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Abstract TIMM9 has been identified as a mediator of essential functions in mitochondria, but its association with pan-cancer is poorly understood. We herein employed bioinformatics, computational chemistry techniques and experiments to investigate the role of TIMM9 in pan-cancer. Our analysis revealed that overexpression of TIMM9 was significantly associated with tumorigenesis, pathological stage progression, and metastasis. Missense mutations (particularly the S49L variant), copy number variations (CNV) and methylation alterations in TIMM9 were found to be associated with poor cancer prognosis. Moreover, TIMM9 was positively related with cell cycle progression, mitochondrial and ribosomal function, oxidative phosphorylation, TCA cycle activity, innate and adaptive immunity. Additionally, we discovered that TIMM9 could be regulated by cancer-associated signaling pathways, such as the mTOR pathway. Using molecular simulations, we identified ITFG1 as the protein that has the strongest physical association with TIMM9, which show a promising structural complement.

BackgroundAs the Internet becomes an increasingly vital source of medical information, the quality and reliability of brain tumor-related short videos on platforms such as TikTok and Bilibili have not been adequately evaluated. Therefore, this study aims to assess these aspects and explore the factors influencing the dissemination of such videos.MethodsA cross-sectional analysis was conducted on the top 100 brain tumor-related short videos from TikTok and Bilibili. The videos were evaluated using the Global Quality Score and the DISCERN reliability instrument. An eXtreme Gradient Boosting algorithm was utilized to predict dissemination outcomes. The videos were also categorized by content type and uploader.ResultsTikTok videos scored relatively higher on both the Global Quality Score (median 2, interquartile range [2, 3] on TikTok vs. median 2, interquartile range [1, 2] on Bilibili, p = 1.51E-04) and the DISCERN reliability instrument (median 15, interquartile range [13, 18.25] on TikTok vs. 13.5, interquartile range [11, 16] on Bilibili, p = 1.66E-04). Subgroup analysis revealed that videos uploaded by professional individuals and institutions had higher quality and reliability compared to those uploaded by non-professional entities. Videos focusing on disease knowledge exhibited the highest quality and reliability compared to other content types. The number of followers emerged as the most important variable in our dissemination prediction model.ConclusionThe overall quality and reliability of brain tumor-related short videos on TikTok and Bilibili were unsatisfactory and did not significantly influence video dissemination. Future research should expand the scope to better understand the factors driving the dissemination of medical-themed videos.

Krylov complexity has emerged as a probe of operator growth in a wide range of nonequilibrium quantum dynamics. However, a fundamental issue remains in such studies: the definition of the distance between basis states in Krylov space is ambiguous. Here we show that Krylov complexity can be rigorously established from circuit complexity when dynamical symmetries exist. Whereas circuit complexity characterizes the geodesic distance in a multidimensional operator space, Krylov complexity measures the height of the final operator in a particular direction. The geometric representation of circuit complexity thus unambiguously designates the distance between basis states in Krylov space. This geometric approach also applies to time-dependent Liouvillian superoperators, where a single Krylov complexity is no longer sufficient. Multiple Krylov complexity may be exploited jointly to fully describe operator dynamics.

Abstract The aim of this study was to explore the impact of chronic apical periodontitis (CAP) on atherosclerosis in apoE−/− mice fed high-fat diet (HFD). This investigation focused on the gut microbiota, metabolites, and intestinal barrier function to uncover potential links between oral health and cardiovascular disease (CVD). In this study, CAP was shown to exacerbate atherosclerosis in HFD-fed apoE−/− mice, as evidenced by the increase in plaque size and volume in the aortic walls observed via Oil Red O staining. 16S rRNA sequencing revealed significant alterations in the gut microbiota, with harmful bacterial species thriving while beneficial species declining. Metabolomic profiling indicated disruptions in lipid metabolism and primary bile acid synthesis, leading to elevated levels of taurochenodeoxycholic acid (TCDCA), taurocholic acid (TCA), and tauroursodeoxycholic acid (TDCA). These metabolic shifts may contribute to atherosclerosis development. Furthermore, impaired intestinal barrier function, characterized by reduced mucin expression and disrupted tight junction proteins, was observed. The increased intestinal permeability observed was positively correlated with the severity of atherosclerotic lesions, highlighting the importance of the intestinal barrier in cardiovascular health. In conclusion, this research underscores the intricate interplay among oral health, gut microbiota composition, metabolite profiles, and CVD incidence. These findings emphasize the importance of maintaining good oral hygiene as a potential preventive measure against cardiovascular issues, as well as the need for further investigations into the intricate mechanisms linking oral health, gut microbiota, and metabolic pathways in CVD development.

Abstract In a quantum many-body system, autocorrelation functions can determine linear responses nearby equilibrium and quantum dynamics far from equilibrium. In this letter, we bring out the connection between the operator complexity and the autocorrelation function. In particular, we focus on a particular kind of operator complexity called the Krylov complexity. We find that a set of Lanczos coefficients { b n } $\{b_{n}\}$ computed for determining the Krylov complexity can reveal the universal behaviors of autocorrelations, which are otherwise impossible. When the time axis is scaled by b 1 $b_{1}$ , different autocorrelation functions obey a universal function form at short time. We further propose a characteristic parameter deduced from { b n } $\{b_{n}\}$ that can largely determine the behavior of autocorrelations at the intermediate time. This parameter can also largely determine whether the autocorrelation function oscillates or monotonically decays in time. We present numerical evidences and physical intuitions to support these universal hypotheses of autocorrelations. We emphasize that these universal behaviors are held across different operators and different physical systems.

Abstract Brainbow is a genetic cell-labeling technique that allows random colorization of multiple cells and real-time visualization of cell fate within a tissue, providing valuable insights into understanding complex biological processes. However, fluorescent proteins (FPs) in Brainbow have distinct excitation spectra with peak difference greater than 35 nm, which requires sequential imaging under multiple excitations and thus leads to long acquisition times. In addition, they are not easily used together with other fluorophores due to severe spectral bleed-through. Here, we report the development of a single-wavelength excitable Brainbow, UFObow, incorporating three newly developed blue-excitable FPs. We have demonstrated that UFObow enables not only tracking the growth dynamics of tumor cells in vivo but also mapping spatial distribution of immune cells within a sub-cubic centimeter tissue, revealing cell heterogeneity. This provides a powerful means to explore complex biology in a simultaneous imaging manner at a single-cell resolution in organs or in vivo.

Berberine (BBR) is a compound derived from Chinese herbal medicine, known for its anticancer properties through multiple signaling pathways. However, whether BBR can inhibit tumor growth by participating in ferroptosis remains unconfirmed. In this study, we demonstrated that berberine synergistically inhibited NSCLC in combination with multiple ferroptosis inducers, and this combination synergistically down-regulated the mRNA and protein expression of SLC7A11, GPX4, and NRF2, resulting in ferroptosis accompanied by significant depletion of GSH, and aberrant accumulation of reactive oxygen species and malondialdehyde. In a lung cancer allograft model, the combination treatment exhibited enhanced anticancer effects compared to using either drug alone. Notably, p53 is critical in determining the ferroptosis sensitivity. We found that the combination treatment did not elicit a synergistic anticancer effect in cells with a p53 mutation or with exogenous expression of mutant p53. These findings provide insight into the mechanism by which combination induces ferroptosis and the regulatory role of p53 in this process. It may guide the development of new strategies for treating NSCLC, offering great medical potential for personal diagnosis and treatment.

