Volkov solutions for relativistic magnetized plasma in strong field quantum electrodynamics regime

This study shows the dynamics of relativistic electrons in terms of Dirac equation solutions when an ultra-intense short laser pulse of intensity $\ge 10^{23} {W.cm^{-2}}$ propagates through magnetized dense plasma ($B_0\approx {1MG})$. The interaction dynamics is analyzed near the strong-field quantum electrodynamics (SF-QED) regime. Our study finds new solutions in plasma media considering the effects of the re-normalized mass of relativistic electrons and the nonzero effective mass of accelerated photons. We have provided a general method for constructing exact solutions of the Dirac relativistic equation that correctly explains the dynamics of electrons in the strongly magnetized plasma medium. The modified solutions of the Dirac equation for one electron are derived and compared to the Volkov solutions. The new solutions are a basis for a feasible explanation of quantum attributes of relativistic electrons in a strong electromagnetic field of very short ultra-intense laser pulses with intensity near Schwinger field intensity. The solutions are called new Volkov solutions in a plasma medium. These solutions can be used to understand better the theory of quantum radiation reaction for the next-generation laser-plasma accelerator. Our results show that the Volkov solutions are not applicable in a magnetized plasma mediumComment: 14 pages,zero figure, journal articl

Understanding Antibiotic Usage on Small-Scale Dairy Farms in the Indian States of Assam and Haryana Using a Mixed-Methods Approach-Outcomes and Challenges

The use and misuse of antibiotics in both humans and animals contributes to the global emergence of antimicrobial resistant (AMR) bacteria, a threat to public health and infection control. Currently, India is the world's leading milk producer but antibiotic usage within the dairy sector is poorly regulated. Little data exists reflecting how antibiotics are used on dairy farms, especially on small-scale dairy farms in India. To address this lack of data, a study was carried out on 491 small-scale dairy farms in two Indian states, Assam and Haryana, using a mixed method approach where farmers were interviewed, farms inspected for the presence of antibiotics and milk samples taken to determine antibiotic usage. Usage of antibiotics on farms appeared low only 10% (95% CI 8-13%) of farmers surveyed confirmed using antibiotics in their dairy herds during the last 12 months. Of the farms surveyed, only 8% (6-11%) had milk samples positive for antibiotic residues, namely from the novobiocin, macrolides, and sulphonamide classes of antibiotics. Of the farmers surveyed, only 2% (0.8-3%) had heard of the term "withdrawal period" and 53% (40-65%) failed to describe the term "antibiotic". While this study clearly highlights a lack of understanding of antibiotics among small-scale dairy farmers, a potential factor in the emergence of AMR bacteria, it also shows that antibiotic usage on these farms is low and that the possible role these farmers play in AMR emergence may be overestimated

Antibiotic use, knowledge, and practices of milk vendors in India's informal dairy value chain

BackgroundMilk vendors play an important role in India's dairy value chain; however, their food safety practices are poorly understood. From a milk safety perspective, vendor behavior is significant because it has the potential to affect both consumer and producer behavior. This study describes the types of milk vendors in two Indian states, in an attempt to investigate vendors' hygienic knowledge and practices toward safety and antimicrobial resistance (AMR). MethodsA cross-sectional study was conducted in the states of Assam and Haryana, India. In selected villages, all the milk vendors identified at the time of visit were interviewed. A questionnaire was used to assess the knowledge and practices on antibiotics, milk safety and hygiene. The milk samples were tested for presence of antibiotic resistant bacteria using antibiotic susceptibility testing. ResultsIn total, 244 milk vendors were interviewed during the survey. Out of these, 146 (59.8%) of the vendors traded raw milk, while 40.2% traded pasteurized milk. Vendors were categorized depending on whom they supplied milk to. Five categories were identified: (a) those who sold at grocery shops; (b) those who sold on roadside (roadside vendors); (c) those who sold from door to door; (d) those who sold to sweet makers/tea stalls, and (e) those who sold from own home/other entity. The level of training among vendors on milk hygiene was non-existent and the knowledge related to antibiotics was low. Most of them [210/244 (86.07%)] agreed that boiled milk is always safer than raw milk but almost half [119 (48.77%)] of them admitted that sometimes they drink milk without boiling it. Most vendors believed that they could identify whether milk is safe or not for consumption just by its appearance and smell. Out of 124 milk samples collected from surveyed milk vendors and tested for the presence of antibiotic-resistant bacteria, 80 (64.52%) were tested positive. ConclusionThis study highlights the low levels of knowledge regarding food safety among milk vendors. It shows the predominance of informal milk vendors in the surveyed states and prevalence of AMR bacteria in milk traded by them. Training may be a beneficial strategy for addressing the issue

