Search

Abstract PANoptosis is engaged in the program of immune response and carcinogenicity. Nonetheless, the actual impacts of PANoptosis on clinical management and oncology immunity in hepatocellular carcinoma (HCC) are not fully grasped. RNA-seq-derived computations were conducted to sort out the molecular subtypes and elucidate the disparities based on PANoptosis molecules. Single-cell sequencing (scRNA-seq) tools including Cytotrace and Addmodulescore were extracted to characterize diversification potency and quantify the PANoptosis motion. Transcriptional factors were inferred by the pySCENIC package and Cellchat program scrutinized the intercellular exchange across cell compartments. The PANoptosis score system originated by incorporating 10 machine learning algorithms and 101 compositions to project clinical results and deteriorate tendencies. Circulatory PANoptosis-associated protein HSP90AA1 was determined by enzyme-linked immunosorbent assay (ELISA). HCC individuals could be categorized into low- and high-PANoptosis groups with diverse biogenic and pharmacotherapy heterogeneity. Individuals in the elevated PANoptosis subtype were characterized as “hot tumor” conveying the increased presence of immunogenicity while reiterating an explicit negative connection with tumor stemness. Compared to immune and stromal cells, cancerous cells showcased decreased PANoptosis and heightened PANoptosis malignant cell subgroups might be tied to a substantial level of genomic expression of SREBF2, JUND, GATAD1, ZBTB20, SMAD5 and implied a more aggressive potential. The PANoptosis index, derived from machine learning, has been established to provide succinct frameworks for predicting outcomes and clarified the noteworthy utility of conventional regimens, as the differentiated power of HCC occurred together with vascular invasion and hepatocellular adenoma (HCA). The experiment confirmed that the circulating HSP90AA1 was aberrantly augmented in HCC patients, thus demonstrating its potential as a discriminatory biomarker. We systematically deciphered the molecular and immune ecosystem traits of PANoptosis in bulk and scRNA-seq degrees, which may deliver advantageous insights for customized treatment, awareness of the pathological process and prognosis scrutiny for HCC patients.

In the present review, we focused on recent translational and clinical discoveries in asthma immunology, facilitating phenotyping and stratified or personalized interventions for patients with this condition. The immune processes behind chronic inflammation in asthma exhibit marked heterogeneity, with diverse phenotypes defining discernible features and endotypes illuminating the underlying molecular mechanisms. In particular, two primary endotypes of asthma have been identified: “type 2-high,” characterized by increased eosinophil levels in the airways and sputum of patients, and “type 2-low,” distinguished by increased neutrophils or a pauci-granulocytic profile. Our review encompasses significant advances in both innate and adaptive immunities, with emphasis on the key cellular and molecular mediators, and delves into innovative biological and targeted therapies for all the asthma endotypes. Recognizing that the immunopathology of asthma is dynamic and continuous, exhibiting spatial and temporal variabilities, is the central theme of this review. This complexity is underscored through the innumerable interactions involved, rather than being driven by a single predominant factor. Integrated efforts to improve our understanding of the pathophysiological characteristics of asthma indicate a trend toward an approach based on disease biology, encompassing the combined examination of the clinical, cellular, and molecular dimensions of the disease to more accurately correlate clinical traits with specific disease mechanisms.

Abstract Background Gastric emptying (GE), with wide inter-individual but lesser intra-individual variations, is a major determinant of postprandial glycaemia in health and type 2 diabetes (T2D). However, it is uncertain whether GE of a carbohydrate-containing liquid meal is predictive of the glycaemic response to physiological meals, and whether antecedent hyperglycaemia influences GE in T2D. We evaluated the relationships of (i) the glycaemic response to both a glucose drink and mixed meals with GE of a 75 g glucose drink, and (ii) GE of a glucose drink with antecedent glycaemic control, in T2D. Methods Fifty-five treatment-naive Chinese adults with newly diagnosed T2D consumed standardised meals at breakfast, lunch and dinner with continuous interstitial glucose monitoring. On the subsequent day, a 75 g glucose drink containing 150 mg 13C-acetate was ingested to assess GE (breath test) and plasma glucose response. Serum fructosamine and HbA1c were also measured. Results Plasma glucose incremental area under the curve (iAUC) within 2 hours after oral glucose was related inversely to the gastric half-emptying time (T50) (r = −0.34, P = 0.012). The iAUCs for interstitial glucose within 2 hours after breakfast (r = −0.34, P = 0.012) and dinner (r = −0.28, P = 0.040) were also related inversely to the T50 of oral glucose. The latter, however, was unrelated to antecedent fasting plasma glucose, 24-hour mean interstitial glucose, serum fructosamine, or HbA1c. Conclusions In newly diagnosed, treatment-naive, Chinese with T2D, GE of a 75 g glucose drink predicts the glycaemic response to both a glucose drink and mixed meals, but is not influenced by spontaneous short-, medium- or longer-term elevation in glycaemia.

Cholestatic liver injury results from the accumulation of toxic bile acids in the liver, presenting a therapeutic challenge with no effective treatment available to date. Andrographolide (AP) has exhibited potential as a treatment for cholestatic liver disease. However, its limited oral bioavailability poses a significant obstacle to harnessing its potent therapeutic properties and restricts its clinical utility. This limitation is potentially attributed to the involvement of gut microbiota in AP metabolism. In our study, employing pseudo-germ-free, germ-free and strain colonization animal models, along with 16S rRNA and shotgun metagenomic sequencing analysis, we elucidate the pivotal role played by gut microbiota in the C-sulfonate metabolism of AP, a process profoundly affecting its bioavailability and anti-cholestatic efficacy. Subsequent investigations pinpoint a specific enzyme, adenosine-5’-phosphosulfate (APS) reductase, predominantly produced by Desulfovibrio piger, which catalyzes the reduction of SO42- to HSO3−. HSO3− subsequently interacts with AP, targeting its C=C unsaturated double bond, resulting in the formation of the C-sulfonate metabolite, 14-deoxy-12(R)-sulfo andrographolide (APM). Inhibition of APS reductase leads to a notable enhancement in AP bioavailability and anti-cholestatic efficacy. Furthermore, employing RNA sequencing analysis and farnesoid X receptor (FXR) knockout mice, our findings suggest that AP may exert its anti-cholestatic effects by activating the FXR pathway to promote bile acid efflux. In summary, our study unveils the significant involvement of gut microbiota in the C-sulfonate metabolism of AP and highlights the potential benefits of inhibiting APS reductase to enhance its therapeutic effects. These discoveries provide valuable insights into enhancing the clinical applicability of AP as a promising treatment for cholestatic liver injury.

To address the data quality issues caused by environmental changes and other factors, this paper proposes a method for repairing missing traffic flow data from loop detectors, leveraging the spatiotemporal characteristics of traffic flow. Then, a Bi-directional Long Short-Term Memory with an Improved Genetic Algorithm (IGA-Bi-LSTM) model and an improved Deep Forest (DF) traffic flow data imputation model are constructed. By combining the advantages of these two models, the improved DF model is used to extract spatiotemporal characteristics and impute sequential data to obtain temporal features. These features are coupled with spatiotemporal characteristics and input into the IGA-Bi-LSTM neural network to establish the Spatiotemporal Imputation Model (STIM), ultimately enhancing data quality. To verify the reliability of the results, the experimental data used the PORTAL public dataset and compared the performance of Historical Average (HA), Autoregressive Integrated Moving Average (ARIMA) model, Random Forest (RF), and Bi-directional Long Short-Term Memory with Genetic Algorithm (GA-Bi-LSTM) models. The results indicate that the STIM model has more advantages compared to other methods. Finally, traffic flow theory is used for validation, and the results confirm that the imputed traffic flow data are reliable, demonstrating the significant importance of this research for traffic flow data analysis.

