Multimodal neuroimaging exploration of the mechanisms of sleep quality deterioration after SARS-CoV-2 Omicron infection.

BACKGROUND: To evaluate the neurological alterations induced by Omicron infection, to compare brain changes in chronic insomnia with those in exacerbated chronic insomnia in Omicron patients, and to examine individuals without insomnia alongside those with new-onset insomnia. METHODS: In this study, a total of 135 participants were recruited between January 11 and May 4, 2023, including 26 patients with chronic insomnia without exacerbation, 24 patients with chronic insomnia with exacerbation, 40 patients with no sleep disorder, and 30 patients with new-onset insomnia after infection with Omicron (a total of 120 participants with different sleep statuses after infection), as well as 15 healthy controls who were never infected with Omicron. Neuropsychiatric data, clinical symptoms, and multimodal magnetic resonance imaging data were collected. The gray matter thickness and T1, T2, proton density, and perivascular space values were analyzed. Associations between changes in multimodal magnetic resonance imaging findings and neuropsychiatric data were evaluated with correlation analyses. RESULTS: Compared with healthy controls, gray matter thickness changes were similar in the patients who have and do not have a history of chronic insomnia groups after infection, including an increase in cortical thickness near the parietal lobe and a reduction in cortical thickness in the frontal, occipital, and medial brain regions. Analyses showed a reduced gray matter thickness in patients with chronic insomnia compared with those with an aggravation of chronic insomnia post-Omicron infection, and a reduction was found in the right medial orbitofrontal region (mean [SD], 2.38 [0.17] vs. 2.67 [0.29] mm; P < 0.001). In the subgroups of Omicron patients experiencing sleep deterioration, patients with a history of chronic insomnia whose insomnia symptoms worsened after infection displayed heightened medial orbitofrontal cortical thickness and increased proton density values in various brain regions. Conversely, patients with good sleep quality who experienced a new onset of insomnia after infection exhibited reduced cortical thickness in pericalcarine regions and decreased proton density values. In new-onset insomnia patients post-Omicron infection, the thickness in the right pericalcarine was negatively correlated with the Self-rating Anxiety Scale (r = - 0.538, P = 0.002, PFDR = 0.004) and Self-rating Depression Scale (r = - 0.406, P = 0.026, PFDR = 0.026) scores. CONCLUSIONS: These findings help us understand the pathophysiological mechanisms involved when Omicron invades the nervous system and induces various forms of insomnia after infection. In the future, we will continue to pay attention to the dynamic changes in the brain related to insomnia caused by Omicron infection.

Microbial bile acid metabolite ameliorates mycophenolate mofetil-induced gastrointestinal toxicity through vitamin D3 receptor.

Mycophenolate mofetil (MMF) is one of the most used immunosuppressive drugs in organ transplantation, but frequent gastrointestinal (GI) side effects through unknown mechanisms limit its clinical use. Gut microbiota and its metabolites were recently reported to play a vital role in MMF-induced GI toxicity, but the specific mechanism of how they interact with the human body is still unclear. Here, we found that secondary bile acids (BAs), as bacterial metabolites, were significantly reduced by MMF administration in the gut of mice. Microbiome data and fecal microbiota transfer model supported a microbiota-dependent effect on the reduction of secondary BAs. Supplementation of the secondary BA lithocholic acid alleviated MMF-induced weight loss, colonic inflammation, and oxidative phosphorylation damage. Genetic deletion of the vitamin D3 receptor (VDR), which serves as a primary colonic BA receptor, in colonic epithelial cells (VDRΔIEC) abolished the therapeutic effect of lithocholic acid on MMF-induced GI toxicity. Impressively, we discovered that paricalcitol, a Food and Drug Administration-approved VDR agonist that has been used in clinics for years, could effectively alleviate MMF-induced GI toxicity. Our study reveals a previously unrecognized mechanism of gut microbiota, BAs, and VDR signaling in MMF-induced GI side effects, offering potential therapeutic strategies for clinics.

Unveiling the hidden role of disulfidptosis in kidney renal clear cell carcinoma: a prognostic signature for personalized treatment.

