Development of a Comprehensive Genotype-to-Fitness Map of Adaptation-Driving Mutations in Yeast.

Adaptive evolution plays a large role in generating the phenotypic diversity observed in nature, yet current methods are impractical for characterizing the molecular basis and fitness effects of large numbers of individual adaptive mutations. Here, we used a DNA barcoding approach to generate the genotype-to-fitness map for adaptation-driving mutations from a Saccharomyces cerevisiae population experimentally evolved by serial transfer under limiting glucose. We isolated and measured the fitness of thousands of independent adaptive clones and sequenced the genomes of hundreds of clones. We found only two major classes of adaptive mutations: self-diploidization and mutations in the nutrient-responsive Ras/PKA and TOR/Sch9 pathways. Our large sample size and precision of measurement allowed us to determine that there are significant differences in fitness between mutations in different genes, between different paralogs, and even between different classes of mutations within the same gene.

Candida albicans' inorganic phosphate transport and evolutionary adaptation to phosphate scarcity.

Phosphorus is essential in all cells' structural, metabolic and regulatory functions. For fungal cells that import inorganic phosphate (Pi) up a steep concentration gradient, surface Pi transporters are critical capacitators of growth. Fungi must deploy Pi transporters that enable optimal Pi uptake in pH and Pi concentration ranges prevalent in their environments. Single, triple and quadruple mutants were used to characterize the four Pi transporters we identified for the human fungal pathogen Candida albicans, which must adapt to alkaline conditions during invasion of the host bloodstream and deep organs. A high-affinity Pi transporter, Pho84, was most efficient across the widest pH range while another, Pho89, showed high-affinity characteristics only within one pH unit of neutral. Two low-affinity Pi transporters, Pho87 and Fgr2, were active only in acidic conditions. Only Pho84 among the Pi transporters was clearly required in previously identified Pi-related functions including Target of Rapamycin Complex 1 signaling, oxidative stress resistance and hyphal growth. We used in vitro evolution and whole genome sequencing as an unbiased forward genetic approach to probe adaptation to prolonged Pi scarcity of two quadruple mutant lineages lacking all 4 Pi transporters. Lineage-specific genomic changes corresponded to divergent success of the two lineages in fitness recovery during Pi limitation. Initial, large-scale genomic alterations like aneuploidies and loss of heterozygosity eventually resolved, as populations gained small-scale mutations. Severity of some phenotypes linked to Pi starvation, like cell wall stress hypersensitivity, decreased in parallel to evolving populations' fitness recovery in Pi scarcity, while severity of others like membrane stress responses diverged from Pi scarcity fitness. Among preliminary candidate genes for contributors to fitness recovery, those with links to TORC1 were overrepresented. Since Pi homeostasis differs substantially between fungi and humans, adaptive processes to Pi deprivation may harbor small-molecule targets that impact fungal growth, stress resistance and virulence.

Knockdown of LncRNA Lcn2-204 alleviates sepsis-induced myocardial injury by regulation of iron overload and ferroptosis.

Ferroptosis is an iron-dependent programmed cell death form resulting from lipid peroxidation damage, it plays a key role in organ damage and tumor development from various causes. Sepsis leads to severe host response after infection with high mortality. The long non-coding RNAs (LncRNAs) are involved in different pathophysiological mechanisms of multiple diseases. Here, we used cecal ligation and puncture (CLP) operation to mimic sepsis induced myocardial injury (SIMI) in mouse model, and LncRNAs and mRNAs were profiled by Arraystar mouse LncRNA Array V3.0. Based on the microarray results, 552 LncRNAs and 520 mRNAs were differentially expressed in the sham and CLP groups, among them, LncRNA Lcn2-204 was the highest differentially expressed up-regulated LncRNA. Iron metabolism disorder was involved in SIMI by bioinformatics analysis, meanwhile, myocardial iron content and lipocalin-2 (Lcn2) protein expressions were increased. The CNC network comprised 137 positive interactions and 138 negative interactions. Bioinformatics analysis showed several iron-related terms were enriched and six genes (Scara5, Tfrc, Lcn2, Cp, Clic5, Ank1) were closely associated with iron metabolism. Then, we constructed knockdown LncRNA Lcn2-204 targeting myocardium and found that it ameliorated cardiac injury in mouse sepsis model through modulating iron overload and ferroptosis. In addition, we found that LncRNA Lcn2-204 was involved in the regulation of Lcn2 expression in septic myocardial injury. Based on these findings, we conclude that iron overload and ferroptosis are the key mechanisms leading to myocardial injury in sepsis, knockdown of LncRNA Lcn2-204 plays the cardioprotective effect through inhibition of iron overload, ferroptosis and Lcn2 expression. It may provide a novel therapeutic approach to ameliorate sepsis-induced myocardial injury.

