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.

Association between alcohol-associated cirrhosis and inpatient complications among COVID-19 patients: A propensity-matched analysis from the United States.

BACKGROUND: Alcohol-associated cirrhosis (AC) contributes to significant liver-related mortality in the United States. It is known to cause immune dysfunction and coagulation abnormalities. Patients with comorbid conditions like AC are at risk of worse clinical outcomes from coronavirus disease 2019 (COVID-19). The specific association between AC and COVID-19 mortality remains inconclusive, given the lack of robust clinical evidence from prior studies. AIM: To study the predictors of mortality and the outcomes of AC in patients hospitalized with COVID-19 in the United States. METHODS: We conducted a retrospective cohort study using the National Inpatient Sample (NIS) database 2020. Patients were identified with primary COVID-19 hospitalizations based on an underlying diagnosis of AC. A matched comparison cohort of COVID-19 patients without AC was identified after 1:N propensity score matching based on baseline sociodemographic characteristics and Elixhauser comorbidities. Primary outcomes included median length of stay, median inpatient charges, and in-hospital mortality. Secondary outcomes included a prevalence of systemic complications. RESULTS: A total of 1325 COVID-19 patients with AC were matched to 1135 patients without AC. There was no difference in median length of stay and hospital charges in COVID-19 patients with AC compared to non-AC (P > 0.05). There was an increased prevalence of septic shock (5.7% vs 4.1%), ventricular fibrillation/ventricular flutter (0.4% vs 0%), atrial fibrillation (13.2% vs 8.8%), atrial flutter (8.7% vs 4.4%), first-degree atrioventricular nodal block (0.8% vs 0%), upper extremity venous thromboembolism (1.5% vs 0%), and variceal bleeding (3.8% vs 0%) in the AC cohort compared to the non-AC cohort (P < 0.05). There was no difference in inpatient mortality in COVID-19 patients with non-AC compared to AC, with an odds ratio of 0.97 (95% confidence interval: 0.78-1.22, P = 0.85). Predictors of mortality included advanced age, cardiac arrhythmias, coagulopathy, protein-calorie malnutrition, fluid and electrolyte disorders, septic shock, and upper extremity venous thromboembolism. CONCLUSION: AC does not increase mortality in patients hospitalized with COVID-19. There is an increased association between inpatient complications among COVID-19 patients with AC compared to non-AC.

Efficient Fault Detection of Rotor Minor Inter-Turn Short Circuit in Induction Machines Using Wavelet Transform and Empirical Mode Decomposition.

This paper introduces a novel approach for detecting inter-turn short-circuit faults in rotor windings using wavelet transformation and empirical mode decomposition. A MATLAB/Simulink model is developed based on electrical parameters to simulate the inter-turn short circuit by adding a resistor parallel to phase "a" of the rotor. The resulting high current in the new phase indicates the presence of the short circuit. By measuring the rotor and stator three-phase currents, the fault can be detected as the currents exhibit asymmetric behavior. Fluctuations in the electromagnetic torque also occur during the fault. The wavelet transform is applied to the rotor current, revealing an effective analysis of sideband frequency components. Specifically, changes in amplitude and frequency, particularly in d7 and a7, indicate the presence of harmonics generated by the inter-turn short circuit. The simulation results demonstrate the effectiveness of wavelet transformation in analyzing these frequency components. Additionally, this study explores the use of empirical mode decomposition to detect faults in their early stages, observing substantial changes in the instantaneous amplitudes of the first three intrinsic mode functions during fault onset. The proposed technique is straightforward and reliable, making it suitable for application in wind turbines with simple electrical inputs.

Operator-specific outcomes in endoscopic sleeve gastroplasty: a propensity-matched analysis of the US population using a multicenter database.

Background: Endoscopic sleeve gastroplasty (ESG) has emerged as an effective endoscopic bariatric procedure over the past decade. Data comparing short-term outcomes of ESG based on operator specialty is scarce. We aimed to assess the impact of operator specialization on patient outcomes using a large bariatric-specific database. Methods: We identified a retrospective cohort of patients who underwent ESG by gastroenterologists using the Metabolic and Bariatric Surgery Accreditation Quality Improvement Program database (2020-2021). A matched comparison cohort of patients who underwent ESG by surgeons was identified and underwent 1:1 propensity score matching based on age, race, gender, American Society of Anesthesiologists physical status classification, and preoperative body mass index. Results: After matching, 154 patients were included in the final analysis. Of these, 77 patients underwent ESG by surgeons and 77 by gastroenterologists. In the matched cohort, the median operation time was lower in ESG by surgeons compared to gastroenterologists (P < 0.001). The median percent body mass index decrease was higher in the gastroenterologist cohort compared to the surgeon cohort (4.9% vs 3.8%, P = 0.04). The median percent weight loss after ESG was 4.8% in the surgeon cohort and 5.9% in the gastroenterologist cohort (P = 0.09). There was no statistically significant difference in postoperative emergency department visits (P = 0.65), reoperations (P = 0.15), or reinterventions within 30 days (P = 0.87) between the cohorts. There was no difference in major adverse effects between the groups (0% each). Conclusions: Operator choice does not affect ESG-related adverse events or 30-day outcomes in patients undergoing ESG.