The role of disulfidptosis in kidney renal clear cell carcinoma (KIRC) remains unknown. This study investigated disulfidptosis-related biomarkers for KIRC prognosis prediction and individualized treatment. KIRC patients were clustered by disulfidptosis profiles. Differential expression analysis, survival models, and machine learning were used to construct the disulfidptosis-related prognostic signature (DRPS). Characterizations of the tumor immune microenvironment, genetic drivers, drug sensitivity, and immunotherapy response were explored according to the DRPS risk stratification. Markers included in the signature were validated using single-cell, spatial transcriptomics, quantitative RT-qPCR, and immunohistochemistry. In the discovery cohort, we unveiled two clusters of KIRC patients that differed significantly in disulfidptosis regulator expressions and overall survival (OS). After multiple feature selection steps, a DRPS prognostic model with four features (CHAC1, COL7A1, FOXM1, SHOX2) was constructed and validated. Combined with clinical factors, the model demonstrated robust performance in the discovery and external validation cohorts (5-year AUC = 0.793 and 0.846, respectively). KIRC patients with high-risk scores are characterized by inferior OS, less tumor purity, and increased infiltrations of fibroblasts, M1 macrophages, and B cells. High-risk patients also have higher frequencies of BAP1 and AHNAK2 mutation. Besides, the correlation between the DRPS score and the chemotherapy-response signature indicated the potential effect of Gefitinib for high-risk patients. Among the signature genes, FOXM1 is highly expressed in cycling tumor cells and exhibits spatial aggregation, while others are expressed sparsely within tumor samples. The DRPS model enables improved clinical management and personalized KIRC therapy. The identified biomarkers and immune characteristics offer new mechanistic insight into disulfidptosis in KIRC.

Chromosome-level genome assembly and demographic history of Euryodendron excelsum in monotypic genus endemic to China.

Euryodendron excelsum is in a monotypic genus Euryodendron, endemic to China. It has intermediate morphisms in the Pentaphylacaceae or Theaceae families, which make it distinct. Due to anthropogenic disturbance, E. excelsum is currently found in very restricted and fragmented areas with extremely small populations. Although much research and effort has been applied towards its conservation, its long-term survival mechanisms and evolutionary history remain elusive, especially from a genomic aspect. Therefore, using a combination of long/short whole genome sequencing, RNA sequencing reads, and Hi-C data, we assembled and annotated a high-quality genome for E. excelsum. The genome assembly of E. excelsum comprised 1,059,895,887 bp with 99.66% anchored into 23 pseudo-chromosomes and a 99.0% BUSCO completeness. Comparative genomic analysis revealed the expansion of terpenoid and flavonoid secondary metabolite genes, and displayed a tandem and/or proximal duplication framework of these genes. E. excelsum also displayed genes associated with growth, development, and defence adaptation from whole genome duplication. Demographic analysis indicated that its fluctuations in population size and its recent population decline were related to cold climate changes. The E. excelsum genome assembly provides a highly valuable resource for evolutionary and ecological research in the future, aiding its conservation, management, and restoration.

Adherence to the Diabetes Risk Reduction Diet and Bladder Cancer Risk in the Prostate, Lung, Colorectal, Ovarian (PLCO) Cohort.

BACKGROUND: This study aimed to explore the relationship between diabetes risk reduction diet (DRRD) and bladder cancer risk in Prostate, Lung, Colorectal, Ovarian (PLCO) cohort. METHODS: Data from 99,001 participants in the PLCO Cancer Screening Trial were analyzed using Cox proportional hazards regression models to estimate HRs and 95% confidence intervals (CI) for the association between DRRD score and bladder cancer incidence. Subgroup analyses were conducted to assess whether variables such as age, sex, body mass index, cigarette smoking status, and history of diabetes influenced the observed association. The DRRD score was formulated on the basis of nine nutrient intake indicators derived from the Dietary History Questionnaire. RESULTS: During the median follow-up of 11.7 years, 761 new bladder cancer cases were identified. Participants with highest DRRD scores exhibited a reduced risk of bladder cancer compared with those in the lowest quartile (unadjusted analysis, HR, 0.65; 95% CI, 0.53-0.82); multivariable adjusted analysis, HR, 0.79; 95% CI, 0.64-0.98; Ptrend = 0.007). A similar risk reduction was seen solely in transitional cell carcinoma (HR, 0.79; 95% CI, 0.64-0.99; P = 0.007). In addition, the significant negative association between DRRD scores and bladder cancer risk persisted even after excluding participants with unique characteristics. CONCLUSIONS: This large prospective population-based study suggests that adherence to a DRRD may contribute to the prevention of bladder cancer. IMPACT: The DRRD could potentially mitigate bladder cancer risk, which warrants further validation in diverse populations.

Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation.

Background: Timely and accurate outcome prediction plays a critical role in guiding clinical decisions for hypertensive ischemic or hemorrhagic stroke patients admitted to the ICU. However, interpreting and translating the predictive models into clinical applications are as important as the prediction itself. This study aimed to develop an interpretable machine learning (IML) model that accurately predicts 28-day all-cause mortality in hypertensive ischemic or hemorrhagic stroke patients. Methods: A total of 4,274 hypertensive ischemic or hemorrhagic stroke patients admitted to the ICU in the USA from multicenter cohorts were included in this study to develop and validate the IML model. Five machine learning (ML) models were developed, including artificial neural network (ANN), gradient boosting machine (GBM), eXtreme Gradient Boosting (XGBoost), logistic regression (LR), and support vector machine (SVM), to predict mortality using the MIMIC-IV and eICU-CRD database in the USA. Feature selection was performed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Model performance was evaluated based on the area under the curve (AUC), accuracy, positive predictive value (PPV), and negative predictive value (NPV). The ML model with the best predictive performance was selected for interpretability analysis. Finally, the SHapley Additive exPlanations (SHAP) method was employed to evaluate the risk of all-cause in-hospital mortality among hypertensive ischemic or hemorrhagic stroke patients admitted to the ICU. Results: The XGBoost model demonstrated the best predictive performance, with the AUC values of 0.822, 0.739, and 0.700 in the training, test, and external cohorts, respectively. The analysis of feature importance revealed that age, ethnicity, white blood cell (WBC), hyperlipidemia, mean corpuscular volume (MCV), glucose, pulse oximeter oxygen saturation (SpO2), serum calcium, red blood cell distribution width (RDW), blood urea nitrogen (BUN), and bicarbonate were the 11 most important features. The SHAP plots were employed to interpret the XGBoost model. Conclusions: The XGBoost model accurately predicted 28-day all-cause in-hospital mortality among hypertensive ischemic or hemorrhagic stroke patients admitted to the ICU. The SHAP method can provide explicit explanations of personalized risk prediction, which can aid physicians in understanding the model.

Gene methylation status in focus of advanced prostate cancer diagnostics and improved individual outcomes.

Background: Prostate cancer (PCa) is the most prevalent type of male genitourinary tumor, remains the second leading cause of deaths due to cancer in the United States in men. The aim of this study was to perform an integrative epigenetic analysis to explore the epigenetic abnormalities involved in the development and progression of PCa, and present advanced diagnostics and improved individual outcomes. Methods: Genome-wide DNA methylation profiles obtained from The Cancer Genome Atlas (TCGA) were analyzed and a diagnostic model was constructed. For validation, we employed profiles from the Gene Expression Omnibus (GEO) and methylation data derived from clinical samples. Gene set enrichment analysis (GSEA) and the Tumor Immune Estimation Resource (TIMER) were employed for GSEA and to assess immune cell infiltration, respectively. Results: An accurate diagnostic method for PCa was established based on the methylation level of Cyclin-D2 (CCND2) and glutathione S-transferase pi-1 (GSTP1), with an impressive area under the curve (AUC) value of 0.937. The model's reliability was further confirmed through validation using four GEO datasets GSE76938 (AUC =0.930), GSE26126 (AUC =0.906), GSE112047 (AUC =1.000), GSE84749 (AUC =0.938) and clinical samples (AUC =0.980). Notably, the TIMER analysis indicated that hypermethylation of CCND2 and GSTP1 was associated with reduced immune cell infiltration, higher tumor purity, and an increased risk of tumor progression. Conclusions: In conclusion, our study provides a robust and reliable methylation-based diagnostic model for PCa. This model holds promise as an improved approach for screening and diagnosing PCa, potentially enhancing early detection and patient outcomes, as well as for an advanced clinical management for PCa in the framework of predictive, preventive and personalised medicine.

