A preoptic neuronal population controls fever and appetite during sickness.

During infection, animals exhibit adaptive changes in physiology and behaviour aimed at increasing survival. Although many causes of infection exist, they trigger similar stereotyped symptoms such as fever, warmth-seeking, loss of appetite and fatigue1,2. Yet exactly how the nervous system alters body temperature and triggers sickness behaviours to coordinate responses to infection remains unknown. Here we identify a previously uncharacterized population of neurons in the ventral medial preoptic area (VMPO) of the hypothalamus that are activated after sickness induced by lipopolysaccharide (LPS) or polyinosinic:polycytidylic acid. These neurons are crucial for generating a fever response and other sickness symptoms such as warmth-seeking and loss of appetite. Single-nucleus RNA-sequencing and multiplexed error-robust fluorescence in situ hybridization uncovered the identity and distribution of LPS-activated VMPO (VMPOLPS) neurons and non-neuronal cells. Gene expression and electrophysiological measurements implicate a paracrine mechanism in which the release of immune signals by non-neuronal cells during infection activates nearby VMPOLPS neurons. Finally, we show that VMPOLPS neurons exert a broad influence on the activity of brain areas associated with behavioural and homeostatic functions and are synaptically and functionally connected to circuit nodes controlling body temperature and appetite. Together, these results uncover VMPOLPS neurons as a control hub that integrates immune signals to orchestrate multiple sickness symptoms in response to infection.

Similarities and Dissimilarities of COVID-19 and Other Coronavirus Diseases.

In less than two decades, three deadly zoonotic coronaviruses, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-2, have emerged in humans, causing SARS, MERS, and coronavirus disease 2019 (COVID-19), respectively. The current COVID-19 pandemic poses an unprecedented crisis in health care and social and economic development. It reinforces the cruel fact that CoVs are constantly evolving, possessing the genetic malleability to become highly pathogenic in humans. In this review, we start with an overview of CoV diseases and the molecular virology of CoVs, focusing on similarities and differences between SARS-CoV-2 and its highly pathogenic as well as low-pathogenic counterparts. We then discuss mechanisms underlying pathogenesis and virus-host interactions of SARS-CoV-2 and other CoVs, emphasizing the host immune response. Finally, we summarize strategies adopted for the prevention and treatment of CoV diseases and discuss approaches to develop effective antivirals and vaccines.

A PilZ domain protein interacts with the transcriptional regulator HinK to regulate type VI secretion system in Pseudomonas aeruginosa.

Type VI secretion systems (T6SS) are bacterial macromolecular complexes that secrete effectors into target cells or the extracellular environment, leading to the demise of adjacent cells and providing a survival advantage. Although studies have shown that the T6SS in Pseudomonas aeruginosa is regulated by the Quorum Sensing system and second messenger c-di-GMP, the underlying molecular mechanism remains largely unknown. In this study, we discovered that the c-di-GMP-binding adaptor protein PA0012 has a repressive effect on the expression of the T6SS HSI-I genes in P. aeruginosa PAO1. To probe the mechanism by which PA0012 (renamed TssZ, Type Six Secretion System -associated PilZ protein) regulates the expression of HSI-I genes, we conducted yeast two-hybrid screening and identified HinK, a LasR-type transcriptional regulator, as the binding partner of TssZ. The protein-protein interaction between HinK and TssZ was confirmed through co-immunoprecipitation assays. Further analysis suggested that the HinK-TssZ interaction was weakened at high c-di-GMP concentrations, contrary to the current paradigm wherein c-di-GMP enhances the interaction between PilZ proteins and their partners. Electrophoretic mobility shift assays revealed that the non-c-di-GMP-binding mutant TssZR5A/R9A interacts directly with HinK and prevents it from binding to the promoter of the quorum-sensing regulator pqsR. The functional connection between TssZ and HinK is further supported by observations that TssZ and HinK impact the swarming motility, pyocyanin production, and T6SS-mediated bacterial killing activity of P. aeruginosa in a PqsR-dependent manner. Together, these results unveil a novel regulatory mechanism wherein TssZ functions as an inhibitor that interacts with HinK to control gene expression.

