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Enlargement of micropores in zeolitic imidazolate framework particles into mesopores is achieved via an ethylene glycol-assisted aqueous etching method. The etched carbon shows a higher specific capacitance than unetched one at high scan rates.

The researchers of this study selected five journals in the field of education and conducted a series of analyses regarding publications dating from 2010 to 2019 to investigate the research trends and characteristics in the field of Educational Technology. By using the analytic tool Content Analysis Toolkit for Academic Research (CATAR), the researchers in this study conducted bibliometric analysis and breakdown analyses to summarize major contributing countries, educational institutions, most productive authors, and most cited papers; moreover, they used co-word analysis to reveal the representative items within each cluster. The findings in this study can provide implications and references for educators and researchers in the field of Educational Technology when selecting variables for their studies and technologies for their students.

The measurement efficiency of a multidimensional computerized adaptive testing (MCAT) can be improved by taking the correlations between the dimensions into account during the item selection and latent-trait estimation procedures (Segall, 1996; Wangamp; Chen, 2004). Although a multidimensional computerized classification test (MCCT), which was based on a multidimensional itemresponse model, was previously found more efficient than its unidimensional counterpart, the difference was negligible (Seitzamp; Frey, 2013); the researchers had adopted a sequential probability ratio test (SPRT) as the termination criterion in this MCCT study. To make a classification decision on each dimension, which is called a grid classification (Wang et al., 2019), only items that loaded on that dimension were used to calculate the likelihood ratio, which squandered the available information of the correlations between the dimensions. The current study utilizes such useful information to improve the measurement efficiency of the MCCT by applying a conditional distribution of the latent-trait estimates and then including all the administered items to calculate the likelihood ratio in the SPRT. The performance of this newly proposed method was evaluated through a series of simulation studies. The results showed that the proposed method can sizably improve the measurement efficiency of an MCCT by saving 1% to 32% of the test length in comparison with the SPRT when the two test dimensions are at least moderately correlated. The findings and further applications of this study are discussed.

Malignant ascites frequently occur in patients with advanced ovarian cancer at initial diagnosis, and in almost all cases of relapse, they are closely related to poor prognosis, chemoresistance, and metastasis. To date, effective management strategies have been limited. In this study, we aimed to investigate the effects of oncolytic adenovirus (OV) on malignant ascites in a mouse model of advanced ovarian cancer. The results suggested that OV conferred an effective ability to reduce ascites development and prolong overall survival. Further analysis of the ascitic immune microenvironment revealed that OV treatment promoted T cell infiltration, activation, and differentiation into the effector phenotype; reprogrammed macrophages toward the M1-like phenotype; and increased the ratios of both CD8+ T cells to CD4+ T cells and M1 to M2 macrophages. However, immunosuppressive factors such as PD-1, LAG-3, and Tregs emerged after treatment. Combination therapy including OV, CSF-1R inhibitor PLX3397, and anti-PD-1 remarkably delayed the progression of ascites, and combination therapy induced a greater extent of T cell infiltration, proliferation, and activation. This study provides experimental and theoretical evidence for oncolytic virus-based treatment of malignant ascites, which may further contribute to advanced ovarian cancer therapy., Graphical abstract, Effective management of ascites in ovarian cancer has been lacking. Here, we found that oncolytic adenovirus could treat ascites of ovarian cancer by reprogramming the ascitic immune microenvironment. Our study provides experimental and theoretical evidence for oncolytic virus-based treatment of malignant ascites, which may further contribute to advanced ovarian cancer therapy.

In order to respond to the theme of national green and healthy sustainable development and in response to the problems of large block rates and pollution of the environment after the blast mining of underground rocks in alpine areas, we conducted research on the joints of underground rocks and the blastability of frozen rocks. According to the actual geological conditions of an underground mine blasting in Heilongjiang Province, three kinds of joint blasting geometric models were established. The rock mass blasting process of different types of joints was simulated by LS-DYNA software and the influence law of joints on rock mass blasting was summarized. The blasting crater test and the triaxial compression test of frozen rock were carried out. Combined with the blasting fragmentation characterization function (R-R and G-G-S), the blasting fragmentation, strength and stiffness of frozen rock at different temperatures were obtained. Based on the above, the blasting parameters of a multi-joint underground rock mass in an alpine region were optimized: hole spacing 4.0 m, row spacing 2.5 m, hole depth 11.5 m, V-type initiation network. The optimized blasting parameters significantly improved the mining efficiency and reduced the large lump rate to 3.1%. In order to promote the sustainable exploitation of resources in alpine regions, this study optimized the blasting technology of underground rock mass.

