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Direct-acting antiviral (DAA) treatment for 8 weeks has a sustained virological response rate in adults with chronic hepatitis C. We have conducted a systematic review and meta-analysis to compare the efficacy and safety of the 8-week vs. 12/24-week DAA treatment in adolescents and children with CHC. The PubMed, Web of Science, and Cochrane databases were searched for the relevant articles from January 1, 2017 to August 28, 2020 and further screened for literature reviews on April 1, 2021. Pool proportions with 95% CIs for SVR12 were summarized with fixed/random effects models using Freeman–Tukey double arcsine transformation. Subgroup analysis was used to explore the source of heterogeneity. Thirty-six relevant publications were identified. For adolescents aged 12–17 years old, the pooled SVR12 and AE rate were 99.4% (95% CI: 98.7–99.9) and 34.7% (95% CI: 31.9–37.6). No one discontinued treatment due to drug intolerance. In addition, the SVR12 adolescents treated for 12 and 8/24 weeks were 99.3% (95% CI: 98.4–99.9) and 100%, respectively. The pooled SVR12 rate, AEs, and SAEs for children younger than 12 years were 98.9% (95% CI: 97.3–99.8), 51.6% (95% CI: 47.0–56.2), and 1.1% (95% CI: 0.4–2.5), respectively. The most common AE was fatigue (28.4%). The SVR12 was 98.8% (95% CI: 97.1–99.8) and 100% for the pediatric patients treated for 12 weeks and 8/24 weeks, respectively. Taken together, DAAs are generally effective against CHC and well-tolerated by the adolescents and children. A treatment duration of 8 weeks is equally effective and safe as 12/24 weeks in this demographic group.

Summary: Naive human embryonic stem cells (hESCs) have been isolated that more closely resemble the pre-implantation epiblast compared to conventional “primed” hESCs, but the signaling principles underlying these discrete stem cell states remain incompletely understood. Here, we describe the results from a high-throughput screen using ∼3,000 well-annotated compounds to identify essential signaling requirements for naive human pluripotency. We report that MEK1/2 inhibitors can be replaced during maintenance of naive human pluripotency by inhibitors targeting either upstream (FGFR, RAF) or downstream (ERK1/2) kinases. Naive hESCs maintained under these alternative conditions display elevated levels of ERK phosphorylation but retain genome-wide DNA hypomethylation and a transcriptional identity of the pre-implantation epiblast. In contrast, dual inhibition of MEK and ERK promotes efficient primed-to-naive resetting in combination with PKC, ROCK, and TNKS inhibitors and activin A. This work demonstrates that induction and maintenance of naive human pluripotency are governed by distinct signaling requirements.

BackgroundKIR/HLA-C signaling pathway influences the innate immune response which is the first defense to hepatitis C virus (HCV) infection. The aim of this study was to determine the association between the genetic polymorphisms of KIR/HLA-C genes and the outcomes of HCV infection in a high-risk Chinese population.MethodsIn this case-control study, four single nucleotide polymorphisms (SNPs) of KIR/HLA-C genes (KIR2DS4/KIR2DS1/KIR2DL1 rs35440472, HLA-C rs2308557, HLA-C rs1130838, and HLA-C rs2524094) were genotyped by TaqMan assay among drug users and hemodialysis (HD) patients including 1,378 uninfected control cases, 307 subjects with spontaneous viral clearance, and 217 patients with persistent HCV infection. Bioinformatics analysis was used to functionally annotate the SNPs.ResultsAfter logistic regression analysis, the rs35440472-A and rs1130838-A alleles were found to be associated with a significantly elevated risk of HCV infection (OR = 1.562, 95% CI: 1.229–1.987, P < 0.001; OR = 2.134, 95% CI: 1.180–3.858, P = 0.012, respectively), which remained significant after Bonferroni correction (0.05/4). The combined effect of their risk alleles and risk genotypes (rs35440472-AA and rs1130838-AA) were linked to the increased risk of HCV infection in a locus-dosage manner (all Ptrend < 0.001). Based on the SNPinfo web server, rs35440472 was predicted to be a transcription factor binding site (TFBS) while rs1130838 was predicted to have a splicing (ESE or ESS) function.ConclusionKIR2DS4/KIR2DS1/KIR2DL1 rs35440472-A and HLA-C rs1130838-A variants are associated with increased susceptibility to HCV infection in a high-risk Chinese population.

