Metabolic health tracking using Ultrahuman M1 continuous glucose monitoring platform in non- and pre-diabetic Indians: a multi-armed observational study.

Continuous glucose monitoring (CGM) device adoption in non- and pre-diabetics for preventive healthcare has uncovered a paucity of benchmarking data on glycemic control and insulin resistance for the high-risk Indian/South Asian demographic. Furthermore, the correlational efficacy between digital applications-derived health scores and glycemic indices lacks clear supportive evidence. In this study, we acquired glycemic variability (GV) using the Ultrahuman (UH) M1 CGM, and activity metrics via the Fitbit wearable for Indians/South Asians with normal glucose control (non-diabetics) and those with pre-diabetes (N = 53 non-diabetics, 52 pre-diabetics) for 14 days. We examined whether CGM metrics could differentiate between the two groups, assessed the relationship of the UH metabolic score (MetSc) with clinical biomarkers of dysglycemia (OGTT, HbA1c) and insulin resistance (HOMA-IR); and tested which GV metrics maximally correlated with inflammation (Hs-CRP), stress (cortisol), sleep, step count and heart rate. We found significant inter-group differences for mean glucose levels, restricted time in range (70-110 mg/dL), and GV-by-SD, all of which improved across days. Inflammation was strongly linked with specific GV metrics in pre-diabetics, while sleep and activity correlated modestly in non-diabetics. Finally, MetSc displayed strong inverse relationships with insulin resistance and dysglycemia markers. These findings present initial guidance GV data of non- and pre-diabetic Indians and indicate that digitally-derived metabolic scores can positively influence glucose management.

Quantitative assessment and optimization of parallel contact model for flexible paddy straw: a definitive screening and central composite design approach using discrete element method.

To simulate the bending behaviour of paddy straw at varied moisture contents after crop harvesting, we created a flexible paddy straw specimen model based on the Hertz-Mindlin with parallel contact bonding model using the discrete element model (DEM) approach. The research presented in this study aims to investigate a new approach called Definitive Screening Design (DSD) for parameterizing and screening the most significant parameters of the DEM model. This investigation will specifically focus on the three-point bending test as a means of parameterization, and the shear plate test will be used for validation purposes. In addition, the most influential DEM parameters were optimized using another Design of Experiments approach called Central Composite Design. The findings from the DSD indicated that parameters such as bonded disk scale, normal stiffness, and shear stiffness have the highest impact on the bending force, while the coefficient of static friction (Straw-Steel) has the least effect. The three bonding parameters were respectively calibrated with the loading rate (0.42, 0.5, and 0.58 mm s-1) and a good agreement between actual and simulated shear force at moisture content M1-35 ± 3.4%, M2-24 ± 2.2% and M3-17 ± 2.6%. Modelled stem helps simulate the straw with low error and increases the accuracy of the simulation. The validated model, with an average relative error of 5.43, 7.63, and 8.86 per cent, produced reasonable agreement between measured and simulated shear force value and loading rate.

3D printed bio-ceramic loaded PEGDA/vitreous carbon composite: Fabrication, characterization, and life cycle assessment.

Stereolithography (SLA) is gaining vast popularity in the development of three-dimensional parts with customized materials for tissue engineering applications. Consequently, developing customized materials like bio-composites (bio-polymers and bio-ceramics) is the basic pillar that meets the application requirement. Photo-crosslinkable poly(ethylene glycol) diacrylate (PEGDA) has outstanding biocompatibility and biophysical properties for tissue engineering. But, because of its poor mechanical properties, its scope is limited to load-bearing applications. This research aims to enhance the mechanical and tribological properties of PEGDA by reinforcing Vitreous Carbon (VC) bioceramic. Therefore, 1 to 5 wt % of VC have been added in PEGDA and developed novel PEGDA/VC composite resins for SLA. The rheological and sedimentation test have been performed to check the suitability for SLA printing. Afterward, printed materials have been characterized by fourier transform infrared spectrometer, X-ray diffraction, thermogravimetric analysis, optical profilometer, and scanning electron microscope. Moreover, tensile compression, flexural, and tribological properties have been evaluated. It was found that the addition of VC in PEGDA enhanced its mechanical, thermal, and tribological properties. Besides, a life cycle assessment of materials and energy resources in SLA process has been performed to investigate the environmental impact.

A qualitative exploration of perceived needs and barriers of individuals with schizophrenia, caregivers and clinicians in using mental health applications in Madhya Pradesh, India.

