Estimation of rice yield using multivariate analysis techniques based on meteorological parameters.

This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980-81 to 2020-21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices.

Attitudes to long-term care in India: A secondary, mixed methods analysis.

OBJECTIVES: In India, globalisation is purported to have contributed to shifting family structures and changing attitudes to long-term care (LTC) facility use. We investigated the attitudes to and usage frequency of LTC in India. METHODS: We conducted secondary analyses of: (a) The Moving Pictures India Project qualitative interviews with 19 carers for people with dementia and 25 professionals, collected in 2022, exploring attitudes to LTC; and (b) The Longitudinal Ageing Study in India (LASI) 2017-2018, cross-sectional survey of a randomised probability sample of Indian adults aged 45+ living in private households. RESULTS: We identified three themes from qualitative data: (1) LTC as a last resort, describes how LTC could be acceptable if care at home was "impossible" due to the person's medical condition or unavailability of the family carer, for example, if family members lived overseas or interstate. (2) Social expectations of care at home from family members and paid carers and; (3) Limited availability of LTC facilities in India, especially in rural localities, and the financial barriers to their use. Of 73,396 LASI participants, 40 were considering moving to LTC; 18,281 had a parent alive, of whom 9 reported that their father, and 16 that their mother, lived in LTC. LTC use was rare. While a third of participants with a living parent lived in urban areas, 14/24 of those with a parent in LTC lived in an urban area, supporting our qualitative findings that LTC is mainly accessed in urban areas. CONCLUSIONS: Preference for intergenerational community care combined with limited availability and societal stigma contribute to low rates of LTC use among Indian families. Future social policies should consider how to plan for greater equity in strengthening care at home and in the community, and bolstering respite and LTC services as a last resort.

Hydraulic modeling of the Periyar River using HEC-RAS: unraveling flow dynamics.

The Periyar River, a vital component of Kerala's ecosystem in India, serves as a lifeline supporting agriculture, hydropower generation, and ecological equilibrium. This study adopts a multifaceted approach to address critical challenges in the Periyar basin, with a primary focus on flood mitigation due to the region's susceptibility to devastating floods. Covering a length of 67.85 km, the study intricately segments the Periyar River into distinct reaches for a comprehensive steady flow analysis, considering factors such as seasonal monsoon fluctuations, diverse catchment topography, and human-induced alterations. Utilizing advanced modeling techniques, particularly HEC-RAS software, the study effectively predicts and simulates shifts in hydraulic behavior. The results, including velocity plots and cross-sectional maps, offer accurate insights into critical parameters, enabling the identification of areas with high velocity occurrence. This information proves instrumental in making informed decisions for the construction of river restoration structures, crucial for mitigating the impact of floods. The study's findings contribute valuable tools for future forecasting and sustainable management of the Periyar River, addressing the complex interplay of natural and anthropogenic factors.

Interplay of natural and anthropogenic inputs on the groundwater contamination of Beenaganj-Chachura block.

The present research work investigates the impact of natural and anthropogenic inputs on the chemistry and quality of the groundwater in the Beenaganj-Chachura block of Madhya Pradesh, India. A total of 50 groundwater samples were examined for nitrates, fluoride, chlorides, total dissolved solids, calcium, magnesium, pH, total hardness, and conductivity, and their impact on entropy-weighted water quality index and pollution index of groundwater (PIG) was investigated via the response surface methodology (RSM) using the central composite design. According to analytical findings, Ca, Mg, Cl-, SO42-, and NO3- exceed the desired limit and permitted limit set by the Bureau of Indian Standards (BIS) and the World Health Organization (WHO). According to PIG findings, 76, 16, and 8% of groundwater samples, respectively, fell into the insignificant, low, and moderate pollution categories. The regression coefficients of the quadratic RSM models for the experimental data provided excellent results. Thus, RSM provides an excellent means to obtain the optimized values of input parameters to minimize the PIG values.

Knowledge, Attitude, and Practice of Physiotherapists about Cardiac Rehabilitation Program Adherence among Patients Discharged from the Hospital after Cardiac Surgery in India.

