Clinical Profile and Adverse Effects of Dolutegravir Treatment in HIV-Positive Patients: A Prospective Observational Study.

Background The emergence of dolutegravir (DTG) within antiretroviral therapy (ART) has drastically improved the management of HIV/AIDS, marking a shift toward a chronic manageable condition. Nevertheless, concerns persist regarding the real-world tolerability and adverse effects (AEs) of DTG. Objective This study aims to explore the clinical characteristics, adverse reactions, and adherence to treatment with DTG among HIV-positive individuals. Methods Through a prospective approach, we examined HIV-positive patients undergoing DTG-based ART regimens. Key parameters, including socio-demographic data, treatment adherence, and clusters of differentiation 4 (CD4) count, were evaluated. Enrolled patients were followed up for six months for the development of comorbidities and AEs. Results Initial observations indicate successful viral suppression and enhanced CD4 counts with DTG-based regimens, t(318)=2.0664, p=0.0392. However, a subset of participants experienced AEs such as neuropsychiatric symptoms (headaches and mood fluctuations), unintended weight gain, and other comorbidities linked to prolonged ART usage. Conclusion While DTG-based therapies offer substantial advantages in HIV/AIDS management, such as rapid viral suppression and reduced toxicity, ongoing vigilance for adverse effects, particularly neuropsychiatric symptoms and metabolic disturbances, is imperative for optimizing patient care. Further research is necessary to fully elucidate the safety profile of DTG in real-world scenarios and mitigate potential adverse reactions.

Extremozymes and compatible solute production potential of halophilic and halotolerant bacteria isolated from crop rhizospheric soils of Southwest Saurashtra Gujarat.

Halophiles are one of the classes of extremophilic microorganisms that can flourish in environments with very high salt concentrations. In this study, fifteen bacterial strains isolated from various crop rhizospheric soils of agricultural fields along the Southwest coastline of Saurashtra, Gujarat, and identified by 16S rRNA gene sequencing as Halomonas pacifica, H. stenophila, H. salifodinae, H. binhaiensis, Oceanobacillus oncorhynchi, and Bacillus paralicheniformis were investigated for their potentiality to produce extremozymes and compatible solute. The isolates showed the production of halophilic protease, cellulase, and chitinase enzymes ranging from 6.90 to 35.38, 0.004-0.042, and 0.097-0.550 U ml-1, respectively. The production of ectoine-compatible solute ranged from 0.01 to 3.17 mg l-1. Furthermore, the investigation of the ectoine-compatible solute production at the molecular level by PCR showed the presence of the ectoine synthase gene responsible for its biosynthesis in the isolates. Besides, it also showed the presence of glycine betaine biosynthetic gene betaine aldehyde dehydrogenase in the isolates. The compatible solute production by these isolates may be linked to their ability to produce extremozymes under saline conditions, which could protect them from salt-induced denaturation, potentially enhancing their stability and activity. This correlation warrants further investigation.

Patterns of brain metastases response to immunotherapy with pembrolizumab.

PURPOSE: Central nervous system (CNS) metastases from lung cancers and melanoma, significantly contribute to morbidity and mortality. Despite advances in local therapies, there is a need for effective systemic treatments. Pembrolizumab, a PD-1 inhibitor, has shown promise for some patients with untreated brain metastases from melanoma and non-small cell lung cancer (NSCLC). This study aims to analyze the response of brain metastasis to pembrolizumab and associate characteristics like size and location with treatment outcome. METHODS: This retrospective study used imaging data from a phase II trial of pembrolizumab in melanoma or NSCLC patients with untreated brain metastases. MRI evaluations were conducted at 2 month intervals, with each brain metastasis treated as a distinct tumor for response assessment, based on modified RECIST criteria (maximum 5 lesions, 5 mm target lesions). RESULTS: Of 130 individual target metastases (> 5 mm), in 65 patients with NSCLC (90 metastases) and Melanoma (40 metastases), 32 (24.6%) demonstrated complete resolution, 24 (18.5%) had partial resolution, 32 (24.6%) were SD and 42 (32.3%) demonstrated PD. Those smaller than 10 mm were more likely to show complete resolution (p = 0.0218), while those ≥ 10 mm were more likely to have PR. There was no significant association between size, number or location (supratentorial vs. infratentorial) and lesion progression. The median time to metastatic lesion progression in the brain was 5.7-7 weeks. CONCLUSION: Pembrolizumab is effective in brain metastases from NSCLC and melanoma, showing response (CR + PR) in 43% and progression (PD) in 32% of metastases. With the median time to CNS progression of 5.7-7 weeks, careful radiographic monitoring is essential to guide timely local treatment decisions.