With the development of technology and demand for online courses, there have been considerable quantities of online, blended, or flipped courses designed and provided. However, in the technology-enhanced learning environments, which are also full of social networking websites, shopping websites, and free online games, it is challenging to focus students' attention and help them achieve satisfactory learning performance. In addition, the instruction of programming courses constantly challenges both teachers and students, particularly in online learning environments. To overcome and solve these problems and to facilitate students' learning, the researchers in this study integrated two teaching approaches, using meta-cognitive learning strategy (MCLS) and team regulation (TR), to develop students' regular learning habits and further contribute to their programming skills, academic motivation, and refusal self-efficacy of Internet use, in a cloud classroom. In this research, a quasi-experiment was conducted to investigate the effects of MCLS and TR adopting the experimental design of a 2 (MCLS vs. non-MCLS) × 2 (TR vs. non-TR) factorial pre-test/post-test. In this research, the participants consisted of four classes of university students from non-information or computer departments enrolled in programming design, a required course. The experimental groups comprised three of the classes, labelled as G1, G2, and G3. G1 concurrently received both the online MCLS and TR intervention, while G2 only received the online MCLS intervention, and G3 only received the online TR intervention. Serving as the control group, the fourth class (G4) received traditional teaching. This study investigated the effects of MCLS, TR, and their combination, on improving students' programming skills, academic motivation, and refusal self-efficacy of Internet use in an online computing course. According to the results, students who received online TR significantly enhanced their programming design skills and their refusal self-efficacy of Internet use a cloud classroom. However, the expected effects of MCLS on developing students' programming skills, academic motivation, and refusal self-efficacy of Internet use were not found in this study. The teaching strategy of integrating MCLS and TR in an online programming course in this study can serve as a reference for educators when conducting online, blended, or flipped courses during the COVID-19 pandemic.

CD8+CD103+ tissue-resident memory T cells (TRMs) are involved in tumor immune response and linked to favorable clinical outcome in human cancer. However, the distribution, phenotype, functional properties and clinical relevance of these cells in gastric cancer (GC) remain elusive. Here, our data show that, in comparison to non-tumor tissues, the percentages of CD8+CD103+ TRMs in tumors are significantly decreased. Most tumor-infiltrating CD8+CD103+ TRMs are CD45RA−CCR7− effector-memory cells with higher PD-1 and 4-1BB expression than those from non-tumor tissues. Further, tumor-infiltrating CD8+CD103+ TRMs show impaired cytolytic capacity due to decreased granzyme B and perforin expression. Moreover, ex vivo PD-1 blockade could restore the cytolytic capacity of tumor-infiltrating CD8+CD103+ TRMs, and such anti-PD-1-mediated reinvigoration of CD8+CD103+ TRMs could be further enhanced by 4-1BB co-stimulation. Finally, lower levels of Tumor-infiltrating CD8+CD103+ TRMs are positively correlated with GC progression and poor patients’ survival. Our data suggest that restoring CD8+CD103+ TRM function by combining PD-1 blockade and 4-1BB co-stimulation may be a promising strategy for treating GC.

Rationale & Objective: We aimed to explore the associated factors of endothelial injury in chronic kidney disease (CKD) and the relationship between endothelial dysfunction and CKD prognosis. Study Design: A prospective observational cohort study. Setting & Participants: 77 adults with CKD stages 1-5 were enrolled January 2010 to December 2010 and followed up until December 2015. Exposure: Serum asymmetric dimethylarginine (ADMA) level at baseline, α-klotho, sodium-phosphorus synergistic transporter, and dimethylarginine-dimethylamine hydrolase expression in kidney biopsy samples. Outcome: Initiation of kidney replacement therapy (KRT). Analytical Approach: Kaplan-Meier analysis was used for evaluation of the incidence rate of KRT. All tests were 2 tailed, and statistical significance was defined as P

