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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced cytokine storm is closely associated with coronavirus disease 2019 (COVID-19) severity and lethality. However, drugs that are effective against inflammation to treat lethal COVID-19 are still urgently needed. Here, we constructed a SARS-CoV-2 spike protein-specific CAR, and human T cells infected with this CAR (SARS-CoV-2-S CAR-T) and stimulated with spike protein mimicked the T-cell responses seen in COVID-19 patients, causing cytokine storm and displaying a distinct memory, exhausted, and regulatory T-cell phenotype. THP1 remarkably augmented cytokine release in SARS-CoV-2-S CAR-T cells when they were in coculture. Based on this “two-cell” (CAR-T and THP1 cells) model, we screened an FDA-approved drug library and found that felodipine, fasudil, imatinib, and caspofungin were effective in suppressing the release of cytokines, which was likely due to their ability to suppress the NF-κB pathway in vitro. Felodipine, fasudil, imatinib, and caspofungin were further demonstrated, although to different extents, to attenuate lethal inflammation, ameliorate severe pneumonia, and prevent mortality in a SARS-CoV-2-infected Syrian hamster model, which were also linked to their suppressive role in inflammation. In summary, we established a SARS-CoV-2-specific CAR-T-cell model that can be utilized as a tool for anti-inflammatory drug screening in a fast and high-throughput manner. The drugs identified herein have great potential for early treatment to prevent COVID-19 patients from cytokine storm-induced lethality in the clinic because they are safe, inexpensive, and easily accessible for immediate use in most countries.

Objective To study the effect of borneol combined with astragaloside IV and Panax notoginseng saponins (BAP) on promoting neurogenesis by regulating microglia polarization after cerebral ischaemia–reperfusion(CI/R) in rats. Methods A focal CI/R injury model was established. Evaluated the effects of BAP on ischaemic brain injury, on promoting neurogenesis, on inhibiting Inflammatory microenvironment and TLR4/MyD88/NFκB signalling pathway. A microglia oxygen-glucose deprivation reoxygenation (OGD/R) model was established that evaluated the effects of BAP on regulating the polarization of microglia and inflammatory microenvironment. Results BAP can inhibit the expression of TLR4, MyD88 and NFκB proteins, reduce IL-1β and increase IL-10, reduce M1 type microglia and increase M2 microglia. The proliferation of neural stem cells increased, synaptic gap decreased, synaptic interface curvature increased, expression of SYN and PSD95 proteins increased, which improved the neurological dysfunction and reduced the volume of cerebellar infarction and nerve cell injury. Conclusion BAP can reduce CI/R injury and promote neurogenesis, the effect is related to inhibition of the activation of TLR4/MyD88/NFκB, regulating the polarization of microglia from M1 type to M2 type and inhibition of inflammatory response.

Noble metal nanomaterials have many excellent optical properties due to localized surface plasmon resonance induced by external electric and magnetic fields. The plasmon-enhanced optical properties of nanomaterials can be controlled by changing their shapes or compositions. Here, we use a gentle approach to synthesize Au/PbS/Au nanostars with multiple tips and explore the surface-enhanced Raman scattering (SERS) activity, the second harmonic generation (SHG), and photocatalytic performance. The Au/PbS/Au nanostars have ultrabroad spectral responses and significantly enhanced local electric fields near the sharp tips. The size and tip length of the Au/PbS/Au nanostars can be adjusted by changing the amount of HAuCl

Third-generation cephalosporins (3rd GCs) have recently become controversial as the first-line strategy for empirical spontaneous bacterial peritonitis (SBP) treatment. This study aimed to identify SBP treatment efficacy predictors of 3rd GCs.In this retrospective cohort study, 279 cirrhosis patients with SBP who received 3rd GC monotherapy for initial empirical treatment from 2013 to 2019 were included. Nonresponse was defined as a decreased ascites polymorphonuclear (PMN) count25% from baseline after 48 hours of antibacterial treatment. Multivariate regression analysis was used to identify efficacy predictors of 3rd GCs in treating SBP. Kaplan-Meier analysis was used to evaluate survival data.The nonresponder group included 120 patients with no response, and the responder group included 159 patients with responses. The response rate to 3rd GCs was 57.0% among all patients. The common pathogens were Escherichia coli (40.6%), Staphylococcus (15.6%), Klebsiella pneumonia (12.5%), and Streptococcus (12.5%) in 32 ascites culture isolates. Nosocomial SBP (NSBP) (odds ratio [OR]: 2.371, 95% confidence interval [CI]: 1.323-4.249, P = .004), pneumonia (OR: 11.561, 95% CI: 1.876-71.257, P = .008), recurrent SBP (OR: 3.386, 95% CI: 1.804-6.357, P.001), platelet count (≥113.5 × 109/L) (OR: 3.515, 95% CI: 1.973-6.263, P.001), and ascites PMN count (≤0.760 × 109/L) (OR: 4.967, 95% CI: 2.553-9.663, P.001) were independent predictors of nonresponse to 3rd GCs against SBP. Survival plot analysis at 30 days showed worse survival for the nonresponders (P = .003).NSBP, pneumonia, recurrent SBP, increased platelet count, and lower ascites PMN count were independent predictors of nonresponse to 3rd GC in treating SBP. Nonresponse to initial antibiotic treatment was associated with worse survival.

