Financial barriers to attending international cardiology conferences: 2022-24 analysis of registration fees.

INTRODUCTION: Cardiology conferences represent a major avenue for learning, career advancement, and professional networking. Yet, costs of attending these conferences represent a major barrier, particularly for trainees and participants from low-middle-income countries (LMICs). Our study aimed to analyze the registration fees of major cardiology conferences worldwide. METHODS: We included conferences organized by international cardiovascular societies and those representing global regions. We did not include individual national or institutional conferences due to inability to systematically identify them. We collected 2024 registration fees from official conference websites, taking 2023 or 2022 fees if unavailable, and categorized them according to career stage and society membership status. Where specified, we chose 'early-bird' fees. All fees were converted to US dollars according to currency exchange rates per the International Monetary Fund on December 4, 2023, or if unavailable, per the last reported US Treasury Data. Other data collected included host country, virtual option availability, and LMIC discounts. RESULTS: 30 (65.2 %) conferences provided discounts for medical students, regardless of membership status, while 1 (2.2 %) provided discounts only for student-members. 36 (78.2 %) conferences offered discounts for residents/fellows, while 2 (4.3 %) offered discounts only for resident/fellow-members. Median fees for students and residents/fellows with membership were $255 and $287 (in US dollars), respectively while median fees for non-members were $303.5 and $397, respectively. 31 (67.4 %) conferences provided discounts for staff- members. Median fees for staff were $701 and $800 for members and non-members, respectively. Only 12 (26.1 %) conferences mentioned a virtual component, with 11 offering discounted registration compared with in-person rates. 7 (15.2 %) conferences had special in-person fees for LMIC-based registrants. 5 offered the same discounted rate regardless of training stage, while 2 offered additional discounts for trainees. CONCLUSION: We found that conference registration costs were substantial, including for trainees, with only a minority of conferences providing discounted rates for LMICs. Professional societies must reduce registration costs, potentially by implementing a tiered system based on training stage and country of origin. Further, to augment LMIC participation, dedicated scholarships and mentorship programs for LMIC-based registrants are needed.

Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping review.

Background: The field of precision medicine endeavors to transform the healthcare industry by advancing individualised strategies for diagnosis, treatment modalities, and predictive assessments. This is achieved by utilizing extensive multidimensional biological datasets encompassing diverse components, such as an individual's genetic makeup, functional attributes, and environmental influences. Artificial intelligence (AI) systems, namely machine learning (ML) and deep learning (DL), have exhibited remarkable efficacy in predicting the potential occurrence of specific cancers and cardiovascular diseases (CVD). Methods: We conducted a comprehensive scoping review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. Our search strategy involved combining key terms related to CVD and AI using the Boolean operator AND. In August 2023, we conducted an extensive search across reputable scholarly databases including Google Scholar, PubMed, IEEE Xplore, ScienceDirect, Web of Science, and arXiv to gather relevant academic literature on personalised medicine for CVD. Subsequently, in January 2024, we extended our search to include internet search engines such as Google and various CVD websites. These searches were further updated in March 2024. Additionally, we reviewed the reference lists of the final selected research articles to identify any additional relevant literature. Findings: A total of 2307 records were identified during the process of conducting the study, consisting of 564 entries from external sites like arXiv and 1743 records found through database searching. After 430 duplicate articles were eliminated, 1877 items that remained were screened for relevancy. In this stage, 1241 articles remained for additional review after 158 irrelevant articles and 478 articles with insufficient data were removed. 355 articles were eliminated for being inaccessible, 726 for being written in a language other than English, and 281 for not having undergone peer review. Consequently, 121 studies were deemed suitable for inclusion in the qualitative synthesis. At the intersection of CVD, AI, and precision medicine, we found important scientific findings in our scoping review. Intricate pattern extraction from large, complicated genetic datasets is a skill that AI algorithms excel at, allowing for accurate disease diagnosis and CVD risk prediction. Furthermore, these investigations have uncovered unique genetic biomarkers linked to CVD, providing insight into the workings of the disease and possible treatment avenues. The construction of more precise predictive models and personalised treatment plans based on the genetic profiles of individual patients has been made possible by the revolutionary advancement of CVD risk assessment through the integration of AI and genomics. Interpretation: The systematic methodology employed ensured the thorough examination of available literature and the inclusion of relevant studies, contributing to the robustness and reliability of the study's findings. Our analysis stresses a crucial point in terms of the adaptability and versatility of AI solutions. AI algorithms designed in non-CVD domains such as in oncology, often include ideas and tactics that might be modified to address cardiovascular problems. Funding: No funding received.