Treatment of neurologic pathology and inflammation in Machado-Joseph disease through in vivo self-assembled siRNA.

Machado-Joseph disease, also known as Spinocerebellar ataxia type 3 (MJD/SCA3), is a fatal autosomal dominant hereditary ataxia characterized by cerebellar ataxia resulting from the abnormal expansion of CAG repeats in exon 10 of the ATXN3 gene. Presently, there is no effective treatment for SCA3. Small interfering RNAs (siRNAs) are emerging as potential therapeutic strategies to specifically target the disease-causing mutant ATXN3 (mATXN3) protein. However, the delivery efficiency of siRNAs remains a major obstacle for clinical application, particularly in brain disorders. This study aimed to develop a synthetic biology strategy to reprogram the host liver as a tissue chassis to induce and deliver in vivo self-assembled siRNAs (IVSA-siRNAs) to target the ATXN3 gene. A synthetic construct directed by a cytomegalovirus promoter was designed to encode a neuron-targeting rabies virus glycoprotein tag and mATXN3-siRNA. After intravenous injection, the synthetic construct was taken up by mouse livers, which were then reprogrammed to enable the self-assembly, production, and secretion of small extracellular vesicles (sEVs) encapsulating mATXN3-siRNA. The sEV-encapsulated mATXN3-siRNA was further transported through the endogenous circulating system of sEVs, crossing the blood-brain barrier and reaching the cerebellar cortex and spinal cerebellar tract, where they silenced the ATXN3 gene. Treatment with the synthetic construct for 8 or 12 weeks led to significant improvements in motor balance ability and reduction of cerebellar atrophy in YACMJD84.2 transgenic mice. The number of Purkinje cells in the cerebellar cortex was significantly increased, and the loss of myelin basic protein was reduced. Moreover, the quantity of neurotoxic nuclear inclusion bodies and the expression of glial fibrillary acidic protein, which promotes neuroinflammation in activated astrocytes, were decreased significantly. The synthetic construct facilitated the generation and delivery of IVSA-siRNA to the cerebellar cortex and spinal cerebellar tract, thereby inhibiting the expression of mATXN3 protein. This treatment successfully addressed motor impairments, alleviated neuropathological phenotypes, and mitigated neuroinflammation in YACMJD84.2 transgenic mice. Our strategy effectively overcomes the primary challenges associated with siRNA therapy for cerebellar ataxia, offering a promising avenue for future clinical treatments.

An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors.

BACKGROUND: Kidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both the graft and the pediatric recipient. However, there is limited research on DGF in pediatric kidney transplant recipients. This study aims to develop a predictive model for the risk of DGF occurrence after pediatric kidney transplantation by integrating donor and recipient characteristics and utilizing machine learning algorithms, ultimately providing guidance for clinical decision-making. METHODS: This single-center retrospective cohort study includes all recipients under 18 years of age who underwent single-donor kidney transplantation at our hospital between 2016 and 2023, along with their corresponding donors. Demographic, clinical, and laboratory examination data were collected from both donors and recipients. Univariate logistic regression models and differential analysis were employed to identify features associated with DGF. Subsequently, a risk score for predicting DGF occurrence (DGF-RS) was constructed based on machine learning combinations. Model performance was evaluated using the receiver operating characteristic curves, decision curve analysis (DCA), and other methods. RESULTS: The study included a total of 140 pediatric kidney transplant recipients, among whom 37 (26.4%) developed DGF. Univariate analysis revealed that high-density lipoprotein cholesterol (HDLC), donor after circulatory death (DCD), warm ischemia time (WIT), cold ischemia time (CIT), gender match, and donor creatinine were significantly associated with DGF (P < 0.05). Based on these six features, the random forest model (mtry = 5, 75%p) exhibited the best predictive performance among 97 machine learning models, with the area under the curve values reaching 0.983, 1, and 0.905 for the entire cohort, training set, and validation set, respectively. This model significantly outperformed single indicators. The DCA curve confirmed the clinical utility of this model. CONCLUSIONS: In this study, we developed a machine learning-based predictive model for DGF following pediatric kidney transplantation, termed DGF-RS, which integrates both donor and recipient characteristics. The model demonstrated excellent predictive accuracy and provides essential guidance for clinical decision-making. These findings contribute to our understanding of the pathogenesis of DGF.

