Quantitative Trait Loci Sequencing and Genetic Mapping Reveal Two Main Regulatory Genes for Stem Color in Wax Gourds.

Stem color is an important agronomic trait of wax gourds. However, its regulatory genes have not been identified. In this study, 105 inbred lines constructed from two parents (GX-71 and MY-1) were sequenced and quantitative trait loci sequencing was used to mine the genes that regulate stem color in wax gourds. The results identified two quantitative trait loci related to stem color, qSC5 and qSC12, located on Chr05 (11,134,567-16,459,268) and Chr12 (74,618,168-75,712,335), respectively. The qSC5 had a phenotypic variation rate of 36.9% and a maximum limit of detection of 16.9. And the qSC12 had a phenotypic variation rate of 20.9%, and a maximum limit of detection of 11.2. Bch05G003950 (named BchAPRR2) and Bch12G020400 were identified as candidate genes involved in stem color regulation in wax gourds. The chlorophyll content and expression of BchAPRR2 and Bch12G020400 were significantly higher in green-stemmed wax gourds than in white-stemmed ones. Therefore, BchAPRR2 and Bch12G020400 were considered the main and secondary regulatory genes for wax gourd stem color, respectively. Finally, InDel markers closely linked to BchAPRR2 were developed to validate the prediction of wax gourd stem color traits in 55 germplasm lines, with an accuracy of 81.8%. These findings lay the foundation for exploring the genetic regulation of wax gourd stem color and future research on wax gourd breeding.

The haplotype-resolved genome of diploid Chrysanthemum indicum unveils new acacetin synthases genes and their evolutionary history.

Acacetin, a flavonoid compound, possesses a wide range of pharmacological effects, including antimicrobial, immune regulation, and anticancer effects. Some key steps in its biosynthetic pathway were largely unknown in flowering plants. Here, we present the first haplotype-resolved genome of Chrysanthemum indicum, whose dried flowers contain abundant flavonoids and have been utilized as traditional Chinese medicine. Various phylogenetic analyses revealed almost equal proportion of three tree topologies among three Chrysanthemum species (C. indicum, C. nankingense, and C. lavandulifolium), indicating that frequent gene flow among Chrysanthemum species or incomplete lineage sorting due to rapid speciation might contribute to conflict topologies. The expanded gene families in C. indicum were associated with oxidative functions. Through comprehensive candidate gene screening, we identified five flavonoid O-methyltransferase (FOMT) candidates, which were highly expressed in flowers and whose expressional levels were significantly correlated with the content of acacetin. Further experiments validated two FOMTs (CI02A009970 and CI03A006662) were capable of catalyzing the conversion of apigenin into acacetin, and these two genes are possibly responsible acacetin accumulation in disc florets and young leaves, respectively. Furthermore, combined analyses of ancestral chromosome reconstruction and phylogenetic trees revealed the distinct evolutionary fates of the two validated FOMT genes. Our study provides new insights into the biosynthetic pathway of flavonoid compounds in the Asteraceae family and offers a model for tracing the origin and evolutionary routes of single genes. These findings will facilitate in vitro biosynthetic production of flavonoid compounds through cellular and metabolic engineering and expedite molecular breeding of C. indicum cultivars.

Development and validation of a nomogram for predicting in-hospital survival rates of patients with COVID-19.

