Maternal genetic diversity and phylogenetic analysis of Indian riverine and swamp buffaloes: insights from complete mitochondrial genomes.

This study explored the genetic diversity and evolutionary history of riverine and swamp buffaloes in India, utilizing complete mitochondrial genome sequences. Through comprehensive sampling across varied agro-climatic zones, including 91 riverine buffaloes from 12 breeds and 6 non-descript populations, along with 16 swamp buffaloes of the Luit breed, this study employed next-generation sequencing techniques to map the mitogenomic landscape of these subspecies. Sequence alignments were performed with the buffalo mitochondrial reference genome to identify mitochondrial DNA (mtDNA) variations and distinct maternal haplogroups among Indian buffaloes. The results uncovered the existence of 212 variable sites in riverine buffaloes, yielding 67 haplotypes with high haplotype diversity (0.991), and in swamp buffaloes, 194 variable sites resulting in 12 haplotypes, displaying haplotype diversity of 0.950. Phylogenetic analyses elucidated the genetic relationships between Indian buffaloes and the recognized global haplogroups, categorizing Indian swamp buffaloes predominantly into the SA haplogroup. Intriguingly, the haplogroup SB2b was observed for the first time in swamp buffaloes. Conversely, riverine buffaloes conformed to established sub-haplogroups RB1, RB2, and RB3, underscoring the notion of Northwestern India as a pivotal domestication site for riverine buffaloes. The study supports the hypothesis of independent domestication events for riverine and swamp buffaloes, highlighting the critical role of genetic analysis in unraveling the complex evolutionary pathways of domestic animals. This investigation contributes to the global understanding of buffalo mitogenome diversity, offering insights into this important livestock species' domestication and dispersal patterns.

Prior Use of Angiotensin-converting Enzyme Inhibitors or Angiotensin II Receptor Blockers and Clinical Outcomes of Sepsis and Septic Shock: A Systematic Review and Meta-analysis.

ABSTRACT: Sepsis and septic shock are life-threatening conditions that are associated with high mortality and considerable health care costs. The association between prior angiotensin-converting enzyme inhibitors (ACEi) or angiotensin II receptor blockers (ARBs) use and outcomes after sepsis is elusive. The aim of this study was to evaluate the role of the prior use of ACEi or ARBs and outcomes after sepsis and septic shock. A relevant literature review was performed in 4 databases from inception until July 2022. Independent reviewers first screened the title, abstract, and full text, and then, data extraction and analysis were performed. One post hoc analysis of a trial and 6 retrospective cohort studies were included in this review. There were 22% lower odds of in-hospital/30-day mortality among patients who have used ACEi/ARBs in the past [23.83% vs. 37.20%; odds ratio (OR), 0.78, 95% confidence interval (CI), 0.64-0.96], and reduced 90-day mortality (OR, 0.80, 95% CI, 0.69-0.92). ACEi/ARBs users were found to have 31% lesser odds of developing acute kidney injury as compared with nonusers (OR, 0.69, 95% CI, 0.63-0.76). There was no significant difference in the length of hospital stay (MD 1.26, 95% CI, ‒7.89 to 10.42), need for renal replacement therapy (OR, 0.71, 95% CI, 0.13-3.92), mechanical ventilation (OR, 1.10, 95% CI, 0.88-1.37) or use of vasopressors (OR, 1.21, 95% CI, 0.91-1.61). Based on this analysis, prior use of ACEi/ARBs lowers the risk of mortality and adverse renal events in patients with sepsis and septic shock.

Satellite or ground-based measurements for air pollutants (PM2.5, PM10, SO2, NO2, O3) data and their health hazards: which is most accurate and why?