Neutrophil extracellular traps as a unique target in the treatment of inflammatory pain.

Pain is a widespread motivation for seeking healthcare and stands as a substantial global public health concern. Despite comprehensive investigations into the mechanisms of pain sensitization induced by inflammation, efficacious treatments options remain scarce. Neutrophil extracellular traps (NETs) have been associated with the progression and tissue damage of diverse inflammatory diseases. This study aims to explore the impact of NETs on the progression of inflammatory pain and explore potential therapeutic approaches. Initially, we observed neutrophil infiltration and the formation of NETs in the left hind paw of mice with inflammatory pain induced by complete Freund's adjuvant (CFA). Furthermore, we employed the peptidyl arginine deiminase 4 (PAD4) inhibitor Cl-amidine (diluted at 50 mg/kg in saline, administered via tail vein injection once daily for three days) to impede NETs formation and administered DNase1 (diluted at 10 mg/kg in saline, once daily for three days) to break down NETs. We investigated the pathological importance of peripheral NETs formation in inflammatory pain and its influence on the activation of spinal dorsal horn microglia. The findings indicate that neutrophils infiltrating locally generate NETs, leading to an increased release of inflammatory mediators that worsen peripheral inflammatory reactions. Consequently, this results in the transmission of more harmful peripheral stimuli to the spinal cord, triggering microglial activation and NF-κB phosphorylation, thereby escalating neuroinflammation and fostering pain sensitization. Suppression of peripheral NETs can mitigate peripheral inflammation in mice with inflammatory pain, reverse mechanical and thermal hypersensitivity by suppressing microglial activation in the spinal cord, ultimately diminishing inflammatory pain. In conclusion, these discoveries propose that obstructing or intervening with NETs introduces a novel therapeutic avenue for addressing inflammatory pain.

DNMT3A mutations define a unique biological and prognostic subgroup associated with cytotoxic T cells in PTCL-NOS.

Peripheral T-cell lymphomas (PTCLs) are heterogenous T-cell neoplasms often associated with epigenetic dysregulation. We investigated de novo DNA methyltransferase 3A (DNMT3A) mutations in common PTCL entities, including angioimmunoblastic T-cell lymphoma and novel molecular subtypes identified within PTCL-not otherwise specified (PTCL-NOS) designated as PTCL-GATA3 and PTCL-TBX21. DNMT3A-mutated PTCL-TBX21 cases showed inferior overall survival (OS), with DNMT3A-mutated residues skewed toward the methyltransferase domain and dimerization motif (S881-R887). Transcriptional profiling demonstrated significant enrichment of activated CD8+ T-cell cytotoxic gene signatures in the DNMT3A-mutant PTCL-TBX21 cases, which was further validated using immunohistochemistry. Genomewide methylation analysis of DNMT3A-mutant vs wild-type (WT) PTCL-TBX21 cases demonstrated hypomethylation in target genes regulating interferon-γ (IFN-γ), T-cell receptor signaling, and EOMES (eomesodermin), a master transcriptional regulator of cytotoxic effector cells. Similar findings were observed in a murine model of PTCL with Dnmt3a loss (in vivo) and further validated in vitro by ectopic expression of DNMT3A mutants (DNMT3A-R882, -Q886, and -V716, vs WT) in CD8+ T-cell line, resulting in T-cell activation and EOMES upregulation. Furthermore, stable, ectopic expression of the DNMT3A mutants in primary CD3+ T-cell cultures resulted in the preferential outgrowth of CD8+ T cells with DNMT3AR882H mutation. Single-cell RNA sequencing(RNA-seq) analysis of CD3+ T cells revealed differential CD8+ T-cell subset polarization, mirroring findings in DNMT3A-mutated PTCL-TBX21 and validating the cytotoxic and T-cell memory transcriptional programs associated with the DNMT3AR882H mutation. Our findings indicate that DNMT3A mutations define a cytotoxic subset in PTCL-TBX21 with prognostic significance and thus may further refine pathological heterogeneity in PTCL-NOS and suggest alternative treatment strategies for this subset.

