. The cell viability was detected and combination effect was calculated by CCK-8 assay. The apoptosis rate was measured by flow cytometry and the level of c-Myc protein was determined by Western blot. RESULTS: Both decitabine and anlotinib could effectively inhibit the proliferation and induce the apoptosis of MM cell lines NCI-H929 and RPMI-8226. The effect of combined treatment on the inhibition of cell proliferation and induction of apoptosis was stronger than that of single-drug treatment. The combination of the two drugs also showed strong cytotoxicity in primary MM cells. Decitabine and anlotinib could down-regulate the level of c-Myc protein in MM cells and the c-Myc level in the combination group was the lowest. CONCLUSION: Decitabine combined with anlotinib can effectively inhibit the proliferation and induce apoptosis of MM cells, which provides a certain experimental basis for the treatment of human MM.
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Mieloma Múltiple , Humanos , Mieloma Múltiple/metabolismo , Decitabina , Línea Celular Tumoral , Apoptosis , Proliferación CelularRESUMEN
OBJECTIVE: To develop and validate artificial intelligence models for the prediction of cognitive impairment in chronic kidney disease (CKD) patients using structural and functional brain network. METHODS: This study retrospectively recruited 621 CKD patients and 625 healthy controls in Jinling hospital and 57 CKD patients in Hainan hospital. These CKD patients were divided into cognitive function impairment (CFI) group and non-CFI group based on diagnostic criteria. All patients underwent brain MRI scan, neuropsychological test and laboratory exam. A deep learning model (Attention MLP) based on structural and functional sub-network (determined by the comparison between the patients and healthy controls) topological properties was developed to generate the MRI signature for the discrimination of CFI. Finally, a clinical-topological logistic regression model was built by combining MRI signature and clinical features. The area under curve (AUC), sensitivity and specificity were calculated to evaluate the model performance. Delong test was used to examine the difference of AUCs between models. The integrated discrimination improvement (IDI) and net reclassification index (NRI) between models were calculated. RESULTS: Attention MLP model performed well in both internal test set and external test set (AUC = 0.744 and 0.763, respectively). After combining with the clinical features, the model performance was further improved both in the internal (AUC: 0.748) and external test sets (AUC: 0.774), while both IDI and NRI were significant (all p < 0.05) in the external test set. According to the comprehensive comparison, the AUC of the Attention MLP model was significantly or marginal significantly higher than that of traditional machine learning models (logistic regression: AUC = 0.634; support vector machine: AUC = 0.613; decision tree: AUC = 0.539; XGBoost: AUC = 0.639) in internal test set. The results showed that the model built on the combining of structural and functional networks data outperformed those on the single network, as well as the connection matrix. CONCLUSION: The result indicated that the integration of the clinical information and the MRI signature generated by artificial intelligence model based on structural and functional network topological properties could help to predict the CFI of CKD patients effectively. Our results provided a set of quantifiable imaging biomarkers for CFI which may be beneficial to CKD patients.
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Inteligencia Artificial , Disfunción Cognitiva , Humanos , Estudios Retrospectivos , Aprendizaje Automático , Encéfalo/diagnóstico por imagen , Disfunción Cognitiva/diagnóstico por imagen , Disfunción Cognitiva/etiologíaRESUMEN
BACKGROUND: Hippocampal alterations have been implicated in the pathophysiology of cognitive impairment in hemodialysis patients. The hippocampus consists of several distinct subfields, and the molecular mechanisms underlying cognition might be associated with specific hippocampal subfield volume changes. However, this has not yet been investigated in hemodialysis patients. This study aimed to explore volumetric abnormalities in hippocampal subfields in regular hemodialysis patients. METHODS: High-resolution T1-weighted structural images were collected in 61 subjects including 36 hemodialysis patients and 25 healthy controls. A state-of-the-art hippocampal segmentation approach was adopted to segment the hippocampal subfields. Group differences in hippocampal subfield volumes were assessed in Python with a statsmodels module using an ordinary least squares regression with age and sex as nuisance effects. RESULTS: Hemodialysis patients had significantly smaller volumes in the bilateral hippocampus (P < .05/2, Bonferroni corrected), cornu ammonis 1 (CA1), CA4, granule cell and molecular layer of the dentate gyrus, hippocampus-amygdala transition area and molecular layer of the hippocampus than healthy controls (P < .05/24, Bonferroni corrected). Hemodialysis patients also had lower volumes in the left hippocampal tail and right fimbria than healthy controls (P < .05/24, Bonferroni corrected). Hippocampal subfield volumes were associated with neuropsychological test scores, the duration of disease and hemoglobin levels. CONCLUSIONS: We found smaller hippocampal subfield volumes in hemodialysis patients, which were associated with impaired cognition, supporting their role in memory disturbance in the hemodialysis population. However, multiple clinical factors may have confounded the results, and therefore, the interpretation of these results needs to be cautious.