Human Coronavirus: Host-Pathogen Interaction.

Human coronavirus (HCoV) infection causes respiratory diseases with mild to severe outcomes. In the last 15 years, we have witnessed the emergence of two zoonotic, highly pathogenic HCoVs: severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). Replication of HCoV is regulated by a diversity of host factors and induces drastic alterations in cellular structure and physiology. Activation of critical signaling pathways during HCoV infection modulates the induction of antiviral immune response and contributes to the pathogenesis of HCoV. Recent studies have begun to reveal some fundamental aspects of the intricate HCoV-host interaction in mechanistic detail. In this review, we summarize the current knowledge of host factors co-opted and signaling pathways activated during HCoV infection, with an emphasis on HCoV-infection-induced stress response, autophagy, apoptosis, and innate immunity. The cross talk among these pathways, as well as the modulatory strategies utilized by HCoV, is also discussed.

Individual cerebellar metabolic connectome in patients with MTLE and NTLE associated with surgical prognosis.

PURPOSE: This study aimed to comprehensively explore the different metabolic connectivity topological changes in MTLE and NTLE, as well as their association with surgical outcomes. METHODS: This study enrolled a cohort of patients with intractable MTLE and NTLE. Each individual's metabolic connectome, as determined by Kullback-Leibler divergence similarity estimation for the [18F]FDG PET image, was employed to conduct a comprehensive analysis of the cerebral metabolic network. Alterations in network connectivity were assessed by extracting and evaluating the strength of edge and weighted connectivity. By utilizing these two connectivity strength metrics with the cerebellum, we explored the network properties of connectivity and its association with prognosis in surgical patients. RESULTS: Both MTLE and NTLE patients exhibited substantial alterations in the connectivity of the metabolic network at the edge and nodal levels (p < 0.01, FDR corrected). The key disparity between MTLE and NTLE was observed in the cerebellum. In MTLE, there was a predominance of increased connectivity strength in the cerebellum. Whereas, a decrease in cerebellar connectivity was identified in NTLE. It was found that in MTLE, higher edge connectivity and weighted connectivity strength in the contralateral cerebellar hemisphere correlated with improved surgical outcomes. Conversely, in NTLE, a higher edge metabolic connectivity strength in the ipsilateral cerebellar hemisphere suggested a worse surgical prognosis. CONCLUSION: The cerebellum exhibits distinct topological characteristics in the metabolic networks between MTLE and NTLE. The hyper- or hypo-metabolic connectivity in the cerebellum may be a prognostic biomarker of surgical prognosis, which might aid in therapeutic decision-making for TLE individuals.

Identification of biomarkers and potential therapeutic targets of kidney stone disease using bioinformatics.

PURPOSE: Kidney stone disease (KSD) is a common urological disease, but its pathogenesis remains unclear. In this study, we screened KSD-related hub genes using bioinformatic methods and predicted the related pathways and potential drug targets. METHODS: The GSE75542 and GSE18160 datasets in the Gene Expression Omnibus (GEO) were selected to identify common differentially expressed genes (DEGs). We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to identify enriched pathways. Finally, we constructed a hub gene-miRNA network and drug-DEG interaction network. RESULTS: In total, 44 upregulated DEGs and 1 downregulated DEG were selected from the GEO datasets. Signaling pathways, such as leukocyte migration, chemokine activity, NF-κB, TNF, and IL-17, were identified in GO and KEGG. We identified 10 hub genes using Cytohubba. In addition, 21 miRNAs were predicted to regulate 4 or more hub genes, and 10 drugs targeted 2 or more DEGs. LCN2 expression was significantly different between the GEO datasets. Quantitative real-time polymerase chain reaction (qRT-PCR) analyses showed that seven hub gene expressions in HK-2 cells with CaOx treatment were significantly higher than those in the control group. CONCLUSION: The 10 hub genes identified, especially LCN2, may be involved in kidney stone occurrence and development, and may provide new research targets for KSD diagnosis. Furthermore, KSD-related miRNAs may be targeted for the development of novel drugs for KSD treatment.

