Development and diversity of lactic acid producing bacteria and bifidobacteria in healthy full term Indian infants from Himachal Pradesh

Background/Aims The initial microbial colonization is a crucial step for the healthy development of an infant. Previous studies from India reported the dominance of target microbial species among Indian infants without any analysis on the diversity of target groups. This is the first study from India with an objective to investigate the establishment and diversity of lactic acid producing bacteria (LAB) and bifidobacteria in vaginally delivered, full term, breastfed infants for the first 4 months after birth. Methods Present study used polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) based sequence analysis of LAB and bifidobacteria in healthy infants. The results were used to compare the development and early colonization by LAB and bifidobacteria using diversity indices during the initial months of development of gut microbiota in infants. Results During the first 4 months, the Shannon diversity index (H) of LAB increased from 1.16 to 1.318 and for bifidobacteria the H increased from 0.975 to 1.293 (P<0.05). Higher Sorenson’s pair wise similarity coefficient was observed for LAB and bifidobacteria during 2nd and the 3rd month. The species of the genera Enterococcus, Streptococcus, and Lactobacillus were dominant among the LAB group whereas Bifidobacterium breve was dominant species among Bifidobacterium group. Conclusions Our results indicate that in breast fed infants, the microbial diversity of LAB and bifidobacteria increased during the period of study

Big flip graphs and their automorphism groups

In this paper, we study the relationship between the mapping class group of an infinite-type surface and the simultaneous flip graph, a variant of the flip graph for infinite-type surfaces defined by Fossas and Parlier [6]. We show that the extended mapping class group is isomorphic to a proper subgroup of the automorphism group of the flip graph, unlike in the finite-type case. This shows that Ivanov\u27s metaconjecture, which states that any “sufficiently rich" object associated to a finite-type surface has the extended mapping class group as its automorphism group, does not extend to simultaneous flip graphs of infinite-type surfaces

Lipoprotein(a) and SYNTAX Score Association with Severity of Coronary Artery Atherosclerosis in North India

Objectives: This cross-sectional study investigated the association of lipoprotein(a) [Lp(a)] levels  as an atherosclerosis predictor and their relationship to the severity of coronary artery disease (CAD). Methods: 360 consecutive patients at Sanjay Gandhi Postgraduate Institute of Medical Sciences and King George’s Medical University hospitals, Lucknow, North India, with chest pains, CAD symptoms and on lipid-lowering therapy were enrolled between June 2009 and October 2011. Before coronary artery angiography (CAG), a fasting blood sample was assessed for lipid and Lp(a) levels. The synergy between percutaneous coronary intervention with taxus and cardiac surgery (SYNTAX) score was calculated according to the CAG results. Patients were divided into 3 groups based on CAD severity and SYNTAX scores. Results: Angiography revealed CAD in 270 patients. Lp(a) levels were higher in CAD compared to non-CAD patients (48.7 ± 23.8 mg/dl versus 18.9 ± 11.1 mg/dl [P &lt;0.0001]). The levels of Lp(a)were lower in single than in double and triple vessels (39.3 ± 18.4 mg/dl versus 58.0 ± 23.0 mg/dl, and 69.2 ± 24.1 mg/dl, [P &lt;0.05]). Lp(a) levels were significantly higher in severe CAD with SYNTAX score &gt;30 (88.0±24.0 mg/dl). Lp(a) levels correlated significantly with SYNTAX scores (r = 0.70, P &lt;0.0001). Conclusion: In this study, Lp(a) levels were positively associated with a patient’s SYNTAX score in diseased vessels. Furthermore, an elevated Lp(a) level was a causal, independent risk factor of CAD. Lowering Lp(a) levels would reduce CAD in primary and secondary prevention settings. There is an urgent need to define more precisely which patients to treat and which to target for earlier interventions.

Nationwide Analysis of The Outcomes and Mortality of Hospitalized COVID-19 Patients

Introduction: The Coronavirus disease 2019 (COVID-19) pandemic has affected people worldwide with the United States (US) with the largest number of reported cases currently. Previous studies in hospitalized COVID-19 patients have been limited by sample size. Methods: The National Inpatient Sample database which is the largest inpatient database in the US was queried in the year 2020 for the diagnosis of COVID-19 based on ICD-10-CM U07.1 and associated outcomes. Multivariate logistic regression analysis was used to identify predictors of mortality. STATA 16.0 was used for statistical analysis. Results: A weighted total of 1,678,995 hospitalizations for COVID-19 were identified. Median age of admitted patients with COVID-19 was 65 year (51-77) with 47.9% female and 49.2% White. Majority of the patients admitted were >65 years of age (49.3%). Hypertension and diabetes were the most common comorbidities (64.2% and 39.5%, respectively). Overall inpatient mortality was 13.2% and increasing to 55.9% in patients requiring mechanical ventilation. Trend of inpatient mortality was significantly decreasing over the year. Predictors of inpatient mortality included age, male sex, diabetes, chronic kidney disease, heart failure, arrythmia, obesity, and coagulopathy. Despite a lower proportion of patients admitted to hospital with COVID-19, Black, Hispanic, and Native Americans were at an increased adjusted odds of inpatient mortality. Disparity was also noted in income, with low median household income associated with higher risk of mortality. Conclusion: In the largest US cohort with >1.6 million hospitalized COVID-19 patients in 2020, overall inpatient mortality was 13.6% with significantly higher mortality in ventilated patients. Significant socioeconomic and racial disparities were present with minorities at higher odds of mortality

Recent Advancement and Emerging Applications of Lignin

Lignin is a significant renewable natural energy resource these days, used as an environmentally acceptable and sustainable alternative fossil fuel feedstock in a huge possibility of value-added products. Lignin is a polymeric molecule that possesses an aromatic unit structure, together with cellulose, and is a main component of the cell walls of plants. It is the byproduct of agriculture residues and biorefinery products and can be extracted from paper-pulp industries. Properties of lignin may differ depending on the extraction method and source and also on an aromatic ring as the main constituent of lignin in the structure. This rare composition of lignin makes it more valuable, allowing for value-added applications such as in the field of storage devices and energy harvesters. This review focuses on derivatives of lignin, structure and composition sources and characteristics, and its sustainable emerging application in various fields are discussed

Behavioural and Emotional Problems in Adolescents

BackgroundAdolescents are highly vulnerable age to psychiatric disorders. This study aimed to explore the prevalence and patterns of behavioural and emotional problems in adolescents. It was also aimed to explore associations between socio-environmental stressors and adverse outcomes.Method  A school based cross-sectional study was conducted between January and July 2008. A stratified random sampling was done. 1150 adolescents in 12 to 18 year age group in grades 7 to 12 in 10 co-educational schools (government run and private) were the subjects of the study. Behavioural and emotional problems were assessed using Youth Self-Report (2001) questionnaire. Family stressors were assessed using a pre-tested 23 item questionnaire. Statistical analysis used:  Univariate and multivariate analysis was done. Multiple logistic regression analysis was also done. ResultsPrevalence of behavioural and emotional problems in adolescents was found to be 30%, with girls exceeding boys in all age groups. Internalizing syndrome was the most common (28.6%) psychiatric problem. On stepwise regression analysis, a perceived lack of emotional proximity to mother had the highest odds (3.489) followed by addiction in father (2.642) and marital discord in parents (1.402). Type of school, type of family, socioeconomic status, relationship with father, mother's employment and educational status were not found to be significantly associated.ConclusionAn alarming number of our adolescents suffer from emotional and behavioural problems which have their roots in the family environment. These data suggest urgency in establishing a school based mental health service

Nanoemulsion Adjuvant Augments Retinaldehyde Dehydrogenase Activity in Dendritic Cells via MyD88 Pathway

Mucosal surfaces are the primary point of entry for many infectious agents and mucosal immune responses serve as the primary defense to these pathogens. In order to mount an effective mucosal immune response, it is important to induce T cell homing to mucosal surfaces. Conventional vaccine adjuvants induce strong systemic immunity but often fail to produce mucosal immunity. We have developed an oil-in-water nanoemulsion (NE) adjuvant that provides mucosal immunity and efficient protection against mucosal pathogens when administered as part of an intranasal vaccine. In the present study, we demonstrate that intranasal immunization with NE indirectly activates the retinaldehyde dehydrogenase (RALDH) activity in dendritic cells through epithelial cell activity leading to SIgA as well as potent cellular responses and expression of α4β7 and CCR9 gut homing receptors on T cells. Confirming these findings, ex-vivo stimulation of splenocytes from NE nasally immunized animals showed increase in Th1/Th17 cytokines while suppressing Th2 responses. In examining mechanisms underlying this activation NE activated RALDH via MyD88 dependent pathways in DCs but did not activate the retinoic acid receptor directly. These results suggest that RALDH immune activities can be achieved by epithelial activation without direct RAR activation, which has significant implications for understanding mucosal immunity and the design of mucosal vaccines

Introducing v0.5 of the AI Safety Benchmark from MLCommons

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark

183 A phase 1B/2A trial of tofacitinib, an oral janus kinase inhibitor, in systemic lupus erythematosus

n/

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic