In-silico study of the impact of system design parameters on microcalcification detection in wide-angle digital breast tomosynthesis.

Purpose: Accurate detection of microcalcifications ( µ Calcs ) is crucial for the early detection of breast cancer. Some clinical studies have indicated that digital breast tomosynthesis (DBT) systems with a wide angular range have inferior µ Calc detectability compared with those with a narrow angular range. This study aims to (1) provide guidance for optimizing wide-angle (WA) DBT for improving µ Calcs detectability and (2) prioritize key optimization factors. Approach: An in-silico DBT pipeline was constructed to evaluate µ Calc detectability of a WA DBT system under various imaging conditions: focal spot motion (FSM), angular dose distribution (ADS), detector pixel pitch, and detector electronic noise (EN). Images were simulated using a digital anthropomorphic breast phantom inserted with 120 µ m µ Calc clusters. Evaluation metrics included the signal-to-noise ratio (SNR) of the filtered channel observer and the area under the receiver operator curve (AUC) of multiple-reader multiple-case analysis. Results: Results showed that FSM degraded µ Calcs sharpness and decreased the SNR and AUC by 5.2% and 1.8%, respectively. Non-uniform ADS increased the SNR by 62.8% and the AUC by 10.2% for filtered backprojection reconstruction with a typical clinical filter setting. When EN decreased from 2000 to 200 electrons, the SNR and AUC increased by 21.6% and 5.0%, respectively. Decreasing the detector pixel pitch from 85 to 50 µ m improved the SNR and AUC by 55.6% and 7.5%, respectively. The combined improvement of a 50 µ m pixel pitch and EN200 was 89.2% in the SNR and 12.8% in the AUC. Conclusions: Based on the magnitude of impact, the priority for enhancing µ Calc detectability in WA DBT is as follows: (1) utilizing detectors with a small pixel pitch and low EN level, (2) allocating a higher dose to central projections, and (3) reducing FSM. The results from this study can potentially provide guidance for DBT system optimization in the future.

Experimental investigation of the distribution patterns of micro-scratches in abrasive waterjet cutting surface.

The existence of striations, and scratches in Abrasive waterjet (AWJ) cutting surface necessitates an exploration of these features for enhancing the cutting accuracy of AWJ machining. This article investigates surface roughness and micro-scratch morphology characteristics on brass cutting surfaces. According to the variation law of surface roughness values, the cutting section can be divided into three regions: the initial region, smooth region, and rough region. Numerous micron-scale scratches were observed in the cutting section. The scratch length, width, and depth values all show an increasing trend as the cutting depth increases, with the scratch length experiencing the greatest growth and variability. The influence of position and traverse speed on scratch size was studied using variance analysis. Furthermore, the length and width of the scratches on the cutting surface are significantly influenced by their position, accounting for 89.19% and 81.13%, respectively. Traverse speed had a minor effect on scratch length and width, accounting for 0.01% and 2.64% respectively. The depth of the scratches is influenced by their position on the cutting surface at a rate of 41.12%, while traverse speed had an impact of 38.10%. Finally, a mathematical method based on standard scores was proposed to assess the quality of the cutting section based on micro-scratch dimension.

Danggui-Shaoyao-San (DSS) ameliorating cognitive impairment in ischemia-reperfusion vascular dementia mice through miR-124 regulating PI3K/Akt signaling pathway.

Vascular dementia (VD) is a disease characterized by cognitive impairment and memory loss due to brain cell damage caused by cerebral vascular ischemia. Danggui-Shaoyao-San (DSS) has been used clinically to treat diseases for centuries. The VD model was established by bilateral common carotid artery (BCCA) repeated ischemia-reperfusion (I/R) and caudal bleeding. Target prediction of DSS and miR-124 in PI3K/Akt signaling pathway by network pharmacology. The effect of DSS on cognitive dysfunction were evaluated through methods such as behavioral experiments, cerebral blood flow monitoring, HE and Nissl staining, western blot, and q-PCR. Prediction result showed that both DSS and miR-124 could target Akt1. DSS treatment significantly reduced hippocampal cell damage, improved learning and memory ability. Mechanically, DSS treatment up-regulated the expression levels of PI3K and Akt protein, and its gene. Bcl-2/Bax index is up-regulated and cell apoptosis reduced. LC3II/LC3I index decreased and autophagy of brain cells increased. Moreover, DSS down-regulated the expression level of miR-124. And inhibition of miR-124 up-regulate the expression of PI3K, Akt. These results suggested that DSS can reduce the content of miR-124 in the hippocampus of VD mice, thus regulating the PI3K/Akt signaling pathway and improving the learning and memory ability of VD mice.