Adverse Drug Reactions and Prescription Patterns of Antiretroviral Drugs: A Longitudinal Observational Study From a Tertiary Care Hospital in Western India.

Background In 2018, the World Health Organisation (WHO) released interim guidelines, advising a change of regimens to dolutegravir-based first- and second-line antiretroviral therapy (ART), based on which, in 2021, the National Aids Control Organisation (NACO) updated its guidelines to include the tenofovir + lamivudine + dolutegravir (TLD) regimen as a first line of therapy for all people living with HIV (PLHIV) and second- and third-line regimens to dolutegravir-based regimens. Considering this change of regimen, the adverse drug reaction (ADR) profiling and longitudinal prescription pattern of antiretroviral and concomitant medications in adult patients at the ART centre of a tertiary care hospital were assessed in this study. Methods Ninety-seven PLHIV out of all the patients who attended the ART centre from September 2021 to July 2022 were enrolled and followed up for six months. The ADRs that occurred during this period were collected along with details of prescription patterns and analyzed by descriptive statistics. Causality assessment for ADR was done using the World Health Organisation-Uppsala Monitoring Centre (WHO-UMC) scale. Results Seventy-eight percent (n=76 out of 97) of patients experienced at least one ADR, and 128 ADRs were seen in 97 patients. The most common ADRs were increased alkaline phosphatase (39.0%, n=128), dyslipidaemia (12.5%, n=128), and nephrotoxicity (10.1%, n=128). The drug most suspected of causing ADRs was dolutegravir (27.5%, n=342). The most common therapeutic regimen was TLD (71.2%, n=97). The most prescribed drug was lamivudine (30.6%, n=1183). The most prescribed concomitant medication was cotrimoxazole (15%, n=312). Conclusions Dolutegravir-based regimens have been implemented for PLHIV in a phased-out manner from previous non-dolutegravir-based ART regimens, which is in line with the recent NACO guidelines. However, it has also led to an increase in dolutegravir-associated ADRs like increased alkaline phosphatase, dyslipidaemia, and nephrotoxicity. Continuous monitoring of prescriptions and ADRs can add to our knowledge regarding their use and ADRs.

Aluminium, Nitrogen-Dual-Doped Reduced Graphene Oxide Co-Existing with Cobalt-Encapsulated Graphitic Carbon Nanotube as an Activity Modulated Electrocatalyst for Oxygen Electrocatalyst for Oxygen Electrochemistry Applications.

There is a rising need to create high-performing, affordable electrocatalysts in the new field of oxygen electrochemistry. Here, a cost-effective, activity-modulated electrocatalyst with the capacity to trigger both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) in an alkaline environment is presented. The catalyst (Al, Co/N-rGCNT) is made up of aluminium, nitrogen-dual-doped reduced graphene oxide sheets co-existing with cobalt-encapsulated carbon nanotube units. Based on X-ray Absorption Spectroscopy (XAS) studies, it is established that the superior reaction kinetics in Al, Co/N-rGCNT over their bulk counterparts can be attributed to their electronic regulation. The Al, Co/N-rGCNT performs as a versatile bifunctional electrocatalyst for zinc-air battery (ZAB), delivering an open circuit potential ≈1.35 V and peak power density of 106.3 mW cm-2, which are comparable to the system based on Pt/C. The Al, Co/N-rGCNT-based system showed a specific capacity of 737 mAh gZn -1 compared to 696 mAh gZn -1 delivered by the system based on Pt/C. The DFT calculations indicate that the adsorption of Co in the presence of Al doping in NGr improves the electronic properties favoring ORR. Thus, the Al, Co/N-rGCNT-based rechargeable ZAB (RZAB) emerges as a highly viable and affordable option for the development of RZAB for practical applications.