Dysbiosis of the gut microbiota in glioblastoma patients and potential biomarkers for risk assessment.

BACKGROUND: The significant death rate of glioblastoma is well-known around the world. The link between gut microbiota and glioma is becoming more studied. The goal of this study was to look at the relationships between intestinal flora and glioblastoma, and to provide a new perspective for the diagnosis as well as treatment of glioblastoma. METHODS: Fecal samples from 80 participants with glioblastoma (n = 40) and healthy individuals (n = 40) in this study were collected as well as analyzed utilizing 16S rRNA gene amplicon sequencing in order to characterize the gut microbial community. RESULTS: Each group has its own microbial community, and the microbial environment of glioblastoma patients had lower richness and evenness. The structure of gut microbiota community in glioblastoma patients showed profound changes, which includes the increase of pathogens in Fusobacteria and Bacteroidetes, and the reduction of probiotic bacteria in Firmicutes, Actinobacteria and Verrucomicrobia. Meanwhile, the significant correlations and clustering of OTUS (operational taxonomic units) in glioblastoma patients were discovered, and a biomarker panel (Fusobacterium, Escherichia/Shigella, Ruminococcus gnavus group, Lachnospira, Akkermansia, Parasutterella) had been used to discriminate the patients with glioblastoma from the healthy subjects (AUC: 0.80). Furthermore, the glioblastoma group exhibited multiple disturbed pathways through KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis, particularly in genetic information processing. Moreover, the prediction of phenotypic characteristics of microbiome proposed that the glioblastoma patients might have more Gram-negative bacteria and opportunistic pathogens than the healthy controls. CONCLUSIONS: When compared to healthy people, glioblastoma sufferers have a different host-microbe interaction. Furthermore, certain types of intestinal flora could be regarded as biomarkers and drug targets for the diagnosis as well as treatment of glioblastomas.

Effect of NLRP3 gene knockdown on pyroptosis and ferroptosis in diabetic cardiomyopathy injury.

Diabetic cardiomyopathy (DCM) is a chronic disease caused by diabetes mellitus, which is recognized as a worldwide challenging disease. This study aimed to investigate the role and the potential mechanism of knocking down the NACHT-, LRR- and PYD domains-containing protein 3 (NLRP3), an inflammasome associated with onset and progression of various diseases, on high glucose or diabetes -induced cardiac cells pyroptosis and ferroptosis, two regulated non-necrosis cell death modalities discovered recent years. In the present study, both in vivo and in vitro studies were conducted simultaneously. Diabetic rats were induced by 55 mg/kg intraperitoneal injection of streptozotocin (STZ). Following the intraperitoneal injection of MCC950 (10 mg/kg), On the other hand, the DCM model in H9C2 cardiac cells was simulated with 35 mmol/L glucose and a short hairpin RNA vector of NLRP3 were transfected to cells. The results showed that in vivo study, myocardial fibers were loosely arranged and showed inflammatory cell infiltration, mitochondrial cristae were broken and the GSDMD-NT expression was found notably increased in the DM group, while the protein expressions of xCT and GPX4 was significantly decreased, both of which were reversed by MCC950. High glucose reduced the cell viability and ATP level in vitro, accompanied by an increase in LDH release. All of the above indicators were reversed after NLRP3 knockdown compared with the HG treated alone. Moreover, the protein expressions of pyroptosis- and ferroptosis-related fators were significantly decreased or increased, consistent with the results shown by immunofluorescence. Furthermore, the protective effects of NLRP3 knockdown against HG were reversed following the mtROS agonist rotenone (ROT) treatment. In conclusion, inhibition of NLRP3 suppressed DM-induced myocardial injury. Promotion of mitochondrial ROS abolished the protective effect of knockdown NLRP3, and induced the happening of pyroptosis and ferroptosis. These findings may present a novel therapeutic underlying mechanism for clinical diabetes-induced myocardial injury treatment.

Prevalence, characteristics, and risk factors of venous thromboembolism in patients with brain tumor undergoing craniotomy: a meta-analysis.

BACKGROUND: Brain tumor patients undergoing craniotomy are significantly associated with the development of venous thromboembolism (VTE), while the contributing factors remains controversial. Our study aimed to investigate the prevalence and risk factors for VTE in postoperational brain tumor patients. METHODS: We searched the PubMed, Embase, Web of Science, Medline, and Cochrane Library databases from their inception to July 2023. Article selection, data extraction, and study quality assessment were performed independently by two reviewers. Publication bias was assessed using Egger's and Begg's tests. Stata 15.0 software was used for data analysis. RESULTS: A total of 25 studies were considered, with a total of 49,620 brain tumor individuals. The pooled prevalence of VTE during hospitalization in postoperational brain tumor patients was 9% [95% CI: (0.08, 0.10)]. Moreover, our results demonstrated that patients with VTE were older than those without VTE [mean difference [MD] = 8.14, 95% CI: (4.97, 11.30)]. The following variables were significantly associated with VTE: prior history of VTE [OR = 7.81, 95% CI: (3.62, 16.88)], congestive heart failure [OR = 2.33, 95% CI: (1.08-5.05)], diabetes [OR = 1.87, 95% CI: (1.12-3.10)], hypertension [OR = 1.27, 95% CI: (1.07-1.50)], steroid use [OR = 1.63, 95% CI: (1.41, 1.88)], high white blood cells counts [MD = 0.32, 95% CI: (0.01, 0.63)], and high fibrinogen levels [MD = 0.19, 95% CI: (0.08, 0.30)]. CONCLUSION: This meta-analysis identified risk factors for postoperational VTE in patients with brain tumor, which can serve as a theoretical foundation for medical staff to manage and treat VTE. TRIAL REGISTRATION: CRD42023357459.

Risk factors and predicting nomogram for the clinical deterioration of non-severe community-acquired pneumonia.

BACKGROUND: Currently, there remains insufficient focus on non-severe community-acquired pneumonia (CAP) patients who are at risk of clinical deterioration, and there is also a dearth of research on the related risk factors. Early recognition of hospitalized patients at risk of clinical deterioration will be beneficial for their clinical management. METHOD: A retrospective study was conducted in The First Affiliated Hospital of Wenzhou Medical University, China, spanning from January 1, 2018 to April 30, 2022, and involving a total of 1,632 non-severe CAP patients. Based on whether their condition worsened within 72 h of admission, patients were divided into a clinical deterioration group and a non-clinical deterioration group. Additionally, all patients were randomly assigned to a training set containing 75% of patients and a validation set containing 25% of patients. In the training set, risk factors for clinical deterioration in patients with non-severe CAP were identified by using LASSO regression analysis and multivariate logistic regression analysis. A nomogram was developed based on identified risk factors. The effectiveness of the nomogram in both the training and validation sets was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: Age, body mass index (BMI), body temperature, cardiovascular comorbidity, respiratory rate, LDH level, lymphocyte count and D-dimer level were identified as risk factors associated with the clinical deterioration of non-severe CAP within 72 h of admission. The area under curve (AUC) value of the nomogram was 0.78 (95% CI: 0.74-0.82) in the training set and 0.75 (95% CI: 0.67-0.83) in the validation set. Furthermore, the calibration curves for both the training and validation sets indicated that the predicted probability of clinical deterioration aligned with the actual probability. Additionally, DCA revealed clinical utility for the nomogram at a specific threshold probability. CONCLUSION: The study successfully identified the risk factors linked to the clinical deterioration of non-severe CAP and constructed a nomogram for predicting the probability of deterioration. The nomogram demonstrated favorable predictive performance and has the potential to aid in the early identification and management of non-severe CAP patients at elevated risk of deterioration.

Study on the correlation between serum indole-3-propionic acid levels and the progression and prognosis of acute ischemic stroke.

