Evaluation of split renal dysfunction using radiomics based on magnetic resonance diffusion-weighted imaging.

BACKGROUND: Accurate and noninvasive assessment of split renal dysfunction is crucial, while there is lack of corresponding method clinically. PURPOSE: To investigate the feasibility of using diffusion-weighted imaging (DWI)-based radiomics models to evaluate split renal dysfunction. METHODS: We enrolled patients with impaired and normal renal function undergoing renal DWI examination. Glomerular filtration rate (GFR, mL/min) was measured using 99mTc-DTPA scintigraphy, which is reference standard of GFR measurement. The kidneys were classified into normal (GFR ≥40), mildly impaired (20≤ GFR < 40), moderately impaired (10≤ GFR < 20), and severely impaired (GFR < 10) renal function groups. Optimized subsets of radiomics features were selected from renal DWI images and radiomics scores (Rad-score) calculated to discriminate groups with different renal function. The radiomics model (Rad-score based) was developed in a training cohort and validated in a test cohort. Evaluations were conducted on the discrimination, calibration, and clinical application of the method. RESULTS: The final analysis included 330 kidneys. Logistic regression was used to develop three radiomics models, model A, B, and C, which were used to distinguish normal from impaired, mild from moderate, and moderate from severe renal function, respectively. The area under the curve of the three models were 0.822, 0.704, and 0.887 in the training cohort and 0.843, 0.717, and 0.897 in the test cohort, respectively, indicating efficient discrimination performance. CONCLUSIONS: DWI-based radiomics models have potential for evaluating split renal dysfunction and discriminating between normal and impaired renal function groups and their subgroups.

Performance of machine learning-based coronary computed tomography angiography for selecting revascularization candidates.

BACKGROUND: Limited studies have investigated the accuracy of therapeutic decision-making using machine learning-based coronary computed tomography angiography (ML-CCTA) compared with CCTA. PURPOSE: To investigate the performance of ML-CCTA for therapeutic decision compared with CCTA. MATERIAL AND METHODS: The study population consisted of 322 consecutive patients with stable coronary artery disease. The SYNTAX score was calculated with an online calculator based on ML-CCTA results. Therapeutic decision-making was determined by ML-CCTA results and the ML-CCTA-based SYNTAX score. The therapeutic strategy and the appropriate revascularization procedure were selected using ML-CCTA, CCTA, and invasive coronary angiography (ICA) independently. RESULTS: The sensitivity, specificity, positive predictive value, negative predictive value, accuracy of ML-CCTA and CCTA for selecting revascularization candidates were 87.01%, 96.43%, 95.71%, 89.01%, 91.93%, and 85.71%, 87.50%, 86.27%, 86.98%, 86.65%, respectively, using ICA as the standard reference. The area under the receiver operating characteristic curve (AUC) of ML-CCTA for selecting revascularization candidates was significantly higher than CCTA (0.917 vs. 0.866, P = 0.016). Subgroup analysis showed the AUC of ML-CCTA for selecting percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) candidates was significantly higher than CCTA (0.883 vs. 0.777, P < 0.001, 0.912 vs. 0.826, P = 0.003, respectively). CONCLUSION: ML-CCTA could distinguish between patients who need revascularization and those who do not. In addition, ML-CCTA showed a slightly superior to CCTA in making an appropriate decision for patients and selecting a suitable revascularization strategy.

N6-methyladenosine methyltransferase KIAA1429 promoted ovarian cancer aerobic glycolysis and progression through enhancing ENO1 expression.

BACKGROUND: Despite improvements in prognosis due to advances in treatment, including surgery, genetic screening, and molecular targeted therapy, the outcomes of ovarian cancer (OC) remain unsatisfactory. Internal mRNA modifications are extremely common in eukaryotes; N6-methyladenosine (m6A) alteration has significant effects on mRNA stability and translation, and it is involved in the pathophysiology of numerous diseases related to cancer. METHODS: Bioinformatics analysis, quantitative real-time polymerase chain reaction and Western blotting were used to detect the expression of vir-like m6A methyltransferase associated (KIAA1429) in OC tissues and cell lines. Several different cell models and animal models were established to determine the role of KIAA1429 in glucose metabolism reprogramming and the underlying molecular mechanism of OC. The mechanism of oncology functional assays, co-immunoprecipitation and a luciferase reporter gene was employed to ascertain how KIAA1429 interacts with important molecular targets. RESULTS: We reported that KIAA1429 was overexpressed in OC and predicted a poor prognosis. Functionally, KIAA1429 promoted cell growth by inducing proliferation and inhibiting necrosis. Mechanistically, KIAA1429 promoted tumor progression and glycolysis via stabilizing ENO1 mRNA in a way dependent on m6A. Furthermore, we investigated that the SPI1 transcription factor is the main transcription factor that regulates KIAA1429 transcription in OC. CONCLUSION: Our findings revealed that SPI1/KIAA1429/ENO1 signaling is a novel molecular axis and raises awareness of the vital functions of the changes in KIAA1429 and m6A changes in the metabolic reprogramming of OC. These results identified new potential biomarkers and treatment targets for OC.