Single-atom alloys of Cu(211) with earth-abundant metals for enhanced activity towards CO2 dissociation.

CO2, a byproduct from various industrial reactions, must not be released into the atmosphere and should be managed through capture, conversion, and utilization. The first step in converting CO2 into valuable products is to break the C-O bond. This work focuses on designing Single Atom Catalysts (SACs) by doping Cu(211) surface with 13 different s, p, and d block elements with an aim to minimize the activation barrier for C-O bond cleavage. Our work demonstrates that SACs of Mg/Al/Pt@Cu(211) favor CO2 chemisorption compared to Cu(211) where CO2 physisorbs. The barrier for CO2 dissociation is lowest for Mg@Cu(211) and it increases in the order Mg@Cu(211) < Al@Cu(211) < Pt@Cu(211) < Zn@Cu(211) < Ga@Cu(211) < Cu@Cu(211) < Pd@Cu(211). These findings suggest that doping Cu(211) with earth-abundant metal like Mg can potentially be a viable catalyst for CO2 conversion, providing a promising solution to reduce carbon footprint and mitigate climate change.

Longitudinal trajectories of depressive symptoms among alcohol consuming men with HIV in India.

BACKGROUND: Depression and alcohol use are common among people living with HIV (PLWH) and associated with adverse outcomes. However, there is a paucity of studies exploring trajectories of depressive symptom presence over time among alcohol consuming men PLWH. METHODS: Men PLWH were repeatedly assessed for depressive symptoms from baseline through 27 months using the 10-item Center for Epidemiologic Studies-Depression scale. Group-based trajectory modeling was used to identify trajectories of depressive symptoms over time among control (n = 188) and intervention participants (n = 564). Multinomial logistic regression was used to explore the relationship between trajectory subgroups and baseline independent variables. RESULTS: Among intervention participants, the three subgroups were characterized as 'low' (85.8 % of the participants), 'fluctuating' (8.7 %), and 'persistently increasing' symptoms (5.5 %). Similarly, three trajectory subgroups among control participants were labeled as: "low" (54.4 %); "fluctuating" (33.5 %) and "persistently increasing'" (12.1 %). Among intervention participants, longer duration since HIV diagnosis (aOR: 1.05, 95 % CI: 1.01-1.12) and HIV-related stigma (aOR: 1.09, 95 % CI: 1.02-1.18) were associated with persistently increasing depressive symptoms trajectory. Further, alcohol drinking problems (aOR: 1.10, 95 % CI: 1.04-1.17) was associated with fluctuating depressive symptoms trajectory. Among control participants, only lower overall self-rated health status was associated with persistently increasing depressive symptoms trajectory (aOR: 0.96, 95 % CI: 0.93-0.99). LIMITATIONS: Selection bias; Information bias; Lack of causal interference; Generalizability. CONCLUSION: Identifying subgroups of men PLWH with different depressive symptoms trajectories may inform effective and tailored intervention approaches to address mental health treatment and prevention among alcohol consuming men PLWH in India and elsewhere.

Role of CD4 count estimation in the era of HIV-1 viral load among PLHIV.

