BENEFICIAL EFFECT OF NISHAAKATHAKAADHI KASHAYAM ON STREPTOZOTOCIN INDUCED DIABETES AND GLUCOSE METABOLIC ENZYMES

Polyherbal traditional formulation Nishaakathakaadhi Kashayam elicit antihyperglycemic effects in streptozotocin induced hyperglycemic rats. Nishaakathakaadhi Kashayam 0.6 ml/kg, p.o. significantly reduced the fasted blood glucose level after 60 days of treatment in diabetic rats. The Kashayam also reduced serum cholesterol, triglycerides, LDL, VLDL, alanine transaminase, aspertate transaminase, alkaline phophatase and urea whereas increased HDL, albumin, protein and haemoglobin levels become normal after the treatment. Glycolytic enzyme showed a significant increases in Streptozotocin induced condition while a significant decrease were observed in levels of the gluconeogenic enzymes in Nishaakathakaadhi Kashayam treated diabetic rats. The Kashayam was non-significantly active with standard drug Glibenclamide (0.6 mg/kg, p.o.). The Kashayam has a positive effect on the histopathological changes of the pancreatic beta cells in Streptozotocin induced diabetic rats. The results suggest that Nishaakathakaadhi Kashayam possesses potential antihyperglycemic effect by regulating glucose homeostasis in streptozotocin induced diabetic rats. The scientific evidences to antidiabetic use suggest that administration of polyherbal formulation to rats, in a dosage used safely by humans, reduces the production of various diabetes causing biochemical parameters and concomitantly prevents the development of Type 2 (NIDDM) diabetes in established animal models. A combination of different herbals in NKK is used to get the enhanced desired activity

Rational Design of Pore Size and Functionality in a Series of Isoreticular Zwitterionic Metal-Organic Frameworks

The isoreticular expansion and functionalization of charged-polarized porosity has been systematically explored by the rational design of 11 isostructural zwitterionic metal-organic frameworks (ZW-MOFs). This extended series of general structural composition {[M3F(L1)3(L2)1.5]·guests}n was prepared by employing the solvothermal reaction of Co and Ni tetrafluoroborates with a binary ligand system composed of zwitterionic pyridinium derivatives and traditional functionalized ditopic carboxylate auxiliary ligands (HL1·Cl = 1-(4-carboxyphenyl)-4,4′-bipyridinium chloride, Hcpb·Cl; or 1-(4-carboxyphenyl-3-hydroxyphenyl)-4,4′-bipyridinium chloride, Hchpb·Cl; and H2L2 = benzene-1,4-dicarboxylic acid, H2bdc; 2-aminobenzene-1,4-dicarboxylic acid, H2abdc; 2,5-dihydroxy-1,4-benzenedicarboxylic acid, H2dhbdc; biphenyl-4,4′-dicarboxylic acid, H2bpdc; or stilbene-4,4′-dicarboxylic acid, H2sdc). Single-crystal structure analyses revealed cubic crystal symmetry (I-43m, a = 31-36 Å) with a 3D pore system of significant void space (73-81%). The pore system features three types of pores being systematically tunable in size ranging from 17.4 to 18.8 Å (pore I), 8.2 to 12.8 Å (pore II), and 4.8 to 10.4 Å (pore III) by the choice of auxiliary ligands. All members of this series have noninterpenetrating structures and exhibit robust architectures, as evidenced by their permanent porosity and high thermal stability (up to 300 °C). The structural integrity and specific surface areas could be systematically optimized using supercritical CO2 exchange methods for framework activation resulting in BET surface areas ranging from 1250 to 2250 m2/g. Most interestingly, as a structural landmark, we found the pore surfaces lined with charge gradients employed by the pyridinium ligands. This key feature results in significant adsorption of carbon dioxide and methane which is attributed to polarization effects. With this contribution we pioneer the reticulation of pyridinium building blocks into extended zwitterionic networks in which specific properties can be targeted

Drug utilization pattern in Schizophrenia

Background: Pharmacotherapy is the mainstay of treatment in schizophrenia. The economic impact of this illness is wide ranging, long lasting and huge. The emergence of newer antipsychotics has changed the prescribing pattern. Purpose of this study is to determine the prescription pattern of antipsychotic drugs and to analyse the drug utilization in patients with schizophrenia based on WHO prescribing indicators.Methods: A descriptive study was conducted for a period of 1-year duration at inpatient Department of Psychiatry of a Government Medical College in Kerala, India among 230 schizophrenic patients. The case sheets of patients meeting inclusion criteria were scrutinised to find out the antipsychotic prescription pattern and drug utilization was analysed using WHO prescribing indicators. Analysis was done using descriptive statistics.Results: Newer antipsychotics (55.2%) were prescribed slightly more in preference to older antipsychotic (44.8%) drugs. Out of the newer drugs prescribed olanzapine (20.9%) was prescribed the most followed by risperidone (18%). Haloperidol (22.9%) was the most frequently prescribed older antipsychotic. Majority (71.3%) of the patients were given more than one antipsychotics during the hospital stay. Trihexyphenidyl (27.9%) was the most frequently co-prescribed drug with antipsychotics. Average number of drugs per encounter was 4.19, 73.4% of the drugs were prescribed in their generic name, 50.4% of the encounters were with an injection prescribed. 44.4%of the drugs were prescribed from the EDL (WHO-19th edition). Average drug cost per encounter was Rs.45.43. Percentage of drug cost spent on injections was 8.44%.Conclusions: Newer antipsychotics were more prescribed for schizophrenia of which olanzapine was the commonest. Newer antipsychotics are preferred because of their propensity to cause less side effects and more efficacy. Study of pattern of drug utilization is useful for measuring the economic impact of drug use among patients thereby facilitating rational prescribing

