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High-velocity, large-coupling acoustic mode is the eternal pursuit of microacoustic research. Surface mode on piezoelectric films supported by an acoustic Bragg reflector (ABR) stack is one possible solution for realizing such a goal. However, some acoustic modes exhibit lower couplings in experiments than theoretically predicted, especially when metal layers are used as high-impedance layers in the ABR. The mechanism of this performance deterioration is still unclear. In this work, the electric field distribution in a piezoelectric plate mounted to an ABR stack is analyzed by considering the inductive current effect in conductive ABR layers. The field distribution required by one mode is found to be distorted by the effect, which results in a reduction in the excitation efficiency for the mode. We propose the use of another acoustic mode with a concentrated electric field in the top layers. As analyzed in comparison, the impact of the inductive effect on the mode is negligible. On an optimized crystal cut of lithium niobate, the selected mode exhibits 22.64% coupling and an acoustic velocity of 6006 m/s. [ABSTRACT FROM AUTHOR]

The relation between hypertension (HTN) and cognition has been reported inclusive results, which may be affected by disease duration. Our study aimed to examine the influence of HTN duration on cognition and its underlying white matter (WM) changes including macrostructural WM hyperintensities (WMH) and microstructural WM integrity. A total of 1218 patients aged ≥55 years with neuropsychological assessment and a subgroup of 233 people with imaging data were recruited and divided into 3 groups (short duration: <5 years, medium duration: 5–20 years, long duration: >20 years). We found that greater HTN duration was preferentially related to worse executive function (EF), processing speed (PS), and more severe WMH, which became more significant during long duration stage. The reductions in WM integrity were evident at the early stage especially in long-range association fibers and then scattered through the whole brain. Increasing WMH and decreasing integrity of specific tracts consistently undermined EF. Furthermore, free water imaging method greatly enhanced the sensitivity in detecting HTN-related WM alterations. These findings supported that the neurological damaging effects of HTN is cumulative and neuroimaging markers of WM at macro- and microstructural level underlie the progressive effect of HTN on cognition. [ABSTRACT FROM AUTHOR]

Three-phase four-wire grid-forming (GFM) inverters are promising to interface distributed energy resources into low-voltage networks. However, these inverters are prone to overcurrent under grid faults. Physically increasing the inverter current capacity is not cost-effective to cope with complicated fault conditions. In this article, an adaptive fault ride-through (FRT) scheme based on instantaneous saturators and virtual negative- and zero-sequence resistances is proposed. It features not only overcurrent limitation by modifying voltage references, but also seamless transition between normal and grid fault conditions. The proposed FRT scheme is first analyzed from different aspects, including the virtual sequence resistances, grid short-circuit ratio, fault types, and fault levels. The virtual sequence resistances are then designed to be adaptive to ensure high voltage quality at the healthy phase. The proposed FRT scheme is verified by MATLAB/Simulink simulations under asymmetrical faults. A laboratory platform with a grid-connected 3kW GFM inverter is further constructed to demonstrate its effectiveness (a video of the experimental results under three asymmetrical faults is attached). [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma(HCC) is one of the most common tumors in the world. Human insulin-like growth factor 2(IGF2) mRNA binding protein 2(IGF2BP2) plays an important role in the progression of hepatocellular carcinoma. Additionally, long non-coding RNA(lncRNA) has been confirmed as a key regulator of hepatocellular carcinoma occurrence. However, the function of TRPC7-AS1 has not been verified in hepatocellular carcinoma. The research results revealed that high IGF2BP2 expression was associated with a decreased survival rate in patients with hepatocellular carcinoma. Furthermore, IGF2BP2 knockdown inhibited and IGF2BP2 overexpression promoted the cell proliferation and invasion of hepatocellular carcinoma cells. The research illuminated that IGF2BP2 regulated the expression of TRPC7-AS1, and a correlation was observed between IGF2BP2 and TRPC7-AS1 expression. TRPC7-AS1 silencing repressed and its overexpression promoted the progression of hepatocellular carcinoma. After silencing or overexpressing TRPC7-AS1, the expression of the high-mobility group AT-hook 2 (HMGA2) gene decreased or increased, respectively. IGF2BP2 enhanced the expression of TRPC7-AS1 and thus affected the expression of HMGA2, thereby promoting hepatocellular carcinoma progression. Note: This picture was drawed through the website. https://www.figdraw.com/#/ [Display omitted] • IGF2BP2 promotes the progression of hepatocellular carcinoma and has a great prognostic value in hepatocellular carcinoma. • IGF2BP2 regulates the expression of lncRNA TRPC7-AS1 in hepatocellular carcinoma. • LncRNA TRPC7-AS1 could be considered as an oncogene in hepatocellular carcinoma. • HMGA2 is a promotive factor in hepatocellular carcinoma progression. • IGF2BP2-lncRNA TRPC7-AS1 and HMGA2 axis promotes hepatocellular carcinoma cell proliferation and invasion. [ABSTRACT FROM AUTHOR]

Testing a global hypothesis for a set of variables is a fundamental problem in statistics with a wide range of applications. A few well-known classical tests include the Hotelling's T2 test, the F-test, and the empirical Bayes based score test. These classical tests, however, are not robust to the signal strength and could have a substantial loss of power when signals are weak or moderate, a situation we commonly encounter in contemporary applications. In this article, we propose a minimax optimal ridge-type set test (MORST), a simple and generic method for testing a global hypothesis. The power of MORST is robust and considerably higher than that of the classical tests when the strength of signals is weak or moderate. In the meantime, MORST only requires a slight increase in computation compared to these existing tests, making it applicable to the analysis of massive genome-wide data. We also provide the generalizations of MORST that are parallel to the traditional Wald test and Rao's score test in asymptotic settings. Extensive simulations demonstrated the robust power of MORST and that the Type I error of MORST was well controlled. We applied MORST to the analysis of the whole-genome sequencing data from the Atherosclerosis Risk in Communities study, where MORST detected 20%–250% more signal regions than the classical tests. for this article are available online. [ABSTRACT FROM AUTHOR]

We consider in this article detection of signal regions associated with disease outcomes in whole genome association studies. Gene- or region-based methods have become increasingly popular in whole genome association analysis as a complementary approach to traditional individual variant analysis. However, these methods test for the association between an outcome and the genetic variants in a prespecified region, for example, a gene. In view of massive intergenic regions in whole genome sequencing (WGS) studies, we propose a computationally efficient quadratic scan (Q-SCAN) statistic based method to detect the existence and the locations of signal regions by scanning the genome continuously. The proposed method accounts for the correlation (linkage disequilibrium) among genetic variants, and allows for signal regions to have both causal and neutral variants, and the effects of signal variants to be in different directions. We study the asymptotic properties of the proposed Q-SCAN statistics. We derive an empirical threshold that controls for the family-wise error rate, and show that under regularity conditions the proposed method consistently selects the true signal regions. We perform simulation studies to evaluate the finite sample performance of the proposed method. Our simulation results show that the proposed procedure outperforms the existing methods, especially when signal regions have causal variants whose effects are in different directions, or are contaminated with neutral variants. We illustrate Q-SCAN by analyzing the WGS data from the Atherosclerosis Risk in Communities study. for this article are available online. [ABSTRACT FROM AUTHOR]

Background: The dose-response association between sedentary time and suicidal ideation and planning among adolescents is unclear. This study examined the association between leisure sedentary time and suicidal ideation, planning and attempts among adolescents in low- and middle-income countries (LMICs).Methods: We used the most recent data (2009-2016) from the Global School-based Student Health Survey (GSHS) in 54 LMICs. Leisure sedentary time and suicidal ideation, planning and attempts were assessed using a standardized questionnaire. A total of 146,345 young adolescents aged 12-15 years were included.Results: Among adolescents in the 54 LMICs, the prevalence of suicidal ideation was 14.8%, planning was 14.5%, and attempts was 13.0%. Compared with those who had less than 1 h/day of sedentary time, those who had 3, 4 h/day sedentary time were at higher odds ratio (OR) of suicidal ideation OR=1.21 (95% confidence interval (CI) =1.14-1.29), planning OR=1.15 (95%CI=1.07-1.22) and attempts OR=1.17 (95%CI=1.09-1.26), and those who had more than 8 h/day sedentary time were at OR=1.58 (95%CI=1.44-1.72), OR=1.44 (95%CI=1.31-1.58) and OR=1.27 (95%CI=1.16-1.40), respectively.Limitations: Suicidal behaviors and sedentary time were assessed by a self-reported questionnaire, which might be prone to recall bias.Conclusions: Higher amounts of leisure sedentary time are associated with suicidal ideation, planning and attempts among adolescents. Adolescents should spend less than 2 h/day of their sedentary time to reduce the likelihood of suicide. [ABSTRACT FROM AUTHOR]