Tumor vaccines that induce effective and sustained antitumor immunity are highly promising for cancer therapy. However, the antitumor potential of these vaccines is weakened due to the immunosuppressive characteristics of the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are the most abundant stromal cells within the TME; they play an important role in tumor growth, metastasis, immunosuppression, and drug resistance. Fibroblast activation protein-α (FAP) is overexpressed in CAFs in more than 90% of human tumor tissues. Further, FAP+CAFs are an ideal interstitial target for the immunotherapy of solid tumors. Exosomes derived from tumor cells contain many tumor antigens, which can be used as the basis of tumor vaccines that elicit strong antitumor immunity. Almost all exosome-based cancer vaccines have been designed and developed for tumor parenchymal cells. Moreover, the exosome production is very low and the purification is very difficult, limiting their clinical application as tumor vaccines. In this study, we developed FAP gene–engineered tumor cell–derived exosome-like nanovesicles (eNVs-FAP) as a tumor vaccine that can be prepared easily and in large quantities. The eNVs-FAP vaccine inhibited tumor growth by inducing strong and specific cytotoxic T lymphocyte (CTL) immune responses against tumor cells and FAP+CAFs and reprogramming the immunosuppressive TME in the colon, melanoma, lung, and breast cancer models. Moreover, eNVs-FAP vaccine–activated cellular immune responses could promote tumor ferroptosis by releasing interferon-gamma (IFN-γ) from CTLs and depleting FAP+CAFs. Thus, eNVs-FAP is a candidate tumor vaccine targeting both the tumor parenchyma and the stroma. Statement of significance Nanovaccines can activate immune cells and promote an antitumor immune response. In this study, we developed the fibroblast activation protein-α (FAP) gene–engineered tumor cell–derived exosome-like vesicle vaccines (eNVs-FAP). A large number of eNVs-FAP were obtained by continuously squeezing FAP gene–engineered tumor cells. eNVs-FAP showed excellent antitumor effects in a variety of tumor-bearing mouse models. The mechanistic analysis showed that eNVs-FAP promoted the maturation of dendritic cells (DCs), increased the infiltration of effector T cells into target tumor cells and FAP-positive cancer-associated fibroblasts (FAP+CAFs), and reduced the proportion of immunosuppressive cells, including M2-like tumor-associated macrophages (M2-TAMs), myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs), in the tumor microenvironment (TME). Moreover, the clearance of FAP+CAFs helped enhance interferon-gamma-induced tumor cell ferroptosis.

Radiofrequency ablation (RFA) is a relatively safe and efficient alternative to surgery for patients with benign thyroid nodules. We investigated predictive factors associated with volume reduction using digital imaging analysis. In this retrospective study, a prospectively maintained database containing the data of patients who received treatment from April 2019 to March 2020 was analyzed. Computerized analysis for quantitative measurement of echogenicity, heterogeneity, and the proportion of cystic components was performed on ultrasonographic images. The volume reduction rate (VRR) was calculated during follow-up. Treatment efficacy was defined as a volume reduction greater than 50% of baseline volume. The median volume of 58 benign thyroid nodules before RFA was 22.7 mL. Of 53 nodules with sufficient follow-up, the median VRR was 46.4%, 61.5%, 63.4%, and 67.4% at 1, 3, 6, and 12 months, respectively. Overall, at one-year follow-up, treatment efficacy was achieved in 39 (74%) nodules. In a multivariate regression analysis, the proportion of cystic components and RFA treatment time were independently associated with treatment efficacy. A subgroup analysis focusing on solid nodules indicated a negative correlation between echogenicity and VRR. The proportion of cystic components in thyroid nodules is the main predictor of RFA treatment efficacy. In solid nodules, higher echogenicity is associated with a lower volume reduction.

Carotenoids are a group of tetraterpene pigments widely used in the food, pharmaceutical, and cosmetic industries. Torulene, torularhodin, and β-carotene, three principal carotenoids synthesized by Rhodotorula glutinis ZHK, possess strong health-promoting properties such as antioxidant, provitamin A, and antitumor. Here, the effect of different salt conditions on carotenoids production of R. glutinisZHK was investigated. The results showed that the total carotenoids were significantly enhanced in 0.5 M (3.91 mg/L) and 0.75 M (5.41 mg/L) NaCl treatments than that in 1.0 M (0.35 mg/L) and control (1.42 mg/L) after 120 h of cultivation. Of which, the increase in torulene and torularhodin production acts as the main contributor to the enhancement of total carotenoids. Transcriptome profiling revealed that salt stress efficiently promotes the gene expression of crtI, which could explain the molecular mechanisms of the enhanced torulene and torularhodin production under salt stress. Further experiments indicated that torulene and torularhodin play an important role in quenching excrescent reactive oxygen species induced by salt stress. Together, the present study reports an effective strategy for simultaneously improving torulene and torularhodin production in R. glutinis ZHK.

