Mindset profiles of secondary school students: Associations with academic achievement, motivation and school burnout symptoms.

BACKGROUND: According to Dweck's mindset theory, implicit beliefs (a.k.a. mindset) have an organizing function, bringing together mindset, achievement goals and effort beliefs in a broader meaning system. Two commonly described meaning systems are a growth-mindset meaning system with mastery goals and positive effort beliefs, and a fixed-mindset meaning system with performance goals and negative effort beliefs. AIMS: Because of assumed heterogeneity within these two meaning systems, we aim to (1) examine multiple-mindset profiles based on mindset, achievement goals and effort beliefs, by using a data-driven person-oriented approach, and (2) relate these different profiles to several outcome measures (academic achievement, motivation and school burnout symptoms). SAMPLE: Self-report questionnaire data were collected from 724 students (11.0-14.7 y.o.; 46.7% girl; 53.3% boy; Mage = 12.8 y.o.). METHODS: Latent profile analysis was conducted using mindset, achievement goals and effort beliefs. RESULTS: Four profiles were revealed: one fixed-mindset profile and three growth-mindset profiles, which differed in their performance goal levels (low, moderate and high). Growth-mindset students with low- or moderate-performance goals had more advantageous outcomes, for example, higher math grades and lower school burnout symptoms, compared to growth-mindset students with high-performance goals. Fixed-mindset students had the least advantageous outcomes, for example, lower grades, less intrinsic motivation and more school burnout symptoms. CONCLUSIONS: Our study emphasizes the importance of taking a holistic approach when examining mindset meaning systems, revealing the importance of the level of performance goals and including multiple academic outcomes.

Structure-Based Design of the Indole-Substituted Triazolopyrimidines as New EED-H3K27me3 Inhibitors for the Treatment of Lymphoma.

Interrupting the embryonic ectoderm development (EED)-H3K27me3 interaction represents a promising strategy to allosterically inhibit polycomb repressive complex 2 (PRC2) for cancer therapy. In this work, we report the structure-based design of new triazolopyrimidine-based EED inhibitors, which structurally feature the electron-rich indole ring at the C8 position. Particularly, ZJH-16 directly binds to EED (HTRF IC50 = 2.72 nM, BLI KD = 4.4 nM) and potently inhibits the growth of KARPAS422 and Pfeiffer cells. In both cells, ZJH-16 is selectively engaged with EED and reduces H3K27 trimethylation levels. ZJH-16 inhibits the gene silencing function of PRC2 in KARPAS422 cells. ZJH-16 possesses favorable pharmacokinetic (PK) profiles with an excellent oral bioavailability (F = 94.7%). More importantly, ZJH-16 shows robust tumor regression in the KARPAS422 xenograft model after oral administration with the tumor growth inhibition reaching nearly 100%. The robust antitumor efficacy and favorable PK profiles of ZJH-16 warrant further advanced preclinical development for lymphoma treatment.

MeDBA: the Metalloenzyme Data Bank and Analysis platform.

Metalloenzymes are attractive research targets in fields of chemistry, biology, and medicine. Given that metalloenzymes can manifest conservation of metal-coordination and ligand binding modes, the excavation and expansion of metalloenzyme-specific knowledge is of interest in bridging metalloenzyme-related fields. Building on our previous metalloenzyme-ligand association database, MeLAD, we have expanded the scope of metalloenzyme-specific knowledge and services, by forming a versatile platform, termed the Metalloenzyme Data Bank and Analysis (MeDBA). The MeDBA provides: (i) manual curation of metalloenzymes into different categories, that this M-I, M-II and M-III; (ii) comprehensive information on metalloenzyme activities, expression profiles, family and disease links; (iii) structural information on metalloenzymes, in particular metal binding modes; (iv) metalloenzyme substrates and bioactive molecules acting on metalloenzymes; (v) excavated metal-binding pharmacophores and (vi) analysis tools for structure/metal active site comparison and metalloenzyme profiling. The MeDBA is freely available at https://medba.ddtmlab.org.