Objective: Our aim was to develop and validate a nomogram for predicting the in-hospital 14-day (14 d) and 28-day (28 d) survival rates of patients with coronavirus disease 2019 (COVID-19). Methods: Clinical data of patients with COVID-19 admitted to the Renmin Hospital of Wuhan University from December 2022 to February 2023 and the north campus of Shanghai Ninth People's Hospital from April 2022 to June 2022 were collected. A total of 408 patients from Renmin Hospital of Wuhan University were selected as the training cohort, and 151 patients from Shanghai Ninth People's Hospital were selected as the verification cohort. Independent variables were screened using Cox regression analysis, and a nomogram was constructed using R software. The prediction accuracy of the nomogram was evaluated using the receiver operating characteristic (ROC) curve, C-index, and calibration curve. Decision curve analysis was used to evaluate the clinical application value of the model. The nomogram was externally validated using a validation cohort. Result: In total, 559 patients with severe/critical COVID-19 were included in this study, of whom 179 (32.02 %) died. Multivariate Cox regression analysis showed that age >80 years [hazard ratio (HR) = 1.539, 95 % confidence interval (CI): 1.027-2.306, P = 0.037], history of diabetes (HR = 1.741, 95 % CI: 1.253-2.420, P = 0.001), high APACHE II score (HR = 1.083, 95 % CI: 1.042-1.126, P < 0.001), sepsis (HR = 2.387, 95 % CI: 1.707-3.338, P < 0.001), high neutrophil-to-lymphocyte ratio (NLR) (HR = 1.010, 95 % CI: 1.003-1.017, P = 0.007), and high D-dimer level (HR = 1.005, 95 % CI: 1.001-1.009, P = 0.028) were independent risk factors for 14 d and 28 d survival rates, whereas COVID-19 vaccination (HR = 0.625, 95 % CI: 0.440-0.886, P = 0.008) was a protective factor affecting prognosis. ROC curve analysis showed that the area under the curve (AUC) of the 14 d and 28 d hospital survival rates in the training cohort was 0.765 (95 % CI: 0.641-0.923) and 0.814 (95 % CI: 0.702-0.938), respectively, and the AUC of the 14 d and 28 d hospital survival rates in the verification cohort was 0.898 (95 % CI: 0.765-0.962) and 0.875 (95 % CI: 0.741-0.945), respectively. The calibration curves of 14 d and 28 d hospital survival showed that the predicted probability of the model agreed well with the actual probability. Decision curve analysis (DCA) showed that the nomogram has high clinical application value. Conclusion: In-hospital survival rates of patients with COVID-19 were predicted using a nomogram, which will help clinicians in make appropriate clinical decisions.

Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data.

BACKGROUND: Plant specialized (or secondary) metabolites (PSM), also known as phytochemicals, natural products, or plant constituents, play essential roles in interactions between plants and environment. Although many research efforts have focused on discovering novel metabolites and their biosynthetic genes, the resolution of metabolic pathways and identified biosynthetic genes was limited by rudimentary analysis approaches and enormous number of candidate genes. RESULTS: Here we integrated state-of-the-art automated machine learning (ML) frame AutoGluon-Tabular and multi-omics data from Arabidopsis to predict genes encoding enzymes involved in biosynthesis of plant specialized metabolite (PSM), focusing on the three main PSM categories: terpenoids, alkaloids, and phenolics. We found that the related features of genomics and proteomics were the top two crucial categories of features contributing to the model performance. Using only these key features, we built a new model in Arabidopsis, which performed better than models built with more features including those related with transcriptomics and epigenomics. Finally, the built models were validated in maize and tomato, and models tested for maize and trained with data from two other species exhibited either equivalent or superior performance to intraspecies predictions. CONCLUSIONS: Our external validation results in grape and poppy on the one hand implied the applicability of our model to the other species, and on the other hand showed enormous potential to improve the prediction of enzymes synthesizing PSM with the inclusion of valid data from a wider range of species.

Histone deacetylase Sir2 promotes the systemic Candida albicans infection by facilitating its immune escape via remodeling the cell wall and maintaining the metabolic activity.

Histone deacetylation affects Candida albicans (C. albicans) pathogenicity by modulating virulence factor expression and DNA damage. The histone deacetylase Sir2 is associated with C. albicans plasticity and maintains genome stability to help C. albicans adapt to various environmental niches. However, whether Sir2-mediated chromatin modification affects C. albicans virulence is unclear. The purpose of our study was to investigate the effect of Sir2 on C. albicans pathogenicity and regulation. Here, we report that Sir2 is required for C. albicans pathogenicity, as its deletion affects the survival rate, fungal burden in different organs and the extent of tissue damage in a mouse model of disseminated candidiasis. We evaluated the impact of Sir2 on C. albicans virulence factors and revealed that the Sir2 null mutant had an impaired ability to adhere to host cells and was more easily recognized by the innate immune system. Comprehensive analysis revealed that the disruption of C. albicans adhesion was due to a decrease in cell surface hydrophobicity rather than the differential expression of adhesion genes on the cell wall. In addition, Sir2 affects the distribution and exposure of mannan and ß-glucan on the cell wall, indicating that Sir2 plays a role in preventing the immune system from recognizing C. albicans. Interestingly, our results also indicated that Sir2 helps C. albicans maintain metabolic activity under hypoxic conditions, suggesting that Sir2 contributes to C. albicans colonization at hypoxic sites. In conclusion, our findings provide detailed insights into antifungal targets and a useful foundation for the development of antifungal drugs. IMPORTANCE: Candida albicans (C. albicans) is the most common opportunistic fungal pathogen and can cause various superficial infections and even life-threatening systemic infections. To successfully propagate infection, this organism relies on the ability to express virulence-associated factors and escape host immunity. In this study, we demonstrated that the histone deacetylase Sir2 helps C. albicans adhere to host cells and escape host immunity by mediating cell wall remodeling; as a result, C. albicans successfully colonized and invaded the host in vivo. In addition, we found that Sir2 contributes to carbon utilization under hypoxic conditions, suggesting that Sir2 is important for C. albicans survival and the establishment of infection in hypoxic environments. In summary, we investigated the role of Sir2 in regulating C. albicans pathogenicity in detail; these findings provide a potential target for the development of antifungal drugs.

Dracocephalum moldavica L. extract alleviates experimental colitis in rats by modulating gut microbiome and inflammatory pathways.

Several studies have revealed that an imbalance of the intestinal microbiota is involved in intestinal inflammation associated with ulcerative colitis (UC). Therefore, regulating the homeostasis of gut microbiota is critical for treating UC. Dracocephalum moldavica L. (DML) extract, a common traditional Chinese medicine, has been demonstrated to possess numerous pharmacological effects, such as antioxidative, anti­inflammatory, and antibacterial properties. The aim of the present study was to evaluate the beneficial effects of DML extract and the probable mechanism of action in a dextran sulfate sodium­induced chronic colitis model. It was found that DML extract ameliorated UC by improving disease activity index, weight loss, colon length, and histological scoring. DML extract administration also enhanced the count of Lactobacillus and reduced the count of Romboutsia. Furthermore, the results of network pharmacology analysis revealed that the active ingredients (including luteolin, rosmarinic acid, oleanolic acid, ursolic acid, apigenin, acacetin, kaempferol, and isorhamnetin) in the DML extract were closely associated with anti­inflammatory activity via various signaling pathways, including the NF­κB, IL­17, TNF, and Toll­like receptor (TLR) signaling pathways. Western blot analysis further indicated that DML extract downregulated the expression of members of the TLR4/NF­κB signaling pathway, which was associated with colitis. Thus, it was hypothesized that DML extract exerted its anti­colitis effects by modulating the gut microbiota and inflammatory pathways.

Fine mapping of the major gene BhHLS1 controlling seed size in wax gourd (Benincasa hispida).

Introduction/Background: The seed size of wax gourds is an important agronomic trait; however, the associated genes have not yet been reported. Methods: In this study, we used a high-density genetic map constructed based on F8 recombinant inbred line populations derived from a cross between MY-1 (large seed) and GX-71 (small seed) strains to detect quantitative trait locis (QTLs) for seed-size-related traits in wax gourd over a two-year period. Results: Two stable QTLs (qSL10 and qSW10) for seed length (SL) and seed width (SW) on chromosome 10 were repeatedly detected over two years (2021-2022). qSL10 had a phenotypic variation rate of 75.30% and 80.80% in 2021 and 2022, respectively. Whereas, qSW10 had a phenotypic variation rate of 66.60% and 73.80% in 2021 and 2022, respectively. Further, a single nucleotide polymorphism mutation was found to cause early termination of Bch10G006400 (BhHLS1) translation in GX-71 through sequencing analysis of candidate genes. Based on gene functional annotation and quantitative real-time PCR analyses, BhHLS1 encoded a probable N-acetyltransferase HLS1-like protein and its expression level was significantly different between parents. Therefore, BhHLS1 is a major candidate gene associated with a one-factor polymorphism regulating the SL and SW of wax gourds. Finally, based on variation in the BhHLS1 sequence, a cleaved amplified polymorphic sequence marker was developed for the molecular marker-assisted breeding of wax gourds. Discussion: Overall, this study is of great significance for the genetic improvement of seed size, verification of gene functions, and cultivation of specific germplasm resources for wax gourds.