Abstract Background Primary Sjögren’s syndrome (pSS) is an autoimmune disorder mainly characterized by exocrine gland injury. Costimulatory molecules play an important role in immune-regulatory networks. Although B7 family costimulatory molecules were previously discovered in human salivary gland epithelial (HSGE) cells in pSS, the effects of the B7 family member B7-H3 (CD276) have not been well elucidated. Thus, this study aimed to investigate the role and mechanism of B7-H3 in HSGE cells in pSS. Methods The expression of B7-H3, B7-H1, PD-1 in serum, saliva and salivary gland were examined by immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA). Immunofluorescence was used to test the expression and distribution of B7-H3, AQP5 and CK-8 in salivary gland tissues. Flow cytometry, Cell Counting Kit 8 (CCK-8) and western blot (WB) were performed to research the apoptotic, proliferative and inflammatory effects of B7-H3 in primary HSGE cells and HSGE cell lines. Results Our results showed that the expression of PD-1, B7-H1 and B7-H3 in peripheral blood, and salivary glands in pSS patients was higher than that in healthy controls, which was positive correlation with the grade of the salivary glands. The expression of B7-H3 in saliva was higher in pSS patients than that in healthy controls, which was detected with the most significant difference of them. The expression of B7-H3 in primary HSGE cells of pSS patients was significantly higher than healthy controls. B7-H3 increased activity of NF-κB pathway and promoted inflammation of HSGE cells, decreasing the expression of AQP5. Furthermore, B7-H3 overexpression inhibited proliferation and induced apoptosis in HSGE cell lines. Conclusion B7-H3 could promote inflammation and induce apoptosis of HSGE cells by activating NF-κB pathway, which might be a promising therapeutic target for pSS.

Abstract Background Varicella-zoster virus (VZV) infection in children is an important public health problem in China. We performed the current study to explore the seroprevalence of VZV infection in Chinese children in order to provide more information for improvement of varicella vaccination in China. Methods Three thousand fourteen children were recruited from Chinese kindergarten students aged from four to six years. Anti-VZV IgG and IgM were assayed using enzyme-linked immunosorbent assay. Both ORF22 and ORF62 of VZV were amplified, sequenced, and analyzed by nested PCR. Results Among 3014 children, 43.9% of boys and 46.3% of girls were vaccinated with varicella vaccine, respectively. The seroprevalence of anti-VZV IgG was 54.4% in the children with varicella vaccination, which was significantly higher than those in unvaccinated children (49.2%) (χ2 = 8.206, P = 0.004). Among of the vaccinated children, the detection rates of VZV IgG antibody increased with age, with 49.4, 50.9 and 58.9% in 4, 5 and 6-year groups, respectively (Trend χ2 = 17.202, P = 0.002). However, there was no difference in anti-VZV IgG detection rates among those unvaccinated children in different age groups (Trend χ2 = 8.681, P = 0.070). In addition, 13 boys and 13 girls were positive for anti-VZV IgM, respectively. Among of them, eight children (0.6%) have received varicella vaccination, which was similar to those in unvaccinated children (1.1%). However, only one ORF22 sequence was isolated from an unvaccinated 5-year boy. Compared to the reference VZV sequences, the nucleotide homology was estimated to be 99.7% with genotype J. Conclusions Our study indicated that about half of Chinese children aged four to six years have a high risk of VZV infection. It should be helpful for the evaluation on the necessity of varicella immunization in China.