Prognostic, Clinicopathological, and Function of Key Cuproptosis Regulator FDX1 in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of renal cancer. Cuproptosis is suggested to be a novel therapy target for cancer treatment. However, the function of cuproptosis and its key regulator FDX1 in ccRCC remains unclear. In this study, we adequately explored the prognostic factors, clinicopathological characteristics, and function of FDX1 in ccRCC. We found that the expression of FDX1 was significantly downregulated in ccRCC samples. Patients with a higher FDX1 expression had a significantly better prognosis, including overall survival (OS) (Hazard ratio (HR): 2.54, 95% confidence interval (CI): 1.82−3.53, p < 0.001), disease-specific survival (DSS) (HR: 3.04, 95% CI: 2.04−4.54, p < 0.001), and progression-free survival (PFS) (HR: 2.54, 95% CI: 1.82−3.53, p < 0.001). FDX1 was a clinical predictor to stratify patients into the high or low risk of poor survival, independent of conventional clinical features, with the area under the ROC curve (AUC) of 0.658, 0.677, and 0.656 for predicting the 5-year OS, DSS, and PFS. The nomogram model based on FDX1 had greater predictive power than other individual prognostic parameters. FDX1 mainly participated in the oxidative-related process and mitochondrial respiration-related processes but was not associated with immune infiltration levels. In conclusion, the cuproptosis key regulator FDX1 could serve as a potential novel prognostic biomarker for ccRCC patients.

Successful resection of a huge retroperitoneal venous hemangioma: A case report.

BACKGROUND: Venous hemangioma is a benign and non-invasive type of tumor, which is rarely identified due to the absence of clinical manifestations. A retroperitoneal benign tumor is comparatively rare, and hemangioma is exceptional. Because of the different types and locations of hemangioma, presentations are varied; thus, establishing an accurate diagnosis before surgery is challenging. CASE SUMMARY: A 45-year-old female patient visited our hospital with the complaint of a retroperitoneal mass without symptoms discovered during a medical examination. An abdominal and pelvic computed tomography (CT) revealed a giant hypodense mass that extended from the lower edge of the liver down to the right groin and showed no marked enhancement in the arterial phase of the enhanced CT. On magnetic resonance imaging, the retroperitoneal mass was hyperintense on the T2-weighted image and hypointense on the T1-weighted image. The mass was completely resected and confirmed as a venous hemangioma by pathology. CONCLUSION: Venous hemangioma is rare in adults, and an accurate diagnosis before surgery is challenging. Surgery is the curative treatment for venous hemangioma, and the definitive diagnosis relies on pathology.

The complete chloroplast genome of Stichorkis gibbosa (Orchidaceae: Malaxideae).

Stichorkis gibbosa is a rare orchid species of the tribe Malaxideae mainly distributed in tropical Asia. This is the only species of the genus Stichorkis Thouars which has been reported to occur in China. Despite the importance of this genus, previous molecular studies based on few markers have resulted in limited phylogenetic resolution. With the decline of habitats, the wild population of S. gibbosa has decreased in recent years. In this study, we first reported the complete chloroplast (cp) genome of S. gibbosa. The entire cp genome was determined to be 158,056 bp in length with overall GC content of 36.9%, containing a pair of inverted repeat regions (IRs) of 27,006 bp, separated by a large single-copy (LSC, 86,280 bp) and a small single-copy (SSC, 17,764 bp). A total of 133 unique genes were annotated, including 87 protein-coding genes, 38 tRNA genes, and eight rRNA genes. The phylogenetic tree indicated that S. gibbosa was a sister group of the genus Oberonia and the epiphytic Liparis alliance with strong support.

Integrated Analysis of Prognostic Genes Associated With Ischemia-Reperfusion Injury in Renal Transplantation.

