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Purpose: Development and validation of a radiomics model for predicting occult locally advanced esophageal squamous cell carcinoma (LA-ESCC) on computed tomography (CT) radiomic features before implementation of treatment. Methods: The study retrospectively collected 574 patients with esophageal squamous cell carcinoma (ESCC) from two medical centers, which were divided into three cohorts for training, internal and external validation. After delineating volume of interest (VOI), radiomics features were extracted and subjected to feature selection using three robust methods. Subsequently, 10 machine learning models were constructed, among which the optimal model was utilized to establish a radiomics signature. Furthermore, a predictive nomogram incorporating both clinical and radiomics signatures was developed. The performance of these models was evaluated through receiver operating characteristic curves, calibration curves, decision curve analysis as well as measures including accuracy, sensitivity, and specificity. Results: A total of 19 radiomics features were selected. The multilayer perceptron (MLP), which was found to be optimal, achieved an AUC of 0.919, 0.864 and 0.882 in the training, internal and external validation cohorts, respectively. Similarly, MLP showed good accuracy in distinguish occult LA-ESCC in subgroup of cT1–2N0M0 diagnosed by clinicians with 0.803 and 0.789 in two validation cohorts respectively. By incorporating the radiomics signature with clinical signature, a predictive nomogram demonstrated superior prediction performance with an AUC of 0.877 and accuracy of 0.85 in external validation cohort. Conclusion: The radiomics and machine learning model can offers improved accuracy in prediction of occult LA-ESCC, providing valuable assistance to clinicians when choosing treatment plans.

Shale oil is mainly stored in the nano–micro-pores of shale in the form of adsorption or in a free state. Among them, only free-state oil is the main contributor to shale oil production under natural elastic energy. Therefore, it is crucial to evaluate the movability of crude oil effectively. In this paper, focusing on the Jurassic shale oil reservoir core in the middle-eastern Sichuan region of China, low-field nuclear magnetic resonance (NMR) technology is used to analyze the basic characteristics of shale oil core samples. Experiments on the low-field NMR one-dimensional and two-dimensional spectrum characteristics of the original core, heat-treated core, and thermogravimetric-treated shale core are carried out. The effects of the TG-MS method, T2 method, and the volatilization of light oil components on the movability of shale oil reservoirs are analyzed, and the movability characteristics of shale oil reservoirs in the middle-eastern Sichuan region are preliminarily clarified. The results show that under thermal treatment, the distribution range of the two-dimensional spectrum of the core oil occurrence area is significantly reduced, and the T1 and T2 distribution ranges are reduced by 10.9% and 60.7%, respectively. According to the TG-MS method, the mobile oil, bound oil, and adsorbed oil account for 74.7%, 8.1%, and 17.2%, respectively. The quantitative calculation of movable oil saturation by NMR combined with heat treatment is 65.6%, which is lower than that calculated using the thermogravimetric method. In order to calculate the movability more accurately, the scale effect between different samples should be considered. This study could provide a theoretical basis for the subsequent shale oil development program.

Abstract Background Gallbladder carcinoma (GBC) is a highly malignant tumor with a poor overall prognosis. This study aimed to identify the characteristic microRNAs (miRNAs) of GBC and the competing endogenous RNA (ceRNA) regulatory mechanisms. Methods The microarray data of GBC tissue samples and normal gallbladder (NGB) tissue samples from the Gene Expression Omnibus (GEO) database was downloaded. GBC-related differentially expressed miRNAs (DE-miRNAs) were identified by inter-group differential expression analysis and weighted gene co-expression network analysis (WGCNA). Machine learning algorithms were used to screen the characteristic miRNA based on the intersect between least absolute shrinkage and selection operator (LASSO) and Support vector machine-recursive feature elimination (SVM-RFE). Based on the differential expression analysis of GEO database, the ceRNA network of characteristic miRNA was predicted and constructed. The biological functions of the ceRNA network were revealed by carrying out the gene enrichment analysis was implemented. We further screened the key genes of ceRNA network and constructed a protein-protein interaction (PPI) network, and predicted and generated the transcription factors (TFs) network of signature miRNAs. The expression of characteristic miRNA in clinical samples was verified by quantitative real-time polymerase chain reaction (qRT-PCR). Results A total of 131 GBC-related DE-miRNAs were obtained. The hsa-miR-4770 was defined as characteristic miRNA for GBC. The ceRNA network containing 211 mRNAs, one miRNA, two lncRNAs, and 48 circRNAs was created. Gene enrichment analysis suggested that the downstream genes were mainly involved in actin filament organization, cell-substrate adhesion, cell-matrix adhesion, reactive oxygen species metabolic process, glutamine metabolic process and extracellular matrix (ECM)-receptor interaction pathway. 10 key genes in the network were found to be most correlated with disease, and involved in cell cycle-related processes, p53, and extrinsic apoptotic signaling pathways. The qRT-PCR result demonstrated that hsa-miR-4770 is down-regulated in GBC, and the expression trend is consistent with the public database. Conclusions We identified hsa-miR-4770 as the characteristic miRNA for GBC. The ceRNA network of hsa-miR-4770 may play key roles in GBC. This study provided some basis for potential pathogenesis of GBC.

In spatially resolved transcriptomics, Stereo-seq facilitates the analysis of large tissues at the single-cell level, offering subcellular resolution and centimeter-level field-of-view. Our previous work on StereoCell introduced a one-stop software using cell nuclei staining images and statistical methods to generate high-confidence single-cell spatial gene expression profiles for Stereo-seq data. With advancements allowing the acquisition of cell boundary information, such as cell membrane/wall staining images, we updated our software to a new version, STCellbin. Using cell nuclei staining images, STCellbin aligns cell membrane/wall staining images with spatial gene expression maps. Advanced cell segmentation ensures the detection of accurate cell boundaries, leading to more reliable single-cell spatial gene expression profiles. We verified that STCellbin can be applied to mouse liver (cell membranes) and Arabidopsis seed (cell walls) datasets, outperforming other methods. The improved capability of capturing single-cell gene expression profiles results in a deeper understanding of the contribution of single-cell phenotypes to tissue biology. Availability & Implementation The source code of STCellbin is available at https://github.com/STOmics/STCellbin.

As genomic sequencing technology continues to advance, it becomes increasingly important to perform joint analyses of multiple datasets of transcriptomics. However, batch effect presents challenges for dataset integration, such as sequencing data measured on different platforms, and datasets collected at different times. Here, we report the development of BatchEval Pipeline, a batch effect workflow used to evaluate batch effect on dataset integration. The BatchEval Pipeline generates a comprehensive report, which consists of a series of HTML pages for assessment findings, including a main page, a raw dataset evaluation page, and several built-in methods evaluation pages. The main page exhibits basic information of the integrated datasets, a comprehensive score of batch effect, and the most recommended method for removing batch effect from the current datasets. The remaining pages exhibit evaluation details for the raw dataset, and evaluation results from the built-in batch effect removal methods after removing batch effect. This comprehensive report enables researchers to accurately identify and remove batch effects, resulting in more reliable and meaningful biological insights from integrated datasets. In summary, the BatchEval Pipeline represents a significant advancement in batch effect evaluation, and is a valuable tool to improve the accuracy and reliability of the experimental results. Availability & Implementation The source code of the BatchEval Pipeline is available at https://github.com/STOmics/BatchEval.

PurposeThe need for adjuvant therapy (AT) following neoadjuvant chemoimmunotherapy (nICT) and surgery in esophageal squamous cell cancer (ESCC) remains uncertain. This study aims to investigate whether AT offers additional benefits in terms of recurrence-free survival (RFS) for ESCC patients after nICT and surgery.MethodsRetrospective analysis was conducted between January 2019 and December 2022 from three centers. Eligible patients were divided into two groups: the AT group and the non-AT group. Survival analyses comparing different modalities of AT (including adjuvant chemotherapy and adjuvant chemoimmunotherapy) with non-AT were performed. The primary endpoint was RFS. Propensity score matching(PSM) was used to mitigate inter-group patient heterogeneity. Kaplan-Meier survival curves and Cox regression analysis were employed for recurrence-free survival analysis.ResultsA total of 155 nICT patients were included, with 26 patients experiencing recurrence. According to Cox analysis, receipt of adjuvant therapy emerged as an independent risk factor(HR:2.621, 95%CI:[1.089,6.310], P=0.032), and there was statistically significant difference in the Kaplan-Meier survival curves between non-AT and receipt of AT in matched pairs (p=0.026). Stratified analysis revealed AT bring no survival benefit to patients with pathological complete response(p= 0.149) and residual tumor cell(p=0.062). Subgroup analysis showed no significant difference in recurrence-free survival between non-AT and adjuvant chemoimmunotherapy patients(P=0.108). However, patients receiving adjuvant chemotherapy exhibited poorer recurrence survival compared to non-AT patients (p= 0.016).ConclusionIn terms of recurrence-free survival for ESCC patients after nICT and surgery, the necessity of adjuvant therapy especially the adjuvant chemotherapy, can be mitigated.

Abstract Tumor microenvironment (TME)‐triggered phototheranostic platform offers a feasible strategy to improve cancer diagnosis accuracy and minimize treatment side effects. Developing a stable and biocompatible molecular phototheranostic platform for TME‐activated second near‐infrared (NIR‐II) fluorescence imaging‐guided multimodal cascade therapy is a promising strategy for creating desirable anticancer agents. Herein, a new NIR‐II fluorescence imaging‐guided activatable molecular phototheranostic platform (IR‐FEP‐RGD‐S‐S‐S‐Fc) is presented for actively targeted tumor imaging and hydrogen sulfide (H2S) gas‐enhanced chemodynamic‐hypothermal photothermal combined therapy (CDT/HPTT). It is revealed for the first time that the coupling distance between IR‐FE and ferrocene is proportional to the photoinduced electron transfer (PET), and the aqueous environment is favorable for PET generation. The part of Cyclic‐RGDfK (cRGDfk) peptides can target the tumor and benefit the endocytosis of nanoparticles. The high‐concentration glutathione (GSH) in the TME will separate the fluorescence molecule and ferrocene by the GSH‐sensitive trisulfide bond, realizing light‐up NIR‐II fluorescence imaging and a cascade of trimodal synergistic CDT/HPTT/gas therapy (GT). In addition, the accumulation of hydroxyl radicals (•OH) and down‐regulation of glutathione peroxidase 4 (GPX4) can produce excessive harmful lipid hydroperoxides, ultimately leading to ferroptosis.

The conventional Archie formula struggles with the interpretation of water saturation from resistivity well log data due to the increasing complexity of exploration targets. This challenge has prompted researchers to explore alternative physical parameters, such as acoustic characteristics, for breakthroughs. Clarifying the influencing factors of porous media acoustic characteristics is one of the most important approaches to help understanding the mechanism of acoustic characteristics of carbonate reservoirs. The article uses digital rock technology to characterize the pore structure, quantitatively identify fractures and pore structures in carbonate rocks, and establish digital models. Through conventional acoustic testing, the pressure wave (P-wave) and shear wave (S-wave) velocities of rock samples at different water saturations are obtained, and the dynamic elastic modulus is calculated. A finite element calculation model is established using the digital rock computational model to provide a basis for fluid saturation calculation methods. Based on real digital rock models, different combinations of virtual fractures are constructed, and factors affecting acoustic parameters are analyzed. The study finds that as porosity increases, the velocity difference between porous cores and fractured cores also increases. These findings provide important technical support and a theoretical basis for interpreting acoustic well logging data and evaluating carbonate reservoirs with different pore and fracture types.

SiC, as a representative of the third generation semiconductors, is widely investigated in power devices and sensors. However, ohmic contacts, an important component for signal output of various SiC chips, have always faced challenges with unclear formation mechanism and difficulty to withstand high temperature. To solve such problems, two sets of NPN-type SiC ohmic contact were prepared, including Ti/TaSi2/Pt and Ni/W. Experimental results show that whether ohmic contact can be formed mainly depends on the contact metal. The alloy phase with lower work function is formed after high temperature annealing, which reduces the height and width of the Schottky barrier. For the prepared SiC ohmic contacts, It was demonstrated that the invasion of oxygen atoms cause contacts failure, and incorporation of barrier layer (Ta-based layer) and effective protective layer (Pt layer) determine whether high temperatures can be tolerated. Finally, piezoresistive 4H–SiC pressure sensor chips with dimensions of 3000 μm × 3000 μm × 200 μm were fabricated using the obtained ohmic contacts. Sensor chips output resistance were monitored up to 600 °C in air to show stability of the ohmic contact. The highly stable and high temperature ohmic contact can be applied in a variety of SiC devices.

Abstract Microelectromechanical system (MEMS) pressure sensors based on silicon are widely used and offer the benefits of miniaturization and high precision. However, they cannot easily withstand high temperatures exceeding 150 °C because of intrinsic material limits. Herein, we proposed and executed a systematic and full-process study of SiC-based MEMS pressure sensors that operate stably from −50 to 300 °C. First, to explore the nonlinear piezoresistive effect, the temperature coefficient of resistance (TCR) values of 4H-SiC piezoresistors were obtained from −50 to 500 °C. A conductivity variation model based on scattering theory was established to reveal the nonlinear variation mechanism. Then, a piezoresistive pressure sensor based on 4H-SiC was designed and fabricated. The sensor shows good output sensitivity (3.38 mV/V/MPa), accuracy (0.56% FS) and low temperature coefficient of sensitivity (TCS) (−0.067% FS/°C) in the range of −50 to 300 °C. In addition, the survivability of the sensor chip in extreme environments was demonstrated by its anti-corrosion capability in H2SO4 and NaOH solutions and its radiation tolerance under 5 W X-rays. Accordingly, the sensor developed in this work has high potential to measure pressure in high-temperature and extreme environments such as are faced in geothermal energy extraction, deep well drilling, aeroengines and gas turbines.

Obsessive-compulsive disorder (OCD) is a common mental disease, which can exist as a separate disease or become one of the symptoms of other mental diseases. With the development of society, statistically, the incidence rate of obsessive-compulsive disorder has been increasing year by year. At present, in the diagnosis and treatment of OCD, The clinical performance of patients measured by scales is no longer the only quantitative indicator. Clinical workers and researchers are committed to using neuroimaging to explore the relationship between changes in patient neurological function and obsessive-compulsive disorder. Through machine learning and artificial learning, medical information in neuroimaging can be better displayed. In this article, we discuss recent advancements in artificial intelligence related to neuroimaging in the context of Obsessive-Compulsive Disorder.

Poly(methyl methacrylate) (PMMA), with a glass transition temperature (Tg) over 100 °C, shows good mechanical and optical properties and has broad applications after being machined with single-point diamond turning (SPDT) at room temperature. Because of the high Tg, current efforts mostly focus on optimizing machining parameters to improve workpiece precision without considering the modification of material properties. Cryogenic cooling has been proven to be an effective method in assisting ultra-precision machining for certain types of metals, alloys, and polymers, but has never been used for PMMA before. In this work, cryogenic cooling was attempted during the SPDT of PMMA workpieces to improve surface quality. The machinability and surface properties of cryogenically cooled PMMA were investigated based on the mechanical properties at corresponding temperatures. Nanoindentation tests show that, when temperature is changed from 25 °C to 0 °C, the hardness and Young’s modulus are increased by 37% and 22%, respectively. At these two temperature points, optimal parameters including spindle speed, feed rate and cut depth were obtained using Taguchi methods to obtain workpieces with high surface quality. The surface quality was evaluated based on the total height of the profile (Pt) and the arithmetic mean deviation (Ra). The measurement results show that the values of Pt and Ra of the workpiece machined at 0 °C are 124 nm and 6 nm, respectively, while the corresponding values of that machined at 25 °C are 291 nm and 11 nm. The test data show that cryogenic machining is useful for improving the form accuracy and reducing the surface roughness of PMMA. Moreover, the relationship between temperature, material properties and machinability weas established with dynamic mechanical analysis (DMA) data and a theoretical model. This can explain the origin of the better surface quality of the cryogenic material. The basis of this is that temperature affects the viscoelasticity of the polymer and the corresponding mechanical properties due to relaxation. Then, the material property changes will affect surface profile formation during machining. The experimental results and theoretical analysis show that cryogenically cooled PMMA has good machinability and improved surface quality when using SPDT compared to that at ambient temperature.

As an important therapeutic target in breast cancer, HER2 expression assessed by immunohistochemistry plays a critical role in breast cancer treatment. Recent advances in HER2 antibody–drug conjugate therapy have enabled patients with HER2-low expression breast cancer to benefit from the drugs. However, it is not known whether the HER2-low expression in breast cancer FFPE blocks would be lost as storage time increased. In this study, we aimed to assess the loss of HER2 antigenicity in stored FFPE blocks of breast cancer and the rescue effect of modifying the protocol of antigen staining. We selected archived HER2-low breast cancer FFPE blocks with stored time ranging from 1 year to over 15 years and re-detected the expression of HER2. Our study showed that HER2 antigenicity loss increased with storage time and could cause false negativity in HER2-low detection. Moreover, we showed that by either increasing the antigen retrieval time or applying the tyramide signal amplification (TSA) kit, the HER2 signal can be rescued and detected in about half of the cases with HER2-low loss without causing false positivity.

The oxidation resistance of TiAl alloys is crucial for their commercial application. In this paper, a cyclic oxidation test with stable air circulation was designed to investigate the cyclic oxidation behavior of the TNM alloy and 4822 alloy at 800 °C and to analyze the phase, morphology, and thermal stress evolution of the oxide layer. The oxidation weight gain curves of both alloys are found to be in parabolic form, and the oxidation reaction orders of the TNM alloy and 4822 alloy are 2.374 and 1.838, respectively. The Nb and Mo elements enhance the antioxidant performance of the TNM alloy by inhibiting the dissolution and diffusion of oxygen, Ti, and Al atoms in the TiAl alloy. The thermal stress evolution of the two alloys during the heating and cooling phases of the cyclic oxidation process are calculated separately, and it is found that the thermal stresses in the TNM alloy are smaller than those in the 4822 alloy, while the maximum thermal stresses appear at the oxide/substrate interface rather than inside the oxide scale, which quantitatively explains the oxidation peeling resistance of the two alloys.

Abstract Background Primary focal hyperhidrosis (PFH) is an autonomic neurological disease in which exocrine glands are oversecreted due to autonomic dysfunction of the sympathetic nervous system. Chrna1 promotes the pathogenesis of PFH. We aimed to check if downregulating of Chrna1 by cisatracurium could alleviate the symptoms of PFH. Methods The effect of cisatracurium in a hyperhidrosis mice model induced by pilocarpine hydrochloride was monitored for sweat gland secretion, and ultrastructural sweat secretory granules in sweat glands were analyzed. Meanwhile, markers of hyperhidrosis were checked, and release of Bdnf and Nrg1 from sympathetic ganglia axon was tested. Furthermore, the mechanism of cisatracurium function was evaluated in vitro using HEK293 expressing Chrna1. Finally, the effect of cisatracurium was determined in the hyperhidrosis mice model with overexpression or downregulation of Chrna1. Results In hyperhidrosis mice, pretreatment with cisatracurium effectively inhibited sweat secretion, along with fewer particle secretion in sweat glands. The molecular markers of hyperhidrosis (Aqp5 and Cacna1c) were inhibited by cisatracurium, acetylcholine (Ach) level in serum was found decreased. Neurotrophic factors (Bdnf and Nrg1) secreted by sympathetic axon activation were also inhibited. At last, it was confirmed that cisatracurium could not alter the gene or protein expression level of Chrna1, but could block the ion channel. Overexpression of Chrna1 abolished the effect of cisatracurium on hyperhidrosis, while cisatracurium could not function more in siChrna1‐treated mice. Conclusion Our results suggested that pretreatment of cisatracurium could alleviate hyperhidrosis in mice, probably through blocking the ion channel function of Chrna1.

Abstract Background Long noncoding RNAs (lncRNAs) play an important role in regulating biological activities and their prediction is significant for exploring biological processes. Long short-term memory (LSTM) and convolutional neural network (CNN) can automatically extract and learn the abstract information from the encoded RNA sequences to avoid complex feature engineering. An ensemble model learns the information from multiple perspectives and shows better performance than a single model. It is feasible and interesting that the RNA sequence is considered as sentence and image to train LSTM and CNN respectively, and then the trained models are hybridized to predict lncRNAs. Up to present, there are various predictors for lncRNAs, but few of them are proposed for plant. A reliable and powerful predictor for plant lncRNAs is necessary. Results To boost the performance of predicting lncRNAs, this paper proposes a hybrid deep learning model based on two encoding styles (PlncRNA-HDeep), which does not require prior knowledge and only uses RNA sequences to train the models for predicting plant lncRNAs. It not only learns the diversified information from RNA sequences encoded by p-nucleotide and one-hot encodings, but also takes advantages of lncRNA-LSTM proposed in our previous study and CNN. The parameters are adjusted and three hybrid strategies are tested to maximize its performance. Experiment results show that PlncRNA-HDeep is more effective than lncRNA-LSTM and CNN and obtains 97.9% sensitivity, 95.1% precision, 96.5% accuracy and 96.5% F1 score on Zea mays dataset which are better than those of several shallow machine learning methods (support vector machine, random forest, k-nearest neighbor, decision tree, naive Bayes and logistic regression) and some existing tools (CNCI, PLEK, CPC2, LncADeep and lncRNAnet). Conclusions PlncRNA-HDeep is feasible and obtains the credible predictive results. It may also provide valuable references for other related research.

The formability of magnesium alloys at ambient temperature can be enhanced by alloying additions such as Ca and RE elements, which is ascribed to the weakened basal texture. To produce magnesium alloy sheets with excellent comprehensive performance, the evolution of texture characterization during fabrication process and subsequent effect of texture on mechanical properties are vital controlling factors. In this investigation, three experimental Mg-3Al series alloys were hot rolled and annealed to sheets with 1 mm thickness. The microstructure evolution during rolling and annealing process was investigated. Furthermore, the influence of texture on tensile properties along different tensile directions was also studied. The results show that weakened basal texture and refined grains were achieved with the co-addition of Ca and RE element. However, strengthening of mechanical properties wasn't obtained. During hot rolling process, microstructure was refined, second phase particles broken, and basal texture was increased. While basal texture was weakened during annealing process. Recrystallization behavior influenced by formation of second phase was dominated to attenuate basal texture. Tensile deformation behavior was controlled by basal slip and followed Schmid factor criterion. Moreover, the weakened basal texture and activation of non-basal slips during hot rolling process can contribute to diminish the anisotropy of tensile properties.

Tumor-associated macrophage (TAM) is a major component of tumor microenvironment (TME) and plays critical role in the progression of cancer metastasis. However, TAM-mediated regulation in gallbladder cancer (GBC) has not been fully characterized. Here, we found that exosomes derived from GBC cell polarized macrophage to M2 phenotype, which then facilitated the invasion and migration of GBC cells. We discovered that leptin was enriched in GBC cell-derived exosomes. Exosomal leptin levels promoted invasion and migration of GBC-SD cells. The inhibition of leptin not only attenuated M2 macrophage of polarization but also inhibited the invasive and migratory ability of GBC cell. In addition, GBC-SD cell-derived exosomal leptin induced M2 polarization of macrophage via activation of STAT3 signal pathway. Taken together, our results suggested that GBC cells secrete exosome-enclosed leptin facilitated cell invasion and migration via polarizing TAM.

The appearance and magnitude of the immune response and the related factors correlated with SARS-CoV-2 vaccination need to be defined. Here, we enrolled a prospective cohort of 52 participants who received two doses of inactivated vaccines (BBIBP-CorV). Their serial plasma samples (n = 260) over 2 months were collected at five timepoints. We measured antibody responses (NAb, S-IgG and S-IgM) and routine blood parameter. NAb seroconversion occurred in 90.7% of vaccinated individuals and four typical NAb kinetic curves were observed. All of the participants who seroconverted after the first dose were females and had relatively high prevaccine estradiol levels. Moreover, those without seroconversion tended to have lower lymphocyte counts and higher serum SAA levels than those who experienced seroconversion. The NAb titers in young vaccine recipients had a significantly higher peak than those in elderly recipients. S-IgG and S-IgM dynamics were accompanied by similar trends in NAb. Here, we gained insight into the dynamic changes in NAbs and preliminarily explored the prevaccine blood parameters related to the kinetic subclasses, providing a reference for vaccination strategies.

Successful recovery from hepatectomy is partially contingent upon the rate of residual liver regeneration. The traditional Chinese medicines known as Periplaneta americana extracts (PAEs) positively influence wound healing by promoting tissue repair. However, the effect of PAEs on liver regeneration is unknown. We used a mouse liver regeneration model after 70% partial hepatectomy (PH) and a hepatocyte culture to determine whether PAEs can promote liver regeneration as effectively as skin regeneration and establish their modes of action. L02 cells were divided into serum-starved control (NC) and three PAEs (serum starvation + 0.1 mg/ml, 0.5 mg/ml, or 1 mg/ml PAEs) groups. L02 cell proliferation was assessed at 24 h, 48 h, and 72 h by CCK-8 assay. Forty male C57 mice were randomly divided into control (NC), normal saline (NS), PAEs400 (400 mg/kg/d), and PAEs800 (800 mg/kg/d) groups (n = 10 per group). The NS and both PAEs groups were administered normal saline and PAEs, respectively, by gavage for 10 days. Two hours after the tenth gavage, the NS and both PAEs groups were subjected to 70% PH and the residual liver was harvested after 48 h. The hepatic regeneration rate was evaluated and hepatocyte proliferation was estimated by immunohistochemical (IHC) staining for Ki-67. Twelve DEG libraries (three samples per group) were prepared and sequencing was performed in an Illumina HiSeq 2000 (Mus_musculus) at the Beijing Genomics Institute. The genes expressed in the liver tissues and their expression profiles were analyzed by bioinformatics. KEGG was used to annotate, enrich, and analyze the pathways. PAEs promoted hepatocyte proliferation in vitro and in vivo and accelerated mouse liver regeneration after 70% PH. The screening criteria were fold change (FC) ≥ 2 and q-value < 0.001. We identified 1,092 known DEGs in PAEs400 and PAEs800. Of these, 153 were categorized in cellular processes. The KEGG analysis revealed that the aforementioned DEGs participated in several signaling pathways closely associated with cell proliferation including PI3K-Akt, MAPK, Apelin, Wnt, FoxO, mTOR, Ras, VEGF, ErbB, Hippo, and AMPK. It was concluded that PAEs can effectively improve liver regeneration via the synergistic activation of different signaling pathways.

To eliminate the noise and temperature drift in an Micro-Electro-Mechanical Systems (MEMS) gyroscope’s output signal for improving measurement accuracy, a parallel processing model based on Multi-objective particle swarm optimization based on variational modal decomposition-time-frequency peak filter (MOVMD–TFPF) and Beetle antennae search algorithm- Elman neural network (BAS–Elman NN) is established. Firstly, variational mode decomposition (VMD) is optimized by multi-objective particle swarm optimization (MOPSO); then, the best decomposition parameters [kbest,abest] can be obtained. Secondly, the gyroscope output signals are decomposed by VMD optimized by MOPSO (MOVMD); then, the intrinsic mode functions (IMFs) obtained after decomposition are classified into a noise segment, mixed segment, and drift segment by sample entropy (SE). According to the idea of a parallel model, the noise segment can be discarded directly, the mixed segment is denoised by time-frequency peak filtering (TFPF), and the drift segment is compensated at the same time. In the compensation part, the beetle antennae search algorithm (BAS) is adopted to optimize the network parameters of the Elman neural network (Elman NN). Subsequently, the double-input/single-output temperature compensation model based on the BAS-Elman NN is established to compensate the drift segment, and these processed segments are reconstructed to form the final gyroscope output signal. Experimental results demonstrate the superiority of this parallel processing model; the angle random walk of the compensated gyroscope output is decreased from 0.531076 to 5.22502 × 10−3°/h/√Hz, and its bias stability is decreased from 32.7364°/h to 0.140403°/h, respectively.

Abstract Background Immune checkpoint blockade targeting PD-1/PD-L1 has shown efficacy in several types of cancers. However, the correlation between PD-L1/PD-1 expression and the specific clinicopathological features in papillary thyroid carcinoma (PTC) has not been investigated. Methods We examined the immunohistochemical expression of PD-L1, PD-1, and BRAF V600E on whole-tissue sections from 126 cases of primary PTC more than 1 cm in size. The correlation between the PD-L1/PD-1 expression and the clinicopathological features was evaluated. Results PD-L1 was positively expressed in 53.2% PTCs, and its expression was positively correlated with rich tumor-infiltrating lymphocytes (TILs), background chronic lymphocytic thyroiditis (CLT), female gender, absence of psammoma bodies, and PD-1 expression. Among these parameters, rich TILs, female gender, and absence of psammoma bodies were independent factors affecting PD-L1 expression on the multivariate logistic regression analysis. PD-1 expression was detected in the TILs and was positively correlated with rich TILs, background CLT, and absence of stromal calcification. Lack of stromal calcification was an independent factor affecting PD-1 expression. Neither PD-L1 nor PD-1 expression showed significant correlation with BRAF V600E expression. Conclusions Our results show that the distinctive pathological features of PTCs, including TILs, background CLT, female gender, psammoma bodies, and stromal calcification, are useful parameters for predicting PD-L1 or PD-1 expression.

The effect of Gd, Ce and Y elements on texture, recrystallization and mechanical properties of Mg–1.5Zn alloys was investigated. The results show that the addition of Gd, Ce and Y elements in Mg–1.5Zn alloy, which rolled at 450 °C and subsequently annealed at 350 °C for 1h, can effectively weaken and modify the basal texture, characterized by the splitting basal pole toward to transverse direction, leading to the yield and tensile strength, the highest along the rolling direction and the lowest along the transverse direction. Besides, the unique basal texture contributes to the significant improvement of elongation at room temperature. Electron back scattering diffraction (EBSD) analysis indicated that the non-basal texture in Mg–1.5Zn–0.2RE alloys can be attributed to obstructive effect of static recrystallization and the non-basal orientation grains nucleation near pre-existing grain boundaries during annealing. Specially, the Mg–1.5Zn–0.2Gd sheet exhibits much excellent plasticity with the elongation of 27% than Mg–1.5Zn–0.2Ce and Mg–1.5Zn–0.2Y alloys, resulting from the less and smaller second phase of MgZnGd.

Temporomandibular joint osteoarthritis (TMJ-OA), mainly exhibit extracellular matrix loss and condylar cartilage degradation, is the most common chronic and degenerative maxillofacial osteoarthritis; however, no efficient therapy for TMJ-OA exists due to the poor understanding of its pathological progression. MicroRNA (miR)-140-5p is a novel non-coding microRNAs (miRNAs) that expressed in osteoarthritis specifically. To investigate the molecular mechanisms of miR-140-5p in TMJ-OA, primary mandibular condylar chondrocytes (MCCs) from C57BL/6N mice were treated with interleukins (IL)-1β or transfected with miR-140-5p mimics or inhibitors, respectively. The expression of matrix metallopeptidase (MMP)-13, miR-140-5p, nuclear factor (NF)-kB, Smad3 and transforming growth factor (TGF)-β3 were examined by western blotting or quantitative reverse-transcription polymerase chain reaction (qRT-PCR). The interaction between the potential binding sequence of miR-140-5p and the 3′-untranslated region (3′UTR) of Smad3 mRNA was testified by dual-luciferase assay. Small Interfering RNA of Smad3 (Si-Smad3) was utilized to further identify the role of Smad3 mediated by miR-140-5p. The data showed MMP13, miR-140-5p and NF-kB increased significantly in response to IL-1β inflammatory response in MCCs, meanwhile, Smad3 and TGF-β3 reduced markedly. Moreover, transfection of miR-140-5p mimics significantly suppressed the expression of Smad3 and TGF-β3 in MCCs, while miR-140-5p inhibitors acted in a converse manner. As the luciferase reporter of Smad3 mRNA observed active interaction with miR-140-5p, Smad3 was identified as a direct target of miR-140-5p. Additionally, the expression of TGF-β3 was regulated upon the activation of Smad3. Together, these data suggested that miR-140-5p may play a role in regulating mandibular condylar cartilage homeostasis and potentially serve as a novel prognostic factor of TMJ-OA-like pathology.

Background: Pyrethroids have been widely used in residential and agricultural areas. However, little is known about the effects of prenatal exposure to deltamethrin on cognition in early development of offspring. In this study, the effects of prenatal exposure to deltamethrin on learning and memory abilities, N-methyl-D-aspartate receptor (NMDAR) subunits, brain derived neurotrophic factor (BDNF), Tyrosine kinase B (TrkB) receptor, and phosphorylated cAMP response element binding protein (pCREB) in the hippocampus of offspring rats were investigated.Experimental Approaches: Groups each of six female SD rats, as F0-generation, were administered with deltamethrin (0, 0.54, 1.35, and 2.7, 9 mg/kg), or memantine (10 mg/kg), or co-administered with deltamethrin (9 mg/kg) and memantine (10 mg/kg) daily by gavage during pregnancy. The learning and memory ability was evaluated using Morris water maze (MWM) task on postnatal day 21. The expression of NMDAR (GluN1, GluN2A, and GluN2B), BDNF, pTrkB/TrkB, and pCREB/CREB in hippocampus were assessed with western blotting.Results: Prenatal exposure to a relatively low dose of deltamethrin (2.7, 1.35, and 0.54 mg/kg) had no impact on learning and memory abilities or the expression of NMDAR, BDNF, pTrkB, and pCREB in the hippocampus of the exposed offspring. The group treated with 9 mg/kg deltamethrin showed impaired cognitive abilities and decreased expression levels of GluN1, GluN2A, GluN2B, BDNF, pCREB/CREB, and pTrkB/TrkB in the hippocampus. However, the declined cognitive ability were ameliorated by memantine treatment with increased GluN1, GluN2A, GluN2B, BDNF, pCREB/CREB, and pTrkB/TrkB expression in the hippocampus.Conclusion and Implications: Prenatal exposure to a relatively high does of deltamethrin (9 mg/kg) alters cognition in offsprings and that this cognitive dysfunction can be ameliorated by memantine treatment. Moreover, NMDAR/BDNF signaling may be associated with the effects of prenatal exposure to deltamethrin on cognitive ability in offspring.