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Telomere length (TL) is a marker of ageing and mitochondrial DNA (mtDNA) is an early marker of inflammation caused by oxidative stress. We determined TL and mtDNA content among active pulmonary tuberculosis (PTB) patients to assess if these cellular biomarkers differed between artisanal miners and non-miners, and to assess if they were predictive of treatment outcome. We conducted a prospective cohort study from August 2018 to May 2019 involving newly diagnosed PTB patients at three outpatient TB clinics in a rural Democratic Republic of Congo. We measured relative TL and mtDNA content in peripheral blood leukocytes (at inclusion) via qPCR and assessed their association with PTB treatment outcome. We included 129 patients (85 miners and 44 non-miners) with PTB (median age 40 years; range 5-71 years, 22% HIV-coinfected). For each increase in year and HIV-coinfection, TL shortened by - 0.85% (- 0.19 to - 0.52) (p ≤ 0.0001) and - 14% (- 28.22 to - 1.79) (p = 0.02) respectively. Independent of these covariates, patients with longer TL were more likely to have successful TB treatment [adjusted hazard ratio; 95% CI 1.27 for a doubling of leucocyte telomere length at baseline; 1.05-1.44] than patients with a shorter TL. Blood mtDNA content was not predictive for PTB outcome. Selleckchem MS4078 For a given chronological age, PTB patients with longer telomeres at time of diagnosis were more likely to have successful PTB treatment outcome.We present Python Statistical Analysis of Turbulence (P-SAT), a lightweight, Python framework that can automate the process of parsing, filtering, computation of various turbulent statistics, spectra computation for steady flows. P-SAT framework is capable to work with single as well as on batch inputs. The framework quickly filters the raw velocity data using various methods like velocity correlation, signal-to-noise ratio (SNR), and acceleration thresholding method in order to de-spike the velocity signal of steady flows. It is flexible enough to provide default threshold values in methods like correlation, SNR, acceleration thresholding and also provide the end user with an option to provide a user defined value. The framework generates a .csv file at the end of the execution, which contains various turbulent parameters mentioned earlier. The P-SAT framework can handle velocity time series of steady flows as well as unsteady flows. The P-SAT framework is capable to obtain mean velocities from instantaneous velocities of unsteady flows by using Fourier-component based averaging method. Since P-SAT framework is developed using Python, it can be deployed and executed across the widely used operating systems. The GitHub link for the P-SAT framework is https//github.com/mayank265/flume.git .Anxiety symptoms are relatively common during pregnancy and are associated with behavioural problems in children. The amygdala is involved in emotion regulation, and its volume and function are associated with exposure to prenatal maternal depression. The associations between perinatal maternal anxiety and children's amygdala structure and function remain unclear. The objective of this study was to determine associations between prenatal and postnatal maternal anxiety and amygdala structure and function in children. Maternal anxiety was measured during the second trimester of pregnancy and 12 weeks postpartum. T1-weighted anatomical data and functional magnetic resonance imaging data were collected from 54 children (25 females), between the ages of 3-7 years. Amygdala volume was calculated and functional connectivity maps were created between the amygdalae and the rest of the brain. Spearman correlations were used to test associations between amygdala volume/functional connectivity and maternal anxiety symptoms, controlling for maternal depression symptoms. Second trimester maternal anxiety symptoms were negatively associated with functional connectivity between the left amygdala and clusters in bilateral parietal regions; higher maternal anxiety was associated with increased negative connectivity. Postnatal maternal anxiety symptoms were positively associated with child amygdala volume, but this finding did not remain significant while controlling for total brain volume. These functional connectivity differences may underlie behavioral outcomes in children exposed to maternal anxiety during pregnancy.For epidemics control and prevention, timely insights of potential hot spots are invaluable. Alternative to traditional epidemic surveillance, which often lags behind real time by weeks, big data from the Internet provide important information of the current epidemic trends. Here we present a methodology, ARGOX (Augmented Regression with GOogle data CROSS space), for accurate real-time tracking of state-level influenza epidemics in the United States. ARGOX combines Internet search data at the national, regional and state levels with traditional influenza surveillance data from the Centers for Disease Control and Prevention, and accounts for both the spatial correlation structure of state-level influenza activities and the evolution of people's Internet search pattern. ARGOX achieves on average 28% error reduction over the best alternative for real-time state-level influenza estimation for 2014 to 2020. ARGOX is robust and reliable and can be potentially applied to track county- and city-level influenza activity and other infectious diseases.In mammalian species with prolonged maternal investment in which high-ranking males gain disproportionate numbers of mating opportunities, males that quickly ascend the hierarchy may benefit from eliminating the dependent offspring