Corrigendum to "WCN24-786 PHASE I DOSE ESCALATION STUDY OF SHR6508, A CALCIUM-SENSING RECEPTOR AGONIST, IN HEMODIALYSIS PATIENTS WITH SECONDARY HYPERPARATHYROIDISM" [Kidney International Reports Volume 9, Issue 4, Supplement, April 2024, Pages S368-S369].

[This corrects the article DOI: 10.1016/j.ekir.2024.02.771.].

Current investigation of the high prevalence of sexual dysfunction in female patients with systemic lupus erythematosus: a cross-sectional study.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects women of childbearing age and has been reported to cause sexual dysfunction in women. Although there are articles on sexual function in women with SLE, the number of articles is small, and the factors affecting sexual function in women with SLE are controversial. Based on this, this study aimed to investigate the prevalence of sexual dysfunction in Chinese female SLE patients and to explore the factors that influence it. The study design was a cross-sectional study conducted from December 2023 to April 2024 in the Department of Rheumatology and Immunology of a tertiary hospital in Hefei, Anhui Province. A total of 293 female patients diagnosed with SLE were enrolled using face-to-face questionnaires and online questionnaires. The questionnaire consisted of four parts: general information questionnaire, fatigue severity scale (FSS), depression-anxiety-stress scale (DASS-21), and female sexual functioning index (FSFI) scale. A total of 173 (59.04%) patients had sexual dysfunction, including 251 (85.67%) with decreased libido and 186 (63.46%) with difficulty in sexual arousal. There was a correlation between the patients' total FSFI scores and age (p = 0.028), marital satisfaction (p < 0.001), own education level (p = 0.008), partner's education level (p = 0.003), place of residence (p = 0.039), monthly household income (p < 0.001), family financial satisfaction(p < 0.001), menstrual status (p = 0.003), hormone use (p = 0.021),immunosuppressant use (p = 0.042), disease activity (p = 0.016), FSS score (p < 0.001), stress score (p < 0.001), anxiety score (p < 0.001) and depression score (p < 0.001)were correlated. The results of stepwise regression analysis showed that marital satisfaction (b = 2.011, t = 3.797, p < 0.001), monthly household income (b = 0.854, t = 2.316, p = 0.021), menstrual status (b = 1.218, t = 2.350, p = 0.019), fatigue scale score (b = - 0.069, t = - 2.302, p = 0.022), and depression score (b = - 0.117, t = - 2.910, p = 0.004) were the influencing factors of FSFI total score, and the difference was statistically significant. The incidence of sexual dysfunction in Chinese female SLE patients is high, and medical personnel should pay more attention to patients' sexual problems, to provide theoretical and practical bases for further prevention, treatment, and care of sexual dysfunction in female SLE patients.

KMT2D mutations promoted tumor progression in diffuse large B-cell lymphoma through altering tumor-induced regulatory T cell trafficking via FBXW7-NOTCH-MYC/TGF-ß1 axis.