Abstract This paper proposes a novel machine learning (ML) assisted low‐latency low density parity check (LDPC) coded adaptive modulation (AM) system, where short block‐length LDPC codes are used. Conventional adaptive modulation and coding (AMC) system includes fixed look‐up table method, which is also called inner loop link adaptation (ILLA) and outer loop link adaptation (OLLA). For ILLA, the adaptive capability is achieved by switching the modulation and coding modes based on a look‐up table using signal‐to‐noise ratio (SNR) thresholds at the target bit error rate (BER), while OLLA builds upon the ILLA method by dynamically adjusting the SNR thresholds to further optimize the system performance. Although both improve the system overall throughput by switching between different transmission modes, there is still a gap to optimal performance as the BER is comparatively far away from the target BER. Machine learning (ML) is a promising solution in solving various classification problems. In this work, the supervised learning based k‐nearest neighbours (KNN) algorithm is invoked for choosing the optimum transmission mode based on the training data and the instantaneous SNR. This work focuses on the low‐latency communications scenarios, where short block‐length LDPC codes are utilized. On the other hand, given the short block‐length constraint, we propose to artificially generate the training data to train our ML assisted AMC scheme. The simulation results show that the proposed ML‐LDPC‐AMC scheme can achieve a higher throughput than the ILLA system while maintaining the target BER. Compared with OLLA, the proposed scheme can maintain the target BER while the OLLA fails to maintain the target BER when the block length is short. In addition, when considering the channel estimation errors, the performance of the proposed ML‐LDPC‐AMC maintains the target BER, while the ILLA system's BER performance can be higher than the target BER.

The pathological features of intraductal oncocytic papillary neoplasm (IOPN) of the bile duct include tumor cells that are rich in eosinophilic cytoplasm and arranged in papillary structures. Herein, we report a missed case of IOPN of the bile duct because of concomitant gallstones. A 70-year-old woman was hospitalized with upper abdominal discomfort. The primary diagnosis was choledocholithiasis following imaging examination. However, an unidentified mass was detected after the gallstones were removed. The mass appeared as many papillary protuberances surrounded by fish-egg-like mucosa when viewed by the choledochoscope and was confirmed as IOPN by pathological examination. The patient underwent choledochectomy and no recurrence was observed at the 6-month follow-up examination. In this report, peroral choledochoscopy demonstrated its advantages for the diagnosis of biliary diseases and acquisition of tissue specimens. Therefore, it may solve the challenge related to the lack of preoperative pathological evidence for bile duct tumors.

Background: Poly (ADP-ribose) polymerase (PARP) inhibitor and antiangiogenic agent monotherapy have shown to be effective as maintenance treatment in patients with ovarian cancer (OC). However, there is currently a lack of evidence-based study to directly compare the effects of combination therapy with these two drugs. Therefore, this study aimed to compare the efficacy and safety of combination therapy with PARP inhibitors and antiangiogenic agents in women with OC using a meta-analysis.Methods: An exhaustive search of literature was undertaken using multiple databases, including PubMed, Web of Science, Embase, and the Cochrane Library to identify pertinent randomized controlled trials (RCTs) published up until 17 December 2023. The data on progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were pooled. We computed the pooled hazard ratios (HRs) and their 95% confidence intervals (CIs) for PFS and OS, along with the relative risks (RRs) and 95% CIs for AEs. Trial sequential analysis, heterogeneity test, sensitivity analysis, and publication bias assessment were performed. Stata 12.0 and Software R 4.3.1 were utilized for all analyses.Results: This meta-analysis included 7 RCTs with a total of 3,388 participants. The overall analysis revealed that combination therapy of PARP inhibitors and antiangiogenic agents significantly improved PFS (HR = 0.615, 95% CI = 0.517–0.731; 95% PI = 0.379–0.999), but also increased the risk of AEs, including urinary tract infection (RR = 1.500, 95% CI = 1.114–2.021; 95% PI = 0.218–10.346), fatigue (RR = 1.264, 95% CI = 1.141–1.400; 95% PI = 1.012–1.552), headache (RR = 1.868, 95% CI = 1.036–3.369; 95% PI = 0.154–22.642), anorexia (RR = 1.718, 95% CI = 1.320–2.235; 95% PI = 0.050–65.480), and hypertension (RR = 5.009, 95% CI = 1.103–22.744; 95% PI = 0.016–1580.021) compared with PARP inhibitor or antiangiogenic agent monotherapy. Our study has not yet confirmed the benefit of combination therapy on OS in OC patients (HR = 0.885, 95% CI = 0.737–1.063). Additionally, subgroup analyses further showed that combination therapy resulted in an increased risk of AEs, encompassing thrombocytopenia, vomiting, abdominal pain, proteinuria, fatigue, headache, anorexia, and hypertension (all p < 0.05).Conclusion: Our study demonstrated the PFS benefit of combination therapy with PARP inhibitors and antiangiogenic agents in patients with OC. The OS result need to be updated after the original trial data is mature. Clinicians should be vigilant of AEs when administering the combination therapy in clinical practice.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023494482.

Abstract Tuberous sclerosis complex (TSC) is an autosomal dominant disorder with different initial symptoms and complex clinical manifestations. A 14-year-old female patient presented with persistent fever and severe headache. Medical imaging examinations revealed multiple abnormal intracranial lesions. The patient had previously been misdiagnosed with “encephalitis and acute disseminated encephalomyelitis” after visiting numerous hospitals. Eventually, by combing the characteristics of the case and genetic testing results, the patient was diagnosed with TSC accompanied by Mycoplasma pneumoniae infection. The purpose of this case report and literature review is to improve understanding of the clinical diagnosis and treatment of TSC so as to avoid misdiagnosis, missed diagnosis, and overtreatment.

Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating psychiatric disorders; however, the variability in treatment efficacy among individuals underscores the need for further improvement. Growing evidence has shown that TMS induces a broad network modulatory effect, and its effectiveness may rely on accurate modulation of the pathological network specific to each disorder. Therefore, determining the optimal TMS coil setting that will engage the functional pathway delivering the stimulation is crucial. Compared to group-averaged functional connectivity (FC), individual FC provides specific information about a person’s brain functional architecture, offering the potential for more accurate network targeting for personalized TMS. However, the low signal-to-noise ratio (SNR) of FC poses a challenge when utilizing individual resting-state FC. To overcome this challenge, the proposed solutions include increasing the scan duration and employing the cluster method to enhance the stability of FC. This study aimed to evaluate the stability of a personalized FC-based network targeting model in individuals with major depressive disorder or schizophrenia with auditory verbal hallucinations. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we assessed the model’s stability. We employed longer scan durations and cluster methodologies to improve the precision in identifying optimal individual sites. Our findings demonstrate that a scan duration of 28 minutes and the utilization of the cluster method achieved stable identification of individual sites, as evidenced by the intraindividual distance falling below the ~1cm spatial resolution of TMS. The current model provides a feasible approach to obtaining stable personalized TMS targets from the scalp, offering a more accurate method of TMS targeting in clinical applications.