Phosphorus deficiency is the main limiting factor for re-vegetation and soil microorganisms in Mu Us Sandy Land, Northwest China.

Long-term drought induced by low rainfall leads to environmental degradation of land in arid and semi-arid regions. In past decades, re-vegetation of degraded sandy soils to prevent soil erosion has been widely employed, including in Mu Us Sandy Land, which suffers from severe soil erosion. However, it remains unclear how re-vegetation affects soil properties and soil microbes after long restoration periods. In this study, typical plots planting Artemisia ordosica and Salix psammophila were selected to investigate the influence of plant types on soil properties; an area of bare sandy land was used as a control. The results show that re-vegetation increased soil organic carbon (C), total nitrogen (N), soil microbial carbon, microbial nitrogen and soil organic acid, while decreasing soil total phosphorous (TP) content significantly, resulting in increased C/P and N/P ratios. Correlation analysis showed that TP was negatively correlated with oxalic acid (OA) and acetic acid (AA), indicating that increased AA and OA content could accelerate the active utilization of phosphorus and induced low TP in soil. Re-vegetation with A. ordosica significantly decreased the microbial diversity of topsoil. The redundancy analysis showed that TP was main index in affecting microbes. These results that lower P content, higher C/P and N/P ratio and influence of TP on microbes suggest that phosphorus is the main limiting factor for re-vegetation and growth of soil microorganisms. In the future, strategies for the development of sustainable ecosystems in regions suffers from severe soil erosion should consider phosphorus supplementation.

Development and Validation of a Nomograph Model for Post-Operative Central Nervous System Infection after Craniocerebral Surgery.

PURPOSE: A nomograph model of predicting the risk of post-operative central nervous system infection (PCNSI) after craniocerebral surgery was established and validated. METHODS: The clinical medical records of patients after cranial surgery in Renmin Hospital of Wuhan University from January 2020 to September 2022 were collected, of whom 998 patients admitted to Shouyi Hospital District were used as the training set and 866 patients admitted to Guanggu Hospital District were used as the validation set. Lasso regression was applied to screen the independent variables in the training set, and the model was externally validated in the validation set. RESULTS: A total of 1864 patients after craniocerebral surgery were included in this study, of whom 219 (11.75%) had PCNSI. Multivariate logistic regression analysis showed that age > 70 years, a previous history of diabetes, emergency operation, an operation time ≥ 4 h, insertion of a lumbar cistern drainage tube ≥ 72 h, insertion of an intracranial drainage tube ≥ 72 h, intraoperative blood loss ≥ 400 mL, complicated with shock, postoperative albumin ≤ 30 g/L, and an ICU length of stay ≥ 3 days were independent risk factors for PCNSI. The area under the curve (AUC) of the training set was 0.816 (95% confidence interval (95%CI), 0.773-0.859, and the AUC of the validation set was 0.760 (95%CI, 0.715-0.805). The calibration curves of the training set and the validation set showed p-values of 0.439 and 0.561, respectively, with the Hosmer-Lemeshow test. The analysis of the clinical decision curve showed that the nomograph model had high clinical application value. CONCLUSION: The nomograph model constructed in this study to predict the risk of PCNSI after craniocerebral surgery has a good predictive ability.

Palliative care needs and specialist services post stroke: national population-based study.