Does Digital Inclusive Finance Mitigate the Negative Effect of Climate Variation on Rural Residents' Income Growth in China?

Global anthropogenic greenhouse gas emissions have exacerbated climate variation. Climate variation impacts the agricultural production and rural residents' income negatively, further widening the urban-rural income gap and harming the co-benefits. Narrowing the income gap has always been a global concern and an important part of China's rural revitalization strategy. However, little is known about whether digital inclusive finance can mitigate the negative impact of climate variation on rural residents' income growth in China. Using panel data from 31 provinces in China from 2011 to 2019 and a digital inclusive finance index developed by Peking University, together with historical temperature data, this study examined the impact of digital inclusive finance on Chinese rural residents' income growth in response to climate variation. It was found that digital inclusive finance could promote rural resident operating, wage, and transfer income growth. A heterogeneity analysis revealed that rural residents in central and western regions experienced larger digital inclusive finance facilitating effects on income growth than the eastern regions. Further analyses using the Spatial Dubin Model found that digital inclusive finance had a spatial spillover effect as it could significantly promote income growth in neighboring provinces. Although climate variation reduced rural residents' income and increased their risks, digital inclusive finance significantly mitigated this negative effect. Digital information infrastructure construction, financial risk prevention, digital financial knowledge, and e-commerce popularization were practical paths to optimizing inclusive finance development in rural areas and promoting poverty alleviation and rural revitalization to resist climate risks.

[Responses of soil moisture at different slope positions to rainfall in dry-hot valley]. / 干热河谷区不同坡位土壤水分对降雨的响应特征.

The study of short-term dynamics of soil moisture in the dry-hot valley area during rainfall process will help identify soil hydrological function. In this study, we analyzed the short-term responses of soil moisture to rainfall in Huajiang dry-hot valley of Guizhou, using in-situ monitoring method to yield high-frequency soil moisture monitoring data of different slope positions. The results showed that, during the whole monitoring period, soil moisture at each layer was at a moderate variation level (15.2%≤coefficient of variation CV≤29.7%), for both upper slope and middle slope. The fluctuation range of soil moisture of the upper slope (CV=21.1%) was greater than that of the middle slope (CV=19.1%), and that of the 0-5 cm soil layer (CV=26.2%) was greater than 20-40 cm layer (CV=16.5%). Compared with the middle slope, soil moisture of the upper slope had a faster response to rainfall. The supplement amount of rainfall was bigger and the supplement speed of rainfall was faster at the upper slope than that at the middle slope. The difference between the supplement speed and the depletion speed of soil moisture of the upper slope (2.3%·h-1) was greater than that of the middle slope (1.8%·h-1). With the increase of soil depth, the responses of soil moisture to rainfall in subsoil layer was earlier or synchronous with that in topsoil layer. When the supplement amount of soil moisture decreased and the supplement speed slowed down, the depletion speed slowed down. Compared with the middle slope, soil at the upper slope had greater water infiltration capacity and better water retention capacity. The responses of soil moisture to rainfall in dry-hot valley were influenced by micro-environment and microclimate, and the rapid recharge of dominant flow at rock-soil interface accelerated the response speed of subsoil moisture to rainfall, which made the slopes in this area easier to form mixed runoff generation mechanism.

Developing and predicting of early mortality after endovascular thrombectomy in patients with acute ischemic stroke.

