Peripheral Linker Mediates Acyl Carrier Protein's Recognition of Dehydratase and Stabilizes Type-I Mycobacterium tuberculosis Fatty Acid Synthase.

Incomplete structural details of Mycobacterium tuberculosis (Mtb) fatty acid synthase-I (FAS-I) at near-atomic resolution have limited our understanding of the shuttling mechanism of its mobile acyl carrier protein (ACP). Here, we have performed atomistic molecular dynamics simulation of Mtb FAS-I with a homology-modeled structure of ACP stalled at dehydratase (DH) and identified key residues that mediate anchoring of the recognition helix of ACP near DH. The observed distance between catalytic residues of ACP and DH agrees with that reported for fungal FAS-I. Further, the conformation of the peripheral linker is found to be crucial in stabilizing ACP near DH. Correlated interdomain motion is observed between DH, enoyl reductase, and malonyl/palmitoyl transferase, consistent with prior experimental reports of fungal and Mtb FAS-I.

Temporal change in prevalence of BMI categories in India: patterns across States and Union territories of India, 1999-2021.

BACKGROUND: The problem of overweight/obesity often coexists with the burden of undernutrition in most low- and middle-income countries. BMI change in India incorporating the most recent trends has been under-researched. METHODS: This repeated cross-sectional study of 1,477,885 adults in India analyzed the prevalence of different categories of BMI among adults (age 20-54) in 4 rounds of National Family Health Surveys (1998-1999, 2005-2006, 2015-2016, and 2019-2021) for 36 states/UTs. State differences across time were harmonized for accurate analysis. The categories were Severely/Moderately Thin (BMI < 17.0), Mildly Thin (17.0-18.4), Normal (18.5-24.9), Overweight (25.0-29.9), and Obese (≥ 30.0). We also estimated change in Standardized Absolute Change (SAC), ranking of states, and headcount burden to quantify the trend of BMI distribution across time periods for all-India, urban/rural residence, and by states/UTs. RESULTS: The prevalence of thinness declined from 31.7% in 1999 to 14.2% in 2021 for women, and from 23.4% in 2006 to 10.0% in 2021 for men. Obesity prevalence increased from 2.9% (1999) to 6.3% (2021) for women, and from 2.0% (2006) to 4.2% (2021) for men. In 2021, the states with the highest obesity prevalence were Puducherry, Chandigarh, and Delhi. These states also had a high prevalence of overweight. Dadra and Nagar Haveli and Diu, Gujarat, Jharkhand, and Bihar had the highest prevalence of severe/moderately thin. Prevalence of extreme categories (severely/moderately thin and obese) was larger in the case of women than men. While States/UTs with a higher prevalence of thin populations tend to have a larger absolute burden of severe or moderate thinness, the relationship between headcount burden and prevalence for overweight and obese is unclear. CONCLUSIONS: We found persistent interstate inequalities of undernutrition. Tailored efforts at state levels are required to further strengthen existing policies and develop new interventions to target both forms of malnutrition.

Trends in prevalence of unmet need for family planning in India: patterns of change across 36 States and Union Territories, 1993-2021.