Abstract Lung adenocarcinoma (LUAD) is a malignant tumor in the respiratory system. The efficacy of current treatment modalities varies greatly, and individualization is evident. Therefore, finding biomarkers for predicting treatment prognosis and providing reference and guidance for formulating treatment options is urgent. Cancer immunotherapy has made distinct progress in the past decades and has a significant effect on LUAD. Immunogenic Cell Death (ICD) can reshape the tumor’s immune microenvironment, contributing to immunotherapy. Thus, exploring ICD biomarkers to construct a prognostic model might help individualized treatments. We used a lung adenocarcinoma (LUAD) dataset to identify ICD-related differentially expressed genes (DEGs). Then, these DEGs were clustered and divided into subgroups. We also performed variance analysis in different dimensions. Further, we established and validated a prognostic model by LASSO Cox regression analysis. The risk score in this model was used to evaluate prognostic differences by survival analysis. The treatment prognosis of various therapies were also predicted. LUAD samples were divided into two subgroups. The ICD-high subgroup was related to an immune-hot phenotype more sensitive to immunotherapy. The prognostic model was constructed based on six ICD-related DEGs. We found that high-risk score patients responded better to immunotherapy. The ICD prognostic model was validated as a standalone factor to evaluate the ICD subtype of individual LUAD patients, which might contribute to more effective therapies.

Abstract To guarantee an uninterruptable power supply, a microgrid must be able to operate in both islanded and grid‐connected modes. Hence, it is required to synchronize the voltage phasor of the point of common coupling of the microgrid with the utility grid. Therefore, a distributed cooperative hierarchal control structure is proposed that seamlessly synchronized an islanded microgrid with the utility grid. A proposed method uses a leader‐follower based consensus to regulate the voltage phasor while ensuring proportionate load sharing. A synchronization controller is designed that uses an adjustable parameter to eliminate the voltage magnitude and phase mismatch, and transmit the regulated compensation signal to the leader DGs. The leader DGs transmits these signals to the follower DGs through a cyber‐channels. Moreover, a Massachusetts Institute of Technology rule and Lyapunov function based adaptive controllers are designed to update the secondary control law parameters in case of any disturbance or uncertainty. These adaptive techniques do not require prior knowledge about the microgrid topology, loads, and impedances thus enhancing the system performance. Furthermore, a small signal stability analysis is presented to facilitate the controller parameter design criteria. Finally, the robustness and effectiveness of proposed structure is verified through simulation results in different scenarios.

Natural plants contain numerous chemical compounds that are beneficial to human health. The berries from the Lycium genus are widely consumed and are highly nutritious. Moreover, their chemical constituents have attracted attention for their health-promoting properties. In East Asia, there are three varieties of the Lycium genus (Lycium barbarum L., Lycium chinense Miller, and L. ruthenicum Murray) that possess medicinal value and are commonly used for treating chronic diseases and improving metabolic disorders. These varieties are locally referred to as “red Goji berries” or “black Goji berries” due to their distinct colors, and they differ in their chemical compositions, primarily in terms of carotenoid and anthocyanin content. The pharmacological functions of these berries include anti-aging, antioxidant, anti-inflammatory, and anti-exercise fatigue effects. This review aims to analyze previous and recent studies on the active ingredients and pharmacological activities of these Lycium varieties, elucidating their signaling pathways and assessing their impact on the gut microbiota. Furthermore, the potential prospects for using these active ingredients in the treatment of COVID-19 are evaluated. This review explores the potential targets of these Lycium varieties in the treatment of relevant diseases, highlighting their potential value in drug development.

Abstract The fluctuation of photovoltaics (PVs) output may cause the voltage out‐of‐limit, while the PV inverters and hybrid distribution transformers (HDTs) bring flexible controllability to distribution networks (DNs). However, there are differences in response speeds between power electronic equipment and traditional discrete regulating equipment. Therefore, a network partitioning and hierarchical voltage regulation method using holomorphic embedding method (HEM) ‐based sensitivity is proposed. Firstly, the HEM‐based voltage sensitivity is derived, and the network partitioning method is proposed using the HEM‐based sensitivity matrix. Then, the hierarchical voltage regulation framework is constructed. The objects of the upper layer are the minimum network loss and voltage deviation, which centrally optimizes the operation status of discrete regulation equipment. The lower layer exploits the fast control ability of PV inverters and HDTs, so as to autonomously regulate the voltage of each partition. Finally, a practical 10 kV DN in China is used for case studies. The results demonstrate that the HEM‐based voltage sensitivity calculation method has advantages in computational efficiency and accuracy compared with the conventional method. Moreover, the proposed voltage regulation method can suppress the voltage fluctuation.

Although salinity satellites can provide high-resolution global sea surface salinity (SSS) data, the satellite data still display large errors close to the coast. In this paper, a nonlinear empirical method based on random forest is proposed to correct two Soil Moisture and Ocean Salinity (SMOS) L3 products in the tropical Indian Ocean, including SMOS BEC and SMOS CATDS data. The agreement between in-situ data and the corrected SMOS data is better than that between in-situ data and the original satellite data. The root-mean-square deviation (RMSD) of the satellite SSS data decreased from 0.366 to 0.275 and from 0.367 to 0.255 for SMOS BEC and SMOS CATDS, respectively. The effect of the correction model was better in the Arabian Sea than in the Bay of Bengal. The RMSD of corrected BEC (CATDS) SSS was reduced from 0.44 (0.48) to 0.276 (0.269), and the correlation coefficient was increased to 0.915 from 0.741(0.801) in the Arabian Sea while the correlation coefficient improved less than 0.02 in the Bay of Bengal. The cross-validation results highlight the robustness and effectiveness of the correction model. Additionally, the effects of different features on the correction model are discussed to demonstrate the vital role of geographical information in the correction of satellite SSS data. The proposed method outperformed other machine-learning methods with respect to the RMSD and correlation coefficient.

With the accelerated melting of the Arctic sea ice, the opening of the Northeast Passage of the Arctic is becoming increasingly accessible. Nevertheless, the constantly changing natural environment of the Arctic and its multiple impacts on vessel navigation performance have resulted in a lack of confidence in the outcomes of polar automated route planning. This paper aims to evaluate the effectiveness of two distinct models by examining the advancements in two essential components of e-navigation, namely ship performance methods and ice routing algorithms. We also seek to provide an outlook on the future directions of model development. Furthermore, through comparative experiments, we have examined the existing research on ice path planning and pointed out promising research directions in future Arctic Weather Routing research.