Equation (5) of the published article?(Abbott et al. 2019) is in error; it should read (Formula Presented) The upper limits on ò presented in the published article are unaffected by this error.

A mononuclear complex [Fe(tBu2qsal)2] has been obtained by a reaction between an Fe(II) precursor salt and a tridentate ligand 2,4-di(tert-butyl)-6-((quinoline-8-ylimino)methyl)phenol (tBu2qsalH) in the presence of triethylamine. The complex exhibits a hysteretic spin transition at 117 K upon cooling and 129 K upon warming, as well as light-induced excited spin-state trapping at lower temperatures. Although the strongly cooperative spin transition suggests substantial intermolecular interactions, the complex is readily sublimable, as evidenced by the growth of its single crystals by sublimation at 573 → 373 K and ∼10-3 mbar. This seemingly antagonistic behavior is explained by the asymmetric coordination environment, in which the tBu substituents and quinoline moieties appear on opposite sides of the complex. As a result, the structure is partitioned in well-defined layers separated by van der Waals interactions between the tBu groups, while the efficient cooperative interactions within the layer are provided by the quinoline-based moieties. The abrupt spin transition is preserved in a 20 nm thin film prepared by sublimation, as evidenced by abrupt and hysteretic changes in the dielectric properties in the temperature range comparable to the one around which the spin transition is observed for the bulk material. The changes in the dielectric response are in excellent agreement with differences in the dielectric tensor of the low-spin and high-spin crystal structures evaluated by density functional theory calculations. The substantially higher volatility of [Fe(tBu2qsal)2], as compared to a similar complex without tBu substituents, suggests that asymmetric molecular shapes offer an efficient design strategy to achieve sublimable complexes with strongly cooperative spin transitions.

Magnetoelectric coupling is achieved near room temperature in a spin crossover Fe

Based on engineering background that local heating of coal seam is uneven due to underground coal gasification, coal-bed gas exploitation via heat injection, spontaneous combustion of coal seam, etc., segmented heating coal sample was used to simulate coal seam under uneven heating condition, and experimental study on mechanical behaviors of coal sample after segmented heat treatment at high temperatures was conducted. Test results show that temperature at 100 °C ~ 400 °C did not reach ignition temperature of deep hard coal for the experiment and was not enough to change main ingredients of coal sample, which less affected compression strength, elastic modulus, acoustic emission behavior of coal sample. Although compaction stage-elastic stage-plastic stage-broken stage appeared in compression stress–strain curve of coal sample, height increase led to decrease of compression strength, elastic modulus of coal sample, cumulative amplitude and ringing count for acoustic emission in the form of power function. Meanwhile, it is found that final failure modes of coal sample after segmented heat were mainly shear failure and separation failure and friction mixed failure was secondary. In addition, influence of heating temperature at 100 °C ~ 400 °C on failure modes of coal sample was small. However, height increase in the heating section of coal sample made shear failure surface gradually move to the heating section and separation failure surface moved with the change of contact surface position between heating section and non-heating section. Furthermore, the integral failure degree of coal sample was more serious. Finally, based on variation behaviors of acoustic emission parameter for coal sample after segmented heating, inversion formula on acoustic emission parameter for strength of coal sample was discussed and verified via experimental result of coal sample with different segmented heat height after heating treatment at 200 °C.