Histone methyltransferase KMT2D is one of the most frequently mutated genes in diffuse large B-cell lymphoma (DLBCL) and has been identified as an important pathogenic factor and prognostic marker. However, the biological relevance of KMT2D mutations on tumor microenvironment remains to be determined. KMT2D mutations were assessed by whole-genome/exome sequencing (WGS/WES) in 334 patients and by targeted sequencing in 427 patients with newly diagnosed DLBCL. Among all 761 DLBCL patients, somatic mutations in KMT2D were observed in 143 (18.79%) patients and significantly associated with advanced Ann Arbor stage and MYC expression ≥ 40%, as well as inferior progression-free survival and overall survival. In B-lymphoma cells, the mutation or knockdown of KMT2D inhibited methylation of lysine 4 on histone H3 (H3K4), downregulated FBXW7 expression, activated NOTCH signaling pathway and downstream MYC/TGF-ß1, resulting in alterations of tumor-induced regulatory T cell trafficking. In B-lymphoma murine models established with subcutaneous injection of SU-DHL-4 cells, xenografted tumors bearing KMT2D mutation presented lower H3K4 methylation, higher regulatory T cell recruitment, thereby provoking rapid tumor growth compared with wild-type KMT2D via FBXW7-NOTCH-MYC/TGF-ß1 axis.

HMGB1 released from pyroptotic vascular endothelial cells promotes immune disorders in exertional heatstroke.

BACKGROUND AND OBJECTIVE: Exertional heatstroke (EHS) mainly occurs in healthy young people with rapid onset and high mortality. EHS immune disorders can cause systemic inflammatory responses and multiple organ failure; however, the underlying mechanisms remain unclear. As high mobility group box 1 (HMGB1) is a prototypical alarmin that activates inflammatory and immune responses, this study aimed to investigate the effect and mechanism of HMGB1 in the pathogenesis of EHS. METHODS: Peripheral blood mononuclear cell (PBMC) transcriptome sequencing of healthy volunteers, classical heatstroke patients, and EHS patients was performed. A mouse model of EHS was established and murine tissue damage was evaluated by H&E staining. HMGB1 localization and release were visualized using immunofluorescence staining. Human umbilical vein endothelial cells (HUVECs) and THP-1 cells were co-cultured to study the effects of HMGB1 on macrophages. A neutralizing anti-HMGB1 antibody was used to evaluate the efficacy of EHS treatment in mice. RESULTS: Plasma and serum HMGB1 levels were significantly increased in EHS patients or mice. EHS-induced endothelial cell pyroptosis promoted HMGB1 release in mice. HMGB1 derived from endothelial cell pyroptosis enhanced macrophage pyroptosis, resulting in immune disorders under EHS conditions. Administration of anti-HMGB1 markedly alleviated tissue injury and systemic inflammatory responses after EHS. CONCLUSIONS: The release of HMGB1 from pyroptotic endothelial cells after EHS promotes pyroptosis of macrophages and systemic inflammatory response, and HMGB1-neutralizing antibody therapy has good application prospects for EHS.

TEAD2 Promotes Hepatocellular Carcinoma Development and Sorafenib Resistance via TAK1 Transcriptional Activation.

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer, yet the effectiveness of treatment for HCC patients is significantly hindered by the development of drug resistance to sorafenib. Through the application of ATAC-seq to examine drug-resistant HCC tissues, we identified substantial alterations in chromatin accessibility in sorafenib-resistant patient-derived xenograft (PDX) models. Employing multi-omics data integration analysis, we confirmed TEAD2 as a crucial transcriptional regulator in sorafenib-resistant HCC tissues. Functional assays illustrated that TEAD2 plays a role in promoting HCC progression and enhancing resistance to sorafenib. Mechanistically, we demonstrated that TEAD2 binds to the TAK1 promoter to modulate its expression. Furthermore, we established the involvement of TAK1 in mediating TEAD2-induced sorafenib resistance in HCC, a finding supported by the effectiveness of TAK1 inhibitors. Our research highlights that targeting the TEAD2-TAK1 axis can effectively mitigate drug resistance in HCC patients receiving sorafenib treatment, offering a novel approach for enhancing the treatment outcomes and prognosis of individuals with HCC. Implications: Targeting the TEAD2-TAK1 axis presents a promising therapeutic strategy to overcome sorafenib resistance in HCC, potentially improving treatment outcomes and prognosis for patients.

CDI-NSTSEG: A clinical diagnosis-inspired effective and efficient framework for non-salient small tumor segmentation.

