Investigation of radioactivity and heavy metal levels in soil samples from neutral and vegetation land of Punjab, India.

In this work, radioactivity investigations of soil samples from neutral and agricultural sites in Punjab (India) have been carried out to study the impact of land use patterns. Analyzing soil samples radiological, mineralogical, and physicochemical attributes has employed state-of-the-art techniques. The mean activity concentration of 238U/226Ra, 232Th, 40K, 235U, and 137Cs, measured using a carbon fiber endcap p-type HPGe detector, in neutral land was observed as 58.03, 83.95, 445.18, 2.83, and 1.16 Bq kg-1, respectively. However, in vegetation land, it was found to be 40.07, 64.68, 596.74, 2.26, and 1.90 Bq kg-1, respectively. In the detailed activity analysis, radium equivalent (Raeq) radioactivity is in the safe prescribed limit of 370 Bq kg-1 for all investigated soil samples. However, the dosimetric investigations revealed that the outdoor absorbed gamma dose rate (96.08 nGy h-1) and consequent annual effective dose rate (0.12 mSv y-1) for neutral land and the gamma dose rate (82.46 nGy h-1) and subsequent annual effective dose rate (0.10 mSv y-1) for vegetation land marginally exceeded the global average. The soil's physicochemical parameters (pH, EC, and porosity) from both sites were measured, and their correlations with radionuclides were analyzed. Various heavy metals of health concern, namely, chromium (Cr), arsenic (As), copper (Cu), cobalt (Co), cadmium (Cd), lead (Pb), mercury (Hg), selenium (Se), and zinc (Zn), were also evaluated in soil samples using Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS). Pollution Load Index (PLI) and Ecological Risk Index (RI) revealed that vegetation land was more anthropogenically contaminated than neutral land, with maximum contamination from Hg and As.

Comparative host transcriptomics as a tool to identify candidate biomarkers for immune reactions in leprosy using meta-analysis.

Background Leprosy is no longer considered an imprecation, as an effective multidrug therapy regimen is available worldwide for its cure. However, its diverse clinical manifestations sometimes involve acute inflammatory reactions. These complications result in irreversible nerve damage, neuritis and anatomical deformities that emerge before, during the treatment or after the completion of treatment. Reversal reaction (Type-I) and erythema nodosum leprosum (Type-II) are the leprosy reactions generally seen in patients with lepromatous and borderline forms of leprosy. At present, there is no accurate diagnostic test available to detect these leprosy reactions. Objectives To identify potential biomarkers indicative of Type-I and Type-II leprosy reactions that could help in their early diagnosis. Methods and Results Host-transcriptomics investigations have been utilised in this study to decipher a correlation between host-gene expression-based biomarkers and exacerbation of leprosy reactions. We present a comparative analysis of publicly available host transcriptomics datasets (from Gene Expression Omnibus) related to leprosy reactions. Individual datasets were analysed and integration of results was carried out using meta-analysis. Common differentially expressed genes (DEGs) were identified using the frequentist and Bayesian ratio association test methods. We have identified several genes - ADAMTS5, ADAMTS9, IFITM2, IFITM3, KIRREL, ANK3, CD1E, CTSF, DOCK9 and KRT73 to name a few - which can serve as potential biomarkers for Type-II reaction. Similarly, ACP5, APOC1, CCL17, S100B, SLC11A1 among others may likely serve as biomarkers for Type-I reaction. Limitations The number of datasets related to leprosy reactions found after the systematic search is less (n = 4) and may limit the accuracy of identified biomarker genes. This could be resolved by including more studies in the data analysis. Conclusion We provide a comprehensive list of gene candidates which could be prioritised further in research focusing on immune reactions in leprosy, as they are likely important in understanding its complexities and could be useful in its early diagnosis.

Comparative analysis of parametric B-spline and Hermite cubic spline based methods for accurate ECG signal modeling.