Nonalcoholic fatty liver disease is currently the most common liver disease and is a leading cause of liver‐related morbidity and mortality. However, its pathogenesis remains largely unclear. We previously showed that mice deficient in mitogen‐activated protein kinase (MAPK) phosphatase 5 (MKP5) spontaneously developed insulin resistance and glucose intolerance, which are associated with visceral obesity and adipose tissue inflammation. In this study, we discovered that mice deficient in MKP5 developed more severe hepatic steatosis and steatohepatitis with age or with feeding on a high‐fat diet (HFD) compared to wild‐type (WT) mice, and this was associated with increased expression of proinflammatory cytokines and collagen genes. Increased p38 activation in MKP5 knockout (KO) liver compared to that in WT liver was detected, which contributed to increased expression of lipid droplet‐associated protein cell death‐inducing DFF45‐like effector A (CIDEA) and CIDEC/fat‐specific protein 27 but not CIDEB through activating transcription factor 2 (ATF2). In addition, MKP5 KO liver had higher peroxisome proliferator‐activated receptor gamma (PPARγ) expression compared with WT liver. On the other hand, overexpression of MKP5 or inhibition of p38 activation in hepatocytes resulted in reduced expression of PPARγ. Inhibition of p38 resulted in alleviation of hepatic steatosis in KO liver in response to HFD feeding, and this was associated with reduced expression of CIDEA, CIDEC, and proinflammatory cytokines. Conclusion: MKP5 prevents the development of nonalcoholic steatohepatitis by suppressing p38–ATF2 and p38–PPARγ to reduce hepatic lipid accumulation, inflammation, and fibrosis.

Ultraviolet-visible and nuclear magnetic resonance (NMR) spectroscopy was used to investigate the effects of pH, solvent and temperature on the tautomeric equilibrium of selaginellins from Selaginella. The results demonstrated that the tautomerism of selaginellins could be catalyzed by acid, base and protic solvent. Variable-temperature 1H NMR experiments demonstrated that the tautomerism was interrupted when the temperature fell below 233 K.

Though organic light-emitting diodes (OLEDs) with electroluminescence at sub-bandgap voltages have been reported, realizing high efficiency in such a device is difficult. Here, the authors report high efficiency sub-bandgap OLEDs featuring organic molecules with large singlet-triplet splitting.

Background: Innate lymphoid cells (ILCs) are a newly discovered family of immune cells that have similar cytokine-secreting profiles as T helper cell subsets. Although ILCs are critical for host defense against infections and tissue homeostasis, their roles in tumor development are not well established. Methods: We studied the function of ILC3 cells in the liver for the development of hepatocellular carcinoma (HCC) in murine HCC models using flow cytometry, adoptive transfer, and in vitro functional assays. Findings: We found that ILC3 lacking the natural cytotoxicity-triggering receptor (NCR−ILC3) promoted the development of HCC in response to interleukin 23 (IL-23). IL-23 serum level is elevated in HCC patients and its high expression is associated with poor clinical outcomes. We found that IL-23 could promote tumor development in murine HCC tumor models. IL-23 promoted the expansion of NCR−ILC3 and its differentiation from group 1 ILCs (ILC1s). Furthermore, NCR−ILC3 initiated IL-17 production upon IL-23 stimulation and directly inhibited CD8+ T cell immunity by promoting lymphocyte apoptosis and limiting their proliferation. Interpretation: Together, our findings suggest that NCR−ILC3 initiates the IL-17-rich immunosuppressive tumor microenvironment and promotes the development of HCC, thus may serve as a promising target for future cancer immunotherapy. Fund: This work was supported by grants from National Natural Science Foundation of China (81471586, 81571556), the Priority Academic Program Development of Jiangsu Higher Education Institutions, the collaborative Innovation Center of Hematology, start-up grant from National University of Singapore, the Cancer Prevention and Research Institute of Texas CPRIT (RR180017), and the National Cancer Institute's Cancer Center Support (Core) Grant CA016672 (to The University of Texas MD Anderson Cancer Center). Keywords: IL-23, IL-17, ILC, Tumor microenvironment, HCC

Piezoresistive acceleration sensors are widely used in various fields of the industrial Internet of Things because of their lightweight, fast response, and small size. The structural sensitivity of the sensor affects the accuracy of the measurement. And the sensitivity that the traditional method designs are only a feasible solution, not an optimal solution. Due to the differences in factory processes, the optimization of structural sensitivity is an NP-hard problem. To solve the design problem of structural sensitivity, we adopt the swarm intelligence algorithm in this paper, and we design a model for the structural sensitivity of the piezoresistive acceleration sensor. In addition, an improved grasshopper optimization algorithm (CC-GOA) that combines chaos strategy and Cauchy mutation is proposed to optimize the structural sensitivity of the piezoresistive acceleration sensor, and the structure of the sensor is composed of four beams and mass block. The experiments are compared with six well-known algorithms on 16 benchmark functions to verify the algorithm performance of CC-GOA, and then, the structural sensitivity of the piezoresistive acceleration sensor is optimized by CC-GOA. The results indicate that the piezoresistive acceleration sensor is designed with high sensitivity and superiority.

