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Abstract Background Glaesserella parasuis (G. parasuis) is the causative agent of Glässer’s disease, which causes significant economic losses in the swine industry. However, research on the pathogenesis of G. parasuis has been hampered by the lack of a simple and efficient marker-free knockout system. Results In this study, a marker-free knockout system was developed for G. parasuis using a temperature-sensitive vector. By alternating the incubation of transformants at 30°C and 37°C, we optimized the screening process for this system. The system was successfully applied to knockout the Kan R cassette from JS0135ΔnanH::Kan R , achieving a knockout efficiency of 90% in the final round of screening. To confirm that temperature variation was a key factor, we proceeded with knocking out the nanH and apd genes in the CF7066 strain. The knockout efficiency reached up to 100%, with the shortest screening time being only four days. The knockout of the nanH gene resulted in a significant reduction in the growth vitality of the strains, while the knockout of the apd gene led to an approximate 56% improvement in the adhesion rate. Additionally, we observed that the expression of recombinant genes in transformants was higher at 30℃ than at 37℃, with the recC gene being upregulated approximately 7-fold. In contrast, there was almost no difference in the expression of recombinant genes between 30℃ and 37℃ in the wild-type strains. This discrepancy was likely due to an elevated copy number of target plasmids at 30℃, which may have resulted in the enhanced expression of recombinant genes. Conclusions In conclusion, this newly developed gene knockout system for G. parasuis presents a valuable tool for advancing research on this organism.

Abstract In this paper, we investigate the relationship between the indicators for COVID-19 monitoring and the dynamic of jumps across six major financial markets including China, France, Italy, Germany, the UK, and the US. First, this paper finds that jumps occurred more frequently in the index returns during the COVID-19 pandemic. Second, the empirical findings suggest that the anxiety stemming from potential future control measures, which were prompted by updates in COVID-19 briefings, plays a significant role in explaining the jumps in index returns within financial markets. The strategies of ‘zero tolerance for COVID-19’, ‘maximum healthcare capacity’, and ‘less tolerance for restriction’ were carried out by China, European countries, and the US respectively. These diverse approaches to managing COVID-19 have a significant and varied impact on the market’s sudden price movements.

The successful evolution of KPC-2 in bacteria has limited the clinical practice of carbapenems. This dilemma deteriorated the prognosis of associated infections and hence attracted increasing attention from researchers to explore alternative therapeutic options. Here, the enzyme inhibition assay was first performed to screen for a potent KPC-2 inhibitor. The synergistic effect of the candidate with carbapenems was further confirmed by checkboard minimum inhibitory concentration (MIC) assay, time-killing assay, disk diffusion method, and live/dead bacteria staining analysis. The mechanisms by which the candidate acts were subsequently explored through molecular dynamics (MD) simulations, etc. Our study found that Ginkgolic Acid (C13:0) (GA) exhibited effective KPC-2 inhibitory activity in both laboratory strain and clinical strain containing KPC-2. It could potentiate the killing effect of carbapenems on KPC-2-positive Klebsiella pnenmoniae(K. pnenmoniae). Further explorations revealed that GA could competitively bind to the active pocket of KPC-2 with meropenem (MEM) via residues Trp104, Gly235, and Leu166. The secondary structure and functional groups of KPC-2 were subsequently altered, which may be the main mechanism by which GA exerted its KPC-2 inhibitory effect. In addition, GA was also found to synergize with MEM to disrupt membrane integrity and increase membrane permeability, which may be another mechanism by which GA reinforced the bactericidal ability of carbapenems. Our study indicated that GA was a significant KPC-2 inhibitor that could prolong the lifespan of carbapenems and improve the prognosis of patients.

Abstract The thermal properties of major minerals play a key role in understanding the internal dynamic mechanism and thermal evolution of the Earth and rocky planets. In this study, we first investigated the effect of Fe on the thermal conductivity (κ) and the thermal diffusivity (D) of orthopyroxene at 1–3 GPa and 293–873 K by the transient plane source method. The κ and D both decrease with increasing temperature and decreasing pressure. With increasing Fe content, the two parameters both quickly decrease from the beginning and then slack off. We further modeled the thermal evolution of S‐type asteroids, which strongly depends on the composition model and the dimension of the planet. Combining the present data with surface heat flow and heat production, the lunar's geotherm until 1,400 km is constructed. The core‐mantle boundary temperature of the Moon is refined from 1,883 to 1,754 K.