Background: Ischemia-reperfusion injury (IRI) remains an inevitable and major challenge in renal transplantation. The current study aims to obtain deep insights into underlying mechanisms and seek prognostic genes as potential therapeutic targets for renal IRI (RIRI). Methods: After systematically screening the Gene Expression Omnibus (GEO) database, we collected gene expression profiles of over 1,000 specimens from 11 independent cohorts. Differentially expressed genes (DEGs) were identified by comparing allograft kidney biopsies taken before and after reperfusion in the discovery cohort and further validated in another two independent transplant cohorts. Then, graft survival analysis and immune cell analysis of DEGs were performed in another independent renal transplant cohort with long-term follow-ups to further screen out prognostic genes. Cell type and time course analyses were performed for investigating the expression pattern of prognostic genes in more dimensions utilizing a mouse RIRI model. Finally, two novel genes firstly identified in RIRI were verified in the mouse model and comprehensively analyzed to investigate potential mechanisms. Results: Twenty DEGs upregulated in the process of RIRI throughout different donor types (living donors, cardiac and brain death donors) were successfully identified and validated. Among them, upregulation of 10 genes was associated with poor long-term allograft outcomes and exhibited strong correlations with prognostic immune cells, like macrophages. Furthermore, certain genes were found to be only differentially expressed in specific cell types and remained with high expression levels even months after RIRI in the mouse model, which processed the potential to serve as therapeutic targets. Importantly, two newly identified genes in RIRI, Btg2 and Rhob, were successfully confirmed in the mouse model and found to have strong connections with NF-κB signaling. Conclusions: We successfully identified and validated 10 IRI-associated prognostic genes in renal transplantation across different donor types, and two novel genes with crucial roles in RIRI were recognized for the first time. Our findings offered promising potential therapeutic targets for RIRI in renal transplantation.

Prognostic Value of Preoperative Albumin-to-Fibrinogen Ratio in Patients with Bladder Cancer.

Background: Both nutritional status and coagulation function are closely associated with prognosis in patients with bladder cancer (BC). This study aimed to investigate the prognostic value of albumin-to-fibrinogen ratio (AFR) for BC patients underwent radical cystectomy (RC) or transurethral resection of bladder tumor (TURBT), and develop predictive nomograms based on AFR. Methods: We retrospectively collected medical records of 358 BC patients who underwent RC or TURBT between January 2012 and December 2018. The whole cohort was divided into the training (215 patients, 60.06%) and validation cohorts (143 patients, 39.94%) based on surgery dates. The training cohort was applied to select characteristics and construct nomograms, while the validation cohort was used to verify the nomograms independently. Endpoints of the current study included overall survival (OS), disease-specific survival (DSS) and disease-free survival (DFS). Prognostic values of AFR and other characteristics were evaluated using univariate and multivariate Cox regression analyses and compared using the concordance-index (C-index). Nomograms for OS, DSS and DFS were constructed based on both-directional stepwise Cox proportional hazards regression analysis and evaluated by the receiver operating characteristic (ROC) curve, the C-index and calibration plot. Results: In whole cohort, 86 patients (24.02%) were classified into low AFR group and had worse OS (hazard ratio [HR]: 4.079, 95% confidence interval [CI]: 2.085-7.982, P < 0.001), DSS (HR: 3.012, 95% CI: 1.302-6.966, P = 0.010) and DFS (HR: 1.863, 95% CI: 1.204-2.883, P = 0.005) compared to BC patients in high AFR group. Meanwhile, the AFR processed better prognostic power than albumin and fibrinogen, individually. Multivariate Cox analysis indicated that AFR was an independent prognostic factor for OS (HR: 2.601, 95% CI: 1.057-6.395, P = 0.037) and DFS (HR: 1.971, 95% CI: 1.049-3.703, P = 0.035). Novel nomograms, incorporating AFR, tumor grade and tumor multifocality, were constructed and successfully validated for predictions of OS, DSS and DFS in BC. Conclusions: Preoperative AFR was identified as an independent prognostic predictor for OS and DFS of BC patients underwent surgery. The nomograms incorporating AFR provided accurate predictions for OS, DSS and DFS, which could help urologists in better clinical decision-making.

A Novel Ferroptosis-Related Gene Model for Overall Survival Predictions of Bladder Urothelial Carcinoma Patients.

