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Inhibiting the expression of spindle appendix cooled coil protein 1 (SPDL1) can slow down disease progression and is related to poor prognosis in patients with esophageal cancer. However, the specific roles and molecular mechanisms of SPDL1 in esophageal squamous cell carcinoma (ESCC) have not been explored yet. The current study aimed to investigate the expression levels of SPDL1 in ESCC via transcriptome analysis using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Moreover, the biological roles, molecular mechanisms, and protein networks involved in SPDL1 were identified using machine learning and bioinformatics. The cell counting kit-8 assay, EdU staining, and transwell assay were used to investigate the effects of inhibiting SPDL1 expression on ESCC cell proliferation, migration, and invasion. Finally, the correlation between the SPDL1 expression and cancer immune infiltrating cells was evaluated by analyzing data from the TCGA database. Results showed that SPDL1 was overexpressed in the ESCC tissues. The SPDL1 expression was related to age in patients with ESCC. The SPDL1 co-expressed genes included those involved in cell division, cell cycle, DNA repair and replication, cell aging, and other processes. The high-risk scores of SPDL1-related long non-coding RNAs were significantly correlated with overall survival and cancer progression in patients with ESCC (P < 0.05). Inhibiting the SPDL1 expression was effective in suppressing the proliferation, migration, and invasion of ESCC TE-1 cells (P < 0.05). The overexpression of SPDL1 was positively correlated with the levels of Th2 and T-helper cells, and was negatively correlated with the levels of plasmacytoid dendritic cells and mast cells. In conclusion, SPDL1 was overexpressed in ESCC and was associated with immune cells. Further, inhibiting the SPDL1 expression could effectively slow down cancer cell growth and migration. SPDL1 is a promising biomarker for treating patients with ESCC. [ABSTRACT FROM AUTHOR]

End-stage kidney disease (ESKD) presents a significant public health challenge, with hemodialysis (HD) remaining one of the most prevalent kidney replacement therapies. Ensuring the longevity and functionality of arteriovenous accesses is challenging for HD patients. Blood flow sound, which contains valuable information, has often been neglected in the past. However, machine learning offers a new approach, leveraging data non-invasively and learning autonomously to match the experience of healthcare professionas. This study aimed to devise a model for detecting arteriovenous grafts (AVGs) stenosis. A smartphone stethoscope was used to record the sound of AVG blood flow at the arterial and venous sides, with each recording lasting one minute. The sound recordings were transformed into mel spectrograms, and a 14-layer convolutional neural network (CNN) was employed to detect stenosis. The CNN comprised six convolution blocks with 3x3 kernel mapping, batch normalization, and rectified linear unit activation function. We applied contrastive learning to train the pre-training audio neural networks model with unlabeled data through self-supervised learning, followed by fine-tuning. In total, 27,406 dialysis session blood flow sounds were documented, including 180 stenosis blood flow sounds. Our proposed framework demonstrated a significant improvement (p<0.05) over training from scratch and a popular pre-trained audio neural networks (PANNs) model, achieving an accuracy of 0.9279, precision of 0.8462, and recall of 0.8077, compared to previous values of 0.8649, 0.7391, and 0.6538. This study illustrates how contrastive learning with unlabeled blood flow sound data can enhance convolutional neural networks for detecting AVG stenosis in HD patients. [ABSTRACT FROM AUTHOR]