Seed cotton yield and fiber quality are two primary factors that influence the international competitiveness of cotton. To enhance the water-nitrogen utilization efficiency and promote the sustainable cotton production, field experiments were performed in 2020 and 2021 to explore the effects of irrigation depth and nitrogen (N) fertilization rate on N uptake and distribution, seed cotton yield, fiber quality traits and water-nitrogen utilization efficiency in the Korla region of southern Xinjiang, China. Three irrigation depths (W1: 60% ETc, W2: 80% ETc, W3: 100% ETc; ETc was crop water consumption) and four N rates (N0: 0 kg ha−1, N200: 200 kg ha−1, N300: 300 kg ha−1, N400: 400 kg ha−1) were applied. The results showed irrigation depth and N rate significantly influenced N uptake and distribution in plant organs, seed cotton yield, crop water productivity (WP), partial factor productivity of nitrogen (PFPN) and some fiber quality traits. Increasing irrigation depth improved plant height, leaf area index, aboveground dry matter and seed cotton yield, while increasing N rate increased and then declined these indicators. At the squaring and flowering stages, the N accumulation in all parts of cotton increased as irrigation depth and N rate increased, whereas it increased and then declined with increasing N rate at the boll-setting and harvesting stages. At the squaring and flowering stages, N was mainly accumulated in the leaves. As the growth period progressed, N was transported to bolls and the proportion of N content in leaves decreased. The proportion of N accumulation in cotton bolls was largest at the boll-setting and harvesting stages, and the N accumulation in plant organs followed the order of boll > leaf > stem > root. As irrigation depth increased, PFPN increased but WP decreased. As N rate increased, PFPN decreased but WP increased and then declined. The increases in N rate improved fiber quality. The maximum seed cotton yield (7578 kg ha−1 in 2020 and 7173 kg ha−1 in 2021) and greater WP, PFPN and fiber quality occurred in W3N300, which was recommended as a sustainable cotton production strategy in the Korla region of southern Xinjiang and elsewhere with similar environments to improve water-nitrogen utilization efficiency, seed cotton yield and alleviate soil nitrate pollution risk.

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive disease of the lung. How to build a typical human mimicking animal model has been a challenge. Thus, to reveal the mechanism and to make it useful for IPF clinical treatment, a different type of mice model and inspection methods are used to evaluate which one is applicable for the study of IPF. Method 69 Twelve-weeks-old C57BL/6 mice were divided into 3 type groups (n = 7 for each control group, n = 8 for each BLM-induced pulmonary fibrosis groups), as intraperitoneal injection, intratracheal administration, and intravenous administration of bleomycin (BLM) to initiate lung fibrosis. Changes of the lung function measured through mice Pulmonary function test (PFT). Morphological changes in mice were observed by PET/CT, Masson and Picro-Sirius staining, Transmission electron microscopy (TEM). Biochemical changes were tested by Enzyme-linked immunosorbent assay (Elisa). Results PET/CT of BLM-receiving mice showed an increase in fibrotic consolidations and an increase in non-aerated lung area in BLM-treated mice compared with that in controls. TGF-b1, TNF-a, IL-6, GM-CSF in BALF and serum. PAI-1, HYP in the lung tissue of mice were significantly different in each BLM groups than those in the controls. The results of Masson staining in mice indicate that the lung tissues of all BLM received groups, the intratracheal groups, the intravenous groups, and the intraperitoneal groups have a higher degree of pulmonary septal thickening and collagen fiber consolidation compare to saline control. Picro-Sirius staining results are consistent with the results of Masson staining. Compared with the saline control group, the ratio of Col 1/Col 3 was significantly increased in each BLM group. TEM results found that in BLM group, type I alveolar epithelial cells were degenerated. Exfoliated endothelial cells were swelling, and type II alveolar epithelial cells were proliferated, the shape of the nucleus was irregular, and some tooth-like protrusions were seen. Conclusions With three different methods of animal model construction, high dose of each show more compliable, and BLM can successfully induce animal models of pulmonary fibrosis, however, certain differences in the fibrosis formation sites of them three, and tail vein injection of BLM induced PF model is closer to the idiopathic pulmonary interstitial fibrosis.

Context Asthma is a common respiratory system disease. Louki Zupa decoction (LKZP), a traditional Chinese medicine, presents a promising efficacy against lung diseases.Objective To investigate the pathogenic mechanism of asthma and reveal the intervention mechanism of LKZP.Materials and methods Forty-eight female Balb/c mice were randomly divided into 6 groups: normal control group (NC), ovalbumin (OVA)/saline asthma model group, OVA/LL group, OVA/LM group, OVA/LH group and OVA/DEX group (n = 8 per group). The asthmatic mice were modelled through intraperitoneal injecting and neutralizing OVA. LKZP decoction was administrated by gavage at the challenge stage for seven consecutive days (2.1, 4.2 and 8.4 g/kg/day). We investigated the change in lung function, airway inflammation, mucus secretion and TH-1/TH-2-related cytokines. We further verify the activated status of the IL-33/ST2/NF-κB/GSK3β/mTOR signalling pathway.Results LKZP was proved to improve asthmatic symptoms, as evidenced by the down-regulated airway resistance by 36%, 58% and 53% (p

Abstract The asymmetric introduction of functional groups into polymers is promising due to its potential to provide novel electronic and magnetic properties. Though traditional on‐surface bottom‐up synthesis has succeeded in creating various types of polymers, it struggles at realizing asymmetry due to the difficulty of stereoregular polymerization and the tendency for overall polarity cancellation during agglomeration. Here, enabled by the low halogen‐contaminated metal surfaces provided by two‐zone chemical vapor deposition, “compass” precursors possessing three independent bonding, edge, and dipole vectors undergo isotactic polymerization via the vectorial self‐assembly of chiral precursor diradicals without the need for chiral catalysts required in conventional in‐solution polymerization. The isotactic polymers exhibit polar 2D crystalline structures due to the hetero‐edge CH–π interaction between the standing phenyl and butoxy group surpassing the homo‐edge interactions of π–π and CHCH. The developed vectorial on‐surface synthetic technique not only paves the way to the realization of stereoregular control but also unlocks unprecedented crystal engineering.

Abstract Introduction Epilepsy is one of the most common and serious brain syndromes and has adverse consequences on a patient's neurobiological, cognitive, psychological, and social wellbeing, thereby threatening their quality of life. Some patients with epilepsy experience poor treatment effects due to the unclear pathophysiological mechanisms of the syndrome. Dysregulation of the mammalian target of the rapamycin (mTOR) pathway is thought to play an important role in the onset and progression of some epilepsies. Methods This review summarizes the role of the mTOR signaling pathway in the pathogenesis of epilepsy and the prospects for the use of mTOR inhibitors. Results The mTOR pathway functions as a vital mediator in epilepsy development through diverse mechanisms, indicating that the it has great potential as an effective target for epilepsy therapy. The excessive activation of mTOR signaling pathway leads to structural changes in neurons, inhibits autophagy, exacerbates neuron damage, affects mossy fiber sprouting, enhances neuronal excitability, increases neuroinflammation, and is closely associated with tau upregulation in epilepsy. A growing number of studies have demonstrated that mTOR inhibitors exhibit significant antiepileptic effects in both clinical applications and animal models. Specifically, rapamycin, a specific inhibitor of TOR, reduces the intensity and frequency of seizures. Clinical studies in patients with tuberous sclerosis complex have shown that rapamycin has the function of reducing seizures and improving this disease. Everolimus, a chemically modified derivative of rapamycin, has been approved as an added treatment to other antiepileptic medicines. Further explorations are needed to evaluate the therapeutic efficacy and application value of mTOR inhibitors in epilepsy. Conclusions Targeting the mTOR signaling pathway provides a promising prospect for the treatment of epilepsy.