Abstract Background Inclusions of TAR DNA-binding protein 43 kDa (TDP-43) has been designated limbic-predominant, age-related TDP-43 encephalopathy (LATE), with or without co-occurrence of Alzheimer’s disease (AD). Approximately, 30–70% AD cases present TDP-43 proteinopathy (AD-TDP), and a greater disease severity compared to AD patients without TDP-43 pathology. However, it remains unclear to what extent TDP-43 dysfunction is involved in AD pathogenesis. Methods To investigate whether TDP-43 dysfunction is a prominent feature in AD-TDP cases, we evaluated whether non-conserved cryptic exons, which serve as a marker of TDP-43 dysfunction in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD-TDP), accumulate in AD-TDP brains. We assessed a cohort of 192 post-mortem brains from three different brain regions: amygdala, hippocampus, and frontal cortex. Following RNA and protein extraction, qRT-PCR and immunoassays were performed to quantify the accumulation of cryptic RNA targets and phosphorylated TDP-43 pathology, respectively. Results We detected the accumulation of misspliced cryptic or skiptic RNAs of STMN2, KCNQ2, UNC13A, CAMK2B, and SYT7 in the amygdala and hippocampus of AD-TDP cases. The topographic distribution of cryptic RNA accumulation mimicked that of phosphorylated TDP-43, regardless of TDP-43 subtype classification. Further, cryptic RNAs efficiently discriminated AD-TDP cases from controls. Conclusions Overall, our results indicate that cryptic RNAs may represent an intriguing new therapeutic and diagnostic target in AD, and that methods aimed at detecting and measuring these species in patient biofluids could be used as a reliable tool to assess TDP-43 pathology in AD. Our work also raises the possibility that TDP-43 dysfunction and related changes in cryptic splicing could represent a common molecular mechanism shared between AD-TDP and FTLD-TDP.

Most of the deep-learning algorithms on stock price volatility prediction in the existing literature use data such as same-frequency market indicators or technical indicators, and less consider mixed-frequency data, such as macro-data. Compared with the traditional model that only inputs the same-frequency data such as technical indicators and market indicators, this study proposes an improved deep-learning model based on mixed-frequency big data. This paper first introduces the reserve restricted mixed-frequency data sampling (RR-MIDAS) model to deal with the mixed-frequency data and, secondly, extracts the temporal and spatial features of volatility series by using the parallel model of CNN-LSTM and LSTM, and finally utilizes the Optuna framework for hyper-parameter optimization to achieve volatility prediction. For the deep-learning model with mixed-frequency data, its RMSE, MAE, MSLE, MAPE, SMAPE, and QLIKE are reduced by 18.25%, 14.91%, 30.00%, 12.85%, 13.74%, and 23.42%, respectively. This paper provides a more accurate and robust method for forecasting the realized volatility of stock prices under mixed-frequency data.

Rationale Overactive bladder (OAB) is a common, distressing condition that worsens with age and impacts quality of life significantly. As a results of its clinical symptoms, patients suffer from serious physical and mental health issues, have a poor quality of life, and participate in a serious economic burden. The key social-psychological factors include living habits, eating habits, and personality characteristics on this disease, even though the pathogenesis of OAB is complex. However, there is few cognitions and research on OAB in the field of psychology. Methods/Search Strategy Between 2000 and 2022, two electronic databases were systematically searched in accordance with Cochrane library guidelines (PubMed/Medline, Web of Science). An analysis of the remaining articles with relevant information was conducted using a data extraction sheet. An itemized flow diagram was adopted and used to report systematic reviews and meta-analysis. A systematic review of studies published from 2000 to 2022 in English language were conducted and included in the review. The intended audience Urological surgeon and psychologists majoring in urinary diseases. Implication As a result of this information, we are able to develop a better understanding of the role of psychological factors in the development of OAB and suggest potential therapeutic directions for OAB patients. This may benefit the recovery of OAB patients.