Long hairpin RNA (hpRNA) transgenes are the most widely used RNAi technology in plants, but are potentially subject to self-induced transcriptional silencing. Here, the authors show nucleotide mismatches prevent intrinsic self-silencing of hpRNA transgenes in Arabidopsis and tobacco.

Nicotinamide adenine dinucleotide phosphate (NADP), a co-enzyme and an electron carrier, plays crucial roles in numerous biological functions, including cellular metabolism and antioxidation. Because NADP is subcellular-membrane impermeable, eukaryotes compartmentalize NAD kinases (NADKs), the NADP biosynthetic enzymes. Mitochondria are fundamental organelles for energy production through oxidative phosphorylation. Ten years after the discovery of the mitochondrial NADK (known as MNADK or NADK2), a significant amount of knowledge has been obtained regarding its functions, mechanism of action, human biology, mouse models, crystal structures, and post-translation modifications. NADK2 phosphorylates NAD(H) to generate mitochondrial NADP(H). NADK2-deficient patients suffered from hyperlysinemia, elevated plasma C10:2-carnitine (due to the inactivity of relevant NADP-dependent enzymes), and neuronal development defects. Nadk2-deficient mice recapitulate key features of NADK2-deficient patients, including metabolic and neuronal abnormalities. Crystal structures of human NADK2 show a dimer, with the NADP+-binding site located at the dimer interface. NADK2 activity is highly regulated by post-translational modifications, including S188 phosphorylation, K76 and K304 acetylation, and C193 S-nitrosylation; mutations in each site affect NADK2 activity and function. In mice, hepatic Nadk2 functions as a major metabolic regulator upon increased energy demands by regulating sirtuin 3 activity and fatty acid oxidation. Hopefully, future research on NADK2 will not only elucidate its functional roles in health and disease but will also pave the way for novel therapeutics for both rare and common diseases, including NADK2 deficiency and metabolic syndrome.

The understanding and control of non-Hermitian phenomena is becoming every day more important. Here the authors establish the duality between non-Hermiticity and curved spaces. It unfolds a geometric root of non-Hermitian phenomena and provides a study and tailor non-Hermiticity using curved spaces.

Objective: To investigate the effect and its underlying molecular mechanisms of essential oil from Saussurea costus in esophageal cancer cell line Eca109. Methods: The chemical composition of essential oil from Saussurea costus was investigated by gas chromatography-mass spectrometry (GC-MS). The anti-proliferative, anti-migrative, and apoptotic effects of essential oil from Saussurea costus against Eca109 cells were analyzed. Moreover, the expression of proteins associated with cell cycle, metastasis, and apoptosis was determined. Results: GC-MS analysis showed that essential oil from Saussurea costus was predominantly comprised of sesquiterpenes. Saussurea costus essential oil inhibited the viability of Eca109 cells in a dose-and time-dependent manner with IC50 values of (24.29±1.49), (19.16±2.27) and (6.97±0.86) μg/mL at 12, 24, and 48 h, respectively. The expression levels of target proteins in the cell cycle (phase G1/S), including cyclin D1, p21, and p53, were affected by Saussurea costus essential oil. The essential oil also downregulated the expression of metastasis-related proteins MMP-9 and MMP-2. Moreover, it induced apoptosis of Eca109 cells through the mitochondrial pathway, as well as inhibition of STAT3 phosphorylation. Conclusions: The essential oil from Saussurea costus exhibited anti-proliferative, anti-migrative, and apoptotic effects on Eca109 cells, and could be further explored as a potential anti-esophageal cancer agent.

Microscopic pore structures are of great significance in evaluating shale gas reservoirs and understanding the occurrence state of shale gas. Integrating geochemical analysis, X-ray diffraction (XRD), low-temperature N2 adsorption (LTNA), mercury injection pressure (MIP), small-angle X-ray scattering (SAXS), and field emission scanning electron microscope (FE-SEM), this work systematically characterized microscopic pore structures and then discussed their controlling factors, for the Lower Carboniferous Luzhai (C1lz) shale in Guizhong Depression. The results show that pores in the Luzhai shale are generally shaped by ink bottles, parallel plates, and slits, which are characterized by a larger pore throat ratio, lower efficiency of mercury withdrawal, and poor connectivity. Micropores (

Objectives: Retinal ischemia-reperfusion injury (RIRI) is the common pathological basis of many ophthalmic diseases in the later stages, and inflammation is the primary damage mechanism of RIRI. Our study aimed to assess whether electroacupuncture (EA) has a protective effect against RIRI and to elucidate its related mechanisms.Methods: A high-intraocular pressure (HIOP) model was used to simulate RIRI in Wistar rats. EA was applied to the EA1 group [Jingming (BL1) + Shuigou (GV26)] and the EA2 group [Jingming (BL1) + Hegu (LI4)] respectively for 30 min starting immediately after the onset of reperfusion and repeated (30 min/time) at 12 h and then every 24 h until days 7 after reperfusion. The pathological changes in the retina were observed by H and E staining after HIOP. Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining was utilized to observe retinal cell apoptosis. The mRNA expression of IL1-β, TNF-α, IL-4, IL-10, δ-opioid receptor (DOR), brain-derived neurotrophic factor (BDNF), and tropomyosin-related kinase B (TrkB) in the retina was measured by quantitative real-time PCR.Results: HIOP caused structural disorders of the retina, decreased RGCs, and increased retinal cell apoptosis. At 1 and 3 days of RIRI, retinal apoptotic cells in the EA group were significantly reduced, while there was no distinct difference in the EA group compared with the HIOP group at 7 days of RIRI. Compared with that in the HIOP group, the expression of anti-inflammatory factors, DOR and TrkB was increased, and the expression of pro-inflammatory factors was decreased in the EA group. In contrast, HIOP had no appreciable effect on BDNF expression.Conclusion: EA at Jingming (BL1) and Shuigou (GV26) or at Jingming (BL1) and Hegu (LI4) may inhibit RIRI induced inflammation through activating the DOR-BDNF/TrkB pathway to protect the retina, especially the pair of Jingming (BL1) and Shuigou (GV26) has better inhibitory effects on inflammation.

This longitudinal cohort study aimed to determine whether circulating neurofilaments (NFs) can monitor response to molecular therapies in newborns with spinal muscular atrophy (SMA; NCT02831296). We applied a mixed-effect model to examine differences in serum NF levels among healthy control infants (n = 13), untreated SMA infants (n = 68), and SMA infants who received the genetic therapies nusinersen and/or onasemnogene abeparvovec (n = 22). Increased NF levels were inversely associated with SMN2 copy number. SMA infants treated with either nusinersen or onasemnogene abeparvovec achieved important motor milestones not observed in the untreated cohort. NF levels declined more rapidly in the nusinersen cohort as compared with the untreated cohort. Unexpectedly, those receiving onasemnogene abeparvovec monotherapy showed a significant rise in NF levels regardless of SMN2 copy number. In contrast, symptomatic SMA infants who received nusinersen, followed by onasemnogene abeparvovec within a short interval after, did not show an elevation in NF levels. While NF cannot be used as the single marker to predict outcomes, the elevated NF levels observed with onasemnogene abeparvovec and its absence in infants treated first with nusinersen may indicate a protective effect of co-therapy during a critical period of vulnerability to acute denervation.