Research progress of small-molecule drugs in targeting telomerase in human cancer and aging.

Telomeres are unique structures located at the ends of linear chromosomes, responsible for stabilizing chromosomal structures. They are synthesized by telomerase, a reverse transcriptase ribonucleoprotein complex. Telomerase activity is generally absent in human somatic cells, except in stem cells and germ cells. Every time a cell divides, the telomere sequence is shortened, eventually leading to replicative senescence and cell apoptosis when the telomeres reach a critical limit. However, most human cancer cells exhibit increased telomerase activity, allowing them to divide continuously. The importance of telomerase in cancer and aging has made developing drugs targeting telomerase a focus of research. Such drugs can inhibit cancer cell growth and delay aging by enhancing telomerase activity in telomere-related syndromes or diseases. This review provides an overview of telomeres, telomerase, and their regulation in cancer and aging, and highlights small-molecule drugs targeting telomerase in these fields.

Corylin inhibits the progression of Non-small cell lung cancer cells by regulating NF-κB signaling pathway via targeting p65.

BACKGROUND: Lung cancer is characterized by high-risk and high mortality, among which non-small cell lung cancer (NSCLC) conquers a dominant position. Previous studies have reported that corylin has anti-inflammatory, anti-oxidant, and anti-tumor effects; however, its role in NSCLC cells remains unclear. HYPOTHESIS: Corylin inhibits the progression of NSCLC cells. METHODS: A lentivector NF-κB luciferase reporter was constructed by molecular cloning. Corylin was screened and identified as an NF-κB pathway inhibitor by luciferase reporter assay. Corylin inhibited the expression of NF-κB downstream genes, which was detected by qRT-PCR. The effect of corylin on NSCLC cells was detected by colony formation assay, cell apoptosis, cell proliferation, in vitro invasion, and cell scratch assay. Corylin inhibited p65 nuclear translocation and was detected by molecular docking, immunofluorescence assay, and Western blot analysis. RESULTS: We constructed a lentiviral expression vector, containing an NF-κB luciferase reporter and established a stable A549 cell line for its expression. Using this cell line, corylin was screened and identified as an NF-κB pathway inhibitor. It was found that corylin inhibited the expression of NF-κB downstream genes and inhibited the proliferation and migration of NSCLC cells. Meanwhile, it was also found that corylin significantly reversed the increased proliferation of NSCLC cell lines induced by p65 overexpression. Molecular docking analysis showed that corylin could bind to p65 by hydrogen bonding. Further study showed that corylin inhibited the NF-κB signaling pathway by blocking p65 nuclear translocation. CONCLUSIONS: Our study screened and identified corylin as an NF-κB inhibitor and elucidated the molecular mechanism by which corylin inhibits the growth of NSCLC cells. The present study provides a novel strategy for improving the prognosis and treatment of NSCLC patients.

Pharmacological Activity of Quercetin: An Updated Review.

Quercetin, a natural flavonoid compound with a widespread occurrence throughout the plant kingdom, exhibits a variety of pharmacological activities. Because of the wide spectrum of health-promoting effects, quercetin has attracted much attention of dietitians and medicinal chemists. An updated review of the literature on quercetin was performed using PubMed, Embase, and Science Direct databases. This article presents an overview of recent developments in pharmacological activities of quercetin including anti-SARS-CoV-2, antioxidant, anticancer, antiaging, antiviral, and anti-inflammatory activities as well as the mechanism of actions involved. The biological activities of quercetin were evaluated both in vitro and in vivo, involving a number of cell lines and animal models, but metabolic mechanisms of quercetin in the human body are not clear. Therefore, further large sample clinical studies are needed to determine the appropriate dosage and form of quercetin for the treatment of the disease.

Research progress of CRISPR-based biosensors and bioassays for molecular diagnosis.