Background: In most settings, patients receive phase 1 cardiac rehabilitation in CTVS ICU at the hospital, but there are several barriers to follow-up after patients are discharged from the hospital. Physiotherapists play an important role in the enrolment and continuation of cardiac rehabilitation. Thus, we aim to study the knowledge, attitude, and practice of physiotherapists about CR program adherence among patients discharged from the hospital after cardiac surgery. Objectives: (i) To study the knowledge of physiotherapists about the importance of cardiac rehabilitation after discharge; (ii) to know the attitude of physiotherapists towards cardiac surgery patients after discharge; and (iii) to know what approach various centres are applying for patients after discharge to ensure adherence to cardiac rehabilitation. Methods: A questionnaire was developed with reference to the objectives of the study, which was answered by a total of 127 physiotherapists. Results: The overall response rate was 42.3%; nearly 35.4% of the participants indicated that they knew a lot about CR, while 5.5% said they knew very little. Regarding the program's content, 36.2% of participants reported having a medium degree of awareness of the diverse CR components, while 8.6% reported having very little knowledge of them. Only about one-third, 35.7% stated that CR in India is effective and 95% believed that CR will have an added value for the country. Approximately 80% of respondents thought that it would be challenging for a physiotherapist to recommend patients to a CR in the nation. Nearly 35% of respondents believed that they, "themselves as physios," needed to commence CR, and slightly less than 70% thought that doctors were required to choose and refer the patients when asked who should take the initiative to start this kind of programme in the country. A little over 40% of respondents said that insurance firms are also involved in starting a CR programme. Conclusion: Physiotherapists have good knowledge of cardiac rehabilitation. However, their attitude and practice towards adherence to exercise protocols are confounded by various clinician- and patient-level factors.

Optimization of QuEChERS method for determination of pesticide residues in vegetables and health risk assessment.

The present study focused on the optimization of the QuEChERS extraction method for the determination of 61 pesticide residues and associated health risk assessment in 144 samples of commonly consumed vegetables, viz., eggplant, cabbage, green chilli, okra, and tomato. The samples were collected between January and April 2022 from three different districts within Gujarat, India. The QuEChERS method was optimized and utilized for the extraction of samples. The samples were analyzed by UHPLC-q-TOF/MS and GC-MS/MS. The modified QuEChERS method was successfully validated, and the obtained results were satisfactory as per the 2021 SANTE guidelines. The residue analysis of the vegetable samples showed that about 4% of total samples contained single pesticide residues. Pesticide residues below the quantitation limit (BQL) were observed in eggplant, cabbage, and okra samples. In total, 15.62% (n = 5) samples of green chilli showed the presence of pesticides such as azoxystrobin, bifenthrin, cypermethrin, fenpropathrin, and propargite whereas 3% (n = 1) tomato samples contained cyfluthrin. In total, 97.22% of the samples had residues that were below the European Union Maximum Residue Limit (EU MRL). Two samples of green chilli had pesticide residues above EU MRL. The Hazard Index (HI) and Hazard Quotient (HQ) were used to assess the health risks associated with green chilli and tomato consumption. The HI and HQ values for adolescents and adults were found to be less than 1. The modified QuEChERS method was found to be easy and effective and can be implemented for routine sample analysis. The study revealed the presence of pesticide residues in tomato and green chilli samples. Further, the outcome provided information pertaining to current pesticide status, concluding that consumption of these commodities is unlikely to pose any health risk, though long-term monitoring studies focusing on dietary health risk assessment must be initiated.

Investigating Indian oil sardine aggregation events in coastal waters of the southeastern Arabian sea.