ObjectivesThis study constructs a quantitative assessment model of the impact of the marine environment on the offensive mine-laying operational performance of unmanned underwater vehicles (UUV), and draws quantitative evaluation conclusions.MethodsFirst, the attributes of offensive mine-laying marine environment assessment are researched and the optimal model of the TOPSIS and set pair analysis (SPA) method are proposed on the basis of the combined weight of the fuzzy analytic hierarchy process (FAHP) and entropy weight method (EWM). The current situation of UUV deployment and its impact on the marine environment are then analyzed, and the risk indexes of the marine environment on the offensive mine-laying performance of UUVs are constructed with reference to the main evaluation indexes of the operational performance of traditional and unmanned offensive mine-laying. Finally, according to the existing research results on the impact of the marine environment on UUV systems, a quantitative model of the risk indicators is completed.ResultsThe feasibility of the method and model presented in this paper is verified through a simulation experiment that optimizes the marine environmental risk scheme of the determined UUV offensive mine-laying.conclusionsIt is more effective to disassemble the marine environmental risk indications in the offensive mine-laying stage, and more scientific to construct a quantitative model of marine environmental risk indications. The dynamic preference coefficient of the combined weight takes into account both the authority of decision-making and objectivity of data, and the influence of the same and opposite factors on scheme selection is considered. Finally, the feasibility of the algorithm is verified by the simulation results.

Abstract Blockade of immune checkpoints as a strategy of cancer cells to overcome the immune response has received ample attention in cancer research recently. In particular, expression of PD‐L1 by various cancer cells has become a paradigm in this respect. Delivery of PD‐L1 to its site of action occurs either by local diffusion, or else by transport via small extracellular vesicles (sEVs, commonly referred to as exosomes). Many steps of sEVs formation, their packaging with PD‐L1 and their release into the extracellular space have been studied in detail. The likely dependence of release on Ca2+‐signaling, however, has received little attention. This is surprising, since the intracellular Ca2+‐concentration is known as a prominent regulator of many secretory processes. Here, we report on the roles of three Ca2+‐dependent proteins in regulating release of PD‐L1‐containing sEVs, as well as on the growth of tumors in mouse models. We show that sEVs release in cancer cell lines is Ca2+‐dependent and the knockdown of the gene coding the Ca2+‐channel protein ORAI1 reduces Ca2+‐signals and release of sEVs. Consequently, the T cell response is reinvigorated and tumor progression in mouse models is retarded. Furthermore, analysis of protein expression patterns in samples from human cancer tissue shows that the ORAI1 gene is significantly upregulated. Such upregulation is identified as an unfavorable prognostic factor for survival of patients with non‐small‐cell lung cancer. We show that reduced Ca2+‐signaling after knockdown of ORAI1 gene also compromises the activity of melanophilin and Synaptotagmin‐like protein 2, two proteins, which are important for correct localization of secretory organelles within cancer cells and their transport to sites of exocytosis. Thus, the Ca2+‐channel ORAI1 and Ca2+‐dependent proteins of the secretion pathway emerge as important targets for understanding and manipulating immune checkpoint blockade by PD‐L1.

As ocean environment is complicated and varied, underwater vehicles (UVs) are facing great challenges in safe and precise navigation. Therefore, it is important to evaluate the underwater ocean environment safety for the UV navigation. To deal with the uncertain knowledge and various information in the safety assessment, we present an evaluation model based on the dynamic Bayesian network (DBN) theory. Firstly, characteristic indicators are extract from marine environment systems and discretized with Cloud model. Then, the DBN is constructed through structure learning and parameter learning based on Dempster-Shafer (DS) evidence theory. Finally, the dynamic evaluation and risk zoning of the navigation safety is realized based on Bayesian probabilistic reasoning. The DBN-based assessment model fully considers the uncertainty of influence relationships between marine environment and UV navigation, and effectively fuses expert knowledge and quantitative data for assessment modeling. The experimental results show the proposed model has high reliability and good value of application.

Abstract Background Long non-coding RNAs (lncRNAs) have been reported to play vital roles in diabetic nephropathy (DN). The aim of this study was to explore the function of mechanism of lncRNA KCNQ1 opposite strand/antisense transcript 1 (KCNQ1OT1) in DN. Methods DN cell models were established using high glucose (HG) treatment in human glomerular mesangial cells (HGMC) and human renal glomerular endothelial cells (HRGEC). The expression levels of KCNQ1OT1, microRNA-93-5p (miR-93-5p), and Rho associated coiled-coil containing protein kinase 2 (ROCK2) mRNA was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Cell Counting Kit-8 (CCK-8) assay and flow cytometry were used to detect cell proliferation and apoptosis, respectively. ROCK2 and apoptosis/fibrosis-related protein levels were examined by western blot. The predicted interaction between miR-93-5p and KCNQ1OT1 or ROCK2 was verified by dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay. Results KCNQ1OT1 was upregulated in DN patients and DN cell models. KCNQ1OT1 knockdown inhibited cell proliferation and fibrosis and induced apoptosis in DN cell models. MiR-93-5p was a direct target of KCNQ1OT1, and miR-93-5p inhibition restored the KCNQ1OT1 knockdown-mediated effects on cell proliferation, fibrosis and apoptosis in DN cell models. In addition, ROCK2 was identified as a target of miR-93-5p, and miR-93-5p overexpression suppressed cell proliferation and fibrosis and accelerated apoptosis by targeting ROCK2 in DN cell models. Moreover, KCNQ1OT1 regulated ROCK2 expression by binding to miR-93-5p. Conclusion KCNQ1OT1 knockdown inhibited cell proliferation and fibrosis and induced apoptosis in DN by regulating miR-93-5p/ROCK2 axis, providing potential value for the treatment of DN.

Objective: The mitochondrial nicotinamide adenine dinucleotide (NAD) kinase (MNADK) mediates de novo mitochondrial NADP biosynthesis by catalyzing the phosphorylation of NAD to yield NADP. In this study, we investigated the function and mechanistic basis by which MNADK regulates metabolic homeostasis. Methods: Generalized gene set analysis by aggregating human patient genomic databases, metabolic studies with genetically engineered animal models, mitochondrial bioenergetic analysis, as well as gain- and loss- of-function studies were performed to address the functions and mechanistic basis by which MNADK regulates energy metabolism and redox state associated with metabolic disease. Results: Human MNADK common gene variants or decreased expression of the gene are significantly associated with the occurrence of type-2 diabetes, non-alcoholic fatty liver disease (NAFLD), or hepatocellular carcinoma (HCC). Ablation of the MNADK gene in mice led to decreased fat oxidation, coincident with increased respiratory exchange ratio (RER) and decreased energy expenditure upon energy demand triggered by endurance exercise or fasting. On an atherogenic high-fat diet (HFD), MNADK-null mice exhibited hepatic insulin resistance and glucose intolerance, indicating a type-2 diabetes-like phenotype in the absence of MNADK. MNADK deficiency led to a decrease in mitochondrial NADP(H) but an increase in cellular reactive oxygen species (ROS) in mouse livers. Consistently, protein levels of the major metabolic regulators or enzymes were decreased, while their acetylation modifications were increased in the livers of MNADK-null mice. Feeding mice with a HFD caused S-nitrosylation (SNO) modification, a posttranslational modification that represses protein activities, on MNADK protein in the liver. Reconstitution of an SNO-resistant MNADK variant, MNADK-S193, into MNADK-null mice mitigated hepatic steatosis induced by HFD. Conclusion: MNADK, the only known mammalian mitochondrial NAD kinase, plays important roles in preserving energy homeostasis to mitigate the risk of metabolic disorders.

Abstract Despite newly available treatments for spinal muscular atrophy (SMA), novel circulating biomarkers are still critically necessary to track SMA progression and therapeutic response. To identify potential biomarkers, we performed whole‐blood RNA sequencing analysis in SMA type 1 subjects under 1 year old and age‐matched healthy controls. Our analysis revealed the Heat Shock Protein Family A Member 7 (HSPA7)/heat shock 70kDa protein 7 (HSP70B) as a novel candidate biomarker to track SMA progression early in life. Changes in circulating HSP70B protein levels were associated with changes in circulating neurofilament levels in SMA newborns and infants. Future studies will determine whether HSP70B levels respond to molecular therapies.

A novel one-dimensional malleable spin-crossover (SCO) complex {[Fe(MPEG-trz)3](BF4)2} has been successfully synthesized by molecular self-assembly between 4-amino-1,2,4-triazoles (MPEG-trz) grafted with a long flexible chain methoxy polyethylene glycol (MPEG) and metallic complex Fe(BF4)2•6H2O. The detailed structure information was illustrated by using FT-IR and 1H NMR measurements, while the physical behaviors of the malleable SCO complexes were systematically investigated by using magnetic susceptibility measurements using superconductivity quantum interference device (SQUID) and differential scanning calorimetry (DSC). This new metallopolymer exhibits a remarkable spin crossover transition behavior, between two spin quantum states (Fe2+ ions): high spin (HS) state (quintet state) and low spin (LS) state (singlet state), at a specific critical temperature with a slender hysteresis loop of 1 K. DFT computations revealed the partial rules of HOMO-LUMO energy levels and spin density distributions of different four-position substituted [Fe(1,2,4-triazole)3]2+ derivatives with different length of repeat units in polymer complexes. This can go a step further to depict the spin and magnetic transition behaviors of SCO polymer complexes. Furthermore, the coordination polymers possess an excellent processability due to an outstanding malleability, which can be easily shaped into a polymer film with spin magnetic switching properties.

Risk assessment and management of marine disasters are the prerequisite of ocean exploitation and utilization. Marine disaster assessment is a complicated system engineering with high non-linearity and uncertainty. To deal with the problem, Bayesian network (BN) has become a powerful model used for disaster assessment due to its capability of expressing complex relationships and reasoning with uncertainty. However, scarce data sets and case samples of marine disasters pose an obstacle to BN modeling, particularly for structure and parameter learning. In our research, we combine expert knowledge with small sample to propose a new BN-based assessment model. Expert knowledge is regularly expressed and quantitatively incorporated into BN learning with DS evidence theory. Then, the genetic algorithm is adopted to search the optimal network parameters. Comparative experiments show that the new model has a better assessment accuracy (91.03%) than BPNN (61.34%) and SVM (70.67%), especially with small samples. The proposed model achieves the risk assessment of marine disasters under the small sample condition, providing the technical support for marine disaster prevention and mitigation.

Vegetable intake is an essential element to maintain a healthy body of a human. However, research shows most people do not consume an adequate intake of vegetables per day. An ameliorate dietary assessment for vegetable intake is needed to increase awareness and assist users to improve their vegetable consumption. In this paper, we proposed a novel Quantized Deep Residual Convolutional Neural Network (DRCNN) model to ameliorate the fundamental task of dietary assessment. The proposed deep learning strategy integrating a deep residual architecture and a deep learning model, i.e. convolutional neural network, to apply for image-based dietary assessment. The proposed DRCNN model is then deeply fused with post-training quantization techniques to quantize the network weights of the proposed DRCNN model into low-bit fixed-point representations. Extensive experiments have been done to evaluate the proposed model. Results show that the proposed Quantized DRCNN model outperformed the state-of-the-arts, which include the conventional CNN models and also the machine learning models. Those experiments also indicate the effectiveness of the proposed Quantized DRCNN model. Finally, we further evaluate our model with cross-dataset validation to verify the generalization of the proposed model. The experimental result proves that the proposed Quantized DRCNN model is general enough to predict unseen cases and it works well on a wide range of food images.

Over the past decade, terrorism risk has become a prominent consideration in protecting the well-being of individuals and organizations. Consequence assessment of terrorist attack has become a research hotspot in security science. Aiming at the multi-source, interactional and uncertain factors in terrorism events, we introduce Information Flow (IF) to propose an improved weighted Bayesian Network (BN) with causality-based weights. Based on the weighted BN and Rand Forest (RF), we design a data-driven and expert knowledge-based consequence assessment model of terrorist attack. Firstly, RF is applied to filter effective evaluation indicators objectively. Then, IF is adopted to calculate weights of indicators and the weighted BN is built by structure learning and parameter learning. Finally, assessment experiments are conducted with terrorist attack events recorded in Global Terrorism Database. The results show that our proposed model overcomes the shortcomings of traditional quantitative risk assessment methods in verifiability and flexibility, and can reliably achieve quantitative assessment of terrorist attack risk under multi-source and uncertain information conditions.

Principal component analysis (PCA) and its variations are still the primary tool for feature extraction (FE) in the remote sensing community. This is unfortunate, as there has been a strong argument against using PCA for this purpose due to its inherent linear properties and uninformative principal components. Therefore, several critical issues still should be considered in the hyperspectral image classification when using PCA, among which: the large number of spectral channels and a small number of training samples; the nonlinearities of hyperspectral data; the small-sample issue. In order to alleviate these problems, this article employs a new information-theoretic FE method, the so-called kernel entropic component analysis (KECA), which can not only extract more nonlinear information but also can adapt to the limited-sample environment. A theorem of the pivoted Cholesky decomposition is also introduced to improve the efficiency of the KECA. The optimized version can more rapidly implement spectral-spatial features extraction, particularly for large-scale HSIs, while effectively maintaining the clustering performances of KECA. Experiments implemented on several real HSIs verify the effectiveness of the new method armed with a support vector machine classifier, in comparison with other PCA-based and state-of-the-art HSI classification algorithms. The code will also be made publicly available.