OBJECTIVE: This study aimed to explore the correlation between the serum level of indole-3-propionic acid (IPA) and the progression and prognosis of acute cerebral infarction (ACI). METHODS: This study enrolled 197 patients with ACI, and 53 participants from a community-based stroke screening program during the same period were included as the control group. The patients with ACI were divided into quartiles of serum IPA. A logistic regression model was used for comparison. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive value of the IPA. RESULTS: Compared with the healthy control group, the ACI group had lower serum IPA (P < 0.05). The serum IPA was an independent factor for acute ischemic stroke (OR=0.992, 95% CI: 0.984-0.999, P=0.035). The serum IPA was lower in patients with progressive stroke or poor prognosis than in patients with stable stroke or good prognosis (P < 0.05). Patients with ACI with low serum IPA are prone to progression and poor prognosis. The best cutoff value for predicting progression was 193.62 pg/mL (sensitivity, 67.5%; specificity 83.7%), and that for poor prognosis was 193.77 pg/mL (sensitivity, 71.1%; specificity, 72.5%). CONCLUSION: The serum level of IPA was an independent predictor of ACI and had certain clinical value for predicting stroke progression and prognosis in patients with ACI.

External validation of the iScore, ASTRAL score, DRAGON score, and THRIVE score and development of a nomogram to predict outcome in patients with large vessel occlusion-acute ischemic stroke.

OBJECTIVE: This study aimed to validate the iScore, ASTRAL score, DRAGON score, and THRIVE score for assessing large vessel occlusion-acute ischemic stroke (AIS-LVO) and establish a predictive model for AIS-LVO patients that has better performance to guide clinical practice. METHODS: We retrospectively included 439 patients with AIS-LVO and collected baseline data from all of them. External validation of the iScore, ASTRAL score, DRAGON score, and THRIVE score was performed. All variables were compared between groups via univariate analysis, and the results are expressed as ORs and 95 % CIs. Independent variables with P < 0.25 were included in the multivariate logistic analysis, and statistically significant differences (P < 0.05) were identified as risk factors for prognosis in AIS-LVO patients. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the predictive value of our model. RESULTS: Our external validation resulted in an iScore under the curve (AUC) of 0.8475, an ASTRAL AUC of 0.8324, a DRAGON AUC of 0.8196, and a THRIVE AUC of 0.8039. In our research, multivariate Cox regression revealed 8 independent predictors. We used a nomogram to visualize the results of the data analysis. The AUC for the training cohort was 0.8855 (95 % CI, 0.8487-0.9222), and that in the validation cohort was 0.8992 (95 % CI, 0.8496-0. 9488). CONCLUSIONS: In this study, we verified that the above scores have excellent efficacy in predicting the prognosis of AIS-LVO patients. The nomogram we developed was able to predict the prognosis of AIS-LVO more accurately and may contribute to personalized clinical decision-making and treatment for future clinical work.

Gender Differences in the Association Between Childhood Neighborhood Quality and Depressive Symptoms Trajectory in Middle-Aged and Elderly Chinese: A Seven-Year Longitudinal Study.

This study aimed to examine the role of childhood neighborhood quality on trajectories of depressive symptoms throughout later life based on a nationally representative sample, and to explore the role of gender in the association. Linear mixed-effects model analysis was performed to investigate a longitudinal association of childhood neighborhood quality with depressive symptoms. A total of 7,016 participants aged 45 and above were included in this study. Depressive symptoms progression was significantly faster (ß [95% confidence interval, CI]: 0.13 [0.01, 0.25]; P = .027) in the low childhood neighborhood quality when compared with the high childhood neighborhood quality. The quality of childhood neighborhood was significantly associated with a change in depressive symptoms over time in females (ß [95% CI]: 0.19 [0.02, 0.36]; P = .029) but not in males (ß [95% CI]: 0.09 [-0.06, 0.25]; P = .224). Targeted interventions should be developed to prevent depressive symptoms for those vulnerable groups.

Prediction model for treatment outcomes 3 years after corneal cross-linking for keratoconus.