OBJECTIVES: (1) To compare palliative care needs of patients admitted primarily with stroke and (2) to determine how the care needs of these patients affect their use of different types of specialist palliative care services. METHODS: Observational study based on point-of-care data from the Australian Palliative Care Outcomes Collaboration. Multivariate logistic regression models were used to explore the association between patients' palliative care needs and use of community versus inpatient specialist palliative care services. RESULTS: The majority of patients who had a stroke in this study population had mild or no symptom distress, but experienced a high degree of functional impairment and needed substantial help with basic tasks of daily living. A lower Australia-modified Karnofsky Performance Status score (OR=1.82, 95% CI 1.06 to 3.13) and occurrence of an 'unstable' palliative care phase (OR=28.34, 95% CI 9.03 to 88.94) were associated with use of inpatient versus community palliative care, but otherwise, no clear association was observed between the majority of symptoms and use of different care services. CONCLUSIONS: Many people with stroke could potentially have been cared for and could have experienced the terminal phases of their condition in a community setting if more community support services were available for their families.

Numerical Simulation of Physical Fields during Spark Plasma Sintering of Boron Carbide.

Spark plasma sintering is a new technology for preparing ceramic materials. In this article, a thermal-electric-mechanical coupled model is used to simulate the spark plasma sintering process of boron carbide. The solution of the thermal-electric part was based on the charge conservation equation and the energy conservation equation. A phenomenological constitutive model (Drucker-Prager Cap model) was used to simulate the densification process of boron carbide powder. To reflect the influence of temperature on sintering performance, the model parameters were set as functions of temperature. Spark plasma sintering experiments were conducted at four temperatures: 1500 °C, 1600 °C, 1700 °C, and 1800 °C, and the sintering curves were obtained. The parameter optimization software was integrated with the finite element analysis software, and the model parameters at different temperatures were obtained through the parameter inverse identification method by minimizing the difference between the experimental displacement curve and the simulated displacement curve. The Drucker-Prager Cap model was then incorporated into the coupled finite element framework to analyze the changes of various physical fields of the system over time during the sintering process.

A Nomogram Model for Prediction of Mortality Risk of Patients with Dangerous Upper Gastrointestinal Bleeding: A Two-center Retrospective Study.

OBJECTIVE: This study aimed to establish a nomogram model to predict the mortality risk of patients with dangerous upper gastrointestinal bleeding (DUGIB), and identify high-risk patients who require emergent therapy. METHODS: From January 2020 to April 2022, the clinical data of 256 DUGIB patients who received treatments in the intensive care unit (ICU) were retrospectively collected from Renmin Hospital of Wuhan University (n=179) and the Eastern Campus of Renmin Hospital of Wuhan University (n=77). The 179 patients were treated as the training cohort, and 77 patients as the validation cohort. Logistic regression analysis was used to calculate the independent risk factors, and R packages were used to construct the nomogram model. The prediction accuracy and identification ability were evaluated by the receiver operating characteristic (ROC) curve, C index and calibration curve. The nomogram model was also simultaneously externally validated. Decision curve analysis (DCA) was then used to demonstrate the clinical value of the model. RESULTS: Logistic regression analysis showed that hematemesis, urea nitrogen level, emergency endoscopy, AIMS65, Glasgow Blatchford score and Rockall score were all independent risk factors for DUGIB. The ROC curve analysis indicated the area under curve (AUC) of the training cohort was 0.980 (95%CI: 0.962-0.997), while the AUC of the validation cohort was 0.790 (95%CI:0.685-0.895). The calibration curves were tested for Hosmer-Lemeshow goodness of fit for both training and validation cohorts (P=0.778, P=0.516). CONCLUSION: The developed nomogram is an effective tool for risk stratification, early identification and intervention for DUGIB patients.

Diel dynamics of multi-omics in elkhorn fern provide new insights into weak CAM photosynthesis.