Air pollution is growing at alarming rates on regional and global levels, with significant consequences for human health, ecosystems, and change in climatic conditions. The present 12 weeks (4 October 2021, to 26 December 2021) study revealed the different ambient air quality parameters, i.e., PM2.5, PM10, SO2, NO2, and O3 over four different sampling stations of Delhi-NCR region (Dwarka, Knowledge park III, Sector 125, and Vivek Vihar), India, by using satellite remote sensing data (MERRA-2, OMI, and Aura Satellite) and different ground-based instruments. The ground-based observation revealed the mean concentration of PM2.5 in Dwarka, Knowledge park III, Sector 125, and Vivek Vihar as 279 µg m-3, 274 µg m-3, 294 µg m-3, and 365 µg m-3, respectively. The ground-based instrumental concentration of PM2.5 was greater than that of satellite observations, while as for SO2 and NO2, the mean concentration of satellite-based monitoring was higher as compared to other contaminants. Negative and positive correlations were observed among particulate matter, trace gases, and various meteorological parameters. The wind direction proved to be one of the prominent parameter to alter the variation of these pollutants. The current study provides a perception into an observable behavior of particulate matter, trace gases, their variation with meteorological parameters, their health hazards, and the gap between the measurements of satellite remote sensing and ground-based measurements.

Temporal dynamics of urban air pollutants and their correlation with associated meteorological parameters: an investigation in northern Indian cities.

This study delves into the intricate dynamics of air pollution in the rapidly expanding northern regions of India, examining the intertwined influences of agricultural burning, industrialization, and meteorological conditions. Through comprehensive analysis of key pollutants (PM2.5, PM10, NO2, SO2, CO, O3) across ten monitoring stations in Uttar Pradesh, Haryana, Delhi, and Punjab, a consistent pattern of high pollution levels emerges, particularly notable in Delhi. Varanasi leads in SO2 and O3 concentrations, while Moradabad stands out for CO levels, and Jalandhar for SO2 concentrations. The study further elucidates the regional distribution of pollutants, with Punjab receiving significant contributions from SW, SE, and NE directions, while Haryana and Delhi predominantly face air masses from SE and NE directions. Uttar Pradesh's pollution sources are primarily local, with additional inputs from various directions. Moreover, significant negative correlations (p < 0.05) between PM10, NO2, SO2, O3, and relative humidity (RH) underscore the pivotal role of meteorological factors in shaping pollutant levels. Strong positive correlations between PM2.5 and NO2 (0.71 to 0.93) suggest shared emission sources or similar atmospheric conditions in several cities. This comprehensive understanding highlights the urgent need for targeted mitigation strategies to address the multifaceted drivers of air pollution, ensuring the protection of public health and environmental sustainability across the region.

Brain Tumor Classification Using Deep Neural Network and Transfer Learning.

In the field of medical imaging, the classification of brain tumors based on histopathological analysis is a laborious and traditional approach. To address this issue, the use of deep learning techniques, specifically Convolutional Neural Networks (CNNs), has become a popular trend in research and development. Our proposed solution is a novel Convolutional Neural Network that leverages transfer learning to classify brain tumors in MRI images as benign or malignant with high accuracy. We evaluated the performance of our proposed model against several existing pre-trained networks, including Res-Net, Alex-Net, U-Net, and VGG-16. Our results showed a significant improvement in prediction accuracy, precision, recall, and F1-score, respectively, compared to the existing methods. Our proposed method achieved a benign and malignant classification accuracy of 99.30 and 98.40% using improved Res-Net 50. Our proposed system enhances image fusion quality and has the potential to aid in more accurate diagnoses.

Tracing the genetic footprints: India's role as a gateway for pig migration and domestication across continents.

This study explored the maternal genetic diversity in the pig genetic resources of India by analyzing a mitochondrial D-loop fragment and comparing it with the corresponding sequences of previously published studies involving domestic pigs and wild boars. Sequencing of 103 samples representing different domestic pig populations revealed existence of 32 maternal haplotypes. The indices of haplotype and nucleotide diversity in Indian domestic pigs were 0.9421 and 0.015, respectively. Median-Joining network revealed that Indian pigs belong to Clade A and show conformity to 6 haplogroups reported worldwide (D1a, D1a1, D1a2, D1e, D1h and D3a). Among these, D1e and D1a2 were shared with Asian wild boars too. Interestingly, haplotype sharing was evident between Indian pigs and samples from other countries representing Africa, Asia, Europe and Oceania. This study substantiates India's contribution as a possible pig domestication center and highlights the importance of the Indian subcontinent in dispersal of the species to other continents. Additionally, genetic evidence suggested the influence of trading routes and historical interactions in shaping pig genetic exchange. Overall, this investigation provides valuable insights into the genetic diversity, historical migration, and domestication of Indian domestic pigs, contributing to the broader understanding of global pig genetic resources and their evolutionary history.

