Metabolic dynamics across prolonged diapause development in larvae of the sawfly,Cephalcia chuxiongica (Hymenoptera: Pamphiliidae)

Nutrient metabolism is crucial for the survival of insects through the diapause. However, little is known about the metabolic mechanism of prolonged diapause. The sawfly, Cephalcia chuxiongica (Hymenoptera: Pamphiliidae), is a notorious defoliator of pine trees in southwest China. One of the distinguishing biological characteristics of this pest is the prolonged diapause of about 1.5 years. In this study, the body lipid, carbohydrate (total body sugar, glycogen, trehalose, and glucose), protein, and glycerol contents were measured in diapausing larvae of C. chuxiongica. The results showed that the changes of biochemical composition in C. chuxiongica are associated with the diapause initiation, maintenance, and termination phases. During the initiation phase, trehalose, glucose, and glycerol increased significantly, but glycogen decreased sharply. In general, the lipid, carbohydrate, and glycerol levels decreased gradually across the maintenance phase. At termination phase, the contents of glycogen and lipid persistently decreased, while an increase of trehalose, glucose, and glycerol contents were detected. The protein level was significantly higher at maintenance phase than at initiation and termination phases. It was also found that elevation of trehalose, glucose, and glycerol contents occurred in winter. These implies that the metabolites with altered levels in diapausing larvae of C. chuxiongica are responsible for maintaining a prolonged development and overwintering.     

Conceptual Method of Temperature Sensation in Bionic Hand by Extraordinary Perceptual Phenomenon

Lack of temperature sensation of myoelectric prosthetic hand limits the daily activities of amputees.To this end,a non-invasive temperature sensation method is proposed to train amputees to sense temperature with psychophysical sensory substitution.In this study,22 healthy participants took part besides 5 amputee participants.The duration time of the study was 31 days with five test steps according to the Leitner technique.An adjustable temperature mug and a Peltier were used to change the temperature of the water/phantom digits to induce temperature to participants.Also,to isolate the surround-ings and show colors,a Virtual Reality(VR)glass was employed.The statistical results conducted are based on the response of participants with questionnaire method.Using Chi-square tests,it is concluded that participants answer the experiment significantly correctly using the Leitner technique(P value＜0.05).Also,by applying the"Repeated Measures ANOVA",it is noticed that the time of numbness felt by participants had significant(P value＜0.001)difference.Participants could remember lowest and highest temperatures significantly better than other temperatures(P value＜0.001);furthermore,the well-trained amputee participant practically using the prosthesis with 72.58％could identify object's temperature with only once time experimenting the color temperature.     

A novel dominant-negative PD-1 armored anti-CD19 CAR T cell is safe and effective against refractory/relapsed B cell lymphoma

Refractory/relapsed B cell lymphoma patients who received the available anti-CD19 chimeric antigen receptor (CAR) T cells may still experience a short duration of remission. Here in this study, we evaluated the safety and efficacy of a novel dominant-negative programmed cell death-1 (PD-1) armored anti-CD19 CAR T cells. A total of 9 patients (including 4 diffuse large B cell lymphomas, DLBCL, 2 transformed follicular lymphomas, TFL, and 3 follicular lymphomas, FL) received the novel CAR T cells infusion at a dose of more than 1 × 10⁶/kg. Grade ≥ 3 cytokine release syndrome (CRS) and neurotoxicity were observed in 11.1% (n = 1/9) and 11.1% (n = 1/9) of patients, respectively. The overall response rate (ORR) was 77.8% (n = 7/9) and complete response (CR) rate was 55.6% (n = 5/9). Two patients have ongoing CR (all at 20+ months). CAR T cells expanded after infusion and continued to be detectable at 12+ months in patients with ongoing CR. This novel CD19-CAR T cell was safe and effective with durable remissions in patients with refractory/relapsed B cell lymphoma.     