CRISPR/Cas technology originated from the immune mechanism of archaea and bacteria and was awarded the Nobel Prize in Chemistry in 2020 for its success in gene editing. Molecular diagnostics is highly valued globally for its development as a new generation of diagnostic technology. An increasing number of studies have shown that CRISPR/Cas technology can be integrated with biosensors and bioassays for molecular diagnostics. CRISPR-based detection has attracted much attention as highly specific and sensitive sensors with easily programmable and device-independent capabilities. The nucleic acid-based detection approach is one of the most sensitive and specific diagnostic methods. With further research, it holds promise for detecting other biomarkers such as small molecules and proteins. Therefore, it is worthwhile to explore the prospects of CRISPR technology in biosensing and summarize its application strategies in molecular diagnostics. This review provides a synopsis of CRISPR biosensing strategies and recent advances from nucleic acids to other non-nucleic small molecules or analytes such as proteins and presents the challenges and perspectives of CRISPR biosensors and bioassays.

Network Pharmacology-Integrated Molecular Docking Reveals the Expected Anticancer Mechanism of Picrorhizae Rhizoma Extract.

This study sought to explore the anticancer mechanism of Picrorhizae Rhizoma (PR) extract based on network pharmacology and molecular docking. The potential chemicals of PR were screened through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and relevant literatures. Corresponding targets of active ingredients were found with the help of the UniProtKB database, and therapeutic targets for cancer action were screened with the help of the GeneCards database. We used Cytoscape software to construct the compound-target-pathway network of PR extract. We utilized the STRING database to obtain the protein-protein interaction (PPI) network. We used DAVID database combining Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, molecular docking was employed for initial efficacy checking. We have identified 16 potential active components of PR through screening, involving 112 disease action targets. Utilizing the GeneCards database, 112 intersecting targets between PR extract and cancer were found, which mainly exerts anticancer effects by regulating tumor necrosis factor (TNF), recombinant caspase 3 (CASP3), c-Jun NH2-terminal kinase (JNK)/JUN, epidermal growth factor receptor (EGFR), and estrogen receptor-1 (ESR1) with some other target genes and pathways associated with cancer. The major anticancer species are prostate cancer, colorectal cancer, small cell lung cancer, etc. In the molecular docking study, herbactin had a strong affinity for TNF. Based on network pharmacology and molecular docking studies, PR and their compounds have demonstrated potential anticancer activities against several key targets. Our preliminary findings provide a strong foundation for further experiments with PR constituents.

Exploration of the Protective Mechanism of Naringin in the Acetaminophen-Induced Hepatic Injury by Metabolomics.

Naringin is a dihydroflavone which was found in citrus fruits. Previous studies have indicated the antiapoptotic, antioxidative stress, and anti-inflammatory effects of naringin. It can improve many common diseases, including fibrosis or hepatotoxicity, cardiovascular disease, and diabetes. Acetaminophen (APAP) is a frequently used painkiller, and hepatotoxic side effects limit its use. The purpose of the current examination is to find the impact of naringin on APAP-induced hepatic injury. Firstly, we pretreated mice model groups with naringin. Then, the liver injury model was established by injecting intraperitoneally into mice with APAP. After the mice were euthanized, we obtained serum and liver tissue samples from the mice. Finally, these samples were analyzed using a metabolomics approach to find the underlying mechanism of the effects of naringin on APAP-induced liver injury and provide a new treatment strategy for APAP-induced liver injury. Our data indicate that naringin significantly improves APAP-induced liver injury in mice and reduces the expression levels of liver injury markers in a dose-dependent manner. Furthermore, analysis of differential metabolites in mice with liver injury showed that naringin reduced APAP-induced hepatotoxicity due to reversing multiple metabolite expression levels and the rescue of energy, amino acid, and purine metabolism.

Dose-response relationship between risk factors and incidence of COVID-19 in 325 hospitalized patients: A multicenter retrospective cohort study.

