Dynamics of DNA damage-induced nuclear inclusions are regulated by SUMOylation of Btn2.

Spatial compartmentalization is a key facet of protein quality control that serves to store disassembled or non-native proteins until triage to the refolding or degradation machinery can occur in a regulated manner. Yeast cells sequester nuclear proteins at intranuclear quality control bodies (INQ) in response to various stresses, although the regulation of this process remains poorly understood. Here we reveal the SUMO modification of the small heat shock protein Btn2 under DNA damage and place Btn2 SUMOylation in a pathway promoting protein clearance from INQ structures. Along with other chaperones, and degradation machinery, Btn2-SUMO promotes INQ clearance from cells recovering from genotoxic stress. These data link small heat shock protein post-translational modification to the regulation of protein sequestration in the yeast nucleus.

Geo-spatial epidemiology of gallbladder cancer in Bihar, India.

Recently, a substantial increase in gallbladder cancer (GBC) cases has been reported in Bihar, India. The region's groundwater can naturally contain harmful concentrations of arsenic, which appears to be epidemiologically linked to the unusually high incidence. However, the root causes remain largely unexplored. Recent findings of uranium in the state's groundwater may also have associations. This study investigates the geo-spatial epidemiology of GBC in Bihar, India-with a focus on the correlation between environmental carcinogens, particularly arsenic and uranium in groundwater, and the incidence of GBC. Utilizing data from 8460 GBC patients' registration records over an 11-year period at a single health center, the research employs Semi-parametric Geographically Weighted Poisson Regression (S-GWPR) to account for non-stationarity associations and explores significant factors contributing to GBC prevalence at a subdistrict level. The S-GWPR model outperformed the standard Poisson regression model. The estimates suggest that arsenic and uranium concentrations in groundwater did not present significant associations; however, this could be due to the lower resolution of this data at the district level, necessitating higher resolution data for accurate estimates. Other socio-environmental factors included demonstrated significant regional heterogeneity in their association with GBC prevalence. Notably, each 1 % increase in the coverage of well- and canal-irrigated areas is associated with a maximum of 3.0 % and 5.2 % rise in the GBC incidence rate, respectively, likely attributable to carcinogen exposure from irrigation water. Moreover, distance to the health center and domestic electricity connections appear to influence the number of reported GBC cases. The latter suggests that access to electricity might have facilitated the use of groundwater pumps-increasing exposure to carcinogens. The results underscore the necessity for targeted health policies and interventions based on fine-resolution spatial analysis, as well as ongoing environmental monitoring and research to better understand the multifaceted risk factors contributing to GBC.

Lanthanum(III)hydroxide Nanoparticles and Polyethyleneimine-Functionalized Graphene Quantum Dot Nanocomposites in Photosensitive Silicon Heterojunctions.

Lanthanides are largely used in optoelectronics as dopants to enhance the physical and optical properties of semiconducting devices. In this study, lanthanum(III)hydroxide nanoparticles (La(OH)3NPs) are used as a dopant of polyethylenimine (PEI)-functionalized nitrogen (N)-doped graphene quantum dots (PEI-NGQDs). The La(OH)3NPs-dopedPEI-NGQDs nanocomposites are prepared from La(NO)3 in a single step by a green novel method and are characterized by Fourier-transform infrared spectroscopy (FT-IR), ultraviolet-visible spectroscopy (UV-vis), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). Deposited over an n-type Si wafer, the La(OH)3NPs-dopedPEI-NGQDs nanocomposites form Schottky diodes. The I-V characteristics and the photoresponse of the diodes are investigated as a function of the illumination intensity in the range 0-110 mW cm-2 and at room temperature. It is found that the rectification ratio and ideality factor of the diode decrease, while the Schottky barrier and series resistance increase with the enhancing illuminations. As a photodetector, the La(OH)3NPs-dopedPEI-NGQDs/n-Si heterojunction exhibits an appreciable responsivity of 3.9 × 10-3 AW-1 under 22 mW cm-2 at -0.3 V bias and a maximum detectivity of 8.7 × 108 Jones under 22 mW cm-2 at -0.5 V. This study introduces the green synthesis and presents the structural, electrical, and optoelectronic properties of La(OH)3NPs-dopedPEI-NGQDs, demonstrating that these nanocomposites can be promising for optoelectronic applications.

Multilayer WS2 for low-power visible and near-infrared phototransistors.

Mechanically exfoliated multilayer WS2 flakes are used as the channel of field effect transistors for low-power photodetection in the visible and near-infrared (NIR) spectral range. The electrical characterization as a function of the temperature reveals devices with n-type conduction and slightly different Schottky barriers at the drain and source contacts. The WS2 phototransistors can be operated in self-powered mode, yielding both a current and a voltage when exposed to light. The spectral photoresponse in the visible and the NIR ranges shows a high responsivity (4.5 µA/W) around 1250 nm, making the devices promising for telecommunication applications.

Development, validation, and transportability of several machine-learned, non-exercise-based VO2max prediction models for older adults.

PURPOSE: There exist few maximal oxygen uptake (VO2max) non-exercise-based prediction equations, fewer using machine learning (ML), and none specifically for older adults. Since direct measurement of VO2max is infeasible in large epidemiologic cohort studies, we sought to develop, validate, compare, and assess the transportability of several ML VO2max prediction algorithms. METHODS: The Baltimore Longitudinal Study of Aging (BLSA) participants with valid VO2max tests were included (n = 1080). Least absolute shrinkage and selection operator, linear- and tree-boosted extreme gradient boosting, random forest, and support vector machine (SVM) algorithms were trained to predict VO2max values. We developed these algorithms for: (a) for the overall BLSA, (b) by sex, (c) using all BLSA variables, and (d) for variables common in aging cohorts. Finally, we quantified the associations between measured and predicted VO2max and mortality. RESULTS: The age was 69.0 ± 10.4 years (mean ± SD) and the measured VO2max was 21.6 ± 5.9 mL/kg/min. Least absolute shrinkage and selection operator, linear- and tree-boosted extreme gradient boosting, random forest, and support vector machine yielded root mean squared errors of 3.4 mL/kg/min, 3.6 mL/kg/min, 3.4 mL/kg/min, 3.6 mL/kg/min, and 3.5 mL/kg/min, respectively. Incremental quartiles of measured VO2max showed an inverse gradient in mortality risk. Predicted VO2max variables yielded similar effect estimates but were not robust to adjustment. CONCLUSION: Measured VO2max is a strong predictor of mortality. Using ML can improve the accuracy of prediction as compared to simpler approaches but estimates of association with mortality remain sensitive to adjustment. Future studies should seek to reproduce these results so that VO2max, an important vital sign, can be more broadly studied as a modifiable target for promoting functional resiliency and healthy aging.

Improving the latency for 5G/B5G based smart healthcare connectivity in rural area.

Smart hospitals are poised to greatly enhance life quality by offering persistent health monitoring capabilities. Remote healthcare and surgery, which are highly dependent on low latency, have seen a transformative improvement with the advent of 5G technology. This has facilitated a new breed of healthcare services, including monitoring and remote surgical procedures. The enhanced features of 5G, such as Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC), have enabled the development of advanced healthcare systems. These systems reduce the need for direct patient contact in hospitals, which is especially pertinent as 5G becomes more widespread. This research presents novel hybrid detection algorithms, specifically QR decomposition with M-algorithm maximum likelihood-minimum mean square error (QRM-MLD-MMSE) and QRM-MLD-ZF (zero forcing), for use in Massive MIMO (M-MIMO) technology. These methods aim to decrease the latency in MIMO-based Non-Orthogonal Multiple Access (NOMA) waveforms while ensuring optimal bit error rate (BER) performance. We conducted simulations to evaluate parameters like BER and power spectral density (PSD) over Rician and Rayleigh channels using both the proposed hybrid and standard algorithms. The study concludes that our hybrid algorithms significantly enhance BER and PSD with lower complexity, marking a substantial improvement in 5G communication for smart healthcare applications.

Assessment of functional efficacy of sheep plasma protein hydrolysates and their utilization in mutton sausage.

The present study examines the bioactive potential of sheep plasma protein hydrolysates (SPPH) produced by in-vitro gastrointestinal digestion as antioxidants, antimicrobials, anti-obesity agents, and inhibitors of lipid oxidation in sausage to address the oxidative stability and shelf-life issues of mutton. The antioxidant and antimicrobial activities, indicate a positive relationship between the degree of hydrolysis and digestion duration. The study finds that SPPH has a potent inhibitory effect on pancreatic lipase and cholesterol esterase. It has higher oil holding capacity than sheep plasma protein, observed at one hour of hydrolysis time. SPPH exhibit an improved behavior in foaming properties along alkaline pH and digestion time while display lower emulsifying activity and stability with hydrolysis advancement. The SPPH act as a natural preservative in developing functional mutton sausage by inhibiting lipid-oxidation. This study showed that the recovery of SPPH can be a cost-effective and sustainable strategy for generating available ingredients for enhanced shelf-life of meat products.

