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Abstract Focal segmental glomerulosclerosis (FSGS), a clinicopathological condition characterized by nephrotic-range proteinuria, has a high risk of progression to end-stage renal disease (ESRD). Meanwhile, the recurrence of FSGS after renal transplantation is one of the main causes of graft loss. The diagnosis of recurrent FSGS is mainly based on renal puncture biopsy transplants, an approach not widely consented by patients with early mild disease. Therefore, there is an urgent need to find definitive diagnostic markers that can act as a target for early diagnosis and intervention in the treatment of patients. In this review, we summarize the domestic and international studies on the pathophysiology, pathogenesis and earliest screening methods of FSGS and describe the functions and roles of specific circulating factors in the progression of early FSGS, in order to provide a new theoretical basis for early diagnosis of FSGS recurrence, as well as aid the exploration of therapeutic targets.

ABSTRACT Background In recent decades, natural compounds have been considered a significant source of new antitumor medicines due to their unique advantages. Several in vitro and in vivo studies have focused on the effect of terpenoids on apoptosis mediated by mitochondria in malignant cells. Recent findings In this review article, we focused on six extensively studied terpenoids, including sesquiterpenes (dihydroartemisinin and parthenolide), diterpenes (oridonin and triptolide), and triterpenes (betulinic acid and oleanolic acid), and their efficacy in targeting mitochondria to induce cell death. Terpenoid‐induced mitochondria‐related cell death includes apoptosis, pyroptosis, necroptosis, ferroptosis, autophagy, and necrosis caused by mitochondrial permeability transition. Apoptosis and autophagy interact in meaningful ways. In addition, in view of several disadvantages of terpenoids, such as low stability and bioavailability, advances in research on combination chemotherapy and chemical modification were surveyed. Conclusion This article deepens our understanding of the association between terpenoids and mitochondrial cell death, presenting a hypothetical basis for the use of terpenoids in anticancer management.

Abstract l‐2‐Hydroxyglutarate (l‐2‐HG) is a functionally compartmentalized metabolite involved in various physiological processes. However, its subcellular distribution and mitochondrial transport remain unclear owing to technical limitations. In the present study, an ultrasensitive l‐2‐HG biosensor, sfLHGFRH, composed of circularly permuted yellow fluorescent protein and l‐2‐HG‐specific transcriptional regulator, is developed. The ability of sfLHGFRH to be used for analyzing l‐2‐HG metabolism is first determined in human embryonic kidney cells (HEK293FT) and macrophages. Then, the subcellular distribution of l‐2‐HG in HEK293FT cells and the lower abundance of mitochondrial l‐2‐HG are identified by the sfLHGFRH‐supported spatiotemporal l‐2‐HG monitoring. Finally, the role of the l‐glutamate transporter SLC1A1 in mitochondrial l‐2‐HG uptake is elucidated using sfLHGFRH. Based on the design of sfLHGFRH, another highly sensitive biosensor with a low limit of detection, sfLHGFRL, is developed for the point‐of‐care diagnosis of l‐2‐HG‐related diseases. The accumulation of l‐2‐HG in the urine of patients with kidney cancer is determined using the sfLHGFRL biosensor.

Abstract The burgeoning comprehension of protein phase separation (PS) has ushered in a wealth of bioinformatics tools for the prediction of phase-separating proteins (PSPs). These tools often skew towards PSPs with a high content of intrinsically disordered regions (IDRs), thus frequently undervaluing potential PSPs without IDRs. Nonetheless, PS is not only steered by IDRs but also by the structured modular domains and interactions that aren’t necessarily reflected in amino acid sequences. In this work, we introduce PSPire, a machine learning predictor that incorporates both residue-level and structure-level features for the precise prediction of PSPs. Compared to current PSP predictors, PSPire shows a notable improvement in identifying PSPs without IDRs, which underscores the crucial role of non-IDR, structure-based characteristics in multivalent interactions throughout the PS process. Additionally, our biological validation experiments substantiate the predictive capacity of PSPire, with 9 out of 11 chosen candidate PSPs confirmed to form condensates within cells.