Crassulacean acid metabolism (CAM) has high water-use efficiency (WUE) and is widely recognized to have evolved from C3 photosynthesis. Different plant lineages have convergently evolved CAM, but the molecular mechanism that underlies C3-to-CAM evolution remains to be clarified. Platycerium bifurcatum (elkhorn fern) provides an opportunity to study the molecular changes underlying the transition from C3 to CAM photosynthesis because both modes of photosynthesis occur in this species, with sporotrophophyll leaves (SLs) and cover leaves (CLs) performing C3 and weak CAM photosynthesis, respectively. Here, we report that the physiological and biochemical attributes of CAM in weak CAM-performing CLs differed from those in strong CAM species. We investigated the diel dynamics of the metabolome, proteome, and transcriptome in these dimorphic leaves within the same genetic background and under identical environmental conditions. We found that multi-omic diel dynamics in P. bifurcatum exhibit both tissue and diel effects. Our analysis revealed temporal rewiring of biochemistry relevant to the energy-producing pathway (TCA cycle), CAM pathway, and stomatal movement in CLs compared with SLs. We also confirmed that PHOSPHOENOLPYRUVATE CARBOXYLASE KINASE (PPCK) exhibits convergence in gene expression among highly divergent CAM lineages. Gene regulatory network analysis identified candidate transcription factors regulating the CAM pathway and stomatal movement. Taken together, our results provide new insights into weak CAM photosynthesis and new avenues for CAM bioengineering.

Taurohyodeoxycholic acid alleviates trinitrobenzene sulfonic acid induced ulcerative colitis via regulating Th1/Th2 and Th17/Treg cells balance.

AIMS: Taurohyodeoxycholic acid (THDCA), a natural 6α-hydroxylated bile acid, exhibits intestinal anti-inflammatory effects. This study aimed to explore the efficacy of THDCA on ulcerative colitis and to reveal its mechanisms of action. MAIN METHODS: Colitis was induced by intrarectal administration of trinitrobenzene sulfonic acid (TNBS) to mice. Mice in the treatment group were gavage THDCA (20, 40, and 80 mg/kg/day) or sulfasalazine (500 mg/kg/day) or azathioprine (10 mg/kg/day). The pathologic markers of colitis were comprehensively assessed. The levels of Th1-/Th2-/Th17-/Treg-related inflammatory cytokines and transcription factors were detected by ELISA, RT-PCR, and Western blotting. The balance of Th1/Th2 and Th17/Treg cells was analyzed by Flow cytometry. KEY FINDINGS: THDCA significantly alleviated colitis by improving the body weight, colon length, spleen weight, histological characteristics, and MPO activity of colitis mice. THDCA reduced the secretion of Th1-/Th17-related cytokines (IFN-γ, IL-12p70, IL-6, IL-17A, IL-21, IL-22, and TNF-α) and the expressions of transcription factors (T-bet, STAT4, RORγt, and STAT3), but increase the production of Th2-/Treg-related cytokines (IL-4, IL-10, and TGF-ß1) and the expressions of transcription factors (GATA3, STAT6, Foxp3, and Smad3) in the colon. Meanwhile, THDCA inhibited the expressions of IFN-γ, IL-17A, T-bet, and RORγt, but improved the expression of IL-4, IL-10, GATA3, and Foxp3 in the spleen. Furthermore, THDCA restored the proportion of Th1, Th2, Th17, and Treg cells, and balanced the Th1/Th2 and Th17/Treg immune response of colitis mice. SIGNIFICANCE: THDCA can alleviate TNBS-induced colitis via regulating Th1/Th2 and Th17/Treg balance, which may represent a promising treatment for patients with colitis.

Establishment of a Rat Model of Liver Venous Deprivation: Simultaneous Portal and Hepatic Vein Ligation.