Association of nonalcoholic fatty liver disease with acute cholangitis: a nationwide propensity-matched analysis from the United States.

Background: Nonalcoholic fatty liver disease (NAFLD) has previously been linked to several disease states with an impact on patient outcomes. However, clinical evidence on the association between NAFLD and acute cholangitis (AC) remains scarce. We aimed to evaluate the potential association between NAFLD and AC. Methods: We conducted a retrospective cohort study using the US National Inpatient Sample database from 2016 to 2019 to analyze primary AC hospitalizations with NAFLD compared to non-NAFLD in a 1:1 propensity-matched population. Results: A total of 1550 AC patients with NAFLD were matched to 1550 AC patients without NAFLD. NAFLD had a higher association with AC when compared to patients without NAFLD, with an odds ratio of 2.33 (95% CI [1.81-3.0], P < 0.001). The length of stay was higher in NAFLD than in non-NAFLD (4 vs 3 days, P < 0.001). The median inpatient charges in NAFLD were also higher than in the non-NAFLD cohort ($36,182 vs $35,244, P < 0.001). Inpatient mortality was higher in NAFLD compared to non-NAFLD (1.6% vs 0%, P < 0.001). There was an increased prevalence of portal vein thrombosis (3.2% vs 0%), acute kidney injury (24.2% vs 17.7%), sepsis (3.2% vs 1.6%), mechanical ventilation (3.2% vs 0%), and percutaneous cholecystostomy tube insertion (3.2% vs 1.6%) in NAFLD compared to non-NAFLD (P < 0.05). NAFLD also had a higher association with acute cholecystitis, with an odds ratio of 3.70 (95% CI [3.19-4.29], P < 0.001). Conclusions: This study showed an association between NALFD and AC, resulting in increased length of stay, hospital charges, and inpatient mortality. Underlying NAFLD also increases acute complications of AC.

Trends in hospital admissions and mortality among inflammatory bowel disease patients with substance use disorder: a 10-year United States nationwide analysis.

Background: Patients with inflammatory bowel disease (IBD) and substance use disorder (SUD) may have worse clinical outcomes. However, data specific to the hospital admission and mortality rates among IBD patients with SUD are scarce. Our objective was to assess trends in admission, healthcare expenses, and mortality for IBD patients with SUD. Methods: We conducted a retrospective study using the National Inpatient Sample database to analyze SUD (alcohol, opioids, cocaine, and cannabis) among IBD hospitalizations from 2009 to 2019. Results: A total of 132,894 hospitalizations for IBD had a secondary diagnosis of SUD. Of these patients, 75,172 (57%) were men and 57,696 (43%) were women. The IBD-SUD cohort had a longer length of stay than the non-SUD cohort (P < 0.001). The mean inpatient charges for IBD hospitalizations with SUD increased from $48,699 ± $1374 in 2009 to $62,672 ± $1528 in 2019 (P < 0.001). We found a 159.5% increase in IBD hospitalizations with SUD. The hospitalization rate increased from 3492 per 100,000 IBD hospitalizations in 2009 to 9063 per 100,000 in 2019 (P < 0.001). In-hospital mortality for IBD hospitalizations with SUD increased by 129.6% (from 250 deaths per 100,000 IBD hospitalizations in 2009 to 574 deaths per 100,000 IBD hospitalizations in 2019) (P < 0.001). Conclusions: Over the last decade, there has been a rise in IBD hospitalizations with SUD. This has resulted in a longer length of stay, higher inpatient charges, and higher mortality rates. Identifying IBD patients potentially at risk for SUD by screening for anxiety, depression, pain, or other factors has become crucial.

Tuning the optoelectronic properties of acridine-triphenylamine (ACR-TPA) based novel hole transporting material for high efficiency perovskite and organic solar cell.