INTRODUCTION: Bladder cancer is the most common urinary tract malignancy, and 90% of bladder tumors are urothelial cell carcinomas. Ferroptosis is a new form of cell death discovered in recent years, which is an iron-dependent form of cell death characterized by the lethal intracellular accumulation of lipid-based reactive oxygen species. Ferroptosis is considered to be a double-edged sword for cancer and cancer therapy. MATERIALS AND METHODS: In the current study, expression profiles of bladder cancer (BLCA) specimens were obtained from The Cancer Genome Atlas (TCGA) RNA-Seq database. Ferroptosis-related genes were downloaded from the FerrDb website. The ferroptosis-related differentially expressed genes (DEGs) which were related to overall survival (OS) were first identified. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression methods were utilized to develop a ferroptosis-related prognostic model (FRPM). In addition, a nomogram model based on FRPM and clinicopathological features was successfully constructed and validated. In addition, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) methods were utilized in this study in order to compare the DEGs between the high-risk and low-risk groups. This study also adopted RT-qPCR, CCK-8 assay, and scratch assay methods to perform experimental verification processes. RESULTS AND DISCUSSION: A 7-gene FRPM was constructed in this research investigation in order to stratify the patients into two groups according to their risk scores. The results of this study's survival analysis and time-dependent receiver operating characteristic (ROC) analysis demonstrated that the model had achieved a stable performance level. This multivariate Cox regression results revealed that the FRPM was an independent prognostic predictor for the OS of BLCA patients and the results were displayed using a nomogram. In addition, the ROC analysis, concordance index (C-index), calibration plots, and decision curve analysis (DCA) curves further indicated that this study's nomogram method enabled valuable prediction results. The functional enrichment analysis results suggested that the DEGs between the high- and low-risk groups played vital roles in the progression of the ferroptosis. Also, the ssGSEA indicated that the immune status was different between the two groups. This study found that the RT-qPCR results had confirmed the differential expressions of DEGs in the tissue samples, and the CCK-8 assay and scratch assay results confirmed the promoting effects of SCD on the proliferation and migration of tumor cells. CONCLUSIONS: This study defined a novel prognostic model of seven ferroptosis-related genes, which proved to be independently associated with the OS of BLCA. A nomogram method was developed for the purpose of providing further insight into the accurate predictions of BLCA prognoses.

The Effect of Quenching and Partitioning (Q&P) Heat Treatment on the Microstructure and Mechanical Properties of High Boron Steel.

High boron steel is prone to brittle failure due to the boride distributed in it with net-like or fishbone morphology, which limit its applications. The Quenching and Partitioning (Q&P) heat treatment is a promising process to produce martensitic steel with excellent mechanical properties, especially high toughness by increasing the volume fraction of retained austensite (RA) in the martensitic matrix. In this work, the Q&P heat treatment is used to improve the inherent defect of insufficient toughness of high boron steel, and the effect mechanism of this process on microstructure transformation and the change of mechanical properties of the steel has also been investigated. The high boron steel as-casted is composed of martensite, retained austensite (RA) and eutectic borides. A proper quenching and partitioning heat treatment leads to a significant change of the microstructure and mechanical properties of the steel. The net-like and fishbone-like boride is partially broken and spheroidized. The volume fraction of RA increases from 10% in the as-cast condition to 19%, and its morphology also changes from blocky to film-like. Although the macro-hardness has slightly reduced, the toughness is significantly increased up to 7.5 J·cm-2, and the wear resistance is also improved.

Assessment of chronic allograft injury in renal transplantation using diffusional kurtosis imaging.

BACKGROUND: Chronic allograft injury (CAI) is a significant reason for which many grafts were lost. The study was conducted to assess the usefulness of diffusional kurtosis imaging (DKI) technology in the non-invasive assessment of CAI. METHODS: Between February 2019 and October 2019, 110 renal allograft recipients were included to analyze relevant DKI parameters. According to estimated glomerular filtration rate (eGFR) (mL/min/ 1.73 m2) level, they were divided to 3 groups: group 1, eGFR ≥ 60 (n = 10); group 2, eGFR 30-60 (n = 69); group 3, eGFR < 30 (n = 31). We performed DKI on a clinical 3T magnetic resonance imaging system. We measured the area of interest to determine the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) of the renal cortex and medulla. We performed a Pearson correlation analysis to determine the relationship between eGFR and the DKI parameters. We used the receiver operating characteristic curve to estimate the predicted values of DKI parameters in the CAI evaluation. We randomly selected five patients from group 2 for biopsy to confirm CAI. RESULTS: With the increase of creatinine, ADC, and MD of the cortex and medulla decrease, MK of the cortex and medulla gradually increase. Among the three different eGFR groups, significant differences were found in cortical and medullary MK (P = 0.039, P < 0.001, P < 0.001, respectively). Cortical and medullary ADC and MD are negatively correlated with eGFR (r = - 0.49, - 0.44, - 0.57, - 0.57, respectively; P < 0.001), while cortical and medullary MK are positively correlated with eGFR (r = 0.42, 0.38; P < 0.001). When 0.491 was set as the cutoff value, MK's CAI assessment showed 87% sensitivity and 100% specificity. All five patients randomly selected for biopsy from the second group confirmed glomerulosclerosis and tubular atrophy/interstitial fibrosis. CONCLUSION: The DKI technique is related to eGFR as allograft injury progresses and is expected to become a potential non-invasive method for evaluating CAI.