Background and Aims: The aim was to establish a liver venous deprivation (LVD) model in rats, compare hepatic hypertrophy between LVD and associated liver partition and portal vein ligation for staged hepatectomy (ALPPS), and explore the underlying mechanisms. Methods: The LVD or extended-LVD (e-LVD) group received portal vein ligation (PVL) combined with hepatic vein ligation (HVL). The ALPPS or e-ALPPS group received PVL plus parenchyma ligation. Liver regeneration was assessed by measuring the liver weight and performing pathological analysis. Liver functions and the sphingosine kinase 1 (SPHK1)/sphingosine-1-phosphate (S1P)/sphingosine-1-phosphate receptor 1 (S1PR1) pathway were also investigated. Results: All future liver remnants (FLRs) in the ALPPS, e-ALPPS, LVD, and e-LVD groups exhibited significant hypertrophy compared with the control group. The LVD and e-LVD procedures induced similar liver hypertrophy than that in the corresponding ALPPS groups. Furthermore, the LVD and e-LVD methods led to obvious cytolysis in the venous-deprived lobes as well as a noticeable increase in serum transaminase levels, while no necrosis was observed in the ALPPS and e-ALPPS groups. SPHK1/S1P/S1PR1 pathway were distinctly activated after operation, especially in congestive/ischemic livers. Conclusions: We describe the first rat model of LVD and e-LVD with simultaneously associated HVL and PVL. Compared with the ALPPS technique, the LVD or e-LVD procedure had a comparable overall effect on the hypertrophy response and a stronger effect on liver function. The SPHK1/S1P/S1PR1 pathway was involved in the LVD- or ALPPS-induced liver remodeling.

Construction and Validation of Mortality Risk Nomograph Model for Severe/Critical Patients with COVID-19.

Objective: A nomograph model of mortality risk for patients with coronavirus disease 2019 (COVID-19) was established and validated. Methods: We collected the clinical medical records of patients with severe/critical COVID-19 admitted to the eastern campus of Renmin Hospital of Wuhan University from January 2020 to May 2020 and to the north campus of Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, from April 2022 to June 2022. We assigned 254 patients to the former group, which served as the training set, and 113 patients were assigned to the latter group, which served as the validation set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the variables and build the mortality risk prediction model. Results: The nomogram model was constructed with four risk factors for patient mortality following severe/critical COVID-19 (≥3 basic diseases, APACHE II score, urea nitrogen (Urea), and lactic acid (Lac)) and two protective factors (percentage of lymphocyte (L%) and neutrophil-to-platelets ratio (NPR)). The area under the curve (AUC) of the training set was 0.880 (95% confidence interval (95%CI), 0.837~0.923) and the AUC of the validation set was 0.814 (95%CI, 0.705~0.923). The decision curve analysis (DCA) showed that the nomogram model had high clinical value. Conclusion: The nomogram model for predicting the death risk of patients with severe/critical COVID-19 showed good prediction performance, and may be helpful in making appropriate clinical decisions for high-risk patients.

Protein succinylation associated with the progress of hepatocellular carcinoma.

Although post-translational modification is critical to tumorigenesis, how succinylation modification of lysine sites influences hepatocellular carcinoma (HCC) remains obscure. 90 tumours and paired adjacent normal tissue of liver cancer were enrolled for succinylation staining. 423 HCC samples with 20 genes related to succinylation modification from TCGA were downloaded for model construction. Statistical methods were employed to analyse the data, including the Non-Negative Matrix Factorization (NMF) algorithm, t-Distributed Stochastic Neighbour Embedding (t-SNE) algorithm, and Cox regression analysis. The staining pan-succinyllysine antibody staining indicated that tumour tissues had a higher succinyllysine level than adjacent tissues (p < 0.001), which could be associated with a worse prognosis (p = 0.02). The survival was associated with pathological stage, tumour recurrence status and succinyllysine intensity in the univariate or multivariable cox survival analysis model. The risk model from 20 succinyllysine-related genes had the best prognosis prediction. The high expression of succinylation modification in HCC contributed to the worse patient survival prognosis. Model construction of 20 genes related to succinylation modification (MEAF6, OXCT1, SIRT2, CREBBP, KAT5, SIRT4, SIRT6, SIRT7, CPT1A, GLYATL1, SDHA, SDHB, SDHC, SDHD, SIRT1, SIRT3, SIRT5, SUCLA2, SUCLG1 and SUCLG2) could be reliable in predicting prognosis in HCC.