To accurately segment various clinical lesions from computed tomography(CT) images is a critical task for the diagnosis and treatment of many diseases. However, current segmentation frameworks are tailored to specific diseases, and limited frameworks can detect and segment different types of lesions. Besides, it is another challenging problem for current segmentation frameworks to segment visually inconspicuous and small-scale tumors (such as small intestinal stromal tumors and pancreatic tumors). Our proposed framework, CDI-NSTSEG, efficiently segments small non-salient tumors using multi-scale visual information and non-local target mining. CDI-NSTSEG follows the diagnostic process of clinicians, including preliminary screening, localization, refinement, and segmentation. Specifically, we first explore to extract the unique features at three different scales (1×, 0.5×, and 1.5×) based on the scale space theory. Our proposed scale fusion module (SFM) hierarchically fuses features to obtain a comprehensive representation, similar to preliminary screening in clinical diagnosis. The global localization module (GLM) is designed with a non-local attention mechanism. It captures the long-range semantic dependencies of channels and spatial locations from the fused features. GLM enables us to locate the tumor from a global perspective and output the initial prediction results. Finally, we design the layer focusing module (LFM) to gradually refine the initial results. LFM mainly conducts context exploration based on foreground and background features, focuses on suspicious areas layer-by-layer, and performs element-by-element addition and subtraction to eliminate errors. Our framework achieves state-of-the-art segmentation performance on small intestinal stromal tumor and pancreatic tumor datasets. CDI-NSTSEG outperforms the best comparison segmentation method by 7.38% Dice on small intestinal stromal tumors.

Cord blood vitamin A and vitamin D levels in relation to physical growth in exclusively breastfed infants aged 0-6 months.

Background: Vitamins A and D are essential for the health of pregnant women and infants. Nevertheless, the relationship between umbilical cord blood vitamins A and D levels and the physical growth of exclusively breastfed infants remains uncertain. Objective: This cohort study aims to examine the relationship between cord blood vitamins A and D levels and the physical growth of exclusively breastfed infants aged 0-6 months. Methods: 140 singleton mother-infant pairs were recruited in total. Questionnaires were used to collect maternal and infant information, and liquid chromatography was utilized to quantify the levels of vitamins A and D in the umbilical cord blood. Anthropometric measurements were conducted at birth, at 3 and 6 months of age, and the weight-for-age z-score (WAZ), length-for-age z-score (LAZ), head circumference-for-age z-score (HAZ), and BMI-for-age z-score (BMIZ) were calculated. Univariate and multivariate linear regression models were used for the analysis. Results: The average concentration of vitamins A and D in cord blood was 0.58 ± 0.20 µmol/L and 34.07 ± 13.35 nmol/L, both below the normal range for children. After adjusting for confounding factors, vitamin A levels in cord blood positively correlated with HAZ growth in infants aged 3-6 months (ß= 0.75, P < 0.01) while vitamin D levels negatively correlated with LAZ growth (ß= -0.01, P = 0.01) and positively correlated with BMIZ growth (ß= 0.02, P < 0.01). Conclusion: Higher Vitamin A levels at birth promote HAZ growth in infants aged 3-6 months while higher vitamin D levels at birth promote BMIZ growth in infants aged 3-6 months. Clinical trial registration: https://register.clinicaltrials.gov, identifier NCT04017286.

Biocontrol of plant parasitic nematodes by bacteria and fungi: a multi-omics approach for the exploration of novel nematicides in sustainable agriculture.

Plant parasitic nematodes (PPNs) pose a significant threat to global crop productivity, causing an estimated annual loss of US $157 billion in the agriculture industry. While synthetic chemical nematicides can effectively control PPNs, their overuse has detrimental effects on human health and the environment. Biocontrol agents (BCAs), such as bacteria and fungi in the rhizosphere, are safe and promising alternatives for PPNs control. These BCAs interact with plant roots and produce extracellular enzymes, secondary metabolites, toxins, and volatile organic compounds (VOCs) to suppress nematodes. Plant root exudates also play a crucial role in attracting beneficial microbes toward infested roots. The complex interaction between plants and microbes in the rhizosphere against PPNs is mostly untapped which opens new avenues for discovering novel nematicides through multi-omics techniques. Advanced omics approaches, including metagenomics, transcriptomics, proteomics, and metabolomics, have led to the discovery of nematicidal compounds. This review summarizes the status of bacterial and fungal biocontrol strategies and their mechanisms for PPNs control. The importance of omics-based approaches for the exploration of novel nematicides and future directions in the biocontrol of PPNs are also addressed. The review highlighted the potential significance of multi-omics techniques in biocontrol of PPNs to ensure sustainable agriculture.