[Display omitted] • BP-PEG could promote the accumulation and metabolism of P-Tau in the liver and kidneys. • BP-PEG could improve the symptoms of AD. • BP-PEG appear to be a safe and effective strategy for the peripheral clearance of P-Tau associated with AD. The onset of Alzheimer's disease (AD) is closely related to the accumulation of phosphorylated Tau proteins (P-Tau). However, due to the hindrance posed by the blood–brain barrier (BBB), current therapies targeting brain-derived P-Tau are largely ineffective. Interestingly, the clearance of peripheral P-Tau can eliminate P-Tau from the brain, enabling AD treatment and overcoming the challenges created by the BBB. Here, we prepared polyethylene glycol (PEG)-modified black phosphorus nanosheets (BP-PEG), which showed extended systemic circulation and acted as efficient "garbage trucks" for the removal of peripheral P-Tau. BP-PEG exhibited an exceptional capacity to bind to P-Tau in vitro. Further, in vivo biodistribution analysis demonstrated that BP-PEG accumulated in the liver and kidneys, which are the same organs that metabolize P-Tau. In vivo studies revealed that in okadaic acid (OA)-induced mouse models of AD, BP-PEG significantly reduced the levels of P-Tau in both the peripheral blood and the brain. Moreover, by promoting the clearance of peripheral P-Tau, BP-PEG improved several health indicators in mice, including cognitive function, glucose metabolism in the brain, inflammatory markers in the plasma and hippocampus, oxidative stress, and mitochondrial and myelin morphology. In conclusion, this study provides a new strategy for AD treatment, demonstrating the therapeutic value of removing P-Tau from the peripheral blood, and it also represents a novel attempt for the application of BP-PEG in AD therapy. [ABSTRACT FROM AUTHOR]

Senile osteoporosis—alternatively labeled as skeletal aging—encompasses age-induced bone deterioration and loss of bone microarchitecture. Recent studies have indicated a potential association between senile osteoporosis and chronic systemic inflammation, and pyroptosis in bone marrow-derived mesenchymal stem cells is speculated to contribute to bone loss and osteoporosis. Therefore, targeting pyroptosis in stem cells may be a potential therapeutic strategy for treating osteoporosis. Initially, we conducted bioinformatics analysis to screen the GEO databases to identify the key gene associated with pyroptosis in senile osteoporosis. Next, we analyzed the relationship between altered proteins and clinical data. In vitro experiments were then performed to explore whether the downregulation of PKM2 expression could inhibit pyroptosis. Additionally, an aging-related mouse model of osteoporosis was established to validate the efficacy of a PKM2 inhibitor in alleviating osteoporosis progression. We identified PKM2 as a key gene implicated in pyroptosis in senile osteoporosis patients through bioinformatics analysis. Further analyses of bone marrow and stem cells demonstrated significant PKM2 overexpression in senile osteoporosis patients. Silencing PKM2 expression inhibited pyroptosis in senile stem cells, of which the osteogenesis potential and angiogenic function were also primarily promoted. Moreover, the results in vivo demonstrated that administering PKM2 inhibitors suppressed pyroptosis in senile osteoporosis mice and mitigated senile osteoporosis progression. Our study uncovered PKM2, a key pyroptosis marker of bone marrow mesenchymal stem cells in senile osteoporosis. Shikonin, a PKM2 inhibitor, was then identified as a potential drug candidate for the treatment of osteoporosis. [Display omitted] • Our study identified a key pyroptosis marker, PKM2 in BMSCs of senile osteoporosis patients for the first time, which could be a novel diagnosis biomarker for SOP. • PKM2 was screened by bioinformatics and verified in aged mice and stem cells leading to bone loss through cellular pyroptosis via NLRP3/Caspase-1/GSDMD signaling pathway. • Shikonin, a potent PKM2 inhibitor, was identified for alleviating senile osteoporosis, which could provide a new direction for the prevention and treatment of other bone diseases. [ABSTRACT FROM AUTHOR]

Due to resistance and BCR-ABLT315I-mutated, CML remains a clinical challenge. It needs new potential therapeutic targets to overcome CML resistance related to BCR-ABL. Our research revealed that the deubiquitinating enzyme USP28 was highly expressed in BCR-ABL-dependent CML patients. Similarly, a high expression of USP28 was found in the K562 cell line, particularly in the imatinib-resistant strains. Notably, USP28 directly interacted with BCR-ABL. Furthermore, when BCR-ABL and its mutant BCR-ABLT315I were overexpressed in K562-IMR, they promoted the expression of IFITM3. However, when small molecule inhibitors targeting USP28 and small molecule degraders targeting BCR-ABL were combined, they significantly inhibited the expression of IFITM3. The experiments conducted on tumor-bearing animals revealed that co-treated mice showed a significant reduction in tumor size, effectively inhibiting the progression of CML tumors. In summary, USP28 promoted the proliferation and invasion of tumor cells in BCR-ABL-dependent CML by enhancing the expression of IFITM3. Moreover, imatinib resistance might be triggered by the activation of the USP28-BCR-ABL-IFITM3 pathway. Thus, the combined inhibition of USP28 and BCR-ABL could be a promising approach to overcome CML resistance dependent on BCR-ABL. [Display omitted] • DMP 11 is an innovatively synthesized protac compound targeting the degradation of the BCR-ABLfusion protein. • USP28 was correlated with the imatinib resistance in BCR-ABL-dependent CML. • Imatinib resistance may be triggered by the activation of the USP28-BCR-ABL-IFITM3 pathway. • Combined inhibition of USP28 and BCR-ABL may provide new potential therapeutic strategies to overcome CML resistance dependent on BCR-ABL. [ABSTRACT FROM AUTHOR]

• A novel gated graph neural network is proposed for water quality prediction. • Masking greatly enhances prediction accuracy, addressing sensor data limitation. • The model exhibits robust node-level prediction, enabling network soft sensing. • Sensor location plays a bigger role than quantity in improving prediction accuracy. Ensuring the safety and reliability of drinking water supply requires accurate prediction of water quality in water distribution networks (WDNs). However, existing hydraulic model-based approaches for system state prediction face challenges in model calibration with limited sensor data and intensive computing requirements, while current machine learning models are lack of capacity to predict the system states at sites that are not monitored or included in model training. To address these gaps, this study proposes a novel gated graph neural network (GGNN) model for real-time water quality prediction in WDNs. The GGNN model integrates hydraulic flow directions and water quality data to represent the topology and system dynamics, and employs a masking operation for training to enhance prediction accuracy. Evaluation results from a real-world WDN demonstrate that the GGNN model is capable to achieve accurate water quality prediction across the entire WDN. Despite being trained with water quality data from a limited number of sensor sites, the model can achieve high predictive accuracies (Mean Absolute Error = 0.07 mg L−1 and Mean Absolute Percentage Error = 10.0 %) across the entire network including those unmonitored sites. Furthermore, water quality-based sensor placement significantly improves predictive accuracy, emphasizing the importance of careful sensor location selection. This research advances water quality prediction in WDNs by offering a practical and effective machine learning solution to address challenges related to limited sensor data and network complexity. This study provides a first step towards developing machine learning models to replace hydraulic models in WDN modelling. [Display omitted] [ABSTRACT FROM AUTHOR]

Contamination events in water distribution networks (WDN) pose significant threats to water supply and public health. Rapid and accurate contamination source identification (CSI) can facilitate the development of remedial measures to reduce impacts. Though many machine learning (ML) methods have been proposed for fast detection, there is a critical need for approaches capturing complex spatial dynamics in WDNs to enhance prediction accuracy. This study proposes a gated graph neural network (GGNN) for CSI in the WDN, incorporating both spatiotemporal water quality data and flow directionality between network nodes. Evaluated across various contamination scenarios, the GGNN demonstrates high prediction accuracy even with limited sensor coverage. Notably, directional connections significantly enhance the GGNN CSI accuracy, underscoring the importance of network topology and flow dynamics in ML-based WDN CSI approaches. Specifically, the method achieves a 92.27% accuracy in narrowing the contamination source to 5 points using just 2 h of sensor data. The GGNN showcases resilience under model and measurement uncertainties, reaffirming its potential for real-time implementation in practice. Moreover, our findings highlight the impact of sensor sampling frequency and measurement accuracy on CSI accuracy, offering practical insights for ML methods in water network applications. • A gated graph neural network is proposed for contamination source identification. • The new model utilizes network topology and flow directions for enhanced performance. • Improved sensor sampling frequency and measurement accuracy boost model performance. • Model exhibits resilience to demand and measurement uncertainties. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is a common malignancy worldwide. Radiofrequency ablation (RFA) is applied for treating HCC; however, insufficient RFA promotes HCC development and accelerates HCC recurrence. Therefore, the molecular functions underlying this process have gradually attracted attention. Objective: We sought to examine whether GAS6-AS2 (also known as GAS6-DT: growth arrest specific 6 divergent transcript) played a role in the development of HCC after insufficient RFA. Materials and Methods: The in vitro model was established by heating Huh7 and MHCC97 cells in water bath at 47°C, named as Huh7-H and MHCC97-H. Colony formation, transwell and Western blot assays were conducted for functional analysis. Results:GAS6-AS2 was upregulated in Huh7-H and MHCC97-H cells relative to Huh7 and MHCC97 cells. GAS6-AS2 deficiency hampered cell proliferation, migration, invasion, epithelial-mesenchymal transition, and stemness in Huh7-H and MHCC97-H cells. Moreover, microRNA-3619-5p (miR-3619-5p) combined with GAS6-AS2 and ARL2 (ADP ribosylation factor-like GTPase 2) was the target gene of miR-3619-5p. GAS6-AS2 served as the competing endogenous RNA (ceRNA) of ARL2 via absorbing miR-3619-5p. Conclusion: On the whole, present study uncovered a novel ceRNA mechanism of GAS6-AS2/miR-3619-5p/ARL2 in HCC after insufficient RFA, which might shed a new insight into treatment of HCC after insufficient RFA. [ABSTRACT FROM AUTHOR]

Unlike a synchronous generator that could withstand a large overcurrent, an inverter-based distributed generation (DG) has low thermal inertia, and the inverter is likely damaged by overcurrents during grid faults. In this article, a new strategy, namely positive- and negative-sequence limiting with stability enhanced P-f droop control (PNSL-SEPFC), is proposed to limit the output currents and active power of droop-controlled inverters in islanded microgrids. This strategy is easy to implement in the inverter controller and does not require any fault detection. Inverter stability is analyzed mathematically, which gives guidelines to design the parameters of the PNSL-SEPFC strategy. PSCAD/EMTDC simulation based on a four-DG microgrid shows that the proposed PNSL-SEPFC can limit inverter output currents and powers with better performance under both symmetrical and asymmetrical faults. Furthermore, hardware experiments demonstrate that the proposed PNSL-SEPFC can ensure the inverters riding through grid faults safely and stably. (A video of experimental waveforms is attached.) [ABSTRACT FROM AUTHOR]

In microgrids, intermittency of renewable energy sources (RES) and uncertain state-of-charge (SoC) of energy storage systems (ESS) can cause power deficiency to some distributed generation units (DGs). In this case, DGs with power deficiency may not meet the power demand, resulting in voltage collapse or frequency divergence. Unfortunately, this is seldom considered in inverter control design in existing literature. Thus, in-depth investigation into the microgrid performance under renewable energy resource fluctuations and appropriate control methods are urgently needed. In this article, an adaptive droop and adaptive virtual impedance control strategy is proposed. Unlike conventional droop control where the droop coefficients are fixed by assuming the DGs can always meet the load demand, the droop coefficients here are adjusted according to actual solar PV power output. In this way, proper power sharing among DGs can be achieved under renewable energy variation. Furthermore, the impact of varying DG capacities on system stability is mathematically investigated. An adaptive virtual impedance is then incorporated into the adaptive droop method to deal with the system instability caused by renewable energy variations. The proposed strategy is analyzed theoretically and validated in MATLAB/Simulink simulation and laboratory experiments. The results demonstrate the advantages of the proposed method over conventional approaches under various scenarios. [ABSTRACT FROM AUTHOR]

This study aims to investigate tribological properties in a siliconized graphite (СГ-П-0.5) and hierarchically hybrid SiC/C composites at the load ranging from 10-40 ​N under dry air/water lubrication conditions. A feasible liquid silicon infiltration (LSI) was used to fabricate the SiC/C composites. Morphology and phase identification of two materials were characterized and analyzed by scanning electron microscope (SEM) and energy dispersive spectrometer (EDS). An image feature extraction was used to post-process the data of wear test, further to gain the wear properties of the samples. The results demonstrated that a lower coefficient of friction (COF) and wear rate can be achieved in the LSI SiC composites than that in the sample of СГ-П-0.5. Both COF decreased under water-lubricated conditions, compared with that under the dry air lubrication. The excellent tribological properties in two materials can be due mainly to the microstructure of the СГ-П-0.5 sample, showing much more graphite and Si dispersed on the matrix. The СГ-П-0.5 sample indicated the typical oxidative wear mechanism, whereas, the sample of LSI SiC demonstrated the combined oxidative and fatigue wear. This finding can provide a promising new siliconized graphite materials for ceramic rolling bearings. [Display omitted] • Siliconized graphite was effectively prepared by LSI. • A boundary film formed on the SiC surface under water lubricated friction. • Image feature extraction was used to analyze the BSD images. [ABSTRACT FROM AUTHOR]

Whole-genome sequencing (WGS) studies are being widely conducted in order to identify rare variants associated with human diseases and disease-related traits. Classical single-marker association analyses for rare variants have limited power, and variant-set-based analyses are commonly used by researchers for analyzing rare variants. However, existing variant-set-based approaches need to pre-specify genetic regions for analysis; hence, they are not directly applicable to WGS data because of the large number of intergenic and intron regions that consist of a massive number of non-coding variants. The commonly used sliding-window method requires the pre-specification of fixed window sizes, which are often unknown as a priori , are difficult to specify in practice, and are subject to limitations given that the sizes of genetic-association regions are likely to vary across the genome and phenotypes. We propose a computationally efficient and dynamic scan-statistic method (Scan the Genome [SCANG]) for analyzing WGS data; this method flexibly detects the sizes and the locations of rare-variant association regions without the need to specify a prior, fixed window size. The proposed method controls for the genome-wise type I error rate and accounts for the linkage disequilibrium among genetic variants. It allows the detected sizes of rare-variant association regions to vary across the genome. Through extensive simulated studies that consider a wide variety of scenarios, we show that SCANG substantially outperforms several alternative methods for detecting rare-variant-associations while controlling for the genome-wise type I error rates. We illustrate SCANG by analyzing the WGS lipids data from the Atherosclerosis Risk in Communities (ARIC) study. [ABSTRACT FROM AUTHOR]

Highlights • G20Mn5QT's fatigue crack behaviors were investigated. • A simulation model with using two-parameter driving force and damage accumulation. • It was capable to consider the effects of mean-stress and load history. • There was a good simulation results compared to experimental results. • G20Mn5QT's unified equation of fatigue crack growth was given out. Abstract This paper performs a research on fatigue crack growth in G20Mn5QT cast steel using the experimental method and a semi-empirical fatigue crack growth model. The model combines the two-parameter driving force and fatigue damage accumulation. It would take into account the effects of mean stress and load history, and the fatigue crack growth rate curve would only be influenced by the sort of material. Comparing to the experimental results, the proposed model has good simulation results. A unified fatigue crack growth rate equation for G20Mn5QT cast steel has been given out, which is more convenient for engineering applications. [ABSTRACT FROM AUTHOR]