Analysing district-level climate vulnerability pattern in Madhya Pradesh, India, based on agricultural and socio-economic indicators.

Indian agriculture transitioned from a food deficit sector to a food surplus following the Green Revolution. However, the continued progress of Indian agriculture has been hampered by climate change. This research explores the district-wise vulnerability in Madhya Pradesh, India, to climate change by assessing the composite vulnerability index using the agricultural vulnerability index (AVI) and socio-economic vulnerability index (SEVI). The study seeks to understand how agricultural and socio-economic factors lead to variations in vulnerability across districts and influence targeted adaptation and mitigation strategies. The trend analysis results present declining rainfall and inclining temperature from 1951 to 2021 in Madhya Pradesh, directly affecting the agricultural sector and human livelihood. The composite vulnerability index (CVI) results revealed that districts with low values (< 0.394), such as Burhanpur and Balaghat, demonstrate reduced susceptibility due to limited cultivation, low reliance on rainfall, lower drought susceptibility, and decreased population density. Districts such as Panna and Bhopal show moderate vulnerability (0.394-0.423), with lower fallow land, reduced rainfed agriculture, and socio-economic vulnerability. Extensive agriculture and marginalised workers' presence influence high vulnerability (0.423 to 0.456) in districts such as Tikamgarh and Indore. Districts like Barwani and Jhabua have the highest CVI values (> 0.456), indicating substantial susceptibility to climate impacts. The cluster analysis validates the results of the vulnerability index. The findings highlight the urgent need for tailored adaptation strategies to address the diverse agricultural and socio-economic indicators creating vulnerability in Madhya Pradesh. The study helps understand regional vulnerability patterns and provides evidence-based policy approaches for resilience to climate change effects.

Olanzapine for young PEople with aNorexia nervosa (OPEN): A protocol for an open-label feasibility study.

INTRODUCTION: Antipsychotics are routinely prescribed off-label for anorexia nervosa (AN) despite limited evidence. This article presents a protocol of a study aiming to assess the feasibility of a future definitive trial on olanzapine in young people with AN. METHODS AND ANALYSIS: In an open-label, one-armed feasibility study, 55 patients with AN or atypical AN, aged 12-24, receiving outpatient, inpatient or day-care treatment who are considered for olanzapine treatment will be recruited from NHS sites based in England. Assessments will be conducted at screening, baseline and at 8-, 16 weeks, 6- and 12 months. Primary feasibility parameters will be proportions of patients who agree to take olanzapine and who adhere to treatment and complete study assessments. Qualitative methods will be used to explore acceptability of the intervention and study design. Secondary feasibility parameters will be changes in body mass index, psychopathology, side effects, health-related quality of life, carer burden and proportion of participants who would enrol in a future randomised controlled trial. The study is funded by the National Institute for Health Research via Health Technology Assessment programme. DISCUSSION: Olanzapine for young PEople with aNorexia nervosa will inform a future randomised controlled trial on the efficacy and safety of prescribing olanzapine in young people with AN.

Stochastic modeling and parameter estimation of turbogenerator unit of a thermal power plant under classical and Bayesian inferential framework.

The work reported in present study deals with the development of a novel stochastic model and estimation of parameters to assess reliability characteristics for a turbogenerator unit of thermal power plant under classical and Bayesian frameworks. Turbogenerator unit consists of five components namely turbine lubrication, turbine governing, generator oil system, generator gas system and generator excitation system. The concepts of cold standby redundancy and Weibull distributed random variables are used in development of stochastic model. The shape parameter for all the random variables is same while scale parameter is different. Regenerative point technique and semi-Markov approach are used for evaluation of reliability characteristics. Sufficient repair facility always remains available in plant as well as repair done by the repairman is considered perfect. As the life testing experiments are time consuming, so to highlight the importance of proposed model Monte Carlo simulation study is carried out. A comparative analysis is done between true, classical and Bayesian results of MTSF, availability and profit function.

Cell culture media dependent in vitro dynamics and culture characteristics of adult caprine dermal fibroblast cells.

The enhanced availability of functional fibroblasts from precious tissue samples requires an ideal cell-culture system. Therefore, this study was designed to investigate the performance of caprine adult fibroblast cells (cadFibroblast) when cultivated in different culture media. The cadFibroblast cell lines from adult Barbari (Capra hircus) bucks were established and the effect of different media viz. DMEM/F-12 [with low-glucose (5.5 mM; DL) and high-glucose (30 mM; DH)], α-MEM [with low-glucose (5.5 mM; ML) and with high-glucose (30 mM; MH)], and fibroblast growth medium (FGM) were evaluated. Cells were then compared for growth characteristics and in-vitro dynamics through cellular morphology, proliferation, population-doubling time, double-immunocytochemistry, colony-forming units, wound healing, transwell migration, and differential expression of fibroblast-specific markers (FSP-1 and vimentin). The results of immunocytochemistry, transwell migration/invasion, and wound healing assays showed the superiority of DH over DL and other media tested. Whereas, similar effects of glucose supplementation and expression of FSP-1 were not observed in α-MEM. Transwell migration was significantly (p < 0.05) lower in FGM compared with other media tested. Overall, our results illustrate the media-dependent deviation in in-vitro dynamics and culture characteristics of cadFibroblasts that may be useful to develop strategies to cultivate these cells efficiently for research and downstream applications.

Partial least squares regression to calculate population balance model parameters from material properties in continuous twin-screw wet granulation.

In the pharmaceutical industry, twin-screw wet granulation has become a realistic option for the continuous manufacturing of solid drug products. Towards the efficient design, population balance models (PBMs) have been recognized as a tool to compute granule size distribution and understand physical phenomena. However, the missing link between material properties and the model parameters limits the swift applicability and generalization of new active pharmaceutical ingredients (APIs). This paper proposes partial least squares (PLS) regression models to assess the impact of material properties on PBM parameters. The parameters of the compartmental one-dimensional PBMs were derived for ten formulations with varying liquid-to-solid ratios and connected with material properties and liquid-to-solid ratios by PLS models. As a result, key material properties were identified in order to calculate it with the necessary accuracy. Size- and moisture-related properties were influential in the wetting zone whereas density-related properties were more dominant in the kneading zones.

Availability optimization of power generating units used in sewage treatment plants using metaheuristic techniques.

Metaheuristic techniques have been utilized extensively to predict industrial systems' optimum availability. This prediction phenomenon is known as the NP-hard problem. Though, most of the existing methods fail to attain the optimal solution due to several limitations like slow rate of convergence, weak computational speed, stuck in local optima, etc. Consequently, in the present study, an effort has been made to develop a novel mathematical model for power generating units assembled in sewage treatment plants. Markov birth-death process is adopted for model development and generation of Chapman-Kolmogorov differential-difference equations. The global solution is discovered using metaheuristic techniques, namely genetic algorithm and particle swarm optimization. All time-dependent random variables associated with failure rates are considered exponentially distributed, while repair rates follow the arbitrary distribution. The repair and switch devices are perfect and random variables are independent. The numerical results of system availability have been derived for different values of crossover, mutation, several generations, damping ratio, and population size to attain optimum value. The results were also shared with plant personnel. Statistical investigation of availability results justifies that particle swarm optimization outdoes genetic algorithm in predicting the availability of power-generating systems. In present study a Markov model is proposed and optimized for performance evaluation of sewage treatment plant. The developed model is one that can be useful for sewage treatment plant designers in establishing new plants and purposing maintenance policies. The same procedure of performance optimization can be adopted in other process industries too.

A Causal View of the Role and Potential Limitations of Capitation in Promoting Whole Health System Performance.

For several decades, health systems in developed countries have faced rapidly rising healthcare costs without concomitant improvements in health outcomes. Fee for service (FFS) reimbursement mechanisms (RMs), where health systems are paid based on volume, contribute to this trend. In Singapore, the public health service is trying to curb rising healthcare costs by transitioning from a volume-based RM to a capitated payment for a population within a geographical catchment area. To provide insight into the implications of this transition, we developed a causal loop diagram (CLD) to represent a causal hypothesis of the complex relationship between RM and health system performance. The CLD was developed with input from government policymakers, healthcare institution administrators, and healthcare providers. This work highlights that the causal relationships between government, provider organizations, and physicians involve numerous feedback loops that drive the mix of health services. The CLD clarifies that a FFS RM incentivizes high margin services irrespective of their health benefits. While capitation has the potential to mitigate this reinforcing phenomenon, it is not sufficient to promote service value. This suggests the need to establish robust mechanisms to govern common pool resources while minimizing adverse secondary effects.

Heteropolysaccharides in sustainable corrosion inhibition: 4E (Energy, Economy, Ecology, and Effectivity) dimensions.

Carbohydrate polymers (polysaccharides) and their derivatives are widely utilized in sustainable corrosion inhibition (SCI) because of their various fascinating properties including multiple adsorption sites, high solubility and high efficiency. Contrary to traditional synthetic polymer-based corrosion inhibitors, polysaccharides are related to the 4E dimension, which stands for Energy, Economy, Ecology, and Effectivity. Furthermore, they are relatively more environmentally benign, biodegradable, and non-bioaccumulative. The current review describes the SCI features of various heteropolysaccharides, including gum Arabic (GA), glycosaminoglycans (chondroitin-4-sulfate (CS), hyaluronic acid (HA), heparin, etc.), pectin, alginates, and agar for the first time. They demonstrate impressive anticorrosive activity for different metals and alloys in a variety of corrosive electrolytes. Through their adsorption at the metal/electrolyte interface, heteropolysaccharides function by producing a corrosion-protective film. In general, their adsorption follows the Langmuir isotherm model. In their molecular structures, heteropolysaccharides contain several polar functional groups like -OH, -NH2, -COCH3, -CH2OH, cyclic and bridging O, -CH2SO3H, -SO3OH, -COOH, -NHCOCH3, -OHOR, etc. that serve as adsorption centers when they bind to metallic surfaces.

Assessment of hydrologic impact on flow regime due to dam inception using IHA framework.

In the last century, thousands of dams and diversions have been built to regulate the streamflow, resulting in water impoundment in the upstream and frequent drought conditions in the downstream. It has pressured researchers to study flow regime change and its complication on the downstream biota. The present study planned to develop a framework for trend analyzing of river flow and detecting flow regime change after the inception of Isapur and Arunavati dams, situated on the upstream side of Penganga bridge. Mann-Kendall (MK) and Sen's slope estimator for trend analysis and Indicators of Hydrologic Alteration (IHA) for flow regime alteration analysis were utilized. A total 26 parameters showed negatively altered flow regime with a magnitude varying from - 5.56 to - 100%. Fourteen altered parameters were modified drastically (more than 50% decrease) with the highest modification in 30-day maximum (100%) post-single dam inception. a total of 13 parameters were negatively altered with alteration value - 9.09 to - 86.36% post-double dam inception, out of which, three parameters were severely altered, with the highest alteration in the month of June. The period (1983-1994) was more altered than 1995-2016. This shows that Isapur dam has higher impact on flow regime change than Arunavati dam. Information about alteration of hydrological parameters will be helpful to improve the water flow regulation at Isapur and Arunavati dams for restoring river ecology on the downstream side.

Calibration of low-cost particulate matter sensors for coal dust monitoring.