Since integrated circuits are performed by several untrusted manufacturers, malicious circuits (hardware Trojans) can be implanted in any stage of the Internet-of-Things (IoT) devices. With the globalization of the IoT device manufacturing technologies, protecting the system-on-chip (SoC) security is always the keys issue for scientists and IC manufacturers. The existing SoC high-level synthesis approaches cannot guarantee both register-transfer-level and gate-level security, such as some formal verification and circuit characteristic analysis technologies. Based on the structural characteristics of hardware Trojans, we propose a multi-layer hardware Trojan protection framework for the Internet-of-Things perception layer called RG-Secure, which combines the third-party intellectual property trusted design strategy with the scan-chain netlist feature analysis technology. Especially at the gate level of chip design, our RG-Secure is equipped with a distributed, lightweight gradient lifting algorithm called lightGBM. The algorithm can quickly process high-dimensional circuit feature information and effectively improve the detection efficiency of hardware Trojans. In the meanwhile, a common evaluation index F-measure is used to prove the effectiveness of our method. The experiments show that RG-Secure framework can simultaneously detect register-transfer-level and gate-level hardware Trojans. For the trust-HUB benchmarks, the optimized lightGBM classifier achieves up to 100% true positive rate and 94% true negative rate; furthermore, it achieves 99.8% average F-measure and 99% accuracy, which shows a promising approach to ensure security during the design stage.

With the development of science and technology, the accuracy requirements for solving engineering problems are getting stricter than before. Most structural design optimization problems in civil and mechanical engineering have proven to be the non-deterministic polynomial hard problems. The artificial bee colony (ABC) algorithm has been proven to be an effective method of design optimization problems. This paper proposes an improved ABC algorithm (DSM-ABC) combined with dual-search mechanism containing Lévy flight and differential self-perturbation and applies it to three classical structural design problems, including cantilever beam design, gear train design, and three-bar truss design. The experimental results of benchmark functions from CEC2005 reveal that the proposed DSM-ABC algorithm accelerates the convergence and improves the performance. Eventually, the obtained results of optimization structural design problems prove that the DSM-ABC algorithm has a strong superiority compared with the state-of-the-art algorithms in solving optimization engineering design problems.

Salp swarm algorithm is a new meta-heuristic algorithm which has excellent advantages for solving the multidimensional optimization problem. In this paper, a hybrid model assisted evolutionary algorithm for solving engineering design optimization problems is proposed and investigated. The purpose of the optimizer is to improve the potential shortcomings of the basic salp swarm optimization, including trapping in local or deceptive optima easily. On the one hand, quantum behavior can increase an individual's searchability, which can promote the overall optimization trend. On the other hand, the elite opposition-based learning strategy is used to enhance the diversity of the population. Besides, mutation mechanism is introduced to prevent the individuals of the population from being in stagnation behavior. The proposed quantum-behaved and wavelet mutation salp swarm algorithm (QSSA) is applied on twenty-three benchmark functions and three basic constrained engineering problems. Experimental results demonstrate that the algorithm has excellent solution quality, and it can overcome the defect of the low convergence rate.