Natural disasters lead to the uncertain topological structure of the urban distribution network. It is difficult for the communication system to recover quickly, which brings great difficulties to restoring the power supply. Therefore, the deployment of an emergency power supply is one of the critical measures to ensure the stable operation of isolated network systems and reduce power loss. Compared with the traditional synchronous diesel generator (SDG) as an emergency power supply, a doubly-fed induction diesel generator (DFIDG) has the advantages of flexible and controllable, rapid response and high operation efficiency. This paper presents a layered frequency control strategy for a doubly-fed induction diesel generator in an emergency scenario. Firstly, the models of doubly-fed induction diesel generator and its control system, prime mover and its speed regulation system are established. Secondly, the hierarchical frequency control strategy is proposed, including primary integrated frequency control (including droop control and virtual inertia control) and secondary frequency regulation control based on translation method. The virtual inertia control can make the doubly-fed machine quickly release the rotor kinetic energy when the frequency changes rapidly, so as to improve the frequency supportability. According to the overall shortage of the system and the maximum output power of the doubly-fed induction diesel generator, the strategy calculates the secondary frequency regulation power adjustment as the DFIDG power setting value, and then can realize automatic secondary frequency regulation without a communication system. Finally, simulation results verify the effectiveness of the proposed strategy.

Abstract As the pervasive, standardized format for interchange and deposition of raw mass spectrometry (MS) proteomics and metabolomics data, text-based mzML is inefficiently utilized on various analysis platforms due to its sheer volume of samples and limited read/write speed. Most research on compression algorithms rarely provides flexible random file reading scheme. Database-developed solution guarantees the efficiency of random file reading, but nevertheless the efforts in compression and third-party software support are insufficient. Under the premise of ensuring the efficiency of decompression, we propose an encoding scheme “Stack-ZDPD” that is optimized for storage of raw MS data, designed for the format “Aird”, a computation-oriented format with fast accessing and decoding time, where the core compression algorithm is “ZDPD”. Stack-ZDPD reduces the volume of data stored in mzML format by around 80% or more, depending on the data acquisition pattern, and the compression ratio is approximately 30% compared to ZDPD for data generated using Time of Flight technology. Our approach is available on AirdPro, for file conversion and the Java-API Aird-SDK, for data parsing.

Highland barley flour-based coating batter has rarely been reported, although highland barley flour is promising due to its high β-glucan and amylose content. In this study, highland barley flour was used to substitute 40% to 80% of wheat flour to form a highland barely-wheat composite flour used in the coating batter. The characteristics of the highland barley-wheat composite flour and its effect on the properties of coating batter and deep-fried meat were analyzed. Results showed that the composite flour significantly improved water holding capacity, oil absorbing capacity, and water solubility index. In contrast, no significant change was observed in the water absorption index or swelling power. The incorporation of highland barley flour significantly changed the pasting properties of the composite flour. Compared with the wheat flour, the viscosity and the pickup of the coating batter made with composite flour increased from 4905 Pa·s and 0.53% to more than 12,252 Pa·s and 0.63%, respectively, and its water mobility decreased. These changes were closely related to the substitution rate of highland barley flour. The composite flour significantly increased the moisture content from 27.73% to more than 33.03% and decreased the oil content of the crust from 19.15% to lower than 16.44%, respectively. It decreased L* and increased a* of the crust and decreased the hardness, adhesiveness, and springiness of the deep-fried meat. A spongy inner structure with a flatter surface was formed in all composite flour-based crusts, and the substitution rate influenced the flatness of the crust. Thus, highland barley flour could be used for batter preparation with partial substitution, enhancing the quality of deep-fried meat and acting as an oil barrier-forming ingredient for fried batter foods.

Abstract China has a great wealth of lake resources over a great spatial extent and these lakes are highly sensitive to climate changes through their heat and water budgets. However, little is known about the changes in lake surface water temperature (LSWT) across China under the climate warming conditions over the past few decades. In this study, MODIS land surface temperature (LST) data were used to examine the spatial and temporal (diurnal, intra-annual, and inter-annual) variations in LSWT of China’s lakes during 2001–2016. Our results indicated that 169 large lakes included in the study exhibited an overall increasing trend in LSWT, with an average rate of 0.26 °C/decade. The increasing rate of nighttime LSWT is 0.31 °C/decade, faster than that of daytime temperature (0.21 °C/decade). Overall, 121 (71.6%) lakes showed an increase in daytime temperature with a mean rate of 0.38 °C/decade, while the rest 48 (28.4%) lakes decreased in temperature with a mean rate of − 0.21 °C/decade. We also quantitatively analyzed the relationship of the lake surface temperature and diurnal temperature differences (DTDs) with geographical location, topography, and lake morphometry by utilizing multivariate regression analysis. Our analysis suggested that the geographical location (latitude and longitude) and topography (altitude) were primary driving factors in explaining the national lake water temperature variation (P

To address the problems of 5G network planning and optimization, a 5G user time delay prediction model based on the BiLSTM neural network optimized by APSO-SD is proposed. First, a channel generative model based on the ray-tracing model and the statistical channel model is constructed to obtain a large amount of time delay data, and a 5G user ray data feature model based on three-dimensional stereo mapping is proposed for input feature extraction. Then, an adaptive particle swarm optimization algorithm based on a search perturbation mechanism and differential enhancement strategy (APSO-SD) is proposed for the parameters’ optimization of BiLSTM neural networks. Finally, the APSO-SD-BiLSTM model is proposed to predict the time delay of 5G users. The experimental results show that the APSO-SD has a better convergence performance and optimization performance in benchmark function optimization compared with the other PSO algorithms, and the APSO-SD-BiLSTM model has better user time delay prediction accuracy in different scenarios.

The mechanism of hepatocellular carcinoma (HCC) development induced by liver fibrosis is obscure. The objective of this study is to establish miRNAs from exosomes associated with liver fibrosis, and to identify potential biomarkers for the prediction of personalized clinical management effectiveness in HCC. Our research focused on miRNAs from exosomes and mRNA from liver fibrosis, which we found in the gene expression omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) evaluated miRNAs from exosomes associated with liver fibrosis, and Wilcoxon analysis assessed differentially expressed mRNAs (DEGs) across liver fibrosis/normal tissues. Following that, DEGs were assessed through gene set enrichment analysis (GSEA), gene ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, based on the screened targeted genes, including SAMD12 and CADM2, we further elucidated their correlation in HCC patients from the BEST database. The Kaplan-Meier Plotter platform was applied to evaluate the prognostic values of miRNA in HCC. In vitro and vivo experiments validated our findings. Six miRNAs associated with liver fibrosis were evaluated in our investigation. In-depth research presented exosome-derived miR-106a-5p, SAMD12 and CADM2 could exert valuable predictive implications for HCC treatment and illness assessment. Serum miR-106a-5p derived from liver fibrosis was decreased compared with healthy individuals. SAMD12 and CADM2 were diminished in liver cancer cell lines, and their knockdown of them exacerbated the proliferation capacities of liver cells in vitro. Exosome-derived miRNA of liver fibrosis modulated tumorigenesis by targeting SAMD12 and CADM2 in HCC.

PurposeThe objective of this study was to sort out innovative molecular subtypes associated with mitochondrial ribosomal proteins (MRPs) to predict clinical therapy response and determine the presence of circulating markers in hepatocellular carcinoma (HCC) patients.MethodsUsing an unsupervised clustering method, we categorized the relative molecular subtypes of MRPs in HCC patients. The prognosis, biological properties, immune checkpoint inhibitor and chemotherapy response of the patients were clarified. A signature and nomogram were developed to evaluate the prognosis. Enzyme-linked immunosorbent assay (ELISA) measured serum mitochondrial ribosomal protein L9 (MRPL9) levels in liver disease patients and normal individuals. Receiver operating characteristic (ROC) curves were conducted to calculate the diagnostic effect. The Cell Counting Kit 8 was carried out to examine cell proliferation, and flow cytometry was used to investigate the cell cycle. Transwell assay was applied to investigate the potential of cell migration and invasion. Western blot detected corresponding changes of biological markers.ResultsParticipants were classified into two subtypes according to MRPs expression levels, which were characterized by different prognoses, biological features, and marked differences in response to chemotherapy and immune checkpoint inhibitors. Serum MRPL9 was significantly higher in HCC patients than in normal individuals and the benign liver disease group. ROC curve analysis showed that MRPL9 was superior to AFP and Ferritin in differentiating HCC from healthy and benign patients, or alone. Overexpressed MRPL9 could enhance aggressiveness and facilitate the G1/S progression in HCC cells.ConclusionWe constructed novel molecular subtypes based on MRPs expression in HCC patients, which provided valuable strategies for the prediction of prognosis and clinical personalized treatment. MRPL9 might act as a reliable circulating diagnostic biomarker and therapeutic target for HCC patients.