Trends in polypharmacy among U.S. adults with asthma, 2001-2020.

OBJECTIVE: This study aimed to evaluate trends in polypharmacy prevalence among adults with asthma in the United States. METHODS: Data from the 2001-2020 National Health and Nutrition Examination Survey were used to estimate the weighted prevalence of polypharmacy. Joinpoint regression analysis was conducted to evaluate trends in polypharmacy. Trends were first evaluated overall and then stratified by asthma severity and asthma control. A multivariable logistic regression model was used to identify factors associated with polypharmacy. RESULTS: From 2001 to 2020, a stable trend in polypharmacy among U.S. adults with asthma was observed (average annual percent change [AAPC]=1.02, p=0.71). Trends across different asthma severity were stable (mild asthma: AAPC=2.93, p=0.20; moderate asthma: AAPC=-2.22, p=0.35; severe asthma: AAPC=0.45, p=0.82). Trends in adults with good asthma control and those with poor control stayed constant (good control: AAPC=0.82, p=0.68; poor control: AAPC=-1.22, p=0.82). Several factors, including older age, females, Non-Hispanic Black, health insurance coverage, family income, number of healthcare visits, former smokers, multi-morbidities, asthma severity, and asthma control, were associated with polypharmacy. CONCLUSIONS: Polypharmacy prevalence has remained constant among U.S. adults with asthma over the past two decades. Despite a stable overall trend, disparities in polypharmacy prevalence persist across different asthma severity and control status, underscoring the need for tailored medication management to improve asthma care.

Research Progress on the Experimental Model and Underlying Mechanistic Studies of Tension-Type Headaches.

PURPOSE OF REVIEW: Tension-type headaches (TTH) significantly diminish patients' quality of life and increase absenteeism, thereby imposing a substantial economic burden. Animal models are essential tools for studying disease mechanisms and drug development. However, until now, little focus has been placed on summarizing the animal models of TTH and associated mechanistic studies. This narrative review discusses the current animal models of TTH and related mechanistic studies to provide insights into the pathophysiological mechanisms of and treatments for TTH. RECENT FINDINGS: The primary method for constructing an animal model of TTH involves injecting a solution of pain relievers, such as adenosine triphosphate, nerve growth factor, or a high concentration of salt solution, into the neck to initiate harmful cervical muscle responses. This model enables the examination of the interaction between peripheral muscles and central sensitization, which is crucial for understanding the pathophysiology of TTH. Mechanistic studies based on this model have investigated the effect of the P2X receptor antagonist, P2X7 receptor blockade, the P2Y1 receptor agonist 2-MESADP, P2Y1 receptor antagonist MRS2179, nitric oxide synthase inhibitors, and acetylsalicylic acid. Despite notable advancements, the current model of TTH has limitations, including surgical complexity and the inability to replicate chronic tension-type headache (CTTH). To gain a more comprehensive understanding and develop more effective treatment methods, future studies should focus on simplifying surgical procedures, examining other predisposing factors, and establishing a model for chronic TTH. This will offer a deeper insight into the pathophysiological mechanism of TTH and pave the way for improved treatment approaches.

Polypharmacy among adults with asthma in the United States, 2005-2020.