BACKGROUND: Eliminating unmet need for family planning by 2030 is a global priority for ensuring healthy lives and promoting well-being for all at all ages. We estimate the sub-national trends in prevalence of unmet need for family planning over 30 years in India and study differences based on socio-economic and demographic factors. METHODS: We used data from five National Family Health Surveys (NFHS) conducted between 1993 to 2021 for the 36 states/Union Territories (UTs) of India. The study population included women of ages 15-49 years who were married or in a union at the time of the survey. The outcome was unmet need for family planning which captures the prevalence of fecund and sexually active women not using contraception, who want to delay or limit childbearing. We calculated the standardized absolute change to estimate the change in prevalence on an annual basis across all states/UTs. We examined the patterning of prevalence of across demographic and socioeconomic characteristics and estimated the headcount of women with unmet need in 2021. RESULTS: The prevalence of unmet need in India decreased from 20·6% (95% CI: 20·1- 21·2%) in 1993, to 9·4% (95% CI: 9·3-9·6%) in 2021. Median unmet need prevalence across states/UTs decreased from 17·80% in 1993 to 8·95% in 2021. The north-eastern states of Meghalaya (26·9%, 95% CI: 25·3-28·6%) and Mizoram (18·9%, 95% CI: 17·2-20·6%), followed by the northern states of Bihar (13·6%, 95% CI: 13·1-14·1%) and Uttar Pradesh (12·9%, 95% CI: 12·5-13·2%), had the highest unmet need prevalence in 2021. As of 2021, the estimated number of women with an unmet need for family planning was 24,194,428. Uttar Pradesh, Bihar, Maharashtra, and West Bengal accounted for half of this headcount. Women of ages 15-19 and those belonging the poorest wealth quintile had a relatively high prevalence of unmet need in 2021. CONCLUSIONS: The existing initiatives under the National Family Planning Programme should be strengthened, and new policies should be developed with a focus on states/UTs with high prevalence, to ensure unmet need for family planning is eliminated by 2030.

This study looked at the trends in unmet need for family planning in India, which is defined as the percentage of women of reproductive age who want to delay or limit childbearing but are not using any contraceptive method. A public dataset was used to analyze national and sub-national trends from 1993 to 2021. It was determined that although the percentage prevalence of unmet need decreased in the last 30 years, there were still a substantial number of women with unmet need in 2021. More than half of these women were in Uttar Pradesh, Bihar, Maharashtra, and West Bengal. Furthermore, it was found that percentage prevalence of unmet need was relatively higher amongst younger women and those belonging to poorer households in 2021. Initiatives and policies aimed at reducing unmet need for family planning should be implemented while considering geographic, socioeconomic, and demographic differences.

Synergistic Antibacterial Activity of Gallic Acid Based Chalcone Indl 2 by Inhibiting Efflux Pump Transporters.

As a part of novel discovery of drugs from natural resources, present study was undertaken to explore the antibacterial potential of chalcone Indl-2 in combination with different group of antibiotics. MIC of antibiotics was reduced up to eight folds against the different cultures of E. coli by both chalcones. Among the two compounds, the i. e. 1-(3', 4,'5'-trimethoxyphenyl)-3-(3-Indyl)-prop-2-enone (6, Indl-2), a chalcone derivative of gallic acid (Indl-2) was better along with tetracycline (TET) worked synergistically and was found to inhibit efflux transporters as obvious by ethidium bromide efflux confirmed by ATPase assays and docking studies. In combination, Indl-2 kills the MDREC-KG4 cells, post-antibiotic effect (PAE) of TET was prolonged and mutant prevention concentration (MPC) of TET was also decreased. In-vivo studies revealed that Indl-2 reduces the concentration of TNF-α. In acute oral toxicity study, Indl-2 was non-toxic and well tolerated up-to dose of 2000 mg/kg. Perhaps, the study is going to report gallic acid derived chalcone as synergistic agent acting via inhibiting the primary efflux pumps.

The Slowing Rate of CpG Depletion in SARS-CoV-2 Genomes Is Consistent with Adaptations to the Human Host.

Depletion of CpG dinucleotides in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genomes has been linked to virus evolution, host-switching, virus replication, and innate immune responses. Temporal variations, if any, in the rate of CpG depletion during virus evolution in the host remain poorly understood. Here, we analyzed the CpG content of over 1.4 million full-length SARS-CoV-2 genomes representing over 170 million documented infections during the first 17 months of the pandemic. Our findings suggest that the extent of CpG depletion in SARS-CoV-2 genomes is modest. Interestingly, the rate of CpG depletion is highest during early evolution in humans and it gradually tapers off, almost reaching an equilibrium; this is consistent with adaptations to the human host. Furthermore, within the coding regions, CpG depletion occurs predominantly at codon positions 2-3 and 3-1. Loss of ZAP (Zinc-finger antiviral protein)-binding motifs in SARS-CoV-2 genomes is primarily driven by the loss of the terminal CpG within the motifs. Nonetheless, majority of the CpG depletion in SARS-CoV-2 genomes occurs outside ZAP-binding motifs. SARS-CoV-2 genomes selectively lose CpGs-motifs from a U-rich context; this may help avoid immune recognition by TLR7. SARS-CoV-2 alpha-, beta-, and delta-variants of concern have reduced CpG content compared to sequences from the beginning of the pandemic. In sum, we provide evidence that the rate of CpG depletion in virus genomes is not uniform and it greatly varies over time and during adaptations to the host. This work highlights how temporal variations in selection pressures during virus adaption may impact the rate and the extent of CpG depletion in virus genomes.