of their competitors. In savanna baboons, high-ranking females are the most profitable targets of infanticide or feticide, because their offspring have higher survival rates and their daughters reach sexual maturity at a younger age. However, such patterns may be obscured by environmental stressors that are known to exacerbate fetal losses, especially in lower-ranking females. Using 30 years of data on wild olive baboons (Papio anubis) in Gombe National Park, Tanzania, we found evidence that rapidly-rising immigrant males induced miscarriages in high-ranking females outside of drought conditions. However, miscarriage rates were largely reversed during prolonged periods of low rainfall, suggesting that low-ranking females are particularly vulnerable to low food availability and social instability. Infanticide did not emerge as a recurrent male strategy in this population, likely because of the protective behavior of resident males towards vulnerable juveniles.With the development of 5th generation (5G) mobile networks people of different ages will be exposed in the upper part of the microwave spectrum. From the perspective of non-ionizing radiation dosimetry, an accurate analysis of age-dependent electromagnetic power deposition and resulting heating is required. In this study, we evaluate the effect of age on exposure at 26 GHz and 60 GHz. A near-surface tissue model illuminated by a plane wave is used to asses the exposure considering both frequency-independent and frequency-dependent limits. The age-related variation of the skin thickness and tissue electromagnetic properties has been considered. Moreover, the blood flow decrease rate has been taken into account to assess the age-dependent heating. Our results demonstrate that the overall variations of the power density, specific absorption rate (SAR) and heating in the near-surface tissues are limited to about 10-15%. These variations are mainly due to the tissue permittivity and blood flow change with age. In contrast to the transmitted power density that increases with age, the peak SAR decreases at both frequencies. The peak steady-state heating increases from 5 to 70 years old by roughly 11% at 26 GHz and 13% at 60 GHz.Kingdom of Tonga in Polynesia is one of the most obese nations where metabolic conditions, sedentary lifestyles, and poor quality diet are widespread. These factors can lead to poor musculoskeletal health. However, whether metabolic abnormalities such as osteoporosis occurred in archaeological populations of Tonga is unknown. We employed a microscopic investigation of femur samples to establish whether bone loss afflicted humans in this Pacific region approximately 3000 years ago. Histology, laser confocal microscopy, and synchrotron Fourier-transform infrared microspectroscopy were used to measure bone vascular canal densities, bone porosity, and carbonate and phosphate content of bone composition in eight samples extracted from adult Talasiu males and females dated to 2650 BP. Compared to males, samples from females had fewer vascular canals, lower carbonate and phosphate content, and higher bone porosity. Although both sexes showed evidence of trabecularised cortical bone, it was more widespread in females (35.5%) than males (15.8%). Our data suggest experiences of advanced bone resorption, possibly as a result of osteoporosis. This provides first evidence for microscopic bone loss in a sample of archaeological humans from a Pacific population widely afflicted by metabolic conditions today.Despite the introduction of anti-retroviral therapy, chronic HIV infection is associated with an increased incidence of other comorbidities such as COPD. Based on the knowledge that binding of HIV to human airway basal stem/progenitor cells (BC) induces a destructive phenotype by increased MMP-9 expression through MAPK signaling pathways, we hypothesized that HIV induces the BC to express inflammatory mediators that contribute to the pathogenesis of emphysema. Our data demonstrate that airway BC isolated from HAART-treated HIV+ nonsmokers spontaneously release inflammatory mediators IL-8, IL-1β, ICAM-1 and GM-CSF. Similarly, exposure of normal BC to HIV in vitro up-regulates expression of the same inflammatory mediators. These HIV-BC derived mediators induce migration of alveolar macrophages (AM) and neutrophils and stimulate AM proliferation. This HIV-induced inflammatory phenotype likely contributes to lung inflammation in HIV+ individuals and provides explanation for the increased incidence of COPD in HIV+ individuals.Deep learning is an emerging tool, which is regularly used for disease diagnosis in the medical field. A new research direction has been developed for the detection of early-stage gastric cancer. The computer-aided diagnosis (CAD) systems reduce the mortality rate due to their effectiveness. In this study, we proposed a new method for feature extraction using a stacked sparse autoencoder to extract the discriminative features from the unlabeled data of breath samples. A Softmax classifier was then integrated to the proposed method of feature extraction, to classify gastric cancer from the breath samples. Precisely, we identified fifty peaks in each spectrum to distinguish the EGC, AGC, and healthy persons. This CAD system reduces the distance between the input and output by learning the features and preserve the structure of the input data set of breath samples. The features were extracted from the unlabeled data of the breath samples. After the completion of unsupervised training, autoencoders with Softmax classifier were cascaded to develop a deep stacked sparse autoencoder neural network.
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