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Social networks can serve as a valuable communication channel for calls for help, offering assistance, and coordinating rescue activities in disaster. Social networks such as Twitter allow users to continuously update relevant information, which is especially useful during a crisis, where the rapidly changing conditions make it crucial to be able to access accurate information promptly. Social media helps those directly affected to inform others of conditions on the ground in real time and thus enables rescue workers to coordinate their efforts more effectively, better meeting the survivors' need. This paper presents a new sequence to sequence based framework for forecasting people's needs during disasters using social media and weather data. It consists of two Long Short-Term Memory (LSTM) models, one of which encodes input sequences of weather information and the other plays as a conditional decoder that decodes the encoded vector and forecasts the survivors' needs. Case studies utilizing data collected during Hurricane Sandy in 2012, Hurricane Harvey and Hurricane Irma in 2017 were analyzed and the results compared with those obtained using a statistical language model n-gram and an LSTM generative model. Our proposed sequence to sequence method forecast people's needs more successfully than either of the other models. This new approach shows great promise for enhancing disaster management activities such as evacuation planning and commodity flow management.

This exploration aims to explore how to use the new media technology of deep learning to analyze the cross-cultural differences between network users. First, the combination of edge computing and deep neural network model is adopted to complete data acquisition. Then, the network user behavior of the new media technology platform is analyzed. Finally, network user behavior and cross-cultural differences are studied. The survey data show that the interaction between new media technology and cross-cultural communication is very complex, which depends on the user behavior of the network society. Different behaviors of users produce different cultural exchange contents. Besides, most users of the new media technology platform will form independent individuals because they accept the past culture and ideas. The differences among individuals are closely related to their situation. There are also some differences in hobbies, habits and behaviors. People of different nationalities, skin colors, races and beliefs communicate on the network platform, because their communication crosses the obstacles of distance, time and language to a certain extent, and realizes cross-cultural interaction. Hence, for a country with a long cultural heritage and splendid historical civilization, the network society can significantly reflect the cultural differences between countries. The inclusiveness and openness of national culture provide great advantages for people to create new culture. This exploration provides a reference for relevant research and has a certain reference significance.

Background:. Vasovagal syncope (VVS) greatly impairs quality of life. The therapeutic efficacy of oral rehydration saline (ORS) for unselected VVS patients is not satisfactory due to the diverse mechanisms of the disease. Body mass index (BMI) was demonstrated to reflect blood volume to a certain extent. Therefore, the present study explored the capability of BMI to predict the therapeutic response of children with VVS to ORS treatment. Methods:. Seventy-four children with VVS who visited the Syncope Unit of Pediatrics at Peking University First Hospital from November 2010 to June 2019 receiving ORS treatment were enrolled for this retrospective case-control study. A comparison of demographic, clinical, and hemodynamic characteristics was performed between responders and non-responders. The correlation between baseline BMI and response time was analyzed. To determine the value of baseline BMI in predicting the therapeutic efficacy of ORS in children with VVS, a receiver operating characteristic curve analysis was performed. Results:. Fifty-two children were identified as responders, and the remaining 22 children were identified as non-responders. The baseline BMI of the responders was much lower than that of the non-responders (16.4 [15.5, 17.8] kg/m2vs. 20.7 ±e6 kg/m2, P

Background Despite considerable efforts, the pathogenic mechanisms of asthma are still incompletely understood, due to its heterogeneous nature. However, metabolomics can offer a global view of a biological system, making it a valuable tool for further elucidation of mechanisms and biomarker discovery in asthma. Methods GC-MS-based metabolomic analysis was conducted for comparison of urine metabolic profiles between asthmatic children (n=30) and healthy controls (n=30). Results An orthogonal projections to latent structures discriminant-analysis model revealed a clear separation of the asthma and control groups (R2x =0.137, R2y =0.947, Q2=0.82). A total of 20 differential metabolites were identified as discriminant factors, of which eleven were significantly increased and nine decreased in the asthma group compared to the control group. Pathway-enrichment analysis based on these differential metabolites indicated that sphingolipid metabolism, protein biosynthesis, and citric acid cycle were strongly associated with asthma. Among the identified metabolites, 2-hydroxybutanoic acid showed excellent discriminatory performance for distinguishing asthma from healthy controls, with an AUC of 0.969. Conclusion Our study revealed significant changes in the urine metabolome of asthma patients. Several perturbed pathways (eg, sphingolipid metabolism and citric acid cycle) may be related to asthma pathogenesis, and 2-hydroxybutanoic acid could serve as a potential biomarker for asthma diagnosis.

Immunosuppression of unknown aetiology is a hallmark feature of glioblastoma and is characterized by decreased CD4 T-cell counts and downregulation of major histocompatibility complex class II expression on peripheral blood monocytes in patients. This immunosuppression is a critical barrier to the successful development of immunotherapies for glioblastoma. We recapitulated the immunosuppression observed in glioblastoma patients in the C57BL/6 mouse and investigated the aetiology of low CD4 T-cell counts. We determined that thymic involution was a hallmark feature of immunosuppression in three distinct models of brain cancer, including mice harbouring GL261 glioma, B16 melanoma, and in a spontaneous model of diffuse intrinsic pontine glioma. In addition to thymic involution, we determined that tumour growth in the brain induced significant splenic involution, reductions in peripheral T cells, reduced MHC II expression on blood leucocytes, and a modest increase in bone marrow resident CD4 T cells. Using parabiosis we report that thymic involution, declines in peripheral T-cell counts, and reduced major histocompatibility complex class II expression levels were mediated through circulating blood-derived factors. Conversely, T-cell sequestration in the bone marrow was not governed through circulating factors. Serum isolated from glioma-bearing mice potently inhibited proliferation and functions of T cells both in vitro and in vivo. Interestingly, the factor responsible for immunosuppression in serum is non-steroidal and of high molecular weight. Through further analysis of neurological disease models, we determined that the immunosuppression was not unique to cancer itself, but rather occurs in response to brain injury. Non-cancerous acute neurological insults also induced significant thymic involution and rendered serum immunosuppressive. Both thymic involution and serum-derived immunosuppression were reversible upon clearance of brain insults. These findings demonstrate that brain cancers cause multifaceted immunosuppression and pinpoint circulating factors as a target of intervention to restore immunity.

To study the substitutability of noble metal electrodes in memristors, the effect of Pt/HfO2/Ti structure on the replacement of noble metal electrode Pt by different electrodes was studied. Compared with the unsubstituted devices, the HfO2-based RRAM devices with TiN and TiOxNy electrodes devices showed good resistive switching performance and resistive switching mechanism under oxygen ion migration. Five devices were prepared, and their resistive switching mechanism under oxygen ion migration was investigated. Moreover, besides the resistive switching phenomenon of these RRAM devices, it was found that significant rectifying characteristics were exhibited in a highresistance state (HRS). This phenomenon can be explained by regulation of the Schottky barrier of the interface between the top electrode and the resistive layer, which can be influenced by the migration of oxygen vacancies.