BACKGROUND: ART has improved the life expectancy of people living with HIV (PLHIV) by suppressing the virus and increasing CD4 count. Some PLHIV shows immune-virological discordant responses i.e. suppressed viral load to the undetectable level but still with immunological failure or good immunological response with virological failure. Immuno-virological response plays a key role to address treatment outcome, regimen change and management for people living with HIV. It is reported that PLHIV with discordant responses were found to be at an increased risk to develop AIDS and non-AIDS events related death. AIMS & OBJECTIVE: To determine immuno-virological discordance amongst PLHIV on ART and its effect on mortality. MATERIAL & METHOD: After getting institutional Ethics committee approval, total 1921 patients were included in the study who were on ART for at least 6 month or more and have at least two CD4 count tests results and were tested from July 2019 to June 2020. Retrospective analysis was done. RESULTS: Total 1921 patients were included in study of which 1383 (72%) showed immuno-virological concordance & 538 (28%) showed immuno-virological discordance. Overall mortality rate among PLHIV was 3.6%. Mortality rate in immuno-virological concordant group was 2.8%. Of immuno-virological discordant population, 505 (26.3%) were virological only responders (VO) with 5.35% mortality rate & 33 (1.7%) were immunological only responders (IO) with 9.09% mortality rate. High number of immunological discordant patients in the present study warrants the further evaluation of these patients with change in appropriate treatment strategy to decrease the mortality among this group. CONCLUSION: This study emphasizes the role of immunological monitoring as well as virological monitoring to improve the life expectancy of PLHIV.

Keras/TensorFlow in Drug Design for Immunity Disorders.

Homeostasis of the host immune system is regulated by white blood cells with a variety of cell surface receptors for cytokines. Chemotactic cytokines (chemokines) activate their receptors to evoke the chemotaxis of immune cells in homeostatic migrations or inflammatory conditions towards inflamed tissue or pathogens. Dysregulation of the immune system leading to disorders such as allergies, autoimmune diseases, or cancer requires efficient, fast-acting drugs to minimize the long-term effects of chronic inflammation. Here, we performed structure-based virtual screening (SBVS) assisted by the Keras/TensorFlow neural network (NN) to find novel compound scaffolds acting on three chemokine receptors: CCR2, CCR3, and one CXC receptor, CXCR3. Keras/TensorFlow NN was used here not as a typically used binary classifier but as an efficient multi-class classifier that can discard not only inactive compounds but also low- or medium-activity compounds. Several compounds proposed by SBVS and NN were tested in 100 ns all-atom molecular dynamics simulations to confirm their binding affinity. To improve the basic binding affinity of the compounds, new chemical modifications were proposed. The modified compounds were compared with known antagonists of these three chemokine receptors. Known CXCR3 compounds were among the top predicted compounds; thus, the benefits of using Keras/TensorFlow in drug discovery have been shown in addition to structure-based approaches. Furthermore, we showed that Keras/TensorFlow NN can accurately predict the receptor subtype selectivity of compounds, for which SBVS often fails. We cross-tested chemokine receptor datasets retrieved from ChEMBL and curated datasets for cannabinoid receptors. The NN model trained on the cannabinoid receptor datasets retrieved from ChEMBL was the most accurate in the receptor subtype selectivity prediction. Among NN models trained on the chemokine receptor datasets, the CXCR3 model showed the highest accuracy in differentiating the receptor subtype for a given compound dataset.

Role of PET/CT in Oropharyngeal Cancers.

Oropharyngeal squamous cell carcinoma (OPSCC) comprises cancers of the tonsils, tongue base, soft palate, and uvula. The staging of oropharyngeal cancers varies depending upon the presence or absence of human papillomavirus (HPV)-directed pathogenesis. The incidence of HPV-associated oropharyngeal cancer (HPV + OPSCC) is expected to continue to rise over the coming decades. PET/CT is a useful modality for the diagnosis, staging, and follow up of patients with oropharyngeal cancers undergoing treatment and surveillance.

Alcohol Use, HIV Stigma and Quality of Life Among Alcohol Consuming Men Living with HIV in India: A Mediation Analysis.

This study examined the hypothesis that HIV-related stigma mediates the effect of alcohol use on health-related quality of life (HRQoL) among alcohol consuming Indian men living with HIV (PLWH). The study used baseline data from a randomized controlled clinical trial entitled 'Alcohol and ART adherence: Assessment, Intervention, and Modeling in India. Participants completed surveys assessing demographic characteristics, alcohol use, HIV-related stigma, HRQoL. Mediation analysis was conducted to establish the mediation effect of HIV-related stigma on the relationship between alcohol use and HRQoL. The final mediation model showed that the effect of alcohol use on HRQoL were partially mediated by overall HIV-related stigma. Specially, 27.1% of the effects of alcohol use on HRQoL was mediated through overall HIV stigma. In the HIV stigma subdomain analyses, negative self-image mediated 14% and concerns with public attitudes (anticipated stigma) mediated 17.3% of the effect of alcohol use on HRQoL respectively. The findings suggest that efforts to reduce the negative impact of alcohol use on HRQoL and improve HRQoL among PLWH should include interventions addressing both alcohol use and specific forms of HIV-related stigma.