Mining-induced coal dust causes various respiratory diseases to mine workers mainly coal workers' pneumoconiosis (CWP). Currently available underground monitors are expensive and bulky. These disadvantages limit them for regulatory sample monitoring purposes. Moreover, personal exposure levels for most miners remain unknown, risking them to potential overexposures. Low-cost light scattering particulate matter (PM) sensors offer a potential solution to this problem with the capability to characterize PM concentration with high spatio-temporal resolution. However, these sensors require precise calibration before they can be deployed in mining environments. No previous study has promulgated a standard protocol to assess these sensors for coal dust monitoring. The goal of this study was to calibrate Plantower PMS5003 sensors for coal dust monitoring using linear regression models. Two other commercially available PM sensors, the Airtrek and Gaslab CM-505 multi-gas sensors, were also evaluated and calibrated. They were evaluated for factors including linearity, precision, limit of detection, upper concentration limits, and the influence of temperature and relative humidity in a laboratory wind tunnel. The PMS5003 sensors were observed to be accurate below 3.0 mg/m3 concentration levels with R-squared values of 0.70 to 0.90 which was the best among the sensors under with an acceptable precision below 1.5 mg/m3. Moreover, this study shows that temperature and relative humidity have minimal influence on the efficacy of low-cost PM sensors' ability to monitor coal dust. This investigation reveals the feasibility of low-cost sensors for real-time personal coal dust monitoring in underground coal mines if a robust calibration model is applied.

Development and Validation of India-specific Hindi Version of Osteoporosis Knowledge Assessment Tool.

Purpose: Patient education is one of the important components of reducing the morbidity of osteoporosis. The aim of this study is to validate the Hindi version of the Osteoporosis Knowledge Assessment Tool (OKAT-H) among a hospital-based sample in the age group of 18-44 years of age. Methods: The study was conducted in two phases - translation and adaption of the OKAT in Hindi followed by its validation. The translated tool was analyzed by Flesch reading ease, McNemar test, Cronbach alpha, difficulty index, discrimination index, and principal factor analysis. Results: Two hundred and sixty women with a mean age of 28.3 ± 17.2 years were enrolled in the study. The mean score of the OKAT-H tool obtained in the study was 11.3 ± 2.1. A significant difference was noted in the scores based on educational qualification or with any family history of either osteoporosis or fracture (P < 0.05). The Flesch score for the OKAT-H tool was 86. Inter-item correlation for all the items ranged between 0.15 and 0.5. The Cronbach's alpha measured 0.892 suggesting high internal consistency. Items number 6, 7, 8, 9, 13, and 14 showed a significant difference on the McNemar test questioning its consistency on test-retest. Conclusion: A new shorter version of the tool may be developed since six items showed low consistency. The use of such an instrument in local language would help spread awareness about the disease as well as help the population in adopting osteoprotective strategies and also to seek help and advice regarding treatment.

Oral Health Status and Treatment Needs of Chromium Mine Workers in India.

Background: Several diseases are related to occupation. The workers in chromium mines may be exposed to hazardous environments. The objective of this research was to evaluate the oral health condition and treatment needs of chromium mine workers. Materials and Methods: This was a cross-sectional study conducted on workers in the chromium mines located in the Jajpur district, Odisha. The study included a total of 453 mine workers. The World Health Organization (WHO) oral health assessment proforma (1997) was used to assess the oral health status and treatment needs of the workers. Face-to-face interviews were conducted to acquire information on socio-demographic data, along with clinical examinations of type III. Frequency distribution analysis and independent-sample t-test were performed. Results: The majority of mineworkers demonstrated poor oral health status with high caries experience (Decayed Missing and Filled Tooth (DMFT) = 3.13 ± 1.82). The prevalence of tobacco consumption was very prevalent among them (74.8%). Leukoplakia (13.2%) was the most commonly noted oromucosal lesions. The buccal mucosa (16.8%) and commissures of the lips (3.3%) were the most common affected sites. Most workers demonstrated poor periodontal conditions. More than half of the mine workers (53.6%) showed malocclusion. Restoration, extraction, and pulp care were needed in most of the workers. Conclusion: A critical intervention should be provided to promote oral hygiene among Indian chromium mine workers. Dental health education and tobacco cessation programs are of utmost importance to improve the health conditions of these workers.

Outcomes and Readmission in Patients With Retinal Artery Occlusion (from the Nationwide Readmission Database).

