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Sinomenine (SIN) is commonly used as part of rheumatoid arthritis (RA) therapy in China, but there is still no published evidence of the efficacy of SIN monotherapy. This work investigates the efficacy and safety of SIN in treating RA patients and analyzes the correlation between ornithine level and the alleviation of disease activity in RA patients. In this 24 week, randomized, placebo-controlled, double-blind clinical trial, people with mild to moderate RA were randomly assigned (1:1:1, stratified by hospital) to receive SIN (120 mg, twice daily), methotrexate (MTX) (10 mg per week), or SIN + MTX therapy. The primary outcome was the proportion of patients who achieved a 50% improvement in the American College of Rheumatology (ACR) criteria at week 24 and who showed improvement according to the clinical disease activity index (CDAI). In this prospective subgroup analysis, we also assessed whether the 24 week alterations of disease activity in the treatment group were significantly correlated to the levels of blood ornithine. Of the 135 enrolled participants, 38, 39, and 36 patients were treated with SIN, MTX, and SIN + MTX, respectively. In the SIN-treated group, 52.63% of patients achieved ACR50 after 24 weeks of treatment, which was comparable to the results in the MTX-treated and SIN + MTX-treated groups. Hepatic and gastrointestinal disorders were the main adverse events; however, the ratio of patients suffering from hepatic disorder in the SIN group (1/38) was much lower than that in the MTX (10/39) and SIN + MTX (8/36) groups. A total of 221 serum samples were collected at the four follow-up time points in the three treatments, and the levels of ornithine, citrulline, and arginine were obtained through ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS). The serum ornithine level decreased after the 24 week treatment along with a decrease in disease activity, and may reflect therapeutic responses with a sensitivity value of 80%. In conclusion, SIN revealed a comparable efficacy to MTX for treating RA patients, but with fewer side effects. In addition, the serum ornithine level was found for the first time to have a close correlation with the alleviation of RA, which shows the value of this measure as an assessment indicator of drugs in treating RA.

BACKGROUND: Racial/ethnic minorities face stark inequalities in lung cancer incidence, treatment, survival, and mortality compared with U.S. born non-Hispanic Whites. Lung cancer screening (LCS) with low-dose computed tomography (LDCT) is effective at reducing lung cancer mortality in high-risk current and former smokers and is recommended by the U.S. Preventive Services Task Force (USPSTF). This study sought to assess primary care providers’ (PCPs’) knowledge, attitudes, beliefs, and practice related to LCS and the recent USPSTF guidelines in five high risk immigrant communities in New York City. METHODS: We surveyed 83 eligible PCPs between December 2016 and January 2018 through surveys sent by mail, email, and fax, administered by phone or in-person. The survey included questions about providers’ clinical practice, knowledge, attitudes and beliefs related to LCS and the USPSTF guidelines. Information about patient demographics, PCPs’ training background and practice type were also collected. RESULTS: Sixty-seven percent of respondents reported that they did not have established guidelines for LCS at their practice and 52% expressed that “vague” screening criteria influenced their referral processes for LCS. Barriers to LCS with LDCT included concerns that LDCT is not covered by insurance, patients’ fears of screening results, and patients’ concerns regarding radiation exposure. DISCUSSION: Targeted educational interventions for both PCPs and patients may increase access to recommended LCS, especially for populations at disproportionate risk for lung cancer.

A multi-port converter with bipolar outputs to integrate renewable energy and energy storage into the bipolar dc bus is the desirable solution due to its high reliability and efficiency. A novel symmetric bipolar outputs full-bridge four-port converter based on phase-shift modulated buck-boost voltage balancer is proposed in this paper. The interleaved bidirectional buck/boost circuit with pulse width modulation is used as the primary side to achieve the integration of renewable energy and energy storage, while the phase-shift modulated buck-boost voltage balancer is derived as a secondary side circuit to generate a symmetrical and common ground bipolar output voltage. Single-stage power conversion, symmetrical bipolar output voltage, approximately decoupled control loop, and soft switching can be realized in the proposed four-port converter. Detailed analysis of the proposed converter is presented, including operation principle, steady-state performance, soft switching performance, and control method. Finally, experimental verifications are carried out to illustrate the feasibility and effectiveness of the proposed topology.

Blockchain, an emerging paradigm of secure and shareable computing, is a systematic integration of 1) chain structure for data verification and storage, 2) distributed consensus algorithms for generating and updating data, 3) cryptographic techniques for guaranteeing data transmission and access security, and 4) automated smart contracts for data programming and operations. However, the progress and promotion of Blockchain have been seriously impeded by various security issues in blockchain-based applications. Furthermore, previous research on blockchain security has been mostly technical, overlooking considerable business, organizational, and operational issues. To address this research gap from the perspective of information systems, we review blockchain security research in three levels, namely, the process level, the data level, and the infrastructure level, which we refer to as the PDI model of blockchain security. In this survey study, we first examine the state of blockchain security in the literature. Based on the insights obtained from this initial analysis, we then suggest future directions of research in blockchain security, shedding light on urgent business and industrial concerns in related computing disciplines.

The rapidly growing number of Internet of Things (IoT) devices poses new challenges for spectrum management in future wireless communication networks. It is critical to achieve efficient and dynamic spectrum management in the sixth-generation wireless communication networks (6G) era. To tackle the challenges of managing a large-scale IoT network with heterogeneous devices, we propose a directed acyclic graph (DAG) blockchain enhanced user-autonomy spectrum sharing model. As the proposed consensus rule is closely related to system utility, the swarm intelligence of users gradually reaches the point of convergence in the process of blockchain consensus. We analyse the effect of the tip selection method of DAG blockchain on spectrum allocation utility. A dynamic tip selection method is proposed to enhance the global utility, which is related to the spectrum supply-demand. In addition, the ring signature technique is utilized to realize privacy protection during the sharing process. Simulation indicates that the proposed tip selection method achieves a 10% enhancement in terms of the global utility. Furthermore, significant reductions in administrative expense and reliability improvement are demonstrated by the simulation results. The stability of the tip number in the proposed model has been proved theoretically, which is also validated by simulation experiments.

Location-Based Social Networks have been widely studied in recent years; new approaches constantly developed to solve individuals' trajectory prediction tasks. However, most of these methods require sufficient data to learn individual features, which is not always satisfied in real situations, especially for online data. The digital data on human behavior typically follows a power-law distribution, indicating that only a few people have rich activities recorded while most people's behavioral data are limited. In order to overcome this hurdle, our work constructs the user behavior proximity network (UBPN) and proposes a new walking strategy based on this network that extracts the hidden information from the social contacts to substitute the unobserved behavioral information of an individual. Specifically, our proposed walking strategy has two walking paths, accounting for the temporal and social information on the ego users' and their alters' mobility activities. This walking strategy is model-agnostic and can be integrated with many existing walk-based deep learning methods. Our work applies the methods on two real-world datasets with rich spatiotemporal information and shows that the performances of the existing prediction methods improve significantly by integrating the proposed walking strategy.

BACKGROUND: Chinese immigrant for-hire vehicle (FHV) drivers who smoke or smoked are at high risk for lung cancer due to the combined impact of tobacco use and air pollution exposure yet underutilize lung cancer screening (LCS). Community Health Worker (CHW) programs have been effective at improving cancer screening rates. This study describes a community needs assessment to inform the adaptation of an existing CHW intervention to facilitate LCS among Chinese FHV drivers. METHODS: Interviews were conducted until saturation with 13 Chinese-serving health professionals to determine the community’s needs, priorities, and preferences. Transcripts were qualitatively analyzed using Atlas.ti. RESULTS: Seven frequently occurring themes were identified: Knowledge of Guidelines/Access to LCS, Acceptability of CHW Program, CHW Role in Screening Process, Qualities of an Ideal CHW, Barriers to LCS, Challenges to Implementing a CHW Program, and Adaptations to CHW Program. DISCUSSION: The adapted CHW intervention should include culturally tailored health education to increase LCS knowledge for patients and providers.

Recently, advances in neural network approaches have achieved many successes in both sentiment classification and probabilistic topic modelling. On the one hand, latent topics derived from the global context of documents could be helpful in capturing more accurate word semantics and hence could potentially improve the sentiment classification accuracy. On the other hand, the word-level attention vectors obtained during the learning of sentiment classifiers could carry word-level polarity information and can be used to guide the discovery of topics in topic modelling. This paper proposes a multi-task learning framework which jointly learns a sentiment classifier and a topic model by making the word-level latent topic distributions in the topic model to be similar to the word-level attention vectors in the classifier through mutual learning. Experimental results on the Yelp and IMDB datasets verify the superior performance of the proposed framework over strong baselines on both sentiment classification accuracy and topic modelling evaluation results including perplexity and topic coherence measures. The proposed framework also extracts more interpretable topics compared to other conventional topic models and neural topic models.

Background: Young people in the United States know little about contraceptive options available to them, although method use is sensitive to individual preferences, and method switching is common. For young people to gain reproductive autonomy, a first step is to be aware of different contraceptives, including hormonal and nonhormonal methods. We tested whether an educational intervention delivered on community college campuses was effective in increasing contraceptive awareness. Materials and Methods: We developed a low-cost educational intervention featuring youth-friendly visual tools and tested its impact on method awareness and knowledge among 1,051 students of all genders, aged 18-25 years, at five community colleges. We used generalized estimating equations to test changes in awareness of a range of methods, including male and female (internal) condoms, the pill, patch, vaginal ring, shot, intrauterine devices, implant, and emergency contraception. Results: Over 90% of participants were aware of male condoms and the pill at baseline, but fewer had heard of other options (ranging from 31% to 76% for different methods). Across all methods, awareness increased to a mean of 88% among female participants and 82% among male participants postintervention. Awareness of the full range of methods increased from 31% to 55% (adjusted odds ratio [aOR]: 4.4, 95% confidence interval [CI]: 3.1-6.2]) among female participants and 11% to 36% (aOR: 10.8, 95% CI: 5.3-21.8) among male participants postintervention. The intervention was similarly effective by sexual orientation, race/ethnicity, nativity, or insurance coverage. Conclusion: This educational intervention significantly improved all students' awareness of a range of contraceptives, supporting one important aspect of reproductive health for young people in community settings.

BACKGROUND: Non-invasive fractional flow reserve (FFR) has been increasingly used in the clinical workflow to assist clinical decision-making for percutaneous coronary intervention (PCI). This clinical study evaluates the diagnostic accuracy of coronary stenosis assessed by a non-invasive FFR analysis method (termed AccuFFRangio) based on invasive coronary angiography (ICA). It is a blinded, self-controlled, retrospective, and dual-center clinical investigation study. METHODS: Coronary angiography data and the related information of 320 patients with 320 vessels were collected, and AccuFFRangio was used to assess the FFR for these patients. Compared with the wire-measured FFR values, we evaluated AccuFFRangio performance by its accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: The diagnostic accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRangio in identifying hemodynamically significant coronary stenosis were 93.3%, 92.6%, 93.5%, 84.3%, and 97.1%, respectively. The direct correlation between computed AccuFFRangio and measured FFR was 0.812 (P

Background Physician visual assessment (PVA) in invasive coronary angiography (ICA) is the current clinical method to determine stenosis severity and guide percutaneous coronary intervention. This study sought to evaluate the effect of sex differences in assessing coronary stenosis severity between PVA and quantitative coronary angiography (QCA). Methods 209 patients with coronary artery disease (288 coronary lesions) underwent ICA and fractional flow reserve (FFR). ICA image processing including PVA and QCA was used to quantify diameter stenosis (DS). The difference of DS (ΔDS) between PVA and QCA was defined as DSPVA-DSQCA. DS ≥50% was considered anatomically obstructive. FFR ≤0.8 was defined as myocardial ischemia. Results Mean ± SD age was 63 ± 9 years. There were no significant differences in DSPVA (61.1 ± 16.3% vs 60.1 ± 18.9%) and DSQCA (53.1 ± 12.1% vs 55.4 ± 14.3%) between females and males. However, ΔDS between PVA and QCA was higher in females (8.0 ± 10.9%) than in males (4.7 ± 10.9%) (P = 0.03). Thirty-four of 72 vessels (47.2%) in female patients and 75 of 216 vessels (34.7%) in male patients were classified differently by at least one grade using PVA compared to QCA assessment. DSPVA and DSQCA were negatively correlated with FFR in females (rPVA = −0.397, rQCA = −0.448) with an even stronger negative correlation in males (rPVA = −0.607, rQCA = −0.607). ROC analysis demonstrated that DSQCA myocardial ischemia (FFR ≤ 0.80) discrimination capability was superior to DSPVA in both sexes (P Conclusions A systematic bias was found in PVA (QCA reference) for overestimating severity of coronary artery disease in females compared to males.

Pregnant women represent a high-risk population for severe/critical COVID-19 and mortality. However, the maternal-fetal immune responses initiated by SARS-CoV-2 infection, and whether this virus is detectable in the placenta, are still under investigation. Here we show that SARS-CoV-2 infection during pregnancy primarily induces unique inflammatory responses at the maternal-fetal interface, which are largely governed by maternal T cells and fetal stromal cells. SARS-CoV-2 infection during pregnancy is also associated with humoral and cellular immune responses in the maternal blood, as well as with a mild cytokine response in the neonatal circulation (i.e., umbilical cord blood), without compromising the T-cell repertoire or initiating IgM responses. Importantly, SARS-CoV-2 is not detected in the placental tissues, nor is the sterility of the placenta compromised by maternal viral infection. This study provides insight into the maternal-fetal immune responses triggered by SARS-CoV-2 and emphasizes the rarity of placental infection., As pregnant women are considered vulnerable to SARSCoV-2 infection, it is important to investigate the actual risks involved. The authors show here that, while a T cell-dominant inflammatory response is observed at the maternal-foetal interface, the virus remains undetectable in the placenta but triggers specific immune responses in the neonatal (umbilical cord blood) circulation.

Retinal angiogenesis is a critical process for normal retinal function. However, uncontrolled angiogenesis can lead to pathological neovascularization (NV), which is closely related to most irreversible blindness-causing retinal diseases. Understanding the molecular basis behind pathological NV is important for the treatment of related diseases. Twist-related protein 1 (TWIST1) is a well-known transcription factor and principal inducer of epithelial-mesenchymal transition (EMT) in many human cancers. Our previous study showed that Twist1 expression is elevated in pathological retinal NV. To date, however, the role of TWIST1 in retinal pathological angiogenesis remains to be elucidated. To study the role of TWIST1 in pathological retinal NV and identify specific molecular targets for antagonizing pathological NV, we generated an inducible vascular endothelial cell (EC)-specific Twist1 transgenic mouse model (Tg-Twist1iEC+). Whole-mount retinas from Tg-Twist1iEC+ mice showed retarded vascular progression and increased vascular density in the front end of the growing retinal vasculature, as well as aneurysm-like pathological retinal NV. Furthermore, overexpression of Twist1 in the ECs promoted cell proliferation but disturbed cell polarity, thus leading to uncontrolled retinal angiogenesis. TWIST1 promoted pathological NV by activating the Wnt/β-catenin signaling pathway and inducing the expression of NV formation-related genes, thereby acting as a ‘valve’ in the regulation of pathological angiogenesis. This study identified the critical role of TWIST1 in retinal pathological NV, thus providing a potential therapeutic target for pathological NV.

Background A near-fall is defined as a loss of balance that would result in a fall if sufficient balance recovery manoeuvres are not executed. Compared to falls, near-falls and its associated balance recovery manoeuvres have been understudied. Older adults may not recognise a near-fall or identify the use of their balance recovery manoeuvres to prevent a fall. The consensus on the methods to collect near-fall data is lacking. The primary objective of this study was to determine the feasibility of recruitment and retention. Secondary objectives were to establish evidence that Singapore community-dwelling older adults can identify near-falls and associated balance recovery manoeuvres. Texting and calling methods were explored as reporting methods. Methods This study took place in Singapore (September to October 2019). Participants were healthy, community-dwelling adults aged 65 or older. Recruitment was done through poster advertisement, and all participants gave informed consent. Participants attended a briefing session and reported their near-fall or fall incidence over 21 days using either daily texting or calling. The primary outcome measures were the recruitment rate, retention rate, preferred modes for data reporting and ability to report near-falls or falls. Secondary outcomes included the self-reported incidence of falls and near-falls. Results Thirty older adults were recruited in 5 weeks. All participants completed the study. They understood near-fall concepts and were able to report the occurrence and relevant balance recovery manoeuvres used to prevent a fall. 87% (26/30) chose to text while 13% (4/30) selected calling as their reporting method. One actual fall (0.16%) out of 630 responses was reported. Thirty-six incidents (5.7%) of near-falls were recorded. Sixteen participants (53.3%) experienced near-falls and half of this group experienced two or more near-falls. The use of reach-to-grasp strategy (36%), compensatory stepping (52.8%), and other body regions (11.2%) were used to prevent the fall. Conclusions The study provided evidence that studying near-falls in Singapore community-dwelling older adults is feasible and can be applied to a large-scale study. Recruitment and retention rates were good. Older adults were able to identify near-falls and balance recovery manoeuvres. Both texting and calling were feasible reporting methods, but texting was preferred. Trial registration ClinicalTrials identifier: NCT04087551. Registered on September 12, 2019

Background Falls efficacy is a widely-studied latent construct in community-dwelling older adults. Various self-reported instruments have been used to measure falls efficacy. In order to be informed of the choice of the best measurement instrument for a specific purpose, empirical evidence of the development and measurement properties of falls efficacy related instruments is needed. Methods The Consensus-based Standards for the Selection of Health Measurement Intruments (COSMIN) checklist was used to summarise evidence on the development, content validity, and structural validity of instruments measuring falls efficacy in community-dwelling older adults. Databases including MEDLINE, Web of Science, PsychINFO, SCOPUS, CINAHL were searched (May 2019). Records on the development of instruments and studies assessing content validity or structural validity of falls efficacy related scales were included. COSMIN methodology was used to guide the review of eligible studies and in the assessment of their methodological quality. Evidence of content validity: relevance, comprehensiveness and comprehensibility and unidimensionality for structural validity were synthesised. A modified GRADE approach was applied to evidence synthesis. Results Thirty-five studies, of which 18 instruments had been identified, were included in the review. High-quality evidence showed that the Modified Falls Efficacy Scale (FES)-13 items (MFES-13) has sufficient relevance, yet insufficient comprehensiveness for measuring falls efficacy. Moderate quality evidence supported that the FES-10 has sufficient relevance, and MFES-14 has sufficient comprehensibility. Activities-specific Balance Confidence (ABC) Scale–Simplified (ABC-15) has sufficient relevance in measuring balance confidence supported by moderate-quality evidence. Low to very low-quality evidence underpinned the content validity of other instruments. High-quality evidence supported sufficient unidimensionality for eight instruments (FES-10, MFES-14, ABC-6, ABC-15, ABC-16, Iconographical FES (Icon-FES), FES–International (FES-I) and Perceived Ability to Prevent and Manage Fall Risks (PAPMFR)). Conclusion Content validity of instruments to measure falls efficacy is understudied. Structural validity is sufficient for a number of widely-used instruments. Measuring balance confidence is a subset of falls efficacy. Further work is needed to investigate a broader construct for falls efficacy.

Background Anxiety is associated with poor health outcomes among chronic kidney disease (CKD) patients. This review summarizes the prevalence and risk factors associated with elevated anxiety symptoms and disorders among CKD patients. Methods Articles evaluating the prevalence and risk factors associated with elevated anxiety symptoms and disorders among CKD patients, as diagnosed via DSM 4th or 5th edition criteria, clinical interviews or validated questionnaires, were searched in Medline®, Embase®, PsychINFO® and CINAHL®. Using random-effects meta-analyses, the prevalence of elevated anxiety symptoms and disorders were estimated. A narrative review on the risk factors associated with elevated anxiety symptoms and disorders was presented. Results From 4941 articles, 61 studies were included. The pooled prevalence of anxiety disorders (9 studies, n = 1071) among CKD patients across studies was 19% while that of elevated anxiety symptoms (52 studies, n = 10,739) was 43%. Across continents, prevalence of elevated anxiety symptoms was highest in Europe and Asia. Between pre-dialysis and dialysis patients, the prevalence of elevated anxiety symptoms was not statistically different at 31% and 42% respectively. Common risk factors associated with elevated anxiety symptoms included concomitant depression, lower parathyroid hormone levels, increased comorbidities, increased duration of hospitalization, reduced perceived quality of life, and decreased vitality levels. Conclusion Given the high prevalence of anxiety disorders and elevated anxiety symptoms, more studies are required to assess the role and outcomes of anxiety screening among CKD patients. This could facilitate early identification of at-risk patients and potentially improve their clinical outcomes.

BACKGROUND Penetrating neck injuries require prompt recognition, diagnosis and management of critical airways. This case demonstrates an emergent situation that a “medical negligence” was avoided with the aid of end-tidal carbon dioxide (ETCO2) waveform. CASE SUMMARY We report a case of malposition of the endotracheal tube into the right hemithoracic cavity for cervical knife trauma, resulting in pneumothorax. Tube placement was not confirmed during emergency airway management, and the patient was directly transferred to the emergency operation room. Assisted by ETCO2 and imaging examinations, the anesthetist timely noticed the absence of ETCO2 waveform and resolved this urgent situation before anesthesia induction. CONCLUSION This case emphasizes the necessity of ETCO2 waveform and/or X-ray confirmation of endotracheal intubation even in emergent situations.

A real-time, personalized consumption-based pricing scheme can induce electricity users to change their purchase behaviors, thus becoming an important issue in exploring the management mechanisms of electricity markets. To stabilize electricity prices, increase operators' revenues, and balance market demands, we consider the pricing scheme in a smart grid market where traditional and renewable energies are available for sales. Under the scheme, we develop a leader-follower game to characterize the strategic interactions between a demand side management center and residential users, and show that there exists a unique Stackelberg equilibrium. Our numerical analysis indicates that the real-time pricing scheme makes the electricity price difference between valley and peak times within 0.4 cents, thereby achieving the goal of mitigating peak loads and stabilizing electricity prices. We reveal that the renewable energy loads dominate traditional energy loads even when the price of renewable energy is higher than that of traditional energy. We also perform sensitivity analysis and find that an increase in a user's dissatisfaction with the electricity supply can raise electricity price for the user and two different electricity loads. Moreover, the demand side management center's revenue changes with a concave appearance.

Based on the current-mode switching cell (CMSC), an inductive power transfer (IPT) system with dual-output is proposed in this letter. In the proposed IPT system, two CMSCs are inversely connected in series at the Rx side. Two CMSCs operate in the positive half-cycle and in the negative half-cycle of the Rx coil current, respectively. The dual output voltages can be regulated independently. The circuit structure of the CMSC is quite simple and helps to make the Rx side more compact. The control scheme is based on Rx-side real-time regulation and thereby wireless communication links are not required. Additionally, zero voltage switching (ZVS) is ensured for all switches. In order to verify the theoretical analysis, an experimental prototype with 20V/3.3A and 5V/3A outputs is fabricated, and the maximum efficiency can reach 92.8%.

Background Antiviral therapy should reduce the recurrence of hepatitis B virus‐related hepatocellular carcinoma (HBV‐related HCC) after surgical resection. However, there is little research on whether various antiviral drugs have different prognostic effects in patients with HBV‐related HCC after curative liver resection. The present study compared the effects of nucleotide analog (NtA) and nucleoside analog (NsA) antiviral therapies after surgical resection on the prognosis of HBV‐related HCC. Methods A total of 1303 patients with HBV‐related HCC who received curative hepatectomy at five institutes between April 2014 and April 2019 were retrospectively enrolled and analyzed. Propensity matching analysis was used to compare the outcomes of HCC patients given NsA versus NtA therapy. Subgroup analysis of patients treated with entecavir (ETV) and tenofovir disoproxil fumarate (TDF) was also performed. Results Among 1303 patients, 759 (58.2%) patients developed recurrence, and 460 (35.3%) patients died. Multivariable analyses revealed that NtA therapy significantly decreased the risk of HCC recurrence (hazard ratio [HR], 0.64; 95% confidence interval [CI], 0.51–0.80; p, The aim of this study was to investigate the effect of antiviral drug on the prognosis of hepatitis B virus‐related hepatocellular carcinoma (HCC) after curative hepatectomy. We found that nucleotide analog treatment, rather than nucleoside analog treatment, significantly reduced HCC recurrence and improved overall survival after curative hepatic resection.

In this paper, a densely connected graph convolutional network is proposed to jointly realize the semantic and instance segmentation of indoor point clouds. We combine a Graph Convolutional Network (GCN) and Multilayer Perceptron (MLP) into a new model (namely GCN-MLP) and design a more efficient attention pooling operation to establish a new and efficient module for extracting point cloud features. Also, we add a point cloud channel aggregation module to aggregate multi-level deep features to better express the discriminative characteristics of indoor point clouds. Next, a framework for joint semantic and instance segmentation is designed on the basis of the above modules. In the framework, the semantic branch and instance branch promote each other and obtain better semantic and instance segmentation effects simultaneously. Besides, a dense connection way among different levels of feature maps is designed, to fully extract the features of indoor scene. We have conducted the experiments on the public datasets (S3DIS and ShapeNet), and the results show that our framework is superior to other methods and also achieve better results in part segmentation. Compared with JSNet (Zhao and Tao, 2020), our method improves the indicators of mCov, mWCov, mRec, and mPrec by 3.3, 3.5, 4.6, and 1.8, respectively, in the instance segmentation of S3DIS (Area 5). Besides, we obtain the best results in 10 of the 13 classes in terms of IoU. For part segmentation of indoor objects, we also outperform ASIS (Wang et al., 2019b) by 0.4 on mIoU.

Purpose Conventional model observers (MO) in CT are often limited to a uniform background or varying background that is random and can be modelled in an analytical form. It is unclear if these conventional MOs can be readily generalized to predict human observer performance in clinical CT tasks that involve realistic anatomical background. Deep-learning-based model observers (DL-MO) have recently been developed, but have not been validated for challenging low contrast diagnostic tasks in abdominal CT. We consequently sought to validate a DL-MO for a low-contrast hepatic metastases localization task. Methods We adapted our recently-developed DL-MO framework for the liver metastases localization task. Our previously-validated projection-domain lesion- / noise-insertion techniques were used to synthesize realistic positive and low-dose abdominal CT exams, using the archived patient projection data. Ten experimental conditions were generated, which involved different lesion sizes / contrasts, radiation dose levels, and image reconstruction types. Each condition included 100 trials generated from a patient cohort of 7 cases. Each trial was presented as liver image patches (160×160×5 voxels). The DL-MO performance was calculated for each condition and was compared with human observer performance, which was obtained by 3 sub-specialized radiologists in an observer study. The performance of DL-MO and radiologists was gauged by the area under localization receiver-operating-characteristic curves. The generalization performance of the DL-MO was estimated with the repeated 2-fold cross-validation method over the same set of trials used in human observer study. A multi-slice Channelized Hoteling Observers (CHO) was compared with the DL-MO across the same experimental conditions. Results The performance of DL-MO was highly correlated to that of radiologists (Pearson's correlation coefficient: 0.987; 95% C.I.: 0.942, 0.997). The performance level of DL-MO was comparable to that of the grouped radiologists, i.e. the mean performance difference was -3.3%. The CHO performance was poorer than the grouped radiologist performance, before internal noise could be added. The correlation between CHO and radiologists was weaker (Pearson's correlation coefficient: 0.812, and 95% C.I.: [0.378, 0.955]), and the corresponding performance bias (-29.5%) was statistically significant. Conclusion The presented study demonstrated the potential of using the DL-MO for image quality assessment in patient abdominal CT tasks. This article is protected by copyright. All rights reserved.

Current artificial magnetic conductor (AMC) designs use metallic patterns on rigid substrates and focus on shapes and sizes of AMC structures, rather than on material performance, which has hindered operation bandwidth and design flexibility. Here, we introduce printed graphene AMC-based broadband and flexible microwave radar absorbers, which not only redirect but also absorb the incident wave so to broaden the operation bandwidth. Contrasting to other reported works, the phase characteristics of the AMCs are realized through the control of the surface resistance provided by printed graphene laminates. We produced a variety of AMC structures, composed of printed graphene circular ring arrays with exactly the same shape and size, but different sheet resistances. By carefully designing the sheet resistance of printed graphene laminates, the optimized anti-phase reflection cancellation between AMCs can be achieved. With printed graphene AMCs and flexible dielectric substrate, the absorber presented in this work has a broadband effective absorption (above 90% absorptivity) from 7.58 GHz to 18 GHz, is polarization insensitive under normal incident and can work at relatively wide incident angles. Furthermore, this absorber is capable of bending easily with notable performance, which makes it ideal for applications with irregular and uneven shapes.

Conventional di/dt and dv / dt control and gate protection techniques for gallium nitride (GaN) power transistors usually employ external controllers, isolation circuits, discrete pull-up, and pull-down resistors. With large number of components, power modules become more complex and may introduce additional parasitic. Gate driver ICs with segmented output stages and dynamic gate driving have been reported previously to be effective in simultaneously suppressing gate ringing and overshoot voltage while maintaining fast switching speed. However, the programming for dynamic gate driving is rather complicated, requiring the user to load a sequence of driving patterns obtained from trial and error ahead of time. This article presents a gate driver IC for E-mode GaN power transistors with seven segmented output stages. More importantly, it offers a simplified programming method for the dynamic gate driving pattern. The optimal gate drive pattern can be defined by simply adjusting one external bias resistor. The proposed method eliminates the complex trial and error digital control, and can potentially promoting the wider acceptance of dynamic gate driving by the industry. The timing resolution for the gate drive pattern can be varied in steps from 0.5 to 5 ns. It can also be used to drive many commercially available GaN power transistors.

Objectives There is a lack of clinical research in the Chinese market concerning dissolving microarray (DMA) patches in cosmetic applications. In this study, the clinical efficacy and safety tests of DMA patch technology were performed on Chinese consumers. Methods A 4-week clinical efficacy and safety evaluation was conducted on 30 Chinese female subjects with crow's feet and eye bags. DMA patches loaded with hyaluronic acid (HA-DMA) were applied under the eyes and corners of the eyes of the subjects three times a week over four consecutive weeks. Skin firmness and dermal layer strength were measured using ultrasound, and changes in skin wrinkles were detected using VISIA-CR and Primos Lite. Eye bag ratings were evaluated by professional dermatologists based on the 0-6 grades of eye bags in the "Skin Aging Atlas Volume 2: Asian Type." Results HA-DMA patches produced good clinical improvements on both crow's feet and eye bags in the study participants. HA-DMA effectively increased skin firmness while reducing the number, area, and volume of crow's feet, along with reducing eye bag ratings. The reductions in all metrics were statistically significant with positive effects evident in as little as 1 week of treatment. There were no adverse effects related to the treatments observed during the test period. Conclusions In a clinical efficacy trial of 30 Chinese female subjects, HA-DMA showed excellent therapeutic benefits without adverse effects while reducing crow's feet and eye bags. HA-DMA is expected to be a safe, effective, and novel cosmetic for improving the appearance of aging skin.

Water inrush disasters are extremely prone to occur if the coal seam floor contains a confined aquifer. To find out the failure behavior of coal seam floor of paste filling working face, a beam-based theoretical model for the floor aquifuge was built, and then, the water inrush risk was evaluated based on the thickness of floor aquifuge. Next, the floor failure characteristics of the paste filling face was numerically studied and the effects of the filling interval and long-term strength of the filling body on the floor failure depth, stress and displacement distributions, and plastic zone were explored. The results showed that the theoretical model for evaluating the safety of the floor of the paste filling face based on the empty roof distance is proved to be consistent with that of the empirical formula judged based on the assumption that the paste filling working face was regarded as a cut hole with a certain width. The filling interval has a significant effect on the stress concentration of the surrounding rock, failure depth of floor, and roof-floor convergence. The smaller the filling interval is, the smaller their values are. When the filling rate is 98%, the long-term strength of the filling body is 5 MPa, and the floor failure depth is not more than 4 m. In contrast, the strength of the filling body has no obvious influence on the floor failure depth, but it has a certain impact on the roof-floor convergence. From the perspective of reducing floor failure depth, there is no need to increase the long-term strength of backfill, but it is necessary to increase the early strength of backfill so as to reduce the width of the equivalent roadway.

PURPOSE Oesophageal squamous cell carcinoma (ESCC) patients have severe symptom burden after oesophagectomy; however, longitudinal studies of symptom recovery after surgery are scarce. This study used longitudinal patient-reported outcome (PRO)-based symptoms to identify severe symptoms and profile symptom recovery from surgery in patients undergoing oesophagectomy. METHODS Oesophageal cancer patients (N = 327) underwent oesophagectomy were consecutively included between April 2019 and March 2020. Data were extracted from the Sichuan Cancer Hospital's Esophageal Cancer Case Management Registration Database. Symptom assessment time points were pre-surgery and 1, 3, 5, 7, 14, 21, 30, and 90 days post-surgery using the Chinese version of the MD Anderson Symptom Inventory. And each symptom was rated on an 11-point scale, with 0 being 'not present' and 10 being 'as bad as you can imagine'. The symptom recovery trajectories were profiled using mixed effect models and Kaplan-Meier analysis. RESULTS The most-severe symptoms on day 1 after oesophagectomy were pain, fatigue, dry mouth, disturbed sleep, and distress. The severity of symptoms peaked on day 1 after surgery. The top two symptoms were fatigue (mean: 5.44 [SD 1.88]) and pain (mean: 5.23 [SD 1.29]). Fatigue was more severe 90 days after surgery than at baseline (mean: 1.77 [SD 1.47] vs 0.65 [SD 1.05]; P

BACKGROUND: The prevalence of radicular defects after root canal instrumentation is unresolved. This study used micro-CT to assess the relationship between the formation of radicular defects and chemo-mechanical instrumentation in a cadaver model. METHODS: Maxillary and mandibular molars (n = 24) were sectioned from cadaver specimens as a tissue block containing the teeth, alveolar bone and attached mucogingival tissues. After a baseline micro-CT scan (13.45 μm), the specimens were distributed into 3 groups (n = 8 molars): Reciproc® , ProTaper Next™ and Mtwo® . Micro-CT scans of each specimen were obtained after access, glide path and preparation with each instrument. The pre-operative and final post-operative micro-CT cross-sectional images of the roots were screened by two blinded examiners to identify any pre-existing and new radicular defects. Pre-existing and new radicular defects were examined histologically. RESULTS: Overall, 16 pre-existing radicular defects were identified in 12 of the 24 molars (50%). Most of these were cemental tears (87.5%), and not true dentinal microcracks. New dentinal microcracks were observed in the post-operative micro-CT scans of only 3 canals (3.9%; 3/77). However, only one of these defects was found to be present histologically. CONCLUSIONS: Within the limitations of the study, chemo-mechanical instrumentation did not routinely promote the formation of radicular defects.

With the development of technology, more infants receive general anesthesia for surgery, other interventions, or clinical examination at an early stage after birth. However, whether general anesthetics can affect the function and structure of the developing infant brain remains an important, complex, and controversial issue. Sevoflurane is the most-used anesthetic in infants, but this drug is potentially neurotoxic. Short or single exposure to sevoflurane has a weak effect on cognitive function, while long or repeated exposure to general anesthetics may cause cognitive dysfunction. This review focuses on the mechanisms by which sevoflurane exposure during development may induce long-lasting undesirable effects on the brain. We review neural cell death, neural cell damage, impaired assembly and plasticity of neural circuits, tau phosphorylation, and neuroendocrine effects as important mechanisms for sevoflurane-induced developmental neurotoxicity. More advanced technologies and methods should be applied to determine the underlying mechanism(s) and guide prevention and treatment of sevoflurane-induced neurotoxicity. 1. We discuss the mechanisms underlying sevoflurane-induced developmental neurotoxicity from five perspectives: neural cell death, neural cell damage, assembly and plasticity of neural circuits, tau phosphorylation, and neuroendocrine effects. 2. Tau phosphorylation, IL-6, and mitochondrial dysfunction could interact with each other to cause a nerve damage loop. 3. miRNAs and lncRNAs are associated with sevoflurane-induced neurotoxicity.

Machine learning (ML) based pavement performance models have gained increasing popularity in recent years due to their strong power in modelling complex relationships. However, the insufficiency of...

Mobile edge computing (MEC) is emerging as a promising paradigm to support the applications of Internet of Things (IoT). The edge servers bring computing resources to the edge of the network, so as to meet the delay requirements of the IoT devices’ service requests. At the same time, the edge servers can gain profit by leasing computing resources to IoT users and realize the allocation of computing resources. How to determine a reasonable resource leasing price for the edge servers and how to determine the number of resource purchased by users with different needs is a challenging problem. In order to solve the problem, this paper proposes a game-based scheme for resource purchasing and pricing aiming at maximizing user utility and server profit. The interaction between users and the edge servers is modeled based on Stackelberg game theory. The properties of incentive compatibility and envy freeness are theoretically proved, and the existence of Stackelberg equilibrium is also proved. A game-based user resource purchasing algorithm called GURP and a game-based server resource pricing algorithm called GSRP are proposed. It is theoretically proven that solutions of the proposed algorithms satisfy the individual rationality property. Finally, simulation experiments are carried out, and the experimental results show that the GURP algorithm and the GSRP algorithm can quickly converge to the optimal solutions. Comparison experiments with the benchmark algorithms are also carried out, and the experimental results show that the GURP algorithm and the GSRP algorithm can maximize user utility and server profit.

Shale gas is an important unconventional natural gas resource, and its reservoirs have pores with strong heterogeneity, which have an important effect on the adsorption and migration of shale gas, but the specific mechanism is still unclear. To further clarify the pore structure characteristics of shale gas reservoirs and the mechanism of their influence on CH4 adsorption capacity, marine shale samples from the Wufeng–Longmaxi formation of wells N1, N3, and N10 in Changning block, southern Sichuan Basin, China, were selected for total organic carbon (TOC), X-ray diffraction (XRD), N2 gas adsorption (N2-GA), CH4 gas adsorption (CH4-GA), and field emission scanning electron microscopy (FE-SEM). The Frenkel–Halsey–Hill (FHH) model and Slit Island Analysis (SIA) were used to calculate the fractal dimension of the pore system and different types of pores, and their relationship and influence on CH4 adsorption capacity were also discussed. The results show that the fractal dimension could reflect the complexity and heterogeneity of pores. According to the FHH model, fractal dimensions of the surface and structure of the pore system (D1 and D2, D1 < D2) were obtained, and the pore structure was more complex than the pore surface. According to SIA, the surface fractal dimensions of four types of reservoir space (DDP, DOP, DIP, and DMF) decrease progressively, and their main body is 2.60–2.80, 2.40–2.65, 2.20–2.40, and 2.05–2.30. Organic pores and intergranular pores are the most abundant, and so D1 is mainly related to DOP and DIP. In high-TOC samples, D1 is close to DOP, while in low-TOC samples, D1 is close to DIP. The complexity of the pore surface, D1, and specific surface area have a positive correlation, and with the increase of pore surface complexity, methane adsorption capacity could be significantly improved. Therefore, D1 may be used as a characterization parameter of CH4 adsorption capacity, which could provide some evidence to further clarify the adsorption mechanism of shale gas.

OBJECTIVE To project the future age distribution of people with HIV using antiretroviral therapy (ART) in the US, under expected trends in HIV diagnosis and survival (baseline scenario) and achieving the Ending the HIV Epidemic (EHE) goals of a 75% reduction in HIV diagnoses from 2020-25 and sustaining levels to 2030 (EHE75% scenario). DESIGN An agent-based simulation model with mathematical functions estimated from North American AIDS Cohort Collaboration on Research and Design data and parameters from the US Centers for Disease Control and Prevention's annual HIV surveillance reports. METHODS The PEARL (ProjEcting Age, multimoRbidity, and poLypharmacy in adults with HIV) model simulated individuals in 15 subgroups of sex-and-HIV acquisition risk and race/ethnicity. Simulation outcomes from the baseline scenario are compared with outcomes from the EHE75% scenario. RESULTS Under the baseline scenario, PEARL projects a substantial increase in number of ART-users over time, reaching a population of 909,638 [95%uncertaintyrange(UR):878,449-946,513] by 2030. The overall median age increased from 50 years (y) in 2020 to 52y in 2030, with 23% of ART-users age ≥65y in 2030. Under the EHE75% scenario, the projected number of ART-users was 718,348 [703,044-737,817] (median age=56y) in 2030, with a 70% relative reduction in ART-users

Multi-parametric magnetic resonance imaging (mpMRI) has been playing an increasingly important role in the detection of prostate cancer (PCa). Various computer-aided detection algorithms were proposed for automated PCa detection by combining information in multiple mpMRI parameters. However, there are specific features of mpMRI, including between-voxel correlation within each prostate and heterogeneity across patients, that have not been fully explored but could potentially improve PCa detection if leveraged appropriately. This article proposes novel Bayesian approaches for voxel-wise PCa classification that accounts for spatial correlation and between-patient heterogeneity in the mpMRI data. Modeling the spatial correlation is challenging due to the extreme high dimensionality of the data, and we propose three scalable approaches based on Nearest Neighbor Gaussian Process (NNGP), reduced-rank approximation, and a conditional autoregressive (CAR) model that approximates a Gaussian Process with the Matern covariance, respectively. Our simulation study shows that properly modeling the spatial correlation and between-patient heterogeneity can substantially improve PCa classification. Application to in vivo data illustrates that classification is improved by all three spatial modeling approaches considered, while modeling the between-patient heterogeneity does not further improve our classifiers. Among the proposed models, the NNGP-based model is recommended given its high classification accuracy and computational efficiency.

Benxi Formation is an abundant natural gas reservoir in Gaoqiao area. Therefore, it is essential to analyze the sequence and sedimentary characteristics of the Benxi Formation to predict the distribution of favorable gas reservoirs . After the comprehensive use of the core, thin section, drilling, and logging data, the sequence framework, sedimentary microfacies, planar distribution and vertical microfacies associations of the Benxi formation were studied. The Benxi Formation in the Gaoqiao area is barrier coastal sedimentary system, which is divided into eight sedimentary microfacies, namely, tidal delta, tidal channel, sand flat, mixed flat, mud flat, peat flat, barrier bar, and lagoon mud microfacies. In addition, we concluded that i) From west to east, peat flat, mud flat, mixed flat, sand flat, lagoon mud, and barrier bar have been developed in the study area. ii) Four typical vertical sequences were identified: MA1, MA2, MA1, and MA4. The first three sequences developed extensively and completely in the study area, whereas the last one generally has one or more microfacies missing. iii) The sedimentary system of the Benxi Formation in the Gaoqiao area was primarily vulnerable to tectonism, sequence, and sea-level changes. The Second Member was the target gas-producing stratum of the Formation. Both barrier bar and sand flat microfacies exhibited an excellent gas display. However, the barrier bar microfacies were the most favorable natural gas distribution zones with giant and premium gas reserves.

The temperature-dependent (T-dependent) linewidth (ΓG) and frequency shift (ΔωG) of the G mode provide valuable information on the phonon anharmonicity of graphene-based materials. In contrast to the negligible contribution from electron-phonon coupling (EPC) to the linewidth of a Raman mode in semiconductors, ΓG in pristine graphene is dominated by EPC contribution at room temperature due to its semimetallic characteristics. This leads to difficulty in resolving intrinsic contribution from phonon anharmonicity to ΓG. Here, we probed the intrinsic phonon anharmonicity of heavily-doped graphene by T-dependent Raman spectra based on FeCl3-based stage-1 graphite intercalation compound (GIC), in which the EPC contribution is negligible due to the large Fermi level (EF) shift. The ΔωG and ΓG exhibit a nonlinear decrease and noticeable broadening with increasing temperature, respectively, which are both dominated by phonon anharmonicity processes. The contribution of phonon anharmonicity to ΓG of heavily-doped graphene decreases as the EF approaches to the Dirac point. However, the T dependence of ΔωG is almost independent on EF and qualitatively agrees with the theoretical result of pristine graphene. These results provide a deeper understanding of the role of phonon anharmonicity on the Raman spectra of heavily doped graphene.

The population is rapidly aging worldwide, and there is an age-related decline in muscle mass. Therefore, it is important to examine the prevalence and associated factors of low appendicular skeletal muscle mass index (ASMI) in older adults. The objectives of this cross-sectional study were (i) to determine the prevalence of low ASMI (ASM/height2) and (ii) to identify factors associated with low ASMI. This study included 1211 community-dwelling adults aged ≥ 65 years. Low ASMI was defined as 2 in males and 2 in females (bioelectrical impedance analysis). Gender-specific cut-off values of calf circumference for low ASMI were determined. The prevalence of low ASMI in the overall cohort was 59.9%, i.e., 57.0% among males and 61.8% among females, with no significant difference between genders (P = 0.1068). The prevalence of low ASMI was 81.3% in individuals at risk of malnutrition compared to 20.6% in their counterparts with normal nutritional status (P P P ≤ 0.0328). Cut-off values of calf circumference for low ASMI for males was 33.4 cm and for females was 32.2 cm. In conclusion, we found that low ASMI was highly prevalent among community-dwelling older adults at risk of malnutrition. Other significant factors associated with low ASMI were age, smoking, drinking, calf circumference, and bone mass. Screening community-dwelling older adults for risk of malnutrition can prevent or delay onset of low ASMI.

We present a benchmark comparison of several deep learning models including Convolutional Neural Networks, Recurrent Neural Network and Bi-directional Long Short Term Memory, assessed based on various word embedding approaches, including the Bi-directional Encoder Representations from Transformers (BERT) and its variants, FastText and Word2Vec. Data augmentation was administered using the Easy Data Augmentation approach resulting in two datasets (original versus augmented). All the models were assessed in two setups, namely 5-class versus 3-class (i.e., compressed version). Findings show the best prediction models were Neural Network-based using Word2Vec, with CNN-RNN-Bi-LSTM producing the highest accuracy (96%) and F-score (91.1%). Individually, RNN was the best model with an accuracy of 87.5% and F-score of 83.5%, while RoBERTa had the best F-score of 73.1%. The study shows that deep learning is better for analyzing the sentiments within the text compared to supervised machine learning and provides a direction for future work and research.

Weiling Leng,1 Danlan Pu,2 Juan Jiang,2 Xiaotian Lei,1 Qinan Wu,3,&ast; Bing Chen1,&ast; 1Endocrinology Department, The First Affiliated Hospital of the Third Military Medical University (Army Medical University), Chongqing, People’s Republic of China; 2Endocrinology and Nephrology Department, Chongqing University Cancer Hospital and Chongqing Cancer Institute and Chongqing Cancer Hospital, Chongqing, People’s Republic of China; 3Endocrinology Department, Chongqing Medical University Affiliated Dazu Hospital, Dazu District People’s Hospital, Chongqing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Qinan Wu; Bing Chen Email wqn11@126.com; chenbingxnyy@126.comBackground: This study investigated the effects of metformin on breast density in overweight/obese premenopausal women.Methods: Overweight/obese premenopausal women (n=120) were randomly assigned to the metformin or placebo group, and all women received lifestyle interventions. The outcomes included weight, BMI, FPG, FIN, glucose, HOMA-IR, LDL-C, HDL-C, TG, TC, SBP, DBP, FSH, E, AD, and the BIRADS grade, and the incidence of breast cancer was assessed by pathological biopsy and BIRADS grade greater than 4.Results: In total, 120 overweight/obese women completed the 1-year trial. Seven patients had a BIRADS grade greater than 4, including 5 patients who were biopsy positive, in the control group, and 2 patients had a BIRADS grade greater than 4, including 1 patient who was biopsy positive, in the metformin group. Compared with those in the control group, the body weight, BMI, FIN, FPG, HOMA-IR, TC, BIRADS grade and positive pathological biopsy rate in the metformin group were significantly decreased (P< 0.05), while AD was significantly increased (P< 0.05). The correlation analysis indicated that the BIRADS grade was significantly correlated with weight, BMI, FPG, FIN, HOMA-IR, SBP, AD and the positive pathological biopsy rate, and the positive pathological biopsy rate was significantly correlated with weight, BMI, HOMA-IR, SBP, AD and BIRADS grade. The logistic regression analysis revealed that the BIRADS grade was significantly correlated with the positive pathological biopsy rate and AD and that the positive pathological biopsy rate was significantly correlated with the BIRADS grade.Conclusion: As adjunctive therapy, the combination of lifestyle changes and metformin was found to be a safe strategy for improving related metabolic markers and increasing adiponectin. The BIRADS grade was significantly correlated with the positive pathological biopsy rate and AD, and the positive pathological biopsy rate was significantly correlated with the BIRADS grade.Keywords: metformin, breast density, overweight/obese, adiponectin

Motivation Differential network inference is a fundamental and challenging problem to reveal gene interactions and regulation relationships under different conditions. Many algorithms have been developed for this problem; however, they do not consider the differences between the importance of genes, which may not fit the real-world situation. Different genes have different mutation probabilities, and the vital genes associated with basic life activities have less fault tolerance to mutation. Equally treating all genes may bias the results of differential network inference. Thus, it is necessary to consider the importance of genes in the models of differential network inference. Results Based on the Gaussian graphical model with adaptive gene importance regularization, we develop a novel Importance-Penalized Joint Graphical Lasso method (IPJGL) for differential network inference. The presented method is validated by the simulation experiments as well as the real datasets. Furthermore, to precisely evaluate the results of differential network inference, we propose a new metric named APC2 for the differential levels of gene pairs. We apply IPJGL to analyze the TCGA colorectal and breast cancer datasets and find some candidate cancer genes with significant survival analysis results, including SOST for colorectal cancer and RBBP8 for breast cancer. We also conduct further analysis based on the interactions in the Reactome database and confirm the utility of our method. Availability and implementation R source code of Importance-Penalized Joint Graphical Lasso is freely available at https://github.com/Wu-Lab/IPJGL. Supplementary information Supplementary data are available at Bioinformatics online.

Background To develop and validate a risk prediction nomogram based on a deep learning convolutional neural networks (CNN) model and epidemiological characteristics for lung cancer screening in patients with small pulmonary nodules (SPN). Methods This study included three data sets. First, a CNN model was developed and tested on data set 1. Then, a hybrid prediction model was developed on data set 2 by multivariable binary logistic regression analysis. We combined the CNN model score and the selected epidemiological risk factors, and a risk prediction nomogram was presented. An independent multicenter cohort was used for model external validation. The performance of the nomogram was assessed with respect to its calibration and discrimination. Results The final hybrid model included the CNN model score and the screened risk factors included age, gender, smoking status and family history of cancer. The nomogram showed good discrimination and calibration with an area under the curve (AUC) of 91.6% (95% CI: 89.4%–93.5%), compare with the CNN model, the improvement was significance. The performance of the nomogram still showed good discrimination and good calibration in the multicenter validation cohort, with an AUC of 88.3% (95% CI: 83.1%–92.3%). Conclusions Our study showed that epidemiological characteristics should be considered in lung cancer screening, which can significantly improve the efficiency of the artificial intelligence (AI) model alone. We combined the CNN model score with Asian lung cancer epidemiological characteristics to develop a new nomogram to facilitate and accurately perform individualized lung cancer screening, especially for Asians., A novel AI model was developed for LDCT detection specifically. Our study showed that epidemiological characteristics should be considered in lung cancer screening, which can significantly improve the efficiency of AI model alone. We combined the CNN model score with Asian lung cancer epidemiological characteristics to develop a new Nomogram to facilitate and accurately perform individualized lung cancer screening, especially for Asians.

Research on the sixth-generation cellular networks (6G) is gaining huge momentum to achieve ubiquitous wireless connectivity. Connected autonomous vehicles (CAVs) is a critical vertical application for 6G, holding great potentials of improving road safety, road and energy efficiency. However, the stringent service requirements of CAV applications on reliability, latency, and high speed communications will present big challenges to 6G networks. New channel access algorithms and intelligent control schemes for connected vehicles are needed for 6G-supported CAV. In this article, we investigated 6G-supported cooperative driving, which is an advanced driving mode through information sharing and driving coordination. First, we quantify the delay upper bounds of 6G vehicle-to-vehicle (V2V) communications with hybrid communication and channel access technologies. A deep learning neural network is developed and trained for the fast computation of the delay bounds in real-time operations. Then, an intelligent strategy is designed to control the intervehicle distance for cooperative autonomous driving. Furthermore, we propose a Markov chain-based algorithm to predict the parameters of the system states, and also a safe distance mapping method to enable smooth vehicular speed changes. The proposed algorithms are implemented in the AirSim autonomous driving platform. Simulation results show that the proposed algorithms are effective and robust with safe and stable cooperative autonomous driving, which greatly improve the road safety, capacity, and efficiency.

The hemodynamic changes of acute small subcortical infarction (SSI) are not well understood. We evaluate the hemodynamic changes and collaterals in acute SSI using perfusion magnetic resonance imaging (MRI). A total of 103 patients with acute SSI in penetrating artery territories were recruited and underwent MRI within 24 h of stroke onset. Using 4D dynamic perfusion MRI, they were divided into three patterns: 25 (24%) with normal perfusion, 31 (30%) with compensated perfusion, and 47 (46%) with hypoperfusion. The development of anterograde or retrograde collaterals was also evaluated. Patients with hypoperfusion pattern had the highest rate of early neurological deterioration (32%, p = 0.007), the largest initial and final infarction volumes (p p = 0.029), the lowest relative cerebral blood flow (0.63, p p p = 0.002). The anterograde collaterals were associated with higher relative cerebral blood volume (0.91 vs. 0.77; p = 0.024) and a higher rate of deep cerebral microbleeds (48 vs. 21%; p = 0.028), whereas retrograde collaterals were associated with higher systolic and diastolic blood pressure (p = 0.031 and 0.020), smaller initial infarction volume (0.81 vs. 1.34 ml, p = 0.031), and a higher rate of lobar cerebral microbleeds (30 vs. 0%; p = 0.013). Both anterograde and retrograde collaterals may play a critical role in maintaining cerebral perfusion and can have an impact on patient clinical outcomes. Further studies are warranted to verify these findings and to investigate effective treatments.

BACKGROUND Endothelial progenitor cells have shown the ability to enhance neovascularization. In this study, the authors tested whether intraosseous delivery of simvastatin could mobilize endothelial progenitor cells and enhance recovery in a hindlimb ischemia model. METHODS There are eight groups of rats in this study: normal control; type 1 diabetes mellitus control group control without drug intervention; and type 1 diabetes mellitus rats that randomly received intraosseous simvastatin (0, 0.5, or 1 mg) or oral simvastatin administration (0, 20, or 400 mg). All type 1 diabetes mellitus rats had induced hindlimb ischemia. The number of endothelial progenitor cells in peripheral blood, and serum markers, were detected. The recovery of blood flow at 21 days after treatment was used as the main outcome. RESULTS The authors demonstrated that endothelial progenitor cell mobilization was increased in the simvastatin 0.5- and 1-mg groups compared with the type 1 diabetes mellitus control and simvastatin 0-mg groups at 1, 2, and 3 weeks. Serum vascular endothelial growth factor levels were significantly increased at 2 weeks in the simvastatin 0.5- and 1-mg groups, in addition to the increase of the blood flow and the gastrocnemius weight at 3 weeks. Similar increase can also been seen in simvastatin 400 mg orally but not in simvastatin 20 mg orally. CONCLUSION These findings demonstrate that a single intraosseous administration of simvastatin mobilized endothelial progenitor cells at a dose one-hundredth of the required daily oral dose in rats, and this potent mobilization of endothelial progenitor cells markedly improved diabetic limb ischemia by means of neovascularization.

To explore the role of adiponectin-resistin (AR) index as a better indicator of obesity-related hypertension.This study continued a case control study that had finished recruiting 153 subjects divided as four characteristic groups. Fasting serum resistin levels (FSR) and Fasting serum adiponectin levels (FSA) were tested by ELISA. And, other related anthropometric clinical and metabolic data were collected. Analyzation on correlations between research index and differences between groups were done by SPSS. AR index's performance was also validated by the receiver operating characteristic (ROC) curves, the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI).The AR index was defined as 1+ logThe AR index was more strongly associated with increased risk of obesity-related hypertension than the solely index of FSR or FSA and was useful for early diagnosis of obesity-related hypertension.

Introduction: Sleep deprivation impacts clinical performance. However, literature is conflicting, with insufficient focus on patient outcomes. The aim of this study was to assess if patient satisfaction and prescription errors in outpatient clinics were adversely affected when consulting post-call versus non-post-call registrars. Methods: This prospective, quantitative study was set in a large teaching hospital in Singapore. Between November 2015 and February 2016, patients from clinics run by a registrar after 24-hour shift were recruited to post-call group. Patients from non-post-call clinics run by the same registrar were controls. Outcome measures were patient satisfaction, using 5-item 4-point Likert scale questionnaire, and prescribing error rate, defined as number of errors over number of orders. Differences were analysed using chi-squared test. Results: 103 of 106 (97%) patients in 9 post-call clinics and 93 of 105 (90%) patients in 9 non-post-call clinics were recruited. Questionnaire completion rate was 99%. 536 and 526 prescriptions were ordered in post-call and non-post-call groups, respectively. Percentage of top-box responses (greatest satisfaction) was higher in post-call group overall (79.3% versus 62.4%, p

Significant advances have been made in designing CNNs for RGB semantic segmentation. However, these CNNs are not widely adopted for RGB-D segmentation, due to the asymmetry between the RGB and depth modalities. Instead, dedicated architectures are designed to fuse them for effective RGB-D segmentation, wherein complex structures are often employed, resulting in much increased computational cost. In this paper, we propose a novel way to learn the fusion of RGB and depth information in an early stage. This enables our method to easily adopt existing RGB segmentation networks with minimal modification. Our method is simple yet effective to build a bridge between RGB and RGBD semantic segmentation, so as to avoid designing a far more complex network structure for RGBD segmentation. The proposed method treats RGB and depth information in an inherently asymmetric manner, and to the best of our knowledge, this is the first approach that learns to fuse them in a multiplicative manner for RGB-D segmentation; thus, we call it RGB × D. Extensive experiments and ablation studies on the challenging NYUDv2, SUN RGB-D and Cityscapes semantic segmentation benchmarks show that the proposed RGB × D offers a consistent improvement over several baselines.