RESUMEN: Este estudio examinó la hipótesis de que el estigma relacionado con el VIH mediaría el efecto del consumo de alcohol en la calidad de vida relacionada con la salud entre hombres indios que consumen alcohol y viven con VIH. El estudio utilizó datos de línea base de un ensayo clínico aleatorizado controlado titulado "Consumo de alcohol y adherencia al TAR: evaluación, intervención y modelización en India". Los participantes completaron encuestas que evaluaron características demográficas, consumo de alcohol, estigma relacionado con el VIH y calidad de vida relacionada con la salud (CVRS). Se realizó un análisis de mediación para establecer el efecto de la mediación del estigma relacionado con el VIH en la relación entre el consumo de alcohol y la CVRS. El modelo final de mediación mostró que el efecto del consumo de alcohol en la CVRS fue parcialmente mediado por el estigma general relacionado con el VIH. Específicamente, el 27,1% de los efectos del consumo de alcohol en la CVRS se medió a través del estigma general relacionado con el VIH. En los análisis de subdominios del estigma del VIH, la imagen negativa de sí mismo medió el 14% y las preocupaciones sobre las actitudes públicas (estigma anticipado) mediaron el 17,3% del efecto del consumo de alcohol en la CVRS, respectivamente. Los resultados sugieren que los esfuerzos para reducir el impacto negativo del consumo de alcohol en la CVRS y mejorar la CVRS entre las personas que viven con VIH deberían incluir intervenciones que aborden tanto el consumo de alcohol como formas específicas de estigma relacionado con el VIH.

The Mediating Effect of Changes in Depression Symptoms on the Relationship between Health-Related Quality of Life and Alcohol Consumption: Findings from a Longitudinal Study among Men Living with HIV in India.

Heavy alcohol use is negatively affecting antiretroviral therapy adherence, mental health and health-related quality of life among people living with HIV (PLWH). This paper aims to test the mediation model examining whether changes in depression symptoms mediate in the relationship between health-related quality of life and alcohol use among male PLWH who consume alcohol in India. The study is guided by the stress-coping model, which posits that individuals facing stress may turn to maladaptive coping mechanisms such as alcohol use to alleviate their distress, which includes depression and a low health-related quality of life due to various physical, psychological, and social factors associated with the HIV infection. This study used the data from a randomized controlled clinical trial entitled 'Alcohol and ART adherence: Assessment, Intervention, and Modeling in India'. Participants completed surveys assessing demographic characteristics, health-related quality of life, depressive symptoms, and alcohol use. Multiple simple mediation models were investigated to examine whether changes in depression symptoms mediated the association between the changes in health-related quality of life and alcohol use after a 9-month follow-up. A total of 940 male PLWH were recruited and interviewed, with 564 participants in the intervention group and 376 participants in the control group. After a 9-month intervention, the mediation results showed that, among intervention participants, a decrease in depressiove symptoms mediated the relationship between improved health-related quality of life and lower alcohol use. However, among control participants, changes in depressive symptoms did not mediate the relationship between changes in health-related quality of life and alcohol use. The study findings have practical and theoretical implications. From a practical perspective, the results suggest that interventions aimed at simultaneously improving HRQoL and depressive symptoms among male PLWH with alcohol use may help reduce alcohol consumption. Therefore, interventions that address depressive symptoms in addition to improving HRQoL may have an even greater impact on reducing alcohol use among this population. Theoretically, the study supports the use of the stress-coping theory in understanding the association between HRQoL, mental health, and alcohol use among male PLWH, contributing to existing literature on a gap in our understanding of the interactions among these factors among PLWH.