In this research, five distinct small donor molecules (designated as ACR-TPA-X1, ACR-TPA-X2, ACR-TPA-X3, ACR-TPA-X4, ACR-TPA-X5) are constructed by replacing the methoxy groups on both sides of the model molecule (ACR-TPA-R) with thiophene bridged acceptor moieties. We have used the B3LYP/6-31G (d,p) model for our computational studies. Our model molecule's morphological alteration has resulted in a lowered Eg of 1.77-2.51 eV as compared to model (ACR-TPA-R=3.84 eV). ACR-TPA-X2 investigated the λmax at 776 nm. ACR-TPA-X4 was found to be most miscible with dichloromethane (DCM). The greatest VOC(1.21 eV) was observed in ACR-TPA-X1. Among all of the variants, ACR-TPA-X1 had the highest PCE (23.42%). It was found that ACR-TPA-X4 had the highest electron mobility (0.00370 eV) and ACR-TPA-X5 had the highest hole mobility (0.00324 eV) of all the materials examined. The findings prove the worth of the methods used, paving the way for the development of effective small donors for OSCs and HTMs for PSCs.

Revisiting Plant Heterosis-From Field Scale to Molecules.

Heterosis refers to the increase in biomass, stature, fertility, and other characters that impart superior performance to the F1 progeny over genetically diverged parents. The manifestation of heterosis brought an economic revolution to the agricultural production and seed sector in the last few decades. Initially, the idea was exploited in cross-pollinated plants, but eventually acquired serious attention in self-pollinated crops as well. Regardless of harvesting the benefits of heterosis, a century-long discussion is continued to understand the underlying basis of this phenomenon. The massive increase in knowledge of various fields of science such as genetics, epigenetics, genomics, proteomics, and metabolomics persistently provide new insights to understand the reasons for the expression of hybrid vigor. In this review, we have gathered information ranging from classical genetic studies, field experiments to various high-throughput omics and computational modelling studies in order to understand the underlying basis of heterosis. The modern-day science has worked significantly to pull off our understanding of heterosis yet leaving open questions that requires further research and experimentation. Answering these questions would possibly equip today's plant breeders with efficient tools and accurate choices to breed crops for a sustainable future.

Investigation of the anti-hyperglycemic and antioxidant effects of wheat bread supplemented with onion peel extract and onion powder in diabetic rats.

AIM: Onion is one of the commonly cultivated and consumed vegetables rich in nutrients and phytochemicals. Various nutraceuticals are found in the outer fleshy layers and dry peel of onion which usually is treated as a common biowaste. Diabetes mellitus is a leading non communicable disease causing hyperglycemia and increased production of free radicals that potentially disrupts antioxidant enzymatic activity. Considering global consumption of wheat, the present study was designed to evaluate the anti-hyperglycemic and antioxidant effects of wheat bread supplemented with onion peel extract (OPE) or onion powder (OP) on diabetic rats. METHODS: In this study, ethanolic extract of onion peel and onion bulb were prepared separately. Male Sprague Dawley rats were divided into 6 groups (n = 7). Different regimens of supplemented wheat bread (OPE (1% and 3%) and OP (5% and 7%)) were given to diabetic rats for eight weeks, plain bread was used as the control. Blood glucose level, body weight and activities of SOD, CAT, GPx, GR, GSH and MDA in the liver and kidney tissues were evaluated. Statistical analysis was performed using SPSS Version (25) and Dunnett's multiple comparison test. RESULTS: Bread supplemented with 1% and 3% onion peel extract and 7% onion powder significantly reduced blood glucose levels and MDA in the treated rats compared with the control group diabetic rats. Body weight of diabetic rats was reduced for control group, while onion supplemented diet improved the body weight of treated rats. Onion supplementation also brought significant improvement in antioxidant enzyme activities among the treated diabetic rats. CONCLUSION: These findings suggested that onion supplementation is effective in lowering blood glucose and could potentially aid in protecting organs from oxidative stress.

Investigating particle track topology for range telescopes in particle radiography using convolutional neural networks.

BACKGROUND: Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy and in situ treatment validation in proton therapy. The pCT system of the Bergen pCT collaboration is able to handle very high particle intensities by means of track reconstruction. However, incorrectly reconstructed and secondary tracks degrade the image quality. We have investigated whether a convolutional neural network (CNN)-based filter is able to improve the image quality. MATERIAL AND METHODS: The CNN was trained by simulation and reconstruction of tens of millions of proton and helium tracks. The CNN filter was then compared to simple energy loss threshold methods using the Area Under the Receiver Operating Characteristics curve (AUROC), and by comparing the image quality and Water Equivalent Path Length (WEPL) error of proton and helium radiographs filtered with the same methods. RESULTS: The CNN method led to a considerable improvement of the AUROC, from 74.3% to 97.5% with protons and from 94.2% to 99.5% with helium. The CNN filtering reduced the WEPL error in the helium radiograph from 1.03 mm to 0.93 mm while no improvement was seen in the CNN filtered pRads. CONCLUSION: The CNN improved the filtering of proton and helium tracks. Only in the helium radiograph did this lead to improved image quality.