Overview of hepatocellular carcinoma: from molecular aspects to future therapeutic options.

Hepatocellular carcinoma (HCC) is the seventh most highly prevalent malignant tumor globally and the second most common cause of mortality. HCC develops with complex pathways that occur through multistage biological processes. Non-alcoholic fatty liver disease, metabolic-associated fatty liver disease, alcoholic liver disease, autoimmune hepatitis, hepatitis B, and hepatitis C are the causative etiologies of HCC. HCC develops as a result of epigenetic changes, protein-coding gene mutations, and altered signaling pathways. Biomarkers and potential therapeutic targets for HCC open up new possibilities for treating the disease. Immune checkpoint inhibitors are included in the treatment options in combination with molecular targeted therapy

Causal discovery to understand hot corrosion

Gas turbine superalloys experience hot corrosion, driven by factors including corrosive deposit flux, temperature, gas composition, and component material. The full mechanism still needs clarification and research often focuses on laboratory work. As such, there is interest in causal discovery to confirm the significance of factors and identify potential missing causal relationships or codependencies between these factors. The causal discovery algorithm fast causal inference (FCI) has been trialled on a small set of laboratory data, with the outputs evaluated for their significance to corrosion propagation, and compared to existing mechanistic understanding. FCI identified salt deposition flux as the most influential corrosion variable for this limited data set. However, HCl was the second most influential for pitting regions, compared to temperature for more uniformly corroding regions. Thus, FCI generated causal links aligned with literature from a randomised corrosion data set, while also identifying the presence of two different degradation modes in operation

Association between cannabis use and psychosis-related outcomes using sibling pair analysis in a cohort of young adults

Context: Prospective cohort studies have identified an association between cannabis use and later psychosis-related outcomes, but concerns remain about unmeasured confounding variables. The use of sibling pair analysis reduces the influence of unmeasured residual confounding

Whole genome analysis of Rhizopus species causing rhino-cerebral mucormycosis during the COVID-19 pandemic

IntroductionMucormycosis is an acute invasive fungal disease (IFD) seen mainly in immunocompromised hosts and in patients with uncontrolled diabetes. The incidence of mucormycosis increased exponentially in India during the SARS-CoV-2 (henceforth COVID-19) pandemic. Since there was a lack of data on molecular epidemiology of Mucorales causing IFD during and after the COVID-19 pandemic, whole genome analysis of the Rhizopus spp. isolated during this period was studied along with the detection of mutations that are associated with antifungal drug resistance.Materials and methodsA total of 50 isolates of Rhizopus spp. were included in this prospective study, which included 28 from patients with active COVID-19 disease, 9 from patients during the recovery phase, and 13 isolates from COVID-19-negative patients. Whole genome sequencing (WGS) was performed for the isolates, and the de novo assembly was done with the Spades assembler. Species identification was done by extracting the ITS gene sequence from each isolate followed by searching Nucleotide BLAST. The phylogenetic trees were made with extracted ITS gene sequences and 12 eukaryotic core marker gene sequences, respectively, to assess the genetic distance between our isolates. Mutations associated with intrinsic drug resistance to fluconazole and voriconazole were analyzed.ResultsAll 50 patients presented to the hospital with acute fungal rhinosinusitis. These patients had a mean HbA1c of 11.2%, and a serum ferritin of 546.8 ng/mL. Twenty-five patients had received steroids. By WGS analysis, 62% of the Rhizopus species were identified as R. delemar. Bayesian analysis of population structure (BAPS) clustering categorized these isolates into five different groups, of which 28 belong to group 3, 9 to group 5, and 8 to group 1. Mutational analysis revealed that in the CYP51A gene, 50% of our isolates had frameshift mutations along with 7 synonymous mutations and 46% had only synonymous mutations, whereas in the CYP51B gene, 68% had only synonymous mutations and 26% did not have any mutations.ConclusionWGS analysis of Mucorales identified during and after the COVID-19 pandemic gives insight into the molecular epidemiology of these isolates in our community and establishes newer mechanisms for intrinsic azole resistance

Unconventional animal models for traumatic brain injury and chronic traumatic encephalopathy