Brain resting-state functional connectivity (rsFC) has been widely analyzed in substance use disorders (SUDs), including methamphetamine (MA) dependence. Most of these studies utilized Pearson correlation analysis to assess rsFC, which cannot determine whether two brain regions are connected by direct or indirect pathways. Moreover, few studies have reported the application of rsFC-based graph theory in MA dependence. We evaluated alterations in Tikhonov regularization-based rsFC and rsFC-based topological attributes in 46 MA-dependent patients, as well as the correlations between topological attributes and clinical variables. Moreover, the topological attributes selected by least absolute shrinkage and selection operator (LASSO) were used to construct a support vector machine (SVM)-based classifier for MA dependence. The MA group presented a subnetwork with increased rsFC, indicating overactivation of the reward circuit that makes patients very sensitive to drug-related visual cues, and a subnetwork with decreased rsFC suggesting aberrant synchronized spontaneous activity in subregions within the orbitofrontal cortex (OFC) system. The MA group demonstrated a significantly decreased area under the curve (AUC) for the clustering coefficient (Cp) (Pperm < 0.001), shortest path length (Lp) (Pperm = 0.007), modularity (Pperm = 0.006), and small-worldness (σ, Pperm = 0.004), as well as an increased AUC for global efficiency (E.glob) (Pperm = 0.009), network strength (Sp) (Pperm = 0.009), and small-worldness (ω, Pperm < 0.001), implying a shift toward random networks. MA-related increased nodal efficiency (E.nodal) and altered betweenness centrality were also discovered in several brain regions. The AUC for ω was significantly positively associated with psychiatric symptoms. An SVM classifier trained by 36 features selected by LASSO from all topological attributes achieved excellent performance, cross-validated prediction area under the receiver operating characteristics curve, accuracy, sensitivity, specificity, and kappa of 99.03 ± 1.79, 94.00 ± 5.78, 93.46 ± 8.82, 94.52 ± 8.11, and 87.99 ± 11.57%, respectively (Pperm < 0.001), indicating that rsFC-based topological attributes can provide promising features for constructing a high-efficacy classifier for MA dependence.

Air quality has a significant influence on the environment and health. Instruments that efficiently and inexpensively detect air quality could be extremely valuable in detecting air quality indices. This study presents a robust deep learning model named AQE-Net, for estimating air quality from mobile images. The algorithm extracts features and patterns from scene photographs collected by the camera device and then classifies the images according to air quality index (AQI) levels. Additionally, an air quality dataset (KARACHI-AQI) of high-quality outdoor images was constructed to enable the model’s training and assessment of performance. The sample data were collected from an air quality monitoring station in Karachi City, Pakistan, comprising 1001 hourly datasets, including photographs, PM2.5 levels, and the AQI. This study compares and examines traditional machine learning algorithms, e.g., a support vector machine (SVM), and deep learning models, such as VGG16, InceptionV3, and AQE-Net on the KHI-AQI dataset. The experimental findings demonstrate that, compared to other models, AQE-Net achieved more accurate categorization findings for air quality. AQE-Net achieved 70.1% accuracy, while SVM, VGG16, and InceptionV3 achieved 56.2% and 59.2% accuracy, respectively. In addition, MSE, MAE, and MAPE values were calculated for our model (1.278, 0.542, 0.310), which indicates the remarkable efficacy of our approach. The suggested method shows promise as a fast and accurate way to estimate and classify pollutants from only captured photographs. This flexible and scalable method of assessment has the potential to fill in significant gaps in the air quality data gathered from costly devices around the world.

A new esterase gene, est6, was discovered in an activated sludge metagenomic library. The 729-bp gene encodes a 242-amino acid protein (designated Est6) with a molecular mass of 26.1 kDa. Est6 shared only a moderate identity to a putative hydrolase with the highest BLASTP analysis score. Most of the closely related proteins are uncharacterized and are predicted from genome sequencing data of microorganisms or metagenomic DNA sequences. The phylogenetic analysis of Est6 showed that the protein was assigned to family VI esterases/lipases. The catalytic triad of Est6 was predicted to be Ser135, Asp188, and His219, with Ser135 in a typically conserved pentapeptide (GFSQG) of family VI members, which was further confirmed by site-directed mutagenesis. The est6 gene was overexpressed successfully in its soluble form in Escherichia coli and then purified to its tag-free form and homogeneity by affinity chromatography. The purified Est6 in pH 8.0 buffer was active as a monomer. The optimal conditions for Est6 activity were at a temperature of 45 °C and pH of 8.0 when using p-nitrophenyl acetate as a substrate. The enzyme was stable over wide temperature and pH ranges, and it exhibited activity in the presence of organic solvents, metal cations, or detergents. Furthermore, the enzyme showed significant regioselectivity in the spectrophotometric analysis. In conclusion, Est6 might have the potential for applications in biotechnological processes.