PURPOSE: This study aimed to identify preoperative factors that predict visual acuity and Kmax 3 years after corneal cross-linking (CXL) in patients with keratoconus (KC), and to develop a prediction model. METHODS: We enrolled 68 patients with KC and followed up on 100 eyes that received CXL for at least 3 years. Preoperative data, including age, UDVA, CDVA, cylinder, SE, and the parameters of tomography including Kmax were collected as predictors. The primary outcomes were changes in CDVA (Delta CDVA) and Kmax (Delta Kmax) postoperatively. Univariate and multivariate linear regression were used to identify the correlation between the primary outcomes and predictors and establish prediction models. RESULTS: Both CDVA and Kmax remained stable from baseline to 3 years after CXL: from 0.25 ± 0.18 to 0.22 ± 0.20 (P = 0.308) and from 58.70 ± 9.52 D to 57.02 ± 8.83 D (P = 0.187), respectively. Multivariate analysis showed that worse preoperative CDVA (ß coefficient - 0.668, P < 0.001) and lower preoperative Kmean (ß coefficient 0.018,P < 0.001) were associated with greater improvement in CDVA after CXL. A smaller preoperative eccentricity (ß coefficient 8.896, P = 0.01) and a higher preoperative Kmean (ß coefficient - 1.264, P < 0.001) predicted a more flattening of postoperative Kmax. The prediction model for CDVA (R2 = 0.43) and Kmax (R2 = 0.37) could accurately estimate treatment outcomes. CONCLUSIONS: CXL is highly effective in halting or preventing further progression of KC. The preoperative factors CDVA and Kmean were able to predict visual acuity changes 3 years after CXL. And preoperative eccentricity and Kmean could predict Kmax changes 3 years after CXL.

Metabolomics Study Revealing Purines as Potential Diagnostic Biomarkers of Acute Respiratory Distress Syndrome in Patients with Community─Acquired Pneumonia.

Community-acquired pneumonia (CAP) is a significant threat to human health and the leading cause of acute respiratory distress syndrome (ARDS). We aimed to reveal the metabolic profiling whether can be used for assessing CAP with or without ARDS (nARDS) and therapeutic effects on CAP patients after treatment. Urine samples were collected at the onset and recovery periods, and metabolomics was employed to identify robust biomarkers. 19 metabolites were significantly changed in the ARDS relative to nARDS, mainly involving purines and fatty acids. After treatment, 7 metabolites in the nARDS and 14 in the ARDS were found to be significantly dysregulated, including fatty acids and amino acids. In the validation cohort, we observed that the biomarker panel consisted of N2,N2-dimethylguanosine, 1-methyladenosine, 3-methylguanine, 1-methyladenosine, and uric acid exhibited better AUCs of 0.900 than pneumonia severity index and acute physiology and chronic health evaluation II (APACHE II) scores between the ARDS and nARDS. Combining L-phenylalanine, phytosphingosine, and N-acetylaspartylglutamate as biomarkers for discriminating the nARDS and ARDS patients after treatment exhibited good AUCs of 0.811 and 0.821, respectively. The metabolic pathway and defined biomarkers may serve as crucial indicators for predicting the development of ARDS in CAP patients and for assessing therapeutic effects.

GelFAP v2.0: an improved platform for Gene functional analysis in Gastrodia elata.

BACKGROUND: Gastrodia elata (tianma), a well-known medicinal orchid, is widely used to treat various kinds of diseases with its dried tuber. In recent years, new chromosome-level genomes of G.elata have been released in succession, which offer an enormous resource pool for understanding gene function. Previously we have constructed GelFAP for gene functional analysis of G.elata. As genomes are updated and transcriptome data is accumulated, collection data in GelFAP cannot meet the need of researchers. RESULTS: Based on new chromosome-level genome and transcriptome data, we constructed co-expression network of G. elata, and then we annotated genes by aligning with sequences from NR, TAIR, Uniprot and Swissprot database. GO (Gene Ontology) and KEGG (Kyoto Encylopaedia of Genes and Genomes) annotations were predicted by InterProScan and GhostKOALA software. Gene families were further predicted by iTAK (Plant Transcription factor and Protein kinase Identifier and Classifier), HMMER (hidden Markov models), InParanoid. Finally, we developed an improved platform for gene functional analysis in G. elata (GelFAP v2.0) by integrating new genome, transcriptome data and processed functional annotation. Several tools were also introduced to platform including BLAST (Basic Local Alignment Search Tool), GSEA (Gene Set Enrichment Analysis), Heatmap, JBrowse, Motif analysis and Sequence extraction. Based on this platform, we found that the flavonoid biosynthesis might be regulated by transcription factors (TFs) such as MYB, HB and NAC. We also took C4H and GAFP4 as examples to show the usage of our platform. CONCLUSION: An improved platform for gene functional analysis in G. elata (GelFAP v2.0, www.gzybioinformatics.cn/Gelv2 ) was constructed, which provides better genome data, more transcriptome resources and more analysis tools. The updated platform might be preferably benefit researchers to carry out gene functional research for their project.