The southwest coast of India experiences frequent Indian oil sardine (IOS) nearshore aggregation events, especially in the coastal waters off Kerala. These ephemeral dense IOS aggregation events are known as "Sardine Run". To investigate the reason and provide a scientific basis for these sporadic events, satellite/model-derived physical, meteorological, and biological parameters were analysed. Sea Surface Temperature during a majority of events was in the range of 26-29 °C, agreeing with the reported temperature conditions for IOS in the Arabian Sea. Additionally, a marginal lowering of SST as an effect of precipitation before most of the events might have attracted IOS towards the near-coastal waters in addition to the phytoplankton diet availability, resulting in the aggregation event. However, different scenarios also depicted coastal warming and probable hypoxic conditions in degrading IOS habitat and resulting in beach aggregation events. During most of the IOS aggregation events, the wind and surface current direction was alongshore/coastward, which complemented the propagation of live IOS shoals towards the beach.

Influence of building orientation and thermal mass configuration on the prediction of Natural Ventilation Potential (NVP) of various climates of India.

Natural ventilation potential (NVP) of a climate is a theoretical basis, and it gains importance due to the promising need for building energy conservation while conceding required thermal comfort conditions. A modified NVP analytical model is proposed by considering parameters involved in the earlier models (Yang et al., Build Environ 40:738-746, 2005; Luo et al., Build Environ 42:2289-2298, 2007). The effect of the dynamic thermal behavior of the wall/roof and building orientation on the indoor air temperature has been evaluated. The analytical model is applied to 11 major cities of India that belong to composite, hot-dry, temperate, and warm-humid climates. Five different envelope configurations are analyzed to envisage the NVP of concern climate (ED-I to ED-V). The results show that the effect of dynamic thermal response factors on the NVP is significant, and optimization of thermal response factors in addition to the U-value is mandatory. The impact of wind frequency on the selection of building orientation is substantial since it influences the total heat gained by the building envelope. Moreover, it is perceived that the optimum building orientation is independent of the climate and weather conditions. ED-II and ED-III are energy-efficient envelopes for composite, temperate, warm-humid, and hot-dry climates. The results revealed that the Mumbai climate has the highest NVP of 66% while the building is oriented in an E-W direction, and the lowest is observed for Jodhpur, i.e., 44% of the year when the building is in the NE-SW direction. The model helps the building architectural designers envisage the true NVP and assess the suitability of the building for natural ventilation.

Molecular characterization and phylogenetic analysis of babA gene of Helicobacter pylori isolated from Indian patients with gastrointestinal diseases.

INTRODUCTION: Outer membrane protein (OMP) of Helicobacter pylori (H. pylori) i.e., blood group antigen binding adhesin (babA) is responsible for the attachment of H. pylori in the gastric epithelium. Its adherence is causative for gastric pathology such as gastritis, peptic ulcer disease (PUD), or digestive tract disorders like erosive reflux disease (ERD) and (NERD) non-erosive reflux disease and together called Gastroesophageal reflux disease (GERD). BabA manifests rapid and varied selection via substitution of amino acid in its Leb-carbohydrate binding domain (CBD) which enables better binding preferences for distinct human populations and ABO blood group phenotypes. The positive evolutionary selection of the pathogenic factor of this genetically diverse bacterium has enabled it to adapt to the host gastric environment. Analyzing the association of virulent genes (cagA, vacA) and babA will help us better understand bacteria's pathogenicity. METHOD: 109 H. pylori strains from patients with distinct gastrointestinal diseases were genotyped using Polymerase Chain Reaction(PCR) for cagA, vacA, and babA followed by Sanger sequencing and phylogenetic analysis. RESULT: In the babA + ve genotype, a statistically significant association with p = 0.04 and < 0.0001 is seen in gastritis and ERD respectively. A significant association of genotype vacAs1m2 (p = 0.0002) was seen in gastritis, vacAs1m1 (p = 0.02) in NERD, vacAs1m1 (p < 0.0001) and vacAs1m2 (p = 0.002) in ERD. This relationship helps to detect gastritis or ERD where BabA gene can be used as an independent marker for detecting their presence. CONCLUSION: The appearance of variants within distinct disease categories is due to local genetic variation.

Human Passage of Schistosoma incognitum, Tamil Nadu, India, and Review of Autochthonous Schistosomiasis, South Asia.