BackgroundDrug repurposing is a fast and effective way to develop drugs for an emerging disease such as COVID-19. The main challenges of effective drug repurposing are the discoveries of the right therapeutic targets and the right drugs for combating the disease.MethodsHere, we present a systematic repurposing approach, combining Homopharma and hierarchal systems biology networks (HiSBiN), to predict 327 therapeutic targets and 21,233 drug-target interactions of 1,592 FDA drugs for COVID-19. Among these multi-target drugs, eight candidates (along with pimozide and valsartan) were tested and methotrexate was identified to affect 14 therapeutic targets suppressing SARS-CoV-2 entry, viral replication, and COVID-19 pathologies. Through the use of in vitro (EC50 = 0.4 μM) and in vivo models, we show that methotrexate is able to inhibit COVID-19 via multiple mechanisms.ResultsOur in vitro studies illustrate that methotrexate can suppress SARS-CoV-2 entry and replication by targeting furin and DHFR of the host, respectively. Additionally, methotrexate inhibits all four SARS-CoV-2 variants of concern. In a Syrian hamster model for COVID-19, methotrexate reduced virus replication, inflammation in the infected lungs. By analysis of transcriptomic analysis of collected samples from hamster lung, we uncovered that neutrophil infiltration and the pathways of innate immune response, adaptive immune response and thrombosis are modulated in the treated animals.ConclusionsWe demonstrate that this systematic repurposing approach is potentially useful to identify pharmaceutical targets, multi-target drugs and regulated pathways for a complex disease. Our findings indicate that methotrexate is established as a promising drug against SARS-CoV-2 variants and can be used to treat lung damage and inflammation in COVID-19, warranting future evaluation in clinical trials.

The sex of honey bees is decided by a regulatory cascade comprising of csd, fem and Amdsx. In order to further identify other genes involved in sex determination and differentiation of honey bees in the early stages of embryo development, the CRISPR/Cas9 method was used to knock out fem gene in the embryonic stage of diploid western honey bees, and RNA-seq was used to analyze gene expression changes in the embryo after fem knockout. Finally, we found that the bees had undergone gender changes due to fem knockout. A total of 155 differentially expressed genes (DEGs) were obtained, with 48 up-regulated and 107 down-regulated DEGs in the mutant group compared to the control group. Of them, many genes are related to sex development or differentiation. In addition, 1502 differentially expressed alternative splicing events (DEASEs) related to 1011 genes, including the main honey bee sex-determining genes csd, tra2, fem, and Amdsx, were identified between the mutant group and control group, indicating that fem regulates alternative splicing of a large number of downstream genes. Our results provide valuable clues for further investigating the molecular mechanism of sex determination and differentiation in honey bees.

In order to improve the degradation activity of β-glucosidase (CpBgl) from Coniophora puteana, the structural modification was conducted. The enzyme activity of mutants CpBgl-Q20C and CpBgl-A240S was increased by 65.75% and 58.58%, respectively. These mutants exhibited maximum activity under the same conditions as wild-type CpBgl (65 ℃ and pH 5.0), slightly improved stabilities compared that of the wild-type, and remarkably enhanced activities in the presence of Mn

The advent of two-dimensional (2D) crystals has led to numerous scientific breakthroughs. Conventional 2D systems have in-plane covalent bonds and a weak out-of-plane van-der-Waals bond. Here we report a new type of 2D material composed of discrete magnetic molecules, where anisotropic van-der-Waals interactions bond the molecules into a 2D packing. Through mechanical exfoliation, we can obtain single-crystalline molecular monolayers, which can be readily integrated into other 2D systems. Optical spectroscopy suggests the few-layered molecules preserve the temperature-induced spin-crossover switching observed in the bulk form but show a drastic increase in thermal hysteresis unique to these thin 2D molecule assemblies. The trapping of spin bistability with decreasing layer number can arise from domain wall dynamics in reduced dimensions. Our results establish molecular solids with strong anisotropy of intermolecular interactions as precursors to a new class of 2D materials, affording possibilities to control molecular functionalities through substrate and interlayer interactions.