Objectives This study aimed to clarify the relationship between white blood cell (WBC) and adverse pregnancy outcomes.Design A total of 25 270 pregnant women underwent peripheral blood white blood cell count tests in the first, second and third trimesters. Adverse pregnancy outcomes were gestational hypertension, pre-eclampsia, gestational diabetes mellitus, preterm birth, low birth weight, caesarean delivery, macrosomia and fetal distress. Due to acute infectious disease or other diseases, 1127 were excluded.Setting Minhang Hospital, China.Participants A total of 24 143 pregnant women were included in this study.Primary and secondary outcome measures The primary outcome was the adverse pregnancy outcomes.Results For the 24 143 participants, we calculated adjusted ORs for adverse pregnancy outcomes associated with an increased WBC count. For gestational hypertension, the ORs were 1.18 (95% CI, 1.05 to 1.24) in the first trimester and 1.10 (1.06 to 1.13) in the second trimester; for pre-eclampsia, ORs were 1.14 (95% CI, 1.47 to 1.64) in the first trimester and 1.10 (1.05 to 1.16) in the second trimester; for gestational diabetes mellitus, ORs were 1.06 (95% CI, 1.00 to 1.13) in the first trimester and 1.10 (1.04 to 1.16) in the second trimester; for preterm birth, ORs were 1.12 (95% CI, 1.06 to 1.18) in the first trimester, 1.10 (1.06 to 1.13) in the second trimester and 1.12 (1.09 to 1.15) in the third trimester; for low birth weight, ORs were 1.09 (95% CI, 1.02 to 1.17) in the first trimester, 1.03 (0.99 to 1.08) in the second trimester and 1.12 (1.08 to 1.16) in the third trimester. Significant associations were not observed obviously for caesarean delivery, macrosomia and fetal distress.Conclusions Our results indicate strong, continuous associations of maternal WBC count with increased risks of adverse pregnancy outcomes.

Treatments for neurodegenerative disease, including Frontotemporal dementia (FTD) and Amyotrophic lateral sclerosis (ALS), remain rather limited, underscoring the need for greater mechanistic insight and disease-relevant models. Our ability to develop novel disease models of genetic risk factors, disease modifiers, and other FTD/ALS-relevant targets is impeded by the significant amount of time and capital required to develop conventional knockout and transgenic mice. To overcome these limitations, we have generated a novel CRISPRi interference (CRISPRi) knockin mouse. CRISPRi uses a catalytically dead form of Cas9, fused to a transcriptional repressor to knockdown protein expression, following the introduction of single guide RNA against the gene of interest. To validate the utility of this model we have selected the TAR DNA binding protein (TDP-43) splicing target, stathmin-2 (STMN2). STMN2 RNA is downregulated in FTD/ALS due to loss of TDP-43 activity and STMN2 loss is suggested to play a role in ALS pathogenesis. The involvement of STMN2 loss of function in FTD has yet to be determined. We find that STMN2 protein levels in familial FTD cases are significantly reduced compared to controls, supporting that STMN2 depletion may be involved in the pathogenesis of FTD. Here, we provide proof-of-concept that we can simultaneously knock down Stmn2 and express the expanded repeat in the Chromosome 9 open reading frame 72 (C9ORF72) gene, successfully replicating features of C9-associated pathology. Of interest, depletion of Stmn2 had no effect on expression or deposition of dipeptide repeat proteins (DPRs), but significantly decreased the number of phosphorylated Tdp-43 (pTdp-43) inclusions. We submit that our novel CRISPRi mouse provides a versatile and rapid method to silence gene expression in vivo and propose this model will be useful to understand gene function in isolation or in the context of other neurodegenerative disease models.

Abstract Frontotemporal lobar degeneration with TDP-43 pathology (FTLD-TDP) is a neurodegenerative disease primarily affecting the frontal and/or temporal cortices. However, a growing body of evidence suggests that the cerebellum contributes to biochemical, cognitive, and behavioral changes in FTLD-TDP. To evaluate cerebellar TDP-43 expression and function in FTLD-TDP, we analyzed TDP-43 protein levels and the splicing of a TDP-43 target, STMN2, in the cerebellum of 95 FTLD-TDP cases and 25 non-neurological disease controls. Soluble TDP-43 was decreased in the cerebellum of FTLD-TDP cases but a concomitant increase in insoluble TDP-43 was not seen. Truncated STMN2 transcripts, an indicator of TDP-43 dysfunction, were elevated in the cerebellum of FTLD-TDP cases and inversely associated with TDP-43 levels. Additionally, lower cerebellar TDP-43 associated with a younger age at disease onset. We provide evidence of TDP-43 loss of function in the cerebellum in FTLD-TDP, supporting further investigation into this understudied brain region.

Summary: Blood neurofilament light chain (NFL) is proposed to serve as an estimate of disease severity in hospitalized patients with coronavirus disease 2019 (COVID-19). We show that NFL concentrations in plasma collected from 880 patients with COVID-19 within 5 days of hospital admission were elevated compared to controls. Higher plasma NFL associated with worse clinical outcomes including the need for mechanical ventilation, intensive care, prolonged hospitalization, and greater functional disability at discharge. No difference in the studied clinical outcomes between black/African American and white patients was found. Finally, vaccination associated with less disability at time of hospital discharge. In aggregate, our findings support the utility of measuring NFL shortly after hospital admission to estimate disease severity and show that race does not influence clinical outcomes caused by COVID-19 assuming equivalent access to care, and that vaccination may lessen the degree of COVID-19-caused disability.

The existing estimators for the drift coefficient in the diffusion model with jumps involve jump components and possess larger boundary error. How to effectively estimate the drift function is an important issue that faces challenges and has theoretical significance. In this paper, the gamma asymmetric kernel for boundary correction and threshold function eliminating jump impacts are combined to estimate the unknown drift coefficient in the jump diffusion process of interest rate. The asymptotic large sample property and the better finite sample property through the Monte Carlo numerical simulation experiment and the empirical analysis of SHIBOR and LIBOR for the corresponding estimator are considered in detail. It is found that the estimator proposed in this paper can correct the estimation error near or far away from the origin point, which provides a more asymptotic unbiased estimator for the drift function in diffusion models with jumps.

Eczema is a common inflammatory skin disorder during infancy. Evidence has shown that skin-microbiome fluctuations may precede eczema development, but their predictive value for eczema phenotypes remains unknown. We aimed to investigate the early-life evolution of the skin microbiome and its temporal associations with different pairs of eczema phenotypes (transient versus persistent, atopic versus non-atopic) in Chinese children. We followed 119 term Chinese infants from birth to 24 months old within a Hong Kong birth cohort. The skin microbes at the left antecubital fossa were serially sampled by flocked swabs at 1, 6, and 12 months for bacterial 16S rRNA gene sequencing. The atopic sensitization at 12 months was strongly associated with eczema persisting to 24 months (odds ratio 4.95, 95% confidence interval 1.29–19.01). Compared with those with non-atopic eczema, the children with atopic eczema had reduced alpha diversity at 12 months (p < 0.001) and transiently higher abundance of the genus Janibacter at 6 months (p < 0.001). Our findings suggest that atopic sensitization at 12 months may predict persistent eczema by 24 months, and atopic eczema at 12 months is associated with unique skin microbiome profiles at 6 and 12 months. Non-invasive skin-microbiome profiling may have predictive value for atopic eczema.

ABSTRACT Despite distinct nasopharyngeal microbiome (NPM) profiles between asthmatics and healthy subjects, little is known about the NPM dynamics and its relation to childhood asthma exacerbation (AE). We investigated NPM changes by longitudinally collecting 135 flocked nasopharyngeal swabs (FNPSs) from 33 school-age asthmatic children at six time points (2 to 4-week intervals) from September to December 2017 in Hong Kong. Subjects were categorized into AE and stable asthma (AS) groups according to whether they experienced any exacerbation during follow-up. One-off FNPSs from nine nonasthmatic children were included as controls. Microbiota profiles were analyzed using 16S rRNA gene sequencing. All 144 NPMs were classified into six microbiome profile groups (MPGs), each dominated by Moraxella, Corynebacterium 1, Dolosigranulum, Staphylococcus, Streptococcus, or Anoxybacillus. The microbial diversity and compositions of NPM in exacerbation samples were different from both baseline samples and those from healthy controls. Moraxella and Dolosigranulum-dominated NPM exhibited high temporal stability revealed by MPG transition analysis. NPM diversity decreased whereas microbial composition remained similar over time. The relative abundances of Moraxella increased while Corynebacterium 1, Anoxybacillus, and Pseudomonas decreased longitudinally. However, these temporal patterns did not differ between AE and AS groups, suggesting that short-term dynamic patterns were not sufficient to predict AE occurrence. Asthmatic NPM underwent Moraxella expansion during AE and presented a high microbiome resilience (recovery potential) after AE resolution. Microbial pathways involved in methane, ketone bodies, and vitamin B3 metabolisms were enhanced during AE and primarily contributed by Moraxella. IMPORTANCE Evidence on the dynamic changes of NPM in asthmatic patients remains limited. Here, we present that asthmatic NPMs deviating from a healthy status still showed resilience after disturbance. Our data imply from a longitudinal perspective that Moraxella increase is closely related to AE occurrence. The finding of functional dysbiosis (imbalance) during AE offers a plausible explanation for the known association between nasopharyngeal Moraxella expansion and increased AE risk. This work serves as a basis for future long-term prospective studies leveraging multiomics approaches to elucidate the temporal association between NPM and pediatric AE.