BACKGROUND: Asthma is a chronic disease that often requires medication for control. Polypharmacy remains a major issue to medication adherence; however, its evidence among patients with asthma is limited. OBJECTIVES: To evaluate the prevalence and determinants of polypharmacy and its associations with asthma control among adults with asthma in the United States. METHODS: Data from the 2005-2020 National Health and Nutrition Examination Survey (NHANES) were used to estimate the weighted prevalence of polypharmacy. Selected variables, including demographics, comorbidities, prescription medications, and asthma-related adverse events, were extracted from the NHANES. Multivariable logistic regression was conducted to identify factors associated with polypharmacy. Another two sets of multivariable logistic regression models were employed to further assess the association between polypharmacy and asthma-related adverse events: one for asthma attacks and the other for asthma-related emergency room visits. RESULTS: From 2005 to 2020, polypharmacy prevalence was 34.3% and 14.1% among adults with and without asthma, respectively. Characteristics, including older age (P<0.01), non-Hispanic blacks (P<0.01), health insurance coverage (P<0.01), number of healthcare visits (P<0.01), and multiple comorbidities (P<0.01) were associated with polypharmacy. Polypharmacy was associated with increased risks of having asthma attacks (OR, 1.38; 95% CI, 1.08-1.76) and asthma-related emergency room visits (OR, 1.46; 95% CI, 1.09-1.94) among adults with asthma. Among patients taking at least one asthma medication, risks of asthma attacks and asthma-related ER visits did not differ between those with and without polypharmacy. CONCLUSION: Approximately one in three adults with asthma experienced polypharmacy in the United States. Disparities existed in several characteristics, highlighting the necessity for appropriate care and policies among vulnerable populations. Further validation on the impact of polypharmacy on asthma control is required.

Sensor Network Attack Synthesis against Fault Diagnosis of Discrete Event Systems.

This paper investigates the problem of synthesizing network attacks against fault diagnosis in the context of discrete event systems (DESs). It is assumed that the sensor observations sent to the operator that monitors a system are tampered with by an active attacker. We first formulate the process of online fault diagnosis under attack. Then, from the attack viewpoint, we define a sensor network attacker as successful if it can degrade the fault diagnosis in the case of maintaining itself as undiscovered by the operator. To verify such an attacker, an information structure called a joint diagnoser (JD) is proposed, which describes all possible attacks in a given attack scenario. Based on the refined JD, i.e., stealthy joint diagnoser (SJD), we present an algorithmic procedure for synthesizing a successful attacker if it exists.

Research on Classification Algorithm of Silicon Single-Crystal Growth Temperature Gradient Trend Based on Multi-Level Feature Fusion.

In the process of silicon single-crystal preparation, the timely identification and adjustment of abnormal conditions are crucial. Failure to promptly detect and resolve issues may result in a substandard silicon crystal product quality or even crystal pulling failure. Therefore, the early identification of abnormal furnace conditions is essential for ensuring the preparation of perfect silicon single crystals. Additionally, since the thermal field is the fundamental driving force for stable crystal growth and the primary assurance of crystal quality, this paper proposes a silicon single-crystal growth temperature gradient trend classification algorithm based on multi-level feature fusion. The aim is to accurately identify temperature gradient changes during silicon crystal growth, in order to promptly react to early growth failures and ensure the stable growth of high-quality silicon single crystals to meet industrial production requirements. The algorithm first divides the temperature gradient trend into reasonable categories based on expert knowledge and qualitative analysis methods. Then, it fuses the original features of actual production data, shallow features extracted based on statistical information, and deep features extracted through deep learning. During the fusion process, the algorithm considers the impact of different features on the target variable and calculates mutual information based on the difference between information entropy and conditional entropy, ultimately using mutual information for feature weighting. Subsequently, the fused multi-level feature vectors and their corresponding trend labels are input into a Deep Belief Network (DBN) model to capture process dynamics and classify trend changes. Finally, the experimental results demonstrate that the proposed algorithm can effectively predict the changing trend of thermal field temperature gradients. The introduction of this algorithm will help improve the accuracy of fault trend prediction in silicon single-crystal preparation, thereby minimizing product quality issues and production interruptions caused by abnormal conditions.

Identification and Analysis of PEPC Gene Family Reveals Functional Diversification in Orchidaceae and the Regulation of Bacterial-Type PEPC.