Purpose. Retinal ischemia–reperfusion injury (RIRI) is the basis of the pathology that leads to many retinal diseases and induces necroptosis and apoptosis. Tumor necrosis factor-α (TNF-α) is critically involved in necroptosis and apoptosis. Delta-opioid receptor (DOR) activation inhibits TNF-α release in our previous studies, it might prevent necroptosis and apoptosis by inhibiting the release of TNF-α. However, the role of TNF-α and DOR in necroptosis and apoptosis of retinal pigment epithelial (RPE) cells remains largely unknown. Here, we explored the mechanisms of TNF-α and DOR in necroptosis and apoptosis using an oxygen-glucose deprivation/reoxygenation (OGD/R) model of adult retinal pigment epithelial cell line-19 (ARPE19) cells. Materials and Methods. ARPE19 cells were exposed to OGD/R conditions to mimic RIRI in vitro. Cell viability was quantified using the Cell Counting Kit-8 (CCK-8) assay. Morphological changes were observed by inverted microscopy. TNF-α protein levels in cell lysates were measured by enzyme-linked immunosorbent assay (ELISA). The DOR agonist TAN-67 and antagonist naltrindole (NTI) were used to pretreat cells for 1 or 2 hours before OGD24/R36 administration. Calcein acetoxymethylester/propidium iodide (Calcein-AM/PI) and Terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) staining were used to detect necroptotic and apoptotic ARPE19 cells, respectively. The protein expression of DOR, p-RIP1 (RIP1), p-RIP3 (RIP3), p-MLKL (MLKL), and cleaved Caspase3 (Caspase3) was measured by western blotting. Results. OGD severely damaged ARPE19 cells. Prolonged reoxygenation significantly increased TNF-α level and decreased DOR expression in ARPE19 cells. Pretreatment with the DOR agonist TAN-67 (10 µM) significantly improved ARPE19 cell viability after OGD24/R36 by reducing the number of necroptotic and apoptotic cells. Furthermore, DOR activation significantly inhibited TNF-α release and suppressed the expression of proteins related to necroptosis and apoptosis, including p-RIP1, p-RIP3, p-MLKL, and cleaved Caspase3, after OGD24/R36. This effect was reversed by the DOR antagonist NTI. Conclusion. These results strongly suggest that DOR activation inhibits necroptosis and apoptosis by decreasing TNF-α release, leading to the prevention of OGD/R-induced injury in ARPE19 cells. This study provides an innovative idea for clinical treatment strategies for retinal damage and vision loss due to RIRI.

This paper elaborates on a digital simulation study on supernormal particle flow used to investigate and analyze the process of picking up jujube branches, which was a meaningful attempt to search for accurate and effective advanced numerical analogy methods in the agricultural field. In this paper, the meshless technology based on the element-free Galerkin method was used for the first time to present the effects of particle size, particle number and particle acting force on the movement of irregular particles, and the influence of the gear rotation speed, the feeding amount, and the jujube branch size on the movement behavior as well as the picking rate. It can describe not only the particles’ dynamic movement in the process of picking up jujube twigs, such as feeding, collision, throwing and rolling, but also the effect of the quality and shape caused by the particle size, which in turn affects the surface force of particles and interparticle acting force, thereby affecting the weight function in the analytical solution, the total feeding amount and the effect of the acting force resulting from the particles’ contact, roll and collision caused by gear rotation. The findings reveal that the digital simulation, based on the meshless Galerkin technology and Rocky software, is effective in dealing with issues related to supernormal particle flow. By eliminating the influence of geometric shapes on calculations, the method boasts an effective solution to the movement problems of irregularly shaped particles, which would be further applied in the agriculture field.

In the above article [1], the funding information has been amended to “This work is funded by Ministry of Higher Education Malaysia, Fundamental Research Grant Scheme [Grant Number: FRGS/1/2019/STG06/USM/02/5], for the project entitled “New Robust Adaptive Model for Coefficient of Variation in Infinite and Finite Horizon Processes.”

In order to solve the problem of low mechanization level of hairy vetch harvesting, a feeding device for an anti-winding hairy vetch harvester was designed. Firstly, the physical properties of hairy vetch stalk were studied. According to the mechanical properties of hairy vetch stalk, the key components of the feeding device were designed and analyzed, the structure and working principle of the feeding device were described. Secondly, the discrete element method was used to simulate and analyze the movement performance of the feeding device. On this basis, the ternary quadratic regression orthogonal rotation combination test was established with the vertical drum, the machine forward speed, and the spiral conveyor speed as the test factors and the stem loss rate as the test index. The simulation results showed that when the vertical drum was 1037.5 r/min, the machine forward speed was 2.76 m/s, the spiral conveyor speed was 348.88 r/min, and the straw loss rate was 2.38%, and the feeding device performs best at this time. Finally, the on-site performance test of the feeding device was carried out. The results showed that: all the test indicators met the requirements of the national standard; the actual cutting width was 1.66 m; the cutting stubble height was 6.41 mm; the over stubble loss rate was 0.45%; the missed cutting loss rate was 0.20%; and the stem loss rate was 3.00%, which verified the rationality of the design of the feeding device. In order to solve the problem of low mechanization level of hairy vetch, which easily becomes entangled in the working process, an anti-winding feeding device for hairy vetch harvesting was designed.

To solve the problem of difficult hazelnut harvesting in mountainous areas of Liaoning, China, a small pneumatic hazelnut harvesting machine was designed, which can realize negative pressure when picking up hazelnut mixtures and positive pressure when cleaning impurities. The key structure and parameters of the harvesting machine were determined by constructing a mechanical model of the whole machine and combining theoretical analysis and operational requirements. To explore the harvesting machine scavenging performance, Liaoning hazelnut No. 3 with a moisture content of 7.47% was used as the experimental object. Firstly, the terminal velocity of hazelnuts and fallen leaves was measured using a material suspension velocity test bench. Secondly, the gas–solid two-phase flow theory was applied comprehensively, and the motion state, particle distribution, and air flow field distribution of hazelnuts from the inlet to the outlet of the pneumatic conveying device were simulated and analyzed using the coupling of computational flow fluid dynamics method (CFD) and discrete element method (DEM) to evaluate the cleaning performance from the perspective of the net fruit rate of hazelnuts in the cleaning box. Finally, a Box–Behnken design experiment was conducted with the sieve plate angle, the distance of the sieve plate, and the air flow velocity as factors and the net fruit rate of hazelnuts as indicators to explore the influence of the three factors on the net fruit rate of hazelnuts. The parameter optimization module of Design-Expert software was used to obtain the optimal combination of parameters for the factors. The experimental results show that the test factors affecting the test index are the following: the air flow rate, the angle of the screen plate, and the distance of the screen plate. The best combination of parameters was an air flow velocity of 14.1 m∙s−1, a sieve plate angle of 55.7°, and a distance of the sieve plate of 33.2 mm. The net fruit rate of hazelnuts was 95.12%. The clearing performance was stable and can guarantee the requirements of hazelnut harvester operation, which provides a certain theoretical basis for the design of a nut harvester.