In order to improve the performance of power knowledge text mining,FP-Growth algorithm is used to mine the strong correlation factors that affect the power demand,and GRNN algorithm is used to realize the power demand forecasting.Firstly,the index of the power text to be mined is extracted and encoded to generate the initial FP-Tree.Then,FP-Growth algorithm traverses all FP-Tree generated frequent sets,filters out the items less than the minimum support,leaves the frequent items with higher frequency.And then according to the updated FP-Tree statistical correlation items,it selects variables with strong correlation with the growth rate of total electricity consumption to generate training samples.Finally,the GRNN algorithm is used to train the power demand text,input the power demand forecasting samples,set the smoothing factor,and obtain the power demand forecasting results through the output and weighted sum of the mode layer.Experimental results show that better power text mining performance can be obtained by setting the minimum support and the smoothing factor of GRNN.Compared with common mining algorithms,this algorithm can obtain higher accuracy of power demand forecasting.

Establishing API mappings between third-party libraries is a prerequisite step for library migration tasks. Manually establishing API mappings is tedious due to the large number of APIs to be examined. Having an automatic technique to create a database of likely API mappings can significantly ease the task. Unfortunately, existing techniques either adopt supervised learning mechanism that requires already-ported or functionality similar applications across major programming languages or platforms, which are difficult to come by for an arbitrary pair of third-party libraries, or cannot deal with lexical gap in the API descriptions of different libraries. To overcome these limitations, we present an unsupervised deep learning based approach to embed both API usage semantics and API description (name and document) semantics into vector space for inferring likely analogical API mappings between libraries. Based on deep learning models trained using tens of millions of API call sequences, method names and comments of 2.8 millions of methods from 135,127 GitHub projects, our approach significantly outperforms other deep learning or traditional information retrieval (IR) methods for inferring likely analogical APIs. We implement a proof-of-concept website ( https://similarapi.appspot.com ) which can recommend analogical APIs for 583,501 APIs of 111 pairs of analogical Java libraries with diverse functionalities. This scale of third-party analogical-API database has never been achieved before.

The $\alpha$-R\'enyi entropy in the gapless models have been obtained by the conformal field theory, which is exact in the thermodynamic limit. However, the calculation of its finite size effect (FSE) is challenging. So far only the FSE in a single interval in the XX model has been understood and the FSE in the other models and in the other conditions are totally unknown. Here we report the FSE of this entropy in disjointed intervals $A = \cup_i A_i$ under a uniform dilation $\lambda A$ in the XY model, showing of a universal scaling law as \begin{equation*} \Delta_{\lambda A}^\alpha = \Delta_A^\alpha \lambda^{-\eta} \mathcal{B}(A, \lambda), \end{equation*} where $|\mathcal{B}(A, \lambda)| \le 1$ is a bounded function and $\eta = \text{min}(2, 2/\alpha)$ when $\alpha < 10$. We verify this relation in the phase boundaries of the XY model, in which the different central charges correspond to the physics of free Fermion and free Boson models. We find that in the disjointed intervals, two FSEs, termed as extrinsic FSE and intrinsic FSE, are required to fully account for the FSE of the entropy. Physically, we find that only the edge modes of the correlation matrix localized at the open ends $\partial A$ have contribution to the total entropy and its FSE. Our results provide some incisive insight into the entanglement entropy in the many-body systems., Comment: Comments are welcome

Nitrogen-containing porous carbon fibers with large BET surface area (919~1625 m2/g) and pore volume (0.429~0.772 cm3/g) were developed from polyimide fiber, which was treated in the presence of po...