Acetylome of acinetobacter baumannii SK17 reveals a highly-conserved modification of histone-like protein HU

Lysine acetylation is a prevalent post-translational modification in both eukaryotes and prokaryotes. Whereas this modification is known to play pivotal roles in eukaryotes, the function and extent of this modification in prokaryotic cells remain largely unexplored. Here we report the acetylome of a pair of antibiotic-sensitive and -resistant nosocomial pathogen Acinetobacter baumannii SK17-S and SK17-R. A total of 145 lysine acetylation sites on 125 proteins was identified, and there are 23 acetylated proteins found in both strains, including histone-like protein HU which was found to be acetylated at Lys13. HU is a dimeric DNA-binding protein critical for maintaining chromosomal architecture and other DNA-dependent functions. To analyze the effects of site-specific acetylation, homogenously Lys13-acetylated HU protein, HU(K13ac) was prepared by genetic code expansion. Whilst not exerting an obvious effect on the oligomeric state, Lys13 acetylation alters both the thermal stability and DNA binding kinetics of HU. Accordingly, this modification likely destabilizes the chromosome structure and regulates bacterial gene transcription. This work indicates that acetyllysine plays an important role in bacterial epigenetics

Leveraging Genomic Associations in Precision Digital Care for Weight Loss: Cohort Study

Background: The COVID-19 pandemic has highlighted the urgency of addressing an epidemic of obesity and associated inflammatory illnesses. Previous studies have demonstrated that interactions between single-nucleotide polymorphisms (SNPs) and lifestyle interventions such as food and exercise may vary metabolic outcomes, contributing to obesity. However, there is a paucity of research relating outcomes from digital therapeutics to the inclusion of genetic data in care interventions. Objective: This study aims to describe and model the weight loss of participants enrolled in a precision digital weight loss program informed by the machine learning analysis of their data, including genomic data. It was hypothesized that weight loss models would exhibit a better fit when incorporating genomic data versus demographic and engagement variables alone. Methods: A cohort of 393 participants enrolled in Digbi Health’s personalized digital care program for 120 days was analyzed retrospectively. The care protocol used participant data to inform precision coaching by mobile app and personal coach. Linear regression models were fit of weight loss (pounds lost and percentage lost) as a function of demographic and behavioral engagement variables. Genomic-enhanced models were built by adding 197 SNPs from participant genomic data as predictors and refitted using Lasso regression on SNPs for variable selection. Success or failure logistic regression models were also fit with and without genomic data. Results: Overall, 72.0% (n=283) of the 393 participants in this cohort lost weight, whereas 17.3% (n=68) maintained stable weight. A total of 142 participants lost 5% bodyweight within 120 days. Models described the impact of demographic and clinical factors, behavioral engagement, and genomic risk on weight loss. Incorporating genomic predictors improved the mean squared error of weight loss models (pounds lost and percent) from 70 to 60 and 16 to 13, respectively. The logistic model improved the pseudo R 2 value from 0.193 to 0.285. Gender, engagement, and specific SNPs were significantly associated with weight loss. SNPs within genes involved in metabolic pathways processing food and regulating fat storage were associated with weight loss in this cohort: rs17300539_G (insulin resistance and monounsaturated fat metabolism), rs2016520_C (BMI, waist circumference, and cholesterol metabolism), and rs4074995_A (calcium-potassium transport and serum calcium levels). The models described greater average weight loss for participants with more risk alleles. Notably, coaching for dietary modification was personalized to these genetic risks. Conclusions: Including genomic information when modeling outcomes of a digital precision weight loss program greatly enhanced the model accuracy. Interpretable weight loss models indicated the efficacy of coaching informed by participants’ genomic risk, accompanied by active engagement of participants in their own success. Although large-scale validation is needed, our study preliminarily supports precision dietary interventions for weight loss using genetic risk, with digitally delivered recommendations alongside health coaching to improve intervention efficac