Adjusting for subsequent therapies in the TOURMALINE-MM1 study shows clinically meaningful improvement in overall survival with addition of ixazomib to lenalidomide and dexamethasone.

TOURMALINE-MM1, the only blinded randomized study in patients with relapsed and/or refractory multiple myeloma (RRMM; ≥1 prior therapy) in the last 10 years, investigated ixazomib+lenalidomide+dexamethasone (IRd) versus lenalidomide+dexamethasone (Rd). Final overall survival (OS) data were based on a median follow-up of 85 months. In RRMM trials where patients have had 1-3 relapses after initial treatment, a high proportion receive subsequent therapy. Application of salvage therapies in blinded trials and newer modes of therapy can increasingly complicate the interpretation of OS. This analysis explores the impact of subsequent therapies on OS outcomes in TOURMALINE-MM1. The inverse probability of censoring weights (IPCW) method, marginal structural model (MSM), and rank preserving structural failure time model (RPSFTM) were utilized to adjust for confounding on OS, introduced by subsequent therapies. Analyses were conducted for the intentto-treat (ITT) population and ≥2 prior lines subgroup. Unadjusted hazard ratio (HR) for IRd versus Rd was 0.94 (95% confidence interval [CI]: 0.78-1.13) in the ITT population. After adjusting for the impact of subsequent therapies by the RPSFTM method, estimated HR for IRd versus Rd in the ITT population was 0.89 (95% CI: 0.74-1.07). Adjusting with IPCW and MSM methods also showed an improvement in HR, favoring IRd. IRd may be particularly beneficial in patients with ≥2 prior lines of therapy (IPCW and MSM HR=0.52, 95% CI: 0.30-0.88; RPSFTM HR=0.68, 95% CI: 0.51-0.91). These analyses highlight the growing challenge of demonstrating OS benefit in multiple myeloma patients and the importance of assessing confounding introduced by subsequent therapies when interpreting OS.

Memory effect and coexistence of negative and positive photoconductivity in black phosphorus field effect transistor for neuromorphic vision sensors.

Black phosphorus (BP) field-effect transistors with ultrathin channels exhibit unipolar p-type electrical conduction over a wide range of temperatures and pressures. Herein, we study a device that exhibits mobility up to 100 cm2 V-1 s-1 and a memory window up to 1.3 µA. Exposure to a supercontinuum white light source reveals that negative photoconductivity (NPC) and positive photoconductivity (PPC) coexist in the same device. Such behavior is attributed to the chemisorbed O2 molecules, with a minor role of physisorbed H2O molecules. The coexistence of NPC and PPC can be exploited in neuromorphic vision sensors, requiring the human eye retina to process the optical signals through alerting and protection (NPC), adaptation (PPC), followed by imaging and processing. Our results open new avenues for the use of BP and other two-dimentional (2D) semiconducting materials in transistors, memories, and neuromorphic vision sensors for advanced applications in robotics, self-driving cars, etc.

Antidiabetic Evaluation of Kigelia pinnata Root Bark Extract in Streptozotocin-Induced Type-2 Diabetes Model of Rats.

Diabetes mellitus (DM) is the most common endocrine disorder characterized by increased blood glucose levels resulting from defective insulin secretion, resistance to insulin action, or both. DM is often associated with severe complications, and there is an increasing appreciation that cognitive function declines in DM. The aim of this research work was to evaluate Kigelia pinnata root bark extract in Streptozotocin (STZ)-induced type-2 diabetes. Experimental diabetes was induced by a single administration of STZ (60 mg/kg, intraperitoneal [i.p.]), immediately after the STZ administration, and all animals were fed with normal food and water. Nicotinamide was administered (120 mg/kg, i.p.) 15 min before STZ. The development of hyperglycemia was confirmed by the elevated blood glucose levels determined at fixed intervals, which was confirmed by measuring fasting blood glucose levels in rats' blood taken from the tail vein. Supplementation with ethanolic extract of K. pinnata root bark (EEKP) significantly reduced the elevated blood glucose in STZ-induced hyperglycemia in rats. EEKP significantly restored the biochemical and antioxidant defense system. On the final day of the protocol, the extract also reduced inflammatory cytokines in the blood serum.

Tribological and Rheological Study of Thixotropic Gels of 2D Nanoparticles.