It has been recognized that the efficacy of TMS-based modulation may depend on the network profile of the stimulated regions throughout the brain. However, what profile of this stimulation network optimally benefits treatment outcomes is yet to be addressed. The answer to the question is crucial for informing network-based optimization of stimulation parameters, such as coil placement, in TMS treatments. In this study, we aimed to investigate the feasibility of taking a disease-specific network as the target of stimulation network for guiding individualized coil placement in TMS treatments. We present here a novel network-based model for TMS targeting of the pathological network. First, combining E-field modeling and resting-state functional connectivity, stimulation networks were modeled from locations and orientations of the TMS coil. Second, the spatial anti-correlation between the stimulation network and the pathological network of a given disease was hypothesized to predict the treatment outcome. The proposed model was validated to predict treatment efficacy from the position and orientation of TMS coils in two depression cohorts and one schizophrenia cohort with auditory verbal hallucinations. We further demonstrate the utility of the proposed model in guiding individualized TMS treatment for psychiatric disorders. In this proof-of-concept study, we demonstrated the feasibility of the novel network-based targeting strategy that uses the whole-brain, system-level abnormity of a specific psychiatric disease as a target. Results based on empirical data suggest that the strategy may potentially be utilized to identify individualized coil parameters for maximal therapeutic effects.

Cl− movement and Cl−-sensitive signal pathways contributes to the survival and switch of inflammatory phenotype of microglia and are believed to play a key role in the inflammatory brain injury after ischemic stroke. Here, we demonstrated an important role of Cl− transmembrane transporter Swell1, in the survival and M2-like polarization of microglia in ischemic stroke. Knockdown or overexpression of Swell1 in cultured microglia inhibited or increased hypotonic-activated Cl− currents, respectively, and these changes were completely blocked by the volume-regulated anion channels (VRACs) inhibitor DCPIB. Swell1 conditional knock-in mice promoted microglia survival in ischemic brain region and resulted in significant reductions in neural cell death, infarction volume and neurological deficits following transient middle cerebral artery occlusion (tMCAO). Using gene manipulating technique and pharmacological inhibitors, we further revealed that Swell1 opening led to SGK1 (a Cl−-sensitive kinase)-mediated activation of FOXO3a/CREB as well as WNK1 (another Cl−-sensitive kinase)-mediated SPAK/OSR1-CCCs activation, which promoted microglia survival and M2-like polarization, thereby attenuating neuroinflammation and ischemic brain injury. Taken together, our results demonstrated that Swell1 is an essential component of microglia VRACs and its activation protects against ischemic brain injury through promoting microglia survival and M2-like polarization.

BackgroundThis study aimed to develop a nomogram to predict the survival for stage IIIC endometrial cancer (EC) patients with adjuvant radiotherapy (ART) alone and personalize recommendations for the following adjuvant chemotherapy (ACT).MethodsIn total, 746 stage IIIC EC patients with ART alone were selected from the Surveillance, Epidemiology, and End Results (SEER) registry. Cox regression analysis was performed to identify independent risk factors. A nomogram was developed accordingly, and the area under the receiver operating characteristic curve (AUC) and C-index were implemented to assess the predictive power. The patients were divided into different risk strata based on the total points derived from the nomogram, and survival probability was compared between each risk stratus and another SEER-based cohort of stage IIIC EC patients receiving ART+ACT (cohort ART+ACT).ResultsFive independent predictors were included in the model, which had favorable discriminative power both in the training (C-index: 0.732; 95% CI: 0.704–0.760) and validation cohorts (C-index: 0.731; 95% CI: 0.709–0.753). The patients were divided into three risk strata (low risk 205), where low-risk patients had survival advantages over patients from cohort ART+ACT (HR: 0.45, 95% CI: 0.33–0.61, P < 0.001). However, the middle- and high-risk patients were inferior to patients from cohort ART+ACT in survival (P < 0.001).ConclusionA nomogram was developed to exclusively predict the survival for stage IIIC EC patients with ART alone, based on which the low-risk patients might be perfect candidates to omit the following ACT. However, the middle- and high-risk patients would benefit from the following ACT.

Objectives: This study aimed to estimate the long-term trends of deaths attributable smoking in China, Japan, the United Kingdom (UK) and the United States (US).Methods: Using 2000–2019 death data from Global Burden of Disease (GBD) 2019, we estimated age-period-cohort effects on smoking attributable mortality, and decomposed of differences in smoking-attributable deaths in 1990 and 2019 into demographic factors.Results: From 1990 to 2019, smoking-attributable deaths increased in China, which was due to population growth and demographic aging. From 1990 to 2019, both age-standardized smoking attributable mortality rates trended downward across countries. Among four countries, age rate ratios (RRs) for smoking-attributable mortality increased with age, while period and cohort RRs decreased with year.Conclusion: The age-standardized mortality rates, period effects and cohort effects of smoking attributable mortality in China, Japan, UK, and US have been declining in both sexes from 1990 to 2019, which suggests that smoke-free policies, help to quit tobacco use, improved health education, more accessible healthcare service, and increased taxes have been effective. Additionally, increased smoking attributable deaths in elderly should got more attention.

Chronic kidney disease (CKD) caused heavy burden globally. This study aimed to investigate the patterns and temporal variations in the burden of CKD in China, Japan, the United Kingdom (U.K.), and the United States (U.S.) from 1990 to 2019, and decompose the difference in CKD disease burden between 1990 and 2019 into demographic factors. From 1990 to 2019, although the age-standardized rate (ASR) of incidence remained stable in the four countries, and the ASR of mortality and disability-adjusted life years (DALY) have declined in four countries (except for the increase in U.S.), the number of CKD incidence, death, and DALY increased significantly. The average disease burden per case in U.S. has increased between 1990 and 2019, with an increasing proportion of death-related disease burden. For the CKD due to diabetes and hypertension, whose incidences accounted for < 25% of the total CKD, while it accounts for more than 70% of the deaths (except in U.K. with 54.14% in women and 51.75% in men). CKD due to diabetes and hypertension should be the focus of CKD prevention and control. Considering the high treatment costs of CKD and ESRD, it is urgent and necessary to transform CKD treatment into primary and secondary prevention.

Abstract Co‐pyrolysis synergy between cornstalk and bituminous coal was investigated based on the physicochemical properties of the char. The char was prepared by directly putting the individual or blended materials into a heated resistance furnace at 600°C or 800°C. The performance of surface morphology and mineral matters was not notably changed by co‐pyrolysis, indicated by scanning electron microscope and X‐ray diffraction. However, N2 and CO2 adsorption‐desorption isotherms confirmed that surface area and pore structure were strongly influenced, particularly in large micropores and mesopores. Ultimate analysis and inductively coupled plasma optical emission spectrometer measurement revealed excessive depositions of carbon, alkali, and alkaline‐earth metal species in co‐pyrolysis char. Energy‐dispersive X‐ray spectrometer analysis examined the elemental surface distribution, suggesting that co‐pyrolysis under moderate temperature strongly favored inhibiting potassium release. The non‐isothermal thermogravimetry‐differential scanning calorimeter experiments under air atmosphere were conducted for char combustion reactivity, which was expected to be instructive for deeper understanding about co‐pyrolysis synergy and reutilization of the char. The thermal behaviors during combustion of co‐pyrolysis char clearly resembled a single fuel, which completely varied from those of the char blends. Besides, co‐pyrolysis chars and char blends were superior in total heat release compared with the simple addition of calculated values from individual char. Based on these observations, key factors of the synergy were supposed to have consisted of free radical reaction, secondary char formation, and the migration of alkali and alkaline‐earth metal species.

Abstract Few study has revealed spatial transmission characteristics of COVID-19 in Wuhan, China. We aimed to analyze the spatiotemporal spread of COVID-19 in Wuhan and its influence factors. Information of 32,682 COVID-19 cases reported through March 18 were extracted from the national infectious disease surveillance system. Geographic information system methods were applied to analysis transmission of COVID-19 and its influence factors in different periods. We found decrease in effective reproduction number (Rt) and COVID-19 related indicators through taking a series of effective public health measures including restricting traffic, centralized quarantine and strict stay-at home policy. The distribution of COVID-19 cases number in Wuhan showed obvious global aggregation and local aggregation. In addition, the analysis at streets-level suggested population density and the number of hospitals were associated with COVID-19 cases number. The epidemic situation showed obvious global and local spatial aggregations. High population density with larger number of hospitals may account for the aggregations. The epidemic in Wuhan was under control in a short time after strong quarantine measures and restrictions on movement of residents were implanted.

BackgroundThe coronavirus disease 2019 (COVID-19) is a severe acute respiratory disease that poses a continuous threat to global public health. Many non-pharmacological interventions (NPIs) have been implemented to control the COVID-19 pandemic since the beginning. The aim of this study was to assess the impact of various NPIs on COVID-19 mortality during pre-vaccination and vaccination periods.MethodsThe COVID-19 data used in this study comes from Our World in Data, we used the Oxford Strict Index (OSI) and its five combination interventions as independent variables. The COVID-19 mortality date (MRT) was defined as a date when daily rate of 0.02 COVID-19 deaths per 100,000 population in a country was reached, and the COVID-19 vaccination date (VRT) was defined as people vaccinated reaching 70%. Linear regression and random forest models were used to estimate the impact of various NPI implementation interventions during pre-vaccination and vaccination periods. The performance of models was assessed among others with Shapley Additive Explanations (SHAP) explaining the prediction capability of the model.ResultsDuring the pre-vaccination period, the various NPIs had strong protective effect. When the COVID-19 MRT was reached, for every unit increase in OSI, the cumulative mortality as of June 30, 2020 decreased by 0.71 deaths per 100,000 people. Restrictions in travel (SHAP 1.68) and cancelation of public events and gatherings (1.37) had major reducing effect on COVID-19 mortality, while staying at home (0.26) and school and workplace closure (0.26) had less effect. Post vaccination period, the effects of NPI reduced significantly: cancelation of public events and gatherings (0.25), staying at home (0.22), restrictions in travel (0.14), and school and workplace closure (0.06).ConclusionContinued efforts are still needed to promote vaccination to build sufficient immunity to COVID-19 in the population. Until herd immunity is achieved, NPI is still important for COVID-19 prevention and control. At the beginning of the COVID-19 pandemic, the stringency of NPI implementation had a significant negative association with COVID-19 mortality; however, this association was no longer significant after the vaccination rate reached 70%. As vaccination progresses, “cancelation of public events and gatherings” become more important for COVID-19 mortality.

Abstract Background Until January 18, 2021, coronavirus disease-2019 (COVID-19) has infected more than 93 million individuals and has caused a certain degree of panic. Viral pneumonia caused by common viruses such as respiratory syncytial virus, rhinovirus, human metapneumovirus, human bocavirus, and parainfluenza viruses have been more common in children. However, the incidence of COVID-19 in children was significantly lower than that in adults. The purpose of this study was to describe the clinical manifestations, treatment and outcomes of COVID-19 in children compared with those of other sources of viral pneumonia diagnosed during the COVID-19 outbreak. Methods Children with COVID-19 and viral pneumonia admitted to 20 hospitals were enrolled in this retrospective multi-center cohort study. A total of 64 children with COVID-19 were defined as the COVID-19 cohort, of which 40 children who developed pneumonia were defined as the COVID-19 pneumonia cohort. Another 284 children with pneumonia caused by other viruses were defined as the viral pneumonia cohort. The epidemiologic, clinical, and laboratory findings were compared by Kolmogorov-Smirnov test, t-test, Mann-Whitney U test and Contingency table method. Drug usage, immunotherapy, blood transfusion, and need for oxygen support were collected as the treatment indexes. Mortality, intensive care needs and symptomatic duration were collected as the outcome indicators. Results Compared with the viral pneumonia cohort, children in the COVID-19 cohort were mostly exposed to family members confirmed to have COVID-19 (53/64 vs. 23/284), were of older median age (6.3 vs. 3.2 years), and had a higher proportion of ground-glass opacity (GGO) on computed tomography (18/40 vs. 0/38, P

In this paper, the leader-following consensus problem of a multi-Euler-Lagrange system is studied under deception attacks, where attackers can inject the false data into the data being exchanged over the communication network between two Euler-Lagrange systems. A distributed adaptive filter is proposed to compensate the unknown injection false data, where the magnitude of the false data is estimated. Meanwhile, the performance of the multiple Euler-Lagrange system consensus with the proposed filter can be guaranteed to be similar to that with the traditional controller when the communication network is not injected into false data by a malicious attacker. Furthermore, the consensus criteria of a multiple Euler-Lagrange system and the parameter design scheme of the proposed adaptive filter are achieved by using Lyapunov stability theory. Finally, a numerical example is carried out to demonstrate the effectiveness of the proposed consensus controller for a multi-Euler-Lagrange system attacked by using the false data injection.

Abstract Hand, foot, and mouth disease (HFMD) is common among children below 5 years. HFMD has a high incidence in Hubei Province, China. In this study, the Prophet model was used to forecast the incidence of HFMD in comparison with the autoregressive-integrated moving average (ARIMA) model, and HFMD incidence was decomposed into trends, yearly, weekly seasonality and holiday effect. The Prophet model fitted better than the ARIMA model in daily reported incidence of HFMD. The HFMD incidence forecast by the Prophet model showed that two peaks occurred in 2019, with the higher peak in May and the lower peak in December. Periodically changing patterns of HFMD incidence were observed after decomposing the time-series into its major components. In specific, multi-year variability of HFMD incidence was found, and the slow-down increasing point of HFMD incidence was identified. Relatively high HFMD incidences appeared in May and on Mondays. The effect of Spring Festival on HFMD incidence was much stronger than that of other holidays. This study showed the potential of the Prophet model to detect seasonality in HFMD incidence. Our next goal is to incorporate climate variables into the Prophet model to produce an accurate forecast of HFMD incidence.

Surge is the most significant instability observed in the compressors, and its control requires the exact dynamics of the compressor systems. Uncertainty in compressor characteristics and unknown opening percentage of the throttle and spillback valves, as well as disturbances in compressor’s flow and pressures, are among the major issues to be addressed in controller design for surge instability. Furthermore, in compressor systems that consist of several individual compressors, their reciprocal effects should also be taken into account. This paper presents an LMI-based decentralized robust model predictive control to ensure the stability of the compressor system against surge instability, uncertainty, and disturbance. The proposed scheme benefits from the optimized control signal with minimum computational complexity to overcome the destabilizing effects in a complex compressor system. The considered working class for this compressor system is a continuous-time nonlinear system. Through this method, the optimization problem is designed for a worst-case scenario. The implementation results of the presented robust controller for a compressor system, consisting of three parallel and series compressors, suggest the effectiveness of the presented method.

ObjectiveThis study aimed to assess the knowledge, attitude, and practice (KAP) of diabetic subjects with diabetic retinopathy (DR) and those without DR (NDR) in an urban community in Northeast China, as well as their risk factors in subjects with DR and NDR.MethodsA community-based survey involving 1,662 subjects was conducted in Fushun, China, between July 2012 and May 2013. The subjects included diabetics with DR (n = 783) and those NDR (n = 879), and questionnaires were completed to collect information about their sociodemographic and healthcare characteristics. A Chi-square test and multiple logistic analyses were performed to analyze the data.ResultsAmong the DR group, 21.88% had a good knowledge of DR, 94.15% had a positive attitude, and 68.07% followed good practice, whereas 20.98% of the NDR group had a good knowledge of DR, 94.18% had a positive attitude, and 66.92% followed good practice. There was no significant difference in the KAP of the two groups of subjects. In the NDR group, a good level of knowledge was associated with a high-level of education (OR = 0.1, 0.2; p < 0.05), a good attitude was associated with retirement (OR = 0.2; p < 0.05), and good practice was associated with being female, having a high-level of education, and the type of treatment (OR = 0.5, 0.4, 2.3, 3.1; p < 0.05). In the DR group, good practice was associated with older age and retirement (OR = 0.6, 0.4; p < 0.05).ConclusionsThere was no significant difference between the DR and NDR subjects in the overall levels of KAP, but both groups showed a poor level of knowledge. Age, gender, education, occupation, and type of treatment were the main factors associated with the KAP scores, more risk factors in the NDR group than in the DR group. There is an urgent need for coordinated educational campaigns with a prioritized focus on the northeast region of China, especially NDR group.

Magnolol, the main active ingredient of Magnolia officinalis, has been reported to display anti-inflammatory activity. Sulfation plays an important role in the metabolism of magnolol. The magnolol sulfated metabolite was identified by the ultra-performance liquid chromatography to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and a proton nuclear magnetic resonance (1H-NMR). The magnolol sulfation activity of seven major recombinant sulfotransferases (SULTs) isoforms (SULT1A1*1, SULT1A1*2, SULT1A2, SULT1A3, SULT1B1, SULT1E1, and SULT2A1) was analyzed. The metabolic profile of magnolol was investigated in liver S9 fractions from human (HLS9), rat (RLS9), and mouse (MLS9). The anti-inflammatory effects of magnolol and its sulfated metabolite were evaluated in RAW264.7 cells stimulated by lipopolysaccharide (LPS). Magnolol was metabolized into a mono-sulfated metabolite by SULTs. Of the seven recombinant SULT isoforms examined, SULT1B1 exhibited the highest magnolol sulfation activity. In liver S9 fractions from different species, the CLint value of magnolol sulfation in HLS9 (0.96 µL/min/mg) was similar to that in RLS9 (0.99 µL/min/mg) but significantly higher than that in MLS9 (0.30 µL/min/mg). Magnolol and its sulfated metabolite both significantly downregulated the production of inflammatory mediators (IL-1β, IL-6 and TNF-α) stimulated by LPS (p < 0.001). These results indicated that SULT1B1 was the major enzyme responsible for the sulfation of magnolol and that the magnolol sulfated metabolite exhibited potential anti-inflammatory effects.

Quantitative analysis of brain volume is quite significant for the diagnosis of brain diseases. Accurate segmentation of essential brain tissues from 3D medical images is fundamental to quantitative brain analysis. Since manual segmentation is extremely tedious and time-consuming, there is a growing demand for automated segmentation. In this paper, we propose a 3D convolutional neural network including recursive residual blocks and a pyramid pooling module (RP-Net) for segmenting brain from 3D magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). RP-Net is an U-Net like the network that consists of a downsampling path and an upsampling path. Each path consists of four stages with a recursive residual block. All layers in RP-Net are implemented in a 3D manner. The pyramid pooling module is applied before a voxel-wise classification layer for obtaining both local and global context information. The RP-Net has been evaluated on WM, GM, and CSF segmentation with CANDI, IBSR18, and IBSR20 dataset. The experiments show that the RP-Net achieved mean dice similarity coefficients of 90.7% on CANDI, 90.49% on IBSR18 and 84.96% on IBSR20. The results demonstrate that our proposed method has achieved a significant improvement in segmentation accuracy compared to other reported approaches.

Various side information has been exploited in recommender systems to help users finding items they prefer to alleviate data sparsity. Because item category can be used to view the user's preference in a high-level scope and an item can have more than one associated category, the existing works leverage this characteristic, that enriches the information density of item, to further improve the recommendation performance. However, the existing works either treat item categories or their correlations as additional information to compute the similarity between users and items, or introduce category hierarchy as a latent factor into matrix factorization (MF) models. In these works, each item corresponds to a category set, that makes it too difficult to utilize item category's potential and valuable information. In this paper, we propose a novel combinatorial category space based recommendation model, which can fully exploit item category information and reduce the difficulty by converting the relationship between item and its categories from one-to-many to one-to-one. It considers a combinatorial category associated with an item, not each of them individually. Specifically, we first define a combinatorial category space (CCS), which is viewed as a subset-superset lattice of item categories. Then semantic relations and semantic distances are defined to model a user preference, and a compound graph (CoGraph) is constructed to model users' interactive behaviors in CCS, respectively. Finally, two recommendation models, CCSRank and CCSMF, are exploited on user interactive graph. We carry out extensive experimental evaluations on two real datasets to show the effectiveness of our model.

Distributed machine learning is primarily motivated by the promise of increased computation power for accelerating training and mitigating privacy concerns. Unlike machine learning on a single device, distributed machine learning requires collaboration and communication among the devices. This creates several new challenges: (1) the heavy communication overhead can be a bottleneck that slows down the training, and (2) the unreliable communication and weaker control over the remote entities make the distributed system vulnerable to systematic failures and malicious attacks. This paper presents a variant of stochastic gradient descent (SGD) with improved communication efficiency and security in distributed environments. Our contributions include (1) a new technique called error reset to adapt both infrequent synchronization and message compression for communication reduction in both synchronous and asynchronous training, (2) new score-based approaches for validating the updates, and (3) integration with both error reset and score-based validation. The proposed system provides communication reduction, both synchronous and asynchronous training, Byzantine tolerance, and local privacy preservation. We evaluate our techniques both theoretically and empirically.

Uniform error estimates with power-type asymptotic constants of the finite element method for the unsteady Navier–Stokes equations are deduced in this paper. By introducing an iterative scheme and studying its convergence, we firstly derive that the solution of the Navier–Stokes equations is bounded by power-type constants, where we avoid applying the Gronwall lemma, which generates exponential-type factors. Then, the technique is extended to the error estimate of the long-time finite element approximation. The analyses show that, under some assumptions on the given data, the asymptotic constants in the finite element error estimates for the unsteady Navier–Stokes equations are uniformly power functions with respect to the initial data, the viscosity, and the body force for all time t>0. Finally, some numerical examples are shown to verify the theoretical predictions.