Most frictional systems are composed of components that are in sliding contact. Thus they have natural contact interfaces on which normal contact forces and tangential friction forces are acting. These real systems are complicated and friction brings further complexity, which presents a challenge to their dynamic analysis and control. In this paper, a model reduction strategy for complicated frictional systems is put forward based on the idea of mode synthesis, and its applications and experimental validation are presented. Firstly, the accuracy of the reduction method and the feasibility of the reduced model in stability analysis are verified on a theoretical multi-degree-of-freedom frictional system. Then, a tribometer in the form of a pad-on-disc test rig is designed and built and its corresponding detailed finite element (FE) model is constructed. A specific reduction strategy for this real friction system which involves direct contact at the pad-disc interface, is proposed. It is found that the reduced model with 80 modes of each of the two substructures of the system can already correctly predict the mode-coupling instability of the full FE model (which has over 900,000 degrees of freedom) of the real system, and unstable frequencies that are fairly close to the unstable frequencies of the FE full model computed by Abaqus CEA and the vibration frequencies measured in the test on the tribometer, which demonstrates the efficiency and accuracy of the model reduction strategy for dynamic analysis of real friction systems. Its computational efficiency would be even much greater when applied to nonlinear dynamic analysis of real friction systems. Model reduction for friction-induced vibration validated by experiments has not been reported in the literature. [ABSTRACT FROM AUTHOR]

Accumulating evidence indicates that exosomes help to regulate bone homeostasis. The roles of bone-derived exosomes have been well-described; however, recent studies have shown that some non-bone-derived exosomes have better bone targeting ability than bone-derived exosomes and that their performance as a drug delivery vehicle for regulating bone homeostasis may be better than that of bone-derived exosomes, and the sources of non-bone-derived exosomes are more extensive and can thus be better for clinical needs. Here, we sort non-bone-derived exosomes and describe their composition and biogenesis. Their roles and specific mechanisms in bone homeostasis and bone-related diseases are also discussed. Furthermore, we reveal obstacles to current research and future challenges in the practical application of exosomes, and we provide potential strategies for more effective application of exosomes for the regulation of bone homeostasis and the treatment of bone-related diseases. 67yBviMJcTRjcZnyRK6kR4 Video Abstract [ABSTRACT FROM AUTHOR]

• Simulation ability of dynamic response to the complete AMB-rotor drop process;. • Theoretical analysis of dry whirl and dry whip of a vertical rotor;. • Simulation model and test rig together verify the theoretical validity;. • Parametric study of the factors influencing the natural whirl speed. A horizontal rotor is usually the research subject of rotor drop failure in active magnetic bearing (AMB) test rigs. However, research shows, that a vertical rotor drop failure is not sufficiently understood at present. The experiments in other research studies show that the vertical rotor dynamic response is not simple whirl behavior after dropping on the touchdown bearing (TDB), which concludes dry whirl and dry whip processes, where the former is synchronous forward whirl, and the latter is subsynchronous forward whirl. To predict the dynamic response of a vertical rotor drop failure, theoretical research based on a rotor-TDB model system is developed in this paper, and the effectiveness of this model is validated by an AMB-TDB rotor experiment. The conclusion is that the natural whirl speed and the resulting critical speed clearly distinguish two states of forward whirl motion. When the rotation speed is less than the critical speed, the rotor is in a dry whirl state; otherwise, it behaves as in a dry whip. The rotor unbalance is introduced in the model, which explains the change in the whirl speed. Moreover, the influencing factors on the natural whirl speed are analyzed in depth. The result shows that parameters of the TDB, such as the friction coefficient and protective clearance, and the rotor unbalance have significant effects. [ABSTRACT FROM AUTHOR]

The effect of estrogen receptors on diabetes-induced vascular dysfunction is critical, but ambiguous. Individuals with diabetic vascular disease may require estrogen receptor-specific targeted therapy in the future. The G protein-coupled estrogen receptor (GPER) has beneficial effects on vascular function. However, its fundamental mechanisms are unclear. The RhoA/Rho-kinase pathway contributes to diabetic vascular complications, whereas estrogen can suppress Rho-kinase function. Thus, we assumed that GPER inhibits diabetes-mediated RhoA activation to prevent vascular dysfunction. We further investigated the underlying mechanisms involved in this process. Vascular endothelial cells and ex vivo cultured ovariectomized (OVX) C57BL/6 mouse aortae were treated with high glucose (HG) alone or in combination with GPER agonist (G1). G1 treatment was also administered to OVX db/db mice for 8 weeks. An ex-vivo isovolumic myograph was used to analyze the endothelium-dependent vasodilation and endothelium-independent contraction of mouse aortae. Apoptosis, oxidative stress, and inflammation were attenuated in G1-pretreated vascular endothelial cells. G1 significantly decreased the phosphorylation of inhibitory endothelial nitric oxide (NO) synthase residue threonine 495 (eNOS Thr495), inhibited RhoA expression, and increased NO production. Additionally, G1 rescued the impaired endothelium-dependent relaxation and inhibited RhoA activation in the thoracic aorta of OVX db/db mice and ex-vivo cultured OVX C57BL/6 mouse aortae treated with HG. Estrogens acting via GPER could protect vascular endothelium, and GPER activation might elicit ERα-independent effect to inhibit RhoA/Rho-kinase pathway. Additionally, GPER activation might reduce vascular smooth muscle contraction by inhibiting RhoA activation. Thus, the results of the present study suggest a new therapeutic paradigm for end-stage vascular dysfunction by inhibiting RhoA/Rho-kinase pathway via GPER activation. [ABSTRACT FROM AUTHOR]

In this paper, we propose variable selection and estimation in generalized linear models using the seamless $L_0$ (SELO) penalized likelihood approach. The SELO penalty is a smooth function that very closely resembles the discontinuous $L_0$ penalty. We develop an efficient algorithm to fit the model, and show that the SELO-GLM procedure has the oracle property in the presence of a diverging number of variables. We propose a Bayesian information criterion (BIC) to select the tuning parameter. We show that under some regularity conditions, the proposed SELO-GLM/BIC procedure consistently selects the true model. We perform simulation studies to evaluate the finite sample performance of the proposed methods. Our simulation studies show that the proposed SELO-GLM procedure has a better finite sample performance than several existing methods, especially when the number of variables is large and the signals are weak. We apply the SELO-GLM to analyze a breast cancer genetic dataset to identify the SNPs that are associated with breast cancer risk. The Canadian Journal of Statistics 40: 745-769; 2012 © 2012 Statistical Society of Canada [ABSTRACT FROM AUTHOR]

• Studied instability of 3 models of friction-induced vibration due to mode-coupling. • Discovered the intriguing and counter-intuitive roles of damping on stability. • Revealed drop of stability boundary caused by nonproportional damping. • Analysed damping effects in one direction or a part of the system on stability. • Found unsual and beneficial effects of proportional damping. This study addresses a fundamental problem of linear friction-induced vibration (FiV), the intriguing role of damping on the instability of FiV in the form of mode-coupling. Two well-known classic 2-degree-of-freedom (DoF) slider-belt models are revisited, and a 4-DoF slider-belt model considering different damping configurations in the slider and the belt is investigated. Since proportional damping is very rare in reality, non-proportional damping is given much attention in this paper. Firstly, the analytical solutions of bifurcation boundary of the critical coefficients of friction of the classic 2-DoF models are derived, which show the subtle role of damping clearly and theoretically explain and clear misunderstandings and confusions on the phenomenon about the drop of the stability boundary from that of the undamped system caused by adding non-proportional damping. Secondly, a further increase of non-proportional damping is found to improve the stability and even bring higher degree of stability than increasing proportional damping (which is a new finding). Thirdly, the influences of the different damping distributions among the system components on the stability of the 4-DoF slider-belt model are explored. The evolution of the bifurcation boundary indicates the importance of the ratio of the horizontal to the vertical damping in the slider and in the belt. For some non-proportional damping values, the bifurcation boundary fluctuates, which could exhibit local optimal values of the ratio of damping in different directions of a system component and can be exploited in design against FiV. These findings are valid for general linear second-order dynamic systems with an asymmetric stiffness matrix. [ABSTRACT FROM AUTHOR]