Shuanglong Xiong, Dairong Li, Donglin Wang, Lumi Huang, Guanzhong Liang, Zhijuan Wu, Jianlin Long, Dan Yang, Yan Teng, Shuangyi Lei, Yan Li Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital and Chongqing Cancer Institute and Chongqing Cancer Hospital, Chongqing, People’s Republic of ChinaCorrespondence: Yan LiChongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital and Chongqing Cancer Institute and Chongqing Cancer Hospital, No. 181, Hanyu Road, Shapingba District, Chongqing 400030, People’s Republic of ChinaEmail liyandrmed1101@163.comIntroduction: Circular RNAs (circRNAs) are deregulated in many types of human cancers, including non-small cell lung cancer (NSCLC). In this study, we aimed to explore the functional role of circMYLK in NSCLC.Materials and Methods: The expression levels of circMYLK and miR-195-5p in NSCLC tissues and cell lines were detected by RT-qPCR analysis. MTT assay, colony formation assay and transwell assay were performed to investigate the effects of circMYLK and miR-195-5p on the malignant phenotypes of NSCLC cells. The glucose consumption and lactate production of NSCLC cells were detected using commercial kits. The direct binding relation between circMYLK and miR-195-5p in NSCLC was predicted by bioinformatics analysis and validated by dual-luciferase reporter assay.Results: The results showed that circMYLK was significantly up-regulated in NSCLC tissues and cell lines, and its high expression was closely associated with deleterious clinicopathological characteristics and poor prognosis of NSCLC patients. Knockdown of circMYLK remarkably inhibited the malignant phenotypes of NSCLC cells, including proliferation, migration, invasion, glucose consumption and lactate production. Moreover, circMYLK was identified as a molecule sponge for miR-195-5p, and glucose transporter member 3 (GLUT3) was shown to be a target gene of miR-195-5p in NSCLC. Further rescue experiments revealed that the oncogenic effects of circMYLK on NSCLC cells could be largely abrogated by co-transfection with miR-195-5p mimic.Conclusion: In summary, our study provides convincing evidence that circMYLK serves as a tumor promoter in NSCLC and can be used as a potential therapeutic target for NSCLC patients.Keywords: non-small cell lung cancer, circular RNA MYLK, miR-195-5p, glycolysis, glucose transporter member 3

To understand the influence of lignin characteristics on their antioxidant activities, lignins were isolated from Broussonetia papyrifera by organosolv pretreatment at different temperatures. The physicochemical features of the lignins were investigated by GPC, 31P NMR and 2D HSQC NMR analyses. An increase of organosolv pretreatment temperature resulted in a decrease of Mw and an increase of the phenolic hydroxyl group content in the isolated lignin. The lignins extracted at higher organosolv pretreatment temperature showed higher antioxidant activity according to the IC50 determined using DPPH and ABTS. The correlations between the physicochemical properties of organosolv lignins and their antioxidant activities were studied. The contents of phenolic hydroxyl groups, especially syringyl and guaiacyl, and double bonds in the Cα position had positive effects on the antioxidant activity of the lignins. On the other hand, Mw and aliphatic hydroxyl groups of the lignins exhibited negative correlations with the antioxidant activity.

Electroslag casting (ESC) is an important method to produce high quality castings. In this study, the ESC up-pulling inner mold method (EUPIM) was used to produce hollow cylindrical castings with the multiple consumable electrodes. The radial deformation, the axial and radial internal stress of the inner mold, and the axial internal stress of the slag shell were analyzed using the finite element method (FEM) with the aid of ANSYS software. The ProCAST software was used to calculate the specific heat, heat conductivity and density curve of Cu. Simulation results show that the radial deformation, the axial and radial internal stress of the inner mold, and the axial internal stress of the slag shell near the slag-metal interface of hollow cylndrical casting gradually increase from 0 s to 360 s after the ESC starting (slagging) process but before applying the up-pulling force. The suitable initial up-pulling moment of the inner mold is at around 180–198 s after the starting process.

Antibody therapeutics for the treatment of COVID-19 has been highly successful while faces a challenge of the recent emergence of the Omicron variant which escapes the majority of existing SARS-CoV-2 neutralizing antibodies (nAbs). Here, we successfully generated a panel of SARS-CoV-2/SARS-CoV cross-neutralizing antibodies by sequential immunization of the two pseudoviruses. Of which, nAbs X01, X10 and X17 showed broadly neutralizing breadths against most variants of concern (VOCs) and X17 was further identified as a Class 5 nAb with undiminished neutralization against the Omicron variant. Cryo-EM structures of three-antibody in complex with the spike proteins of prototyped SARS-CoV-2, Delta, Omicron and SARS-CoV defined three non-overlapping conserved epitopes on the receptor-binding domain (RBD). The triple antibody cocktail exhibited enhanced resistance to viral escape and effective protection against the infection of Beta variant in hamsters. Our finding will aid the development of both antibody therapeutics and broad vaccines against SARS-CoV-2 and emerging variants.