Phosphoenolpyruvate carboxylase (PEPC) gene family plays a crucial role in both plant growth and response to abiotic stress. Approximately half of the Orchidaceae species are estimated to perform CAM pathway, and the availability of sequenced orchid genomes makes them ideal subjects for investigating the PEPC gene family in CAM plants. In this study, a total of 33 PEPC genes were identified across 15 orchids. Specifically, one PEPC gene was found in Cymbidium goeringii and Platanthera guangdongensis; two in Apostasia shenzhenica, Dendrobium chrysotoxum, D. huoshanense, Gastrodia elata, G. menghaiensis, Phalaenopsis aphrodite, Ph. equestris, and Pl. zijinensis; three in C. ensifolium, C. sinense, D. catenatum, D. nobile, and Vanilla planifolia. These PEPC genes were categorized into four subgroups, namely PEPC-i, PEPC-ii, and PEPC-iii (PTPC), and PEPC-iv (BTPC), supported by the comprehensive analyses of their physicochemical properties, motif, and gene structures. Remarkably, PEPC-iv contained a heretofore unreported orchid PEPC gene, identified as VpPEPC4. Differences in the number of PEPC homolog genes among these species were attributed to segmental duplication, whole-genome duplication (WGD), or gene loss events. Cis-elements identified in promoter regions were predominantly associated with light responsiveness, and circadian-related elements were observed in each PEPC-i and PEPC-ii gene. The expression levels of recruited BTPC, VpPEPC4, exhibited a lower expression level than other VpPEPCs in the tested tissues. The expression analyses and RT-qPCR results revealed diverse expression patterns in orchid PEPC genes. Duplicated genes exhibited distinct expression patterns, suggesting functional divergence. This study offered a comprehensive analysis to unveil the evolution and function of PEPC genes in Orchidaceae.

Bulked Segregant RNA-Seq Reveals Different Gene Expression Patterns and Mutant Genes Associated with the Zigzag Pattern of Tea Plants (Camellia sinensis).

The unique zigzag-patterned tea plant is a rare germplasm resource. However, the molecular mechanism behind the formation of zigzag stems remains unclear. To address this, a BC1 genetic population of tea plants with zigzag stems was studied using histological observation and bulked segregant RNA-seq. The analysis revealed 1494 differentially expressed genes (DEGs) between the upright and zigzag stem groups. These DEGs may regulate the transduction and biosynthesis of plant hormones, and the effects on the phenylpropane biosynthesis pathways may cause the accumulation of lignin. Tissue sections further supported this finding, showing differences in cell wall thickness between upright and curved stems, potentially due to lignin accumulation. Additionally, 262 single-nucleotide polymorphisms (SNPs) across 38 genes were identified as key SNPs, and 5 genes related to zigzag stems were identified through homologous gene function annotation. Mutations in these genes may impact auxin distribution and content, resulting in the asymmetric development of vascular bundles in curved stems. In summary, we identified the key genes associated with the tortuous phenotype by using BSR-seq on a BC1 population to minimize genetic background noise.

The role of regulatory T cells in the pathogenesis of acute kidney injury.

The incidence of acute kidney injury (AKI) is on the rise and is associated with high mortality; however, there are currently few effective treatments. Moreover, the relationship between Tregs and other components of the immune microenvironment (IME) in the pathogenesis of AKI remains unclear. We downloaded four publicly accessible AKI datasets, GSE61739, GSE67401, GSE19130, GSE81741, GSE19288 and GSE106993 from the gene expression omnibus (GEO) database. Additionally, we gathered two kidney single-cell sequencing (scRNA-seq) samples from the Department of Organ Transplantation at Zhujiang Hospital of Southern Medical University to investigate chronic kidney transplant rejection (CKTR). Moreover, we also collected three samples of normal kidney tissue from GSE131685. By analysing the differences in immune cells between the AKI and Non-AKI groups, we discovered that the Non-AKI group contained a significantly greater number of Tregs than the AKI group. Additionally, the activation of signalling pathways, such as inflammatory molecules secretion, immune response, glycolytic metabolism, NOTCH, FGF, NF-κB and TLR4, was significantly greater in the AKI group than in the Non-AKI group. Additionally, analysis of single-cell sequencing data revealed that Tregs in patients with chronic kidney rejection and in normal kidney tissue have distinct biology, including immune activation, cytokine production, and activation fractions of signalling pathways such as NOTCH and TLR4. In this study, we found significant differences in the IME between AKI and Non-AKI, including differences in Tregs cells and activation levels of biologically significant signalling pathways. Tregs were associated with lower activity of signalling pathways such as inflammatory response, inflammatory molecule secretion, immune activation, glycolysis.

