Expression profiling and function analysis identified new genes regulating cumulus expansion and apoptosis.

Studies on the mechanisms behind cumulus expansion and cumulus cell (CC) apoptosis are essential for understanding the mechanisms for oocyte maturation. Genes expressed in CCs might be used as markers for competent oocytes and/or embryos. In this study, both in vitro (IVT) and in vivo (IVO) mouse oocyte models with significant difference in cumulus expansion and CC apoptosis were used to identify and validate new genes regulating cumulus expansion and CC apoptosis of mouse oocytes. We first performed mRNA sequencing and bioinformatic analysis using the IVT oocyte model to identify candidate genes. We then analyzed functions of the candidate genes by RNAi or gene overexpression to select the candidate cumulus expansion and CC apoptosis-regulating genes. Finally, we validated the cumulus expansion and CC apoptosis-regulating genes using the IVO oocyte model. The results showed that while Spp1, Sdc1, Ldlr, Ezr and Mmp2 promoted, Bmp2, Angpt2, Edn1, Itgb8, Cxcl10 and Agt inhibited cumulus expansion. Furthermore, Spp1, Sdc1 and Ldlr inhibited CC apoptosis. In conclusion, by using both IVT and IVO oocyte models, we have identified and validated a new group of cumulus expansion and/or apoptosis-regulating genes, which may be used for selection of quality oocytes/embryos and for elucidating the molecular mechanisms behind oocyte maturation.

A Visual Analysis of the Research Dynamics in Resistance to EGFR Inhibitors for NSCLC.

Purpose: Activating mutations in epidermal growth factor receptor (EGFR) have been identified as key predictive biomarkers for the customized treatment with EGFR tyrosine kinase inhibitors (TKIs) in non-small cell lung cancer (NSCLC), aiding in improving patient response rates and survival. However, resistance challenges the efficacy of these treatments, with limited understanding of post-resistance therapeutic strategies. A deep understanding of the biology and resistance mechanisms of EGFR-mutant NSCLC is crucial for developing new treatment approaches. This study, through bibliometric analysis, summarizes the trends in research on resistance to EGFR-TKIs. Methods: Research papers on NSCLC with EGFR inhibitor resistance were collected from the Web of Science Core Collection (WoSCC). The analysis utilized bibliometric tools like CiteSpace, VOSviewer, and other platforms for comprehensive analysis and visualization of the outcomes. Results: The WoSCC database contains a total of 5866 documents on resistance to EGFR-TKIs treatment, including 4727 articles (93.48%) and 1139 reviews (6.52%), spanning 81 countries and regions, 4792 institutions, with the involvement of 23,594 authors. Since 2016, there has been a significant increase in publications in this field. China has the highest publication output, while the United States has the highest citation count for papers. Harvard University leads in terms of the number of publications. Among the top ten journals with the highest output, Clinical Cancer Research has the highest impact factor at 11.5, with 90% of the journals classified in Q1 or Q2. Rafael Rosell is one of the most influential authors in this field, ranking second in publication volume and fourth in citation count. Research on EGFR-TKIs resistance mainly focuses on genetic testing, resistance mechanisms, and post-resistance treatment strategies. Conclusion: This study provides researchers with a reliable basis and guidance for finding authoritative references, understanding research trends, and exploring potential directions.

Remote ischemic conditioning prevents ischemic cerebrovascular events in children with moyamoya disease: a randomized controlled trial.

BACKGROUND: Moyamoya disease (MMD) is a significant cause of childhood stroke and transient ischemic attacks (TIAs). This study aimed to assess the safety and efficacy of remote ischemic conditioning (RIC) in children with MMD. METHODS: In a single-center pilot study, 46 MMD patients aged 4 to 14 years, with no history of reconstructive surgery, were randomly assigned to receive either RIC or sham RIC treatment twice daily for a year. The primary outcome measured was the cumulative incidence of major adverse cerebrovascular events (MACEs). Secondary outcomes included ischemic stroke, recurrent TIA, hemorrhagic stroke, revascularization rates, and clinical improvement assessed using the patient global impression of change (PGIC) scale during follow-up. RIC-related adverse events were also recorded, and cerebral hemodynamics were evaluated using transcranial Doppler. RESULTS: All 46 patients completed the final follow-up (23 each in the RIC and sham RIC groups). No severe adverse events associated with RIC were observed. Kaplan-Meier analysis indicated a significant reduction in MACEs frequency after RIC treatment [log-rank test (Mantel-Cox), P = 0.021]. At 3-year follow-up, two (4.35%) patients had an ischemic stroke, four (8.70%) experienced TIAs, and two (4.35%) underwent revascularization as the qualifying MACEs. The clinical improvement rate in the RIC group was higher than the sham RIC group on the PGIC scale (65.2% vs. 26.1%, P < 0.01). No statistical difference in cerebral hemodynamics post-treatment was observed. CONCLUSIONS: RIC is a safe and effective adjunct therapy for asymptomatic children with MMD. This was largely due to the reduced incidence of ischemic cerebrovascular events.