Cardiovascular disease is a major threat to global public health. Tissue plasminogen activator (TPA) is a serine protease that dissolves blood clots, which can also lead to excessive bleeding. Fibrinogen (FIBR), a glycoprotein, is converted by thrombin to fibrin and then to a fibrin-based blood clot. Both TPA and FIBR levels in the blood are associated with an increased risk of coronary heart disease, and the levels of the two factors are also positively correlated with total adipose tissue amounts. Visceral and subcutaneous adipose tissues (VAT and SAT) can contribute differently to whole-body metabolism. In this study, we sought to assess: (1) the strength of the correlation between the changing levels of the two factors and the changing amounts of VAT/SAT during exercise-induced weight loss, (2) whether there is any difference between the two types of adipose tissues in terms of the correlation, and (3) which factor, TPA or FIBR, is more sensitive to changes in adiposity? For this study, we analyzed the data from the diabetes prevention program (DPP), in which the participants were divided into three groups, with one group undergoing a lifestyle change that involved maintaining a minimum of 7% weight loss with physical activity. We found that the basal amounts of VAT and SAT were correlated with TPA and FIBR levels. However, following weight loss, adiposity changes were strongly correlated with the changing levels of TPA, but not FIBR, for both men and women. Therefore, TPA, but not FIBR, is sensitive to changes in adiposity. Furthermore, regarding TPA, weight loss sensitized its correlation with SAT, but not VAT. This study shows how adipose tissues distinctively affect TPA and FIBR levels, two factors associated with cardiovascular disease and ischemic stroke.

Elevated triglyceride (TG) and reduced high-density lipoprotein-cholesterol (HDL-C) plasma levels are risk factors for atherosclerosis and cardiovascular disease. Therefore, a drug that simultaneously reduces TG and increases HDL-C plasma levels has the potential to prevent and treat these diseases. Angiopoietin-like 3 (ANGPTL3) regulates plasma TG and HDL-C levels by inhibiting lipoprotein lipase (LPL) and endothelial lipase (EL), respectively. ANGPTL3 inhibition of LPL requires complex formation with ANGPTL8, which is not required for its inhibition of EL. Therefore, the entire pool of plasma ANGPTL3 can be classified as ANGPTL8-associated ANGPTL3 and ANGPTL8-free ANGPTL3, where the former inhibits LPL and the latter inhibits EL. ANGPTL8 antibodies or inhibitors that block its interactions with ANGPTL3 can disrupt or preclude the ANGPTL3-8 complex formation, resulting in fewer ANGPTL3-8 complexes (reduced LPL inhibition), but more free ANGPTL3 (enhanced EL inhibition). Therefore, ANGPTL8 antagonism increases LPL activity while decreasing EL activity, thus leading to reduced plasma TG while simultaneously increasing HDL-C levels. In humans, carriers of ANGPTL8 truncating variants consistently have lower TG but higher HDL-C levels, supporting this hypothesis.

A new dopant-free hole transporting material (HTM) 4′,4‴,4‴'',4‴''''-(adamantane-1,3,5,7-tetrayl)tetrakis(N,N-bis(4-methoxyphenyl)-[1,1′-biphenyl]-4-amine) (Ad-Ph-OMeTAD) (named FDY for short), which consists of a nonconjugated 3D bulky caged adamantane (Ad) as the core, triphenyl amines as side arms, and phenyl units as a linking bridge, is synthesized and applied in an inverted planar perovskite solar cell (PSC). As a result, the champion device with FDY as HTM yields an impressive power of conversion efficiency (PCE) of 18.69%, with JSC = 22.42 mA cm−2, VOC = 1.05 V, and FF = 79.31% under standard AM 1.5G illumination, which is ca. 20% higher than that of the device based on PEDOT:PSS (only 15.41%). Notably, the stability of PSC based on FDY is much better than that of devices based on PEDOT:PSS, and the corresponding devices retain over 90% of their initial PCEs after storing for 60 days in a nitrogen glove box without any encapsulation. Even when stored in an open air condition with 50–60% relative humidity for 188 h, the retained PCE is still over 81% of its initial one. All these results demonstrate that the new design strategy by combing the bulky and nonconjugated (aliphatic) adamantane unit as the core and triphenyl amines as side arms can efficiently develop highly efficient HTMs for PSCs, which is different from the traditional way based on conjugated backbones, and it may open a new way for scientists to design small-molecule HTMs for PSCs.

The navigability potential of the Northeast Passage has gradually emerged with the melting of Arctic sea ice. For the purpose of navigation safety in the Arctic area, a reliable daily sea ice concentration (SIC) prediction result is required. As the mature application of deep learning technique in short-term prediction of other fields (atmosphere, ocean, and hurricane, etc.), a new model was proposed for daily SIC prediction by selecting multiple factors, adopting gradient loss function (Grad-loss) and incorporating an improved predictive recurrent neural network (PredRNN++). Three control experiments are designed to test the impact of these three improvements for model performance with multiple indicators. Results show that the proposed model has best prediction skill in our experiments by taking physical process and local SIC variation into consideration, which can continuously predict daily SIC for up to 9 days.

This paper analyses the stochastic dynamics of the COVID-19 Case-Fatality Ratios (CFR) in three developing economies in East Asia: Indonesia, Malaysia, and the Philippines. The sample covers the daily frequency data from April 28, 2020, to June 29, 2021. For this purpose, we utilize two unit root tests, which consider one structural break and two structural breaks. The findings reveal that the CFR follows a unit root process in Indonesia and the Philippines. However, the CFR is stationary in Malaysia. This evidence indicates that the COVID-19 has a permanent effect in Indonesia and the Philippines but temporary in Malaysia. The paper also discusses the potential economic implications of these results for the post-COVID-19 era in the related developing economies.

Offshore wind energy has become a hot spot in new-energy development due to its abundant reserves, long power generation time, high unit capacity and low land occupation. In response to the current situation whereby wind energy, and natural and human factors have not been taken into account in the selection of sites for offshore wind-energy-resource development in the traditional “21st Century Maritime Silk Road” region, this paper intends to establish a new risk assessment framework that comprehensively considers the influence of wind resources, the natural environment, and the geopolitical and humanistic environment. The rationality of the new index system and weight determination methods are separately investigated. Some interesting results are obtained by comparing the new framework with traditional frameworks. The results show that the Persian Gulf, the Timor Sea in northern Australia, and the northern part of Sri Lanka in southern India are rich in wind-energy resources and have a low overall risk, making them recommended sites. In addition, unlike the results of previous studies, this paper does not recommend the Somali Sea as a priority area for wind-energy siting due to its high geographic humanity risks.

Abstract It is necessary to evaluate satellite sea surface salinity (SSS) L3 products prior to using them to analyze SSS variability. Instead of performing comparison analysis on the accuracy of products (e.g., Root Mean Square Deviation (RMSD)), two new evaluation methods, information entropy and local variance, are introduced to assess the performance of satellite SSS products in resolving SSS fronts in the tropical Pacific from a new perspective. The satellite SSS except for SMOS BEC has captured the zonal displacement of SSS fronts under the strong El Niño in 2015. It is effective to use entropy and local variance for the assessment of the capability of satellite SSS products, which can provide new sights for analyzing the variability and distributions of SSS. The spatial distribution of local variance identified the abnormal SSS of the satellite products on or near the islands and the result of SSS entropy is beneficial to the analysis of the mechanisms of the SSS variability. In general, the SMOS CATDS and SMAP_70 km product is recommended for scientific applications in the tropical Pacific.