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Disfunción Cognitiva , Imagen por Resonancia Magnética , Humanos , Imagen por Resonancia Magnética/métodos , Hipocampo/diagnóstico por imagen , Cognición , Pruebas NeuropsicológicasRESUMEN
This study was designed to explore the potential of gypenosides as a novel natural stabilizer for the production of nanosuspensions. The gypenosides-stabilized quercetin nanosuspensions(QUE-NS) were prepared using the high-speed shearing and high-pressure homogenization method with quercetin as a model drug, followed by their in vitro evaluation.Based on the measured mean particle size and polydispersity index(PDI) of QUE-NS,the single factor experiment was conducted to optimize the preparation process parameters.The freeze-drying method was used to transform QUE-NS into freeze-dried powders, whose storage stability and saturation solubility were then studied.Moreover, the effects of pH and ionic strength on the physical stability of the nanosuspension system were examined.According to the results, the optimized process parameters were listed as follows: shear rate 13 000 r·min~(-1),shear time 2 min, homogenization pressure 100 MPa, and homogenization frequency 12 times.The mean particle size of QUE-NS prepared under the optimum process conditions was(461.9±2.4) nm, and the PDI was 0.059±0.016.During the two months of storage at room temperature, the freeze-dried QUE-NS powders remained stable.The saturation solubility of freeze-dried QUE-NS powders was proved higher than those of quercetin and the physical mixture.The results of stability testing demonstrated that QUE-NS stabilized with gypenosides exhibited good stability within the pH range of 6 to 8,while coalescence was prone to occur in the presence of salt.Overall, gypenosides is expected to become a new natural stabilizer for the preparation of nanosuspensions.
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Nanopartículas , Quercetina , Estabilidad de Medicamentos , Gynostemma , Tamaño de la Partícula , Extractos Vegetales , Polvos , Solubilidad , SuspensionesRESUMEN
Renal fibrosis could lead to chronic kidney disease (CKD) developing into the end-stage with its pathological manifestation is the deposition of extracellular matrix (ECM). Danggui Shaoyao San (DSS) is one of the widely used herbal formulas in ancient China, which has been proven to have efficacy in the treatment of CKD. The experiment employed TGF-ß1 to stimulate the NRK-52E cells to establish a renal fibrosis model. With rapamycin (RAPA) used as the positive control, we detected the expression of fibronectin (FN), caspase-3, and autophagy-related proteins in the NRK-52E cells treated with DSS by Western blot and immunofluorescence assay. In order to further verify autophagy-promoting effects of DSS, we adopted 3-MA to inhibit autophagy. The experiment has found that DSS can lower the protein levels of FN and caspase-3 in the NRK-52E cells induced by TGF-ß1. After TGF-ß1 stimulation, the expression of LC3 II/I and Beclin 1 has decreased, and the protein levels of mTOR and p62 have increased. Consistent with rapamycin, DSS has significantly reduced these effects of TGF-ß1. It has also been found that DSS can increase the expression of LC3 II/I and Beclin 1 proteins and can reduce the level of mTOR in cells treated with 3-MA, suggesting that DSS can promote autophagy. In conclusion, DSS has been proved to reduce the apoptosis and fibrosis of NRK-52E cells induced by TGF-ß1, which may be achieved by promoting autophagy.
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Purpose: This study aimed to examine the relationship between anxiety, depression, sleep quality and health-related quality of life among systemic lupus erythematosus (SLE) patients in China. Patients and Methods: After ethical approval and obtaining participants' informed consent, a cross-sectional study was conducted in The First Affiliated Hospital of Anhui Medical University between October 1, 2021 and January 30, 2022. The data comprised demographic information, number of SLE symptoms, Hospital Anxiety and Depression Scale (HADS), Pittsburgh Sleep Quality Index (PSQI) and Systemic Lupus Erythematosus-Specific Quality of Life Questionnaire (SLEQoL). We performed descriptive statistics, Spearman or Pearson correlations, and multiple linear regression. And Path analysis was performed to examine direct and indirect associations between these variables and health-related quality of life. Results: A total of 580 patients were recruited and 513 met our target criteria. Our final model fitted the data well: goodness-of-fit index (GFI) =0.996; adjusted goodness-of-fit index (AGFI) =0.974; comparative fit index (CFI) =0.998; root mean square error of approximation (RMSEA) =0.043. This model explained 57.3% of the variance on health-related quality of life (HRQoL) in patients with SLE and all the hypothesized paths reached significance (P<0.05). Anxiety, depression, sleep quality, income/family, and number of SLE symptoms were related to health-related quality of life, and anxiety had the most influence on HRQoL (ß=0.561). Conclusion: The study model helps to explain the relation among anxiety, depression, sleep quality and health-related quality of life in patients with SLE. It also suggests that health care professionals should be aware of factors such as anxiety, sleep quality, number of SLE symptoms, and depression in their care for HRQoL of SLE patients.