Concomitant genomic features stratify prognosis to patients with advanced EGFR mutant lung cancer.

This study aimed to explore the clinical significance of genomics features including tumor mutation burden (TMB) and copy number alteration (CNA) for advanced EGFR mutant lung cancer. We retrospectively identified 1378 patients with advanced EGFR mutant lung cancer and next-generation sequencing tests from three cohorts. Multiple co-occurring genomics alternations occurred in a large proportion (97%) of patients with advanced EGFR mutant lung cancers. Both TMB and CNA were predictive biomarkers for these patients. A joint analysis of TMB and CNA found that patients with high TMB and high CNA showed worse responses to EGFR-TKIs and predicted worse outcomes. TMBhighCNAhigh, as a high-risk genomic feature, showed predictive ability in most of the subgroups based on clinical characteristics. These patients had larger numbers of metastatic sites, and higher rates of EGFR copy number amplification, TP53 mutations, and cell-cycle gene alterations, which showed more potential survival gain from combination treatment. Furthermore, a nomogram based on genomic features and clinical features was developed to distinguish prognosis. Genomic features could stratify prognosis and guide clinical treatment for patients with advanced EGFR mutant lung cancer.

Glycyrol Relieves Ulcerative Colitis by Promoting the Fusion of ZO-1 with the Cell Membrane through the Enteric Glial Cells GDNF/RET Pathway.

The damage to the mechanical barrier of the intestinal mucosa is the initiating factor and the core link of the progression of ulcerative colitis (UC). Protecting the mechanical barrier of the intestinal mucosa is of great significance for improving the health status of UC patients. ZO-1 is a key scaffold protein of the mechanical barrier of the intestinal mucosa, and its fusion with the membrane of the intestinal epithelium is a necessary condition to maintain the integrity of the mechanical barrier of the intestinal mucosa. Enteric glial cells (EGCs) play an important role in the maintenance of intestinal homeostasis and have become a new target for regulating intestinal health in recent years. In this study, we found that glycyrol (GC), a representative coumarin compound isolated from Licorice (Glycyrrhiza uralensis Fisch, used for medicine and food), can alleviate UC by promoting the production of neurotrophic factor GDNF in mice EGCs. Specifically, we demonstrated that GC promotes the production of GDNF, then activates its receptor RET, promotes ZO-1 fusion with cell membranes, and protects the intestinal mucosal mechanical barrier. The results of this study can provide new ideas for the prevention and treatment of UC.

CRISPR/Cas9 screen reveals that targeting TRIM34 enhances ferroptosis sensitivity and augments immunotherapy efficacy in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a prevalent malignancy characterized by complex heterogeneity and drug resistance. Resistance to ferroptosis is closely related to the progression of HCC. While HCC tumors vary in their sensitivity to ferroptosis, the precise factors underlying this heterogeneity remain unclear. In this study, we sought to elucidate the mechanisms that contribute to ferroptosis resistance in HCC. Whole-genome CRISPR/Cas9 screen using a subtoxic concentration (IC20) of ferroptosis inducer erastin in the HCC cell line Huh7 revealed TRIM34 as a critical driver of ferroptosis resistance in HCC. Further investigation revealed that TRIM34 suppresses ferroptosis in HCC cells, promoting their proliferation, migration, and invasion both in vitro and in vivo. Furthermore, TRIM34 expression is elevated in HCC tumor tissues, correlating with a poor prognosis. Mechanistically, TRIM34 directly interacts with Up-frameshift 1 (UPF1), a core component of the nonsense-mediated mRNA decay (NMD) pathway, to promote its ubiquitination and degradation. This interaction suppresses GPX4 transcript degradation, thus promoting the protein levels of this critical ferroptosis suppressor in HCC. In light of the close crosstalk between ferroptosis and the adaptive immune response in cancer, HCC cells with targeting knockdown of TRIM34 exhibited an improved response to anti-PD-1 treatment. Taken together, the TRIM34/UPF1/GPX4 axis mediates ferroptosis resistance in HCC, thereby promoting malignant phenotypes. Targeting TRIM34 may thus represent a promising new strategy for HCC treatment.