Epidemiological and clinical features in patients with coronavirus disease 2019 outside of Wuhan,China: Special focus in asymptomatic patients

ObjectivesIn December 2019, coronavirus disease 2019 (COVID-19) emerged in Wuhan City and rapidly spread across the world. The clinical characteristics of affected patients in different regions and populations may differ. Thus, this study aimed to identify the characteristics of the disease to provide an insight about the prevention and treatment of COVID-19.MethodsData on the demographic characteristics and clinical findings of the patients admitted at the First Hospital of Changsha from January 1, 2020 to February 10, 2020 were assessed.ResultsIn this study, there were 8 (3.8%) asymptomatic, 21 (10.0%) mild upper respiratory tract infection (URTI), and 180 (86.1%) pneumonia cases. In total, 47 (22.5%) patients resided in Wuhan, and 45 (21.5%) had recently traveled to Wuhan before disease onset. Moreover, 19 (9.1%) had contact with people from Wuhan, and 69 (33.0%) were family cluster cases. The median incubation period was approximately 6.3 (range: 1.0–20.0) days. Fever and cough were the most common initial symptoms: 99 (49.3%) patients presented with fever, without cough; 59 (29.4%) with cough, without fever; and 33 (16.4%) with both fever and cough.ConclusionThe symptoms of patients with COVID-19 were relatively mild outside Wuhan, and family cluster was a remarkable epidemic characteristic. Special attention should be paid to asymptomatic patients.     

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.     

Blockade of JAK2 signaling produces immunomodulatory effect to preserve pancreatic homeostasis in severe acute pancreatitis

JAK/STAT plays an important role in cytokine signal transduction and it is potentially involved in the proinflammatory response during the early phase of severe acute pancreatitis (SAP). However, whether JAK2 activity is upregulated and whether JAK2 inhibition plays a role in the maintenance of pancreatic homeostasis during SAP is incompletely understood. Here we show that JAK2/STAT3 activity is highly elevated in SAP and blockade of JAK2 by AG-490 protects against SAP-induced pancreatic inflammation and injury. Gene expression and ELISA studies showed that JAK2 inhibition altered the cytokine profiles in both the circulation and pancreases. Further analysis revealed that JAK2 inhibition restored the level of cytokines critical for macrophage polarization towards M2 macrophage. Our findings suggest that pharmacological targeting at JAK2/STAT signalling may be an effective choice of therapeutic interventions against SAP.     

模拟氮沉降对长白山苔原灌草混合群落中植物光合特性的影响

由于草本植物持续上侵长白山灌木苔原,形成了强烈的灌草群落种间竞争。本研究以牛皮杜鹃-小叶章群落（Comm.Rhododendron aureum-Deyeuxia purpurea）为对象,根据小叶章的入侵程度设置4种盖度差异显著的样方（无、轻度、中度、重度入侵）,并设3个施氮水平（自然状态、添加11.8 kgN·hm^-2·a^-1及添加23.6 kgN·hm^-2·a^-1）,进行原位氮沉降模拟实验,监测灌木牛皮杜鹃和草本植物小叶章光合特性的差异和变化趋势,研究小叶章入侵苔原带的内在生理机制。结果显示：（1）小叶章净光合速率大于牛皮杜鹃,小叶章盖度越高、其叶绿素含量越高,而牛皮杜鹃叶绿素含量降低,随着小叶章入侵程度的增加,其净光合速率增强;（2）施氮可以提高牛皮杜鹃和小叶章的叶绿素含量和净光合速率,促进植物生长,但小叶章的增幅更大,从而增强了小叶章的竞争优势;（3）施氮和小叶章入侵具有复合作用,小叶章盖度越大,对其施氮导致小叶章净光合速率与叶绿素含量的增幅越大,而牛皮杜鹃的增幅减小。所以小叶章的成功入侵可能与其具有较高的净光合速率有关,并且施氮有利于提高小叶章的净光合速率,随着氮沉降的继续增加,更有利于小叶章的生长并提高其竞争力。