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[This corrects the article DOI: 10.3389/fpsyt.2021.779878.].
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BACKGROUND: The structural changes recent-onset posttraumatic stress disorder (PTSD) subjects were rarely investigated. This study was to compare temporal and causal relationships of structural changes in recent-onset PTSD with trauma-exposed control (TEC) subjects and non-TEC subjects. METHODS: T1-weighted magnetic resonance images of 27 PTSD, 33 TEC and 30 age- and sex-matched healthy control (HC) subjects were studied. The causal network of structural covariance was used to evaluate the causal relationships of structural changes in PTSD patients. RESULTS: Volumes of bilateral hippocampal and left lingual gyrus were significantly smaller in PTSD patients and TEC subjects than HC subjects. As symptom scores increase, reduction in gray matter volume began in the hippocampus and progressed to the frontal lobe, then to the temporal and occipital cortices (p < 0.05, false discovery rate corrected). The hippocampus might be the primary hub of the directional network and demonstrated positive causal effects on the frontal, temporal and occipital regions (p < 0.05, false discovery rate corrected). The frontal regions, which were identified to be transitional points, projected causal effects to the occipital lobe and temporal regions and received causal effects from the hippocampus (p < 0.05, false discovery rate corrected). CONCLUSIONS: The results offer evidence of localized abnormalities in the bilateral hippocampus and remote abnormalities in multiple temporal and frontal regions in typhoon-exposed PTSD patients.
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Tormentas Ciclónicas , Trastornos por Estrés Postraumático , Corteza Cerebral/patología , Sustancia Gris/diagnóstico por imagen , Sustancia Gris/patología , Hipocampo/diagnóstico por imagen , Hipocampo/patología , Humanos , Imagen por Resonancia Magnética/métodos , Trastornos por Estrés Postraumático/diagnóstico por imagen , Trastornos por Estrés Postraumático/patologíaRESUMEN
Patients with posttraumatic stress disorder (PTSD) might have white matter abnormalities. However, less is known about white matter changes after exposing a specific traumatic event. The purpose of this study was to explore the abnormalities of diffusion in cerebral white matter and its relationship with the clinical symptoms in patients with PTSD by using diffusion tensor imaging (DTI). Diffusion-weighted imaging of the cerebrum was performed in typhoon survivors with (n = 27) and without PTSD (n = 33) and healthy controls (HCs) (n = 30). Differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated among groups using voxel-based analysis of the DTI data. Correlations between diffusion indices and clinical symptoms in patients with PTSD were also assessed. Both patients with PTSD and trauma-exposed control (TEC) group showed increased FA in the anterior limb of the internal capsule, forceps of the corpus callosum, and corona radiata relative to the HC group. Additionally, there was a negative correlation between FA values in the white matter and the clinical symptoms. Trauma exposure may result in disruption of cerebral white matter in individuals with or without PTSD, particularly in the frontal fibers. Aberrant white matter alterations may be associated with the severity of PTSD symptoms.
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BACKGROUND: To develop a machine learning-based CT radiomics model is critical for the accurate diagnosis of the rapid spreading coronavirus disease 2019 (COVID-19). METHODS: In this retrospective study, a total of 326 chest CT exams from 134 patients (63 confirmed COVID-19 patients and 71 non-COVID-19 patients) were collected from January 20 to February 8, 2020. A semi-automatic segmentation procedure was used to delineate the volume of interest (VOI), and radiomic features were extracted. The Support Vector Machine (SVM) model was built on the combination of 4 groups of features, including radiomic features, traditional radiological features, quantifying features, and clinical features. By repeating cross-validation procedure, the performance on the time-independent testing cohort was evaluated by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RESULTS: For the SVM model built on the combination of 4 groups of features (integrated model), the per-exam AUC was 0.925 (95% CI 0.856 to 0.994) for differentiating COVID-19 on the testing cohort, and the sensitivity and specificity were 0.816 (95% CI 0.651 to 0.917) and 0.923 (95% CI 0.621 to 0.996), respectively. As for the SVM models built on radiomic features, radiological features, quantifying features, and clinical features, individually, the AUC on the testing cohort reached 0.765, 0.818, 0.607, and 0.739, respectively, significantly lower than the integrated model, except for the radiomic model. CONCLUSION: The machine learning-based CT radiomics models may accurately classify COVID-19, helping clinicians and radiologists to identify COVID-19 positive cases.