Analyzing Electrocardiogram (ECG) signals is imperative for diagnosing cardiovascular diseases. However, evaluating ECG analysis techniques faces challenges due to noise and artifacts in actual signals. Machine learning for automatic diagnosis encounters data acquisition hurdles due to medical data privacy constraints. Addressing these issues, ECG modeling assumes a crucial role in biomedical and parametric spline-based methods have garnered significant attention for their ability to accurately represent the complex temporal dynamics of ECG signals. This study conducts a comparative analysis of two parametric spline-based methods-B-spline and Hermite cubic spline-for ECG modeling, aiming to identify the most effective approach for accurate and reliable ECG representation. The Hermite cubic spline serves as one of the most effective interpolation methods, while B-spline is an approximation method. The comparative analysis includes both qualitative and quantitative evaluations. Qualitative assessment involves visually inspecting the generated spline-based models, comparing their resemblance to the original ECG signals, and employing power spectrum analysis. Quantitative analysis incorporates metrics such as root mean square error (RMSE), Percentage Root Mean Square Difference (PRD) and cross correlation, offering a more objective measure of the model's performance. Preliminary results indicate promising capabilities for both spline-based methods in representing ECG signals. However, the analysis unveils specific strengths and weaknesses for each method. The B-spline method offers greater flexibility and smoothness, while the cubic spline method demonstrates superior waveform capturing abilities with the preservation of control points, a critical aspect in the medical field. Presented research provides valuable insights for researchers and practitioners in selecting the most appropriate method for their specific ECG modeling requirements. Adjustments to control points and parameterization enable the generation of diverse ECG waveforms, enhancing the versatility of this modeling technique. This approach has the potential to extend its utility to other medical signals, presenting a promising avenue for advancing biomedical research.

Dual role of arsenite in hydrolysis and post-hydrolysis fluorescence sensing of selective pH-dependent probes.

In comparison to the sensing activity, the reactivity of arsenite (AsO2-) is less explored. Herein, we focused on AsO2- reactivity studies based on its pKa and compared the study with other common anions. All three pKa values of arsenite are >9.0, affording a flexible working pH range to design a probe for reactivity studies. We designed and synthesized six pH dependent benzothiazole-based Schiff bases, namely, 1-(((6-nitrobenzo[d]thiazol-2-yl)imino)methyl)naphthalen-2-ol (1), 5-(diethylamino)-2-(((6-nitrobenzo[d]thiazol-2-yl)imino)methyl)phenol (2), 9-(((6-nitrobenzo[d]thiazol-2-yl)imino)methyl)-2,3,6,7-tetrahydro-1H,5H-pyrido[3,2,1-ij]quinolin-8-ol (3), 5-methoxy-2-(((6-nitrobenzo[d]thiazol-2-yl)imino)methyl)phenol (4), 4-(((6-nitrobenzo[d]thiazol-2-yl)imino)methyl)benzene-1,3-diol (5), and 2-(((6-nitrobenzo[d]thiazol-2-yl)imino)methyl)phenol (6), as probes for hydrolysis studies containing 5% water in acetonitrile. In spite of the presence of water in the solution, no hydrolysis was observed for all the probes in the absence of a salt. In the presence of selected sodium salts of various anions in solution, intramolecular charge transfer (ICT) was observed after the deprotonation of an aromatic hydroxy group at the ortho position with respect to the imine groups within the probes. Among the studied anions, selective AsO2- induced imine hydrolysis was observed for probes 1 and 4. In the case of 5 with both o- and p-hydroxy groups, no hydrolysis was observed in the presence of AsO2-. Probe 6 with only the o-hydroxy group showed very fast hydrolysis with poor selectivity. The p-hydroxy group in 4-(((6-nitrobenzo[d]thiazol-2-yl)imino)methyl)phenol (7) resulted in poor AsO2- induced hydrolysis. The aldehyde, which was generated after hydrolysis of probe 1, showed selective emission at 450 nm in the presence of AsO2-. The time dependent hydrolysis reaction of probe 1 controls the emission intensity enhancement.

Evaluating therapeutic potential of NR2E3 doses in the rd7 mouse model of retinal degeneration.

Retinitis Pigmentosa is a leading cause of severe vision loss. Retinitis Pigmentosa can present with a broad range of phenotypes impacted by disease age of onset, severity, and progression. This variation is influenced both by different gene mutations as well as unique variants within the same gene. Mutations in the nuclear hormone receptor 2 family e, member 3 are associated with several forms of retinal degeneration, including Retinitis Pigmentosa. In our previous studies we demonstrated that subretinal administration of one Nr2e3 dose attenuated retinal degeneration in rd7 mice for at least 3 months. Here we expand the studies to evaluate the efficacy and longitudinal impact of the NR2E3 therapeutic by examining three different doses administered at early or intermediate stages of retinal degeneration in the rd7 mice. Our study revealed retinal morphology was significantly improved 6 months post for all doses in the early-stage treatment groups and for the low and mid doses in the intermediate stage treatment groups. Similarly, photoreceptor function was significantly improved in the early stage for all doses and intermediate stage low and mid dose groups 6 months post treatment. This study demonstrated efficacy in multiple doses of NR2E3 therapy.