Photoinduced CO2 and N2 reductions on plasmonically enabled gallium oxide.

Ag-containing ZnO/ ß-Ga2O3 semiconductor, which exhibit reduced bandgap, increased light absorption, and hydrophilicity, have been found to be useful for photocatalytic CO2 reduction and N2 fixation by water. The charge-separation is facilitated by the new interfaces and inherent vacancies. The Ag@GaZn demonstrated the highest photocurrent response, about 20- and 2.27-folds that of the Ga and GaZn samples, respectively. CO, CH4, and H2 formed as products for photo-reduction of CO2. Ag@GaZn catalyst exhibited the highest AQY of 0.121 % at 400 nm (31.2 W/m2). Also, Ag@GaZn generated 740 µmolg-1 of NH4+ ions, which was about 18-folds higher than Ga sample. In situ DRIFTS for isotopic-labelled 13CO2 and 15N2 reaffirmed the photo-activity of as-synthesized catalysts. Density functional theory provided insight into the relative affinity of different planes of heterostructures towards H2O, CO2 and N2 molecules. The structure-photoactivity rationale behind the intriguing Ag@GaZn sample offers a fundamental insight into the role of plasmonic Ag and design principle of heterostructure with improved photoactivity and stability.

Anterior Cruciate Ligament Tear Detection Based on Deep Convolutional Neural Network.

Anterior cruciate ligament (ACL) tear is very common in football players, volleyball players, sprinters, runners, etc. It occurs frequently due to extra stretching and sudden movement and causes extreme pain to the patient. Various computer vision-based techniques have been employed for ACL tear detection, but the performance of most of these systems is challenging because of the complex structure of knee ligaments. This paper presents a three-layered compact parallel deep convolutional neural network (CPDCNN) to enhance the feature distinctiveness of the knee MRI images for anterior cruciate ligament (ACL) tear detection in knee MRI images. The performance of the proposed approach is evaluated for the MRNet knee images dataset using accuracy, recall, precision, and the F1 score. The proposed CPDCNN offers an overall accuracy of 96.60%, a recall rate of 0.9668, a precision of 0.9654, and an F1 score of 0.9582, which shows superiority over the existing state-of-the-art methods for knee tear detection.

Logistic regression-based parametric analysis of HIV-associated dementia using a screening tool in a tertiary care hospital in Mumbai.

Context: The AIDS dementia complex is one of the most common and clinically important complications of HIV infection. Subclinical dementia not presenting with features of frank disease may be missed. The use of screening tools provides a good alternative to a psychiatrist's diagnosis in resource-limited settings like the site of this study. Aims: The study aimed to analyze various parameters such as age, gender, duration of the disease, duration since treatment, clinical staging, CD4 count, mode of transmission, and comorbidities like tuberculosis with the prevalence of AIDS dementia complex in the participants. Settings and Design: A cross-sectional study involving 180 participants was conducted over a duration of 18 months. Materials and Methods: The assessment of dementia was done using the International HIV Dementia Scale. Statistical Analysis Used: Backward binomial logistics regression. Results: Both duration of treatment and duration since diagnosis of HIV were found to be significantly associated with the presence of AIDS dementia. Patients having stage 4 disease and CD4 counts <200 were likelier to have dementia as compared to other participants. People with an unknown mode of transmission had higher odds of having AIDS dementia than persons having a mode of transmission as via blood/blood products/invasive procedures/mother-to-child transmission/IV drug abuse. Binomial logistic regression revealed mode of transmission or rather its awareness to be the strongest contributor. Conclusions: These findings highlight the need for early screening and diagnosis of HIV-associated dementia in patients living with HIV and that of early assessment and initiation of treatment.

Predicting the Redox Potentials of Phenazine Derivatives Using DFT-Assisted Machine Learning.