Background: Stroke is one of the leading causes of mortality across the world. However, there is a paucity of information regarding mortality rates and associated risk factors in patients with acute ischemic stroke (AIS) undergoing endovascular thrombectomy (EVT). In this study, we aimed to clarify these issues and analyzed previous publications related to mortality in patients treated with EVT. Methods: We analyzed the survival of 245 consecutive patients treated with mechanical thrombectomy for AIS for which mortality information was obtained. Early mortality was defined as death occurring during hospitalization after EVT or within 7 days following hospital discharge from the stroke event. Results: Early mortality occurred in 22.8% of cases in this cohort. Recanalization status (modified thrombolysis in cerebral infarction, mTICI) (p = 0.002), National Institute of Health Stroke Scale Score (NIHSS) score 24-h after EVT (p < 0.001) and symptomatic intracerebral hemorrhage (sICH) (p < 0.001) were independently associated with early mortality. Age, sex, cardiovascular risk factors, NIHSS score pre-treatment, Alberta Stroke Program Early CT Score (ASPECTS), stroke subtype, site of arterial occlusion and timing form onset to recanalization did not have an independent influence on survival. Non-survivors had a shorter hospitalization (p < 0.001) but higher costs related to their hospitalization and outpatient care. Conclusion: The recanalization status, NIHSS score 24-h after EVT and sICH were predictors of early mortality in AIS patients treated with EVT.

Deep learning in target prediction and drug repositioning: Recent advances and challenges.

Drug repositioning is an attractive strategy for discovering new therapeutic uses for approved or investigational drugs, with potentially shorter development timelines and lower development costs. Various computational methods have been used in drug repositioning, promoting the efficiency and success rates of this approach. Recently, deep learning (DL) has attracted wide attention for its potential in target prediction and drug repositioning. Here, we provide an overview of the basic principles of commonly used DL architectures and their applications in target prediction and drug repositioning, and discuss possible ways of dealing with current challenges to help achieve its expected potential for drug repositioning.

Targeting Metalloenzymes by Boron-Containing Metal-Binding Pharmacophores.

Metalloenzymes have critical roles in a wide range of biological processes and are directly involved in many human diseases; hence, they are considered as important targets for therapeutic intervention. The specific characteristics of metal ion(s)-containing active sites make exploitation of metal-binding pharmacophores (MBPs) critical to inhibitor development targeting metalloenzymes. This Perspective focuses on boron-containing MBPs, which display unique binding modes with metalloenzyme active sites, particularly via mimicking native substrates or tetrahedral transition states. The design concepts regarding boron-containing MBPs are highlighted through the case analyses on five distinct classes of clinically relevant nucleophilic metalloenzymes from medicinal chemistry perspectives. The challenges (e.g., selectivity) faced by some boron-containing MBPs and possible strategies (e.g., bioisosteres) for metalloenzyme inhibitor transformation are also discussed.

AncPhore: A versatile tool for anchor pharmacophore steered drug discovery with applications in discovery of new inhibitors targeting metallo-ß-lactamases and indoleamine/tryptophan 2,3-dioxygenases.

We herein describe AncPhore, a versatile tool for drug discovery, which is characterized by pharmacophore feature analysis and anchor pharmacophore (i.e., most important pharmacophore features) steered molecular fitting and virtual screening. Comparative analyses of numerous protein-ligand complexes using AncPhore revealed that anchor pharmacophore features are biologically important, commonly associated with protein conservative characteristics, and have significant contributions to the binding affinity. Performance evaluation of AncPhore showed that it had substantially improved prediction ability on different types of target proteins including metalloenzymes by considering the specific contributions and diversity of anchor pharmacophore features. To demonstrate the practicability of AncPhore, we screened commercially available chemical compounds and discovered a set of structurally diverse inhibitors for clinically relevant metallo-ß-lactamases (MBLs); of them, 4 and 6 manifested potent inhibitory activity to VIM-2, NDM-1 and IMP-1 MBLs. Crystallographic analyses of VIM-2:4 complex revealed the precise inhibition mode of 4 with VIM-2, highly consistent with the defined anchor pharmacophore features. Besides, we also identified new hit compounds by using AncPhore for indoleamine/tryptophan 2,3-dioxygenases (IDO/TDO), another class of clinically relevant metalloenzymes. This work reveals anchor pharmacophore as a valuable concept for target-centered drug discovery and illustrates the potential of AncPhore to efficiently identify new inhibitors for different types of protein targets.

Design and enantioselective synthesis of 3-(α-acrylic acid) benzoxaboroles to combat carbapenemase resistance.