ETL-YOLO v4: A face mask detection algorithm in era of COVID-19 pandemic.

During the last two years, several deep learning-based methods for face mask detection have been proposed by researchers. However, most of the proposed methods struggle with the detection of face masks that are too small an object to detect and further achieve low detection accuracy. Considering the issues of the existing methods, in this work, we have proposed ETL-YOLO v4 with a modified and improved feature extraction and prediction network for tiny YOLO v4 which surpasses all its predecessors and other related work in the literature. To develop ETL-YOLO v4, we have improved the backbone architecture of tiny YOLO v4 by adding a modified-dense SPP network, two additional detection layers with modified and optimized CNN layers that aid in accurate prediction, used Mish as the activation function, and utilized modified anchor boxes. Furthermore, to obtain detection results in images of varied viewpoints, we have added Mosaic and CutMix data augmentation at training time. The proposed ETL-YOLO v4 achieved 9.93% higher mAP, 5.75% higher average precision (AP) for faces with masks, and 16.6% higher average precision (AP) for the face mask region as compared to its original base-line variant.

Anaesthesia for tracheal resection and anastomosis.

Tracheal resection anastomosis is one of the most challenging surgeries. Notable advances in this field have made possible a variety of surgical, anesthetic, and airway management options. There are reports of newer approaches ranging from use of supraglottic airway devices, regional anesthesia, and extracorporeal support. Endotracheal intubation with cross-field ventilation and jet ventilation are the standard techniques for airway management followed. These call for multidisciplinary preoperative planning and close communication during surgery and recovery. This review highlights the anesthetic challenges faced during tracheal resection and anastomosis with specific considerations to preoperative workup, classification of tracheal stenosis, airway management, ventilation strategies, and extubation. The newer advances proposed have been reviewed.

Correction: Association Between Institutional Social Media Involvement and Gastroenterology Divisional Rankings: Cohort Study.

[This corrects the article DOI: 10.2196/13345.].

Association Between Institutional Social Media Involvement and Gastroenterology Divisional Rankings: Cohort Study.

BACKGROUND: Patients often look to social media as an important tool to gather information about institutions and professionals. Since 1990, United States News and World Report (USNWR) has published annual rankings of hospitals and subspecialty divisions. It remains unknown if social media presence is associated with the USNWR gastroenterology and gastrointestinal (GI) surgery divisional rankings, or how changes in online presence over time affects division ranking. OBJECTIVE: The objective of this study was to determine if social media presence is associated with USNWR gastroenterology and GI surgery divisional rankings and to ascertain how changes in online presence over time affect division rankings. METHODS: Social media presence among the top 30 institutions listed in the 2014 USNWR gastroenterology and GI surgery divisional rankings were assessed using Pearson's correlation coefficients and multivariate analysis, controlling for covariates. Linear and logistic regression using data from 2014 and 2016 USNWR rankings were then used to assess the association between institutional ranking or reputation score with any potential changes in numbers of followers over time. Sensitivity analysis was performed by assessing the area under the receiver operating characteristic curve to determine the follower threshold associated with improved or maintained ranking, which was done by dichotomizing changes in followers at values between the 7000 and 12,000 follower mark. RESULTS: Twitter follower count was an independent predictor of divisional ranking (ß=.00004; P<.001) and reputation score (ß=-.00002; P=.03) in 2014. Academic affiliation also independently predicted USNWR division ranking (ß=5.3; P=.04) and reputation score (ß=-7.3; P=.03). Between 2014 and 2016, Twitter followers remained significantly associated with improved or maintained rankings (OR 14.63; 95% CI 1.08-197.81; P=.04). On sensitivity analysis, an 8000 person increase in Twitter followers significantly predicted improved or maintained rankings compared to other cutoffs. CONCLUSIONS: Institutional social media presence is independently associated with USNWR divisional ranking and reputation score. Improvement in social media following was also independently associated with improved or maintained divisional ranking and reputation score, with a threshold of 8000 additional followers as the best predictor of improved or stable ranking.