Selection of interfacial layer is critical for nonfullerene active layers to obtain high performance due to high chemical reactivity with base or amines. So far, alcohol‐processed ethoxylated polyethylenimine (PEIE) interfacial layer has not been successfully used in high‐performance nonfullerene solar cells. Herein, findings are reported as follows: 1) alcohol‐processed PEIE as an interfacial layer can deliver high‐performance (15.3%) Y6‐based nonfullerene solar cells if its thickness is reduced to about 1.2 nm rather than 5–10 nm that is generally used in fullerene solar cells. That is comparable with the reference cells with ZnO interlayer. Slightly thicker PEIE (5 nm) would significantly reduce the power conversion efficiency down to 7.5%. This is completely different from the fullerene‐based solar cells. 2) The ultrathin thickness strategy is not universal for other nonfullerene acceptors. Even though the PEIE thickness is about 1.2 nm, the IT‐4F‐based nonfullerene solar cells exhibit lower performance than reference cells with ZnO interlayer. That is because the IT‐4F is more chemically reactive than Y6 with the PEIE. The observation suggests the proper selection and optimization of the interfacial layer is critical to the solar cells with different nonfullerene electron acceptors.

The COVID-19 epidemic is associated with negative mood, which has the potential to be a powerful driver of creativity. However, the influence of negative mood on cognitive creativity and emotional creativity remains elusive. Previous research has indicated that self-focused attention is likely to be related to both negative mood and creativity. The current study introduced two self-focused attention variables (i.e., rumination, reflection) to explore how negative mood might contribute to cognitive creativity and emotional creativity. Based on a sample of 351 participants, our study found that (1) negative mood during the outbreak of COVID-19 was associated with cognitive creativity and emotional creativity. Meanwhile, there were significant serial mediation effects of rumination and reflection in the relationship between negative mood and creativity and (2) the psychological impact after exposure to the COVID-19 epidemic was positively correlated with emotional creativity but not with cognitive creativity. These results suggested that individuals, in real life and work, could achieve better creative performance through moderate self-focus. Moreover, individuals with different mood states can be induced to enhance their creativity in times of crisis through intervention training to promote reflection.

The interaction of nutrients with the small intestine modulates postprandial cardiovascular function. Rapid small intestinal nutrient delivery may reduce blood pressure markedly, particularly in patients with type 2 diabetes (T2DM). Postprandial hypotension occurs in ~30% of patients with longstanding T2DM, but there is little information about the cardiovascular effects of different macronutrients. We compared the blood pressure and heart rate responses to standardized intraduodenal glucose and fat infusions in T2DM. Two parallel groups, including 26 T2DM patients who received intraduodenal glucose infusion and 14 T2DM patients who received intraduodenal fat, both at 2 kcal/min over 120 min, were compared retrospectively. Blood pressure and heart rate were measured at regular intervals. Systolic blood pressure was stable initially and increased slightly thereafter in both groups, without any difference between them. Diastolic blood pressure decreased in response to intraduodenal glucose, but remained unchanged in response to lipid, with a significant difference between the two infusions (P = 0.04). Heart rate increased during both intraduodenal glucose and lipid infusions (P < 0.001 each), and the increment was greater in response to intraduodenal fat than glucose (P = 0.004). In patients with T2DM, intraduodenal fat induced a greater increase in heart rate, associated with a diminished reduction in blood pressure, when compared with isocaloric glucose. The macronutrient composition of meals may be an important consideration in T2DM patients with symptomatic postprandial hypotension.

In 2018, there were more than 371 million cigarette smokers and 12. 6 million electronic cigarette users, with 340.2 million non-smokers exposed to secondhand smoke (SHS) in China, which resulted in heavy tobacco-attributable disease burden. According to the definition by the Global Burden of Disease Study 2017 (GBD 2017), tobacco is a level 2 risk factor that consists of three sublevel risk factors, namely, smoking, SHS, and chewing tobacco. In this study, we aimed to evaluate the trends in deaths and disability-adjusted life years (DALYs) attributable to tobacco, smoking, SHS, and chewing tobacco by sex in China from 1990 to 2017 and to explore the leading causes of tobacco-attributable deaths and DALYs using data from the GBD 2017. From 1990 to 2017, the tobacco-attributable death rates per 100,000 people decreased from 75.65 [95% uncertainty interval (95% UI) = 56.23–97.74] to 70.90 (95% UI = 59.67–83.72) in females and increased from 198.83 (95% UI = 181.39–217.47) to 292.39 (95% UI = 271.28–313.76) in males. From 1990 to 2017, the tobacco-attributable DALY rates decreased from 2209.11 (95% UI = 1678.63–2791.91) to 1489.05 (95% UI = 1237.65–1752.57) in females and increased from 5650.42 (95% UI = 5070.06–6264.39) to 6994.02 (95% UI = 6489.84–7558.41) in males. In 2017, the tobacco-attributable deaths in China were concentrated on chronic obstructive pulmonary disease, ischemic heart disease, lung cancer, and stroke. The focus of tobacco control for females was SHS in 1990, whereas smoking and SHS were equally important for tobacco control in females in 2017. Increasing tobacco taxes and prices may be the most effective and feasible measure to reduce tobacco-attributable disease burdens.

China has experienced unprecedented urbanization in the past decades, resulting in dramatic changes in the physical, limnological, and hydrological characteristics of lakes in urban landscapes. However, the spatiotemporal dynamics in distribution and abundance of urban lakes in China remain poorly understood. Here, we characterized the spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015 using remote-sensing data and landscape metrics. The results showed that the urban lake landscape patterns have experienced drastic changes over the past 25 years. The total surface area of the urban lakes has decreased by 17,620.02 ha, a decrease of 24.22%, with a significant increase in the landscape fragmentation and a reduction in shape complexity. We defined three lake-shrinkage types and found that vanishment was the most common lake-shrinkage pattern, followed by edge-shrinkage and tunneling in terms of lake area. Moreover, we also found that urban sprawl was the dominant driver of the lake shrinkage, accounting for 67.89% of the total area loss, and the transition from lakes to cropland was also an important factor (19.86%). This study has potential for providing critical baseline information for government decision-making in lake resources management and urban landscape design.

X-ray images obtained from synchrotron beamlines are large-scale, high-resolution and high-dynamic-range grayscale data encoding multiple complex properties of the measured materials. They are typically associated with a variety of metadata which increases their inherent complexity. There is a wealth of information embedded in these data but so far scientists lack modern exploration tools to unlock these hidden treasures. To bridge this gap, we propose MultiSciView, a multivariate scientific x-ray image visualization and exploration system for beamline-generated x-ray scattering data. Our system is composed of three complementary and coordinated interactive visualizations to enable a coordinated exploration across the images and their associated attribute and feature spaces. The first visualization features a multi-level scatterplot visualization dedicated for image exploration in attribute, image, and pixel scales. The second visualization is a histogram-based attribute cross filter by which users can extract desired subset patterns from data. The third one is an attribute projection visualization designed for capturing global attribute correlations. We demonstrate our framework by ways of a case study involving a real-world material scattering dataset. We show that our system can efficiently explore large-scale x-ray images, accurately identify preferred image patterns, anomalous images and erroneous experimental settings, and effectively advance the comprehension of material nanostructure properties. Keywords: Scientific x-ray image visualization, Multi-level scatterplot, Cross-data space exploration

Postprandial hypotension (PPH) is an important and under-recognised disorder resulting from inadequate compensatory cardiovascular responses to meal-induced splanchnic blood pooling. Current approaches to management are suboptimal. Recent studies have established that the cardiovascular response to a meal is modulated profoundly by gastrointestinal factors, including the type and caloric content of ingested meals, rate of gastric emptying, and small intestinal transit and absorption of nutrients. The small intestine represents the major site of nutrient-gut interactions and associated neurohormonal responses, including secretion of glucagon-like peptide-1, glucose-dependent insulinotropic peptide and somatostatin, which exert pleotropic actions relevant to the postprandial haemodynamic profile. This review summarises knowledge relating to the role of these gut peptides in the cardiovascular response to a meal and their potential application to the management of PPH.