A fecal survey in Tamil Nadu, India, revealed 2 persons passed schistosome eggs, later identified as Schistosoma incognitum, a parasite of pigs, dogs, and rats. We investigated those cases and reviewed autochthonous schistosomiasis cases from India and Nepal. Whether the 2 new cases represent true infection or spurious passage is undetermined.

Risk Factors for Stroke in Children with Tuberculous Meningitis: A Prospective Observational Study.

OBJECTIVE: The purpose of the study is to establish the prevalence of stroke as well as the clinical and radiological correlates of stroke in children with tuberculous meningitis (TBM). METHODS AND MATERIALS: A prospective observational study was conducted at the Pediatric Department, King George's Medical University (KGMU), Lucknow, Uttar Pradesh, India. Using a computed tomography (CT) scan/brain magnetic resonance imaging (MRI), patients were divided into stroke and non-stroke groups. Demographic characteristics, clinical presentations, cerebrospinal fluid examination, basal meningeal enhancement, hydrocephalus, tuberculoma, and clinical outcome were compared between the two groups. RESULTS: Seventy-eight TBM patients, aged between 6 months and 14 years, were included. Out of 78 enrolled patients, 3 (3.8%) had definite TBM, 73 (91%) had probable TBM, and 4 (5.1%) had possible TBM (LCS). As per the Medical Research Council (MRC) staging, 13% had Stage 1 TBM, 26% had stage 2, and 61% had stage 3 TBM. Out of 78 patients with chest X-ray findings, 42 (53%) had findings suggestive of tuberculosis (TB), which included 33 (42%) with hilar lymphadenopathy and 9 (11%) with a miliary pattern. On neuroimaging, hydrocephalous was seen in 62.8% of cases, basal meningeal enhancement in 64.1%, tuberculoma in 6.4% of cases, and infarction in 53.8% of cases. There was no statistically significant association found between the staging of TBM and the presence of infarction as the majority of cases involved were in stage 3 of the disease (61.5%). TBM patients with stroke had poor clinical outcomes. CONCLUSION: Age, altered sensorium, focal neurological deficits, vomiting, and basal meningeal enhancement can predict the occurrence of stroke in young adults with TBM.

Psychosurgery in Indian Scenario: Time to Think with Phronesis.

With advances in technology, neurosurgical procedures are being examined for potential use in psychiatric conditions. However, the use of neurosurgical procedures in psychiatry carries the baggage of memories of psychosurgery. Different neurosurgical techniques carry their characteristic safety, efficacy, and complication profile. The introduction of deep brain stimulation has generated a new interest in surgical treatment with a distinct advantage over lesioning procedures used in the past. In such a scenario, it is essential that an informed discussion takes place regarding the use of these neurosurgical procedures in psychiatric disorders such that patient safety, informed consent, regulatory requirements, and research are taken care of.

Exploring the Big Data Paradox for various estimands using vaccination data from the global COVID-19 Trends and Impact Survey (CTIS).

Selection bias poses a substantial challenge to valid statistical inference in nonprobability samples. This study compared estimates of the first-dose COVID-19 vaccination rates among Indian adults in 2021 from a large nonprobability sample, the COVID-19 Trends and Impact Survey (CTIS), and a small probability survey, the Center for Voting Options and Trends in Election Research (CVoter), against national benchmark data from the COVID Vaccine Intelligence Network. Notably, CTIS exhibits a larger estimation error on average (0.37) compared to CVoter (0.14). Additionally, we explored the accuracy (regarding mean squared error) of CTIS in estimating successive differences (over time) and subgroup differences (for females versus males) in mean vaccine uptakes. Compared to the overall vaccination rates, targeting these alternative estimands comparing differences or relative differences in two means increased the effective sample size. These results suggest that the Big Data Paradox can manifest in countries beyond the United States and may not apply equally to every estimand of interest.

Pedestrian crash risk analysis using extreme value models: New insights and evidence.