Intraoperative partial pressure of oxygen measurement to predict flap survival.

INTRODUCTION: Flap monitoring using partial pressure of oxygen (pO2) is a proven modality. Instruments needed are expensive and are not readily available to a clinician. Here, pO2 of flap has been determined using readily available and cheap methods, and a cut-off value is calculated which helps in predicting flap outcome. METHODS AND RESULTS: Total 235 points on 84 skin flaps were studied. Capillary blood was collected from flap and fingertip using 1-ml syringes after at least 30 min of flap inset, and pO2 analysed using blood gas analyser. Fall/change of pO2 (difference of mean of pO2 [diff-pO2]) was also calculated by subtracting the flap pO2 from the finger pO2. Flap was monitored clinically in post-operative period and divided into two groups depending on its survival with Group 1 - dead points and Group 2 - alive points. pO2 and diff-pO2 amongst both the groups were compared and found to be statistically different (P = 0.0001). Cut-off value calculated for pO2 was found to be <86.3 mmHg with a sensitivity of 100% and specificity of 89.05%. The difference of >68.503 mmHg of flap pO2 compared from finger pO2 was calculated as a cut-off with sensitivity of 94.12 and specificity of 79.60%. CONCLUSIONS: Flap areas having intra-operative pO2 value <86.3 mmHG have higher chances (60.71%) of getting necrosis later. Similarly, if diff-pO2 compared to fingertip is >68.5 mmHg, chances of those points getting necrosed in post-operative period are high.

Virtual screening, ADMET profiling, molecular docking and dynamics approaches to search for potent selective natural molecules based inhibitors against metallothionein-III to study Alzheimer's disease.

MOTIVATION: Metallothionein-III (MT-III) displays neuro-inhibitory activity and is involved in the repair of neuronal damage. An altered expression level of MT-III suggests that it could be a mitigating factor in Alzheimer's disease (AD) neuronal dysfunction. Currently there are limited marketed drugs available against MT-III. The inhibitors are mostly pseudo-peptide based with limited ADMET. In our present study, available database InterBioScreen (natural compounds) was screened out for MT-III. Pharmacodynamics and pharmacokinetic studies were performed. Molecular docking and simulations of top hit molecules were performed to study complex stability. RESULTS: Study reveals potent selective molecules that interact and form hydrogen bonds with amino acids Ser-6 and Lys-22 are common to established melatonin inhibitors for MT-III. These include DMHMIO, MCA B and s27533 derivatives. The ADMET profiling was better with comparable interaction energy values. It includes properties like blood brain barrier, hepatotoxicity, druggability, mutagenicity and carcinogenicity. Molecular dynamics studies were performed to validate our findings.

Gallic acid-based indanone derivative interacts synergistically with tetracycline by inhibiting efflux pump in multidrug resistant E. coli.

The purpose of the present study was to study the synergy potential of gallic acid-based derivatives in combination with conventional antibiotics using multidrug resistant cultures of Escherichia coli. Gallic acid-based derivatives significantly reduced the MIC of tetracycline against multidrug resistant clinical isolate of E. coli. The best representative, 3-(3',4,'5'-trimethoxyphenyl)-4,5,6-trimethoxyindanone-1, an indanone derivative of gallic acid, was observed to inhibit ethidium bromide efflux and ATPase which was also supported by in silico docking. This derivative extended the post-antibiotic effect and decreased the mutation prevention concentration of tetracycline. This derivative in combination with TET was able to reduce the concentration of TNFα up to 18-fold in Swiss albino mice. This derivative was nontoxic and well tolerated up to 300 mg/kg dose in subacute oral toxicity study in mice. This is the first report of gallic acid-based indanone derivative as drug resistance reversal agent acting through ATP-dependent efflux pump inhibition.

Assessing the metabolic impact of nitrogen availability using a compartmentalized maize leaf genome-scale model.

Maize (Zea mays) is an important C4 plant due to its widespread use as a cereal and energy crop. A second-generation genome-scale metabolic model for the maize leaf was created to capture C4 carbon fixation and investigate nitrogen (N) assimilation by modeling the interactions between the bundle sheath and mesophyll cells. The model contains gene-protein-reaction relationships, elemental and charge-balanced reactions, and incorporates experimental evidence pertaining to the biomass composition, compartmentalization, and flux constraints. Condition-specific biomass descriptions were introduced that account for amino acids, fatty acids, soluble sugars, proteins, chlorophyll, lignocellulose, and nucleic acids as experimentally measured biomass constituents. Compartmentalization of the model is based on proteomic/transcriptomic data and literature evidence. With the incorporation of information from the MetaCrop and MaizeCyc databases, this updated model spans 5,824 genes, 8,525 reactions, and 9,153 metabolites, an increase of approximately 4 times the size of the earlier iRS1563 model. Transcriptomic and proteomic data have also been used to introduce regulatory constraints in the model to simulate an N-limited condition and mutants deficient in glutamine synthetase, gln1-3 and gln1-4. Model-predicted results achieved 90% accuracy when comparing the wild type grown under an N-complete condition with the wild type grown under an N-deficient condition.

CLCA: maximum common molecular substructure queries within the MetRxn database.

The challenge of automatically identifying the preserved molecular moieties in a chemical reaction is referred to as the atom mapping problem. Reaction atom maps provide the ability to locate the fate of individual atoms across an entire metabolic network. Atom maps are used to track atoms in isotope labeling experiments for metabolic flux elucidation, trace novel biosynthetic routes to a target compound, and contrast entire pathways for structural homology. However, rapid computation of the reaction atom mappings remains elusive despite significant research. We present a novel substructure search algorithm, canonical labeling for clique approximation (CLCA), with polynomial run-time complexity to quickly generate atom maps for all the reactions present in MetRxn. CLCA uses number theory (i.e., prime factorization) to generate canonical labels or unique IDs and identify a bijection between the vertices (atoms) of two distinct molecular graphs. CLCA utilizes molecular graphs generated by combining atomistic information on reactions and metabolites from 112 metabolic models and 8 metabolic databases. CLCA offers improvements in run time, accuracy, and memory utilization over existing heuristic and combinatorial maximum common substructure (MCS) search algorithms. We provide detailed examples on the various advantages as well as failure modes of CLCA over existing algorithms.

Prevalence of girl and boy child marriage across states and Union Territories in India, 1993-2021: a repeated cross-sectional study.

BACKGROUND: India's success in eliminating child marriage is crucial to the achievement of the Sustainable Development Goal target 5.3. We aimed to estimate the prevalence of child marriage in girls and boys in India and describe its change across 36 states and Union Territories between 1993 and 2021. METHODS: For this cross-sectional study, data from five National Family Health Surveys from 1993, 1999, 2006, 2016, and 2021 were used. The study included 310 721 women aged 20-24 years between 1993 and 2021 and 43 436 men aged 20-24 years between 2006 and 2021. Child marriage was defined as marriage in individuals younger than 18 years for men and women. We calculated the annual change in prevalence during the study period for states and Union Territories and estimated the population headcount of child brides and grooms. FINDINGS: Child marriage declined during 1993 to 2021. The all-India prevalence of child marriage in girls declined from 49·4% (95% CI 48·1-50·8) in 1993 to 22·3% (21·9-22·7) in 2021. Child marriage in boys declined from 7·1% (6·9-30·8) in 2006 to 2·2% (1·8-2·7) in 2021. The largest decreases in child marriage occurred between 2006 and 2016. Between 2016 and 2021, a few states and Union Territories saw an increase in prevalence of child marriage in girls (n=6) and boys (n=8) despite declines in the all-India prevalence. In 2021, 13 464 450 women aged 20-24 years and 1 454 894 men aged 20-24 years were estimated to be married as children. INTERPRETATION: One in five girls and nearly one in six boys are still married below the legal age of marriage in India. There remains an urgent need for strengthened national and state-level policy to eliminate child marriage by 2030. FUNDING: Bill & Melinda Gates Foundation.