To improve the resistive switching performance of RRAM devices, it is desirable to find electrodes with good ability of oxygen reservoir. In this paper, bipolar switching mode of TiN/SiO2/FePt devices is achieved by using FePt as oxygen reservoir, since O atoms will be absorbed by Fe atoms to form FeOx film. Therefore, the oxygen reservoir’s ability can be evaluated by the molar ratio of FeOx in FePt film and it is found that the more molar ratio of FeOx the stronger oxygen reservoir’s ability is obtained. Interestingly, the self-rectifying characteristics in the devices with FePt electrode is observed due to the different work functions between TiN (4.7 eV) and FePt (> 5 eV). Furthermore, the transition between self-rectifying mode and diode mode can be achieved by controlling the applied voltage, which is beneficial for 1D1R architecture. The study in this paper may offer a method for fabrication of oxide-RRAM based 3D crossbar array with good performances.

Background Bone metabolism can be influenced by type 2 diabetes mellitus (T2DM). However, the relationship between T2DM and bone mineral density (BMD) remains inconsistent. This study explored the differences in BMD in middle-aged adults with and without T2DM. Methods We conducted a cross-sectional study of 4986 participants aged 40-59 years who participated in the National Health and Nutrition Examination Survey (NHANES) 2011-2018. We performed multivariable logistic regression models to evaluate the associations between T2DM status, serum glucose, glycohemoglobin (HbA1c), disease duration and lumbar BMD. Results There was a positive association between T2DM status and lumbar BMD in all three models (model 1: β=0.039, 95% CI: 0.025-0.052; model 2: β=0.045, 95% CI: 0.031-0.059; model 3: β=0.035, 95% CI: 0.014-0.055). In the subgroup analysis stratified by gender, this positive association existed in both gender after adjusting for confounders (males: β=0.033, 95% CI: 0.003-0.062; females: β=0.035, 95% CI: 0.008-0.062). Besides, there were no significant associations of serum glucose, HbA1c, disease duration with lumbar BMD in both genders with T2DM. Conclusion This study indicated that middle-aged adults with T2DM had significantly higher lumbar BMD compared with those without DM.

Background and Aims Potential drug resistance (DR) related variants in the hepatitis B virus (HBV) reverse transcriptase (RT) region may be associated with the effectiveness of antiviral drugs and disease progression. The aim of this study was to investigate the prevalence and clinical characteristics of potential DR-related variants in Chinese CHB patients not receiving nucleos(t)ide analogues (NAs). Patients and Methods Two hundred and six untreated CHB patients from Huzhou Central Hospital in eastern China were recruited for this study. The serum DNA was extracted and the HBV RT region was amplified using nest polymerase chain reaction (nest-PCR). The 42 potential DR-related variants were analyzed by direct sequencing. Results Among these CHB patients, HBV genotype B and genotype C were identified in 121 (58.7%) and 85 (41.3%) patients, respectively. Potential DR-related variants were detected in 42.7% (88/206) of patients. Primary and secondary DR variants were found in 7.3% (15/206) of patients, including rtL80I/V, rtI169T, rtV173L rtL180M, rtA181T/V, rtM204I/V, and rtN236T. The variants at rt53, rt82, rt221, rt233, rt237, and rt256 were specific for genotype B, and those at rt38, rt84, rt126, rt139, rt153, rt191, rt214, rt238, and rt242 were specific for genotype C. Moreover, the variation frequency in the A-B interdomain (3.96%) was significantly higher than that in the functional domains (1.17%) and non-A-B interdomains (1.11%). Multivariate logistic regression analysis showed that lower HBV-DNA load (

Background Multidrug-resistant tuberculosis (MDR-TB) is currently a major problem in China. The prevention and treatment work for MDR-TB patients started late in Anhui province. To determine the prevalence of MDR-TB in sputum smear-positive TB patients (SSPTBPs) and analyze the risk factors for MDR-TB in Anhui province, we conducted an investigation of drug resistance among SSPTB outpatients from September 2015 to August 2016. Methods A stratified cluster-randomized sampling method was used to obtain a representative sample. It was estimated that 2290 new cases and 440 previously treated cases of SSPTBPs needed to be recruited from 40 survey sites. Isolates were tested for resistance to six first-line and second-line anti-TB drugs. Information from patient questionnaire survey was used to identify factors linked to MDR-TB. Results Finally, a total of 3047 SSPTBPs were recruited from 40 survey sites; of these, 2530 specimens were successfully cultured and had drug susceptibility testing done. The proportions of rifampin resistant (RR)-TB were 11.42% (289/2530, 95% CI: 10.18-12.66%), 7.64% (163/2133, 95% CI: 6.38-8.62%) and 31.74% (126/397, 95% CI: 27.38-36.60%) in all cases, new cases and previously treated cases, respectively, and the proportions of confirmed MDR-TB were 7.63% (193/2530, 95% CI: 6.59-8.66%), 4.97% (106/2133, 95% CI: 4.05-5.89%) and 21.91% (87/397, 95% CI: 17.83-26.00%), respectively. The ofloxacin resistance rate in previously treated SSPTBPs reached 21.66% (95% CI: 17.33-26.75%). Patients who had received two or more anti-TB treatment courses were significantly associated with MDR-TB compared to patients who have received one anti-TB course. Conclusion MDR-TB prevalence was high among SSPTBPs in Anhui province, and past anti-TB treatment course was associated with MDR-TB.

This study investigated the impact of electrode materials on HfO₂-based RRAM devices. The research includes three types of electrode materials: (1) the electrodes with strong ability of oxygen reservoirs; (2) the electrode with poor ability of oxygen reservoirs; (3) the active electrode with injection ability. Through implementing different combinations of electrodes, three types of switching modes were obtained and the relative conduction mechanism was analyzed, as well as conduction model. Those studies may offer ways of using electrodes to control the resistive switching processes and fabricating the RRAM devices with good performance.

Fat accumulation in the liver cells can increase the risk of cardiac complications and cardiovascular disease mortality. Therefore, a way to quickly and accurately detect hepatic steatosis is critically important. However, current methods, e.g., liver biopsy, magnetic resonance imaging, and computerized tomography scan, are subject to high cost and/or medical complications. In this paper, we propose a deep neural network to estimate the degree of hepatic steatosis (low, mid, high) using only body shapes. The proposed network adopts dilated residual network blocks to extract refined features of input body shape maps by expanding the receptive field. Furthermore, to classify the degree of steatosis more accurately, we create a hybrid of the center loss and cross entropy loss to compact intra-class variations and separate inter-class differences. We performed extensive tests on the public medical dataset with various network parameters. Our experimental results show that the proposed network achieves a total accuracy of over 82 % and offers an accurate and accessible assessment for hepatic steatosis.