Retinal artery occlusion (RAO) is an ophthalmologic emergency, leading to sudden vision loss. Understanding its risk factors and garnering information on the incidence of adverse events can provide helpful information on the cost-effective evaluation of patients and secondary prevention. In this retrospective cohort study, we used the Nationwide Readmission Database from 2016 to 2018 and queried the database to identify patients with RAO. The clinical outcomes were cumulative incidence of myocardial infarction (MI), stroke, death (in-hospital and 6 months after discharge), resource utilization, all-cause readmission at 6 months, and reasons for all-cause readmission. We identified a total of 14,527 patients with RAO. The mean age of patients with RAO was 69 ± 13 years. Hypertension (11,839, 82%), hyperlipidemia (8,868, 61%), ischemic cardiomyopathy (4,826, 33%), smoking (4,772, 33%), and diabetes (4,588, 32%) were common co-morbidities in patients with RAO. Of 14,527 patients with RAO, 308 patients (2.1%) died, 1,577 (10.9%) developed stroke, and 615 (4.2%) developed MI within 6 months. A total of 2,841 patients (24.9%) were readmitted within 6 months of discharge. Carotid artery stenosis (386, 10.8%) was the most common cause of readmission. History of stroke or transient ischemic attack and Elixhauser co-morbidity index ≥3 were predictors of stroke. Female gender, ischemic cardiomyopathy, carotid artery disease, heart failure, chronic kidney disease, and cancer were predictors of MI. Cancer, chronic kidney disease, Elixhauser co-morbidity index ≥3, Medicare/Medicaid payer status, nonelective index admission, atrial fibrillation, and carotid artery disease were predictors of 6-month all-cause readmission. In conclusion, patients with RAO have a significant burden of co-morbidities, death, stroke, MI, and readmission. RAO may be used as a clinical marker of future stroke and MI, and should trigger screening for acute vascular ischemic events.

Disparities in the Prescription of Statins in the Primary Care Setting: A Retrospective Observational Study.

Despite the high disease burden of atherosclerosis, evidence exists for the disparity in the prescription of guideline-indicated medications between genders, racial groups, socioeconomic groups, and ages. We aim to perform a retrospective study looking at the disparity in statin prescription for primary and secondary prevention in these groups. Data were collected from a single center and included patients with an LDL level >190 mg/dL, diagnosis of diabetes mellitus with LDL level >70 mg/dL, and diagnosis of cardiovascular disease regardless of LDL level. Patients older than 75 or younger than 21 were excluded from the study. Complex samples multivariable logistic and linear regression models were used to calculate the adjusted odds ratio and 95% confidence interval. The total study population was n = 56,995. Of those, 57.89% (n = 32,992) were female. Only 59.56 % of these patients for whom statin therapy was indicated received it. Most patients were White (53.21%) followed by African Americans (35.98%), Asians (2.43%), American Indian/Native Alaskans (0.40%), and Native Hawaiian/Pacific Islander (0.18%). There is a clear disparity in statin prescription favoring males, the elderly, and people of white ethnicity. Interestingly, Asians were more likely to be prescribed statins as opposed to whites. Self-pay patients were more likely to receive statins than patients on Medicare.Despite being indicated, Statins are under prescribed. Disparities based on race, gender, and insurance type mirror previous trends in the literature. Some results have shown a reversal in trends such as the higher prescription for Asian-Americans. Multiple patient-specific, provider-related, institutional factors might explain these disparities and must be investigated.

Capability assessment of conventional and data-driven models for prediction of suspended sediment load.

Information about suspended sediment concentration (SSC) in the stream is vital for sustainability of water conservation and erosion control planning, designing and monitoring. In this research, prediction of SSC has been done using artificial neural network (ANN), support vector regression (SVR) and multi-linear regression (MLR) models. Performance evaluation of developed models has been carried out on the basis of root mean square error (RMSE), correlation coefficient (r), coefficient of efficiency (CE) and pooled average relative error (PARE). Cross-correlation function (CCF) validated that gamma test (GT) is an appropriate tool for the selection of most responsive input variables. On the basis of GT and CCF, GT-6 model was selected as the model with most effective input variables, with the values of gamma, standard error and V-ratio as 0.0643, 0.00583 and 0.2570, respectively. The ANN (6-3-1) model performed better than the other single and double hidden layered ANN models with the values of r, RMSE, CE and PARE as 0.939, 0.0063 g/l, 85.17 and 0.0160, respectively. The performance of the SVR model was found better with the values of r, RMSE, CE and PARE as 0.906, 0.018 g/l, 79.09 and 0001, respectively, but slightly poor than the selected ANN (6-3-1) model. The values of r, RMSE, CE and PARE were found as 0.899, 0.0312 g/l, 65.15 and - 0.0031, respectively, in the case of MLR model. The present study revealed that among the ANN, SVR and MLR models, the ANN model with a single hidden layer is most suitable for observed SSC. The present study offers the simple efficient model to estimate the suspended sediment concentration in the stream with minimum error using limited data set.