Recently, there are various methods for detecting the hardware trojans (HTs) in the integrated circuits (ICs). The circuit's logic representations of different types, structures, and functional characteristics should be different. Each type of circuit has its' own performance characteristics according to its' purpose. However, the traditional HTs detection methods adopt the same approach to deal with the multi-purpose hardware trojan. At the same time, as the scale of integrated circuits growing, the structures are more complex, and the functions are more refined. The current situation makes the traditional HTs detection methods weaker and even unfeasible. Therefore, we propose an HTs classified locating method based on machine learning, named ML-HTCL, which belongs to the static detection and locating method. In ML-HTCL, different purpose HTs were represented by different features. Due to the different features, the ML-HTCL employs the multi-layer BP neural network for the control signal type HTs and the one-class SVM for the information leakage HTs, respectively. To deal with the HTs completely, the boundary nets are considered for all data set, while those were ignored by the most existing methods due to the high detection error rate. After detection, the HTs' precise locations were achieved. To evaluate the ML-HTCL, 17 gate-level netlist benchmarks are used for training and testing by leave-one-out cross-validation. From the results, the ML-HTCL reaches 85.05% of TPR and 73.91% of TNR for all kinds of HTs, which performs better than the most existing methods.

The powders with the nominal compositions of Ba0.6Sr0.4TiO3+x wt.% Li2CO3 (x=0 and x=1.0) were synthesized by a citrate precursor method. The sintering behavior, structure and dielectric properties of the ceramic specimens were investigated. Compared with the lithium-free specimen (x=0), the lithium-added specimen (x=1.0) showed appreciably enhanced sintering properties, achieving a relative density of 96.0% after sintering at 900°C. The enhanced sintering properties were related to a liquid-phase sintering mechanism. The origin of the liquid-phase was explained. The effects of the liquid-phase on the densification progress of the lithium-added specimen in different sintering stages were elucidated. The lithium addition was found to be beneficial to the nonlinear dielectric properties. The ceramic specimen with x=1.0 exhibited a figure-of-merit of 106 under a bias electric field of 20 kV/cm, higher by ~60% than the value (67) for the specimen with x=0.

As one of the most imperative antioxidants in higher plants, carotenoids serve as accessory pigments to harvest light for photosynthesis as well as photoprotectors for plants to adapt to high light stress. Phytoene synthase (PSY) is the entry enzyme and also the major rate-limiting enzyme in the carotenoid pathway. Here, we report a dehydration-responsive element-binding protein (DREB) transcription factor member in Nicotiana tabacum K326, NtDREB-1BL1, which regulates carotenoids biosynthesis by binding to the NtPSY promoter. The NtDREB-1BL1 transcript was widely distributed in leaves by Real-time PCR. Confocal image revealed that NtDREB-1BL1 was localized in the nucleus. The chromatin immunoprecipitation (ChIP) with the qPCR technique indicated that NtDREB-1BL1 could anchor the promoter region of NtPSY. Overexpression (NtDREB-1BL1 OE) and RNA interference (NtDREB-1BL1 RNAi) of NtDREB-1BL1 were performed to evaluate its biological function in N. tabacum. Both carotenoid and chlorophyll contents increased in transgenic plants of NtDREB-1BL1 OE compared with wild-type (WT) plants, with the augment of the genes involved in carotenoid biosynthesis. In contrast, the contents of carotenoid and chlorophyll significantly decreased in transgenic plants of NtDREB-1BL1 RNAi compared to WT, along with the decline in the expression of genes related to carotenoid biosynthesis. Moreover, transgenic plants of NtDREB-1BL1 OE exhibited enhanced tolerance under drought stress, with the weakened tolerance of drought stress in transgenic plants of NtDREB-1BL1 RNAi. In conclusion, our results illustrated the new role of transcription factor NtDREB-1BL1 in improving carotenoid biosynthesis through regulating NtPSY expression.

Solving linear systems of equations is one of the most common and basic problems in classical identification systems. Given a coefficient matrix A and a vector b, the ultimate task is to find the solution x such that Ax=b. Based on the technique of the singular value estimation, the paper proposes a modified quantum scheme to obtain the quantum state |x⟩ corresponding to the solution of the linear system of equations in O(κ2rpolylog(mn)/ϵ) time for a general m×n dimensional A, which is superior to existing quantum algorithms, where κ is the condition number, r is the rank of matrix A and ϵ is the precision parameter. Meanwhile, we also design a quantum circuit for the homogeneous linear equations and achieve an exponential improvement. The coefficient matrix A in our scheme is a sparsity-independent and non-square matrix, which can be applied in more general situations. Our research provides a universal quantum linear system solver and can enrich the research scope of quantum computation.