This paper presents the uniform concentration inequality for the stochastic integral of marked point processes. We developed a new chaining method to obtain the results. Our main result is presented under an entropy condition for partitioning the index set of the integrands. Our result is an improvement of the work of van de Geer on exponential inequalities for martingales in 1995. As applications of the main result, we also obtained the uniform concentration inequality of functional indexed empirical processes and the Kakutani–Hellinger distance of the maximum likelihood estimator.

Microbiome mediates early life immune deviation in asthma development. Recurrent wheeze (RW) in pre-school years is a risk factor for asthma diagnosis in school-age children. Dysbiosis exists in asthmatic airways, while its origin in pre-school years and relationship to RW is not clearly defined. This study investigated metagenomics of nasopharyngeal microbiome in pre-school children with RW. We applied whole-genome shotgun sequencing and human rhinovirus (HRV) detection on nasopharyngeal samples collected from three groups of pre-school children: (i) RW group: 16 children at-risk for asthma who were hospitalized for RW, (ii) inpatient control (IC): 18 subjects admitted for upper respiratory infection, and (iii) community control (CC): 36 children without respiratory syndromes. Sequence reads were analyzed by MetaPhlAn2 and HUMAnN2 algorithm for taxonomic and functional identification. Linear discriminant analysis effect size (LEfSe) analysis was used to identify discriminative features. We identified that Moraxella catarrhalis and Dolosigranulum pigrum were predominant species in nasopharynx. RW had lower alpha diversity (Shannon diversity index) than CC (0.48 vs. 1.07; Padj = 0.039), characterized by predominant Proteobacteria. LEfSe analysis revealed D. pigrum was the only discriminative species across groups (LDA = 5.57, P = 0.002), with its relative abundance in RW, IC, and CC being 9.6, 14.2, and 37.3%, respectively (P < 0.05). LEfSe identified five (ribo)nucleotides biosynthesis pathways to be group discriminating. Adjusting for HRV status, pre-school children with RW have lower nasopharyngeal biodiversity, which is associated with Proteobacteria predominance and lower abundance of D. pigrum. Along with discriminative pathways found in RW and CC, these microbial biomarkers help to understand RW pathogenesis.

Granular computing has advantage of knowledge discovery for complex data. In the paper, we present Fuzzy Granular Hyperplane Classifiers (FGHCs) for data classification from a new angle of Granular Computing. First, we introduce a fuzzy granular hyperplane concept by defining fuzzy granule, fuzzy granular vector, metrics and operators. Next, for binary classification problem, we present solving optimal fuzzy granular hyperplane through evolution strategy; the learning algorithm of parameters and the prediction algorithm of instances are also proposed. Finally, a multi-classification prediction model is designed by combining a set of Fuzzy Granular Hyperplane Classifiers based on vote strategy. In order to evaluate performance, we employed 10-fold cross validation to verify on UCI dataset and Alzheimer’s Disease Voice dataset. Theoretical analysis and experiments demonstrated that FGHCs have good performance.

Abstract Background Haemophilus parasuis is a commensal pathogen in the swine upper respiratory tract and causes Glässer’s disease. Surveillance, screening for infection, and vaccination response of H. parasuis is hindered by the lack of a rapid antibody detection method. Results In the present study, a monomeric autotransporter was identified as a novel antigen for developing an indirect ELISA. The autotransporter passenger domain (Apd) was expressed, purified, and demonstrated to be specific in ELISA and western blotting. Mouse antiserum of recombinant Apd (rApd) recognized native Apd in the 15 serotype reference strains and five non-typeable isolate stains, but showed no reaction with seven other bacterial pathogens. The rApd ELISA was optimized and validated using 67 serum samples with known background, including 27 positive sera from experimentally infected and vaccinated pigs along with 40 negative sera that had been screened with H. parasuis whole cell ELISA from clinically healthy herds. The rApd ELISA provided positive and negative percent agreements of 96.4 and 94.9%, respectively, and an AUC value of 0.961, indicating that the assay produced accurate results. Conclusion Apd was a universal antigen component among 15 serotype and non-typeable strains of H. parasuis and was also specific to this pathogen. The rApd ELISA could detect antibodies elicited by H. parasuis infection and vaccination, thereby exhibiting the potential to be applied for Glässer’s disease diagnosis, H. parasuis vaccination evaluation, and large-scale serological surveillance.