Traumatic brain injury (TBI) is one of the main causes of death worldwide. It is a complex injury that influences cellular physiology, causes neuronal cell death, and affects molecular pathways in the brain. This in turn can result in sensory, motor, and behavioral alterations that deeply impact the quality of life. Repetitive mild TBI can progress into chronic traumatic encephalopathy (CTE), a neurodegenerative condition linked to severe behavioral changes. While current animal models of TBI and CTE such as rodents, are useful to explore affected pathways, clinical findings therein have rarely translated into clinical applications, possibly because of the many morphofunctional differences between the model animals and humans. It is therefore important to complement these studies with alternative animal models that may better replicate the individuality of human TBI. Comparative studies in animals with naturally evolved brain protection such as bighorn sheep, woodpeckers, and whales, may provide preventive applications in humans. The advantages of an in-depth study of these unconventional animals are threefold. First, to increase knowledge of the often-understudied species in question; second, to improve common animal models based on the study of their extreme counterparts; and finally, to tap into a source of biological inspiration for comparative studies and translational applications in humans

Comparison of length-frequency versus statolith age analysis of Uroteuthis (Photololigo) singhalensis in eastern Arabian Sea

Loliginid squids are a commercially important group of neritic squids in the coastal marine waters in tropical and temperate regions around the world and are valuable resources in many areas. Uroteuthis (Photololigo) singhalensis is listed among the commercial species of loliginid squid exploited from the China Sea to the eastern Arabian Sea. Though this species is distributed from western Pacific to the Indian Ocean from the Andaman Sea, the Bay of Bengal to the Arabian Sea and the eastern African coasts, there is little information on the life cycle of this species throughout its distributional range. The objective of this study is to determine the length-weight relationship, age and growth of U. (P.) singhalensis off eastern Arabian Sea. Most earlier estimates of growth in tropical squids are derived from length frequency analysis. The accuracy and precision of squid growth estimates have been enhanced by using statolith increment analysis, hence statolith increment is used to determine age and individual growth rate of squid off the eastern Arabian Sea. Further, the comparison of the length frequency analysis with statolith ageing techniques is attempted

Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017

Background To inform actions at the district level under the National Nutrition Mission (NNM), we assessed the prevalence trends of child growth failure (CGF) indicators for all districts in India and inequality between districts within the states. Methods We assessed the trends of CGF indicators (stunting, wasting and underweight) from 2000 to 2017 across the districts of India, aggregated from 5 × 5 km grid estimates, using all accessible data from various surveys with subnational geographical information. The states were categorised into three groups using their Socio-demographic Index (SDI) levels calculated as part of the Global Burden of Disease Study based on per capita income, mean education and fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using coefficient of variation (CV). We projected the prevalence of CGF indicators for the districts up to 2030 based on the trends from 2000 to 2017 to compare with the NNM 2022 targets for stunting and underweight, and the WHO/UNICEF 2030 targets for stunting and wasting. We assessed Pearson correlation coefficient between two major national surveys for district-level estimates of CGF indicators in the states. Findings The prevalence of stunting ranged 3.8-fold from 16.4% (95% UI 15.2–17.8) to 62.8% (95% UI 61.5–64.0) among the 723 districts of India in 2017, wasting ranged 5.4-fold from 5.5% (95% UI 5.1–6.1) to 30.0% (95% UI 28.2–31.8), and underweight ranged 4.6-fold from 11.0% (95% UI 10.5–11.9) to 51.0% (95% UI 49.9–52.1). 36.1% of the districts in India had stunting prevalence 40% or more, with 67.0% districts in the low SDI states group and only 1.1% districts in the high SDI states with this level of stunting. The prevalence of stunting declined significantly from 2010 to 2017 in 98.5% of the districts with a maximum decline of 41.2% (95% UI 40.3–42.5), wasting in 61.3% with a maximum decline of 44.0% (95% UI 42.3–46.7), and underweight in 95.0% with a maximum decline of 53.9% (95% UI 52.8–55.4). The CV varied 7.4-fold for stunting, 12.2-fold for wasting, and 8.6-fold for underweight between the states in 2017; the CV increased for stunting in 28 out of 31 states, for wasting in 16 states, and for underweight in 20 states from 2000 to 2017. In order to reach the NNM 2022 targets for stunting and underweight individually, 82.6% and 98.5% of the districts in India would need a rate of improvement higher than they had up to 2017, respectively. To achieve the WHO/UNICEF 2030 target for wasting, all districts in India would need a rate of improvement higher than they had up to 2017. The correlation between the two national surveys for district-level estimates was poor, with Pearson correlation coefficient of 0.7 only in Odisha and four small north-eastern states out of the 27 states covered by these surveys. Interpretation CGF indicators have improved in India, but there are substantial variations between the districts in their magnitude and rate of decline, and the inequality between districts has increased in a large proportion of the states. The poor correlation between the national surveys for CGF estimates highlights the need to standardise collection of anthropometric data in India. The district-level trends in this report provide a useful reference for targeting the efforts under NNM to reduce CGF across India and meet the Indian and global targets. Keywords Child growth failureDistrict-levelGeospatial mappingInequalityNational Nutrition MissionPrevalenceStuntingTime trendsUnder-fiveUndernutritionUnderweightWastingWHO/UNICEF target