A Novel Rabbit Model of Retained Hemothorax with Pleural Organization.

Retained hemothorax (RH) is a commonly encountered and potentially severe complication of intrapleural bleeding that can organize with lung restriction. Early surgical intervention and intrapleural fibrinolytic therapy have been advocated. However, the lack of a reliable, cost-effective model amenable to interventional testing has hampered our understanding of the role of pharmacological interventions in RH management. Here, we report the development of a new RH model in rabbits. RH was induced by sequential administration of up to three doses of recalcified citrated homologous rabbit donor blood plus thrombin via a chest tube. RH at 4, 7, and 10 days post-induction (RH4, RH7, and RH10, respectively) was characterized by clot retention, intrapleural organization, and increased pleural rind, similar to that of clinical RH. Clinical imaging techniques such as ultrasonography and computed tomography (CT) revealed the dynamic formation and resorption of intrapleural clots over time and the resulting lung restriction. RH7 and RH10 were evaluated in young (3 mo) animals of both sexes. The RH7 recapitulated the most clinically relevant RH attributes; therefore, we used this model further to evaluate the effect of age on RH development. Sanguineous pleural fluids (PFs) in the model were generally small and variably detected among different models. The rabbit model PFs exhibited a proinflammatory response reminiscent of human hemothorax PFs. Overall, RH7 results in the consistent formation of durable intrapleural clots, pleural adhesions, pleural thickening, and lung restriction. Protracted chest tube placement over 7 d was achieved, enabling direct intrapleural access for sampling and treatment. The model, particularly RH7, is amenable to testing new intrapleural pharmacologic interventions, including iterations of currently used empirically dosed agents or new candidates designed to safely and more effectively clear RH.

The role of LTBPs in TGF beta signaling.

The purpose of this review is to discuss the transforming growth factor beta (TGFB) binding proteins (LTBP) with respect to their participation in the activity of TGFB. We first describe pertinent aspects of the biology and cell function of the LTBPs. We then summarize the physiological consequences of LTBP loss in humans and mice. Finally, we consider a number of outstanding questions relating to LTBP function.

Wildfire-induced pollution and its short-term impact on COVID-19 cases and mortality in California.

Globally, wildfires have seen remarkable increase in duration and size and have become a health hazard. In addition to vegetation and habitat destruction, rapid release of smoke, dust and gaseous pollutants in the atmosphere contributes to its short and long-term detrimental effects. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has emerged as a public health concern worldwide that primarily target lungs and respiratory tract, akin to air pollutants. Studies from our lab and others have demonstrated association between air pollution and COVID-19 infection and mortality rates. However, current knowledge on the impact of wildfire-mediated sudden outburst of air pollutants on COVID-19 is limited. In this study, we examined the association of air pollutants and COVID-19 during wildfires burned during August-October 2020 in California, United States. We observed an increase in the tropospheric pollutants including aerosols (particulate matter [PM]), carbon monoxide (CO) and nitrogen dioxide (NO2) by approximately 150%, 100% and 20%, respectively, in 2020 compared to the 2019. Except ozone (O3), similar proportion of increment was noticed during the peak wildfire period (August 16 - September 15, 2020) in the ground PM2.5, CO, and NO2 levels at Fresno, Los Angeles, Sacramento, San Diego and San Francisco, cities with largest active wildfire area. We identified three different spikes in the concentrations of PM2.5, and CO for the cities examined clearly suggesting wildfire-induced surge in air pollution. Fresno and Sacramento showed increment in the ground PM2.5, CO and NO2 levels, while San Diego recorded highest change rate in NO2 levels. Interestingly, we observed a similar pattern of higher COVID-19 cases and mortalities in the cities with adverse air pollution caused by wildfires. These findings provide a logical rationale to strategize public health policies for future impact of COVID-19 on humans residing in geographic locations susceptible to sudden increase in local air pollution.

Role of Lactate Measurement in Flap Monitoring: An Useful Adjunct.