AbstractNumerous reports have suggested that infectious agents could play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated. To search for candidate agents in an unbiased fashion, we have developed a bioinformatic pipeline that identifies microbial sequences in mammalian RNA-seq data, including sequences with no significant nucleotide similarity hits in GenBank. Effectiveness of the pipeline was tested using publicly available RNA-seq data and in a reconstruction experiment using synthetic data. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis patients and controls, and identified sequences corresponding to known bacteria and viruses, as well as novel virus-like sequences. The presence of these novel virus-like sequences, which were identified in subsets of both patients and controls, were confirmed by quantitative RT-PCR. We believe this pipeline will be a useful tool for the identification of potential etiological agents in the many RNA-seq datasets currently being generated.

Objective: Recent studies have shown that neuregulin 4 (Nrg4), a member of the epidermal growth factor (EGF) family of extracellular ligands, plays an important role in the prevention of obesity, insulin resistance and nonalcoholic fatty liver disease (NAFLD). Considering that thyroid hormone (TH) has profound effects on whole-body energy metabolism, we speculate that circulating Nrg4 levels might be altered in patients with hyperthyroidism. Design and methods: A total of 129 hyperthyroid patients and 100 healthy subjects were recruited. Of them, 39 hyperthyroid patients received thionamide treatment for 3 months until euthyroidism. Serum Nrg4 levels were determined using the ELISA method. To further confirm the relationship between TH and Nrg4, C57BL/6 mice were treated with T3 and quantitative real-time PCR was performed to detect Nrg4 gene expression. Results: Serum Nrg4 levels were significantly elevated in hyperthyroid patients as compared with normal controls (3.84 ± 1.63 vs 2.21 ± 1.04 ng/mL, P < 0.001). After achieving euthyroidism by thionamide treatment, serum Nrg4 levels dropped markedly from 3.57 ± 1.26 to 1.94 ± 0.72 ng/ml (P < 0.001). After adjustment for potential confounders, serum Nrg4 levels were independently associated with hyperthyroidism. The upregulation of Nrg4 expression in the livers and white adipose tissues by T3 was further confirmed by animal and cell culture experiments. Conclusions: Serum Nrg4 levels were increased in patients with hyperthyroidism. The liver and white adipose tissue might be primary sources contributing to elevated serum Nrg4 concentrations.

Background: Many studies have demonstrated that microRNAs, a class of small and non-coding RNA molecules, play an important role in the regulation of glucose and lipid homeostasis. In the present study, we sought to investigate the function of miR-592 in the development of obesity-associated metabolic disorders, including hyperglycemia andinsulin resistance. Methods: The expression levels of miR-592 were measured in the liver of obese mice and humans by quantitative reverse transcription PCR. Loss- and gain-of function experiments were employed to explore the metabolic function of miR-592 using locked nucleic acids and adenovirus in lean and obese mice, respectively. The molecular target of miR-592 was determined by western blotting and luciferase reporter assays. Findings: We found a significant decreased expression of miR-592 in the liver of obese mice and humans. Inhibition of miR-592 led to elevated blood glucose levels, enhanced gluconeogenesis and reduced insulin sensitivity in lean mice. In contrast, adenovirus-mediated overexpression of hepatic miR-592 improved metabolic disorders in obese mice. Mechanistically, we found that the transcription factor forkhead box O1 (FOXO1) is a direct target gene of miR-592 to mediate its metabolic functions. miR-592 was able to inhibit the mRNA and protein expression of FOXO1 by binding to its 3′-untranslated region. Interpretations: Our findings demonstrate that obesity-associated down-regulation of miR-592 plays an important role in the progression of metabolic diseases. Restoration of hepatic miR-592 could improve glucose and lipid metabolism in obese mice. Fund: This work is supported by the National Key Research and Development Program of China (No. 2016YFC1304805 to Dr. Chen), Natural Science Foundation of China (No. 81771574 to Dr. Wu), Shanghai Science Foundation (No. 18ZR1437800 to Dr. Li), Science and Technology Commission of Shanghai Municipality (Nos.18dz2304400 and 15,411,970,700 to Dr. Yang). Keywords: Obesity, Gluconeogenesis, Insulin resistance, Liver steatosis, MicroRNAs, FOXO1