To scavenge energy from imperceptible vibrations, this paper investigates the broadband response and output performance of a microvibrational piezoelectric energy harvesting system with mechanical stopper. The energy harvesting system comprises a cantilever beam made of piezoelectric material, which is affixed with a coil at its unbound end and a mechanical stopper. The coil is placed in a magnetic field to provide an ultra‐low level excitation. The electromechanical model is derived according to force integration method (FIM) and Hertz's contact theory, and numerical simulations are undertaken to evaluate the influence of the excitation level, and the gap on the performance. For the linear counterpart without stopper, experimental results indicate the system generates a peak power of 24.12 μW with matched resistance under excitation with a level of 0.003 N and a frequency of 200.3 Hz. When a polydimethylsiloxane (PDMS) stopper is introduced, the vibration of the piezoelectric beam exhibits an obvious nonlinearity with an amplitude of micron scale. Increasing the excitation level and decreasing the gap could efficiently broaden the response bandwidth. Experimental results demonstrate that a copper stopper with larger elastic modulus results in a wider response frequency range, and the half‐power bandwidth could reach 37.1 Hz under excitation with a level of 0.003 N. [ABSTRACT FROM AUTHOR]

• A rolling magnetic spring energy harvester is proposed for handshaking. • The influence of the coil's position on output performance is investigated. • Excitation with a level of 0.3 g witnesses a half-power bandwidth of 1.61 Hz. • Maximum average power of 2.22 mW is achieved under handshaking excitation. • Handshaking excitation in 5 s could enable a watch to operate for 1100 s. Aiming at the random and low-frequency characteristics of human motion, a hand-held rolling magnetic-spring energy harvester is proposed to scavenge energy from handshaking. The harvester applies the rolling movement of a magnetically suspended magnet and possesses the merit of low damping. The dynamic model is established and the open-circuit voltages are predicted by combining Faraday's law of electromagnetic induction and finite element analysis. By calculating magnetic flux through coils, the effect of the coil's position on energy harvesting efficiency is studied through numerical and experimental approaches. Experimental results under harmonic excitations indicate that the coil positioned directly below the stable equilibrium position of the moving magnet has the best output capability, and a maximum open-circuit voltage of 1.33 V and a half-power bandwidth of 1.61 Hz is achieved at 0.3 g. Under handshaking excitation, an instantaneous peak power of 20.15 mW is achieved, along with a maximum average power of 2.22 mW. The corresponding volume and mass power densities are respectively 26.04 μW/cm3 and 23.28 μW/g. Furthermore, handshaking excitation in 5 s to charge a capacitor of 470 μF could enable the watch, time display, timer, and hygrothermograph to operate for 1100 s, 513 s, 86 s, and 35 s respectively, demonstrating the brilliant application foreground of the proposed harvester. [ABSTRACT FROM AUTHOR]

In this study, we employed the principle of Relative Mode Transfer Method (RMTM) to establish a model for a single pendulum subjected to sudden changes in its length. An experimental platform for image processing was constructed to accurately track the position of a moving ball, enabling experimental verification of the pendulum's motion under specific operating conditions. The experimental data demonstrated excellent agreement with simulated numerical results, validating the effectiveness of the proposed methodology. Furthermore, we performed simulations of a double obstacle pendulum system, investigating the effects of different parameters, including obstacle pin positions, quantities, and initial release angles, on the pendulum's motion through numerical simulations. This research provides novel insights into addressing the challenges associated with abrupt and continuous changes in pendulum length. [ABSTRACT FROM AUTHOR]

Carbonate rock chemical weathering carbon sinks reduce the rate of increase of the atmospheric CO2 concentration and global warming. However, uncertainty still exists in the estimation results of carbonate rock chemical weathering carbon sink fluxes (CCSF), and the contributions of climate change and ecological restoration to the CCSF are not clear. To this end, we compiled published site data on ion concentrations in different watersheds in China and used a classical thermodynamic dissolution model to reassess the potential and spatial and temporal patterns of the CCSF in China from 1991 to 2020. We quantified the contributions of temperature (MAT), precipitation (MAP), evapotranspiration (ET), soil water (SM), and the normalized difference vegetation index (NDVI) to the CCSF. The results revealed that (1) China's CCSF was 22.76 t CO2 km−2 yr−1, which was higher than the global average (15.771CO2 km−2 yr−1). The total carbonate rock chemical weathering carbon sink (CCS) was 4772.67×104 t CO2, contributing 14.91% of the global CCS through a carbonate rock area of 252.98×104 km−2. (2) China's CCSF decreased gradually from southeast to northwest, with values of 33.14, 12.93, and 7.27 t CO2 km−2 yr−1 in the southern karst, Qinghai-Tibetan karst, and northern karst regions, respectively. (3) The overall CCSF in China exhibited an increasing trend from 1991 to 2020, with a rate of increase of 0.16 t CO2 km−2 yr−1. (4) The contributions of the MAP, MAT, ET, SM, and NDVI to the CCSF were 63.3%, 3.02%, 27.5%, 3.1%, and 3.05%, respectively. Among them, the increase in precipitation was the main contributor to the increase in the CCSF in China over the last 30 years, while the enhancement of ET offset part of the positive contribution of the increase in precipitation to the CCSF. In conclusion, the results of this study provide a systematic quantification of the magnitude, the patterns, and the influencing factors of CCS over a long time series in China. The results are of great significance and provide a reference for the diagnosis and gap analysis of the national and global carbon neutrality capacities. [ABSTRACT FROM AUTHOR]

• A novel automated approach was proposed for localizing seizure onset zone (SOZ) by cortico-cortical evoked potentials (CCEPs). • Cortical hyperexcitability at the stim-SOZ/rec-SOZ sites was increased in patients with hippocampus sclerosis compared to those with focal cortical dysplasia IIa. • The patients with complex partial seizures have more distinctive characteristics of CCEP than those with generalized tonic-clonic seizures in areas with different epileptogenicity. We aimed to develop a new approach for identifying the localization of the seizure onset zone (SOZ) based on corticocortical evoked potentials (CCEPs) and to compare the connectivity patterns in patients with different clinical phenotypes. Fifty patients who underwent stereoelectroencephalography and CCEP procedures were included. Logistic regression was used in the model, and six CCEP metrics were input as features: root mean square of the first peak (N1RMS) and second peak (N2RMS), peak latency, onset latency, width duration, and area. The area under the curve (AUC) for localizing the SOZ ranged from 0.88 to 0.93. The N1RMS values in the hippocampus sclerosis (HS) group were greater than that of the focal cortical dysplasia (FCD) IIa group (p < 0.001), independent of the distance between the recorded and stimulated sites. The sensitivity of localization was higher in the seizure-free group than in the non-seizure-free group (p = 0.036). This new method can be used to predict the SOZ localization in various focal epilepsy phenotypes. This study proposed a machine-learning approach for localizing the SOZ. Moreover, we examined how clinical phenotypes impact large-scale abnormality of the epileptogenic networks. [ABSTRACT FROM AUTHOR]

• The relationship between TLR2 polymorphism and TB susceptibility is not as close as we thought before. • Screening more gene mutations to provide new ideas for prevention and treatment of TB. • TLR2 rs5743708 polymorphism exhibits a significant association with a higher tuberculosis risk. • The polymorphism of TLR2 gene was systematically reviewed for the first time. Toll-like receptor 2 (TLR2) is a crucial factor in the development of tuberculosis. However, no studies have explored the association between TLR2 polymorphisms and tuberculosis susceptibility. This study aimed to explore the correlation between tuberculosis susceptibility and TLR2 polymorphisms (rs3804099, rs3804100, rs1898830, rs5743708, rs121917864, and (-196-174) del). All relevant online databases including PubMed, CNKI, WANFANG DATA, and METSTR-FMRS were systematically searched. STATA17.0 (Stata Corp LP, College Station, Texas, USA) was used. A total of 37 studies, covering six polymorphisms and comprising 9,474 cases and 10,295 controls, were included in this analysis. rs3804099(C vs T: OR = 1.00, 95 % CI: 0.93–1.08, CC + TC vs TT: OR = 1.04, 95 % CI: 0.98–1.10), rs3804100 (C vs T: OR = 1.19, 95 % CI: 0.93–1.07, CC + TC vs TT: OR = 0.97, 95 % CI: 0.89–1.06), rs1898830(G vs A: OR = 0.90, 95 % CI: 0.81–1.00, GG + AG vs AA: OR = 0.87, 95 % CI: 0.67–1.12), (-196 ∼174) del polymorphism (Del vs Ins: OR = 0.93,95 % CI: 0.76–1.14, DD + DI vs II: OR = 0.92,95 % CI: 0.72–1.17). This study indicated that only the TLR2 rs5743708 polymorphism exhibited a significant association with a higher tuberculosis risk, while TLR2 rs3804099, rs3804100, rs1898830, rs121917864, and (-196-174) del polymorphisms were not associated with tuberculosis susceptibility. [ABSTRACT FROM AUTHOR]