Using machine learning method to identify MYLK as a novel marker to predict biochemical recurrence in prostate cancer.

Aim: This study aims to identify novel marker to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy with negative surgical margin. Materials & methods: The Cancer Genome Atlas database, Gene Expression Omnibus database and Cancer Cell Line Encyclopedia database were employed. The ensemble support vector machine-recursive feature elimination method was performed to select crucial gene for BCR. Results: We identified MYLK as a novel and independent biomarker for BCR in The Cancer Genome Atlas training cohort and confirmed in four independent Gene Expression Omnibus validation cohorts. Multi-omic analysis suggested that MYLK was a DNA methylation-driven gene. Additionally, MYLK had significant positive correlations with immune infiltrations. Conclusion:MYLK was identified and validated as a novel, robust and independent biomarker for BCR in prostate cancer.

Ovule Development and in Planta Transformation of Paphiopedilum Maudiae by Agrobacterium-Mediated Ovary-Injection.

In this paper, the development of the Paphiopedilum Maudiae embryo sac at different developmental stages after pollination was assessed by confocal laser scanning microscopy. The mature seeds of P. Maudiae consisted of an exopleura and a spherical embryo, but without an endosperm, while the inner integument cells were absorbed by the developing embryo. The P. Maudiae embryo sac exhibited an Allium type of development. The time taken for the embryo to develop to a mature sac was 45-50 days after pollination (DAP) and most mature embryo sacs had completed fertilization and formed zygotes by about 50-54 DAP. In planta transformation was achieved by injection of the ovaries by Agrobacterium, resulting in 38 protocorms or seedlings after several rounds of hygromycin selection, corresponding to 2, 7, 5, 1, 3, 4, 9, and 7 plantlets from Agrobacterium-mediated ovary-injection at 30, 35, 42, 43, 45, 48, 50, and 53 DAP, respectively. Transformation efficiency was highest at 50 DAP (2.54%), followed by 2.48% at 53 DAP and 2.45% at 48 DAP. Four randomly selected hygromycin-resistant plants were GUS-positive after PCR analysis. Semi-quantitative PCR and quantitative real-time PCR analysis revealed the expression of the hpt gene in the leaves of eight hygromycin-resistant seedlings following Agrobacterium-mediated ovary-injection at 30, 35, 42, 43, 45, 48, 50, and 53 DAP, while hpt expression was not detected in the control. The best time to inject P. Maudiae ovaries in planta with Agrobacterium is 48-53 DAP, which corresponds to the period of fertilization. This protocol represents the first genetic transformation protocol for any Paphiopedilum species and will allow for expanded molecular breeding programs to introduce useful and interesting genes that can expand its ornamental and horticulturally important characteristics.

Identification of a three-long noncoding RNA prognostic model involved competitive endogenous RNA in kidney renal clear cell carcinoma.