The mitochondrial carboxylase PCCA interacts with Listeria monocytogenes phospholipase PlcB to modulate bacterial survival.

Listeria monocytogenes, a prominent foodborne pathogen responsible for zoonotic infections, owes a significant portion of its virulence to the presence of the phospholipase PlcB. In this study, we performed an in-depth examination of the intricate relationship between L. monocytogenes PlcB and host cell mitochondria, unveiling a novel participant in bacterial survival: the mitochondrial carboxylase propionyl-coenzyme A carboxylase (PCCA). Our investigation uncovered previously unexplored levels of interaction and colocalization between PCCA and PlcB within host cells, with particular emphasis on the amino acids 504-508 of PCCA, which play a pivotal role in this partnership. To assess the effect of PCCA expression on L. monocytogenes proliferation, PCCA expression levels were manipulated by siRNA-si-PCCA or pCMV-N-HA-PCCA plasmid transfection. Our findings demonstrated a clear inverse correlation between PCCA expression levels and the proliferation of L. monocytogenes. Furthermore, the effect of L. monocytogenes infection on PCCA expression was investigated by assessing PCCA mRNA and protein expression in HeLa cells infected with L. monocytogenes. These results indicate that L. monocytogenes infection did not significantly alter PCCA expression. These findings led us to propose that PCCA represents a novel participant in L. monocytogenes survival, and its abundance has a detrimental impact on bacterial proliferation. This suggests that L. monocytogenes may employ PlcB-PCCA interactions to maintain stable PCCA expression, representing a unique pro-survival strategy distinct from that of other intracellular bacterial pathogens. IMPORTANCE: Mitochondria represent attractive targets for pathogenic bacteria seeking to modulate host cellular processes to promote their survival and replication. Our current study has uncovered mitochondrial carboxylase propionyl-coenzyme A carboxylase (PCCA) as a novel host cell protein that interacts with L. monocytogenes PlcB. The results demonstrate that PCCA plays a negative regulatory role in L. monocytogenes infection, as heightened PCCA levels are associated with reduced bacterial survival and persistence. However, L. monocytogenes may exploit the PlcB-PCCA interaction to maintain stable PCCA expression and establish a favorable intracellular milieu for bacterial infection. Our findings shed new light on the intricate interplay between bacterial pathogens and host cell mitochondria, while also highlighting the potential of mitochondrial metabolic enzymes as antimicrobial agents.

Hypomethylation-enhanced CRTC2 expression drives malignant phenotypes and primary resistance to immunotherapy in hepatocellular carcinoma.

The cyclic AMP-responsive element-binding protein (CREB)-regulated transcription coactivator 2 (CRTC2) is a crucial regulator of hepatic lipid metabolism and gluconeogenesis and correlates with tumorigenesis. However, the mechanism through which CRTC2 regulates hepatocellular carcinoma (HCC) progression is largely unknown. Here, we found that increased CRTC2 expression predicted advanced tumor grade and stage, as well as worse prognosis in patients with HCC. DNA promoter hypomethylation led to higher CRTC2 expression in HCC. Functionally, CRTC2 contributed to HCC malignant phenotypes through the activated Wnt/ß-catenin pathway, which could be abrogated by the small-molecular inhibitor XAV-939. Moreover, Crtc2 facilitated tumor growth while concurrently downregulating the PD-L1/PD-1 axis, resulting in primary resistance to immunotherapy. In immunocompetent mice models of HCC, targeting Crtc2 in combination with anti-PD-1 therapy prominently suppressed tumor growth by synergistically enhancing responsiveness to immunotherapy. Collectively, targeting CRTC2 might be a promising therapeutic strategy to sensitize immunotherapy in HCC.