BackgroundPatients who are newly screened HIV positive by EIA are lost to follow-up due to complicated HIV testing procedures. Because this is the first step in care, it affects the entire continuum of care. This is a particular concern in rural China.Objective(s)To assess the routine HIV testing completeness and treatment initiation rates at 18 county-level general hospitals in rural Guangxi.MethodsWe reviewed original hospital HIV screening records. Investigators also engaged with hospital leaders and key personnel involved in HIV prevention activities to characterize in detail the routine care practices in place at each county.Results699 newly screened HIV-positive patients between January 1 and June 30, 2013 across the 18 hospitals were included in the study. The proportion of confirmatory testing across the 18 hospitals ranged from 14% to 87% (mean of 43%), and the proportion of newly diagnosed individuals successfully initiated antiretroviral treatment across the hospitals ranged from 3% to 67% (mean of 23%). The average interval within hospitals for individuals to receive the Western Blot (WB) and CD4 test results from HIV positive screening (i.e. achieving testing completion) ranged from 14-116 days (mean of 41.7 days) across the hospitals. The shortest interval from receiving a positive EIA screening test result to receiving WB and CD4 testing and counseling was 0 day and the longest was 260 days.ConclusionThe proportion of patients newly screened HIV positive that completed the necessary testing procedures for HIV confirmation and received ART was very low. Interventions are urgently needed to remove barriers so that HIV patients can have timely access to HIV/AIDS treatment and care in rural China.

BackgroundLate diagnosis of HIV infection is common. We aim to assess the proportion of newly diagnosed HIV cases receiving timely baseline CD4 count testing and the associated factors in China.MethodsData were extracted from the Chinese HIV/AIDS Comprehensive Response Information Management System. Adult patients over 15 years old who had been newly diagnosed with HIV infection in China between 2006 and 2012 were identified. The study cohort comprised individuals who had a measured baseline CD4 count.ResultsAmong 388,496 newly identified HIV cases, the median baseline CD4 count was 294 cells/µl (IQR: 130-454), and over half (N = 130,442, 58.8%) were less than 350 cells/µl. The median baseline CD4 count increased from 221 (IQR: 63-410) in 2006 to 314 (IQR: 159-460) in 2012. A slight majority of patients (N = 221,980, 57.1%) received baseline CD4 count testing within 6 months of diagnosis. The proportion of individuals who received timely baseline CD4 count testing increased significantly from 20.0% in 2006 to 76.9% in 2012. Factors associated with failing to receiving timely CD4 count testing were: being male (OR: 1.17, 95% CI: 1.15-1.19), age 55 years or older (OR:1.03, 95% CI: 1.00-1.06), educational attainment of primary school education or below (OR: 1.30, 95% CI: 1.28-1.32), infection with HIV through injection drug use (OR: 2.07, 95% CI: 2.02-2.12) or sexual contact and injection drug use (OR: 1.87, 95% CI: 1.76-1.99), diagnosis in a hospital (OR: 1.91, 95% CI: 1.88-1.95) or in a detention center (OR: 1.75, 95% CI: 1.70-1.80), and employment as a migrant worker (OR:1.55, 95% CI:1.53-1.58).ConclusionThe proportion of newly identified HIV patients receiving timely baseline CD4 testing has increased significantly in China from 2006-2012. Continued effort is needed for further promotion of early HIV diagnosis and timely baseline CD4 cell count testing.

Volatile profiles yielded from gas chromatography-mass spectrometry (GC-MS) analysis provide abundant information not only for metabolism-related research, but also for chemotaxonomy. To study the chemotaxonomy of Mangshanyegan, its volatile profiles of fruit and leaf and those of 29 other genotypes of Citrus, Poncirus, and Fortunella were subjected to phylogenetic analyses. Results showed that 145 identified (including 64 tentatively identified) and 15 unidentified volatile compounds were detected from their peel oils. The phylogenetic analysis of peel oils based on hierarchical cluster analysis (HCA) demonstrated a good agreement with the Swingle taxonomy system, in which the three genera of Citrus, Poncirus, and Fortunella were almost completely separated. As to Citrus, HCA indicated that Citrophorum, Cephalocitrus, and Sinocitrus fell into three subgroups, respectively. Also, it revealed that Mangshanyegan contain volatile compounds similar to those from pummelo, though it is genetically believed to be a mandarin. These results were further supported by the principal component analysis of the peel oils and the HCA results of volatile profiles of leaves in the study. [ABSTRACT FROM AUTHOR]