BACKGROUND: Long noncoding RNA (lncRNA) is generally identified as competing endogenous RNA (ceRNA) that plays a vital role in the pathogenesis of kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma with poor prognosis and unclear pathogenesis. This study established a novel ceRNA network and thus identified a three-lncRNA prognostic model in KIRC patients. METHODS: Differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) database. The lncATLAS was applied to determine the differentially expressed lncRNAs (DElncRNAs) of the cytoplasm. The miRcode, miRDB, miRTarBase, and TargetScan databases were utilized to predict the interactions of DElncRNAs, DEmiRNAs, and DEmRNAs. Cytoscape was used to construct the ceRNA network. Then, a lncRNA prognostic model (LPM) was constructed based on ceRNA-related lncRNA that was significantly related to overall survival (OS), and its predictive ability was evaluated. Moreover, an LPM-based nomogram model was constructed. The significantly different expression of genes in the LPM was validated in an independent clinical cohort (N = 21) by quantitative RT-PCR. RESULTS: A novel ceRNA regulatory network, including 73 lncRNAs, 8 miRNAs, and 21 mRNAs was constructed. Functional enrichment analysis indicated that integral components of membrane and PI3K-Akt signaling pathway represented the most significant GO terms and pathway, respectively. The LPM established based on three lncRNAs (MIAT, LINC00460, and LINC00443) of great prognostic value from the ceRNA network was proven to be independent of conventional clinical parameters to differentiate patients with low or high risk of poor survival, with the AUC of 1-, 5- and 10-year OS were 0.723, 0.714 and 0.826 respectively. Furthermore, the nomogram showed a better predictive value in KIRC patients than individual prognostic parameters. The expression of MIAT and LINC00460 was significantly upregulated in the KIRC samples, while the expression of LINC00443 was significantly downregulated compared with the adjacent normal samples in the clinical cohort, TCGA, and GTEx. CONCLUSION: This LPM based on three-lncRNA could serve as an independent prognostic factor with a tremendous predictive ability for KIRC patients, and the identified novel ceRNA network may provide insight into the prognostic biomarkers and therapeutic targets of KIRC.

Butyric acid normalizes hyperglycemia caused by the tacrolimus-induced gut microbiota.

Approximately 33.6% of nondiabetic solid organ transplant recipients who received tacrolimus developed hyperglycemia. Whether the tacrolimus-induced gut microbiota is involved in the regulation of hyperglycemia has not been reported. Hyperglycemia was observed in a tacrolimus-treated mouse model, with reduction in taxonomic abundance of butyrate-producing bacteria and decreased butyric acid concentration in the cecum. This tacrolimus-induced glucose metabolic disorder was caused by the gut microbiota, as confirmed by a broad-spectrum antibiotic model. Furthermore, oral supplementation with butyrate, whether for remedy or prevention, significantly increased the butyric acid content in the cecum and arrested hyperglycemia through the regulation of glucose-regulating hormones, including glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and insulin, in serum. The butyrate-G-protein-coupled receptor 43-GLP-1 pathway in the intestinal crypts may be involved in the pathogenesis of normalization of hyperglycemia caused by the tacrolimus. Therefore, tacrolimus affects glucose metabolism through the butyrate-associated GLP-1 pathway in the gut, and oral supplementation with butyrate provides new insights for the prevention and treatment of tacrolimus-induced hyperglycemia in transplant recipients.

Fabrication of Biodegradable Poly(caprolactone) Spherical-Microcarriers for Arterial Embolization.

This study aimed to develop emulsification assisted with ultrasonic atomization (EUA) to make embolic biodegradable poly(caprolactone) (PCL) spherical-microcarriers with uniform particle size for mass production which was used to cure hepatocellular carcinoma, because this kind of embolic drugs is expensive at the current market due to their complex manufacturing process. The embolic spherical-microcarriers with sustained-releasing therapeutic agents can shrink an unresectable tumor into a respectable size. Through high frequency vibrating surface on the ultrasonic atomizer nozzle, the thin liquid film for PCL oil-phase solution was broken into the uniform PCL microdroplets (particle sizes are from 20 to 55 µm) with less medicine loss. To determine the optimal parameters to make PCL microcarriers, the ultrasonic module parameters including the concentration of PCL solution, vibrating amplitude of atomizer, feeding rate of PCL oil-phase solution and collection distance on the particle size of microdroplets were analyzed. Besides, a vertical circulation flow field of aqueous-phase poly(vinyl alcohol) (PVA) solution was created to enhance the separation of the microdroplets and increase the production of the PCL microcarriers, and about 8~11 wt% of PVA solution with high stable dispersion property was used to effectively improve the yield rate of PCL spherical-microcarriers (89.8~98.2 wt%). The final particle size of PCL microcarriers was ca. 5-18 µm, indicating an about 25-50% volume shrinkage from microdroplets to solid spherical-microcarriers.