Background Detection of vascular compromise in flap is often a challenging task for reconstructive surgeons. A timely salvage procedure depends on objectivity and reliability of postoperative flap monitoring. This study determined if flap capillary lactate helps in prediction of flap viability in first 48 postoperative hours of surgery. Methods We conducted this study on all flaps with accessible skin paddle where capillary lactate values were assessed along with clinical observation to check viability of flap at 0, 1, 6, 12, 24 and 48 hours of surgery. The data was statistically analyzed for significance and area under the receiver operating characteristic curve was used for calculating cutoff value for lactate. Results Out of a total of 30 patients included in this study, 25 were males and the mean age was 45.03 years. Fifteen patients underwent free flap and rest pedicled. Highly significant association of role of clinical observation in the outcome of flap was found. The average of lactate values for survived and distally ischemic flap was 5.32 ± 1.91 and 8.38 ± 1.81, respectively, which was highly significant. The cutoff value of lactate below which all flaps survived was found to be 6.09 mmol/L. Conclusion Flap capillary lactate measurement is an easy, quick, cost-effective, and objective tool for checking viability of flaps.

Calponin 1 contributes to myofibroblast differentiation of human pleural mesothelial cells.

Pleural mesothelial cells (PMCs) can become myofibroblasts via mesothelial-mesenchymal transition (MesoMT) and contribute to pleural organization, fibrosis, and rind formation. However, how these transformed mesothelial cells contribute to lung fibrosis remains unclear. Here, we investigated the mechanism of contractile myofibroblast differentiation of PMCs. Transforming growth factor-ß (TGF-ß) induced marked upregulation of calponin 1 expression, which was correlated with notable cytoskeletal rearrangement in human PMCs (HPMCs) to produce stress fibers. Downregulation of calponin 1 expression reduced stress fiber formation. Interestingly, induced stress fibers predominantly contain α-smooth muscle actin (αSMA) associated with calponin 1 but not ß-actin. Calponin 1-associated stress fibers also contained myosin II and α-actinin. Furthermore, focal adhesions were aligned with the produced stress fibers. These results suggest that calponin 1 facilitates formation of stress fibers that resemble contractile myofibrils. Supporting this notion, TGF-ß significantly increased the contractile activity of HPMCs, an effect that was abolished by downregulation of calponin 1 expression. We infer that differentiation of HPMCs to contractile myofibroblasts facilitates stiffness of scar tissue in pleura to promote pleural fibrosis (PF) and that upregulation of calponin 1 plays a central role in this process.

Genetic characterization and diversity assessment in 'Bhangor' indigenous swamp buffalo population using heterologous microsatellite markers.

'Bhangor' newly identified swamp buffalo population from North East Indian, was characterized using microsatellite markers. Genomic DNA was isolated from blood samples of 76 unrelated animals, 15 microsatellite markers (CSSM33, BM1818, CSRM60, HEL13, ILSTS019, ILSTS025, ILSTS028, ILSTS029, ILSTS033, ILSTS036, ILSTS056, ILSTS058, ILSTS061, ILSTS089 and ETH003) were found to be highly polymorphic in the population of the selected markers. A total of 114 alleles were observed, which ranged from 3 in CSRM60 and ILSTS025 locus to 12 in ILSTS056 and ILSTS061. The mean effective number of alleles across all polymorphic loci was found to be 3.76. The overall mean expected heterozygosity and unbiased expected heterozygosity values were 0.67 and 0.68, ranging from 0.067 (ILSTS025) to 0.85 (ILSTS058) and 0.068 (ILSTS025) to 0.86 (ILSTS058), respectively. Within the population, the inbreeding estimates (FIS) ranged between -0.4352 and 0.804, with an average FIS of 0.114 ± 0.033. The outcome for infinite allele model (IAM), two-phase model (TPM) and test for mode shift revealed the absence of any recent bottleneck in the investigated buffalo population. The population was found to be in optimum diversity based on polymorphic microsatellite markers. With fast changing agro-climatic conditions; there is an urgent need to characterize the nondescript livestock populations.

Transcriptomic diversity in longissimus thoracis muscles of Barbari and Changthangi goat breeds of India.