Qualitative study to explore the perspectives and mental health experiences of first episode psychosis patients and their caregivers in North India.

BACKGROUND: The onset of psychosis brings unfamiliar experiences that can be disturbing for patients and their caregivers. Few studies from India (only one from North India) have examined these experiences from the perspective of the patient and caregiver. We explored experiences of first episode psychosis (FEP) patients and their caregivers within a North Indian context. METHOD: Semi-structured interviews were conducted in 2019 with ten FEP patients and their caregivers (total n=20) receiving out-patient care in a tertiary care centre. Topic guides focused on concerns/complaints, symptoms, help-seeking, and barriers and facilitators to treatment. Interviews were audio recorded, transcribed, and analysed using qualitative content analysis. RESULTS: Main categories of responses from patients and caregivers included: initial complaints for seeking help, initial emotional response, barriers to seeking treatment, perceived dysfunction and improvement, experienced stigma, understanding about illness, early follow-up, preventive measures and awareness programs. Caregivers undergo myriad of emotional reactions including anger, anxiety, guilt, and confusion. Symptoms other than psychotic symptoms were the primary complaint upon seeking help, and there was lack of understanding about the psychosocial model of care (role of medications acknowledged with little awareness regarding psychosocial interventions in recovery). Persisting occupational dysfunction despite perceived symptomatic improvement was described by both patients and caregivers. CONCLUSION: North Indian patients with FEP lack awareness of symptoms. Therefore, onus for seeking help often falls on their caregivers. Psychoeducation from first contact with services and increasing awareness about psychotic illness within the community might help address lack of awareness about symptoms, mental health services, early signs of relapse, and importance of psychosocial interventions in achieving functional recovery.

Pilot study to test the feasibility and clinical efficacy of a psychosocial care programme for patients with psychosis in low-resource settings.

BACKGROUND: Home-based psychosocial care has the potential to improving outcomes in patients with schizophrenia and related disorders (SCZ). There is lack of India data for such care in early psychosis. We developed the "Saksham" programme, a bespoke self-managed home-based psychosocial care model, available in two formats: manual-based and mobile-application based. With the anticipated success of recruitment of early psychosis cases in our setting, we plan to test the such intervention in this population in future trials. AIM: To assess the feasibility of the Saksham programme intervention in people with SCZ and its clinical efficacy as an adjunct to treatment as usual. METHODS: Seventy-five patient-caregiver pairs (total n=150) were recruited. Patients received either: treatment-as-usual (TAU) (n=25), manual-based Saksham intervention+TAU (n=25), or app-based Saksham intervention+TAU (n=25). Feasibility (i.e. acceptability, practicality, demand, implementation and integration) was assessed at three-months. Participants were assessed for psychopathology, illness-severity, cognition, functioning, disability, and caregiver-coping at baseline, one-month, and three-month. The percentage changes over time were compared across three groups. RESULTS: More found the mobile application-based intervention acceptable and easy-to-use than the manual-based intervention (92 % vs 68 %, and 76 % vs 68 %, respectively). Psychopathology and caregiver-burden improved significantly in all three groups (p<0.05). Cognition, disability, functioning, and caregiver burden improved significantly in the two Saksham intervention groups, with greater improvement in the Saksham app group (p<0.05). CONCLUSION: Home-based intervention is feasible and acceptable in a low-resource setting, with preliminary evidence for effectiveness. These findings need corroboration with randomised controlled trials in early psychosis to ameliorate course of illness.

Genomic characterization of Influenza A (H1N1)pdm09 and SARS-CoV-2 from Influenza Like Illness (ILI) and Severe Acute Respiratory Illness (SARI) cases reported between July-December, 2022.

Influenza Like Illness (ILI) and Severe Acute Respiratory Infection (SARI) cases are more prone to Influenza and SARS-CoV-2 infection. Accordingly, we genetically characterized Influenza and SARS-CoV-2 in 633 ILI and SARI cases by rRT-PCR and WGS. ILI and SARI cases showed H1N1pdm09 prevalence of 20.9% and 23.2% respectively. 135 (21.3%) H1N1pdm09 and 23 (3.6%) H3N2 and 5 coinfection (0.78%) of H1N1pdm09 and SARS-CoV-2 were detected. Phylogenetic analysis revealed H1N1pdm09 resemblance to clade 6B.1A.5a.2 and their genetic relatedness to InfA/Perth/34/2020, InfA/Victoria/88/2020 and InfA/Victoria/2570/2019. Pan 24 HA and 26 NA nonsynonymous mutations and novel HA (G6D, Y7F, Y78H, P212L, G339R, T508K and S523T) and NA (S229A) mutations were observed. S74R, N129D, N156K, S162N, K163Q and S164T alter HA Cb and Sa antibody recognizing site. Similarly, M19T, V13T substitution and multiple mutations in transmembrane and NA head domain drive antigenic drift. SARS-CoV-2 strains genetically characterized to Omicron BA.2.75 lineage containing thirty nonsynonymous spike mutations exhibited enhanced virulence and transmission rates. Coinfection although detected very minimal, the mutational changes in H1N1pdm09 and SARS-CoV-2 virus infected individuals could alter antibody receptor binding sites, allowing the viruses to escape immune response resulting in better adaptability and transmission. Thus continuous genomic surveillance is required to tackle any future outbreak.

Investigating the Presence of Rotavirus in Wastewater Samples of Bhopal Region, India, by Utilizing Droplet Digital Polymerase Chain Reaction.

INTRODUCTION: Rotavirus-induced viral gastroenteritis outbreaks result in over two million hospitalizations globally yearly. Wastewater-based epidemiology (WBE) has emerged as a crucial tool for detecting and monitoring viral outbreaks. The adoption of WBE has been instrumental in the early detection and surveillance of such viral outbreaks, providing a non-invasive method to assess public health. OBJECTIVE: This study aims to utilize droplet digital polymerase chain reaction (ddPCR) technology to detect and quantify Rotavirus in wastewater samples collected from the Bhopal region of India, thereby contributing to the understanding and management of viral gastroenteritis outbreaks through environmental surveillance. METHODS: In this study, we used ddPCR to detect and quantify Rotavirus in wastewater samples collected from the Bhopal region of India. We monitored its viral presence in municipal sewage treatment plants bi-weekly using an advanced ddPCR assay. Targeting the rotavirus non-structural protein 3 (NSP-3) region with custom primers and TaqMan probes, we detected virus concentration employing polyethylene glycol (PEG). Following RNA isolation, complementary DNA (cDNA) synthesis, and ddPCR analysis, our novel method eliminated standard curve dependence, propelling virus research and treatment forward. RESULTS: Out of the 42 samples collected, a 16.60% positivity rate was observed, indicating a moderate presence of Rotavirus in Bhopal. The wastewater treatment plants (WWTP) attached to a hospital exhibited a 42.85% positivity rate, indicating the need for targeted monitoring. Leveraging ddPCR, precise quantification of rotavirus concentrations (ranging from 0.75 to 28.9 copies/µL) facilitated understanding and supported effective remediation. CONCLUSIONS:  This study emphasizes the importance of vigilant wastewater surveillance, especially in WWTPs with higher rotavirus prevalence. The significance of ddPCR in comparison to conventional and real-time PCR lies in its superior sensitivity and specificity in detecting and quantifying positive samples. Furthermore, it can identify positive samples even in the smallest quantities without the need for a standard curve to evaluate. This makes ddPCR a valuable tool for accurate and precise detection and quantification of samples.

Exploring a new frontier in cardiac diagnosis: ECG analysis enhanced by machine learning and parametric quartic spline modeling.

The heart's study holds paramount importance in human physiology, driving valuable research in cardiovascular health. However, assessing Electrocardiogram (ECG) analysis techniques poses challenges due to noise and artifacts in authentic recordings. The advent of machine learning systems for automated diagnosis has heightened the demand for extensive data, yet accessing medical data is hindered by privacy concerns. Consequently, generating artificial ECG signals faithful to real ones is a formidable task in biomedical signal processing. This paper introduces a method for ECG signal modeling using parametric quartic splines and generating a new dataset based on the modeled signals. Additionally, it explores ECG classification using three machine learning techniques facilitated by Orange software, addressing both normal and abnormal sinus rhythms. The classification enables early detection and prediction of heart-related ailments, facilitating timely clinical interventions and improving patient outcomes. The assessment of synthetic signal quality is conducted through power spectrum analysis and cross-correlation analysis, power spectrum analysis of both real and synthetic ECG waves provides a quantitative assessment of their frequency content, aiding in the validation and evaluation of synthetic ECG signal generation techniques. Cross-correlation analysis revealing a robust correlation coefficient of 0.974 and precise alignment with a negligible time lag of 0.000 s between the synthetic and real ECG signals. Overall, the adoption of quartic spline interpolation in ECG modeling enhances the precision, smoothness, and fidelity of signal representation, thereby improving the effectiveness of diagnostic and analytical tasks in cardiology. Three prominent machine learning algorithms, namely Decision Tree, Logistic Regression, and Gradient Boosting, effectively classify the modeled ECG signals with classification accuracies of 0.98620, 0.98965, and 0.99137, respectively. Notably, all models exhibit robust performance, characterized by high AUC values and classification accuracy. While Gradient Boosting and Logistic Regression demonstrate marginally superior performance compared to the Decision Tree model across most metrics, all models showcase commendable efficacy in ECG signal classification. The study underscores the significance of accurate ECG modeling in health sciences and biomedical technology, offering enhanced accuracy and flexibility for improved cardiovascular health understanding and diagnostic tools.

Sequential trypsin and ProAlanase digestions unearth immunological protein biomarkers shrouded by skeletal collagen.

This study investigates the efficacy of proteomic analysis of human remains to identify active infections in the past through the detection of pathogens and the host response to infection. We advance leprosy as a case study due to the sequestering of sufferers in leprosaria and the suggestive skeletal lesions that can result from the disease. Here we present a sequential enzyme extraction protocol, using trypsin followed by ProAlanase, to reduce the abundance of collagen peptides and in so doing increase the detection of non-collagenous proteins. Through our study of five individuals from an 11th to 18th century leprosarium, as well as four from a contemporaneous non-leprosy associated cemetery in Barcelona, we show that samples from 2 out of 5 leprosarium individuals extracted with the sequential digestion methodology contain numerous host immune proteins associated with modern leprosy. In contrast, individuals from the non-leprosy associated cemetery and all samples extracted with a trypsin-only protocol did not. Through this study, we advance a palaeoproteomic methodology to gain insights into the health of archaeological individuals and take a step toward a proteomics-based method to study immune responses in past populations.

Exploring the feasibility, acceptability and preliminary effects of a nurse delivered mhealth intervention for women living with HIV in South India: a pilot randomized controlled trial.

PURPOSE: We evaluated the feasibility, acceptability and preliminary efficacy of a standardized nurse delivered mobile phone intervention to improve adherence to antiretroviral treatment and clinical outcomes. METHODS: Feasibility and acceptability of the phone intervention was assessed with rates of eligibility, completed visits, and attritions. Intervention fidelity was assessed by checking recorded calls and feedback. Efficacy was assessed using a randomized controlled trial in which 120 women living with HIV and psychosocial vulnerabilities, were randomized to Treatment as Usual (TAU = 60) or TAU plus the mobile phone intervention (N = 60). Trained basic nurses delivered the theory-guided, standardized mobile phone intervention for mental health issues and psychosocial risk factors to improve antiretroviral treatment (ART) adherence and retention in care and improve clinical outcomes. Blind raters performed the assessments at 6, 12 and 24 weeks post-randomization. RESULTS: Adherence diminished over time in the TAU only group, while it was sustained in the TAU Plus group, only dropping at 24 weeks after the intervention had been discontinued. Among participants with depressive symptoms (CESD ≥ 16), the intervention had significant improvement in adherence rates (p < 0.01), psychological quality of life (p < 0.05) and illness perception (p < 0.05) compared to those in the TAU only group. Greater improvements of quality of life subscales were observed in the TAU Plus group among participants with less psychological vulnerability (PSV < 2). HIV RNA was not significantly different between the groups at week 24. CONCLUSIONS: The mobile-delivered counseling intervention was feasible and acceptable and shows promise among women living with HIV and psychosocial vulnerabilities in rural South India. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02319330 [Registered on: December 18, 2014].

Genetic diversity of Mycobacterium leprae: Need to move towards genome-wide approaches.

ABSTRACT: Leprosy, an ancient disease, continues to be a public health concern as it remains endemic in several countries. After reaching the elimination target (1/10,000) as a public health problem in 2005 in India, around 1.2 lakh cases have been detected every year over the last decade indicating active transmission of leprosy bacillus (Mycobacterium leprae). Single-nucleotide polymorphisms (SNPs), genomic insertions/deletions and variable-number tandem repeats (VNTRs) have been identified as genetic markers for tracking M. leprae transmission. As the leprosy bacilli cannot be cultured in vitro, molecular testing of M. leprae genotypes is done by polymerase chain reaction-based sequencing which provides a practical alternative for the identification of strains as well as drug resistance-associated mutations. Whole-genome sequencing (WGS) of M. leprae directly from clinical samples has also proven to be an effective tool for identifying genetic variations which can further help refine the molecular epidemiological schemes based on SNPs and VNTRs. However, the WGS data of M. leprae strains from India are scarce, being responsible for a gross under-representation of the genetic diversity of M. leprae strains present in India and need to be addressed suitably. Molecular studies of leprosy can provide better insight into phylogeographic markers to monitor the transmission dynamics and emergence of antimicrobial resistance. An improved understanding of M. leprae transmission is essential to guide efficient leprosy control strategies. Therefore, this review compiles and discusses the current status of molecular epidemiology, genotyping and the potential of genome-wide analysis of M. leprae strains in the Indian context.

Cone-beam computed tomography (CBCT) dose optimization technique and image quality assessment scoring.

INTRODUCTION: Linear accelerator (LINAC) embedded with kV source-imager system is capable to do image-guided radiotherapy. The only disadvantage of cone-beam computed tomography image acquisition during treatment is the extra radiation dose to the patient. The aim of this study is to optimize the CBCT imaging doses likely to be received by the patient undergoing radiotherapy without affecting image quality. MATERIAL AND METHODS: The imaging dose to the patient was estimated on CTDI phantoms. The effect of additional filters of different materials (copper, brass, aluminum of thickness 0.1 mm each) was evaluated to find the optimized dose imaging technique. For the pelvis, a single imaging protocol available on the machine was used, whereas for the head and neck region, two protocols, high-quality head and standard-dose head were used. The image quality was assessed on CATPHAN-504 phantom using Owl CATPHAN® QA online tool. A new term "Image Assessment score" (IAS) was introduced to evaluate the image quality. RESULT: In the pelvis protocol, CBCT imaging doses with an additional 0.1-mm brass, copper, and aluminum filter were measured to be reduced by 7.1%, 4.7%, and 2.5%, respectively, whereas for high-quality head protocol, the dose reduction was 25.4% (with brass filter), 22% (with copper filter), and 3.1% (with aluminum filter). For the standard-dose head protocol, doses were reduced by 7.5%, 2.8%, and 2.1% with additional 0.1-mm brass copper and aluminum filters, respectively. Acceptable image quality was observed with all the filters. CONCLUSION: Although the reconstructed images were found somewhat noisier, they did not affect the purpose of imaging, that is, treatment position verification. It was observed that these extra filters further reduce the imaging dose without much affecting the image quality.

Challenges in commissioning the "TSET" technique: A new approach towards monitor unit calculation and beam profile measurements.

INTRODUCTION: Total skin electron beam therapy, commonly known as TSET, is a good choice of treatment for patients suffering from mycosis fungoides. The aim of this study was to introduce a new approach to the beam profile measurement using diodes and to calculate the monitor units required for the TSET treatment by the use of a simple setup of output measurement. Dosimetric measurements required for the treatment were taken to establish the Stanford technique in the department, and the measured data was compared with the published data. MATERIALS AND METHODS: High-energy Linear Accelerator Clinac-DHX, Varian medical system, Palo Alto, CA, was commissioned for TSET. The output of the machine was measured by the use of a Parallel-Plate Chamber (PPC40) as per the TRS 398 recommendation. Diode dosimeters (EDD2 and EDD5) were used for beam profile measurements due to easy setup and to reduce the measurement time. RESULTS: Homogeneous dose distribution within a field size of 80 cm x160 cm was observed with the variation of -5.0% on the horizontal axis and -5.4% on the vertical axis. The calculated monitor unit to deliver 200 cGy per fraction per field at the source to surface (SSD) of 416 cm was 489 MU. CONCLUSION: The technique described for the output measurements is simple and accurate. Results of the absorbed dose and MU measured were within good agreement compared to the published literature.