Chiral 3-substituted benzoxaboroles were designed as carbapenemase inhibitors and efficiently synthesised via asymmetric Morita-Baylis-Hillman reaction. Some of the benzoxaboroles were potent inhibitors of clinically relevant carbapenemases and restored the activity of meropenem in bacteria harbouring these enzymes. Crystallographic analyses validate the proposed mechanism of binding to carbapenemases, i.e. in a manner relating to their antibiotic substrates. The results illustrate how combining a structure-based design approach with asymmetric catalysis can efficiently lead to potent ß-lactamase inhibitors and provide a starting point to develop drugs combatting carbapenemases.

X-ray Structure-Guided Discovery of a Potent, Orally Bioavailable, Dual Human Indoleamine/Tryptophan 2,3-Dioxygenase (hIDO/hTDO) Inhibitor That Shows Activity in a Mouse Model of Parkinson's Disease.

Human indoleamine 2,3-dioxygenase 1 (hIDO1) and tryptophan 2,3-dioxygenase (hTDO) have been closely linked to the pathogenesis of Parkinson's disease (PD); nevertheless, development of dual hIDO1 and hTDO inhibitors to evaluate their potential efficacy against PD is still lacking. Here, we report biochemical, biophysical, and computational analyses revealing that 1H-indazole-4-amines inhibit both hIDO1 and hTDO by a mechanism involving direct coordination with the heme ferrous and ferric states. Crystal structure-guided optimization led to 23, which manifested IC50 values of 0.64 and 0.04 µM to hIDO1 and hTDO, respectively, and had good pharmacokinetic properties and brain penetration in mice. 23 showed efficacy against the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced mouse motor coordination deficits, comparable to Madopar, an anti-PD medicine. Further studies revealed that different from Madopar, 23 likely has specific anti-PD mechanisms involving lowering IDO1 expression, alleviating dopaminergic neurodegeneration, reducing inflammatory cytokines and quinolinic acid in mouse brain, and increasing kynurenic acid in mouse blood.

Discovery of 3-aryl substituted benzoxaboroles as broad-spectrum inhibitors of serine- and metallo-ß-lactamases.

The production of ß-lactamases represents the main cause of resistance to clinically important ß-lactam antibiotics. Boron containing compounds have been demonstrated as promising broad-spectrum ß-lactamase inhibitors to combat ß-lactam resistance. Here we report a series of 3-aryl substituted benzoxaborole derivatives, which manifested broad-spectrum inhibition to representative serine-ß-lactamases (SBLs) and metallo-ß-lactamases (MBLs). The most potent inhibitor 9f displayed an IC50 value of 86 nM to KPC-2 SBL and micromolar inhibitory activity towards other tested enzymes. Cell-based assays further revealed that 9f was able to significantly reduce the MICs of meropenem in clinically isolated KPC-2-producing bacterial strains and it showed no apparent toxicity in HEK293T cells.

Complete chloroplast genome of adonis amurensis (ranunculaceae), an important cardiac folk medicinal plant in east asia.

Adonis amurensis Regel et Radde is an important cardiac folk medicinal plant which endemic to Northeast Asia. We determined the first complete chloroplast genome of A. amurensis using genome skimming approach. The cp genome was 157,032 bp long, with a large single-copy region (LSC) of 86,218 bp and a small single-copy region (SSC) of 18,212 bp separated by a pair of inverted repeats (IRs) of 26,301 bp. It encodes 129 genes, including 84 protein-coding genes, 37 tRNA genes, and 8 ribosomal RNA genes. We also reconstructed the phylogeny of Adonideae and Isopyreae using maximum likelihood (ML) method, including our data and previously reported cp genomes of related taxa. The phylogenetic analysis indicated that A. amurensis is close related with Adonis sutchuenensis.

Which Boys and Which Girls Are Falling Behind? Linking Adolescents' Gender Role Profiles to Motivation, Engagement, and Achievement.