This paper investigates the profile of COVID-19 cases in Hong Kong, highlighting the unique age structure of confirmed cases compared to other territories. While the majority of cases in most territories around the world have fitted an older age profile, our analysis shows that positive cases in Hong Kong have been concentrated among younger age groups, with the largest incidence of cases reported in the 15–24 age group. This is despite the population's rapidly aging structure and extremely high levels of population density. Using detailed case data from Hong Kong's Centre for Health Department and Immigration Department, we analyze the sex and age distribution of the confirmed cases along with their recent travel histories and immigration flows for the period January to April 2020. Our analysis highlights Hong Kong's high proportion of imported cases and large overseas student population in developing COVID-19 hotspot areas such as the United Kingdom. Combined with community action and targeted and aggressive early policy measures taken to contain the virus, these factors may have contributed to the uniquely younger age structure of COVID-19 cases in the city. Consequently, this young profile of confirmed cases may have prevented fatalities in the territory. Recent research has highlighted the importance of a demographic approach to understanding COVID-19 transmission and fatality rates. The experience in Hong Kong shows that while an older population age structure may be important for understanding COVID-19 fatality, it is not a given. From a social science perspective at least, there is 'no easy answer' to why one area should experience COVID-19 differently from another. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs. Wang and colleagues conducted rare-variant association analyses of long non-coding RNAs (lncRNAs) in 66,000 ancestrally diverse TOPMed participants with whole-genome sequencing and measurements of blood lipids and lipoproteins. The findings suggest an additional genomic element in known lipid gene regions that is distinct from the known lipid-associated genes. [ABSTRACT FROM AUTHOR]

Objective: Estrogen is indispensable in health and disease and mainly functions through its receptors. The protection of the cardiovascular system by estrogen and its receptors has been recognized for decades. Numerous studies with a focus on estrogen and its receptor system have been conducted to elucidate the underlying mechanism. Although nuclear estrogen receptors, including estrogen receptor-α and estrogen receptor-β, have been shown to be classical receptors that mediate genomic effects, studies now show that GPER mainly mediates rapid signaling events as well as transcriptional regulation via binding to estrogen as a membrane receptor. With the discovery of selective synthetic ligands for GPER and the utilization of GPER knockout mice, significant progress has been made in understanding the function of GPER. In this review, the tissue and cellular localizations, endogenous and exogenous ligands, and signaling pathways of GPER are systematically summarized in diverse physiological and diseased conditions. This article further emphasizes the role of GPER in vascular pathology and physiology, focusing on the latest research progress and evidence of GPER as a promising therapeutic target in hypertension, pulmonary hypertension, and atherosclerosis. Thus, selective regulation of GPER by its agonists and antagonists have the potential to be used in clinical practice for treating such diseases. [ABSTRACT FROM AUTHOR]

The potential applications of nanowires in thermal management and thermoelectric energy conversion have sparked extensive research on thermal transport in various nanowires. Nickel nanowires, with their unique properties and promising applications, have been extensively studied. However, the influence of size, particularly the impact of kink structures, on the thermal transport behavior in nickel nanowires remains unclear. In this paper, we employed electron-beam lithography and liftoff techniques to fabricate suspended nickel nanowires with varying sizes and kinks to experimentally investigate the size and kink effect on the thermal conductivity. The experimental results revealed that the thermal transport behavior of nickel nanowires is significantly influenced by both size and kink effects. Notably, as the nanowire size decreases, the thermal conductivity also decreases. Furthermore, we discovered that the thermal conductivity can be adjusted by altering the number and angle of kinks. Increasing the number of kinks from 18 to 36 resulted in a significant decrease in thermal conductivity. In contrast, as the kink angle decreased from 157° to 90°, the thermal conductivity also decreased. However, intriguingly, when the kink angle was further decreased from 90° to 43°, the thermal conductivity increases. This non-monotonic change in thermal conductivity with the kink angle provides an interesting insight into the intricate behavior of heat carriers in kinked nickel nanowires. Additionally, we found that varying the alloy elements can profoundly alter the thermal conductivity of nanowires with kinks. These results offer valuable insights into the behaviors of heat carriers, including electrons and phonons, during heat transfer in nickel nanowires. [ABSTRACT FROM AUTHOR]

This letter presents a novel model predictive control strategy without involving any proportional-integral-differential regulators for practical renewable energy based ac microgrids. The proposed method consists of a model predictive power control (MPPC) scheme and a model predictive voltage control (MPVC) scheme. By controlling the bidirectional buck-boost converters of the battery energy storage systems based on the MPPC algorithm, the fluctuating output from the renewable energy sources can be smoothed, while stable dc-bus voltages can be maintained as the inverters' inputs. Then, the parallel inverters are controlled by using a combination of the MPVC scheme and the droop method to ensure stable ac voltage output and proper power sharing. Compared with the traditional cascade control, the proposed method is simpler and shows better performance, which is validated in simulation on MATLAB/Simulink and on real-time laboratory platform. [ABSTRACT FROM AUTHOR]

Venous thromboembolism occurs in up to one-third of patients with COVID-19. Venous thromboembolism and COVID-19 may share a common genetic architecture, which has not been clarified. To fill this gap, we leverage summary-level genetic data from the latest COVID‐19 host genetics consortium and UK Biobank and examine the shared genetic etiology and causal relationship between COVID-19 and venous thromboembolism. The cross-trait and co-localization analyses identify 2, 3, and 4 shared loci between venous thromboembolism and severe COVID-19, COVID-19 hospitalization, SARS-CoV-2 infection respectively, which are mapped to ABO, ADAMTS13, FUT2 genes involved in coagulation functions. Enrichment analysis supports shared biological processes between COVID-19 and venous thromboembolism related to coagulation and immunity. Bi-directional Mendelian randomization suggests that venous thromboembolism was associated with higher risk of three COVID-19 traits, and SARS-CoV-2 infection was associated with a higher risk of venous thromboembolism. Our study provides timely evidence for the genetic etiology between COVID-19 and venous thromboembolism (VTE). Our findings contribute to the understanding of COVID-19 and VTE etiology and provide insights into the prevention and comorbidity management of COVID-19. Joint analysis of existing summary statistics data using genome-wide crosstrait analysis and bi-directional Mendelian randomization provides further evidence for a shared genetic etiology between COVID-19 and venous thromboembolism. [ABSTRACT FROM AUTHOR]

Thermoelectric generators (TEGs) can convert heat to electricity based on the temperature difference between their hot and cold sides. However, during practical operations, low thermoelectric conversion efficiency is usually caused by non-uniform temperature difference (NTD) conditions; thus, reliable and effective maximum power point tracking (MPPT) under NTD conditions is imperative for TEG arrays. Therefore, in this study, a jellyfish search (JS) algorithm-based TEG array reconfiguration strategy is proposed to realise MPPT under NTD conditions, upon which the overall power loss is effectively decreased, the energy conversion efficiency is efficiently enhanced, and the MPPT speed is improved. In particular, the simulation results demonstrate that the JS algorithm-based TEG array reconfiguration using a random pattern can enhance the maximum output power by 23.32% for 9 × 9 symmetric TEG arrays and 15.78% for 10 × 15 asymmetric TEG arrays. Finally, a hardware-in-the-loop (HIL) test was conducted on the RTLAB platform to verify its feasibility for hardware implementation. [ABSTRACT FROM AUTHOR]

The incidence of heart failure mainly resulting from cardiac hypertrophy and fibrosis increases sharply in post-menopausal women compared with men at the same age, which indicates a cardioprotective role of estrogen. Previous studies in our group have shown that the novel estrogen receptor G Protein Coupled Receptor 30 (GPR30) could attenuate myocardial fibrosis caused by ischemic heart disease. However, the role of GPR30 in myocardial hypertrophy in ovariectomized mice has not been investigated yet. In this study, female mice with bilateral ovariectomy or sham surgery underwent transverse aortic constriction (TAC) surgery. After 8 weeks, mice in the OVX + TAC group exhibited more severe myocardial hypertrophy and fibrosis than mice in the TAC group. G1, the specific agonist of GPR30, could attenuate myocardial hypertrophy and fibrosis of mice in the OVX + TAC group. Furthermore, the expression of LC3II was significantly higher in the OVX + TAC group than in the OVX + TAC + G1 group, which indicates that autophagy might play an important role in this process. An in vitro study showed that G1 alleviated AngiotensionII (AngII)-induced hypertrophy and reduced the autophagy level of H9c2 cells, as revealed by LC3II expression and tandem mRFP-GFP-LC3 fluorescence analysis. Additionally, Western blot results showed that the AKT/mTOR pathway was inhibited in the AngII group, whereas it was restored in the AngII + G1 group. To further verify the mechanism, PI3K inhibitor LY294002 or autophagy activator rapamycin was added in the AngII + G1 group, and the antihypertrophy effect of G1 on H9c2 cells was blocked by LY294002 or rapamycin. In summary, our results demonstrate that G1 can attenuate cardiac hypertrophy and fibrosis and improve the cardiac function of mice in the OVX + TAC group through AKT/mTOR mediated inhibition of autophagy. Thus, this study demonstrates a potential option for the drug treatment of pressure overload-induced cardiac hypertrophy in postmenopausal women. [ABSTRACT FROM AUTHOR]

Inducing protein degradation by proteolysis-targeting chimeras (PROTACs) has gained tremendous momentum in the field for its promise in the discovery and development of new therapies. Based on our previously reported PROTAC BCR-ABL degraders, we designed and synthesized additional 4 PROTAC compounds with a novel linker that contains pyrimidine rings. Molecular and cellular studies have shown that different linkers affect the degradation activity of small-molecule degraders on the target protein of BCR-ABL. We screened out a lead compound, DMP11, with stable physicochemical properties and high activity. Preliminary evaluation of its pharmacodynamics in vitro model showed that it has a good inhibitory effect on imatinib-resistant chronic myeloid leukemia cell lines, as has been shown in animal models. Our preliminary research into the mechanism of DMP11 found that DMP11 can overcome drug resistance by simultaneously inhibiting the targets of BCR-ABL and SRC-family kinase (SFK). [ABSTRACT FROM AUTHOR]

• A magnetic rolling pendulum bistable harvester is proposed for handshaking. • Complex dynamic behaviors and multiple solutions of the system are emphasized. • Bandwidth for high-energy orbit oscillation is 4.84 Hz under excitation of 0.5 g. • Matched impedance sees an average power of 4.21 mW under handshaking excitation. • Handshaking vibration in 13 s to charge a capacitor powers a watch for 44 min. Converting the kinetic energy of human movement into electricity provides a solution for the power supply of portable electronics for communication, medical treatment, positioning, search-and-rescue, etc. Due to the characteristics of high sensitivity and snap-through, a magnetic rolling pendulum bistable energy harvester (MRP-BEH) based on magnetic-spring mechanism is proposed for scavenging energy from handshaking vibration. The harvester possessing the advantage of small damping exploits the rolling oscillation of a suspended magnet. By establishing the electromechanical model, numerical outcomes of the MRP-BEHs with different potential well depths are investigated through the response under constant and sweep frequency excitations. Particularly, the complex dynamic behaviors are characterized by basins of attraction and bifurcation diagrams. A prototype is fabricated, and experiments are undertaken under harmonic and handshaking excitations. Experimental results are consistent with numerical simulations, and excitation of 0.5 g witnesses a broadband frequency range from 5.18 Hz to 10.02 Hz for the harvester with proper system parameters. Regarding the excitation of handshaking, an instantaneous maximum power of 21.9 mW and an average power of 4.21 mW is achieved with matched load resistance. By boosting the output voltage with a transformer, the charging and discharging experiments of capacitors for powering various electronics demonstrate the broad application prospects of the harvester. This research, in a nutshell, broadens the methodology for achieving bistable oscillation and introduces a fresh perspective for designing high-efficiency energy harvesters attuned to human motion. [ABSTRACT FROM AUTHOR]

Attempts to identify and prioritize functional DNA elements in coding and non-coding regions, particularly through use of in silico functional annotation data, continue to increase in popularity. However, specific functional roles can vary widely from one variant to another, making it challenging to summarize different aspects of variant function with a one-dimensional rating. Here we propose multi-dimensional annotation-class integrative estimation (MACIE), an unsupervised multivariate mixed-model framework capable of integrating annotations of diverse origin to assess multi-dimensional functional roles for both coding and non-coding variants. Unlike existing one-dimensional scoring methods, MACIE views variant functionality as a composite attribute encompassing multiple characteristics and estimates the joint posterior functional probabilities of each genomic position. This estimate offers more comprehensive and interpretable information in the presence of multiple aspects of functionality. Applied to a variety of independent coding and non-coding datasets, MACIE demonstrates powerful and robust performance in discriminating between functional and non-functional variants. We also show an application of MACIE to fine-mapping and heritability enrichment analysis by using the lipids GWAS summary statistics data from the European Network for Genetic and Genomic Epidemiology Consortium. [ABSTRACT FROM AUTHOR]

• Pining synchronization protocols for distributed secondary control in microgrid. • Impact analysis of communication topology using spectral graph properties. • Development of critical algebraic connectivity constraint for communication network. • Communication network planning model based on Mixed Integer Semidefinite Program. • Problem relaxation using Linear Matrix Inequalities and KKT conditions. Driven by the fact that the structural topology of the communication network has a significant effect on the dynamical performance of the related physical network, this paper addresses the communication network planning problem for islanded microgrids (MGs). The optimal communication topology with the lowest communication cost, which supports the desired performance of pinning-based distributed control is designed in the MG planning stage. To achieve that, firstly, pinning synchronization control (PSC) is developed to regulate the voltage and frequency at each distributed generator (DG) to the reference state. Then criteria of the algebraic connectivity of communication network to fulfill the convergence requirement of PSC protocols are derived analytically using spectral graph properties and Lyapunov theory. A communication network planning model is formulated as Mixed Integer Semidefinite Program (MISDP) by using Linear Matrix Inequalities (LMI) techniques. The convergence speed requirement of PSC, communication time delay and the importance of connections between DGs are considered as constraints. The optimal communication network with the lowest communication cost can be acquired and meanwhile the satisfactory dynamical performance of PSC protocols can be guaranteed. The case studies are designed to evaluate how the planning model can practically facilitate the pinning-based control in the islanded MG. The simulation results effectively verify that the dynamical control convergence can be improved under the properly designed communication network. The control performance of the proposed protocol is validated experimentally based on a two-DG MG prototype. [ABSTRACT FROM AUTHOR]

• A novel dynamic unitary PV array reconfiguration method is proposed. • IPDO achieves the highest power over other eight comparison algorithms. • Four metrics are used to quantitatively assess various algorithms. • HIL experiments effectively validate the implementation feasibility of IPDO. • A new switch matrix is designed to reduce the switch number. This work designs an advanced dynamic unitary PV array reconfiguration scheme based on a novel improved prairie dog optimization (IPDO) to solve the power loss issue due to partial shading of PV arrays. This method takes the PV cell as the smallest entity of reconfiguration, and is suitable for large-scale PV arrays. To avoid invalid and redundant relocation of PV modules, an innovative self-rectify strategy is employed and embedded in the reconfiguration algorithm, which can reduce invalid actions of switching matrix by up to 80 %. Comparative simulation tests among nine algorithms (IPDO, genetic algorithm, particle swarm optimization, simulated annealing, four-square sudoku, arithmetic sequence pattern, modified harris hawks optimizer, artificial ecosystem-based optimization, Runge Kutta optimizer) under eight typical shading types verify the superiority of IPDO from four metrics, i.e., power loss, power enhancement, fill factor and execution ratio. Particularly, IPDO reduces power loss by 7.33 % to 30.63 %, enhances the harvested power by 6.1 % to 31.59 %, enhances fill factor (FF) by 0.579 to 0.773, and enhances execution ratio (ER) by 60.37 % to 92.67 % for asymmetric (20 × 30) PV array. For symmetric (30 × 30) PV array, IPDO reduces power loss by 9.01 % to 27.86 %, enhances the harvested power by 8.33 % to 43.69 %, enhances FF by 0.602 to 0.759, and enhances ER by 72.14 % to 90.99 %. Moreover, a new switching matrix with double-pole multi-throw switches is designed for the required switches number reduction. Lastly, hardware-in-the-loop (HIL) experiments based on RTLAB are carried out which validate the implementation feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