This study investigates four machine-learning (ML) models to predict the redox potentials of phenazine derivatives in dimethoxyethane using density functional theory (DFT). A small data set of 151 phenazine derivatives having only one type of functional group per molecule (20 unique groups) was used for the training. Prediction accuracy was improved by a combined strategy of feature selection and hyperparameter optimization, using the external validation set. Models were evaluated on the external test set containing new functional groups and diverse molecular structures. High prediction accuracies of R 2 > 0.74 were obtained on the external test set. Despite being trained on the molecules with a single type of functional group, models were able to predict the redox potentials of derivatives containing multiple and different types of functional groups with good accuracies (R 2 > 0.7). This type of performance for predicting redox potential from such a small and simple data set of phenazine derivatives has never been reported before. Redox flow batteries (RFBs) are emerging as promising candidates for energy storage systems. However, new green and efficient materials are required for their widespread usage. We believe that the hybrid DFT-ML approach demonstrated in this report would help in accelerating the virtual screening of phenazine derivatives, thus saving computational and experimental costs. Using this approach, we have identified promising phenazine derivatives for green energy storage systems such as RFBs.

Plant growth promoting characteristics of halophilic and halotolerant bacteria isolated from coastal regions of Saurashtra Gujarat.

Halophiles are a class of microorganisms that thrive in environments with very high salt concentrations. The coastal regions of Saurashtra Gujarat host a diverse group of microorganisms including halophilic and halotolerant bacteria that may have plant growth promoting characteristics. Microorganisms with plant growth promoting characteristics are of immense importance in the field of agriculture and the present study was conducted to investigate the characteristics of halophilic and halotolerant bacteria isolated from agricultural soils of coastal regions of Junagadh and Porbandar districts of Saurashtra, Gujarat. A total of 15 isolated strains showed indole acetic acid production, solubilization of phosphate and potash, and nitrogen fixing capacity ranging from 18.77-33.48 µg ml-1, 50.10-106.10%, 180.42-239.92% and 0.170-0.480 g kg-1 of Jensen's agar medium, respectively, while two isolates were also found positive for siderophore production. Besides, nine out of fifteen isolates also showed positive ACC deaminase activity ranging from 0.92-5.78 µM α-ketobutyrate mg-1 h-1. The isolates were further characterized by physiological, microscopic, and biochemical tests. The halophilic and halotolerant bacterial isolates were identified by 16S rRNA gene sequencing as belonging to Halomonas pacifica, H. stenophila, and Bacillus haynesii, B. licheniformis and Oceanobacillus aidingensis respectively. The 16S rRNA partial gene sequence of two isolates belonging to H. pacifica and H. stenophila were submitted to NCBI with accession number MK955347 and MK961217 respectively. The findings of the present investigation showed that isolated bacterial halophiles possess promising plant growth promoting characteristics. Their potential as bioinoculants to alleviate salinity stress in crops and for bioremediation deserves further investigation.

Achieving UNAIDS Viral Suppression Goal: Experience from a Tertiary Care Public Hospital, Western India.

INTRODUCTION: Targeted HIV 1 viral load testing has been recommended in 2010 only for suspected cases of antiretroviral therapy failure. India is committed to achieve UNAIDS '90-90-90' target by 2020. The third 90 target was to ensure all people receiving antiretroviral therapy (ART) are virologically suppressed. Implementation of routine viral load testing in national programme helps us in assessing early treatment failure and the need to switch to second line therapy; thus eventually reducing drug resistance and improving patient outcomes. AIMS: Study was aimed to determine the proportion of patients responding to antiretroviral therapy, correlates of viral suppression & the discordance between virological and immunological failure. DESIGN: Retrospective analysis. MATERIAL & METHODS: As per the NACO policy, all patients diagnosed as HIV positive are started on antiretroviral therapy and are monitored regularly. The patient's adherence details are noted down during regular follow up visit and patient is referred for routine HIV 1 VL and/or CD4 testing as per National guidelines. Analysis of data was carried out retrospectively for all patients referred for HIV 1 viral load and/or CD4 testing during the study period from July 2019 to June 2020. Confidentiality of the patient was maintained at all times as per routine protocol. RESULTS: A total of 7601 PLHIV on antiretroviral therapy, 3813 samples were tested for both HIV 1 VL and CD4 counts and these results were further analyzed. 3616 (94.8%) showed virological suppression and 197(5.2%) showed virological failure. Among virologically failed group, 46.2% (91/197) underwent retesting after adherence counseling and among these 48.4%(44/91) showed viral suppression. Virological failure was significantly high in younger PLHIV receiving second or third line ART for less than 5 years duration who were non adherent. Immunological discordance was seen in 28.3 % of PLHIV. CONCLUSION: In the present study, 95.99% patients showed virological suppression indicating that the third "90"target is being exceeded.