The present study is an attempt to examine the differential expression of genes in longissimus thoracis muscles between meat and wool type Indian goat breeds. Barbari goat is considered the best meat breed while Changthangi is famous for its fine fibre quality. RNA sequencing data was generated from four biological replicates of longissimus thoracis muscles of Barbari and Changthangi goats. A clear demarcation could be observed between the breeds in terms of expression of genes associated with lipid metabolism (FASN, SCD, THRSP, DGAT2 and FABP3). Most significant genes with high connectivity identified by gene co-expression network analysis were associated with triacylglycerol biosynthesis pathway in Barbari goat. Highly interactive genes identified in Changthangi goat were mainly associated with muscle fibre type. This study provides an insight into the differential expression of genes in longissimus thoracis muscles between Barbari and Changthangi goats that are adapted to and reared in different agro-climatic regions.

An introduction to new robust linear and monotonic correlation coefficients.

BACKGROUND: The most common measure of association between two continuous variables is the Pearson correlation (Maronna et al. in Safari an OMC. Robust statistics, 2019. https://login.proxy.bib.uottawa.ca/login?url=https://learning.oreilly.com/library/view/-/9781119214687/?ar&orpq&email=^u). When outliers are present, Pearson does not accurately measure association and robust measures are needed. This article introduces three new robust measures of correlation: Taba (T), TabWil (TW), and TabWil rank (TWR). The correlation estimators T and TW measure a linear association between two continuous or ordinal variables; whereas TWR measures a monotonic association. The robustness of these proposed measures in comparison with Pearson (P), Spearman (S), Quadrant (Q), Median (M), and Minimum Covariance Determinant (MCD) are examined through simulation. Taba distance is used to analyze genes, and statistical tests were used to identify those genes most significantly associated with Williams Syndrome (WS). RESULTS: Based on the root mean square error (RMSE) and bias, the three proposed correlation measures are highly competitive when compared to classical measures such as P and S as well as robust measures such as Q, M, and MCD. Our findings indicate TBL2 was the most significant gene among patients diagnosed with WS and had the most significant reduction in gene expression level when compared with control (P value = 6.37E-05). CONCLUSIONS: Overall, when the distribution is bivariate Log-Normal or bivariate Weibull, TWR performs best in terms of bias and T performs best with respect to RMSE. Under the Normal distribution, MCD performs well with respect to bias and RMSE; but TW, TWR, T, S, and P correlations were in close proximity. The identification of TBL2 may serve as a diagnostic tool for WS patients. A Taba R package has been developed and is available for use to perform all necessary computations for the proposed methods.

Analysis of Nonbattle Deaths Among U.S. Service Members in the Deployed Environment.

OBJECTIVE: Describe etiologies and trends in non-battle deaths (NBD) among deployed U.S. service members to identify areas for prevention. BACKGROUND: Injuries in combat are categorized as battle (result of hostile action) or nonbattle related. Previous work found that one-third of injured US military personnel in Iraq and Afghanistan had nonbattle injuries and emphasized prevention. NBD have not yet been characterized. METHODS: U.S. military casualty data for Iraq and Afghanistan from 2001 to 2014 were obtained from the Defense Casualty Analysis System (DCAS) and the Department of Defense Trauma Registry (DoDTR). Two databases were used because DoDTR does not capture prehospital deaths, while DCAS does not contain clinical details. Nonbattle injuries and NBD were identified, etiologies classified, and NBD trends were assessed using a weighted moving average and time-series analysis with autoregressive integrated moving average. Future NBD rates were forecast. RESULTS: DCAS recorded 59,799 casualties; 21.0% (n = 1431) of all deaths (n = 6745) were NBD. DoDTR recorded 29,958 casualties; 11.5% (n = 206) of all deaths (n = 1788) were NBD. After early fluctuations, NBD rates for both Iraq and Afghanistan stabilized at approximately 21%. Leading causes of NBD were gunshot wounds and vehicle accidents, accounting for 66%. Approximately 25% was self-inflicted. A 24% NBD rate was forecasted from 2015 through 2025. CONCLUSIONS: Approximately 1 in 5 deaths were NBD. The majority were potentially preventable, including a significant proportion of self-inflicted injuries. A single comprehensive data repository would facilitate future mortality monitoring and performance improvement. These data may assist military leaders with implementing targeted safety strategies.