ECG arrhythmia detection in an inter-patient setting using Fourier decomposition and machine learning.

ECG beat classification or arrhythmia detection through artificial intelligence (AI) is an active topic of research. It is vital to recognize and detect the type of arrhythmia for monitoring cardiac abnormalities. The AI-based ECG beat classification algorithms proposed in the literature suffer from two main drawbacks. Firstly, some of the works have not considered any unseen test data to validate the performance of their algorithms. Secondly, the accuracy of detecting superventricular ectopic beats (SVEB) needs to be improved. In this work, we address these issues by considering an inter-patient paradigm where the test dataset is collected from a different set of subjects than the training data. Also, the proposed methodology detects SVEB with an F1 score of 89.35%, which is better than existing algorithms. We have used the Fourier decomposition method (FDM) for multi-scale analysis of ECG signals and extracted time-domain and statistical features from the narrow-band signal components obtained using FDM. Feature selection techniques, including the Kruskal-Wallis test and minimum redundancy maximum relevance (mRMR) have been used to select only the relevant features and rank these features to remove any redundancy. Since the dataset used is highly imbalanced, Mathew's correlation coefficient (MCC) has also been used to analyze the performance of the proposed method. Support vector machine classifier with linear kernel achieves an overall 98.03% accuracy and 91.84% MCC for the MIT-BIH arrhythmia dataset.

A comprehensive profile of SARS-CoV-2 variants spreading during the COVID-19 pandemic: a genomic characterization study from Chhattisgarh State, India.

SARS-CoV-2 has expressively changed its sequences during the COVID-19 pandemic situation by encompassing persistent evolutionary mutational changes resulting in the emergence of many clades and lineages. Evolution of these SARS-CoV-2 variants have significantly imparted fitness advantage to the virus, enhanced its transmissibility and severity of the disease. These new variants are a potential threat to the vaccine efficacy as well. It is therefore pertinent to monitor the evolution of these variants and their epidemiological and clinical impact, in a geographic setting. This study has thus looked into the geographic distribution and genetic diversity of SARS-CoV-2 variants and the evolutionary circulation of different clades in Chhattisgarh (CG) state from March 2020 to July 2023. A total of 3018 sequences were retrieved from the GISAID database, in which 558 were submitted by us. The demographic data revealed male preponderance of 56.45% versus 43.54% females, with the overall mean age of 36.5 years. SARS-CoV-2 sequences represented many variants viz., Delta (55%), Omicron (22%) and others (15%) with a small proportion of recombinant (5%), Kappa (2%), and Alpha (1%). The viral clades G was found predominant for a year from initial days of pandemic in March, 2020 to January, 2021 which then subsequently evoluted to subclade GK (Delta B.1.617.2) and remained in circulation in CG till November, 2021. From December 2021, the GRA (Omicron B.1.1.529) variant had replaced GK to become the dominant strain and continues to predominate in present time. GRA clade is however continuously encompassing new recombinant strains, having various non-synonymous mutations especially in spike protein. The non-synonymous mutation P314L in ORF1b, S84L in ORF8 and D614G in spike protein were found as the pan mutation carried over from clade G to GRA. The continuous evolution in SARS-CoV2 warrants periodical geographic genomic surveillance monitoring to timely detect any new variants having the potential of causing future outbreak.

Preclinical dose response study shows NR2E3 can attenuate retinal degeneration in the retinitis pigmentosa mouse model RhoP23H+/.