In order to improve the resistive switching performance of SiO2-based resistance random access memory (RRAM) devices, the evolution from pure oxide-based devices to metallic nanoparticle dispersed oxide-based devices is investigated in this paper. It is found that a high ratio of dispersed-oxide/pure-oxide and thin SiO2 film can increase the uniformity and endurance of RRAM devices. Pure TiN/SiO2/Au RRAM devices show large distributions and poor endurance for repeated resistive switching process, while the TiN/SiO2:FePt/SiO2/Au RRAM devices exhibit higher uniformity and better endurance. Moreover, the fluctuations and degradation of high-resistance state and low-resistance state are observed in the former devices; by increasing the ratio of dispersed-oxide/pure-oxide in TiN/SiO2/SiO2:FePt/SiO2/Au, high consistency resistive switching is obtained. It is believed that the random formation of conducting filaments (CFs) causes poor performance of RRAM devices, and with a higher ratio of dispersed-oxide/pure-oxide the morphology of CFs is controlled due to the local field enhancement. The results in this paper may provide a method of fabricating high-performance RRAM devices for industry application.

Objective: The clinical significance of coexistence of HBsAg/anti-HBs in chronic hepatitis B (CHB) patients remains controversial. This study was aimed to assess the association of this serological pattern with hepatocellular carcinoma (HCC) in patients with CHB. Methods: In this cross-section study, 206 CHB patients with coexistence of HBsAg/anti-HBs and 206 CHB patients with HBsAg alone were included to evaluate the risk of HCC development by logistic regression analysis. In addition, a retrospective cohort of 260 patients with CHB was recruited to estimate the cumulative incidence of HCC by Kaplan–Meier analysis. Results: The serological pattern of coexistence of HBsAg/anti-HBs, with high levels of (“High”) HBsAg/low levels of (“Low”) anti-HBs, were considered as independent risk factors for HCC. In particular, patients with “High” HBsAg/“High” anti-HBs [odds ratio (OR), 4.295; 95% confidence interval (CI), 1.104–16.699; p = 0.035] and “Low” HBsAg/ “High” anti-HBs (OR, 3.207; 95%CI, 1.299–7.919; p = 0.012) exhibited significantly higher risk for HCC development. However, only “Low” HBsAg /“High” anti-HBs might increase risk of HCC in CHB patients with high HBV load (logrank p

There continues to be a major need for more effective inflammatory bowel disease (IBD) therapies. IL-13Rα2 is a decoy receptor that binds the cytokine IL-13 with high affinity and diminishes its STAT6-mediated effector functions. Previously, we found that IL-13Rα2 was necessary for IBD in mice deficient in the anti-inflammatory cytokine IL-10. Here, we tested for the first time a therapeutic antibody specifically targeting IL-13Rα2. We also used the antibody and Il13ra2−/− mice to dissect the role of IL-13Rα2 in IBD pathogenesis and recovery. Il13ra2−/− mice were modestly protected from induction of dextran sodium sulfate (DSS)-induced colitis. Following a seven-day recovery period, Il13ra2−/− mice or wild-type mice administered the IL-13Rα2-neutralizing antibody had significantly improved colon health compared to control mice. Neutralizing IL-13Rα2 to increase IL-13 bioavailability promoted resolution of IBD even if neutralization occurred only during recovery. To link our observations in mice to a large human cohort, we conducted a phenome-wide association study of a more active variant of IL-13 (R130Q) that has reduced affinity for IL-13Rα2. Human subjects carrying R130Q reported a lower risk for Crohn’s disease. Our findings endorse moving anti-IL-13Rα2 into preclinical drug development with the goal of accelerating recovery and maintaining remission in Crohn’s disease patients.

The surveillance and preventions of infectious disease epidemics such as influenza and Ebola are important and challenging issues. It is therefore crucial to characterize the disease progress and epidemics process efficiently and accurately. Computational epidemiology can model the progression of the disease and its underlying contact network, but as yet lacks the ability to process of real-time and fine-grained surveillance data. Social media, on the other hand, provides timely and detailed disease surveillance but is insensible to the underlying contact network and disease model. To address these challenges simultaneously, this paper proposes a novel semi-supervised neural network framework that integrates the strengths of computational epidemiology and social media mining techniques for influenza epidemiological modeling. Specifically, this framework learns social media users’ health states and intervention actions in real time, regularized by the underlying disease model and contact network. The learned knowledge from social media can then be fed into the computational epidemic model to improve the efficiency and accuracy of disease diffusion modeling. We propose an online optimization algorithm that iteratively processes the above interactive learning process. The extensive experimental results provided demonstrated that our approach can not only outperform competing methods by a substantial margin in forecasting disease outbreaks, but also characterize the individual-level disease progress and diffusion effectively and efficiently.

The performance of TiN/HfO2/Ag resistive random-access memory (RRAM) devices combining the oxygen-based RRAM (OxRRAM) and conducting bridge random-access memory (CBRAM) was studied. Current compliance (CC) values could significantly affect the resistive switching process: with unidirectional CC, permanent breakdown for the devices was observed. With bidirectional smaller CC, the stable bipolar resistive switching mode was obtained, and the cation injection played a leading role in the resistive switching process, while the devices with higher CC always remained in low-resistance state (LRS). The resistance–voltage (R–V) curve and conducting mechanism were analyzed for the bidirectional smaller CC devices, indicating ohmic conduction for the LRS, while the space charge limited the current for the high-resistance state. The results of x-ray photoelectron spectroscopy showed that oxygen vacancies participated in the resistive switching process. It could be concluded that conducting paths were formed from conducting filaments of oxygen vacancies and conducting bridges of Ag grains, and the different formation rate of conducting filaments related to the values of CC was the prime reason for the various changes. Moreover, the characteristics of TiN/HfO2/Ta devices proved the universality of bidirectional CC. The method of making the OxRRAM and CBRAM coexist in the RRAM devices may offer a way to fabricate devices with low power consumption.

Background:. Vasovagal syncope (VVS) is common in children and greatly affect both physical and mental health. But the mechanisms have not been completely explained. This study was designed to analyze the gut microbiota in children with VVS and explore its clinical significance. Methods:. Fecal samples from 20 VVS children and 20 matched controls were collected, and the microbiota were analyzed by 16S rRNA gene sequencing. The diversity and microbiota compositions of the VVS cases and controls were compared with the independent sample t test or Mann-Whitney U test. The correlation between the predominant bacteria and clinical symptoms was analyzed using Pearson or Spearman correlation test. Results:. No significant differences in diversity were evident between VVS and controls (P > 0.05). At the family level, the relative abundance of Ruminococcaceae was significantly higher in VVS children than in controls (median [Q1, Q3]: 22.10% [16.89%, 27.36%] vs. 13.92% [10.31%, 20.18%], Z = −2.40, P 4, P

Previous studies reported that gender, age, diets or lifestyles could influence urine metabolomics, which should be considered in biomarker discovery. As a consequence, for the baseline of urine metabolomics characteristics, it becomes critical to avoid confounding effects in clinical cohort studies. In this study, we provided a comprehensive characterization of urine metabolomics in a cohort of 348 healthy children (Aged 1~18) and 315 adults (Aged 20-78) for evaluation gender and age effects. Our results suggested that urine metabolites showed larger gender differences in children than in adults. For both male/boy and female/girl, each age group showed specific metabolic characterization. Especially, the pantothenate and CoA biosynthesis and alanine metabolism pathways were enriched in early life. Androgen and estrogen metabolism showed high activity during adolescence and youth stages. Pyrimidine metabolism was enriched in the old stage. This work could help us understand the baseline of urine metabolism characteristics and contribute to further studies of clinical disease biomarker discovery.

Progressive remodeling of the left ventricle (LV) following myocardial infarction (MI) involves spatiotemporal interactions among multiple cell types and the extracellular matrix environment. Despite the extensive experimental studies designed to elucidate the regulatory mechanisms, there is a growing recognition that the complexity of LV remodeling precludes the efficient identification of early diagnostic indicators after myocardial infarction. Currently, systemic approaches are needed to reduce this complexity. Previous studies in other systems demonstrate that establishing a multi-scale analytical model of LV remodeling response to MI will likely help in the development of prognostic therapies. In this review, we discuss the current approaches used for mathematical modeling of the LV, advantages and disadvantages of the approaches, and methods used to validate these models.

Background Childhood-onset systemic lupus erythematosus (cSLE) is a kind of chronic inflammatory disease characterized by a highly abnormal immune system. This study aimed to detect the serum levels of Th (T helper) cytokines (IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-13, IL-17A, IL-17F, IL-21, IL-22, IFN-γ and TNF-α) in cSLE and healthy controls, and then to elucidate their association with clinical manifestations, disease activity and laboratory parameters. In order to provide clues for early diagnosis and timely intervention treatment of cSLE patients. Methods A total of 33 children with cSLE and 30 healthy children were enrolled in this study. Children in the cSLE group were classified into the inactive or active cSLE group according to their SLE disease activity index 2000 (SLEDAI-2 K) score. Th cytokine profiles in the peripheral blood were detected and analysed. Results Levels of IL-2, IL-10 and IL-21 in the cSLE group were significantly higher than those in the healthy control group (P P P P P P P P P P P P P P P +/CD8+, and the concentration of IL-6 (P Conclusion This study provides a theoretical basis for the discovery of effective methods to regulate imbalance in T lymphocyte subsets in cSLE, which may lead to new approaches for the diagnosis of cSLE.

Autonomous driving has gained popularity due to its high reliability compared to human drivers. Autonomous vehicles combine variety of sensors to perceive their surroundings, and use deep learning (DL) to extract complicated information from the sensing data. However, there are several challenges: Many DL models have explosive model sizes, and therefore not only time consuming but also power consuming when implementing on embedded systems on vehicles, further degrading the battery life-cycle. The current on-board AI treats lane detection and car location separately. In this paper, we propose an end-to-end multi-task environment detection framework. We fuse the 3D point cloud object detection model and lane detection model, with model compression technique applied. As on-board sensors forward information to the multi-task network, it not only parallel two detection tasks to extract combination information, but also reduces entire running time of the DL model. Experiments show by adding the model compression technique, the running speed of multi-task model improves more than $2\times$. Also, running time of lane detection model on Nvidia Jetson TX2 is almost $6\times$ less comparing with running on CPU, which shows reasonableness of using embedded AI computing device on autonomous vehicle.

Background It is reported that osteoporosis commonly occurs among patients with rheumatoid arthritis (RA), whereas the association between osteoporosis and osteoarthritis (OA) remains controversial. Our aim in this study was to investigate the association between BMD, as a marker of osteoporosis, and OA and RA among adults 20−59 years of age, using a population-based sample from the National Health and Nutrition Examination Survey (NHANES). Methods Our analysis was based on the NHANES data collected between 2011 and 2018. Data regarding arthritis status and the type of arthritis (OA or RA) were obtained from questionnaires. Lumbar BMD was measured by dual-energy X-ray absorptiometry. The association between OA, RA, and lumbar BMD was evaluated using logistic regression models. Subgroup analyses, stratified by gender and race, were performed. The association between duration of arthritis and lumbar BMD was also investigated. Results A total of 11,094 adults were included in our study. Compared to the non-arthritis group, participants with OA had a higher lumbar BMD (β = 0.023, 95% CI 0.011–0.035), with no significant association between lumbar BMD and RA (β = 0.014, 95% CI − 0.003 to 0.031). On subgroup analyses stratified by gender, males with OA had a higher lumbar BMD compared to those without OA (β = 0.047, 95% CI 0.028–0.066). In females, OA was not associated with lumbar BMD (β = 0.007, 95% CI − 0.008 to 0.021). There was no association between lumbar BMD and RA in both males (β = 0.023, 95% CI − 0.003 to 0.048) and females (β = 0.008, 95% CI − 0.015 to 0.031). Duration of arthritis was not associated with lumbar BMD for both OA (β = − 0.0001, 95% CI − 0.0017 to 0.0015) and RA (β = 0.0006, 95% CI − 0.0012 to 0.0025). Conclusions Lumbar BMD was associated with OA but not with RA. While a higher lumbar BMD was associated with OA in males, but not in females. Our findings may improve our understanding between OA, RA, and bone health.

Glioblastoma is associated with severe and multifaceted immunosuppression affecting all immune organs. Immunosuppression in GBM is a critical barrier to the success of immunotherapies and patient survival. We demonstrated that immunosuppression in the GL261-model of experimental GBM presents with significant thymic and spleen atrophy, MHCII downregulation, presence of potent immunosuppressive factors in serum, and sequestration of T-cells in the bone marrow. Parabiosis studies determined that soluble factors mediate immunosuppression by inhibiting T-cell proliferation, thymic involution, and loss of peripheral T-cells. In contrast, bone marrow T-cell sequestration was not mediated through soluble factors. While the immunosuppression in GBM is severe, a causative link between each facet of immunosuppression and overall survival is lacking. We used two strategies to block T-cell sequestration into the bone marrow and evaluated the extent survival was impacted in experimental GBM. First, we evaluated the extent a novel and off-the-shelf combination immunotherapy that uses extended 1/2-life IL-2 and anti-PD-1 reverses bone marrow T-cell sequestration. Sham treatment or anti-PD1 monotherapy did not alter T-cell sequestration in the bone marrow and animals had no enhanced survival. Extended 1/2-life IL-2 monotherapy and combination strategy both prevented T-cell sequestration into the bone marrow. However, only combined therapy, which also prevented MHC class II downregulation, improved survival. Second, we determined that glioma-bearing adrenalectomized mice do not present with bone marrow T-cell sequestration. However, sera of glioma-bearing adrenalectomized mice is as immunosuppressive as glioma-bearing controls. Blocking bone marrow T-cell sequestration in the presences of serum immunosuppression led to no survival benefit in glioma-bearing adrenalectomized mice compared to controls. In short, bone marrow T-cell sequestration alone does not correspond with overall survival in experimental glioma. Importantly, a concerted effort to reverse MHC class II downregulation and define inhibitory circulating factors may have the highest impact in immunotherapeutic efficacy and improving patient survival.

ECG signal classification is a popular topic in healthcare for arrhythmia detection. Recently, ECG signal analysis using supervised learning has been investigated with the goal to help physicians to automatically identify the premature atrial complex (PAC) heartbeats. PAC may be a sign of underlying heart conditions, which may change to supraventricular tachycardia that increases the possibility of sudden death. In this paper, we propose a data-driven approach, GFDLECG, which is based on ECG behavior to detect abnormal beats. We extract further features from ECG using the gradient feature generation algorithm. We also build the classification model by utilizing the gated recurrent unit (GRU) and the residual fully convolutional networks with GRU to learn long short-term patterns of ECG behaviors.

Respiratory diseases such as COVID-19, Pneumonia, SARS, and Streptococcus have caused severe worldwide public health concerns. Specifically, COVID-19, as an emerging worldwide pandemic, imposed the most critical challenge to all scientists and researchers for prognosis, diagnosis, and treatment of COVID-19 infection. This study aims to predict the aforementioned 4 respiratory diseases and normal people with chest X-ray and CT scan images using convolutional neural networks. A total of 1,156 images has been collected from 3 published databases. The combined dataset was enriched by empowering augmentation techniques and visual filters such as rotation and lung segmentation. The noises for augmentation include Gaussian and Speckle noises with zero mean and variance of 0.05, 0.10, and 0.20, and Salt and Pepper noise with 50% and 75% ratio. The customized convolutional neural network reached a prediction accuracy of 94% in classifying the test images into the normal and 4 disease categories, and 92%, 93%, and 92% as average precision, recall, and F1-score over all categories, respectively.

Automating pneumonia diagnosis from X-ray images could significantly improve patient diagnosing outcomes. A major challenge is that disease information (features) must be extracted directly from the image backgrounds. Motivated by recent advances in Convolutional Neural Network (CNN), we propose a hierarchical weighting deep learning model, ChestWNet, that combines DenseNet and transfer learning to detect and localize thoracic diseases from chest x-rays. Hierarchical weighting networks are designed to assign scores reflecting the importance of specific pixels (regions), and learning weights at pixel-, region-, and image-levels, jointly learning these hierarchical weighting networks and the image classification network in an end-to-end manner. Chest X-ray datasets are customized to solve the unbalancing label problem in these datasets. Extensive experiments show that ChestWNet significantly outperforms other established prediction methods, and can also be applied to similar scenarios with fixed point-of-interest regions in images.

Immunosuppression of unknown etiology is a hallmark feature of glioblastoma (GBM) and is characterized by decreased CD4 T cell counts and down regulation of MHC class II expression on peripheral blood monocytes in patients. This immunosuppression is a critical barrier to the successful development of immunotherapies for GBM. We recapitulated the immunosuppression observed in GBM patients in the C57BL/6 mouse and investigated the etiology of low CD4 T cell counts. We determined that thymic involution was a hallmark feature of immunosuppression in three distinct models of CNS cancer, including mice harboring GL261 glioma, B16 melanoma, and in a spontaneous model of Diffuse Intrinsic Pontine Glioma (DIPG). In addition to thymic involution, we determined that tumor growth in the brain induced significant splenic involution, reductions in peripheral T cells, reduced MHC class II expression on hematopoietic cells, and a modest increase in bone marrow resident CD4 T cells with a naïve phenotype. Using parabiosis we report that thymic involution, declines in peripheral T cell counts, and reduced MHC class II expression levels were mediated through circulating blood-derived factors. Conversely, T cell sequestration in the bone marrow was not governed through circulating factors. Serum isolated from glioma-bearing mice potently inhibited proliferation and functions of T cells both in vitro and in vivo. Interestingly, the factor responsible for immunosuppression in serum is nonsteroidal and of high molecular weight. Through further analysis of neurological disease models, we determined that the aforementioned immunosuppression was not unique to cancer itself, but rather occurs in response to CNS injury. Noncancerous acute neurological insults also induced significant thymic involution and rendered serum immunosuppressive. Both thymic involution and serum-derived immunosuppression were reversible upon clearance of brain insults. These findings demonstrate that CNS cancers cause multifaceted immunosuppression and pinpoint circulating factors as a target of intervention to restore immunity.

Importance In this study, we retrospectively investigated the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) antibodies within serum samples from children in Beijing, China. These findings provide preliminary guidance regarding population susceptibility to SARS‐CoV‐2, which will aid in establishing policy toward coronavirus disease 2019 (COVID‐19) prevention and control. Objective To understand the seropositivity of anti‐SARS‐CoV‐2 IgM/IgG antibodies among children in Beijing, China, evaluate the susceptibility of children in Beijing to SARS‐CoV‐2, and provide prima facie evidence to guide SARS‐CoV‐2 prevention and control. Methods IgM/IgG antibody kits (colloidal gold) were used to conduct preliminary screening of SARS‐CoV‐2 IgM/IgG antibodies in serum samples of children who presented to Beijing Children’s Hospital, Capital Medical University, having fever or requiring hospitalization, from March 2020 to August 2020. Statistical analysis of anti‐SARS‐CoV‐2 antibody seropositivity was performed according to the children’s general demographic characteristics, timing of admission to hospital, presence of pneumonia, and viral nucleic acid test results. Results The study included 19 797 children with both IgM and IgG antibody results. Twenty‐four children had anti‐SARS‐CoV‐2 IgM‐positive results (positive rate of 1.2‰), twelve children had anti‐SARS‐CoV‐2 IgG‐positive results (positive rate of 0.6‰). Viral nucleic acid test results were negative for the above‐mentioned children with positive antibody findings; during the study, two children exhibited positive viral nucleic acid test results, but their anti‐SARS‐CoV‐2 IgM/IgG antibody results were negative. Anti‐SARS‐CoV‐2 IgM antibody seropositivity was higher in the

Mutations in the methylenetetrahydrofolate reductase (MTHFR) gene can result in a reduced ability to utilize folic acid. The MTHFR 677C>T polymorphism in particular has been linked to both birth defects and pregnancy-associated diseases. This study aimed to evaluate the prevalence of the MTHFR 677C>T mutation among pregnant women in Yunnan Province so as to collect baseline data that may be utilized to guide folic acid supplementation efforts and to support related disease prevention programs. We retrospectively reviewed 3387 pregnant women from Yunnan Province. The MTHFR 677C>T polymorphism was identified using polymerase chain reaction (PCR) and DNA sequencing. In total, 1350 (39.9%) subjects were homozygous for the C allele (CC), 1540 (45.4%) subjects were heterozygous (CT), and 497 (14.7%) subjects were homozygous for the T allele (TT). The MTHFR 677C>T polymorphism was found to be present within the studied population, with ∼60% of these patients being either heterozygous or homozygous for the mutant allele and with an overall T allele frequency of 0.37. The frequency of the T allele was significantly higher among pregnant women with complications relative to women with healthy pregnancies, particularly among women T polymorphism may be a genetic risk factor associated with pregnancy complications and may help identify pregnant women at a high risk of such complications.

Wind energy, as a promising renewable and clean energy resource, has caused problems including power quality issues and electromagnetically oscillations such as sub-synchronous resonance. Virtual synchronous generator (VSG) has been proposed as a solution to improve dynamic frequency stability in wind turbines, but its impact on the risk of sub-synchronous resonance has not been investigated so far. This study, for the first time, presented that while VSG control helps tracking the rated frequency in normal operations and reviving the frequency during disturbances in the power grid, it increases the risk of occurrence of SSCI.

Adipokines, including leptin, visfatin, adiponectin, and interleukin-6 (IL)-6, play multiple roles in the pathophysiology of epilepsy and febrile seizures (FS). We aimed to investigate the associations among plasma adipokines, mainly leptin, visfatin, adiponectin, or IL-6, and the prognosis of FS. This prospective cross-sectional study was conducted from January 2017 to December 2018 at the Wuxi Second People' Hospital China. The levels of serum leptin, visfatin, adiponectin, and IL-6 in 55 children with FS (FS group) were compared with 42 febrile children without seizure (FC group) and 48 healthy children (HC group) in an acute phase. The correlation with clinical indicators was determined by logistic regression analysis. Serum adiponectin and IL-6 levels were significantly higher in the FS group than in the FC and HC groups (p < 0.05), but there was no statistical difference between the FC and HC groups. In addition, logistic regression analysis showed that high concentrations of adiponectin and IL-6 were significantly associated with the occurrence of FS. For leptin and visfatin, they were significantly lower in the FS and FC groups than in the normal control group, but there was no statistical difference between the FS and FC groups. Our results suggest that higher plasma levels of IL-6 and adiponectin may serve as an additional biomarker in the early treatment or follow-up of the FS children.

Cerebral palsy (CP), a group of clinical syndromes caused by non-progressive brain damage in the developing fetus or infant, is one of the most common causes of lifelong physical disability in children in most countries. At present, many researchers believe that perinatal cerebral hypoxic ischemic injury or inflammatory injury are the main causes of cerebral palsy. Previous studies including our works confirmed that melatonin has a protective effect against convulsive brain damage during development and that it affects the expression of various molecules involved in processes such as metabolism, plasticity and signaling in the brain. Integral membrane protein plppr5 is a new member of the plasticity-related protein family, which is specifically expressed in brain and spinal cord, and induces filopodia formation as well as neurite growth. It is highly expressed in the brain, especially in areas of high plasticity, such as the hippocampus. The signals are slightly lower in the cortex, the cerebellum, and in striatum. Noteworthy, during development plppr5 mRNA is expressed in the spinal cord, i.e., in neuron rich regions such as in medial motor nuclei, suggesting that plppr5 plays an important role in the regulation of neurons. However, the existing literature only states that plppr5 is involved in the occurrence and stability of dendritic spines, and research on its possible involvement in neonatal ischemic hypoxic encephalopathy has not been previously reported. We used plppr5 knockout (plppr5−/−) mice and their wild-type littermates to establish a model of hypoxicischemic brain injury (HI) to further explore the effects of melatonin on brain injury and the role of plppr5 in this treatment in an HI model, which mainly focuses on cognition, exercise, learning, and memory. All the tests were performed at 3–4 weeks after HI. As for melatonin treatment, which was performed 5 min after HI injury and followed by every 24h. In these experiments, we found that there was a significant interaction between genotype and treatment in novel object recognition tests, surface righting reflex tests and forelimb suspension reflex tests, which represent learning and memory, motor function and coordination, and the forelimb grip of the mice, respectively. However, a significant main effect of genotype and treatment on performance in all behavioral tests were observed. Specifically, wild-type mice with HI injury performed better than plppr5−/− mice, regardless of treatment with melatonin or vehicle. Moreover, treatment with melatonin could improve behavior in the tests for wild-type mice with HI injury, but not for plppr5−/− mice. This study showed that plppr5 knockout aggravated HI damage and partially weakened the neuroprotection of melatonin in some aspects (such as novel object recognition test and partial nerve reflexes), which deserves further study.

Anti-theft problem has been challenging since it mainly depends on the existence of external devices to defend from thefts. Recently, driver behavior analysis using supervised learning has been investigated with the goal to detect burglary by identifying drivers. In this paper, we propose a data-driven technique, LiveDI, which uses driving behavior removing the use of external devices in order to identify drivers. The built model utilizes Gated Recurrent Unit (GRU) and Fully Convolutional Networks (FCN) to learn long-short term patterns of the driving behaviors from drivers. Additionally, we improve the training time by utilizing the Segmented Feature Generation (SFG) algorithm to reduce the state space where the driving behaviors are split with a time window for analysis. Extensive experiments are conducted which show the impact of parameters on our technique and verify that our proposed approach outperforms the state-of-the-art baseline methods.

Background Cancer has been a leading cause of death in the United States with significant health care costs. Accurate prediction of cancers at an early stage and understanding the genomic mechanisms that drive cancer development are vital to the improvement of treatment outcomes and survival rates, thus resulting in significant social and economic impacts. Attempts have been made to classify cancer types with machine learning techniques during the past two decades and deep learning approaches more recently. Results In this paper, we established four models with graph convolutional neural network (GCNN) that use unstructured gene expressions as inputs to classify different tumor and non-tumor samples into their designated 33 cancer types or as normal. Four GCNN models based on a co-expression graph, co-expression+singleton graph, protein-protein interaction (PPI) graph, and PPI+singleton graph have been designed and implemented. They were trained and tested on combined 10,340 cancer samples and 731 normal tissue samples from The Cancer Genome Atlas (TCGA) dataset. The established GCNN models achieved excellent prediction accuracies (89.9-94.7%) among 34 classes (33 cancer types and a normal group). In silico gene-perturbation experiments were performed on four models based on co-expression graph, co-expression+singleton, PPI graph, and PPI+singleton graphs. The co-expression GCNN model was further interpreted to identify a total of 428 markers genes that drive the classification of 33 cancer types and normal. The concordance of differential expressions of these markers between the represented cancer type and others are confirmed. Successful classification of cancer types and a normal group regardless of normal tissues' origin suggested that the identified markers are cancer-specific rather than tissue-specific. Conclusion Novel GCNN models have been established to predict cancer types or normal tissue based on gene expression profiles. We demonstrated the results from the TCGA dataset that these models can produce accurate classification (above 94%), using cancer-specific markers genes. The models and the source codes are publicly available and can be readily adapted to the diagnosis of cancer and other diseases by the data-driven modeling research community.

The accurate detection of the weak magnetic signal has important applications in many fields, and lock-in amplifiers are often used in them. However, commercial lockin amplifiers are expensive and bulky, and are not suitable for use in field environments such as the magnetic exploration. In this paper, a weak magnetic signal detection system is designed based on a portable lock-in amplifier, which is used to solve the problem. The system takes the portable lock-in amplifier circuit as its core, and contains a fluxgate sensor. Combined with A/D acquisition and LabVIEW, the system achieves the real-time display of measurement data on the laptop. Experimental results show that the correlation coefficient of input and output of the system is up to 0.998 under the noise environment. The system achieves the effective measurement of the amplitude of the weak alternating magnetic field signal when the interference magnetic fields are complex. The detection system has the characteristics of high resolution, good linearity and portability, and has good potential for field applications.

Background A prompt diagnosis of HIE remains a challenge clinically. This study aimed to identify potential biomarkers of neonatal hypoxic-ischemic encephalopathy (HIE) via a novel proteomic approach, the isobaric tags for absolute and relative quantification (iTRAQ) method. Methods Blood samples were collected from neonates with mild (n = 4), moderate (n = 4), or severe (n = 4) HIE who were admitted to the neonatal intensive care unit of Children’s Hospital of Soochow University between Oct 2015 and Oct 2017. iTRAQ was performed in HIE patients and healthy controls (n = 4). Bioinformatics analyses including Gene Ontology and KEGG pathway enrichment analysis were performed to evaluate the potential features and capabilities of the identified differentially expressed proteins. Results A total of 51 commonly differentially expressed proteins were identified among the comparisons between mild, moderate, and severe HIE as well as healthy controls. Haptoglobin (HP) and S100A8 were most significantly up-regulated in patients with HIE and further validated via real-time PCR and western blotting. The differentially expressed proteins represented multiple biological processes, cellular components and molecular functions and were markedly enriched in complement and coagulation cascades. Conclusions HP and S100A8 may serve as a potential biomarker for neonatal HIE and reflects the severity of HIE. The complement and coagulation cascades play crucial roles in the development of neonatal HIE.

Downregulation of microRNA-200b (miR-200b) has been identified in a range of cancers, yet the specific mechanisms whereby it influences lung cancer growth require further exploration. We determined that lung cancer patient tumor samples exhibit decreased miR-200b expression, and we further found this miRNA to inhibit tumor growth via interfering with ERK1/2 and AKT signaling, targeting p70S6K1 to suppress HIF-1α expression. This miRNA further rendered H1299 cells more sensitive to cisplatin while impairing their proliferative and invasive potential through its ability to target and inhibit the activity of p70S6K1. These results were further confirmed in a murine xenograft model in which miR-200b also inhibited the growth of tumor and suppressed p70S6K1, p-AKT, p-ERK1/2, and HIF-1α expression. These findings clearly demonstrate a role for miR-200b in suppressing lung cancer development, making it a potentially relevant target for future diagnostic and therapeutic interventions.

Background Occlusive granulation tissue formation, as one of the most common sequelae of chronic foreign body aspiration, can cause tracheobronchial obstruction and delayed fixed airway stenosis necessitating interventions. The aim of this study was to explore the clinical efficacy and safety of interventional therapy via flexible bronchoscopy for treatment of granulation tissue related airway obstruction secondary to foreign body aspiration in children. Method Patients with long-term foreign body related granulation tissue were treated with flexible bronchoscopy therapeutic modalities, including forceps, cryotherapy, holmium laser, and balloon dilatation. Clinical efficacy was evaluated by clinical symptoms and endoscopic manifestations. Results A total of eight patients with granulation tissue hyperplasia caused by foreign body in bronchus, with a median age of 29.5 (range, 18-54) months, underwent interventional therapy between January 2016 and December 2019. Four patients received forceps and CO2 cryotherapy and one patient required forceps only. The remaining three patients received holmium laser combined with CO2 cryotherapy, and one of them required additional balloon dilatation. Four cases required a second cryotherapy procedure, and one case received three cryotherapy procedures for extensive granulation tissue. The treatment efficacy was 100% without complications. Conclusion Interventional procedure via flexible bronchoscopy is a safe, reliable, and effective method in the management of tracheobronchial obstruction and stenosis caused by foreign body-related granulation tissue hyperplasia. It is worthy of clinical application.

Mycoplasma pneumoniae (MP) is one of the most common pathogens of respiratory infection in children, while Epstein-Barr virus (EBV) infection is usually subclinical in immunocompetent children. Although single MP infection is common enough, MP and EBV coinfection have received little attention. Especially, the pathogenic role of EBV in lung when coinfection with MP, has not been clarified. The purpose of this study was to investigate the impact of EBV on MP pneumonia (MPP) in hospitalized children. We retrospectively reviewed the clinical data of MPP children who underwent screening for EBV by polymerase chain reaction in bronchoalveolar lavage fluid during hospitalization in 2014. Of total 147 patients, 68 patients were in the MP group and 79 were in the MP/EBV coinfection group. We found longer fever duration and higher CRP, IgA, IgG, interleukin-2 (IL-2), percentage of peripheral neutrophils levels, higher incidence of pulmonary consolidation and percentage of refractory MPP in coinfection group, when compared to those in MP group. In ROC curve analysis, IL-2 was useful for differentiating patients with coinfection from those with MP infection. Logistic regression analysis showed that the IL-2 ≥ 3.35 pg/ml (OR = 3.677) was a significant predictor regarding to MP/EBV coinfection. In conclusion, coinfection of EBV and MP poses a higher risk for prolonged symptoms. IL-2 could be used as a good predictor of coinfection.

Efficient job scheduling on data centers under heterogeneous complexity is crucial but challenging since it involves the allocation of multi-dimensional resources over time and space. To adapt the complex computing environment in data centers, we proposed an innovative Advantage Actor-Critic (A2C) deep reinforcement learning based approach called A2cScheduler for job scheduling. A2cScheduler consists of two agents, one of which, dubbed the actor, is responsible for learning the scheduling policy automatically and the other one, the critic, reduces the estimation error. Unlike previous policy gradient approaches, A2cScheduler is designed to reduce the gradient estimation variance and to update parameters efficiently. We show that the A2cScheduler can achieve competitive scheduling performance using both simulated workloads and real data collected from an academic data center.

ObjectivePulmonary tuberculosis (TB) is a severe infectious respiratory disease, the burden of which remains high in China. To provide scientific evidence for developing more targeted prevention and control strategies, this study aimed to determine the incidence trends and explore the epidemiological characteristics of pulmonary TB in Anhui Province, Eastern China between 2013 and 2018.MethodsThe retrospective study analyzed information regarding pulmonary TB cases reported by the National Infectious Disease Reporting System and census data collected from the Anhui Provincial Bureau of Statistics.ResultsOverall, 211,892 cases of TB patients were reported in Anhui Province, China between 2013 and 2018, with an average annual reported incidence rate of 57.7 per 100,000 persons. A significant decrease in the incidence rate of pulmonary TB (p < 0.001) was observed during the study period. Men had a higher incidence rate of pulmonary TB than women (p < 0.001). The highest annual average reported incidence rate was 204.2 per 100,000 persons in those aged 70-74 years. The number of farmers with pulmonary TB, i.e., 155,415, accounted for 73.4% of all cases. Moreover, the peak period of reported cases was from January to March. Four cities along the Yangtze River-Anqing, Tongling, Chizhou, and Wuhu-reported significantly higher incidence rates of pulmonary TB than other cities (p < 0.001).ConclusionsFrom 2013 to 2018, there was a significant decline in the incidence rate of pulmonary TB in Anhui Province, with peaks occurring from January to March. Prevention and control strategies targeting men, people aged 70-74 years, farmers, and the four cities along the Yangtze River should be strengthened.

Genome-wide associations and HLA genotyping have revealed associations between HLA alleles and susceptibility to primary membranous nephropathy. However, associations with clinical phenotypes and kidney outcome are poorly defined. We previously identified DRB1*1501 and DRB1*0301 as independent risk alleles for primary membranous nephropathy. Here, we investigated HLA associations with demographic characteristics, anti-phospholipase A2 receptor (PLA2R) antibody, treatment response and kidney outcome after a median follow-up of 52 months in 258 patients. DRB1*0301, but not DRB1*1501, was associated with a significantly higher level of PLA2R antibody (odds ratio 1.58, 95% confidence interval 1.13-2.22). Although DRB1*1502, which differs from DRB1*1501 by a single amino acid, was not a risk allele for primary membranous nephropathy (odds ratio 1.01), it was associated with significantly lower estimated glomerular filtration rates both at baseline (1.79, 1.18-2.72) and at last follow-up (1.72, 1.17-2.53), a significantly worse renal outcome by Kaplan-Meier analysis and a significantly higher risk of end-stage renal disease by Cox regression analysis (hazard ratio 4.52, 1.22-16.74). Nevertheless, the absence of remission remained the only independent risk factor for end-stage renal disease by multivariate analysis. DRB1*1502 was also associated with a significantly higher median PLA2R antibody level [161.4 vs. 36.3 U/mL] and showed interaction with DRB1*0301 for this variable. Thus, HLA genes control PLA2R antibody production and primary membranous nephropathy severity and outcome. Additionally, DRB1*1502 behaves like a modifier gene with a strong predictor value when associated with HLA risk alleles. Other modifier genes need further investigations in larger cohorts.

We propose and analyse a novel optical pressure sensor based on series-coupled double microring resonators (SDMRRs) on a simple beam. The pressure applied on the sensor is measured through the chan...

It is widely acknowledged that addiction relapse is highly associated with spatial-temporal factors such as some specific places or time periods. Current studies suggest that those factors can be utilized for better relapse interventions, however, there is no relapse prevention application that makes use of those factors. In this paper, we introduce a mobile app called "Addict Free", which records user profiles, tracks relapse history and summarizes recovering statistics to help users better understand their recovering situations. Also, this app builds a relapse recovering community, which allows users to ask for advice and encouragement, and share relapse prevention experience. Moreover, machine learning algorithms that ingest spatial and temporal factors are utilized to predict relapse, based on which helpful addiction diversion activities are recommended by a recovering recommendation algorithm. By interacting with users, this app targets at providing smart suggestions that aim to stop relapse, especially for alcohol and tobacco addiction users., 4 pages

In order to increase the resistive switching performance of memory devices based on TiN electrode, it is desirable to fabricate TiN with good oxygen reservoir ability. In the present paper, we report that the crystallized (200) textured TiN electrode were achieved by epitaxial grown on CrRu intermediate layer, which had better oxygen reservoir ability than the amorphous TiN. It is found that the Pt/HfO2/TiN devices with crystallized TiN electrode exhibited a typical bipolar resistive switching behavior, while the I-V curves of the Pt/HfO2/TiN devices with amorphous TiN electrode showed the unipolar resistive switching behavior regardless of voltage polarity, which is similar to the Pt/HfO2/Pt devices. It is believed that this originates from the different oxygen reservoir ability of TiN with different fabricating process. Moreover, the RRAM device with the new structure of TiN (amorphous)/HfO2/TiN (crystallized) exhibited the bipolar resistive switching behavior. This further proved the amorphous TiN electrode had poorer ability of oxygen reservoir than crystallized TiN, which was similar to a noble electrode like Pt electrode. Tuning the resistive switching behaviors of RRAM devices by controlling the crystalline state of TiN electrode may offer a method for fabrication of transition metal oxides based RRAM device with good performances.

Histone deacetylases (HDAC) plays important roles in the post-translational modifications of histone cores as well as non-histone targets. Many of them are involved in key inflammatory processes. Despite their importance, whether and how HDAC9 is regulated under inflammatory conditions remains unclear. The aim of this study was to evaluate the effects of HDAC9 under chronic inflammation condition in human periodontal ligament stromal cell (PDLSCs) and to explore the underlying regulatory mechanism. PDLSCs from healthy or periodontitis human tissue was compared. The therapeutic effects of HDAC inhibitors was determined in PDLSC pellet transplanted nude mice and LPS-induced rat periodontitis. We report that HDAC9 was the most affected HDAC family member under inflammatory conditions in PDLSCs. HDAC9 impaired osteogenic differentiation capacity of PDLSCs under inflammatory conditions. Downregulation of HDAC9 by HDAC inhibitors or si-HDAC9 rescued the osteogenic differentiation capacity of inflammatory PDLSC to a similar level with the healthy PDLSC. In this context, HDAC9 and miR-17 formed an inhibitory loop. The inhibition of miR-17 aggravated loss of calcified nodules in inflamed PDLSCs and interrupted the effect of HDAC inhibitor in rescuing osteogenesis. In vivo experiments using nude mice and LPS-induced periodontitis model confirmed that HDAC inhibitors could improve new bone formation. We conclude that HDAC inhibitors improved osteogenesis of PDLSCs in vitro and periodontitis in vivo.