Multi-model GWAS reveals key loci for horticultural traits in reconstructed garden strawberry.

The cultivated garden strawberry (Fragaria × ananassa) has a rich history, originating from the hybridization of two wild octoploid strawberry species in the 18th century. Two-step reconstruction of Fragaria × ananassa through controlled crossings between pre-improved selections of its parental species is a promising approach for enriching the breeding germplasm of strawberry for wider adaptability. We created a population of reconstructed strawberry by hybridizing elite selections of F. virginiana and F. chiloensis. A replicated field experiment was conducted to evaluate the population's performance for eleven horticulturally important traits, over multiple years. Population structure analyses based on Fana-50 k SNP array data confirmed pedigree-based grouping of the progenies into four distinct groups. As complex traits are often influenced by environmental variables, and population structure can lead to spurious associations, we tested multiple genome-wide association study (GWAS) models. GWAS uncovered 39 quantitative trait loci (QTL) regions for eight traits distributed across twenty chromosomes, including 11 consistent and 28 putative QTLs. Candidate genes for traits including winter survival, flowering time, runnering vigor, and hermaphrodism were identified within the QTL regions. To our knowledge, this study marks the first comprehensive investigation of adaptive and horticultural traits in a large, multi-familial reconstructed strawberry population using SNP markers.

Identification and Characterization of Evolutionary Conserved Muskmelon Non-coding miRNAs and Their Target Proteins.

MicroRNAs (miRNAs) are short, endogenously encoded small RNAs, 18-26 nucleotides in length, which can posttranscriptionally regulate gene expression through translation inhibition or endonucleolytic cleavage. The muskmelon is one of the most widely cultivated fruits in the Cucurbitaceae family. Despite its significance, only 120 miRNAs from different families have been reported in muskmelon. In this study, we aimed to expand this knowledge base by predicting 40 new miRNAs in muskmelon using a spectrum of genomic-based tools. Precursor and mature sequences were obtained from microRNA registry database as reference and analyzed via the basic local alignment search tool (Blastn) for ESTs identification. After removing the non-coding sequences, the remaining candidate sequences were analyzed using MFOLD to generate secondary structures for the newly predicted miRNAs. Additionally, the predicted muskmelon miRNAs were validated using a set of five randomly chosen primers and RT-PCR. Through gene ontology (GO) analysis, we identified 89 targets associated with newly predicted muskmelon miRNAs. Transcription factor-coding genes play a crucial role in plant growth and development. Additionally, the miR4249 has been found to have the same targets in muskmelon that have been linked to cell signaling and transcription factors. The identified targets are integral for diverse biological processes including plant growth, development, metabolism, aging, disease resistance, and resistance to environmental stresses, such as salt, cold, and oxidative stress. As a result, the outcomes of this study demonstrate that this mechanism not only contributes to the production of a higher quality crop but also enhances overall production.

Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning.

Background: Acute pancreatitis (AP) is a complex and life-threatening disease. Early recognition of factors predicting morbidity and mortality is crucial. We aimed to develop and validate a pragmatic model to predict the individualized risk of early intensive care unit (ICU) admission for patients with AP. Methods: The 2019 Nationwide Readmission Database was used to identify patients hospitalized with a primary diagnosis of AP without ICU admission. A matched comparison cohort of AP patients with ICU admission within 7 days of hospitalization was identified from the National Inpatient Sample after 1:N propensity score matching. The least absolute shrinkage and selection operator (LASSO) regression was used to select predictors and develop an ICU acute pancreatitis risk (IAPR) score validated by 10-fold cross-validation. Results: A total of 1513 patients hospitalized for AP were included. The median age was 50.0 years (interquartile range: 39.0-63.0). The three predictors that were selected included hypoxia (area under the curve [AUC] 0.78), acute kidney injury (AUC 0.72), and cardiac arrhythmia (AUC 0.61). These variables were used to develop a nomogram that displayed excellent discrimination (AUC 0.874) (bootstrap bias-corrected 95% confidence interval 0.824-0.876). There was no evidence of miscalibration (test statistic = 2.88; P = 0.09). For high-risk patients (total score >6 points), the sensitivity was 68.94% and the specificity was 92.66%. Conclusions: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.