Introduction: About 3.5 million people are living with schizophrenia in India, with most failing to receive minimally adequate care. Digital mental health applications could potentially decrease this treatment gap; however, these applications should be tailored to meet the needs and overcoming barriers of its end-users to ensure their adoption and sustained usage. Few studies in India have explored the perspectives of target stakeholders to understand how digital tools could be viable for supporting care. Therefore, this study explores the perceived needs and barriers of patients with schizophrenia, caregivers and clinicians in using digital mental health applications. Methods: Focus group discussions (FGDs) were conducted with patients having schizophrenia attending outpatient clinics at a government tertiary hospital, and their caregivers, and mental health clinicians in Bhopal, Madhya Pradesh, India. FGDs were audio-recorded and coded. Framework analysis was employed to guide the analysis, involving deductive and inductive generation of themes, data triangulation and comparison of perspectives between participant groups. Results: Six FGDs were conducted with individuals with schizophrenia (n â€‹= â€‹11), their caregivers (n â€‹= â€‹14), and mental health clinicians (n â€‹= â€‹19). Four a priori themes were established: a) Prior experiences with health applications; b) Content of a mental health application; c) Involvement of caregivers in mental health application usage and d) Supporting doctors' work through mental health applications. Additionally, two themes were generated inductively: a) Qualities of a mental health application and b) Data privacy and confidentiality. Conclusion: Exploration of stakeholder perspectives on the content, features, and uses of mental health applications is crucial to yield initial insights about the use of these digital programs in India. This study generated a multitude of suggestions on app functionality and components, which can guide ongoing efforts to develop and deliver digital mental health applications for patients living with schizophrenia in low-resource settings, with limited access to mental health services.

Recent advances in low-cost, portable automated resuscitator systems to fight COVID-19.

World is fighting one of its greatest battle against COVID-19 (a highly infectious disease), leading to death of hundreds of thousands of people around the world, with severe patients requiring artificial breathing. To overcome the shortage of ventilators in medical infrastructure, various low-cost, easy to assemble, portable ventilators have been proposed to fight the ongoing pandemic. These mechanical ventilators are made from components that are generally readily available worldwide. Such components are already associated with day-to-day gadgets or items and which do not require specialized manufacturing processes. Various designs have been proposed, focussing on meeting basic requirements for artificial ventilation to fight the ongoing pandemic. But some people are against the usage of these mechanical ventilators in real-life situations, owing to poor reliability and inability of these designs to meet certain clinical requirements. Each design has its own merits and demerits, which need to be addressed for proper designing. Therefore, this article aims to provide readers an overview of various design parameters that needs to be considered while designing portable ventilators, by systematic analysis from available pool of proposed designs. By going through existing literature, we have recognized multiple factors influencing device performance and how these factors need to be considered for efficient device operation.

Assessment of antifungal resistance and associated molecular mechanism in Candida albicans isolates from different cohorts of patients in North Indian state of Haryana.

The present study examines the trend in distribution of Candida species and their antifungal resistance patterns in hospitals across Haryana, a North Indian state with poorly addressed epidemiology of fungal infections. In our collection of 228 Candida isolates, Candida albicans dominated in both high vaginal swab (HVS) and urine samples while Candida glabrata and Candida tropicalis were the second-highest non-albicans Candida species (NAC), respectively. Of note, in blood samples, C. tropicalis and C. albicans were present in equal numbers. All 228 isolates were subjected to antifungal susceptibility tests, whereby 51% of C. albicans recovered from HVS samples displayed fluconazole resistance. To understand its mechanistic basis, expression profiling of efflux pump genes CDR1, CDR2, MDR1 and azole drug target, ERG11 was performed in 20 randomly selected resistant isolates, wherein many isolates elicited higher expression. Further, ERG11 gene sequencing suggested that most of the isolates harbored mutations, which are not reported with azole resistance. However, one isolate, RPCA9 (MIC 64 µg/mL) harbored triple mutation (Y132C, F145L, A114V), wherein Y132 and F145 sites were previously implicated in azole resistance. Interestingly, one isolate, (RPCA61) having MIC > 128 µg/mL harbored a novel mutation, G129R. Of note, HVS isolates RPCA 21, RPCA 22, and RPCA 44 (MICs 64 to > 128 µg/mL) did not show any change in alteration in ERG11 or overexpression of efflux pump genes. Together, this study presents a first report of Candida infections in selected hospitals of Haryana State.

Capillary electrophoresis, gas-phase electrophoretic mobility molecular analysis, and electron microscopy: effective tools for quality assessment and basic rhinovirus research.

We describe standard methods for propagation, purification, quality control, and physicochemical characterization of human rhinoviruses, using HRV-A2 as an example. Virus is propagated in HeLa-OHIO cells grown in suspension culture and purified via sucrose density gradient centrifugation. Purity and homogeneity of the preparations are assessed with SDS-polyacrylamide gel electrophoresis (SDS-PAGE), capillary electrophoresis (CE), gas-phase electrophoretic mobility molecular analysis (GEMMA), and electron microscopy (EM). We also briefly describe usage of these methods for the characterization of subviral particles as well as for the analysis of their complexes with antibodies and soluble recombinant receptor mimics.

Assessment of traffic noise at Kolar Gold Fields, India.

Traffic noise produces environmental problems on surroundings. At Kolar Gold Fields (KGF), traffic load at different locations can cause noise pollution. Therefore, a detailed study was carried out at KGF in commercial, residential and silence zone. Different monitoring locations were identified in these zones and A-weighted equivalent sound pressure levels (L(eq)) were measured. The study was conducted on different weekdays and weekend for different periods of the day and compared with ambient noise standards. Since many variables were noted during noise monitoring, therefore, a multiple regression analysis was also carried out to develop a regression model for prediction of L(eq). Stepwise regression procedure was followed for the selection of most influencing variables. Model adequacy was checked using normal distribution with zero mean and constant variance, difference between F-observed and F-critical, and correlation between measured and predicted noise levels.