Facilitating proactive pedestrian safety management, the application of extreme value theory (EVT) models has gained popularity due to its extrapolation capabilities of estimating crashes from their precursors (i.e., conflicts). However, past studies either applied EVT models for crash risk analysis of autonomous vehicle-pedestrian interactions or human-driven vehicle-pedestrian interactions at signalised intersections. However, our understanding of human-driven vehicle-pedestrian interactions remains elusive because of scant evidence of (i) EVT models' application for heterogeneous traffic conditions, (ii) appropriate set of determinants, (iii) which EVT approach to be used, and (iv) which conflict measure is appropriate. Addressing these issues, the objective of this study is to investigate pedestrian crash risk analysis in heterogeneous and disordered traffic conditions, where drivers do not follow lane disciplines. Eleven-hour video recording was collected from a busy pedestrian crossing at a midblock location in India and processed using artificial intelligence techniques. Vehicle-pedestrian interactions are characterised by two conflict measures (i.e., post encroachment time and gap time) and modelled using block maxima and peak over threshold approaches. To handle the non-stationarity of pedestrian conflict extremes, several explanatory variables are included in the models, which are estimated using the maximum likelihood estimation procedure. Modelling results indicate that the EVT models provide reasonable estimates of historical crash records at the study location. From the EVT models, a few key insights related to vehicle-pedestrian interactions are as follows. Firstly, a comparison of EVT models shows that the peak over threshold model outperforms the block maxima model. Secondly, post encroachment time conflict measure is found to be appropriate for modelling vehicle-pedestrian interactions compared to gap time. Thirdly, pedestrian crash risk significantly increases when they interact with two-wheelers in contrast with interactions involving buses where the crash risk decreases. Fourthly, pedestrian crash risk decreases when they cross in groups compared to crossing individually. Finally, pedestrian crash risk is positively related to average vehicle speed, pedestrian speed, and five-minute post encroachment time counts less than 1.5 s. Further, different block sizes are tested for the block maxima model, and the five-minute block size yields the most accurate and precise pedestrian crash estimates. These findings demonstrate the applicability of extreme value analysis for heterogeneous and disordered traffic conditions, thereby facilitating proactive safety management in disordered and undisciplined lane conditions.

Occupational health screening during Gurkha Central Selection: a retrospective cohort study.

OBJECTIVE: The selection process to the British Army's Brigade of Gurkhas is rigorous, demanding and competitive. The ethos of recruitment to the Gurkhas is grounded in an overarching tenant: that selection is free, fair and transparent. The aim of this study was to retrospectively review reasons for potential recruits (PRs) to be deemed medically unsuitable or deferred suitability on medical grounds for selection to the Brigade of Gurkhas. METHODS: A retrospective review was conducted by extracted data from published post-exercise reports for the past four years to ascertain numbers of PRs deemed medically fit, medically unsuitable or deferred suitability on medical grounds. The International Classification of Disease version 11 (ICD-11) codes were retrospectively assigned to code medical reasons for non-progression. Rates of medical non-progression were compared by year. RESULTS: A total of 3154 PRs were analysed between 2018 and 2021. There was no significant difference between PRs deemed medically fit and those deemed medically suitable or deferred on medical grounds over the study period (p=0.351). There was a significant difference in the ratio of PRs deferred on medical grounds and those deemed medically unsuitable over the study period (p<0.05). CONCLUSION: Selection to the Gurkhas is extremely competitive. These data demonstrate that, overall, reasons for medical deferral or unsuitability have remained constant despite the impact of a global pandemic. These data reinforce the central tenant of Gurkha selection; that it continues to be free, fair, and transparent.

Bioproduction of yeast single cell oil with acute oral toxicity study intended for edible oil application.