BACKGROUND: The epidemiological and clinical characteristics of coronavirus disease 2019 (COVID-19) patients have been widely reported, but the assessment of dose-response relationships and risk factors for mortality and severe cases and clinical outcomes remain unclear. AIM: To determine the dose-response relationship between risk factors and incidence of COVID-19. METHODS: In this retrospective, multicenter cohort study, we included patients with confirmed COVID-19 infection who had been discharged or had died by February 6, 2020. We used multivariable logistic regression and Cox proportional hazard models to determine the dose-response relationship between risk factors and incidence of COVID-19. RESULTS: It clarified that increasing risk of in-hospital death were associated with older age (HR: 1.04, 95%CI: 1.01-1.09), higher lactate dehydrogenase [HR: 1.04, 95% confidence interval (CI): 1.01-1.10], C-reactive protein (HR: 1.10, 95%CI: 1.01-1.23), and procalcitonin (natural log-transformed HR: 1.88, 95%CI: 1.22-2.88), and D-dimer greater than 1 µg/mL at admission (natural log transformed HR: 1.63, 95%CI: 1.03-2.58) by multivariable regression. D-dimer and procalcitonin were logarithmically correlated with COVID-19 mortality risk, while there was a linear dose-response correlation between age, lactate dehydrogenase, D-dimer and procalcitonin, independent of established risk factors. CONCLUSION: Higher lactate dehydrogenase, D-dimer, and procalcitonin levels were independently associated with a dose-response increased risk of COVID-19 mortality.

Research Progress on G-Quadruplexes in Human Telomeres and Human Telomerase Reverse Transcriptase (hTERT) Promoter.

The upregulation telomerase activity is observed in over 85-90% of human cancers and provides an attractive target for cancer therapies. The high guanine content in the telomere DNA sequences and the hTERT promoter can form G-quadruplexes (G4s). Small molecules targeting G4s in telomeres and hTERT promoter could stabilize the G4s and inhibit hTERT expression and telomere extension. Several G4 ligands have shown inhibitory effects in cancer cells and xenograft mouse models, indicating these ligands have a potential for cancer therapies. The current review article describes the concept of the telomere, telomerase, and G4s. Moreover, the regulation of telomerase and G4s in telomeres and hTERT promoter is discussed as well. The summary of the small molecules targeting G4s in telomeric DNA sequences and the hTERT promoter will also be shown.

Maximum chest CT score is associated with progression to severe illness in patients with COVID-19: a retrospective study from Wuhan, China.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic is a world-wide health crisis. Limited information is available regarding which patients will experience more severe disease symptoms. We evaluated hospitalized patients who were initially diagnosed with moderate COVID-19 for clinical parameters and radiological feature that showed an association with progression to severe/critical symptoms. METHODS: This study, a retrospective single-center study at the Central Hospital of Wuhan, enrolled 243 patients with confirmed COVID-19 pneumonia. Forty of these patients progressed from moderate to severe/critical symptoms during follow up. Demographic, clinical, laboratory, and radiological data were extracted from electronic medical records and compared between moderate- and severe/critical-type symptoms. Univariable and multivariable logistic regressions were used to identify the risk factors associated with symptom progression. RESULTS: Patients with severe/critical symptoms were older (p < 0.001) and more often male (p = 0.046). A combination of chronic obstructive pulmonary disease (COPD) and high maximum chest computed tomography (CT) score was associated with disease progression. Maximum CT score (> 11) had the greatest predictive value for disease progression. The area under the receiver operating characteristic curve was 0.861 (95% confidence interval: 0.811-0.902). CONCLUSIONS: Maximum CT score and COPD were associated with patient deterioration. Maximum CT score (> 11) was associated with severe illness.

Asymmetric polyamide nanofilms with highly ordered nanovoids for water purification.

Tailor-made structure and morphology are critical to the highly permeable and selective polyamide membranes used for water purification. Here we report an asymmetric polyamide nanofilm having a two-layer structure, in which the lower is a spherical polyamide dendrimer porous layer, and the upper is a polyamide dense layer with highly ordered nanovoids structure. The dendrimer porous layer was covalently assembled in situ on the surface of the polysulfone (PSF) support by a diazotization-coupling reaction, and then the asymmetric polyamide nanofilm with highly ordered hollow nanostrips structure was formed by interfacial polymerization (IP) thereon. Tuning the number of the spherical dendrimer porous layers and IP time enabled control of the nanostrips morphology in the polyamide nanofilm. The asymmetric polyamide membrane exhibits a water flux of 3.7-4.3 times that of the traditional monolayer polyamide membrane, showing an improved divalent salt rejection rate (more than 99%), which thus surpasses the upper bound line of the permeability-selectivity performance of the existing various structural polyamide membranes. We estimate that this work might inspire the preparation of highly permeable and selective reverse osmosis (RO), organic solvent nanofiltration (OSNF) and pervaporation (PV) membranes.