BackgroundThe tumor necrosis factor superfamily (TNFSF) and TNF receptor superfamily (TNFRSF) play important roles in the immune responses to infections. The aim of this study was to determine the impact of single nucleotide polymorphisms (SNPs) of several TNFSF/TNFRSF genes on the risk of hepatitis C virus (HCV) infection in the Chinese high-risk population.MethodsThe TNFSF4-rs1234313, TNFSF4-rs7514229, TNFSF8-rs3181366, TNFSF8-rs2295800, TNFRSF8-rs2298209, and TNFRSF8-rs2230625 SNPs were genotyped in 2309 uninfected controls, 597 subjects with spontaneous HCV clearance and 784 patients with persistent HCV infection using the TaqMan-MGB assay. The putative functions of the positive SNPs were determined using online bioinformatics tools.ResultsAfter adjusting for gender, age, high-risk population, alanine transaminase (ALT), aspartate aminotransferase (AST), IL28B-rs12979860 and rs8099917 genotypes, the non-conditional logistic regression showed that rs7514229-T, rs3181366-T, and rs2295800-C were associated with an increased risk of HCV infection (all PFDR < 0.05). Combined analysis of rs7514229-T and rs3181366-T risk alleles showed that the subjects carrying 2–4 risk alleles were more susceptible to HCV infection compared with those lacking any risk allele (all P < 0.001). Furthermore, the risk of HCV infection increased with the number of risk alleles (Ptrend < 0.001). In silico analysis showed that rs7514229, rs3181366, and rs2295800 polymorphisms may affect the transcription of mRNA by regulating miRNA binding, TF binding, and promoter activation, respectively, which may have biological consequences.ConclusionTNFSF4-rs7514229, TNFSF8-rs3181366, and TNFSF8-rs2295800 are associated with increased risk of HCV infection in the Chinese high-risk population.

Background: Since a greater number of hepatitis C virus (HCV) patients have access to direct-acting antiviral (DAA) based therapies, the number of patients not properly responding to prior DAA regimens is increasing. The objective of this comprehensive analysis was to assess the efficacy and safety of glecaprevir/pibrentasvir (GLE/PIB) in HCV patients who experienced previous DAA therapy failures.Methods: Bibliographic databases were systematically searched for relevant articles published by November 2020. The main endpoints were sustained viral response after 12 weeks (SVR12), adverse events (AEs; any grade) and severe adverse events (SAEs). Publication bias assessment was performed using funnel plots and the Egger's test.Results: Fourteen studies consisting of a total of 1,294 subjects were included in this study and the pooled estimate of SVR12, AEs and SAEs rates were 96.8% (95%CI: 95.1–98.2), 47.1% (95%CI: 26.0–69.3), and 1.8% (95%CI: 0.7–3.4), respectively. Subgroup analysis showed that pooled SVR12 rates were 97.9% (95%CI: 96.7–98.9) for Japan and 91.1% (95%CI: 87.3–94.3) for the United States; 95.8% (95%CI: 93.9–97.4) for genotype (GT)1 and 100.0% (95%CI: 99.6–100.0) for GT2; 95.3% (95%CI: 92.4–97.2) for cirrhosis and 96.3% (95%CI: 94.2–97.7) for non-cirrhosis cases. There was no publication bias included this study.Conclusion: This comprehensive analysis revealed that GLE/PIB is an effective and secure retreatment option for patients who did not optimally respond to DAA treatment, especially the Asian population with GT1-2.

Abstract When the traditional Meta database model is used to integrate multicultural media in the network’s space of public opinion, the performance of cooperative processing of distributed heterogeneous network data is poor, the logic of integration of multicultural media information is poor, the integration time is long, and the accuracy is low. This article proposes a multicultural media integration model based on multi-agent collaboration, which combines the life cycle of multicultural media models in the network’s space of public opinion. In distributed heterogeneous network spaces of public opinion, data is obtained from the distributed multicultural media information source, transferred to the multi-agent, and the collaboration among the agents is constructed. The multicultural media integration model provides the work flow and the standard principle of the model, and shapes the integrated model’s architecture including the data layer, the middle layer, and the expression layer, so as to achieve the intelligent integration of the multicultural media information. The experimental results show that the proposed model has high practicability, high integration efficiency and accuracy, and can enhance the penetration of multicultural media brands.