BackgroundThe value of semiquantitative resting myocardial perfusion imaging (MPI) in coronary artery disease (CAD) is limited. At present, quantitative MPI can be performed by a new cadmium zinc tellurium single-photon emission computed tomography (CZT-SPECT) scan. The quantitative index of resting myocardial blood flow (MBF) has received little attention, and its manifestations and clinical value in the presence of unstable coronary blood flow have not been clarified.PurposeIn patients with ST-segment elevation myocardial infarction (STEMI), whether resting MBF can provide additional value of blood flow than semi-quantitative resting MPI is not sure. We also explored the influencing factors of resting MBF.MethodsThis was a retrospective clinical study. We included 75 patients with STEMI in the subacute phase who underwent resting MPI and dynamic scans after reperfusion therapy. General patient information, STEMI-related data, MPI, gated MPI (G-MPI), and resting MBF data were collected and recorded. According to the clinically provided culprit vessels, the resting MBF was divided into ischemic MBF and non-ischemic MBF. The paired Wilcoxon signed-rank test was used for resting MBF. The receiver operating characteristic (ROC) curves were used to determine the optimal threshold for ischemia, and multiple linear regression analysis was used to analyze the influencing factors of resting MBF.ResultsThere was a statistically significant difference between the ischemic MBF and non-ischemic MBF [0.59 (0.47–0.72) vs. 0.76 (0.64–0.93), p

Abstract The lack of available protons severely lowers the activity of alkaline hydrogen evolution reaction process than that in acids, which can be efficiently accelerated by tuning the coverage and chemical environment of protons on catalyst surface. However, the cycling of active sites by proton transfer is largely dependent on the utilization of noble metal catalysts because of the appealing electronic interaction between noble metal atoms and protons. Herein, an all-non-noble W/WO2 metallic heterostructure serving as an efficient solid-acid catalyst exhibits remarkable hydrogen evolution reaction performance with an ultra-low overpotential of −35 mV at −10 mA/cm2 and a small Tafel slope (−34 mV/dec), as well as long-term durability of hydrogen production (>50 h) at current densities of −10 and −50 mA/cm2 in alkaline electrolyte. Multiple in situ and ex situ spectroscopy characterizations combining with first-principle density functional theory calculations discover that a dynamic proton-concentrated surface can be constructed on W/WO2 solid-acid catalyst under ultra-low overpotentials, which enables W/WO2 catalyzing alkaline hydrogen production to follow a kinetically fast Volmer-Tafel pathway with two neighboring protons recombining into a hydrogen molecule. Our strategy of solid-acid catalyst and utilization of multiple spectroscopy characterizations may provide an interesting route for designing advanced all-non-noble catalytic system towards boosting hydrogen evolution reaction performance in alkaline electrolyte.

Abstract Very recently, with the widespread research of deep learning, its achievements are increasingly evident in image inpainting tasks. However, many existing multi-stage methods fail to effectively inpainting the larger missing areas, their common drawback is that the result of each stage is easily misguided by the wrong content generated in the previous stage. To solve this issue, in this paper, a novel one-stage generative adversarial network based on the progressive decoding architecture and gradient guidance. Firstly, gradient priors are extracted at the encoder stage to be passed to the decoding branch, and multiscale attention fusion group is used to help the network understand the image features. Secondly, multiple parallel decoding branches fill and refine the missing regions by top-down passing the reconstructed priors. This progressively guided repair avoids the detrimental effects of inappropriate priors. The joint guidance of features and gradient priors helps the restoration results contain the correct structure and rich details. And the progressive guidance is achieved by our fusion strategy, combining reimage convolution and design channel coordinate attention to fuse and reweight the features of different branches. Finally, we use the multiscale fusion to merge the feature maps at different scales reconstructed by the last decoding branch and map them to the image space, which further improves the semantic plausibility of the restoration results. Experiments on multiple datasets show that the qualitative and quantitative results of our computationally efficient model are competitive with those of state-of-the-art methods.

Abstract For images corrupted for various reasons, the size of the corrupted area is often arbitrary and it has been a challenge to inpainting the larger missing areas. Though popular multistage networks ease the inpainting difficulty by repairing damaged image from coarse to fine, their common drawback is that the result of each stage is easily misguided by the wrong content generated in the previous stage. To address this problem, we propose a novel progressive guidance decoding network. First, multiple parallel decoding branches fill and refine the missing regions by top–down passing the reconstructed priors. This inpainting way of progressive guidance avoids adverse effects of inappropriate premises, since the decoding branches can learn what priors can be utilized. And convolution layers of decoder with different locations would pass down the different priors. The joint guidance of features and gradient priors helps the inpainting result contains the correct structure and rich details. The second fold of progressive guidance is achieved by our fusing strategy, combining ghost convolution and the designed cascaded efficient channel attention (CECA) to fuse and reweight the features from different branches. CECA explores the dependencies among adjant and non-adjant channels more effectively than popular ones. Finally, we merges the different-scale feature maps reconstructed by the last decoding branch and mapping them to the image space, which further improves the semantic plausibility of the restoration results. Extensive experiments verify the effectiveness of our method in both subjective and objective evaluation.

Plakophilin 3 (PKP3) affects cell signal transduction and cell adhesion and performs a crucial function in tumorigenesis. The current investigation evaluated the predictive significance and underlying processes of PKP3 within pancreatic cancer (PC) tissues. The assessment of differences in PKP3 expression was conducted through an analysis of RNA-seq data acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Additionally, clinical samples were collected to validate the findings. The predictive significance of PKP3 was investigated by analyzing survival data derived from TCGA and clinical specimens. PKP3′s biological function was assessed via phenotypic experiments after the suppression of PKP3 expression within PC cells. Functional enrichment analysis, encompassing KEGG, GO, and GSEA, was employed to assess the underlying mechanism of PKP3. Immune infiltration analysis was conducted in the present investigation to determine the association between PKP3 and tumor-infiltrating immune cells (TICs). In PC tissues, PKP3 expression was abnormally upregulated and correlated with a negative prognosis in individuals with PC. PKP3 can promote the progression, migration, and invasive capacity of PC cells and is relevant to the regulation of the PI3K–Akt and MAPK signaling pathways. Immune infiltration analysis demonstrated that PKP3 impeded CD8+ T-cell infiltration and immune cytokine expression within the tumor microenvironment. The PKP3 protein was identified as a prospective independent predictive indicator and represents a viable approach for immunotherapy in the context of PC. PKP3 may impact prognosis by broadly inhibiting immune cell infiltration and promoting the activation of tumor-associated signaling pathways.

In modern society, there is an increasing demand for energy storage solutions with superior energy density. Due to the low capacity of commercial graphite anode (372 mAh/g), high capacity and high stability anode materials for lithium-ion batteries (LIBs) have become a research hotspot. Among all kinds of anode materials, Ga-based materials have attracted much attention due to their high theoretical capacity and self-healing properties. These characteristics make it very suitable for the anode of high-performance LIBs and drive its commercialization. In this review, we analyzed the modification strategy, the feasibility of Ga-based lithium batteries, and how to utilize the electrochemical properties of Ga efficiently, to provide some insights into the design of high-performance batteries.

The aim of this work is to develop a novel nanofiber wound dressing with multiple functional properties that combines suitable mechanical properties, slow and controlled drug release, antifungal activity, and visual drug monitoring to accelerate wound healing while reducing systemic circulation of the drug, achieving reduced dose and side effects, and achieving patient satisfaction and compliance. In this paper, visualized nanofiber films were prepared using electrostatic spinning technology. This nanofiber wound dressing has soft tissue-like mechanical and antifungal properties and is biocompatible. In particular, the poly(N-isopropylacrylamide) (PNIPAAm)/tetraphenylethylene (TPE)/amphotericin B (AMB) nanofiber films showed good performance in terms of antifungal activity and cytocompatibility compared with medical gauze, and significantly accelerated the wound healing process in a mouse total wound defect model with PCL+PVP+TPE+AMB+PNIPAAm. The wound healing rate of nanofibrous membrane group was 100% at 14 days. In addition, histological analysis, collagen deposition and immunohistochemistry showed, for example, fewer inflammatory cells, more fibroblasts around the damaged area, increased wound epithelial atrophy, reduced granulation tissue, connective tissue reconstruction, epithelial tissue formation, and abundant small angiogenesis in the dermis near the epidermis; a higher level of collagen deposition fraction of 49.97%; and a simultaneous reduction in HIF-1α production and upregulated the expression of CD31. In conclusion, this antifungal nanofiber film showed promising applications throughout the skin wound healing process.

Abstract Tobacco is be sensitively affected by chilling injury in the vigorous growth period, which can easily lead to tobacco leaf browning during flue-curing and quality loss, however, the physiological response of tobacco in the prosperous period under low temperature stress is unclear. The physiological response parameters of two tobacco varieties to low temperature stress were determined. The main results were as follows: ① For tobacco in the vigorous growing period subjected to low-temperature stress at 4–16 °C, the tissue structure of chloroplast changed and photosynthetic pigments significantly decreased compared with each control with the increase of intensity of low-temperature stress. ② For tobacco in the vigorous growing period at 10–16 °C, antioxidant capacity of the protective enzyme system, osmotic adjustment capacity of the osmotic adjusting system and polyphenol metabolism in plants gradually increased due to induction of low temperature with the increase of intensity of low-temperature stress. ③ Under low-temperature stress at 4 °C, the protective enzyme system, osmotic adjusting system and polyphenol metabolism of the plants played an insignificant role in stress tolerance, which cannot be constantly enhanced based on low-temperature resistance at 10 °C. This study confirmed that under the temperature stress of 10–16 °C, the self-regulation ability of tobacco will be enhanced with the deepening of low temperature stress, but there is a critical temperature between 4 and 10 °C. The self-regulation ability of plants under low temperature stress will be inhibited.

The electric mode is the main operational mode of dual-motor hybrid electric vehicles (HEVs), so the reliability of the dual-motor electric drive system (DEDS) is particularly important. To research the electromechanical coupling mechanism of the DEDS of HEVs, firstly, considering the time-varying mesh stiffness of gears and the nonlinear characteristics of inverters, an electromechanical coupling dynamics model of the DEDS was established, including the permanent magnet synchronous motor (PMSM) and the gear transmission system. Then, the electromechanical coupled dynamic characteristics of the DEDS in the single-motor and dual-motor drive modes were analyzed under steady-state and impact load conditions, respectively. The results show that the motor stator current frequency is modulated by the complicated gear meshing frequency, and the operation state of the gear transmission system can thus be monitored in the stator current. Impact load causes the instantaneous torsional vibration of the transmission system dominated by the first-order natural frequency, and the vibration characteristic frequency appears in the form of a side frequency in the stator current signal; moreover, compared with the single-motor drive mode, the speed synchronization error in the dual-motor drive mode will aggravate torsional vibration in the gear system. The impact energy of the gear system caused by external impact load can be suppressed by reducing the speed synchronization error.

Hepatocellular carcinoma (HCC) is a leading cause of mortality. Checkpoint inhibitors of programmed cell death protein‐1 (PD‐1) and programmed death‐ligand 1 (PD‐L1) have shown great efficacy, but lack biomarkers that predict response. Circulating tumor cells (CTCs) have promise as a liquid‐biopsy biomarker; however, data on HCC CTCs expressing PD‐L1 have not been reported. We sought to detect PD‐L1‐expressing HCC‐CTCs and investigated their role as a prognostic and predictive biomarker. Using an antibody‐based platform, CTCs were enumerated/phenotyped from a prospective cohort of 87 patients with HCC (49 early‐stage, 22 locally advanced, and 16 metastatic), 7 patients with cirrhosis, and 8 healthy controls. Immunocytochemistry identified total HCC CTCs (4′,6‐diamidino‐2‐phenylindole–positive [DAPI+]/cytokeratin‐positive [CK+]/clusters of differentiation 45–negative [CD45−]) and a subpopulation expressing PD‐L1 (DAPI+/CK+/PD‐L1+/CD45−). PD‐L1+ CTCs were identified in 4 of 49 (8.2%) early‐stage patients, but 12 of 22 (54.5%) locally advanced and 15 of 16 (93.8%) metastatic patients, accurately discriminating early from locally advanced/metastatic HCC (sensitivity = 71.1%, specificity = 91.8%, area under the receiver operating characteristic curve = 0.807; P

Selective detection of l-lactate levels in foods, clinical, and bacterial fermentation samples has drawn intensive attention. Many fluorescent biosensors based on non-stereoselective recognition elements have been developed for lactate detection. Herein, the allosteric transcription factor STLldR from Salmonella enterica serovar Typhimurium LT2 was identified to be stereo-selectively respond to l-lactate. Then, STLldR was combined with Förster resonance energy transfer (FRET) to construct a fluorescent l-lactate biosensor FILLac. FILLac was further optimized by truncating the N- and C-terminal amino acids of STLldR between cyan and yellow fluorescent proteins. The optimized biosensor FILLac10N0C exhibited a maximum emission ratio change (ΔRmax) of 33.47 ± 1.91%, an apparent dissociation constant (Kd) of 6.33 ± 0.79 μM, and a limit of detection of 0.68 μM. FILLac10N0C was applied in 96-well microplates to detect l-lactate in bacterial fermentation samples and commercial foods such as Jiaosu and yogurt. The quantitation results of FILLac10N0C exhibited good agreement with that of a commercial l-lactate biosensor SBA-40D bioanalyzer. Thus, the biosensor FILLac10N0C compatible with high-throughput detection may be a potential choice for quantitation of l-lactate in different biological samples.

This study aimed to develop a simple, high-throughput method based on modified QuEChERS (quick, easy, cheap, effective, rugged, and safe) followed by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF/MS) for the rapid determination of multi-class pesticide residues in raw milk. With acidified acetonitrile as the extraction solvent, the raw milk samples were pretreated with the modified QuEChERS method, including extraction, salting-out, freezing, and clean-up processes. The target pesticides were acquired in a positive ion electrospray ionization mode and an All ions MS/MS mode. The developed method was validated, and good performing characteristics were achieved. The screening detection limits (SDL) and limits of quantitation (LOQ) for all the pesticides ranged within 0.1–20 and 0.1–50 μg/kg, respectively. The recoveries of all analytes ranged from 70.0% to 120.0% at three spiked levels (1 × LOQ, 2 × LOQ, and 10 × LOQ), with relative standard deviations less than 20.0%. The coefficient of determination was greater than 0.99 within the calibration linearity range for the detected 195 pesticides. The method proved the simple, rapid, high throughput screening and quantitative analysis of pesticide residues in raw milk.

The ongoing development of wireless sensor networks has been greatly restricted because of scarce spectrum resources, limited battery power, and ineffective topologic structures. Thus, how to construct a suitable topological structure and allocate the appropriate node channels has become an urgent problem. In this study, we built a game model that took into account the influence of channel allocation and topology structure on network performance. The game model considered the nodes in wireless sensor networks to be players and took transmitting power, node channels, and node rest energy into account to establish the income function. Then, the model certified that it has Nash equilibrium. Next, we propose an energy-optimized game algorithm joint topology and channel for wireless sensor network (CETGA) in accordance with the game model. The CETGA algorithm improved each node’s income by changing the transmitting power and node channel gradually, assuming that the network retained connectivity. Then, we demonstrated that the algorithm could converge to a Pareto optimal. Finally, we used MATLAB software to verify the simulation. The results show that the topology created by CETGA is with low interference and long lifetime. In addition, the nodes’ average residual energy is more balanced and the network robustness and real time are improved.

Abstract Background Sequencing analysis of circulating tumor cells (CTCs) enables “liquid biopsy” to guide precision oncology strategies. However, this requires low-template whole genome amplification (WGA) that is prone to errors and biases from uneven amplifications. Currently, quality control (QC) methods for WGA products, as well as the number of CTCs needed for reliable downstream sequencing, remain poorly defined. We sought to define strategies for selecting and generating optimal WGA products from low-template input as it relates to their potential applications in precision oncology strategies. Methods Single pancreatic cancer cells (HPAF-II) were isolated using laser microdissection. WGA was performed using multiple displacement amplification (MDA), multiple annealing and looping based amplification (MALBAC) and PicoPLEX. Quality of amplified DNA products were assessed using a multiplex/RT-qPCR based method that evaluates for 8-cancer related genes and QC-scores were assigned. We utilized this scoring system to assess the impact of de novo modifications to the WGA protocol. WGA products were subjected to Sanger sequencing, array comparative genomic hybridization (aCGH) and next generation sequencing (NGS) to evaluate their performances in respective downstream analyses providing validation of the QC-score. Results Single-cell WGA products exhibited a significant sample-to-sample variability in amplified DNA quality as assessed by our 8-gene QC assay. Single-cell WGA products that passed the pre-analysis QC had lower amplification bias and improved aCGH/NGS performance metrics when compared to single-cell WGA products that failed the QC. Increasing the number of cellular input resulted in improved QC-scores overall, but a resultant WGA product that consistently passed the QC step required a starting cellular input of at least 20-cells. Our modified-WGA protocol effectively reduced this number, achieving reproducible high-quality WGA products from ≥5-cells as a starting template. A starting cellular input of 5 to 10-cells amplified using the modified-WGA achieved aCGH and NGS results that closely matched that of unamplified, batch genomic DNA. Conclusion The modified-WGA protocol coupled with the 8-gene QC serve as an effective strategy to enhance the quality of low-template WGA reactions. Furthermore, a threshold number of 5–10 cells are likely needed for a reliable WGA reaction and product with high fidelity to the original starting template.

Applications of precision oncology strategies rely on accurate tumor genotyping from clinically available specimens. Fine needle aspirations (FNA) are frequently obtained in cancer management and often represent the only source of tumor tissues for patients with metastatic or locally advanced diseases. However, FNAs obtained from pancreas ductal adenocarcinoma (PDAC) are often limited in cellularity and/or tumor cell purity, precluding accurate tumor genotyping in many cases. Digital PCR (dPCR) is a technology with exceptional sensitivity and low DNA template requirement, characteristics that are necessary for analyzing PDAC FNA samples. In the current study, we sought to evaluate dPCR as a mutation analysis tool for pancreas FNA specimens. To this end, we analyzed alterations in the KRAS gene in pancreas FNAs using dPCR. The sensitivity of dPCR mutation analysis was first determined using serial dilution cell spiking studies. Single-cell laser-microdissection (LMD) was then utilized to identify the minimal number of tumor cells needed for mutation detection. Lastly, dPCR mutation analysis was performed on 44 pancreas FNAs (34 formalin-fixed paraffin-embedded (FFPE) and 10 fresh (non-fixed)), including samples highly limited in cellularity (100 cells) and tumor cell purity (1%). We found dPCR to detect mutations with allele frequencies as low as 0.17%. Additionally, a single tumor cell could be detected within an abundance of normal cells. Using clinical FNA samples, dPCR mutation analysis was successful in all preoperative FNA biopsies tested, and its accuracy was confirmed via comparison with resected tumor specimens. Moreover, dPCR revealed additional KRAS mutations representing minor subclones within a tumor that were not detected by the current clinical gold standard method of Sanger sequencing. In conclusion, dPCR performs sensitive and accurate mutation analysis in pancreas FNAs, detecting not only the dominant mutation subtype, but also the additional rare mutation subtypes representing tumor heterogeneity.

Concrete compressive strength is an important parameter of material properties for assessing seismic performance of reinforced concrete (RC) structures, which has a certain level of uncertainty due to its inherent variability. In this paper, the method of concrete strength validation of finite element model using smart aggregate (SA)-based stress monitoring is proposed. The FE model was established using Open System for Earthquake Engineering Simulation (OpenSEES) platform. The concrete strengths obtained from the material test, peak stress of SA, and estimated concrete strength based on SA stress were employed in FE models. The lateral displacement monitored by Liner variable differential transformer and vertical axial load monitored by load cell in the experiment are applied in the model. By comparing the global response (i.e., lateral reaction force and hysteretic loop), local response (i.e., concrete stress, rebar strain, and cross-section moment) and corresponding root-mean-square error obtained from experiment and numerical analysis, the capabilities of validation of FE model using SA-based stress monitoring method were demonstrated.