DN-ODE: Data-driven neural-ODE modeling for breast cancer tumor dynamics and progression-free survivals.

Pharmacokinetic/Pharmacodynamic (PK/PD) modeling is crucial in the development of new drugs. However, traditional population-based PK/PD models encounter challenges when modeling for individual patients. We aim to explore the potential of constructing a pharmacodynamic model for individual breast cancer pharmacodynamics leveraging only limited data from early clinical trial phases. While previous studies on Neural Ordinary Differential Equations (ODEs) suggest promising results in clinical trial practices, they primarily focused on theoretical applications or independent PK/PD modeling. PD modeling from complex and irregular clinical trial data, especially when interacting with PK parameters, is still unclear. To achieve that, we introduce a Data-driven Neural Ordinary Differential Equation (DN-ODE) modeling for breast cancer tumor dynamics and progression-free survival data. To validate this approach, experiments are conducted with early-phase clinical trial data from the Amcenestrant (an oral treatment for breast cancer) dataset (AMEERA 1-2), aiming to predict pharmacodynamics in the later phase (AMEERA 3). DN-ODE model achieves RMSE scores of 8.78 and 0.21 in tumor size and progression-free survival, respectively, with R2 scores over 0.9 for each task. Compared to PK/PD methodologies, DN-ODE is able to predict robust individual tumor dynamics with only limited cycle data. We also introduce Principal Component Analysis visualizations for encoder results, demonstrating the DN-ODE's capability to discern individual distributions and diverse tumor growth patterns. Therefore, DN-ODE facilitates comprehensive drug efficacy assessments, pinpoints potential responders, and aids in trial design.

Global, regional, and national burden and trends of migraine among youths and young adults aged 15-39 years from 1990 to 2021: findings from the global burden of disease study 2021.

BACKGROUND: Migraine, a widespread neurological condition, substantially affects the quality of life, particularly for adolescents and young adults. While its impact is significant, there remains a paucity of comprehensive global research on the burden of migraine in younger demographics. Our study sought to elucidate the global prevalence, incidence, and disability-adjusted life-years (DALYs) associated with migraine in the 15-39 age group from 1990 to 2021, utilizing data from the Global Burden of Disease (GBD) 2021 study. METHODS: Our comprehensive study analyzed migraine data from the GBD 2021 report, examining the prevalence, incidence, and DALYs across 204 countries and territories over a 32-year span. We stratified the information by age, sex, year, geographical region, and Socio-demographic Index (SDI). To evaluate temporal trends in these metrics, we employed the estimated annual percentage change (EAPC) calculation. RESULTS: Between 1990 and 2021, the worldwide prevalence of migraine among 15-39 year-olds increased substantially. By 2021, an estimated 593.8 million cases were reported, representing a 39.52% rise from 425.6 million cases in 1990. Global trends showed increases in age-standardized prevalence rate, incidence rate, and DALY rate for migraine during this period. The EAPC were positive for all three metrics: 0.09 for ASPR, 0.03 for ASIR, and 0.09 for DALY rate. Regions with medium SDI reported the highest absolute numbers of prevalent cases, incident cases, and DALYs in 2021. However, high SDI regions demonstrated the most elevated rates overall. Across the globe, migraine prevalence peaked in the 35-39 age group. Notably, female rates consistently exceeded male rates across all age categories. CONCLUSION: The global impact of migraine on youths and young adults has grown considerably from 1990 to 2021, revealing notable variations across SDI regions, countries, age groups, and sexes. This escalating burden necessitates targeted interventions and public health initiatives, especially in areas and populations disproportionately affected by migraine.