Retinitis pigmentosa (RP) is a heterogeneous disease and the main cause of vision loss within the group of inherited retinal diseases (IRDs). IRDs are a group of rare disorders caused by mutations in one or more of over 280 genes which ultimately result in blindness. Modifier genes play a key role in modulating disease phenotypes, and mutations in them can affect disease outcomes, rate of progression, and severity. Our previous studies have demonstrated that the nuclear hormone receptor 2 family e, member 3 (Nr2e3) gene reduced disease progression and loss of photoreceptor cell layers in RhoP23H-/- mice. This follow up, pharmacology study evaluates a longitudinal NR2E3 dose response in the clinically relevant heterozygous RhoP23H mouse. Reduced retinal degeneration and improved retinal morphology was observed 6 months following treatment evaluating three different NR2E3 doses. Histological and immunohistochemical analysis revealed regions of photoreceptor rescue in the treated retinas of RhoP23H+/- mice. Functional assessment by electroretinogram (ERG) showed attenuated photoreceptor degeneration with all doses. This study demonstrates the effectiveness of different doses of NR2E3 at reducing retinal degeneration and informs dose selection for clinical trials of RhoP23H-associated RP.

A novel partitioning of gross primary production and water use efficiency for sustaining water and food security using Budyko hypothesis.

This study coupled the green water and blue water accounting with the existing standard Budyko framework and Fu's 1-parameter Budyko framework to diagnose the basin hydrological behavior. Both Budyko frameworks were employed to determine green water consumption (ETGreen) and blue water consumption (ETBlue) which, in turn, were used to map the blue water index (BWI) hotspots and green water index (GWI) bright spots. The relative contributions of green water and blue water were quantified for sustaining water and food security. A new methodology is proposed using BWI and GWI for partitioning the Gross Primary Production (GPP) and Water Use Efficiency (WUE) into GPPBlue, GPPGreen and WUEBlue and WUEGreen. The methodology was applied to five sub-basins of the Central Godavari River Basin (CGRB): Purna, Dhalegaon, GR Bridge, Yeli and Delta. Results showed that all five basins exhibited larger deviations from the theoretical Budyko curve of Fu's 1-parameter Budyko framework than did the standard Budyko framework and the Dhalegaon basin showed the largest deviations. The partitioning of GPP and WUE by the proposed methodology showed that the proportion of GPPGreen to the total GPP was much higher than that of the GPPBlue. Similarly, the proportion of WUEGreen to WUE was more than that of WUEBlue. The mapping of GPPBlue and GPPGreen, and WUEBlue and WUEGreen showed that the Delta and Yeli basins had the highest values of both GPPGreen & GPPBlue and WUEBlue and WUEGreen (bright spot basins) and the Dhalegaon and parts of GR Bridge basin had the lowest values (hot spot basins). The proposed partitioning of GPP and WUE will help identify the relative contributions of green water and blue water (for managing agricultural waters) and formulate agronomical and engineering practices for stakeholders and policy makers for increasing the overall WUE and GPP to sustain water and food security.

Novel mutations found in Mycobacterium leprae DNA repair gene nth from central India.

INTRODUCTION: The importance of DNA repair enzymes in maintaining genomic integrity is highlighted by the hypothesis that DNA damage by reactive oxygen/nitrogen species produced inside the host cell is essential for the mutagenesis process. Endonuclease III (Nth), formamidopyrimide (Fpg) and endonuclease VIII (Nei) DNA glycosylases are essential components of the bacterial base excision repair process. Mycobacterium leprae lost both fpg/nei genes during the reductive evolution event and only has the nth (ML2301) gene. This study aims to characterize the mutations in the nth gene of M. leprae strains and explore its correlation with drug-resistance. METHOD: A total of 91 M. leprae positive DNA samples extracted from skin biopsy samples of newly diagnosed leprosy patients from NSCB Hospital Jabalpur were assessed for the nth gene as well as drug resistance-associated loci of the rpoB, gyrA and folP1 genes through PCR followed by Sanger sequencing. RESULTS: Of these 91 patients, a total of two insertion frameshift mutations, two synonymous and seven nonsynonymous mutations were found in nth in seven samples. Sixteen samples were found to be resistant to ofloxacin and one was found to be dapsone resistant as per the known DRDR mutations. No mutations were found in the rpoB region. Interestingly, none of the nth mutations were identified in the drug-resistant associated samples. CONCLUSION: The in-silico structural analysis of the non-synonymous mutations in the Nth predicted five of them were to be deleterious. Our results suggest that the mutations in the nth gene may be potential markers for phylogenetic and epidemiological studies.