Improving handover competency in preclinical medical and health professions students: establishing the reliability and construct validity of an assessment instrument.

BACKGROUND: As part of the worldwide call to enhance the safety of patient handovers of care, the Association of American Medical Colleges (AAMC) requires that all graduating students "give or receive a patient handover to transition care responsibly" as one of its Core Entrustable Professional Activities (EPAs) for Entering Residency. Students therefore require educational activities that build the necessary teamwork skills to perform structured handovers. To date, a reliable instrument designed to assess teamwork competencies, like structured communication, throughout their preclinical and clinical years does not exist. METHOD: Our team developed an assessment instrument that evaluates both the use of structured communication and two additional teamwork competencies necessary to perform safe patient handovers. This instrument was utilized to assess 192 handovers that were recorded from a sample of 229 preclinical medical students and 25 health professions students who participated in a virtual course on safe patient handovers. Five raters were trained on utilization of the assessment instrument, and consensus was established. Each handover was reviewed independently by two separate raters. RESULTS: The raters achieved 72.22 % agreement across items in the reviewed handovers. Krippendorff's alpha coefficient to assess inter-rater reliability was 0.6245, indicating substantial agreement among the raters. A confirmatory factor analysis (CFA) demonstrated the orthogonal characteristics of items in this instrument with rotated item loadings onto three distinct factors providing preliminary evidence of construct validity. CONCLUSIONS: We present an assessment instrument with substantial reliability and preliminary evidence of construct validity designed to evaluate both use of structured handover format as well as two team competencies necessary for safe patient handovers. Our assessment instrument can be used by educators to evaluate learners' handoff performance as early as their preclinical years and is broadly applicable in the clinical context in which it is utilized. In the journey to optimize safe patient care through improved teamwork during handovers, our instrument achieves a critical step in the process of developing a validated assessment instrument to evaluate learners as they seek to accomplish this goal.

DART: deep learning enabled topological interaction model for energy prediction of metal clusters and its application in identifying unique low energy isomers.

Recently, machine learning (ML) has proven to yield fast and accurate predictions of chemical properties to accelerate the discovery of novel molecules and materials. The majority of the work is on organic molecules, and much more work needs to be done for inorganic molecules, especially clusters. In the present work, we introduce a simple topological atomic descriptor called TAD, which encodes chemical environment information of each atom in the cluster. TAD is a simple and interpretable descriptor where each value represents the atom count in three shells. We also introduce the DART deep learning enabled topological interaction model, which uses TAD as a feature vector to predict energies of metal clusters, in our case gallium clusters with sizes ranging from 31 to 70 atoms. The DART model is designed based on the principle that the energy is a function of atomic interactions and allows us to model these complex atomic interactions to predict the energy. We further introduce a new dataset called GNC_31-70, which comprises structures and DFT optimized energies of gallium clusters with sizes ranging from 31 to 70 atoms. We show how DART can be used to accelerate the process of identification of low energy structures without geometry optimization. Albeit using a topological descriptor, DART achieves a mean absolute error (MAE) of 3.59 kcal mol-1 (0.15 eV) on the test set. We also show that our model can distinguish core and surface atoms in the Ga-70 cluster, which the model has never encountered earlier. Finally, we demonstrate the transferability of the DART model by predicting energies for about 6k unseen configurations picked up from molecular dynamics (MD) data for three cluster sizes (46, 57, and 60) within seconds. The DART model was able to reduce the load on DFT optimizations while identifying unique low energy structures from MD data.