Research on gender gaps in school tends to focus on average gender differences in academic outcomes, such as motivation, engagement, and achievement. The current study moved beyond a binary perspective to unpack the variations within gender. It identified distinct groups of adolescents based on their patterns of conformity to different gender norms and compared group differences in motivation, engagement, and achievement. Data were collected from 597 English students (aged 14-16 years, 49% girls) on their conformity to traditional masculine and feminine norms, growth mindset, perseverance, self-handicapping, and their English and mathematics performance at the end of secondary school. Latent profile analysis identified seven groups of adolescents (resister boys, cool guys, tough guys, relational girls, modern girls, tomboys, wild girls) and revealed the prevalence of each profile. Within-gender variations show that two thirds of the boys were motivated, engaged, and performed well in school. In contrast, half of the girls showed maladaptive patterns of motivation, engagement, and achievement, and could be considered academically at risk. By shifting the focus from "boys versus girls" to "which boys and which girls", this study reveals the invisibility of well-performing boys and underachieving girls in educational gender gap research.

Evaluation of total phenolic, flavonoid, carbohydrate contents and antioxidant activities of various solvent extracts from Angelica amurensis root.

We investigated the antioxidant activities of different solvent extracts of Angelica amurensis root (AAR). The yield of aqueous extract was the highest. The methanol extract had the highest total phenolic content and total flavonoid content. The aqueous extract showed the highest total carbohydrate content. Methanol and ethanol extracts showed high DPPH and ABTS radical-scavenging abilities, and high antioxidant activities in FRAP and CUPRAC assays. The extract of chloroform and water exhibited high ability to scavenge hydroxyl radicals. All extracts showed high inhibition of ß-carotene bleaching, ethyl acetate extract showed the best effect. Ethyl acetate extract exhibited the highest protection against cellular oxidative damage. The best extraction solvent for the active substance in AAR was methanol. AAR may act as a natural antioxidant.

The complete chloroplast genome of a medicinal plant, Abutilon theophrasti Medik. (Malvaceae).

Abutilon theophrasti Medik. is an annual weed, widely distributed in Asia and Europe. The complete chloroplast genome reported here is 160,446 bp in length, including two inverted repeats (IRs) of 25,064 bp, which are separated by a large single-copy (LSC) and a small single-copy (SSC) of 89,089 and 21,229 bp, respectively. The whole chloroplast genome of A. theophrasti contains 113 distinct genes, including 79 protein-coding genes, 30 transfer RNA, and four ribosome RNA. Phylogenetic analysis indicated that A. theophrasti is located in the basal position in Malveae.

Bilirubin Can Be Used as a Prognostic Factor for Lung Adenocarcinoma Patients with EGFR Mutations.

BACKGROUND AND OBJECTIVES: Non-small cell lung cancer (NSCLC) patients with an epidermal growth factor receptor (EGFR) mutation demonstrate only a median progression-free survival (PFS) of 8 to 10 months and undergo EGFR tyrosine kinase inhibitors (EGFR-TKIs) therapy. For decades, bilirubin has been reported to be associated with the onset and prognosis of lung cancer as a prooxidant. This study aimed to investigate the prediction of pretreatment circulating bilirubin for PFS in lung adenocarcinoma (LAC) patients who underwent EGFR-TKIs targeted therapy. PATIENTS AND METHODS: LAC cases diagnosed and undergone EGFR-TKIs targeted therapy at The First Affiliated Hospital of Zhengzhou University between 2013 and 2015 were retrospectively reviewed. A total of 180 patients were studied according to inclusion and exclusion criteria. Follow-up data were collected for all patients until the disease progressed. RESULTS: Univariate analysis showed that the levels of pretreatment total bilirubin (TBIL), indirect bilirubin (IBIL) and direct bilirubin (DBIL) were related to PFS (all p<0.05). Considering the close relationship among the three factors, we combined TBIL, IBIL and DBIL into one total factor, which is called bilirubin. Kaplan-Meier survival curves and Log rank tests indicated that patients with lower bilirubin levels had a shorter median PFS than those with higher bilirubin levels (8 vs. 15 months; p=0.002). Multivariate analysis demonstrated that pretreatment bilirubin is an independent prognostic factor (HR=0.454, CI: 0.267-0.773, p=0.004). CONCLUSION: This study confirms that bilirubin can predict the prognosis of LAC patients who had undergone EGFR-TKIs targeted therapy.

