Domestication-driven Gossypium profilin 1 (GhPRF1) gene transduces early flowering phenotype in tobacco by spatial alteration of apical/floral-meristem related gene expression

Floral dimensions in transgenic Pf-OX4 line. (PPT 123 kb

Comparative Study to Evaluate the Efficacy and Safety of Propranolol versus Amitriptyline for Prophylaxis of Migraine

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A prospective study on drug utilization pattern of anti-diabetic drugs in a tertiary care teaching hospital of eastern Uttar Pradesh, India

Background: Diabetes mellitus is a metabolic disorder with common denominator of hyperglycemia, arising from a variety of pathogenic mechanisms. The aim of the study was to evaluate the drug utilization pattern of anti-diabetic drugs in diabetic patients and observe adverse drug events (ADEs) associated with anti-diabetic therapy in a prospective way.Methods: A prospective study was carried out in diabetic patients visiting the Departments of General Medicine in a tertiary care teaching hospital. Demographic data, drug utilization pattern and ADEs due to Anti-diabetic drugs were summarized.Results: In the present study, 153 (54%) of the 282 diabetic patients were males and 129 (46%) were females. Majority of patients were in the age group of 51-60 years (31.20%) and most of the patients (31.56%) had a diabetic history of 11-15 years. Metformin was the most commonly prescribed drug (64.89%). Majority of the patients (36.87%) were on multidrug therapy. Co-morbid condition was found in 232 patients (82.26%) where hypertension (22.69%) being the most common co-morbid condition. 32 ADRs were observed with Nausea being the most common ADR reported.Conclusions: The present study helps to find out current prescribing pattern of oral diabetic medications with different co-morbidities with respect to diagnosis, cost of treatment and it also highlight the need for comprehensive management of diabetic patients, including life style changes, dietary control, hypoglycemic agents, cardiovascular prevention, treatment of complications and co-morbidity. Therefore, through the existing prescribing patterns, attempts can be made to improve the quality and efficiency of drug therapy

Comparative study of dimer vacancies and dimer-vacancy lines on Si(001) and Ge(001)

Although the clean Si(001) and Ge(001) surfaces are very similar, experiments to date have shown that dimer-vacancy (DV) defects self-organize into vacancy lines (VLs) on Si(001), but not on Ge(001). In this paper, we perform empirical-potential calculations aimed at understanding the differences between the vacancies on Si(001) and Ge(001). We identify three energetic parameters that characterize the DVs on the two surfaces: the formation energy of a single DV, the attraction between two DVs in adjacent dimer rows, and the strain sensitivity of the formation energy of DVs and VLs. At the empirical level of treatment of the atomic interactions (Tersoff potentials), all three parameters are favorable for the self-assembly of DVs on the Si(001) surface rather than on Ge(001). The most significant difference between the defects on Si(001) and on Ge(001) concerns the formation energy of single DVs, which is three times larger in the latter case. By calculating the strain-dependent formation energies of DVs and VLs, we propose that the experimental observation of self-assembly of vacancies on clean Ge(001) could be achieved by applying compressive strains of the order of 2%.Comment: 3 tables, 4 figures, to appear in Surface Scienc

Mitochondrial uncoupler DNP induces coexistence of dual-state hyper-energy metabolism leading to tumor growth advantage in human glioma xenografts

IntroductionCancer bioenergetics is an essential hallmark of neoplastic transformation. Warburg postulated that mitochondrial OXPHOS is impaired in cancer cells, leading to aerobic glycolysis as the primary metabolic pathway. However, mitochondrial function is altered but not entirely compromised in most malignancies, and that mitochondrial uncoupling is known to increase the carcinogenic potential and modifies treatment response by altering metabolic reprogramming. Our earlier study showed that transient DNP exposure increases glycolysis in human glioma cells (BMG-1). The current study investigated the persistent effect of DNP on the energy metabolism of BMG-1 cells and its influence on tumor progression in glioma xenografts.MethodsBMG-1 cells were treated with 2,4-dinitrophenol (DNP) in-vitro, to establish the OXPHOS-modified (OPM-BMG) cells. Further cellular metabolic characterization was carried out in both in-vitro cellular model and in-vivo tumor xenografts to dissect the role of metabolic adaptation in these cells and compared them with their parental phenotype. Results and DiscussionChronic exposure to DNP in BMG-1 cells resulted in dual-state hyper-energy metabolism with elevated glycolysis++ and OXPHOS++ compared to parental BMG-1 cells with low glycolysis+ and OXPHOS+. Tumor xenograft of OPM-BMG cells showed relatively increased tumor-forming potential and accelerated tumor growth in nude mice. Moreover, compared to BMG-1, OPM-BMG tumor-derived cells also showed enhanced migration and invasion potential. Although mitochondrial uncouplers are proposed as a valuable anti-cancer strategy; however, our findings reveal that prolonged exposure to uncouplers provides tumor growth advantage over the existing glioma phenotype that may lead to poor clinical outcomes

Global benchmarks in primary robotic bariatric surgery redefine quality standards for Roux-en-Y gastric bypass and sleeve gastrectomy