Image-Based Methods to Score Fungal Pathogen Symptom Progression and Severity in Excised Arabidopsis Leaves.

Image-based symptom scoring of plant diseases is a powerful tool for associating disease resistance with plant genotypes. Advancements in technology have enabled new imaging and image processing strategies for statistical analysis of time-course experiments. There are several tools available for analyzing symptoms on leaves and fruits of crop plants, but only a few are available for the model plant Arabidopsis thaliana (Arabidopsis). Arabidopsis and the model fungus Botrytis cinerea (Botrytis) comprise a potent model pathosystem for the identification of signaling pathways conferring immunity against this broad host-range necrotrophic fungus. Here, we present two strategies to assess severity and symptom progression of Botrytis infection over time in Arabidopsis leaves. Thus, a pixel classification strategy using color hue values from red-green-blue (RGB) images and a random forest algorithm was used to establish necrotic, chlorotic, and healthy leaf areas. Secondly, using chlorophyll fluorescence (ChlFl) imaging, the maximum quantum yield of photosystem II (Fv/Fm) was determined to define diseased areas and their proportion per total leaf area. Both RGB and ChlFl imaging strategies were employed to track disease progression over time. This has provided a robust and sensitive method for detecting sensitive or resistant genetic backgrounds. A full methodological workflow, from plant culture to data analysis, is described.

Evaluation of Antiulcer and Cytotoxic Potential of the Leaf, Flower, and Fruit Extracts of Calotropis procera and Isolation of a New Lignan Glycoside.

Calotropis procera is traditionally used for treating many diseases including ulcers and tumors. It was thus deemed of interest to investigate and compare the antiulcer and cytotoxic activities of C. procera leaf, flower, and fruit extracts in an attempt to verify its traditional uses. Phytochemical studies on the fruits, flowers, and leaves of C. procera, collected from the desert of Saudi Arabia, led to the isolation of one new lignan 7'-methoxy-3'-O-demethyl-tanegool-9-O-ß-d-glucopyranoside and five known compounds from the flowers, four compounds from leaves, and a flavonoid glycoside and a lignan glycoside from the fruits. The structures of compounds were determined by spectroscopic techniques. Ethanol extracts of the three parts of C. procera were evaluated for their antiulcer activity and we found that the leaf extract possessed a powerful antiulcer activity which could be considered as a promising drug candidate. All the extracts and the isolated compounds were evaluated for their cytotoxic activity against MCF-7, HCT-116, HepG-2, and A-549 human cancer cell lines. Compound 2 was highly active on all the cell lines, whereas compounds 5 and 11 were more selective on colon and liver cell lines. Compound 10 demonstrated a significant activity on liver and lung cancer cell lines.

Congenital hypoplasia of first digital ray of hands as an isolated presentation in four subjects.

Congenital hypoplasia of thumb is rare malformation which is less likely to appear as an isolated entity. Four independent subjects exhibiting various grades of underdeveloped first digital ray were recruited. The affected autopods had narrow palms, medial or valgus inclinations of index fingers and thenar weakness, while the postaxial digits were least affected. According to the classification of hypoplastic thumb by Blauth and Schneider-Sickert (1981), the phenotypes were concordant with types 3 and 4. In one of the subjects there was contralateral preaxial polydactyly. All cases were sporadic and nonsyndromic and parental consanguinity was witnessed in two individuals. Recurrent appearance of similar phenotypes may suggest genetic etiologies which should be elucidated with the help of high-throughput genetic methods.

Determination of Nitrite and Nitrate in Freshwaters using Flow Injection Luminol Chemiluminescence Detection.

A flow injection method for determination of nitrite and nitrate in freshwaters is described based on luminol-hypochlorite chemiluminescence (CL) system. Nitrate is reduced on-line with a cadmium reduction column to nitrite and its inhibition effect on luminol CL emission was measured. The effects of chemical and physical parameters such as buffer pH and concentration, luminol, sodium hypochlorite and sulfuric acid concentrations, flow rate, and sample volume were investigated. The calibration graphs were linear over the range 0.1-50 µM (R2 = 0.9989 and 0.9984) for nitrite and nitrate respectively with a limit of detection (S/N = 3) of 4.0 × 10-8 M and a sample throughput of 120 samples per hour. The effect of foreign ions was studied and the method was successfully applied to the determination of nitrite and nitrate in water samples. The results obtained were in good agreement with those achieved by a spectrophotometric reference method at the 95% confidence level. Standard addition method was also applied to the freshwater samples and the recovery values were found in the range of 92-109% and 94-105% for nitrite and nitrate respectively.