A district-level analysis for measuring the effects of climate change on production of agricultural crops, i.e., wheat and paddy: evidence from India.

The present study aims to examine the impact of climate change on wheat and rice yield in Punjab, India, during 1981-2017. The study employs fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and pooled mean group (PMG) approaches. The Pedroni cointegration has established a long-run relationship of climate variables with rice and wheat crops. FMOLS and DOLS models show that minimum temperature has a positive effect on both wheat and rice. In contrast, the maximum temperature is found to be negatively contributing to both crops. Rainfall has a significant adverse impact on the production of wheat. In the study period, seasonal rainfall has been found detrimental for the production of wheat and rice crops, indicating that excess rainfall proved counterproductive. Moreover, the Dumitrescu-Hurlin causality test has revealed a unidirectional causality running from minimum temperature, rainfall, and maximum temperature for rice and wheat production. The findings of the study suggest that the government should invest in developing stress-tolerant varieties of wheat and rice, managing crop residuals to curb other environmental effects, and sustaining natural resources for ensuring food security.

PHi-RACE: PGIMER in-house rapid & cost effective classifier for the detection of BCR-ABL1-like acute lymphoblastic leukaemia in Indian patients.

For the detection of BCR-ABL1-like ALL cases, two methodologies, specifically Gene expression profiling (GEP) or Next-generation targeted sequencing (NGS) and TaqMan based low-density (TLDA) card, are being used. NGS is very costly and TLDA is not widely commercially available. In this study, we quantified the expression of 8 selected overexpressed genes in 536 B-ALL cases. We identified 26.67% (143/536) BCR-ABL1-like ALLs using hierarchical clustering and principal component analysis. BCR-ABL1-like ALL cases were significantly older at presentation (p = 0.036) and had male preponderance (p = 0.047) compared to BCR-ABL1-negative ALL cases. MRD-positivity and induction failure were more commonest in BCR-ABL1-like ALL cases (30.55 vs.19.35% in BCR-ABL1-negative ALL cases). Lastly, we built a PHi-RACE classifier (sensitivity = 95.2%, specificity= 83.7%, AUC= 0.927) using logistic regression to detect BCR-ABL1-like ALL cases promptly at diagnosis. This classifier is beneficial for hematologists in quick decision making at baseline to start tailored treatment regimes.

Assessment of Pattern of Oral Prosthetic Treatment and Prevalence of Oral Diseases in Edentulous Patients in North Indian Population: A Cross-sectional Study.

BACKGROUND: The present study was undertaken for assessing the pattern of oral prosthetic treatment and prevalence of dental diseases in edentulous patients in North Indian population. MATERIALS AND METHODS: A survey was carried out in North Indian population, and screening of the edentulous patients was done. Five hundred edentulous patients were enrolled. Complete oral and general examination was carried out. Pro forma was framed, and clinical details were recorded. Using mouth mirror and explorer, complete oral examination was carried out. Demographic profile was also evaluated. Prosthetic rehabilitation pattern of all the participants was also recorded. RESULTS: Complete removable denture and removable partial denture were method of rehabilitation in 28% and 31% of the participants. Dental implant-supported complete denture was used in 8% of the patients, whereas dental implant-supported overdenture was used in 33% of the participants. Ulcerative lesions were present in 5% of the patients, whereas oral leukoplakia was present in 4% of the patients. Oral lichen planus and torus were present in 2% and 1% of the patients. CONCLUSION: Majority of the geriatric patients prefer having removable denture. Furthermore, due to nutritional deficiency associated with geriatric age, oral leukoplakia and ulcerative lesions are more common in them.