BACKGROUNDNo therapeutics have yet been proven effective for the treatment of severe illness caused by SARS-CoV-2. METHODSWe conducted a randomized, controlled, open-label trial involving hospitalized adult patients with confirmed SARS-CoV-2 infection, which causes the respiratory illness Covid-19, and an oxygen saturation (Sao 2 ) of 94% or less while they were breathing ambient air or a ratio of the partial pressure of oxygen (Pao 2 ) to the fraction of inspired oxygen (Fio 2 ) of less than 300 mm Hg. Patients were randomly assigned in a 1:1 ratio to receive either lopinavir-ritonavir (400 mg and 100 mg, respectively) twice a day for 14 days, in addition to standard care, or standard care alone. The primary end point was the time to clinical improvement, defined as the time from randomization to either an improvement of two points on a seven-category ordinal scale or discharge from the hospital, whichever came first. RESULTSA total of 199 patients with laboratory-confirmed SARS-CoV-2 infection underwent randomization; 99 were assigned to the lopinavir-ritonavir group, and 100 to the standard-care group. Treatment with lopinavir-ritonavir was not associated with a difference from standard care in the time to clinical improvement (hazard ratio for clinical improvement, 1.24; 95% confidence interval [CI], 0.90 to 1.72). Mortality at 28 days was similar in the lopinavir-ritonavir group and the standard-care group (19.2% vs. 25.0%; difference, −5.8 percentage points; 95% CI, −17.3 to 5.7). The percentages of patients with detectable viral RNA at various time points were similar. In a modified intention-to-treat analysis, lopinavir-ritonavir led to a median time to clinical improvement that was shorter by 1 day than that observed with standard care (hazard ratio, 1.39; 95% CI, 1.00 to 1.91). Gastrointestinal adverse events were more common in the lopinavir-ritonavir group, but serious adverse events were more common in the standard-care group. Lopinavir-ritonavir treatment was stopped early in 13 patients (13.8%) because of adverse events. CONCLUSIONS

Type 1 diabetes (T1D) is a debilitating autoimmune disease that results from T cell-mediated destruction of insulin-producing β cells. Its incidence has increased during the past several decades in developed countries 1, 2, suggesting that changes in the environment (including human microbial environment) may influence disease pathogenesis. The incidence of spontaneous T1D in non-obese diabetic (NOD) mice can be affected by the microbial environment in the animal housing facility3 or by exposure to microbial stimuli, such as injection with mycobacteria or various microbial products 4,5. Here we show that specific-pathogen free (SPF) NOD mice lacking MyD88 protein (an adaptor for multiple innate immune receptors that recognize microbial stimuli) do not develop T1D. The effect is dependent on commensal microbes as germ-free (GF) MyD88-negative NOD mice develop robust diabetes, whereas colonization of these GF NOD.MyD88-negative mice with a defined microbial consortium (representing bacterial phyla normally present in human gut) attenuates T1D. We also find that MyD88-deficiency changes the composition of the distal gut microbiota, and that exposure to the microbiota of SPF NOD.MyD88-negative donors attenuates T1D in GF NOD recipients. Together, these findings indicate that interaction of the intestinal microbes with the innate immune system is a critical epigenetic factor modifying T1D predisposition.

High energy-density lithium-ion batteries are in demand for portable electronic devices and electrical vehicles. Since the energy density of the batteries relies heavily on the cathode material used, major research efforts have been made to develop alternative cathode materials with a higher degree of lithium utilization and specific energy density. In particular, layered, Ni-rich, lithium transition-metal oxides can deliver higher capacity at lower cost than the conventional LiCoO2 . However, for these Ni-rich compounds there are still several problems associated with their cycle life, thermal stability, and safety. Herein the performance enhancement of Ni-rich cathode materials through structure tuning or interface engineering is summarized. The underlying mechanisms and remaining challenges will also be discussed.

Epithelial-to-mesenchymal transition (EMT) is a developmental process important for cell fate determination. Fibroblasts, a product of EMT, can be reset into induced pluripotent stem cells (iPSCs) via exogenous transcription factors but the underlying mechanism is unclear. Here we show that the generation of iPSCs from mouse fibroblasts requires a mesenchymal-to-epithelial transition (MET) orchestrated by suppressing pro-EMT signals from the culture medium and activating an epithelial program inside the cells. At the transcriptional level, Sox2/Oct4 suppress the EMT mediator Snail, c-Myc downregulates TGF-beta1 and TGF-beta receptor 2, and Klf4 induces epithelial genes including E-cadherin. Blocking MET impairs the reprogramming of fibroblasts whereas preventing EMT in epithelial cells cultured with serum can produce iPSCs without Klf4 and c-Myc. Our work not only establishes MET as a key cellular mechanism toward induced pluripotency, but also demonstrates iPSC generation as a cooperative process between the defined factors and the extracellular milieu. PAPERCLIP:

Anomaly detection in videos refers to the identification of events that do not conform to expected behavior. However, almost all existing methods tackle the problem by minimizing the reconstruction errors of training data, which cannot guarantee a larger reconstruction error for an abnormal event. In this paper, we propose to tackle the anomaly detection problem within a video prediction framework. To the best of our knowledge, this is the first work that leverages the difference between a predicted future frame and its ground truth to detect an abnormal event. To predict a future frame with higher quality for normal events, other than the commonly used appearance (spatial) constraints on intensity and gradient, we also introduce a motion (temporal) constraint in video prediction by enforcing the optical flow between predicted frames and ground truth frames to be consistent, and this is the first work that introduces a temporal constraint into the video prediction task. Such spatial and motion constraints facilitate the future frame prediction for normal events, and consequently facilitate to identify those abnormal events that do not conform the expectation. Extensive experiments on both a toy dataset and some publicly available datasets validate the effectiveness of our method in terms of robustness to the uncertainty in normal events and the sensitivity to abnormal events. All codes are released in https://github. com/StevenLiuWen/ano_pred_cvpr2018.We also compare the video prediction network based and Auto-Encoder network based anomaly detection. Here for Auto-Encoder network based anomaly detection, we use the Conv-AE [13] which is the latest work and achieves state-of-the-art performance for anomaly detection. Because of the capacity of deep neural network, Auto-Encoder

Emerging evidence has linked the gut microbiome to human obesity. We performed a metagenome-wide association study and serum metabolomics profiling in a cohort of lean and obese, young, Chinese individuals. We identified obesity-associated gut microbial species linked to changes in circulating metabolites. The abundance of Bacteroides thetaiotaomicron, a glutamate-fermenting commensal, was markedly decreased in obese individuals and was inversely correlated with serum glutamate concentration. Consistently, gavage with B. thetaiotaomicron reduced plasma glutamate concentration and alleviated diet-induced body-weight gain and adiposity in mice. Furthermore, weight-loss intervention by bariatric surgery partially reversed obesity-associated microbial and metabolic alterations in obese individuals, including the decreased abundance of B. thetaiotaomicron and the elevated serum glutamate concentration. Our findings identify previously unknown links between intestinal microbiota alterations, circulating amino acids and obesity, suggesting that it may be possible to intervene in obesity by targeting the gut microbiota.

It is estimated that the world will need to double its energy supply by 2050. Nanotechnology has opened up new frontiers in materials science and engineering to meet this challenge by creating new materials, particularly carbon nanomaterials, for efficient energy conversion and storage. Comparing to conventional energy materials, carbon nanomaterials possess unique size-/surface-dependent (e.g., morphological, electrical, optical, and mechanical) properties useful for enhancing the energy-conversion and storage performances. During the past 25 years or so, therefore, considerable efforts have been made to utilize the unique properties of carbon nanomaterials, including fullerenes, carbon nanotubes, and graphene, as energy materials, and tremendous progress has been achieved in developing high-performance energy conversion (e.g., solar cells and fuel cells) and storage (e.g., supercapacitors and batteries) devices. This article reviews progress in the research and development of carbon nanomaterials during the past twenty years or so for advanced energy conversion and storage, along with some discussions on challenges and perspectives in this exciting field.

Somatic cells can be reprogrammed into induced pluripotent stem cells (iPSCs) by defined factors. However, the low efficiency and slow kinetics of the reprogramming process have hampered progress with this technology. Here we report that a natural compound, vitamin C (Vc), enhances iPSC generation from both mouse and human somatic cells. Vc acts at least in part by alleviating cell senescence, a recently identified roadblock for reprogramming. In addition, Vc accelerates gene expression changes and promotes the transition of pre-iPSC colonies to a fully reprogrammed state. Our results therefore highlight a straightforward method for improving the speed and efficiency of iPSC generation and provide additional insights into the mechanistic basis of the reprogramming process.