Comparative and phylogenetic analysis of Chiloschista (Orchidaceae) species and DNA barcoding investigation based on plastid genomes.

BACKGROUND: Chiloschista (Orchidaceae, Aeridinae) is an epiphytic leafless orchid that is mainly distributed in tropical or subtropical forest canopies. This rare and threatened orchid lacks molecular resources for phylogenetic and barcoding analysis. Therefore, we sequenced and assembled seven complete plastomes of Chiloschista to analyse the plastome characteristics and phylogenetic relationships and conduct a barcoding investigation. RESULTS: We are the first to publish seven Chiloschista plastomes, which possessed the typical quadripartite structure and ranged from 143,233 bp to 145,463 bp in size. The plastomes all contained 120 genes, consisting of 74 protein-coding genes, 38 tRNA genes and eight rRNA genes. The ndh genes were pseudogenes or lost in the genus, and the genes petG and psbF were under positive selection. The seven Chiloschista plastomes displayed stable plastome structures with no large inversions or rearrangements. A total of 14 small inversions (SIs) were identified in the seven Chiloschista plastomes but were all similar within the genus. Six noncoding mutational hotspots (trnNGUU-rpl32 > rpoB-trnCGCA > psbK-psbI > psaC-rps15 > trnEUUC-trnTGGU > accD-psaI) and five coding sequences (ycf1 > rps15 > matK > psbK > ccsA) were selected as potential barcodes based on nucleotide diversity and species discrimination analysis, which suggested that the potential barcode ycf1 was most suitable for species discrimination. A total of 47-56 SSRs and 11-14 long repeats (> 20 bp) were identified in Chiloschista plastomes, and they were mostly located in the large single copy intergenic region. Phylogenetic analysis indicated that Chiloschista was monophyletic. It was clustered with Phalaenopsis and formed the basic clade of the subtribe Aeridinae with a moderate support value. The results also showed that seven Chiloschista species were divided into three major clades with full support. CONCLUSION: This study was the first to analyse the plastome characteristics of the genus Chiloschista in Orchidaceae, and the results showed that Chiloschista plastomes have conserved plastome structures. Based on the plastome hotspots of nucleotide diversity, several genes and noncoding regions are suitable for phylogenetic and population studies. Chiloschista may provide an ideal system to investigate the dynamics of plastome evolution and DNA barcoding investigation for orchid studies.

TMEM151A variants associated with paroxysmal kinesigenic dyskinesia.

TMEM151A, located at 11q13.2 and encoding transmembrane protein 151A, was recently reported as causative for autosomal dominant paroxysmal kinesigenic dyskinesia (PKD). Here, through comprehensive analysis of sporadic and familial cases, we expand the clinical and mutation spectrum of PKD. In doing so, we clarify the clinical and genetic features of Chinese PKD patients harboring TMEM151A variants and further explore the relationship between TMEM151A mutations and PKD. Whole exome sequencing was performed on 26 sporadic PKD patients and nine familial PKD pedigrees without PRRT2 variants. Quantitative real-time PCR was used to assess the gene expression of frameshift mutant TMEM151A in a PKD patient. TMEM151A variants reported to date were reviewed. Four TMEM151A variants were detected in four unrelated families with 12 individuals, including a frameshift mutation [c.606_607insA (p.Val203fs)], two missense mutations [c.166G > A (p.Gly56Arg) and c.791T > C (p.Val264Ala)], and a non-pathogenic variant [c.994G > A (p.Gly332Arg)]. The monoallelic frameshift mutation [c.606_607insA (p.Val203fs)] may cause TMEM151A mRNA decay, suggesting a potential pathogenic mechanism of haploinsufficiency. Patients with TMEM151A variants had short-duration attacks and presented with dystonia. Our study provides a detailed clinical description of PKD patients with TMEM151A mutations and reports a new disease-causing mutation, expanding the known phenotypes caused by TMEM151A mutations and providing further detail about the pathoetiology of PKD.