Influences of reopening businesses and social venues: COVID-19 incidence rate in East Texas county.

As the on-going severe acute respiratory syndrome coronavirus 2 pandemic, we aimed to understand whether economic reopening (EROP) significantly influenced coronavirus disease 2019 (COVID-19) incidence. COVID-19 data from Texas Health and Human Services between March and August 2020 were analysed. COVID-19 incidence rate (cases per 100 000 population) was compared to statewide for selected urban and rural counties. We used joinpoint regression analysis to identify changes in trends of COVID-19 incidence and interrupted time-series analyses for potential impact of state EROP orders on COVID-19 incidence. We found that the incidence rate increased to 145.1% (95% CI 8.4-454.5%) through 4th April, decreased by 15.5% (95% CI -24.4 -5.9%) between 5th April and 30th May, increased by 93.1% (95% CI 60.9-131.8%) between 31st May and 11th July and decreased by 13.2% (95% CI -22.2 -3.2%) after 12 July 2020. The study demonstrates the EROP policies significantly impacted trends in COVID-19 incidence rates and accounted for increases of 129.9 and 164.6 cases per 100 000 populations for the 24- or 17-week model, respectively, along with other county and state reopening ordinances. The incidence rate decreased sharply after 12th July considering the emphasis on a facemask or covering requirement in business and social settings.

Temporary reduction in air pollution due to anthropogenic activity switch-off during COVID-19 lockdown in northern parts of India.

Due to fast and deadly spread of corona virus (COVID-19), the Government of India implemented lockdown in the entire country from 25 April 2020. So, we studied the differences in the air quality index (AQI) of Delhi (DTU, Okhla and Patparganj), Haryana (Jind, Palwal and Hisar) and Uttar Pradesh (Agra, Kanpur and Greater Noida) from 17 February 2020 to 4 May 2020. The AQI was calculated by combination of individual sub-indices of seven pollutants, namely PM2.5, PM10, NO2, NH3, SO2, CO and O3, collected from the Central Pollution Control Board website. The AQI has improved by up to 30-46.67% after lockdown. The AQI slope values - 1.87, - 1.70 and - 1.35 were reported for Delhi, - 1.11, - 1.31 and - 1.04 were observed for Haryana and - 1.48, - 1.79 and - 1.78 were found for Uttar Pradesh (UP), which may be attributed to limited access of transportation and industrial facilities due to lockdown. The ozone (O3) concentration was high at Delhi because of lesser greenery as compared to UP and Haryana, which provides higher atmospheric temperature favourable for O3 formation. The air mass back trajectory (AMBT) analysis reveals the contribution of air mass from Europe, Africa and Gulf countries as well as local emissions from Indo-Gangetic Plain, Madhya Pradesh and Maharashtra states of India.

Burnout and Anxiety Among Trauma Nursing Specialties in a Rural Level I Trauma Center.

BACKGROUND: Burnout and anxiety compromise physical and mental well-being of nurses and jeopardize patient safety. Personal, professional, and workplace characteristics have been associated with burnout and anxiety across diverse practice settings, yet none in rural, community trauma centers. We sought to identify the severity and predictors of burnout and anxiety in the trauma nursing staff of a rural Level I trauma center. METHODS: A convenience sample of trauma nurses from the emergency department (ED), intensive care unit (ICU), and trauma ward was voluntarily surveyed using a demographic questionnaire, the Maslach Burnout Inventory (MBI) subscales: depersonalization (DP), emotional exhaustion (EE), and reduced personal accomplishment, as well as the Generalized Anxiety Disorder seven-item (GAD-7) scale. Multivariable linear regression identified the significant predictors of burnout and anxiety. RESULTS: Ninety-six nurses completed surveys (response rate: 83.5%). Married or divorced status, and ICU or trauma ward job assignments were associated with significantly lower adjusted DP scores. Thus, the model-predicted score for a single ED nurse was 15 versus a predicted score of 7 for a divorced ICU or trauma ward nurse, p < .001 for each group. The GAD-7 model demonstrated that race/ethnicity (Asian compared with White, coefficient: -5.06, p = .03), number of children (2 compared with 0, coefficient: -2.54, p = .02), and job tenure (5-10 years vs. <2, coefficient: -3.18, p = .01) were each associated with fewer GAD-7 points. CONCLUSION: Depersonalization and anxiety vary across the trauma nursing workforce based on identifiable personal and work-related risk factors. Group-specific, targeted interventions are needed to effectively reduce burnout and anxiety in trauma nursing staff.

Microbiome Diversity in Sputum of Nontuberculous Mycobacteria Infected Women with a History of Breast Cancer.

BACKGROUND/AIMS: The nontuberculous mycobacterial lung disease (NTM), caused by Mycobacterium avium complex (MAC) is an increasing health problem in the USA and worldwide. The NTM disease is prevalent in Caucasian women with a current diagnosis or history of breast cancer (BCa), posing a significant challenge towards treatment. We hypothesize that NTM affected women with considerable therapeutic resistance may harbor pathogenic microbes other than nontuberculous mycobacterium, aiding in disease progression and therapeutic resistance. METHODS: We assessed microbiome diversity in sputa from healthy women, women with nontuberculous mycobacterial lung disease (NTM) and women with both nontuberculous mycobacterial lung disease and breast cancer (NTM-BCa). First, we collected sputa and isolated DNA from sputa of these healthy women and women with NTM and NTM-BCa. We also isolated DNA from sera derived extracellular vesicles from women with NTM-BCa. To identify diverse pathogenic microbes in various groups of subjects, we then performed 16S rDNA sequencing. Data analysis was performed utilizing the analytical pipelines at the Center for Metagenomic and Microbiome Research (CMMR), Baylor College of Medicine. RESULTS: A large community of resident microbes, including bacteria, virus, Archeas and Fungi live in the human body are being increasingly recognized as the key components of human health and disease. We identified a diverse microbiome community in the sputa and the extracellular vesicles dominated by Streptococcus, Haemophillus, Veillonella, Neisseria, Prevotella, Fusobacterium, Bacteroides, Allistipes, Faecalibacterium and Staphylococcus in women with nontuberculous mycobacterial lung disease as well as women with both nontuberculous mycobacterial lung disease and breast cancer. Some of these genera, including Fusobacterium, Bacteroides, and Allistipes have estrobolome activity and associated with breast and other neoplasms. CONCLUSION: This work confirms the presence of a distinct pathogenic microbiome other than nontuberculous mycobacteria in the sputa and the circulating extracellular vesicles of these patients. This information could be useful for better therapeutic design to treat the NTM patients.

Increased expression of plasminogen activator inhibitor-1 (PAI-1) is associated with depression and depressive phenotype in C57Bl/6J mice.

Plasminogen activator inhibitor 1 (PAI-1), which is elevated in numerous disease states, has been implicated as a stress-related protein involved in the pathogenesis of depression. We measured PAI-1 in the plasma of healthy and depressed individuals and assessed plasminogen activator (PA) expression and regulation by PAI-1 in cultured normal human astrocytes (NHA). Elevated plasma PAI-1 levels were found in depressed patients. Brain tissues from depressed individuals also showed stronger expression of hippocampal PAI-1 by confocal imaging in comparison to healthy individuals. Using a lipopolysaccharide-induced inflammatory model of depression in mice, we measured PAI-1 in murine plasma and brain, by ELISA and immunohistochemistry, respectively. Similar elevations were seen in plasma but not in brain homogenates of mice exposed to LPS. We further correlated the findings with depressive behavior. Ex vivo experiments with NHA treated with proinflammatory cytokines implicated in the pathogenesis of depression showed increased PAI-1 expression. Furthermore, these studies suggest that urokinase-type plasminogen activator may serve as an astrocyte PA reservoir, able to promote cleavage of brain-derived neurotrophic factor (BDNF) during stress or inflammation. In summary, our findings confirm that derangements of PAI-1 variably occur in the brain in association with the depressive phenotype. These derangements may impede the availability of active, mature (m)BDNF and thereby promote a depressive phenotype.