Early-Neonatal, Late-Neonatal, Postneonatal, and Child Mortality Rates Across India, 1993-2021.

Importance: The global success of the child survival agenda depends on how rapidly mortality at early ages after birth declines in India, and changes need to be monitored to evaluate the status. Objective: To understand the disaggregated patterns of decrease in early-life mortality across states and union territories (UTs) of India. Design, Setting, and Participants: Repeated cross-sectional data from the 5 rounds of the National Family Health Survey conducted in 1992-1993, 1998-1999, 2005-2006, 2015-2016, and 2019-2021 were used in a representative population-based study. The study was based on data of children born in the past 5 years with complete information on date of birth and age at death. The analysis was conducted in February 2024. Exposure: Time and geographic units. Main Outcomes and Measures: Mortality rates were computed for 4 early-life periods: early-neonatal (first 7 days), late-neonatal (8-28 days), postneonatal (29 days to 11 months), and child (12-59 months). For early and late neonatal periods, the rates are expressed as deaths per 1000 live births, for postneonatal, as deaths per 1000 children aged at least 29 days and for child, deaths per 1000 children aged at least 1 year. These are collectively mentioned as deaths per 1000 for all mortalities. The relative burden of each of the age-specific mortalities to total mortality in children younger than 5 years was also computed. Results: The final analytical sample included 33 667 (1993), 29 549 (1999), 23 020 (2006), 82 294 (2016), and 64 242 (2021) children who died before their fifth birthday in the past 5 years of each survey. Mortality rates were lowest for the late-neonatal and child periods; early-neonatal was the highest in 2021. Child mortality experienced the most substantial decrease between 1993 and 2021, from 33.5 to 6.9 deaths per 1000, accompanied by a substantial reduction in interstate inequalities. While early-neonatal (from 33.5 to 20.3 deaths per 1000), late-neonatal (from 14.1 to 4.1 deaths per 1000), and postneonatal (from 31.0 to 10.8 deaths per 1000) mortality also decreased, interstate inequalities remained notable. The mortality burden shifted over time and is now concentrated during the early-neonatal (48.3% of total deaths in children younger than 5 years) and postneonatal (25.6%) periods. A stagnation or worsening for certain states and UTs was observed from 2016 to 2021 for early-neonatal, late-neonatal, and postneonatal mortality. If this pattern continues, these states and UTs will not meet the United Nations Sustainable Development Goal targets related to child survival. Conclusions and Relevance: In this repeated cross-sectional study of 5 time periods, the decrease in mortality during early-neonatal and postneonatal phases of mortality was relatively slower, with notable variations across states and UTs. The findings suggest that policies pertaining to early-neonatal and postneonatal mortalities need to be prioritized and targeting of policies and interventions needs to be context-specific.

SAM C-GAN: a method for removal of face masks from masked faces.

The past years of COVID-19 have attracted researchers to carry out benchmark work in face mask detection. However, the existing work does not focus on the problem of reconstructing the face area behind the mask and completing the face that can be used for face recognition. In order to address this problem, in this work we have proposed a spatial attention module-based conditional generative adversarial network method that can generate plausible images of faces without masks by removing the face masks from the face region. The method proposed in this work utilizes a self-created dataset consisting of faces with three types of face masks for training and testing purposes. With the proposed method, an SSIM value of 0.91231 which is 3.89% higher and a PSNR value of 30.9879 which is 3.17% higher has been obtained as compared to the vanilla C-GAN method.