Development of a clinical decision support system for severity risk prediction and triage of COVID-19 patients at hospital admission: an international multicentre study.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. OBJECTIVE: To develop and validate a machine-learning model based on clinical features for severity risk assessment and triage for COVID-19 patients at hospital admission. METHOD: 725 patients were used to train and validate the model. This included a retrospective cohort from Wuhan, China of 299 hospitalised COVID-19 patients from 23 December 2019 to 13 February 2020, and five cohorts with 426 patients from eight centres in China, Italy and Belgium from 20 February 2020 to 21 March 2020. The main outcome was the onset of severe or critical illness during hospitalisation. Model performances were quantified using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix. RESULTS: In the retrospective cohort, the median age was 50 years and 137 (45.8%) were male. In the five test cohorts, the median age was 62 years and 236 (55.4%) were male. The model was prospectively validated on five cohorts yielding AUCs ranging from 0.84 to 0.93, with accuracies ranging from 74.4% to 87.5%, sensitivities ranging from 75.0% to 96.9%, and specificities ranging from 55.0% to 88.0%, most of which performed better than the pneumonia severity index. The cut-off values of the low-, medium- and high-risk probabilities were 0.21 and 0.80. The online calculators can be found at www.covid19risk.ai. CONCLUSION: The machine-learning model, nomogram and online calculator might be useful to access the onset of severe and critical illness among COVID-19 patients and triage at hospital admission.

The prognostic value of combining the CD8 + lymphocyte density and the circulating lymphocyte ratio in circumferential resection margin biopsy in rectal cancer.

BACKGROUND: A positive circumferential resection margin (CRM) may result in local recurrence (LR), but the significance remains controversial. We attempted to utilize the lymphocyte ratio (LYMR), neutrophil-lymphocyte ratio (NLR), tumor-infiltrating lymphocyte (TIL) count, and their combinations (TIL-LYMR/TIL-NLR) in predicting LR after rectal resection. METHODS: Patients with rectal cancer who underwent curative resection between January 2016 and December 2018 were enrolled. Biopsy samples and data from the blood tests of 124 patients with rectal cancer who underwent curative resection were retrospectively obtained. Patients were divided into 2 groups: LR group and non-local recurrence (nLR) group. CD8 + TILs were immunostained using an antibody against CD8. The density of TILs was defined as the number of positive CD8 lymphocytes per square millimeter and was then graded as either high or low (cutoff = 80/mm). The count of LYMR and NLR was also graded as either high or low. The associations between TILs, LYMR, NLR, and their combinations (TIL-LYMR/TIL-NLR) were evaluated. RESULTS: With a median follow-up of 24.4 months, TIL-LYMR showed a positive correlation with LR (P = .001), but not with the CD8 + TIL count (P = .215) or TIL-NLR count (P = .638). Among inflammatory and immune markers variables, univariate analysis revealed that gender, CD8 + TIL count, and TIL-NLR count were associated with anastomotic leakage (P = .001, P = .014, and P = .036, respectively). In multivariate analysis, TIL-LYMR remained an independent predictor of LR (OR = 8.918, CI = 1.124-70.747, P = .038). We also showed that gender associated with anastomotic leakage in rectal cancer (OR 5.429; 95% CI 1.885-15.637; P = .002). CONCLUSION: In this study, our data indicate that absence of CD8 + T-cell infiltration in CRM may influence LR. These parameters may help identify LR provide additional information for therapeutic decision-making.

Comparative analysis of the male inflorescence transcriptome profiles of an ms22 mutant of maize.

In modern agricultural production, maize is the most successful crop utilizing heterosis. 712C-ms22 is an important male sterile material in maize. In this study, we performed transcriptome sequencing analysis of the V10 stage of male inflorescence. Through this analysis, 27.63 million raw reads were obtained, and trimming of the raw data revealed 26.63 million clean reads, with an average match rate of 94.64%. Using Tophat software, we matched these clean reads to the maize reference genome. The abundance of 39,622 genes was measured, and 35,399 genes remained after filtering out the non-expressed genes across all the samples. These genes were classified into 19 categories by clusters of orthologous groups of protein annotation. Transcriptome sequencing analysis of the male sterile and fertile 712C-ms22 maize revealed some key DEGs that may be related to metabolic pathways. qRT-PCR analysis validated the gene expression patterns identified by RNA-seq. This analysis revealed some of the essential genes responsible for pollen development and for pollen tube elongation. Our findings provide useful markers of male sterility and new insights into the global mechanisms mediating male sterility in maize.