Summary: A G4C2 hexanucleotide repeat expansion in an intron of C9orf72 is the most common cause of frontal temporal dementia and amyotrophic lateral sclerosis (c9FTD/ALS). A remarkably similar intronic TG3C2 repeat expansion is associated with spinocerebellar ataxia 36 (SCA36). Both expansions are widely expressed, form RNA foci, and can undergo repeat-associated non-ATG (RAN) translation to form similar dipeptide repeat proteins (DPRs). Yet, these diseases result in the degeneration of distinct subsets of neurons. We show that the expression of these repeat expansions in mice is sufficient to recapitulate the unique features of each disease, including this selective neuronal vulnerability. Furthermore, only the G4C2 repeat induces the formation of aberrant stress granules and pTDP-43 inclusions. Overall, our results demonstrate that the pathomechanisms responsible for each disease are intrinsic to the individual repeat sequence, highlighting the importance of sequence-specific RNA-mediated toxicity in each disorder.

The existing index system for volatility forecasting only focuses on asset return series or historical volatility, and the prediction model cannot effectively describe the highly complex and nonlinear characteristics of the stock market. In this study, we construct an investor attention factor through a Baidu search index of antecedent keywords, and then combine other trading information such as the trading volume, trend indicator, quote change rate, etc., as input indicators, and finally employ the deep learning model via temporal convolutional networks (TCN) to forecast the volatility under high-frequency financial data. We found that the prediction accuracy of the TCN model with investor attention is better than those of the TCN model without investor attention, the traditional econometric model as the generalized autoregressive conditional heteroscedasticity (GARCH), the heterogeneous autoregressive model of realized volatility (HAR-RV), autoregressive fractionally integrated moving average (ARFIMA) models, and the long short-term memory (LSTM) model with investor attention. Compared with the traditional econometric models, the multi-step prediction results for the TCN model remain robust. Our findings provide a more accurate and robust method for volatility forecasting for big data and enrich the index system of volatility forecasting.

Stanniocalcin 2 (STC2), a secreted glycoprotein hormone, regulates many biological processes, including cell proliferation, apoptosis, tumorigenesis, and atherosclerosis. However, its role in hepatic triglyceride metabolism remains unknown. In the present study, we found that expression levels of STC2 were significantly reduced in the livers of leptin-deficient and high fat diet-induced obese mice. Systemic administration of STC2 recombinant protein or adenovirus-mediated overexpression of STC2 markedly attenuated hepatosteatosis and hypertriglyceridemia in obese mice. At the molecular level, we found that STC2 activated the STAT3 signaling pathway to inhibit lipogenic gene expression. Consistently, in vitro studies further showed that inhibition of STAT3 signaling abolished the anti-steatotic effects of STC2. Together, our results revealed an important role of STC2 in the regulation of hepatic triglyceride metabolism, which might provide a potential therapeutic target for the treatment of fatty liver and related metabolic disorders.

The aim of this study was to determine whether TPCN2 genetic variants are associated with type 2 diabetes and to elucidate which variants in TPCN2 confer diabetes susceptibility in the Chinese population.The sample population included 384 patients with type 2 diabetes and 1468 controls. Anthropometric parameters, glycemic and lipid profiles and insulin resistance were measured. We selected 6 TPCN2 tag single nucleotide polymorphisms (rs35264875, rs267603153, rs267603154, rs3829241, rs1551305, and rs3750965). Genotypes were determined using a Sequenom MassARRAY SNP genotyping system.Ultimately, we genotyped 3 single nucleotide polymorphisms (rs3750965, rs3829241, and rs1551305) in all individuals. There was a 5.1% higher prevalence of the rs1551305 variant allele in type 2 diabetes individuals (A) compared with wild-type homozygous individuals (G). The AA genotype of rs1551305 was associated with a higher diabetes risk (p