Impact of COVID-19 on liver transplant recipients: A nationwide cohort study evaluating hospitalization, transplant rejection, and inpatient mortality.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has posed a major public health concern worldwide. Patients with comorbid conditions are at risk of adverse outcomes following COVID-19. Solid organ transplant recipients with concurrent immunosuppression and comorbidities are more susceptible to a severe COVID-19 infection. It could lead to higher rates of inpatient complications and mortality in this patient population. However, studies on COVID-19 outcomes in liver transplant (LT) recipients have yielded inconsistent findings. AIM: To evaluate the impact of the COVID-19 pandemic on hospital-related outcomes among LT recipients in the United States. METHODS: We conducted a retrospective cohort study using the 2019-2020 National Inpatient Sample database. Patients with primary LT hospitalizations and a secondary COVID-19 diagnosis were identified using the International Classification of Diseases, Tenth Revision coding system. The primary outcomes included trends in LT hospitalizations before and during the COVID-19 pandemic. Secondary outcomes included comparative trends in inpatient mortality and transplant rejection in LT recipients. RESULTS: A total of 15720 hospitalized LT recipients were included. Approximately 0.8% of patients had a secondary diagnosis of COVID-19 infection. In both cohorts, the median admission age was 57 years. The linear trends for LT hospitalizations did not differ significantly before and during the pandemic (P = 0.84). The frequency of in-hospital mortality for LT recipients increased from 1.7% to 4.4% between January 2019 and December 2020. Compared to the pre-pandemic period, a higher association was noted between LT recipients and in-hospital mortality during the pandemic, with an odds ratio (OR) of 1.69 [95% confidence interval (CI): 1.55-1.84), P < 0.001]. The frequency of transplant rejections among hospitalized LT recipients increased from 0.2% to 3.6% between January 2019 and December 2020. LT hospitalizations during the COVID-19 pandemic had a higher association with transplant rejection than before the pandemic [OR: 1.53 (95%CI: 1.26-1.85), P < 0.001]. CONCLUSION: The hospitalization rates for LT recipients were comparable before and during the pandemic. Inpatient mortality and transplant rejection rates for hospitalized LT recipients were increased during the COVID-19 pandemic.

Association between acute peripancreatic fluid collections and early readmission in acute pancreatitis: A propensity-matched analysis.

BACKGROUND: Patients with acute pancreatitis (AP) frequently experience hospital readmissions, posing a significant burden to healthcare systems. Acute peripancreatic fluid collection (APFC) may negatively impact the clinical course of AP. It could worsen symptoms and potentially lead to additional complications. However, clinical evidence regarding the specific association between APFC and early readmission in AP remains scarce. Understanding the link between APFC and readmission may help improve clinical care for AP patients and reduce healthcare costs. AIM: To evaluate the association between APFC and 30-day readmission in patients with AP. METHODS: This retrospective cohort study is based on the Nationwide Readmission Database for 2016-2019. Patients with a primary diagnosis of AP were identified. Participants were categorized into those with and without APFC. A 1:1 propensity score matching for age, gender, and Elixhauser comorbidities was performed. The primary outcome was early readmission rates. Secondary outcomes included the incidence of inpatient complications and healthcare utilization. Unadjusted analyses used Mann-Whitney U and χ 2 tests, while Cox regression models assessed 30-day readmission risks and reported them as adjusted hazard ratios (aHR). Kaplan-Meier curves and log-rank tests verified readmission risks. RESULTS: A total of 673059 patients with the principal diagnosis of AP were included. Of these, 5.1% had APFC on initial admission. After propensity score matching, each cohort consisted of 33914 patients. Those with APFC showed a higher incidence of inpatient complications, including septic shock (3.1% vs 1.3%, P < 0.001), portal venous thrombosis (4.4% vs 0.8%, P < 0.001), and mechanical ventilation (1.8% vs 0.9%, P < 0.001). The length of stay (LOS) was longer for APFC patients [4 (3-7) vs 3 (2-5) days, P < 0.001], as were hospital charges ($29451 vs $24418, P < 0.001). For 30-day readmissions, APFC patients had a higher rate (15.7% vs 6.5%, P < 0.001) and a longer median readmission LOS (4 vs 3 days, P < 0.001). The APFC group also had higher readmission charges ($28282 vs $22865, P < 0.001). The presence of APFC increased the risk of readmission twofold (aHR 2.52, 95% confidence interval: 2.40-2.65, P < 0.001). The independent risk factors for 30-day readmission included female gender, Elixhauser Comorbidity Index ≥ 3, chronic pulmonary diseases, chronic renal disease, protein-calorie malnutrition, substance use disorder, depression, portal and splenic venous thrombosis, and certain endoscopic procedures. CONCLUSION: Developing APFC during index hospitalization for AP is linked to higher readmission rates, more inpatient complications, longer LOS, and increased healthcare costs. Knowing predictors of readmission can help target high-risk patients, reducing healthcare burdens.