Activation of the MKK3-p38-MK2-ZFP36 Axis by Coronavirus Infection Restricts the Upregulation of AU-Rich Element-Containing Transcripts in Proinflammatory Responses.

Coronavirus infections induce the expression of multiple proinflammatory cytokines and chemokines. We have previously shown that in cells infected with gammacoronavirus infectious bronchitis virus (IBV), interleukin 6 (IL-6), and IL-8 were drastically upregulated, and the MAP kinase p38 and the integrated stress response pathways were implicated in this process. In this study, we report that coronavirus infection activates a negative regulatory loop that restricts the upregulation of a number of proinflammatory genes. As revealed by the initial transcriptomic and subsequent validation analyses, the anti-inflammatory adenine-uridine (AU)-rich element (ARE)-binding protein, zinc finger protein 36 (ZFP36), and its related family members were upregulated in cells infected with IBV and three other coronaviruses, alphacoronaviruses porcine epidemic diarrhea virus (PEDV), human coronavirus 229E (HCoV-229E), and betacoronavirus HCoV-OC43, respectively. Characterization of the functional roles of ZFP36 during IBV infection demonstrated that ZFP36 promoted the degradation of transcripts coding for IL-6, IL-8, dual-specificity phosphatase 1 (DUSP1), prostaglandin-endoperoxide synthase 2 (PTGS2) and TNF-α-induced protein 3 (TNFAIP3), through binding to AREs in these transcripts. Consistently, knockdown and inhibition of JNK and p38 kinase activities reduced the expression of ZFP36, as well as the expression of IL-6 and IL-8. On the contrary, overexpression of mitogen-activated protein kinase kinase 3 (MKK3) and MAPKAP kinase-2 (MK2), the upstream and downstream kinases of p38, respectively, increased the expression of ZFP36 and decreased the expression of IL-8. Taken together, this study reveals an important regulatory role of the MKK3-p38-MK2-ZFP36 axis in coronavirus infection-induced proinflammatory response. IMPORTANCE Excessive and uncontrolled induction and release of proinflammatory cytokines and chemokines, the so-called cytokine release syndrome (CRS), would cause life-threatening complications and multiple organ failure in severe coronavirus infections, including severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and COVID-19. This study reveals that coronavirus infection also induces the expression of ZFP36, an anti-inflammatory ARE-binding protein, promoting the degradation of ARE-containing transcripts coding for IL-6 and IL-8 as well as a number of other proteins related to inflammatory response. Furthermore, the p38 MAP kinase, its upstream kinase MKK3 and downstream kinase MK2 were shown to play a regulatory role in upregulation of ZFP36 during coronavirus infection cycles. This MKK3-p38-MK2-ZFP36 axis would constitute a potential therapeutic target for severe coronavirus infections.

Low polarization-sensitive ultra-broadband anti-reflection coatings with improved reliability.

Broader spectra, lower reflectivity and higher reliability are the performance requirements for broadband antireflective (BBAR) films. In this work, a BBAR film structure was proposed, which maintains extremely low reflectivity, ultra-wide spectra, low polarization sensitivity and practical reliability. The BBAR film consists of a dense multilayer interference stack on the bottom and a nano-grass-like alumina (NGLA) layer with a gradient low refractive index distribution on the top. The film was deposited by atomic layer deposition, while the NGLA layer was formed by means of a hot water bath on Al2O3 layer. The top NGLA layer has extremely high porosity and ultra-low refractive index, along with extremely fragile structure. To surmount the fragility of NGLA layer, a sub-nano layer of SiO2 was grown by atomic layer deposition to solidify its structure and also to adjust the refractive index with different thicknesses of SiO2. Finally, in the wide wavelength range of 400-1100 nm, the average transmittance of the double-sided coated fused quartz reaches 99.2%. The absorption, light scattering, reliability and polarization characteristics of BBAR films were investigated. An optimized BBAR film with low polarization-sensitivity and improved reliability was realized, which should be potentially promising for application in optical systems.