NCAPD2 augments the tumorigenesis and progression of human liver cancer via the PI3K­Akt­mTOR signaling pathway.

Non­SMC condensin I complex subunit D2 (NCAPD2) is a newly identified oncogene; however, the specific biological function and molecular mechanism of NCAPD2 in liver cancer progression remain unknown. In the present study, the aberrant expression of NCAPD2 in liver cancer was investigated using public tumor databases, including TNMplot, The Cancer Genome Atlas and the International Cancer Genome Consortium based on bioinformatics analyses, and it was validated using a clinical cohort. It was revealed that NCAPD2 was significantly upregulated in liver cancer tissues compared with in control liver tissues, and NCAPD2 served as an independent prognostic factor and predicted poor prognosis in liver cancer. In addition, the expression of NCAPD2 was positively correlated with the percentage of Ki67+ cells. Finally, single­cell sequencing data, gene­set enrichment analyses and in vitro investigations, including cell proliferation assay, Transwell assay, wound healing assay, cell cycle experiments, cell apoptosis assay and western blotting, were carried out in human liver cancer cell lines to assess the biological mechanisms of NCAPD2 in patients with liver cancer. The results revealed that the upregulation of NCAPD2 enhanced tumor cell proliferation, invasion and cell cycle progression at the G2/M­phase transition, and inhibited apoptosis in liver cancer cells. Furthermore, NCAPD2 overexpression was closely associated with the phosphatidylinositol 3­kinase (PI3K)­Akt­mammalian target of rapamycin (mTOR)/c­Myc signaling pathway and epithelial­mesenchymal transition (EMT) progression in HepG2 and Huh7 cells. In addition, upregulated NCAPD2 was shown to have adverse effects on overall survival and disease­specific survival in liver cancer. In conclusion, the overexpression of NCAPD2 was shown to lead to cell cycle progression at the G2/M­phase transition, activation of the PI3K­Akt­mTOR/c­Myc signaling pathway and EMT progression in human liver cancer cells.

Grain Structure and Texture Evolution in the Bottom Zone of Dissimilar Friction-Stir-Welded AA2024-T351 and AA7075-T651 Joints.

High-strength dissimilar aluminum alloys are difficult to connect by fusion welding, while they can be successfully joined by friction stir welding (FSW). However, the asymmetrical deformation and heat input that occur during FSW result in the formation of a heterogeneous microstructure in their welded zone. In this work, the grain structure and texture evolution in the bottom zones of dissimilar FSW AA2024-T351 and AA7075-T651 joints at different welding speeds (feeding speeds) were quantitatively investigated. The results indicated that dynamic recrystallization occurs in the bottom zones of dissimilar FSW joints, and equiaxed grains with low grain sizes are formed at the welding speed of 60-240 mm/min. A high fraction of the recrystallized grains were generated in the bottom zones of the joints at a low welding speed, while a high fraction of the substructured grains are produced at a high welding speed. Different types of shear textures are produced in the bottom zones of the joints; the number fraction of shear texture types depends on different welding speeds. This study helps to understand the mechanism of microstructure homogenization in dissimilar FSW joints and provides a basis for further improving the microstructure of the welded zone for engineering applications.

Habitat Imaging With Tumoral and Peritumoral Radiomics for Prediction of Lung Adenocarcinoma Invasiveness on Preoperative Chest CT: A Multicenter Study.