Genome-wide identification of SrbHLH transcription factors highlights its potential role in rebaudioside A (RA) biosynthesis in Stevia rebaudiana.

Stevia rebaudiana Bertoni is a valuable medicinal plant and an essential source of natural sweetener, steviol glycosides (SGs), with rebaudioside A (RA) being one of the main components of SGs. bHLH transcription factors play a crucial role in plant development and secondary metabolism. In this study, 159 SrbHLH genes were identified from the S. rebaudiana genome, and each gene was named based on its chromosome location. The SrbHLH proteins were then clustered into 18 subfamilies through phylogenetic analysis. The analysis of conserved motifs and gene structure further supported the classification of the SrbHLH family. Chromosomal location and gene duplication events of SrbHLH genes were also studied. Moreover, based on the RNA-Seq data of different tissues of S. rebaudiana, 28 SrbHLHs were co-expressed with structural genes involved in RA biosynthesis. The expression pattern of candidate SrbHLH genes were confirmed by qPCR. Finally, dual luciferase reporter assays (DLAs) and subcellular localization analysis verified SrbHLH22, SrbHLH111, SrbHLH126, SrbHLH142, and SrbHLH152 are critical regulators of RA biosynthesis. This study provides new insights into the function of SrbHLHs in regulating SGs biosynthesis and lays the foundation for future applications of SrbHLH genes in molecular breeding of S. rebaudiana.

Gastrointestinal microbiome of ARDS patients induces neuroinflammation and cognitive impairment in mice.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a respiratory failure syndrome that can cause many complications, impacting patients' quality of life. Behavioral and cognitive disorders have attracted increasing attention in patients with ARDS, but its potential mechanisms are still elusive. METHODS: Herein we transferred the faecal microbiota from patients with ARDS caused by community-acquired pneumonia (CAP) to antibiotics-treated recipient male mice to explore the microbiota-gut-brain mechanisms. Behavioral functions of mice were evaluated by the open field test, Morris water maze and Y-maze test. The structure and composition of the gut microbiota were analyzed by using 16S rRNA sequencing analysis. Microglia, astrocyte and neuron in the cortex and hippocampus were examined via immunofluorescent staining. RESULTS: We found that the major characteristic of the intestinal flora in ARDS/CAP patients was higher abundances of Gram-negative bacteria than normal controls. The gut microbiota derived from ARDS/CAP patients promoted neuroinflammation and behavioral dysfunctions in mice. Mice who underwent fecal transplant from ARDS/CAP patients had increased systemic lipopolysaccharide (LPS), systemic inflammation, and increased colonic barrier permeability. This may adversely impact blood barrier permeability and facilitate microglia activation, astrocyte proliferation, and loss of neurons. CONCLUSIONS: Our study proposes the role of the microbiota-gut-brain crosstalk on ARDS/CAP-associated behavioral impairments and suggests the gut microbiota as a potential target for the protection of brain health in ARDS patients in clinical practice.

Establishment of a risk prediction model for prolonged mechanical ventilation after lung transplantation: a retrospective cohort study.

BACKGROUND: Prolonged mechanical ventilation (PMV), mostly defined as mechanical ventilation > 72 h after lung transplantation with or without tracheostomy, is associated with increased mortality. Nevertheless, the predictive factors of PMV after lung transplant remain unclear. The present study aimed to develop a novel scoring system to identify PMV after lung transplantation. METHODS: A total of 141 patients who underwent lung transplantation were investigated in this study. The patients were divided into PMV and non-prolonged ventilation (NPMV) groups. Univariate and multivariate logistic regression analyses were performed to assess factors associated with PMV. A risk nomogram was then established based on the multivariate analysis, and model performance was further examined regarding its calibration, discrimination, and clinical usefulness. RESULTS: Eight factors were finally identified to be significantly associated with PMV by the multivariate analysis and therefore were included as risk factors in the nomogram as follows: the body mass index (BMI, P = 0.036); primary diagnosis as idiopathic pulmonary fibrosis (IPF, P = 0.038); pulmonary hypertension (PAH, P = 0.034); primary graft dysfunction grading (PGD, P = 0.011) at T0; cold ischemia time (CIT P = 0.012); and three ventilation parameters (peak inspiratory pressure [PIP, P < 0.001], dynamic compliance [Cdyn, P = 0.001], and P/F ratio [P = 0.015]) at T0. The nomogram exhibited superior discrimination ability with an area under the curve of 0.895. Furthermore, both calibration curve and decision-curve analysis indicated satisfactory performance. CONCLUSION: A novel nomogram to predict individual risk of receiving PMV for patients after lung transplantation was established, which may guide preventative measures for tackling this adverse event.