Human nutrition and health rely on edible oils. Global demand for edible oils is expanding, necessitating the discovery of new natural oil sources subjected to adequate quality and safety evaluation. However, in contrast to other agricultural products, India's edible oil supply is surprisingly dependent on imports. The microbial oil is generated by fermentation of oleaginous yeast Rhodotorula mucilaginosa IIPL32 MTCC 25056 using biodiesel plant byproduct crude glycerol as a fermentable carbon source. Enriched with monounsaturated fatty acid, nutritional indices mapping based on the fatty acid composition of the yeast SCO, suggested its plausible use as an edible oil blend. In the present study, acute toxicity evaluation of the yeast SCO in C57BL/6 mice has been performed by randomly dividing the animals into 5 groups with 50, 300, 2000, and 5000 mg/Kg yeast SCO dosage, respectively, and predicted the median lethal dose (LD50). Detailed blood biochemistry and kidney and liver histopathology analyses were also reported. The functions of the liver enzymes were also evaluated to check and confirm the anticipated toxicity. To determine cell viability and in vitro biocompatibility, the 3T3-L1 cell line and haemolysis tests were performed. The results suggested the plausible use of yeast SCO as an edible oil blend due to its non-toxic nature in mice models.

Evaluation of urban flood susceptibility through integrated Bivariate statistics and Geospatial technology.

Flood disasters are frequent natural disasters that occur annually during the monsoon season and significantly impact urban areas. This area is characterized by impermeable concrete surfaces, which increase runoff and are particularly susceptible to flooding. Therefore, this study aims to adopt Bi-variate statistical methods such as frequency ratio (FR) and weight of evidence (WOE) to map flood susceptibility in an urbanized watershed. The study area encompasses an urbanized watershed surrounding the Chennai Metropolitan area in southern India. The essential parameters considered for flood susceptibility zonation include geomorphology, soil, land use/land cover (LU/LC), rainfall, drainage, slope, aspect, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The flood susceptibility map was derived using 70% of randomly selected flood areas from the flood inventory database, and the other 30% was used for validation using the area under curve (AUC) method. The AUC method produced a frequency ratio of 0.806 and a weight of evidence value of 0.865 contributing to the zonation of the three classes. The study further investigates the impact of urbanization on flood susceptibility and is further classified into high, moderate, and low flood risk zones. With the abrupt change in climatic scenarios, there is an increase in the risk of flash floods. The results of this study can be used by policymakers and planners in developing a preparedness system to mitigate economic, human, and property losses due to floods in any urbanized watershed.

Assessment of land use and land cover change detection and prediction using deep learning techniques for the southwestern coastal region, Goa, India.

Understanding the connections between human activities and the natural environment depends heavily on information about land use and land cover (LULC) in the form of accurate LULC maps. Environmental monitoring using deep learning (DL) is rapidly growing to preserve a sustainable environment in the long term. For establishing effective policies, regulations, and implementation, DL can be a valuable tool for assessing environmental conditions and natural resources that will positively impact the ecosystem. This paper presents the assessment of land use and land cover change detection (LULCCD) and prediction using DL techniques for the southwestern coastal region, Goa, also known as the tourist destination of India. It consists of three components: (i) change detection (CD), (ii) quantification of LULC changes, and (iii) prediction. A new CD assessment framework, Spatio-Temporal Encoder-Decoder Self Attention Network (STEDSAN), is proposed for the LULCCD process. A dual branch encoder-decoder network is constructed using strided convolution with downsampling for the encoder and transpose convolution with upsampling for the decoder to assess the bitemporal images spatially. The self-attention (SA) mechanism captures the complex global spatial-temporal (ST) interactions between individual pixels over space-time to produce more distinct features. Each branch accepts the LULC map of 2 years as one of its inputs to determine binary and multiclass changes among the bitemporal images. The STEDSAN model determines the patterns, trends, and conversion from one LULC type to another for the assessment period from 2005 to 2018. The binary change maps were also compared with the existing state of the art (SOTA) CD methods, with STEDSAN having an overall accuracy of 94.93%. The prediction was made using an recurrent neural network (RNN) known as long short term memory network (LSTM) for the year 2025. Experiments were conducted to determine area-wise changes in several LULC classes, such as built-up (BU), crops (kharif crop (KC), rabi crop (RC), zaid crop (ZC), double/triple (D/T C)), current fallow (CF), plantation (PL), forests (evergreen forest (EF), deciduous forest (DF), degraded/scurb forest (D/SF) ), littoral swamp (LS), grassland (GL), wasteland (WL), waterbodies max (Wmx), and waterbodies min (Wmn). As per the analysis, over the period of 13 years, there has been a net increase in the amount of BU (1.25%), RC (1.17%), and D/TC( 2.42%) and a net decrease in DF (3.29%) and WL(1.44%) being the most dominant classes being changed. These findings will offer a thorough description of identifying trends in coastal areas that may incorporate methodological hints for future studies. This study will also promote handling the spatial and temporal complexity of remotely sensed data employed in categorizing the coastal LULC of a heterogeneous landscape.