Background: Tumors' growth processes result in spatial heterogeneity, with the development of tumor subregions (i.e., habitats) having unique biologic characteristics. Objective: To develop and validate a habitat model combining tumor and peritumoral radiomics features on chest CT for predicting invasiveness of lung adenocarcinoma. Methods: This retrospective study included 1156 patients (mean age, 57.5 years; 464 male, 692 female) from three centers and a public dataset, who underwent chest CT before lung adenocarcinoma resection (variable date ranges across datasets). Patients from one center formed training (n=500) and validation (n=215) sets; patients from the other sources formed three external test sets (n=249, 113, 79). For each patient, a single nodule was manually segmented on chest CT. The nodule segmentation was combined with an automatically generated 4-mm peritumoral region into a whole-volume volume-of-interest (VOI). A Gaussian mixture model (GMM) identified voxel clusters with similar first-order energy across patients. GMM results were used to divide each patient's whole-volume VOI into multiple habitats, defined consistently across patients. Radiomic features were extracted from each habitat. After feature selection, a habitat model was developed for predicting invasiveness, using pathologic assessment as a reference. An integrated model was constructed, combining features extracted from habitats and whole-volume VOIs. Model performance was evaluated, including in subgroups based on nodule density (pure ground-glass, part-solid, solid). Results: Invasive cancer was diagnosed in 625/1156 patients. GMM identified four as the optimal number of voxel clusters and thus of per-patient tumor habitats. The habitat model had AUC of 0.932 in the validation set, and 0.881, 0.880, and 0.764 in the three external test sets. The integrated model had AUC of 0.947 in the validation set and 0.936, 0.908, and 0.800 in the three external test sets. In the three external test sets combined, across nodule densities, AUCs for the habitat model were 0.836-0.969 and for the integrated model were 0.846-0.917. Conclusions: Habitat imaging combining tumoral and peritumoral radiomic features could help predict lung adenocarcinoma invasiveness. Prediction is improved when combining information on tumor subregions and the tumor overall. Clinical Impact: The findings may aid personalized preoperative assessments to guide clinical decision-making in lung adenocarcinoma.

The impact of a growth mindset on high school students' learning subjective well-being: the serial mediation role of achievement motivation and grit.

Purpose: The learning subjective well-being of high school students has significant value for their academic achievement and future life development. A growth mindset is one of the key factors affecting the learning subjective well-being of high school students. However, research on the mechanism by which a growth mindset affects learning subjective well-being is still relatively limited. Therefore, the study aims to investigate the impact of a growth mindset on the learning subjective well-being of high school students, as well as the role that achievement motivation and grit play as serial mediators in this relationship. Methods: This study employed a convenience sampling method to select 708 high school students from Chinese public high schools as participants. The research utilized the Growth Mindset Scale, Achievement Motivation Scale, Grit Scale, and the Learning Subjective Well-being Questionnaire for High School Students to collect data. All data were analyzed using SPSS 26.0, employing Model 6 from Hayes' SPSS PROCESS macro to test the serial mediation model. Results: Our results found that (1) high school students' growth mindset positively predicted their learning subjective well-being. (2) Achievement motivation played a mediating role between a growth mindset and learning subjective well-being among high school students. (3) Grit acted as a mediator between learning subjective well-being and growth mindset among high school students. (4) Achievement motivation and grit served as serial mediators between a growth mindset and learning subjective well-being among high school students. Conclusion: A growth mindset can influence the learning subjective well-being of high school students through achievement motivation and grit. Educators can enhance the learning subjective well-being of high school students by implementing intervention strategies that foster a growth mindset, achievement motivation, and grit.

Identification of phosphodiesterase-7A (PDE7A) as a novel target for reducing ethanol consumption in mice.