Enhancing Prognostic Assessment for Influenza-Associated Pneumonia: An Examination of Contributing Risk Factors.

Objective: This study aims to analyze the prognostic risk factors influencing patient outcomes in cases of influenza-associated pneumonia. Methods: We comprehensively analysed clinical data from patients admitted to the First Affiliated Hospital of Wenzhou Medical University between December 2017 and April 2019. Patients with confirmed influenza-associated pneumonia, determined through nucleic acid detection in throat swabs or sputum samples, were included in the study. The collected data were meticulously analyzed to identify significant prognostic risk factors. Results: A total of 151 patients diagnosed with influenza-associated pneumonia were included in the final analysis, yielding a fatality rate of 19.87% (30/151). The application of multivariate regression analysis revealed that several independent risk factors significantly affected the prognosis of patients afflicted with influenza-associated pneumonia. These included lymphocyte count (L), oxygenation index (O), albumin (A), and urinary (U) levels. Receiver operating characteristic (ROC) curve analysis further elucidated the prognostic value of these factors. Specifically, the Composite Index LOAU (Lymphocyte, Oxygenation index, Albumin, Urinary) demonstrated a robust area under the curve (AUC) of 0.909 (95% CI: 0.851-0.950), surpassing the performance of established scoring systems, such as the pneumonia severity index (PSI) (AUC = 0.746), Apache II (AUC = 0.732), and CURB-65 (AUC = 0.662). These differences were statistically significant (P < .05). Conclusions: The prognosis of influenza-associated pneumonia can be effectively predicted by assessing peripheral blood parameters, including lymphocyte count, albumin level, urinary markers, and the oxygenation index upon admission. Notably, the Composite Index LOAU, as a comprehensive amalgamation of these factors, holds promising potential to enhance prognostic precision and management outcomes in cases of influenza-associated pneumonia.

Prognostic value of the systemic inflammation response index in patients with aneurismal subarachnoid hemorrhage and a Nomogram model construction.

OBJECTIVE: To investigate the prognostic value of inflammatory markers, including neutrophil/lymphocyte ratio (NLR), derived neutrophil/lymphocyte ratio (dNLR), platelet/lymphocyte ratio (PLR), monocyte/lymphocyte ratio (MLR), prognostic nutritional index (PNI), and systemic inflammation response index (SIRI) in patients with aneurismal subarachnoid hemorrhage (aSAH), and then develop a Nomogram prognostic model. METHODS: We analysed 178 aSAH patients who underwent surgery at Subei People's Hospital of Jiangsu province from January 2015 to December 2017. Patients were divided into two groups according to Glasgow outcome scale (GOS) score at 3 months. Univariate and multivariate analysis were used to identify the association between inflammatory markers and prognosis. Subsequently, we identified the best cutoff of SIRI for unfavorable outcome using receiver operating characteristic (ROC) curve analysis and compared the clinical data between high and low SIRI levels. We further evaluated the additive value of SIRI by comparing prognostic nomogram models with and without it. RESULTS: A total of 47 (26.4%) patients had a poor outcome. Multivariate logistic regression analysis showed that SIRI was an independent risk factor of poor outcome. The SIRI of 4.105 × 109/L was identified as the optimal cutoff value, patients with high SIRI levels had worse clinical status and higher rates of unfavorable outcome. ROC analysis showed that a nomogram model combining the SIRI and other conventional factors showed more favorable predictive ability than the model without the SIRI. CONCLUSIONS: SIRI was independently correlated with unfavorable outcome in SAH patients, and the nomogram model combining the SIRI had more favorable discrimination ability.