Identification of Prognostic Genes in Hepatocellular Carcinoma.

Background: Previous studies have demonstrated the important role of tumor stem cells (TSCs) in the development of hepatocellular carcinoma (HCC); however, TSC-related genetic markers have not been investigated. Aim: The aim of the present study was to identify stem cell-related signature genes to predict the prognosis of HCC, using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Methods: In total, 423 liver HCC tissue samples, including 373 tumor and 50 adjacent normal tissue samples from TCGA, and 115 primary tumor and 52 adjacent non-tumor tissue samples from the GEO GSE76427 database, were used in the present study. The non-negative matrix factorization (NMF) algorithm, t-distributed stochastic neighbor embedding (t-SNE) algorithm and Cox regression analysis were combined for model construction and validation. Results: Overall, six clusters were identified using the NMF and t-SNE algorithms with 470 stem cell-related genes. The results demonstrated that patients in cluster 5 had the worst prognosis. For multivariate Cox survival analysis, 15 genes with optimal lambda values were chosen and eight genes were incorporated into the final regression model using the optimal Akaike information criterion value. Validation of the risk model using the aforementioned eight signature genes demonstrated the models strong reliability and stable predictive performance. Conclusion: The results of the present study indicated that the eight-gene (Hes family BHLH transcription factor 5, KIT ligand, methyltransferase-like 3, proteasome 26S subunit non-ATPase 1, Ras-related protein Rab-10, treacle ribosome biogenesis factor 1, YTH N6-methyladenosine RNA binding protein 2 and Zinc Finger CCCH-Type Containing 13) signature constructed by the model may be reliable in predicting the prognosis of patients with HCC.

Evidence-based practice implementation in healthcare in China: a living scoping review.

BACKGROUND: Evidence-based practice (EBP) implementation plays a crucial role in bridging the knowledge-action gaps and reducing health inequities. Little is known about its development in China. This study aims to provide an overview of the EBP implementation research progress in healthcare in China and identify gaps for future studies. METHODS: We conducted a scoping review following the Joanna Briggs Institute scoping review methodology and the Cochrane Collaboration's guidance on living reviews. We performed a literature search in four Chinese databases (i.e., China National Knowledge Infrastructure, Wan Fang Database, The VIP Database, and China Biology Medicine) and three English databases (i.e., Ovid MEDLINE, the Cumulative Index to Nursing and Allied Health Literature, and EMBASE), Google scholar, and Baidu scholar from 1996 to 2021. We included EBP implementation studies conducted in healthcare settings in China and were published in Chinese and English literature. The search will be run on a regular basis to monitor the development of new literature and determine when to update the review. FINDINGS: Of the 11,276 records identified, we finally included 309 papers. The publications were on a sharp rise since 2013 and were predominantly from the nursing field (292/309, 94.50%). The commonly researched areas were symptom management (75/309, 24.27%), tube care (46/309, 14.89%), perioperative care (43/309, 13.92%), and fundamental care (43/309, 13.92%). Joanna Briggs Institute model was the most frequently used model to guide the implementation process (92/159, 59.75%). A median number of 8 people often comprised an implementation team, with 113 studies (36.57%) taking a multidisciplinary approach. 204 studies reported utilizing audit criteria to assist evaluation of evidence implementation rate with diversified methods measuring the criteria. Lack of knowledge, skills, and resources, and incomplete procedures or pathways were top barriers impeding EBP implementation. Leadership support was considered the most common facilitator. Education and training were the most frequently described implementation strategies for healthcare professionals and patients. Optimizing workflows and developing evaluation tools were the primary strategies adopted by organizations. 291 studies measured patient outcomes and 174 studies measured healthcare professional outcomes. INTERPRETATION: To our knowledge, this scoping review is the first one to systematically examine the EBP implementation research progress in healthcare in China. Based on this review, we identified contributions that Chinese EBP implementation research made to the global community, and provided eight recommendations for Chinese researchers in conducting implementation studies in the future. FUNDING: None.