BACKGROUND Whether the benefits of the robotic platform in bariatric surgery translate into superior surgical outcomes remains unclear. The aim of this retrospective study was to establish the 'best possible' outcomes for robotic bariatric surgery and compare them with the established laparoscopic benchmarks. METHODS Benchmark cut-offs were established for consecutive primary robotic bariatric surgery patients of 17 centres across four continents (13 expert centres and 4 learning phase centres) using the 75th percentile of the median outcome values until 90 days after surgery. The benchmark patients had no previous laparotomy, diabetes, sleep apnoea, cardiopathy, renal insufficiency, inflammatory bowel disease, immunosuppression, history of thromboembolic events, BMI greater than 50 kg/m2, or age greater than 65 years. RESULTS A total of 9097 patients were included, who were mainly female (75.5%) and who had a mean(s.d.) age of 44.7(11.5) years and a mean(s.d.) baseline BMI of 44.6(7.7) kg/m2. In expert centres, 13.74% of the 3020 patients who underwent primary robotic Roux-en-Y gastric bypass and 5.9% of the 4078 patients who underwent primary robotic sleeve gastrectomy presented with greater than or equal to one complication within 90 postoperative days. No patient died and 1.1% of patients had adverse events related to the robotic platform. When compared with laparoscopic benchmarks, robotic Roux-en-Y gastric bypass had lower benchmark cut-offs for hospital stay, postoperative bleeding, and marginal ulceration, but the duration of the operation was 42 min longer. For most surgical outcomes, robotic sleeve gastrectomy outperformed laparoscopic sleeve gastrectomy with a comparable duration of the operation. In robotic learning phase centres, outcomes were within the established benchmarks only for low-risk robotic Roux-en-Y gastric bypass. CONCLUSION The newly established benchmarks suggest that robotic bariatric surgery may enhance surgical safety compared with laparoscopic bariatric surgery; however, the duration of the operation for robotic Roux-en-Y gastric bypass is longer

Global Benchmarks in Primary Robotic Bariatric Surgery Redefine Quality Standards for Roux-En-Y Gastric Bypass and Sleeve Gastrectomy

BACKGROUND: Whether the benefits of the robotic platform in bariatric surgery translate into superior surgical outcomes remains unclear. The aim of this retrospective study was to establish the \u27best possible\u27 outcomes for robotic bariatric surgery and compare them with the established laparoscopic benchmarks. METHODS: Benchmark cut-offs were established for consecutive primary robotic bariatric surgery patients of 17 centres across four continents (13 expert centres and 4 learning phase centres) using the 75th percentile of the median outcome values until 90 days after surgery. The benchmark patients had no previous laparotomy, diabetes, sleep apnoea, cardiopathy, renal insufficiency, inflammatory bowel disease, immunosuppression, history of thromboembolic events, BMI greater than 50 kg/m2, or age greater than 65 years. RESULTS: A total of 9097 patients were included, who were mainly female (75.5%) and who had a mean(s.d.) age of 44.7(11.5) years and a mean(s.d.) baseline BMI of 44.6(7.7) kg/m2. In expert centres, 13.74% of the 3020 patients who underwent primary robotic Roux-en-Y gastric bypass and 5.9% of the 4078 patients who underwent primary robotic sleeve gastrectomy presented with greater than or equal to one complication within 90 postoperative days. No patient died and 1.1% of patients had adverse events related to the robotic platform. When compared with laparoscopic benchmarks, robotic Roux-en-Y gastric bypass had lower benchmark cut-offs for hospital stay, postoperative bleeding, and marginal ulceration, but the duration of the operation was 42 min longer. For most surgical outcomes, robotic sleeve gastrectomy outperformed laparoscopic sleeve gastrectomy with a comparable duration of the operation. In robotic learning phase centres, outcomes were within the established benchmarks only for low-risk robotic Roux-en-Y gastric bypass. CONCLUSION: The newly established benchmarks suggest that robotic bariatric surgery may enhance surgical safety compared with laparoscopic bariatric surgery; however, the duration of the operation for robotic Roux-en-Y gastric bypass is longer

Towards sustainable agriculture: Harnessing AI for global food security

The issue of food security continues to be a prominent global concern, affecting a significant number of individuals who experience the adverse effects of hunger and malnutrition. The finding of a solution of this intricate issue necessitates the implementation of novel and paradigm-shifting methodologies in agriculture and food sector. In recent times, the domain of artificial intelligence (AI) has emerged as a potent tool capable of instigating a profound influence on the agriculture and food sectors. AI technologies provide significant advantages by optimizing crop cultivation practices, enabling the use of predictive modelling and precision agriculture techniques, and aiding efficient crop monitoring and disease identification. Additionally, AI has the potential to optimize supply chain operations, storage management, transportation systems, and quality assurance processes. It also tackles the problem of food loss and waste through post-harvest loss reduction, predictive analytics, and smart inventory management. This study highlights that how by utilizing the power of AI, we could transform the way we produce, distribute, and manage food, ultimately creating a more secure and sustainable future for all

Artificial Intelligence in Biological Sciences

Artificial intelligence (AI), currently a cutting-edge concept, has the potential to improve the quality of life of human beings. The fields of AI and biological research are becoming more intertwined, and methods for extracting and applying the information stored in live organisms are constantly being refined. As the field of AI matures with more trained algorithms, the potential of its application in epidemiology, the study of host–pathogen interactions and drug designing widens. AI is now being applied in several fields of drug discovery, customized medicine, gene editing, radiography, image processing and medication management. More precise diagnosis and cost-effective treatment will be possible in the near future due to the application of AI-based technologies. In the field of agriculture, farmers have reduced waste, increased output and decreased the amount of time it takes to bring their goods to market due to the application of advanced AI-based approaches. Moreover, with the use of AI through machine learning (ML) and deep-learning-based smart programs, one can modify the metabolic pathways of living systems to obtain the best possible outputs with the minimal inputs. Such efforts can improve the industrial strains of microbial species to maximize the yield in the bio-based industrial setup. This article summarizes the potentials of AI and their application to several fields of biology, such as medicine, agriculture, and bio-based industry