Objective: The endoplasmic reticulum (ER)-resident E3 ligase HRD1 and its co-activator Sel1L are major components of ER-associated degradation (ERAD) machinery. Here, we investigated the molecular mechanism and functional significance underlying the circadian regulation of HRD1/Sel1L-mediated protein degradation program in hepatic energy metabolism. Methods: Genetically engineered animal models as well as gain- and loss-of-function studies were employed to address the circadian regulatory mechanism and functional significance. Gene expression, transcriptional activation, protein–protein interaction, and animal metabolic phenotyping analyses were performed to dissect the molecular network and metabolic pathways. Results: Hepatic HRD1 and Sel1L expression exhibits circadian rhythmicity that is controlled by the ER-tethered transcriptional activator CREBH, the nuclear receptor peroxisome proliferator-activated receptor α (PPARα), and the core clock oscillator BMAL1 in mouse livers. HRD1/Sel1L mediates polyubiquitination and degradation of the CREBH protein across the circadian cycle to modulate rhythmic expression of the genes encoding the rate-limiting enzymes or regulators in fatty acid (FA) oxidation, triglyceride (TG) lipolysis, lipophagy, and gluconeogenesis. HRD1 liver-specific knockout (LKO) mice displayed increased expression of the genes involved in lipid and glucose metabolism and impaired circadian profiles of circulating TG, FA, and glucose due to overproduction of CREBH. The circadian metabolic activities of HRD1 LKO mice were inversely correlated with those of CREBH KO mice. Suppressing CREBH overproduction in the livers of HRD1 LKO mice restored the diurnal levels of circulating TG and FA of HRD1 LKO mice. Conclusion: Our work revealed a key circadian-regulated molecular network through which the E3 ubiquitin ligase HRD1 and its co-activator Sel1L regulate hepatic circadian metabolism.

The maritime silk road policy of China brings opportunities to companies relating to overseas investment. Despite the investment potentials, the risks cannot be ignored and have still not been well assessed. Considering the fact that ICRG comprehensive risk has certain subjectivity, it is not completely applicable to China’s overseas investment. Therefore, based on the data of the China Statistical Yearbook and International Statistical Yearbook, a new indictor is adopted to better capture the Chinese investment risk and to make our prediction more objective. In order to acquire the ability to predict the investment risk in the future which is essential to stakeholders, machine learning techniques are applied by training the ICRG data of the previous year and Outward Foreign Direct Investment (OFDI) data of the next year together. Finally, a relative reliable link has been built between the OFDI indicator in the next year and the left ICRG indicators in the last year with both the best precision score of 86% and recall score of 86% (KNN method). Additionally, the KNN method has a better performance than the other algorithms even for high-level risk, which is more concerning for stakeholders. The selected model cannot only be used to predict an objective and reasonable investment risk level, but can also be used to provide investment risk predictions and suggestions for stakeholders.

Accurate and fast prediction of sea ice conditions is the foundation of safety guarantee for Arctic navigation. Aiming at the imperious demand of short-term prediction for sea ice, we develop a new data-driven prediction technique for the sea ice concentration (SIC) combined with causal analysis. Through the causal analysis based on kernel Granger causality (KGC) test, key environmental factors affecting SIC are selected. Then multiple popular machine learning (ML) algorithms, namely self-adaptive differential extreme learning machine (SaD-ELM), classification and regression tree (CART), random forest (RF) and support vector regression (SVR), are employed to predict daily SIC, respectively. The experimental results in the Barents-Kara (B-K) sea show: (1) compared with correlation analysis, the input variables of ML models screened out by causal analysis achieve better prediction; (2) when lead time is short (3 d); (3) RF has the best prediction accuracy and generalization ability but hugely time consuming, while SaD-ELM achieves more favorable performance when taking computational complexity into consideration. In summary, ML is applicable to short-term prediction of daily SIC, which develops a new way of sea ice prediction and provides technical support for Arctic navigation.

Abstract This study employs three remotely sensed Sea Surface Salinity products to diagnose the “inconsistent pairs” between the in situ observations of the Near Surface Salinity from delayed‐mode tropical moored buoys and Argo floats and the satellite salinity in the temporal range of April 2015–December 2018. By means of an adapted 3‐Sigma criterion and unanimous voting strategy, 11 (636) moored buoys (Argo floats) have at least one inconsistent observation pairs in their time series and 1 (41) have more than five. Besides, the time series of 1 (25) moored buoy (Argo floats) is diagnosed as inconsistent series due to the large bias of the whole series. Corresponding to a wide range of shifted observations, the continuous inconsistent values of moored buoy 8n38w can be flagged as bad observations. In terms of Argo, the combined analysis of time series, trajectories, profiles, and analyzed fields implies that the inconsistent pairs between Argo and satellite products are closely related to the mesoscale motions. The results suggest that sub‐footprint variability plays a dominant role in the inconsistent pairs of Argo, as most inconsistencies are characterized by the near‐surface mixed layer. Furthermore, the continuous positive inconsistencies of Argo 4901466 highlight the temporal under‐sampling of the existing satellite salinity products.

The coronavirus pandemic has highlighted the capitalist dysfunction showing that considering profit over people can be deadly. The study reveals the LME economies were more responsive toward the impact of the disease outbreaks as compared to the CME economies wherein the impact of the disease was moderated by the government involvement. This allows us to draw that the impact of the disease outbreaks can be moderated by increasing the involvement of the government authorities.

Due to its great biomechanical property, the polyethylene terephthalate (PET) artificial ligament has become one of the most promising allografts for anterior cruciate ligament (ACL) reconstruction. However, because of its chemical and biological inertness, PET is not a favored scaffold material for osteoblast growth, which promotes the ligament-bone healing. Meanwhile, in consideration of prevention of potential infection, the prophylactic injection of antibiotic was used as a post-operative standard procedure but also has the increasing risk of bacterial resistance. To face these two contradictions, in this article we coated a polydopamine (PDA) nano-layer on the PET ligament and used the coating as the adhesion interlayer to introduce nano-hydroxyapatite (nHA) and silver atoms to the surface of PET ligament. Because of the mild self-polymerization reaction of dopamine, the thermogravity analysis (TGA), Raman spectrum, and tensile test results show that the modification procedure have no negative effects on the chemical stability and mechanical properties of the PET. The results of NIH3T3 cell culture show that the PDA and nHA could effectively improve the biocompatibility of PET artificial ligament for fibroblast growth, and staphylococcus aureus antibacterial test results show that the Ag atom provided an antibacterial effect for PET ligament. As shown in this paper, the nano-PDA coating modification procedure could not only preserve the advantages of PET but also introduce new performance characteristics to PET, which opens the door for further functionalization of PET artificial ligament for its advanced development and application.