BACKGROUND: Ethanol elicits a rapid stimulatory effect and a subsequent, prolonged sedative response, which are potential predictors of EtOH consumption by decreasing adenosine signaling; this phenomenon also reflects the obvious sex difference. cAMP-PKA signaling pathway modulation can influence the stimulatory and sedative effects induced by EtOH in mice. This study's objective is to clarify the role of phosphodiesterase (PDE) in mediating the observed sex differences in ethanol responsiveness between male and female animals. METHODS: EtOH was administered intraperitoneally (i.p.) for 7 days to identify the changes in PDE isoforms in response to EtOH treatment. Additionally, EtOH consumption and preference of male and female C57BL/6J mice were assessed using the drinking-in-the-dark (DID) and two-bottle choice (2BC) tests. Further, pharmacological inhibition of PDE7A heterozygote knockout mice was performed to investigate its effects on ethanol-induced stimulation and sedation in both male and female mice. Finally, Western blotting analysis was performed to evaluate the alterations in cAMP-PKA/Epac2 pathways. RESULTS: Ethanol administration resulted in an immediate upregulation in PDE7A expression in female mice, indicating a strong association between PDE7A and ethanol stimulation. Through the pharmacological inhibition of PDE7A KD mice, we have demonstrated, for the first time, that PDE7A selectively attenuates ethanol responsiveness and consumption exclusively in female mice may be associated with the cAMP-PKA/Epac2 pathway and downstream phosphorylation of CREB and ERK1/2. CONCLUSIONS: PDE7A inhibition or knockdown attenuates EtOH responsiveness and consumption exclusively in female mice associated the change of cAMP-PKA/Epac2 signaling pathways, thereby highlighting its potential as a novel therapeutic target for alcohol use disorder.

Salvianolic acid B improves diabetic skin wound repair through Pink1/Parkin-mediated mitophagy.

Diabetic skin wound is a disturbing and rapidly evolving clinical issue. Here, we investigated how salvianolic acid B (Sal B) affected the diabetic wound healing process. Following Sal B administration, histopathological damage was investigated by H&E and Masson staining, and CD34, apoptosis and mitophagy markers were measured by immunofluorescence, immunohistochemistry, and western blotting. Migration, proliferation, and mitochondrial function of high glucose (HG) -induced HMEC-1 cells were measured. The effects of si-Parkin on endothelial cell migration, apoptosis and mitochondrial autophagy were examined. Sal B alleviated inflammatory cell infiltration and promoted angiogenesis in skin wound tissue. Apoptosis and mitophagy were ameliorated by Sal B in diabetic skin wound tissues and HG-induced HMEC-1 cells. Parkin inhibition impaired the migratorypromoted cell apoptosis and inhibited mitophagy of HMEC-1 cells. This finding demonstrated that Sal B promoted diabetic skin wound repair via Pink1/Parkin-mediated mitophagy, improved our understanding of the diabetic wound healing process.

Diffusion Kurtosis Imaging in Diagnosing Parkinson's Disease: A Preliminary Comparison Study Between Kurtosis Metric and Radiomic Features.

RATIONALE AND OBJECTIVES: Parkinson's disease (PD) shows small structural changes in nigrostriatal pathways, which can be sensitively captured through diffusion kurtosis imaging (DKI). However, the value of DKI and its radiomic features in the classification performance of PD still need confirmation. This study aimed to compare the diagnostic efficiency of DKI-derived kurtosis metric and its radiomic features with different machine learning models for PD classification. MATERIALS AND METHODS: 75 people with PD and 80 healthy individuals had their brains scanned using DKI. These images were pre-processed and the standard atlas were non-linearly registered to them. With the labels in atlas, different brain regions in nigrostriatal pathways, including the caudate nucleus, putamen, pallidum, thalamus, and substantia nigra, were chosen as the region of interests (ROIs) to warped to the native space to measure the mean kurtosis (MK). Additionally, new radiomic features were developed for comparison. To handle the large amount of data, a statistical method called Z-score normalization and another method called LASSO regression were used to simplify the information. From this, a few most important features were chosen, and a combined score called Radscore was calculated using LASSO regression. For the comprehensive analyses, three different conventional machine learning models were then created: logistic regression (LR), support vector machine (SVM), and random forest (RF). To ensure the models were accurate, a process called 10-fold cross-validation was used, where the data were split into 10 parts for training and testing. RESULTS: Using MK alone, the models achieved good results in correctly identifying PD in the validation set, with LR at 0.90, RF at 0.93, and SVM at 0.90. When the radiomic features were added, the models performed even better, with LR at 0.92, RF at 0.95, and SVM at 0.91. Additionally, a nomogram combining all the information was created to predict the likelihood of someone having PD, which had an AUC of 0.91. CONCLUSION: These findings suggest that the combination of DKI measurements and radiomic features can effectively diagnose PD by providing more detailed information about the brain's condition and the processes involved in the disease.