Large Magnetoresistance over an Extended Temperature Regime in Monophosphides of Tantalum and Niobium

We report extremely large magnetoresistance (MR) in an extended temperature regime from 1.5 K to 300 K in non-magnetic binary compounds TaP and NbP. TaP exhibits linear MR around $1.8\times 10^4$ at 2 K in a magnetic field of 9 Tesla, which further follows its linearity up to $1.4\times 10^5$ in a magnetic field of 56 Tesla at 1.5 K. At room temperature the MR for TaP and NbP follows a power law of the exponent about $1.5$ with the values larger than $300\%$ in a magnetic field of 9 Tesla. Such large MR in a wide temperature regime is not likely only due to a resonance of the electron-hole balance, but indicates a complicated mechanism underneath.Comment: 13 pages, 4 figures; submitted in May 20, 2015; accepted for publicatio

Strategy for Mitigating Antibiotic Resistance by Biochar and Hyperaccumulators in Cadmium and Oxytetracycline Co-contaminated Soil

Publisher Copyright: © 2021 The Authors. Published by American Chemical SocietyThe global prevalence of antibiotic resistance genes (ARGs) is of increasing concern as a serious threat to ecological security and human health. Irrigation with sewage and farmland application of manure or biosolids in agricultural practices introduce substantial selective agents such as antibiotics and toxic metals, aggravating the transfer of ARGs from the soil environment to humans via the food chain. To address this issue, a hyperaccumulator (Sedum plumbizincicola) combined with biochar amendment was first used to investigate the mitigation of the prevalence of ARGs in cadmium and oxytetracycline co-contaminated soil by conducting a pot experiment. The addition of biochar affected the distribution of ARGs in soil and plants differently by enhancing their prevalence in the soil but restraining transmission from the soil to S. plumbizincicola. The planting of S. plumbizincicola resulted in an increase in ARGs in the soil environment. A structural equation model illustrated that mobile genetic elements played a dominant role in shaping the profile of ARGs. Taken together, these findings provide a practical understanding for mitigating the prevalence of ARGs in this soil system with complex contamination and can have profound significance for agricultural management in regard to ARG dissemination control.Peer reviewe

BCNet: A Novel Network for Blood Cell Classification

Aims: Most blood diseases, such as chronic anemia, leukemia (commonly known as blood cancer), and hematopoietic dysfunction, are caused by environmental pollution, substandard decoration materials, radiation exposure, and long-term use certain drugs. Thus, it is imperative to classify the blood cell images. Most cell classification is based on the manual feature, machine learning classifier or the deep convolution network neural model. However, manual feature extraction is a very tedious process, and the results are usually unsatisfactory. On the other hand, the deep convolution neural network is usually composed of massive layers, and each layer has many parameters. Therefore, each deep convolution neural network needs a lot of time to get the results. Another problem is that medical data sets are relatively small, which may lead to overfitting problems.Methods: To address these problems, we propose seven models for the automatic classification of blood cells: BCARENet, BCR5RENet, BCMV2RENet, BCRRNet, BCRENet, BCRSNet, and BCNet. The BCNet model is the best model among the seven proposed models. The backbone model in our method is selected as the ResNet-18, which is pre-trained on the ImageNet set. To improve the performance of the proposed model, we replace the last four layers of the trained transferred ResNet-18 model with the three randomized neural networks (RNNs), which are RVFL, ELM, and SNN. The final outputs of our BCNet are generated by the ensemble of the predictions from the three randomized neural networks by the majority voting. We use four multi-classification indexes for the evaluation of our model.Results: The accuracy, average precision, average F1-score, and average recall are 96.78, 97.07, 96.78, and 96.77%, respectively.Conclusion: We offer the comparison of our model with state-of-the-art methods. The results of the proposed BCNet model are much better than other state-of-the-art methods

Preoperative Strength Training for Clinical Outcomes Before and After Total Knee Arthroplasty: A Systematic Review and Meta-Analysis

BackgroundThere is an increasing interest in preoperative strength training for promoting post-operative rehabilitation, but the effectiveness of preoperative strength training for clinical outcomes after total knee arthroplasty (TKA) remains controversial.ObjectiveThis study aims to systematically evaluate the effect of preoperative strength training on clinical outcomes before and after TKA.MethodsWe systematically searched PubMed, Cochrane Library, Web of Science, and EMBASE databases from the inception to November 17, 2021. The meta-analysis was performed to evaluate the effects of preoperative strength training on clinical outcomes before and after TKA.ResultsSeven randomized controlled trials (RCTs) were included (n = 306). Immediately before TKA, the pooled results showed significant improvements in pain, knee function, functional ability, stiffness, and physical function in the strength training group compared with the control group, but not in strength (quadriceps), ROM, and WOMAC (total). Compared with the control group, the results indicated strength training had a statistically significant improvement in post-operative knee function, ROM, and functional ability at less than 1 month and 3 months, and had a statistically significant improvement in post-operative strength (quadriceps), stiffness, and WOMAC (total) at 3 months, and had a statistically significant improvement in post-operative pain at 6 months. However, the results indicated strength training had no statistically significant improvement in post-operative strength (quadriceps) at less than 1 month, 6, and 12 months, had no statistically significant improvement in post-operative pain at less than 1 month, 3, and 12 months, had no statistically significant improvement in post-operative knee function at 6 and 12 months, and had no statistically significant improvement in post-operative physical function at 3 months.ConclusionsPreoperative strength training may be beneficial to early rehabilitation after TKA, but the long-term efficacy needs to be further determined. At the same time, more caution should be exercised when interpreting the clinical efficacy of preoperative strength training for TKA

The effects of ECMO on neurological function recovery of critical patients: A double-edged sword

Extracorporeal membrane oxygenation (ECMO) played an important role in the treatment of patients with critical care such as cardiac arrest (CA) and acute respiratory distress syndrome. ECMO is gradually showing its advantages in terms of speed and effectiveness of circulatory support, as it provides adequate cerebral blood flow (CBF) to the patient and ensures the perfusion of organs. ECMO enhances patient survival and improves their neurological prognosis. However, ECMO-related brain complications are also important because of the high risk of death and the associated poor outcomes. We summarized the reported complications related to ECMO for patients with CA, such as north–south syndrome, hypoxic–ischemic brain injury, cerebral ischemia–reperfusion injury, impaired intracranial vascular autoregulation, embolic stroke, intracranial hemorrhage, and brain death. The exact mechanism of ECMO on the role of brain function is unclear. Here we review the pathophysiological mechanisms associated with ECMO in the protection of neurologic function in recent years, as well as the ECMO-related complications in brain and the means to improve it, to provide ideas for the treatment of brain function protection in CA patients