Long noncoding RNA DIO3OS interacts with miR-122 to promote proliferation and invasion of pancreatic cancer cells through upregulating ALDOA.

BACKGROUND: Long noncoding RNA (lncRNA) has been implicated in numerous tumors, including pancreatic cancer (PC). However, the precise cellular roles and molecular mechanisms of lncRNA DIO3OS on PC development remains to be fully clarified. METHODS: We performed the meta-analysis on PC samples and non-tumor samples retrieved from the TCGA database, and measured the levels of DIO3OS in PC cell lines and a normal pancreatic duct epithelial cell line HPDE6-C7. Cell proliferation was evaluated via CCK-8 assay. Cell invasion in vitro was investigated by transwell assay. The RNA immunoprecipitation assay and luciferase reporter assay was utilized to confirm the putative miR-122-binding site in DIO3OS. The effects of DIO3OS on PC progression were tested using in vivo subcutaneous xenografts. RESULTS: Our results showed that DIO3OS was highly expressed in human PC tissues and PC cell lines. DIO3OS exhibited oncogenic properties in stimulating PC cell proliferation and invasion in vitro and promoting cancer growth in vivo. Through online predictive tools and functional experiments, we found that DIO3OS could bind directly to microRNA-122 (miR-122) and inhibited its expression, which functioned as a tumor suppressor in PC cells. We also verified that ALDOA was the direct target of miR-122, and the tumor suppressive effects caused by DIO3OS knockdown or miR-122 overexpression could be rescued by re-expression of ALDOA in PC cells. CONCLUSIONS: Overall, our study suggested that lncRNA DIO3OS promotes PC cell growth and invasion by competing for miR-122 to modulate the expression of ALDOA. These findings yield a better understanding of the potential mechanisms by which gain of DIO3OS expression accelerates PC progression.

Recent progress in nanomaterials for nucleic acid delivery in cancer immunotherapy.

The combination of gene therapy and immunotherapy has the potential to systemically promote anti-tumor effects while reducing adverse reactions. Small interfering RNA (siRNA) has generated great interest in biology, engineering and medicine, especially for cancer treatment due to its ability to knock down genes of interest. Nanomaterials play significant roles in the design of delivery systems of siRNA, and nanomaterial-mediated siRNA delivery in cancer immunotherapy is one of the most important directions for future clinical cancer treatment. Here, we review the recent advances in nanomaterial mediated targeted delivery of siRNA to dendritic cells (DCs), tumor-associated macrophages (TAMs), immune checkpoint inhibitors, B lymphocytes, natural killer cells (NKs), and immunosuppressive cytokines. Fundamental challenges in nucleic acid delivery enabled by bio-barriers, its promising solution strategies and future directions are also reviewed.

Complete chloroplast genome of Prunus pensylvanica and its implications for the phylogenetic position within Prunus sensu lato (Rosaceae).

Prunus pensylvanica is one of the two native cherry species of North America. We determined the first complete chloroplast genome of P. pensylvanica using genome-skimming approach. The cp genome was 157,953 bp long, with a large single-copy region (LSC) of 86,030 bp and a small single-copy region (SSC) of 19,135 bp separated by a pair of inverted repeats (IRs) of 26,394 bp. It encodes 129 genes, including 84 protein-coding genes, 37 tRNA genes, and 8 ribosomal RNA genes. We also reconstructed the phylogeny of Prunus sensu lato using maximum likelihood (ML) method, including our data and previously reported cp genomes of related taxa. The phylogenetic analysis indicated that P. pensylvanica is closely related to P. emarginata.