Unveiling the mechanisms by which inclusive leadership influences the good soldier syndrome among health-care employees.

PURPOSE: The purpose of this study is to investigate the relationship between inclusive leadership (IL), psychological safety (PS), affective commitment (AC) and organizational citizenship behavior (OCB) at the workplace. By understanding the sequential linkages, the research aims to provide insights for fostering a positive organizational culture that promotes employee commitment and employees' willingness to go the extra mile for the organization. DESIGN/METHODOLOGY/APPROACH: The authors study how IL and OCB are related through PS and AC. For this purpose, cross-sectional data from 384 nursing professionals in India was collected and structural equation modeling was conducted on the same using IBM AMOS. FINDINGS: The study found that IL has a major impact on OCB. The study further found that perceived IL leads to PS which is associated with OCB through AC. RESEARCH LIMITATIONS/IMPLICATIONS: The study has many theoretical and practical implications. This study uses a framework that is based on Affective events theory. In a health-care environment, IL can foster AC by promoting a culture of respect, collaboration and value for diverse perspectives, which enhances health-care professionals' emotional attachment to their work and the organization. Additionally, by encouraging open communication and a sense of belonging, IL contributes to OCB, as health-care staff are more likely to engage in discretionary behaviors that support the overall effectiveness and positive functioning of the health-care team if PS is improved, ultimately improving patient care outcomes. ORIGINALITY/VALUE: To the best of the authors' knowledge, this is one of the primary studies that looks into the sequential mechanism through which IL impacts OCB.

Evaluation of Metronomic Therapy as a Low-Cost, Sustainable, Standard-of-Care Option in Desmoid Fibromatosis: Real-World Data From a Tertiary Care Center in India.

PURPOSE: Desmoid fibromatosis (DF) is a locally aggressive tumor with low mortality but significant morbidity. There is a lack of standard of care, and existing therapies are associated with significant barriers including access, cost, and toxicities. This study aimed to explore the efficacy and safety of the metronomic therapy (MT) in DF in a large, homogenous cohort from India. PATIENTS AND METHODS: This study involved histologically confirmed DF cases treated with MT comprising vinblastine (6 mg) and methotrexate (15 mg) both once a week, and tamoxifen (40 mg/m2) in two divided doses once daily between 2002 and 2018. RESULTS: There were 315 patients with a median age of 27 years; the commonest site was extremity (142 of 315; 45.0%). There were 159 (50.1%) male patients. Of the 123 (39.0%) prior treated patients, 119 had surgery. Of 315 patients, 263 (83.5%) received treatment at our institute (MT-151, 77-local treatment, 9-tyrosine kinase inhibitor, and 26 were observed). Among the MT cohort (n = 163, 61.2%), at a median follow-up of 36 (0.5-186) months, the 3-year progression-free and overall survival were 81.1% (95% CI, 74.3 to 88.4) and 99.2% (95% CI, 97.6 to 100), respectively. There were 35% partial responses. Ninety-two patients (56.4%) completed 1-year therapy, which was an independent prognosticator (P < .0001; hazard ratio, 0.177 [95% CI, 0.083 to 0.377]). MT was well tolerated. Predominant grade ≥3 toxicities were febrile neutropenia, 12 (7.4%) without any chemotoxicity-related death. The annual cost of MT was $130 US dollars. CONCLUSION: The novel, low-cost MT qualifies as one of the effective, less toxic, sustainable, standard-of-care options for the treatment of DF with global reach and merits wide recognition.