Impact of left atrial appendage location on risk of thrombus formation in patients with atrial fibrillation

Biomechanics and Modeling in Mechanobiology - Most strokes in patients with atrial fibrillation (AF) are thought to arise from thrombus formation in the left atrial appendage (LAA). Assessing the...     

Loss of longitudinal superiority marks the microarchitecture deterioration of osteoporotic cancellous bones

Biomechanics and Modeling in Mechanobiology - Osteoporosis (OP), a skeletal disease making bone mechanically deteriorate and easily fracture, is a global public health issue due to its high...     

Establishment of an efficient shoot regeneration system in vitro in Brassica rapa

In Vitro Cellular & Developmental Biology - Plant - To improve the genetic transformation system for Brassica rapa L., we established a high-efficiency shoot regeneration protocol. A double...     

Curcumin alleviates acute kidney injury in a dry‐heat environment by reducing oxidative stress and inflammation in a rat model

Curcumin exhibits anti‐inflammatory and antioxidant activities. We investigated the protective effects of curcumin in a renal injury rat model under dry‐heat conditions. We divided Sprague‐Dawley rats into four groups: dry‐heat 0‐ (normal temperature control group), 50‐, 100‐, and 150‐minute groups. Each group was divided into five subgroups (n = 10): normal saline (NS), sodium carboxymethylcellulose (CMCNa), and curcumin pretreated low, medium, and high‐dose (50, 100, and 200 mg/kg, respectively) groups. Compared to the normal temperature group, serum creatinine, blood urea nitrogen, urinary kidney injury molecule‐1, and neutrophil gelatinase‐associated load changes in lipoprotein (NGAL) levels were significantly increased in the dry‐heat environment group (P < .05); inducible nitric oxide synthase (iNOS) and cyclooxygenase‐2 (COX‐2) expression and malondialdehyde (MDA) and related inflammatory factor levels were increased in the kidney tissue. Superoxide dismutase (SOD) and catalase (CAT) levels were decreased. However, following all curcumin pretreatment, the serum levels of kidney injury indicators and NGAL were decreased in the urine compared to those in the NS and CMCNa groups (P < .05), whereas renal SOD and CAT activities were increased and MDA was decreased (P < .05). Renal tissues of the 150‐minute group showed obvious pathological changes. Compared to the NS group, pathological changes in the renal tissues of the 100‐ and 200‐mg/kg curcumin groups were significantly reduced. Furthermore, iNOS and COX‐2 expression and inflammatory factor levels were decreased after curcumin treatment. Curcumin exerted renoprotective effects that were likely mediated by its antioxidant and anti‐inflammatory effects in a dry‐heat environment rat model.     

Molecular epidemiology and recombination of Enterovirus A71 in mainland China from 1987 to 2017

International Microbiology - Enterovirus A71 (EV-A71) is an important pathogen of severe hand, foot, and mouth disease (HFMD) in young children. This study aimed to retrospectively analyze the...     

Airborne and indigenous microbiomes co-drive the rebound of antibiotic resistome during compost storage

Composting is widely used to reduce the abundance of antibiotic resistance genes (ARGs) in solid waste. While ARG dynamics have been extensively investigated during composting, the fate and abundance of residual ARGs during the storage remain unexplored. Here, we tested experimentally how ARG and mobile genetic element (MGE) abundances change during compost storage using metagenomics, quantitative PCR and direct culturing. We found that 43.8% of ARGs and 39.9% of MGEs quickly recovered already during the first week of storage. This rebound effect was mainly driven by the regrowth of indigenous, antibiotic-resistant bacteria that survived the composting. Bacterial transmission from the surrounding air had a much smaller effect, being most evident as MGE rebound during the later stages of storage. While hyperthermophilic composting was more efficient at reducing the relative abundance of ARGs and MGEs, relatively greater ARG rebound was observed during the storage of hyperthermophilic compost, exceeding the initial levels of untreated sewage sludge. Our study reveals that residual ARGs and MGEs left in the treated compost can quickly rebound during the storage via airborne introduction and regrowth of surviving bacteria, highlighting the need to develop better storage strategies to prevent the rebound of ARGs and MGEs after composting.     