At the beginning of 2020, COVID-19 swept the world and changed various aspects of human society, such as economy and finance, life and health, migration and population. We first empirically study how the dynamic behaviors of stock markets are affected by COVID-19, and focus on the large volatility dynamics, variation-fluctuation correlation function and epidemic-fluctuation correlation function. Then we generalize the Heston model to simulate the global stock market dynamics, and an epidemic index computed from empirical data is directly taken as the external force in the modelling.

ObjectiveCurrent pharmacological intervention for the cancer-related pain is still limited. The aim of this study was to explore whether repetitive transcranial magnetic stimulation (rTMS) could be an effective adjuvant therapy to reduce pain in patients with advanced non-small cell lung cancer (NSCLC).MethodsThis was a randomized, sham–controlled study. A total of 41 advanced NSCLC patients with uncontrolled pain (score≥4 on pain intensity assessed with an 11-point numeric rating scale) were randomized to receive active (10 Hz, 2000 stimuli) (n = 20) or sham rTMS (n = 20) for 3 weeks. Pain was the primary outcome and was assessed with the Numeric Rating Scale (NRS). Secondary outcomes were oral morphine equivalent (OME) daily dose, quality of life (WHO Quality of Life-BREF), and psychological distress (the Hospital Depression and Anxiety Scale). All outcomes were measured at baseline, 3 days, 1 week, 2 weeks, and 3 weeks.ResultsThe pain intensity in both groups decreased gradually from day 3 and decreased to the lowest at the week 3, with a decrease rate of 41.09% in the rTMS group and 23.23% in the sham group. The NRS score of the rTMS group was significantly lower than that of the sham group on the week 2 (p < 0.001, Cohen’s d =1.135) and week 3 (p=0.017, Cohen’s d = -0.822). The OME daily dose, physiology and psychology domains of WHOQOL-BREF scores, as well as the HAM-A and HAM-D scores all were significantly improved at week 3 in rTMS group.ConclusionAdvanced NSCL patients with cancer pain treated with rTMS showed better greater pain relief, lower dosage of opioid, and better mood states and quality of life. rTMS is expected to be a new effective adjuvant therapy for cancer pain in advanced NSCLC patients.

A complication is an unanticipated disease arisen following, induced by a disease, a treatment or a procedure. We compile the Human Disease-Complication Network from the medical data and investigate the characteristics of the network. It is observed that the modules of the network are dominated by the classes of diseases. The relations between modules are unveiled in detail. Three nontrivial motifs are identified from the network. We further simulate the dynamics of motifs with the Boolean dynamic model. Each motif represents a specific dynamic behavior, which is potentially functional in the disease system, such as generating temporal progressions and governing the responses to fluctuating external stimuli.Author summaryAdvances in molecular biology lead to a new discipline of network medicine, investigating human diseases in a networked structure perspective. Recently, clinical records have been introduced to the research of complex networks of diseases. An important available medical dataset that has been overlooked so far is the complications of diseases, which are vital for human beings. We compile the Human Disease-Complication Network, representing the causality between the upstream diseases and their downstream complications. This work not only helps us to comprehend why certain groups of diseases appear collectively, but also provides a new paradigm to investigate the dynamics of disease progression. For clinical applications, the investigation of complications may yield new approaches to disease prevention, diagnosis and treatment.

The emergence of numerous variants of SARS-CoV-2, the causative agent of COVID-19, has presented new challenges to the global efforts to control the still ravaging COVID-19 pandemic. Here, we obtain two cross-neutralizing antibodies (7D6 and 6D6) that target Sarbecoviruses’ receptor binding domain (RBD) with sub-picomolar affinities and potently neutralize authentic SARS-CoV-2. Crystal structures show that both antibodies bind a cryptic site different from that recognized by existing antibodies and highly conserved across Sarbecovirus isolates. Binding of these two antibodies to the RBD clashes with the adjacent N-terminal domain and disrupts the viral spike. Significantly, both antibodies confer good mutation resistance to the currently circulating SARS-CoV-2 variants. Thus, our results have direct relevance to public health as options for passive antibody therapeutics and even active prophylactics, and can also inform the design of pan-sarbecovirus vaccines.

Nitrogen-enriched porous carbon fibers were successfully prepared by one-step carbonization–activation treatment of oxidized polyacrylonitrile fibers. Utilizing the low-temperature carbonization an...