Disease relapse and graft-versus-host disease (GVHD) are the major complications affecting the outcomes of allogeneic hematopoietic stem cell transplantation (allo-HSCT). While the functions of αβT cells are extensively studied, the role of donor γδT cells in allo-HSCT is less well defined. Using TCRδ-/- donors lacking γδT cells, we demonstrated that donor γδT cells were critical in mediating graft-versus-leukemia (GVL) effect during allo-HSCT. In the absence of donor γδT cells, IFN-γ production by CD8+ T cells was severely impaired. Vγ4 subset was the major γδT cell subset mediating the GVL effect in vivo, which was partially dependent on IL-17A. Meanwhile, donor γδT cells could mitigate acute GVHD in a murine allo-HSCT model by suppressing CD4+ T cell activation and the major γδT cell subset that exerted this protective function was also Vγ4 γδT cells. Therefore, our findings provide evidence that donor γδT cells, especially Vγ4 subset, can enhance GVL effect and mitigate aGVHD during allo-HSCT.

Production of natural rubber by Parthenium argentaum (guayule) requires increased yield for economic sustainability. An RNAi gene silencing strategy was used to engineer isoprenoid biosynthesis by downregulation of squalene synthase (SQS), such that the pool of farnesyl diphosphate (FPP) substrate might instead be available to initiate natural rubber synthesis. Downregulation of SQS resulted in significantly reduced squalene and slightly increased rubber, but not in the same tissues nor to the same extent, partially due to an apparent negative feedback regulatory mechanism that downregulated mevalonate pathway isoprenoid production, presumably associated with excess geranyl pyrophosphate levels. A detailed metabolomics analysis of isoprenoid production in guayule revealed significant differences in metabolism in different tissues, including in active mevalonate and methylerythritol phosphate pathways in stem tissue, where rubber and squalene accumulate. New insights and strategies for engineering isoprenoid production in guayule were identified.

Improving prediction accuracy is a prominent modeling issue in relation to forest simulations, and ensemble learning is a new effective method for improving the precision of crown profile model simulations in order to overcome the disadvantages of statistical modeling. Background: Ensemble learning (a machine learning paradigm in which multiple learners are trained to achieve better performance) has strong nonlinear problem learning ability and flexibility in terms of analyzing longitudinal data, and it remains rarely explored so far in the field of crown profile modeling forest science. In this study, we explored the application of ensemble learning to the modeling and prediction of crown profiles. Methods: We evaluated the performance of ensemble learning procedures and marginal model in modeling crown profile using the crown profile database from China fir plantations in Fujian, in southern China. Results: The ensemble learning approach for the crown profile model appeared to have better performance and higher efficiency (R2 > 0.9). The crown equation model 18 showed an intermediate performance in its estimation, whereas GBDT (MAE = 0.3250, MSE = 0.2450) appeared to have the best performance and higher efficiency. Conclusions: The ensemble learning method can combine the advantages of multiple learners and has higher model accuracy, robustness and overall induction ability, and is thus an effective technique for crown profile modeling and prediction.

Parkinson’s disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients’ dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.

China is one of the countries with serious land degradation problems in the world. Land degradation directly threatens the food security of our country and determines the sustainable development of social economy. In this paper, the potential evapotranspiration and moisture index are calculated to divide the climatic zone of China. Based on the NPP and precipitation data, the national rRUE is obtained by the edge function. With the climate "relative benchmark", the rules of threshold analysis is used to comprehensively evaluate the land degradation in China. The results show that: excellent land is concentrated in northeast China, western Xinjiang and eastern Qinghai-Tibet Plateau; mildly degraded land is widely and sporadically distributed in the eastern plain of China; moderately degraded land and severely degraded land are concentrated in western Inner Mongolia, southern Xinjiang and northern Qinghai-Xizang Plateau.