Antibiotic use, knowledge, and practices of milk vendors in India's informal dairy value chain

Background: Milk vendors play an important role in India's dairy value chain; however, their food safety practices are poorly understood. From a milk safety perspective, vendor behavior is significant because it has the potential to affect both consumer and producer behavior. This study describes the types of milk vendors in two Indian states, in an attempt to investigate vendors' hygienic knowledge and practices toward safety and antimicrobial resistance (AMR). Methods: A cross-sectional study was conducted in the states of Assam and Haryana, India. In selected villages, all the milk vendors identified at the time of visit were interviewed. A questionnaire was used to assess the knowledge and practices on antibiotics, milk safety and hygiene. The milk samples were tested for presence of antibiotic resistant bacteria using antibiotic susceptibility testing. Results: In total, 244 milk vendors were interviewed during the survey. Out of these, 146 (59.8%) of the vendors traded raw milk, while 40.2% traded pasteurized milk. Vendors were categorized depending on whom they supplied milk to. Five categories were identified: (a) those who sold at grocery shops; (b) those who sold on roadside (roadside vendors); (c) those who sold from door to door; (d) those who sold to sweet makers/tea stalls, and (e) those who sold from own home/other entity. The level of training among vendors on milk hygiene was non-existent and the knowledge related to antibiotics was low. Most of them [210/244 (86.07%)] agreed that boiled milk is always safer than raw milk but almost half [119 (48.77%)] of them admitted that sometimes they drink milk without boiling it. Most vendors believed that they could identify whether milk is safe or not for consumption just by its appearance and smell. Out of 124 milk samples collected from surveyed milk vendors and tested for the presence of antibiotic-resistant bacteria, 80 (64.52%) were tested positive. Conclusion: This study highlights the low levels of knowledge regarding food safety among milk vendors. It shows the predominance of informal milk vendors in the surveyed states and prevalence of AMR bacteria in milk traded by them. Training may be a beneficial strategy for addressing the issue

Molecular Characterization of Methicillin-Resistant Staphylococci from the Dairy Value Chain in Two Indian States

Bovine milk and milk products may contain pathogens, antimicrobial resistant bacteria, and antibiotic residues that could harm consumers. We analyzed 282 gram-positive isolates from milk samples from dairy farmers and vendors in Haryana and Assam, India, to assess the prevalence of methicillin-resistant staphylococci using microbiological tests, antibiotic susceptibility testing, and genotyping by PCR. The prevalence of genotypic methicillin resistance in isolates from raw milk samples was 5% [95% confidence interval, CI (3–8)], with 7% [CI (3–10)] in Haryana, in contrast to 2% [CI (0.2–6)] in Assam. The prevalence was the same in isolates from milk samples collected from farmers [5% (n = 6), CI (2–11)] and vendors [5% (n = 7), CI (2–10)]. Methicillin resistance was also observed in 15% of the isolates from pasteurized milk [(n = 3), CI (3–38)]. Two staphylococci harboring a novel mecC gene were identified for the first time in Indian dairy products. The only SCCmec type identified was Type V. The staphylococci with the mecA (n = 11) gene in raw milk were commonly resistant to oxacillin [92%, CI (59–100)] and cefoxitin [74%, CI (39–94)], while the isolates with mecC (n = 2) were resistant to oxacillin (100%) only. All the staphylococci with the mecA (n = 3) gene in pasteurized milk were resistant to both oxacillin and cefoxitin. Our results provided evidence that methicillin-resistant staphylococci occur in dairy products in India with potential public health implications. The state with more intensive dairy systems (Haryana) had higher levels of methicillin-resistant bacteria in milk

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions