Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated analysis reveals FOXA1 and Ku70/Ku80 as direct targets of ivermectin in prostate cancer

Ivermectin is a widely used antiparasitic drug and shows promising anticancer activity in various cancer types. Although multiple signaling pathways modulated by ivermectin have been identified, few studies have focused on the exact target of ivermectin. Herein, we report the pharmacological effects and direct targets of ivermectin in prostate cancer (PCa). Ivermectin caused G0/G1 arrest, induced cell apoptosis, DNA damage, and decreased androgen receptor (AR) signaling in PCa cells. Using integrated omics profiling, including RNA-seq and thermal proteome profiling, we found that the forkhead box protein A1 (FOXA1) and non-homologous end joining (NHEJ) repair executer Ku70/Ku80 were the direct targets of ivermectin. The binding of ivermectin and FOXA1 reduced the chromatin accessibility of AR and the G0/G1 cell cycle regulator E2F1, leading to cell proliferation inhibition. The binding of ivermectin and Ku70/Ku80 impaired the NHEJ repair ability. Cooperating with the downregulation of homologous recombination repair after AR inhibition, ivermectin triggered synthetic lethality. Our findings demonstrate the anticancer effect of ivermectin in prostate cancer, indicating that its use may be a new therapeutic approach for PCa.
Alcohol consumption, DNA methylation and colorectal cancer risk: Results from pooled cohort studies and Mendelian randomization analysis

Alcohol consumption is thought to be one of the modifiable risk factors for colorectal cancer (CRC). However, the causality and mechanisms by which alcohol exerts its carcinogenic effect are unclear. We evaluated the association between alcohol consumption and CRC risk by analyzing data from 32 cohort studies and conducted two‐sample Mendelian randomization (MR) analysis to examine for casual relationship. To explore the effect of alcohol related DNA methylation on CRC risk, we performed an epigenetic MR analysis with data from an epigenome‐wide association study (EWAS). We additionally performed gene‐alcohol interaction analysis nested in the UK Biobank to assess effect modification between alcohol consumption and susceptibility genes. We discovered distinct effects of alcohol on CRC incidence and mortality from the meta‐analyses, and genetic predisposition to alcohol drinking was causally associated with an increased CRC risk (OR = 1.79, 95% CI: 1.23‐2.61) using two‐sample MR approaches. In epigenetic MR analysis, two alcohol‐related CpG sites (cg05593667 and cg10045354 mapped to COLCA1/COLCA2 gene) were identified causally associated with an increased CRC risk (P < 8.20 × 10−4). Gene‐alcohol interaction analysis revealed that carriage of the risk allele of the eQTL (rs3087967) and mQTL (rs11213823) polymorphism of COLCA1/COLCA2 would interact with alcohol consumption to increase CRC risk (PInteraction = .027 and PInteraction = .016). Our study provides comprehensive evidence to elucidate the role of alcohol in CRC and highlights that the pathogenic effect of alcohol on CRC could be partly attributed to DNA methylation by regulating the expression of COLCA1/COLCA2 gene.
Effect of MMF Immunosuppression Based on CNI Reduction on CNI-Related Renal Damage after Lung Transplantation

In this paper, numerous effects of immunosuppressive regimen of mycophenolate mofetil (MMF) on CNI-related renal damage after lung transplantation are evaluated thoroughly. For this purpose, 110 lung transplant recipients who were treated in our hospital from March 2016 to January 2018 were randomly selected. All patients took prednisone acetate tablets or rapamycin at the same time or not at the same time. MMF is 1 g every time, twice a day, and adjusted according to the re-examination. According to the different drugs taken by 110 patients, they were divided into cyclosporine A group and tacrolimus group. Among them, 92 patients in cyclosporine A group took cyclosporine A; 18 patients in tacrolimus group took tacrolimus. The clinical data of age and gender of the two groups were collected, To observe and compare the occurrence of CNI-related renal damage in lung transplant recipients and different immunosuppressants. The CNI dosage of tacrolimus group and cyclosporine A group was compared before and after MMF. The changes of serum creatinine level and serum creatinine clearance rate were measured before MMF administration and 30, 60, and 90 days after MMF administration, to observe the complications of CNI-related renal damage after lung transplantation. Experimental results showed that there were 16 cases (14.55%) of CNI-related renal damage in lung transplant recipients and different immunosuppressants, including 10 cases (11.36%) in males, 6 cases (27.27%) in females, 11 cases (12.09%) in tacrolimus group, and 5 cases (26.32%) in cyclosporine A group. There was no significant difference between the two groups (P > 0.05). Compared with MMF before and after administration, CNI dosage of cyclosporine A group and tacrolimus group decreased significantly (P < 0.01). Compared with MMF before administration, serum creatinine level decreased and serum creatinine clearance rate increased significantly (P < 0.05). In the follow-up, 16 patients with CNI-related renal damage were found to be immune rejection before the adjustment of immunosuppression program, no complications such as immune rejection, myelosuppression, and infection occurred within 15 months after the adjustment of immunosuppression program, blood glucose increased in 3 patients within 2 years after operation, blood lipid increased in 1 patient, urea increased in 1 patient, and uric acid increased in 1 patient. MMF immunosuppressive therapy based on CNI reduction is a safe and effective immunosuppressive therapy, which can significantly reduce immune rejection, improve renal function, and play an important role in improving CNI-related renal damage after lung transplantation.
Laser ultrasonic scanning for detection of damage in copper pipelines using blind compressive sensing and the adjacent area difference coefficient

Due to its good thermal conductivity and corrosion resistance, copper has become a common material for transmission pipelines. It is necessary to detect the early signs of damage in copper pipelines effectively and quickly. Laser ultrasound scanning is a non-contact and non-destructive damage identification method, which can realize high-precision, non-contact detection. At the same time, with the progress of internet technology, traditional damage testing has begun to use advanced technologies such as the internet of things and cloud computing to promote an upgrade of the testing industry from an offline industry to an online industry. However, obtaining a large amount of wavefield vibration data is time consuming. In this paper, we present a laser ultrasonic scanning cloud platform damage detection method for copper pipelines based on alternating learning blind compressive sensing (BCS) and the adjacent area difference coefficient (AADC); this approach can improve real-time performance and detection accuracy. First, the damage detection method is introduced in detail. BCS is used to compress the laser scanning signal at the data acquisition terminal, and then transmitted to a data processing cloud platform for reconstruction. Copper pipeline damage imaging is realized by taking the AADC value of each detection point as the pixel value. The simulated detection data of the copper pipeline are then obtained through a finite element model, and the weighted vectors of the AADC are determined by a genetic algorithm. Finally, experimental data are used to verify the effectiveness of this method, and the experimental results are analyzed and discussed. The AADC and other distance damage imaging methods are compared. The results demonstrate that this method can compress the wavefield data to 13% of the original data, and the detection of crack damage is realized.
TDP-43 Proteinopathy Causes Broad Metabolic Alterations including TCA Cycle Intermediates and Dopamine Levels in Drosophila Models of ALS

Amyotrophic lateral sclerosis (ALS) is a fatal, complex neurodegenerative disorder that causes selective degeneration of motor neurons. ALS patients exhibit symptoms consistent with altered cellular energetics such as hypermetabolism, weight loss, dyslipidemia, insulin resistance, and altered glucose tolerance. Although evidence supports metabolic changes in ALS patients, metabolic alterations at a cellular level remain poorly understood. Here, we used a Drosophila model of ALS based on TDP-43 expression in motor neurons that recapitulates hallmark features of motor neuron disease including TDP-43 aggregation, locomotor dysfunction, and reduced lifespan. To gain insights into metabolic changes caused by TDP-43, we performed global metabolomic profiling in larvae expressing TDP-43 (WT or ALS associated mutant variant, G298S) and identified significant alterations in several metabolic pathways. Here, we report alterations in multiple metabolic pathways and highlight upregulation of Tricarboxylic acid (TCA) cycle metabolites and defects in neurotransmitter levels. We also show that modulating TCA cycle flux either genetically or by dietary intervention mitigates TDP-43-dependent locomotor defects. In addition, dopamine levels are significantly reduced in the context of TDP-43G298S, and we find that treatment with pramipexole, a dopamine agonist, improves locomotor function in vivo in Drosophila models of TDP-43 proteinopathy.
Device Performance and Switching Characteristics of 16 kV Ultrahigh-Voltage SiC Flip-Type n-Channel IE-IGBTs

Ultrahigh-voltage SiC flip-type n-channel implantation and epitaxial (IE)-IGBTs were developed, and the static and dynamic performance was investigated. A large device (8 mm × 8mm) with a blocking voltage greater than 16 kV was achieved, and an on-state current of 20 A was obtained at the low on-state voltage (Von) of 4.8 V. RonAdiff was 23 mΩ·cm2 at Von = 4.8 V. In order to evaluate the switching characteristics of the IE-IGBT, ultrahigh-voltage power modules were assembled. A chopper circuit configuration was used to evaluate the switching characteristics of the IE-IGBT. Smooth turn-off waveforms were successfully obtained at VCE = 6.5 kV and ICE = 60 A in the temperature range from room temperature to 250°C.
Recent Advances in the Surface Functionalization of PLGA-Based Nanomedicines

Therapeutics are habitually characterized by short plasma half-lives and little affinity for targeted cells. To overcome these challenges, nanoparticulate systems have entered into the disease arena. Poly(d,l-lactide-co-glycolide) (PLGA) is one of the most relevant biocompatible materials to construct drug nanocarriers. Understanding the physical chemistry of this copolymer and current knowledge of its biological fate will help in engineering efficient PLGA-based nanomedicines. Surface modification of the nanoparticle structure has been proposed as a required functionalization to optimize the performance in biological systems and to localize the PLGA colloid into the site of action. In this review, a background is provided on the properties and biodegradation of the copolymer. Methods to formulate PLGA nanoparticles, as well as their in vitro performance and in vivo fate, are briefly discussed. In addition, a special focus is placed on the analysis of current research in the use of surface modification strategies to engineer PLGA nanoparticles, i.e., PEGylation and the use of PEG alternatives, surfactants and lipids to improve in vitro and in vivo stability and to create hydrophilic shells or stealth protection for the nanoparticle. Finally, an update on the use of ligands to decorate the surface of PLGA nanomedicines is included in the review.
An 11.8-fJ/Conversion-Step Noise Shaping SAR ADC with Embedded Passive Gain for Energy-Efficient IoT Sensors

Herein, we present a noise shaping successive-approximation-register (SAR) analog-to-digital converter (ADC) with an embedded passive gain multiplication technique. The noise shaping moves the in-band quantization noise from the signal band to out-of-band for improved signal-to-noise ratio (SNR). The proposed approach tackles the drawback of the previous active noise shaping (increased power and extra noise) and passive noise shaping (limited noise suppression and signal loss). Both noise shaping and gain multiplication are realized on-chip in an energy-efficient manner without an opamp. This approach uses only capacitors and switches in the finite impulse response (FIR) and infinite impulse response (IIR) filters. A comparator suppressing kickback noise is presented to handle the tradeoff between noise suppression and the filter capacitor size. The energy-efficient merged-capacitor switching (MCS) technique is effectively combined with rail-to-rail swing comparator and thermometer-coded capacitor array, which reduces the settling error in the digital to analog converter (DAC). The process-induced mismatch effect in the capacitive DAC is investigated using a behavioral model of the ADC. Additionally, we propose dynamic element matching (DEM) for the thermometer-coded capacitor array. The ADC is fabricated using a 0.18 μm CMOS process in an area of 0.26 mm2. Consuming 4.1 μW, the ADC achieves a signal-to-noise and distortion ratio (SNDR) of 66.5 dB and a spurious-free dynamic range (SFDR) of 79.1 dB. The figure-of-merit (FoM) of the ADC is 11.8 fJ/conversion-step.
Finite Element Analysis of Cylindrical Shell with a Circular Cutout Using Combination Model of Solid Element and Shell Element

In this paper, the structure of cylindrical shell with a reinforced circular cutout using combination model of solid element and shell element was analyzed by Finite Element Method (FEM) simulations. Multipoint constraint (MPC) method is mainly used to solve the connection between solid element and shell element when considering the calculation accuracy and efficiency of the model. The combination model of solid and shell element is established in ANSYS, and has been compared to the model of shell element and the model of solid element. The result showed that in the aspects of the stress distribution of the pressure hull near the cutout, buckling behavior of the structure and its instability response, the combination model of solid and shell element was almost equal to the others, it is convincible as well as possessing merits of other models.
Experimental Study on the Contact Explosion Resistance Performance of High Strength RC Slabs

Influenced by the contact explosion shock,the reinforced concrete slabs are the main structural components of a protective structure under the blast loads.The explosion contact resistance performance of 5 different steel ratio high strength RC two-way slabs and 5 common RC two-way slabs were experimentally studied to explore the mode of failure mechanism.Explosion cratering,explosion spalling and explosion perforating.The contact explosion damage feature and local damage effects of the two kinds of slabs were also systematically analyzed.The experimental results indicate that raising the strength grade of steel bar and steel ratio can enhance the explosion resistance performance of RC slab.Preliminary analysis of the main influence factors on explosion cratering and structure spalling can provide a reference for the design of local damage resisting structures and development shielding covers for protection engineering.
Data-Driven Feedforward Parameter Tuning Optimization Method Under Actuator Constraints

Feedforward control includes iterative force injection-based feedforward control and model-based feedforward control. Model-based feedforward control enables high performance for nonrepetitive motions in industrial motion systems. In particular, model-based feedforward control with a parameterized input shaping filter and a feedforward controller can effectively implement trajectory tracking tasks without relying on mathematical models of systems. However, the pre-existing model-based feedforward control does not consider the saturation boundary of the system actuator, which may lead to saturation of the feedforward force for actual systems with actuator constraints. Therefore, this article aims to develop a feedforward control method that obtains high tracking performance for nonrepetitive trajectory under actuator constraints. In particular, a parameterized input shaping and feedforward control method based on basis functions is pursued, which is combined with a data-driven iterative optimization approach to cope with nonrepetitive trajectory tracking tasks and actuator constraints. Simulations and experiments on a motion system confirm the optimal trajectory tracking performance under actuator constraints and robustness to nonrepetitive trajectory.
Method of Turnout Fault Diagnosis Based on Grey Correlation Analysis

On the basis of the changing rule of the power curve corresponding to the typical faults of the switch machine,the turnout fault diagnosis method was proposed by grey correlation analysis.Using the Fisher criterion to select feature vectort of the corresponding failure mode,optimizing the distinguishing coefficients and calculating the gray relational degrees of the features between the test sample and each failure mode,the diagnosis result of the test sample was obtained according to the failure mode with the maximum gray relational degree meeting the threshold requirements.Experiment results show that the method can achieve fault diagnosis without the need of sample training and also has good adaptability and high accuracy.
Facebook Use and Job Performance: The Mediating Effects of Social Capital, Knowledge Sharing, and Job Satisfaction

ABSTRACT Social networking sites (SNSs) are extensively used worldwide, and the number of workers who use them in their workplaces is increasing. This study empirically examined whether social capital, knowledge sharing, and job satisfaction can mediate the effects of Facebook use on job performance. The results demonstrated that Facebook use positively affected both bonding and bridging social capital. In addition, both types of social capital have positive effects on online and offline knowledge sharing. While offline knowledge sharing and job satisfaction positively affected perceived job performance, online knowledge sharing negatively affected perceived job performance. On the other hand, offline and online knowledge sharing did not have a statistically significant effect on supervisor-rated job performance. Only job satisfaction had a positive effect. This study’s findings provide practical implications for financial companies that are considering policies related to the use of SNSs and want to enhance their employees’ job performance.
Delay impulsive systems: A framework for modeling networked control systems

Delay Impulsive Systems: A Framework For Modeling Networked Control Systems by Payam Naghshtabrizi We model Networked Control Systems (NCSs) with variable delay, sampling intervals and packet dropouts as delay impulsive systems which exhibit continuous evolutions described by ODEs and state jumps or impulses that experience delay. We develop theorems for the exponential stability of nonlinear time-varying delay impulsive systems which can be viewed as extensions of the LyapunovKrasovskii Theorem for time-delay systems. For linear plants and controllers, exponential stability conditions can be formulated as Linear Matrix Inequalities (LMIs), which can be solved numerically. By solving these LMIs, one can find classes of delay-sampling sequences for the different sample-hold pairs in a NCS such that exponential stability is guaranteed. The timing requirements of delay-sampling sequences can be met by deterministic networks for which delivery of packets can be guaranteed with bounded delay. Scheduling theory provides conditions to check whether all the timing requirements can be met. If appropriate scheduling conditions are satisfied, the network will in fact be capable of delivering all the packets on time, and stability of all systems connected to the network is guaranteed. Our analysis leads to the x design of communication protocols to determine which nodes gain access to the network and an algorithm to select sampling sequences. We also consider the tracking problem over the network. A feedforward structure is used to force the state of the plant to follow a desired trajectory and feedback structure is used to obtain the desired performance and robustness. Since the feedback and the feedforward control commands are sampled and experience variable delays, exact trajectory tracking is not possible and there is an error between the desired trajectory and the real trajectory of the system. The error dynamics can be modeled as an impulsive system driven by an external input corresponding to feedforward signal mismatch. Sufficient condition for the Inputto-State Stability (ISS) of the tracking error dynamics with respect to this input is given. These results also provide classes of sampling-delay sequences for which the steady-state tracking error is guaranteed to be smaller than a desired level.
In-vitro optically aided robotic manipulation (IVOARM) system and algorithm development

In-Vitro Optically Aided Robotic Manipulation (IVOARM) constitutes a blind grasping concept using two anthropomorphic fingers with the aid of the directional force sensors and infra-red sensors mounted on it. This manipulator is controlled by an embedded system with high DSP compatibility. The infra-red sensors are mounted on the surface of the finger gripper to detect the presence of the object in the area of the grasping. The physical information of the object such as size and Centroid of the object is determined using the algorithm developed with the aid by the infra red sensors. The purpose of determining the Centroid is to determine the size and method to grasp the object. The result of the object size determination using the IVOARM has been obtained. Based on the size of the object obtained from the calculation, the object will be decided to be gripped in either full envelope gripping or finger tip gripping. Force will be calculated to ensure proper force to be applied.