A thixotropic colloidal gel constituting an aqueous dispersion of synthetic clay Laponite with varying concentrations of salt has been studied for its rheological and tribological performance as a lubricant. We observed that the incorporation of NaCl induces notable enhancements in the colloidal gel's relaxation time, elastic modulus, and yield stress. Although an increase in NaCl concentration decreases the material's relaxation time dependence on waiting time (tw), overall, the strength of its thixotropic character has been observed to increase with an increase in salt concentration. The analysis of friction and wear indicated that the utilization of a thixotropic colloidal gel of Laponite with a higher concentration of NaCl resulted in progressively greater reductions in both the coefficient of friction and specific wear rates under various load-speed conditions. Severe abrasive wear on disc surface under dry test, gradually mitigated upon the introduction of these lubricants. Two simultaneous lubricating mechanisms, first, the smooth sliding of the friction pair, facilitated by the alignment of Laponite particles in the direction of shear forces, and second, the stable structure of Laponite, coupled with the addition of NaCl, enabling continuous replenishment of the wear track with lubricant, are attributed to lubrication effectiveness.

Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit.

End-of-life care (EOLC) exemplifies the joint mission of intensive and palliative care (PC) in their human-centeredness. The explosion of technological advances in medicine must be balanced with the culture of holistic care. Inevitably, it brings together the science and the art of medicine in their full expression. High-quality EOLC in the ICU is grounded in evidence, ethical principles, and professionalism within the framework of the Law. Expert professional statements over the last two decades in India were developed while the law was evolving. Recent landmark Supreme Court judgments have necessitated a review of the clinical pathway for EOLC outlined in the previous statements. Much empirical and interventional evidence has accumulated since the position statement in 2014. This iteration of the joint Indian Society of Critical Care Medicine-Indian Association of Palliative Care (ISCCM-IAPC) Position Statement for EOLC combines contemporary evidence, ethics, and law for decision support by the bedside in Indian ICUs. How to cite this article: Mani RK, Bhatnagar S, Butola S, Gursahani R, Mehta D, Simha S, et al. Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit. Indian J Crit Care Med 2024;28(3):200-250.

Embracing nutritional, physical, pasting, textural, sensory and phenolic profile of functional muffins prepared by partial incorporation of lyophilized wheatgrass, fenugreek and basil microgreens juice powder.

BACKGROUND: Muffins are delightful baked food products that have earned a prominent place in the daily diet of a majority of people around the world. The incorporation of microgreens juice powder (MJP) into muffins boosts their nutritional value. The influence of the incorporation of wheatgrass, fenugreek and basil MJP at 1.5% and 3.0% levels on the nutritional composition, physical properties, pasting, sensory, textural and phenolic profile of functional muffins was evaluated. RESULTS: The results indicated a significant increase in the protein content, ash content, dietary fiber and total phenolic content of MJP incorporated muffins. The incorporation of MJP to the muffins led to a gradual reduction in the L*, a* and b* values. Baking characteristic such as bake loss decreased significantly as a result of MJP incorporation. Furthermore, the incorporation of various MJPs resulted in a significant decrease in the peak viscosity of the flour-MJP blends. Regarding texture, the hardness and chewiness of the muffins increased progressively with an increase in the level of MJP incorporation. The highest hardness (10.15 N) and chewiness (24.45 mJ) were noted for 3% fenugreek MJP incorporated muffins (FK 3.0). The sensory score of MJP incorporated muffins was acceptable and satisfactory. Additionally, 3% basil MJP incorporated muffins (BL 3.0) marked the dominant presence of majority of the detected phenolic acids such as ferulic acid, sinapic acid, chlorogenic acid, caffeic acid, quercetin, cinnamic acid, isothymosin and rosamarinic acid. The highest concentration of p-coumaric acid (11.95 mg kg-1), vanillic acid (26.07 mg kg-1) and kaempferol (8.04 mg kg-1) was recorded for FK 3.0 muffin. CONCLUSION: MJP incorporated muffins revealed the pool of phenolic acids and the reduced bake loss is of industrial interest. The present study concludes that wheatgrass, fenugreek and basil MJP can be incorporated by up to 3% into baked products as a source of functional ingredients for health benefits. © 2024 Society of Chemical Industry.

Terminal Extubation or Terminal Weaning: Is it Feasible in Indian Intensive Care Units?

Terminal extubation (TE) and weaning have long been suggested as a modality of intervention when the continuation of mechanical ventilation is not expected to achieve its therapeutic aim and is merely prolonging the dying process. The decision, however, is complex considering limited evidence regarding the best practices and is often defied due to inherent ethical, legal, and medical dilemmas. The article attempts a brief overview of available literature on this subject and discusses its feasibility in Indian intensive care units (ICUs). How to cite this article: Kumar A, Bhat RS, Mani RK. Terminal Extubation or Terminal Weaning: Is it Feasible in Indian Intensive Care Units? Indian J Crit Care Med 2024;28(2):103-105.

Implementation of the deep learning method for signal detection in massive-MIMO-NOMA systems.

The deep learning method (DLM) is one way to fix issues in optical nonorthogonal multiple access (O-NOMA) systems that are caused by signals that overlap and interfere with each other. NOMA increases the optical framework's spectrum efficiency, allowing several users to share the same time-frequency resources. However, NOMA-DLM-based detection's complicated interference patterns and variable channel conditions are challenging for conventional detection methods to manage. By utilizing deep neural networks' advantages, these methods are able to overcome these challenges and improve detection performance. An overview of the main features and advantages of DLM detection in massive multiple input and output (M-MIMO) O-NOMA systems is given in this article. It describes the essential elements, such as the training procedure and the network design. In order to process the sent symbols or decode data streams, DLM networks are built to process the incoming signal, power allocation coefficients, and extra information. Gradient descent optimization is used to update the network parameters iteratively while training the network, and a diverse and representative dataset is created. Additionally, the challenges of detecting deep learning in O-NOMA systems are examined. It recognizes that in order to get the best results, significant computational resources, a large amount of training data, and careful model design are required. It looks at and compares the 16 × 16, 32 × 32, and 64 × 64 M-MIMO-NOMA models in terms of bit error rate (BER), complexity, and power spectral density (PSD). The suggested DLM algorithms have been demonstrated to perform better than traditional methods by achieving an excellent BER of 10-3 at 4.1 dB and PSD (-2500) performance with low complexity.

Incidence of Cardiovascular Instability in Patients With Guillain-Barré Syndrome: A Retrospective Study.

Introduction Guillain-Barré syndrome (GBS) is an autoimmune disease affecting radicles and peripheral nerves resulting in acute flaccid paralysis. Respiratory failure, autonomic dysfunction, and secondary complications such as pneumonia, and venous thromboembolism are the major causes of death and disability in GBS. Cardiovascular complications play a major role in the prognosis of GBS patients. The aim is to determine the incidence of cardiovascular instability in GBS patients and to see if there are any specific risk groups associated with the development of cardiovascular instability. Methodology This is a retrospective descriptive study conducted in a tertiary care center in South India. Data on 50 consecutive GBS patients were collected from hospital records including case sheets, death summaries, and discharge summaries. Patients with evidence of sepsis, blood loss, heavy alcohol consumption, and chronic liver disease were excluded from the study. Baseline demographic data, symptom onset to admission time, baseline Erasmus Guillain-Barré Syndrome Respiratory Insufficiency Score (EGRIS), and baseline liver function tests were documented. The presence of heart rate and blood pressure fluctuations was noted from the records. Frequency data were calculated from the categorical variables. Analysis of non-parametric variables by chi-square test was done using IBM SPSS Statistics for Windows, Version 25.0 (Released 2017; IBM Corp., Armonk, New York, United States). Results Cardiovascular instability was present in 15 (30%) patients in the study population. It was present in all patients (100%) who require mechanical ventilation. The incidence of cardiovascular instability was higher in patients who had lesser onset to admission times (41.9% vs 10.5%; p=0.019), EGRIS≥4 (40.6% vs 11.1%; p=0.029), and lower cranial nerve involvement (40% vs 6.7%; p=0.018). Conclusion Of patients with GBS, 30% developed cardiovascular instability during their disease course. Patients with lesser onset to admission times, EGRIS ≥4, and those with lower cranial nerve involvement had a greater incidence of cardiovascular instability.

Taking cues from machine learning, compartmental and time series models for SARS-CoV-2 omicron infection in Indian provinces.

SARS-CoV-2, the virus responsible for COVID-19, posed a significant threat to the world. We analyzed COVID-19 dissemination data in the top ten Indian provinces by infection incidences using the Susceptible-Infectious-Removed (SIR) model, an Autoregressive Integrated Moving Average (ARIMA) time series model, a machine learning model based on the Random Forest, and distribution fitting. Outbreaks are expected to continue if the Basic Reproduction Number (R0) > 1, and infection waves are anticipated to end if the R0 < 1, as determined by the SIR model. Different parametric probability distributions are also fitted. Data collected from December 12, 2021, to March 31, 2022, encompassing data from both before and during the implementation of strict control measures. Based on the estimates of the model parameters, health agencies and government policymakers can develop strategies to combat the spread of the disease in the future, and the most effective technique can be recommended for real-world application for other outbreaks of COVID-19. The best method out of these could be also implemented further on the epidemiological data of other similar infectious agents.