Sex differences in the immune response to acute COVID-19 respiratory tract infection

Determine if sex differences exist in clinical characteristics and outcomes of adults hospitalized for coronavirus disease 2019 (COVID-19) in a US healthcare system. Case series study. Sequentially hospitalized adults admitted for COVID-19 at two tertiary care academic hospitals in New Orleans, LA, between 27 February and 15 July 2020. Measures included demographics, comorbidities, presenting symptoms, and laboratory results. Outcomes included intensive care unit admission (ICU), invasive mechanical ventilation (IMV), and in-hospital death. We included 776 patients (median age 60.5 years; 61.4% women, 75% non-Hispanic Black). Rates of ICU, IMV, and death were similar in both sexes. In women versus men, obesity (63.8 vs 41.6%, P < 0.0001), hypertension (77.6 vs 70.1%, P = 0.02), diabetes (38.2 vs 31.8%, P = 0.06), chronic obstructive pulmonary disease (COPD, 22.1 vs 15.1%, P = 0.015), and asthma (14.3 vs 6.9%, P = 0.001) were more prevalent. More women exhibited dyspnea (61.2 vs 53.7%, P = 0.04), fatigue (35.7 vs 28.5%, P = 0.03), and digestive symptoms (39.3 vs 32.8%, P = 0.06) than men. Obesity was associated with IMV at a lower BMI (> 35) in women, but the magnitude of the effect of morbid obesity (BMI ≥ 40) was similar in both sexes. COPD was associated with ICU (adjusted OR (aOR), 2.6; 95%CI, 1.5–4.3) and IMV (aOR, 1.8; 95%CI, 1.2–3.1) in women only. Diabetes (aOR, 2.6; 95%CI, 1.2–2.9), chronic kidney disease (aOR, 2.2; 95%CI, 1.3–5.2), elevated neutrophil-to-lymphocyte ratio (aOR, 2.5; 95%CI, 1.4–4.3), and elevated ferritin (aOR, 3.6; 95%CI, 1.7–7.3) were independent predictors of death in women only. In contrast, elevated D-dimer was an independent predictor of ICU (aOR, 7.3; 95%CI, 2.7–19.5), IMV (aOR, 6.5; 95%CI, 2.1–20.4), and death (aOR, 4.5; 95%CI, 1.2–16.4) in men only. This study highlights sex disparities in clinical determinants of severe outcomes in COVID-19 patients that may inform management and prevention strategies to ensure gender equity.     

An efficient pipeline for ancient DNA mapping and recovery of endogenous ancient DNA from whole‐genome sequencing data

Ancient DNA research has developed rapidly over the past few decades due to improvements in PCR and next‐generation sequencing (NGS) technologies, but challenges still exist. One major challenge in relation to ancient DNA research is to recover genuine endogenous ancient DNA sequences from raw sequencing data. This is often difficult due to degradation of ancient DNA and high levels of contamination, especially homologous contamination that has extremely similar genetic background with that of the real ancient DNA. In this study, we collected whole‐genome sequencing (WGS) data from 6 ancient samples to compare different mapping algorithms. To further explore more effective methods to separate endogenous DNA from homologous contaminations, we attempted to recover reads based on ancient DNA specific characteristics of deamination, depurination, and DNA fragmentation with different parameters. We propose a quick and improved pipeline for separating endogenous ancient DNA while simultaneously decreasing homologous contaminations to very low proportions. Our goal in this research was to develop useful recommendations for ancient DNA mapping and for separation of endogenous DNA to facilitate future studies of ancient DNA.     

Modeling vegetation greenness and its climate sensitivity with deep‐learning technology

Climate sensitivity of vegetation has long been explored using statistical or process‐based models. However, great uncertainties still remain due to the methodologies’ deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate–vegetation models based on long short‐term memory (LSTM) network, which is a powerful deep‐learning algorithm for long‐time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep‐learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.