Introduction: Levodopa has become the main therapy for motor symptoms of Parkinson's disease (PD). This study aimed to test whether the amplitude of low-frequency fluctuation (ALFF) computed by fMRI could predict individual patient's response to levodopa treatment.Methods: We included 40 patients. Treatment efficacy was defined based on motor symptoms improvement from the state of medication off to medication on, as assessed by the Unified Parkinson's Disease Rating Scale score III. Two machine learning models were constructed to test the prediction ability of ALFF. First, the ensemble method was implemented to predict individual treatment responses. Second, the categorical boosting (CatBoost) classification was used to predict individual levodopa responses in patients classified as moderate and superior responders, according to the 50% threshold of improvement. The age, disease duration and treatment dose were controlled as covariates.Results: No significant difference in clinical data were observed between moderate and superior responders. Using the ensemble method, the regression model showed a significant correlation between the predicted and the observed motor symptoms improvement (r = 0.61, p < 0.01, mean absolute error = 0.11 ± 0.02), measured as a continuous variable. The use of the Catboost algorithm revealed that ALFF was able to differentiate between moderate and superior responders (area under the curve = 0.90). The mainly contributed regions for both models included the bilateral primary motor cortex, the occipital cortex, the cerebellum, and the basal ganglia.Conclusion: Both continuous and binary ALFF values have the potential to serve as promising predictive markers of dopaminergic therapy response in patients with PD. [ABSTRACT FROM AUTHOR]

• A new optimal mileage-based PV array reconfiguration (OMAR) is constructed. • The OMAR can maximize the total benefit instead of only the generation benefit. • The OMAR decomposition with two sub-problems reduces the optimization difficulty. • The swarm reinforcement learning is used to obtain high-quality optimums of OMAR. • The proposed method can obtain higher total benefit than 6 comparative algorithms. This paper constructs a new optimal mileage-based PV array reconfiguration (OMAR) in a PV power plant under partial shading conditions. It aims to maximize the power output of a PV power plant, and minimize the additional capacity and mileage payments resulting from the power fluctuation in a performance-based frequency regulation market. To reduce the optimization difficulty of OMAR, it is decomposed into two optimization sub-problems, including an upper-layer discrete optimization of PV array reconfiguration and a lower-layer continuous optimization of real-time generation scheduling. The upper-layer discrete optimization is addressed by the proposed swarm reinforcement learning (SRL), which can implement an efficient exploration and exploitation with multiple cooperative agents instead of a single learning agent. The rest lower-layer optimization is handled by the fast interior point method. The proposed method's effectiveness is thoroughly evaluated on the 10 × 10 total-cross-tied PV arrays under various partial shading conditions. Simulation results demonstrate that the proposed SRL can obtain a larger total benefit than genetic algorithm (GA), particle swarm optimization (PSO), grasshopper optimization algorithm (GOA), harris hawks optimizer (HHO), butterfly optimization algorithm (BOA), and Q-learning, in which the benefit increment can reach from 2.12% (against PSO) to 10.62% (against Q-learning). [ABSTRACT FROM AUTHOR]

Purpose: Recent clinical trials with agents targeting immune checkpoint pathway have emerged as an important therapeutic approach for a broad range of cancer types. Resveratrol has been shown to possess cancer preventive and therapeutic effects and has potential to be chemotherapeutic agent/adjuvant. Here, we assessed the effect of resveratrol on immune checkpoint pathways. Methods: The expression patterns of Wnt components and PD-L1 were examined by Western blot, Chromatin immunoprecipitation (ChIP) was used for analysis of DNA–protein interaction, the promoter activity was determined by luciferase reporter assay, apoptosis was analyzed by flow cytometry and the ability of the resveratrol to modulate T cell function was assessed in a co-culture system. Results: Although the dose-, and cell-type dependent effects of resveratrol on PD-L1 expression have been reported, we show here that resveratrol dose-dependently upregulates PD-L1 expression at the range of pharmacologic-achievable concentrations in lung cancer cells and that is essential for suppression of T-cell-mediated immune response. We also found that Wnt pathway is critical for mediating resveratrol-induced PD-L1 upregulation. Mechanistically, resveratrol activates SirT1 deacetylase to deacetylate and stabilize transcriptional factor Snail. Snail in turn inhibits transcription of Axin2, which leads in disassembly of destruction complex and enhanced binding of β-catenin/TCF to PD-L1 promoter. Conclusion: We conclude that resveratrol is capable to suppress anti-tumor immunity by controlling mainly PD-L1 expression. This finding will extend the understanding of resveratrol in regulation of tumor immunity and is relevant to the debate on resveratrol supplements for lung cancer patients. [ABSTRACT FROM AUTHOR]

Immune-checkpoint blockade (ICB) therapies have been widely used in clinical treatment of cancer patients, but only 20–30% of patients benefit from immunotherapy. Therefore, it is important to decipher the molecular mechanism of resistance to ICB and develop new combined treatment strategies. PD-L1 up-regulation in tumor cells contributes to the occurrence of immune escape. Increasing evidence shows that its transcription level is affected by multiple factors, which limits the objective response rate of ICB. Fibroblast growth factor 19 (FGF19), a member of the fibroblast growth factor family, is widely involved in the malignant progression of many tumors by binding to fibroblast growth factor receptor 4 (FGFR4). In this study, we confirmed that FGF19 acts as a driver gene in hepatocellular carcinoma (HCC) progression by binding to FGFR4. The up-regulation of FGF19 and FGFR4 in HCC is associated with poor prognosis. We found that FGF19/FGFR4 promoted the proliferation and invasion of HCC cells by driving IGF2BP1 to promote PD-L1 expression. Knockdown of FGFR4 significantly reduced the expression of IGF2BP1/PD-L1 and inhibited the proliferation and invasion of HCC cells. These biological effects are achieved by inhibiting the PI3K/AKT pathway. The combination of FGFR4 knockdown and anti-PD-1 antibody greatly suppressed tumor growth and enhanced the sensitivity of immunotherapy, highlighting the clinical significance of FGF19/FGFR4 activation in immunotherapy. [Display omitted] • FGFR4 is upregulated and indicates poor prognosis in HCC patients. • FGF19/FGFR4 promotes IGF2BP1 expression and enhances PD-L1 transcription facilitation HCC cells survival and immune escape. • Anti-PD-1 combined with FGFR4 inhibition improves the sensitivity of HCC immunotherapy. [ABSTRACT FROM AUTHOR]

• Average start of the photosynthetic period in China was on the 123rd day of the year. • The average start of the photosynthetic period advances at a rate of 4.3 d (10 a)−1. • 64% of the region is temperature controlled, others are precipitation controlled. • Importance of temperature and precipitation determined by pre-season precipitation. • Climate change increases NPP by advancing the start of the photosynthetic period. In the context of global warming, the advancement of spring phenology in northern and temperate regions due to increased temperatures has been widely reported. Early and delayed start of the photosynthetic period (SOP) directly affects the vegetation net primary productivity (NPP). However, the interrelationship between climate change, the SOP, and the NPP is unclear. In this paper, we use the dynamics of decadal daily solar-induced chlorophyll fluorescence data to calculate the response of Chinese vegetation photosynthetic phenology to climate change and its impact on the NPP over the last 20 years. The results found that over the last 20 years, the average SOP in China was on the 123rd day of the year, and the SOP has advanced at an average rate of 4.3 d (10 a)−1, with a faster trend of SOP advancement in highland and high-altitude areas. 64% of SOP in China is controlled by temperature; 36% of the SOP in China is controlled by precipitation, and the relative importance of temperature and precipitation was reversed as the precipitation gradient decreased, with SOP dominated by temperature when pre-season precipitation ≧300 mm, and SOP dominated by precipitation when pre-season precipitation ≦300 mm. Finally, we find that climate change indirectly increases vegetation NPP by advancing SOP. Our study emphasizes the importance of precipitation on phenology. It provides a scientific basis for understanding and predicting the response of spring photosynthetic phenology to climate change and the contribution of spring phenology to carbon estimation in terrestrial ecosystems. [ABSTRACT FROM AUTHOR]