The Impact of the Composition on the Properties of Simulated Lunar Mare Basalt Fibers.

Lunar mare basalt is recognized as an important in situ resource on the lunar surface. However, the significant compositional variability of lunar mare basalts introduces uncertainties concerning the potential for their use in fabricating fibers and composite materials. This study investigates the impact of different components on the fiber-forming capabilities of mare basalts by simulating the compositions of basalts collected from several well-known lunar missions and then preparing simulated lunar mare basalt fibers. Raman spectroscopy is primarily employed for analysis and characterization, using "peak area normalization" to explore the impact of compositional fluctuations in the simulated lunar mare basalts on the glass network structure. The findings indicate that an increase in the Fe content raises the likelihood of basalt fibers crystallizing. Additionally, Fe3+ is shown to substitute for Si and Al in constructing bridging oxygen bonds in the network structure, albeit reducing the overall polymerization of the network. Meanwhile, Fe2+ acts as a network modifier to enhance the mechanical properties of the fibers.

A Comprehensive Prediction Model for Futile Recanalization in AIS Patients Post-Endovascular Therapy: Integrating Clinical, Imaging, and No-Reflow Biomarkers.

Our study aimed to construct a predictive model for identifying instances of futile recanalization in patients with anterior circulation occlusion acute ischemic stroke (AIS) who achieved complete reperfusion following endovascular therapy. We included 173 AIS patients who attained complete reperfusion, as indicated by a Modified Thrombolysis in Cerebral Infarction (mTICI) scale score of 3. Our approach involved a thorough analysis of clinical factors, imaging biomarkers, and potential no-reflow biomarkers through both univariate and multivariate analyses to identify predictors of futile recanalization. The comprehensive model includes clinical factors such as age, presence of diabetes, admission NIHSS score, and the number of stent retriever passes; imaging biomarkers like poor collaterals; and potential no-reflow biomarkers, notably disrupted blood-brain barrier (OR 4.321, 95% CI 1.794-10.405; p = 0.001), neutrophil-to-lymphocyte ratio (NLR; OR 1.095, 95% CI 1.009-1.188; p = 0.030), and D-dimer (OR 1.134, 95% CI 1.017-1.266; p = 0.024). The model demonstrated high predictive accuracy, with a C-index of 0.901 (95% CI 0.855-0.947) and 0.911 (95% CI 0.863-0.954) in the original and bootstrapping validation samples, respectively. Notably, the comprehensive model showed significantly improved predictive performance over models that did not include no-reflow biomarkers, evidenced by an integrated discrimination improvement of 8.86% (95% CI 4.34%-13.39%; p < 0.001) and a categorized reclassification improvement of 18.38% (95% CI 3.53%-33.23%; p = 0.015). This model, which leverages the potential of no-reflow biomarkers, could be especially beneficial in healthcare settings with limited resources. It provides a valuable tool for predicting futile recanalization, thereby informing clinical decision-making. Future research could explore further refinements to this model and its application in diverse clinical settings.

Association analysis between Acetyl-Coenzyme A Acyltransferase-1 gene polymorphism and growth traits in Xiangsu pigs.

Introduction: Acetyl-Coenzyme A Acyltransferase-1 (ACAA1) is a peroxisomal acyltransferase involved in fatty acid metabolism. Current evidence does not precisely reveal the effect of the ACAA1 gene on pig growth performance. Methods: The present study assessed the mRNA expression levels of the ACAA1 gene in the heart, liver, spleen, lung, kidney of 6-month-old Xiangsu pigs and in the longissimus dorsi muscle at different growth stages (newborn, 6 months and 12 months of age) using RT-qPCR. The relationship between single-nucleotide polymorphisms (SNPs) of ACAA1 gene and growth traits in 6-month-old and 12-month-old Xiangsu pigs was investigated on 184 healthy Xiangsu pigs using Sanger sequencing. Results: The ACAA1 gene was expressed in heart, liver, spleen, lung, kidney, and longissimus dorsi muscle of 6-month-old pigs, with the highest level of expression in the liver. ACAA1 gene expression in the longissimus dorsi muscle decreased with age (p < 0.01). In addition, four SNPs were identified in the ACAA1 gene, including exon g.48810 A>G (rs343060194), intron g.51546 T>C (rs319197012), exon g.55035 T>C (rs333279910), and exon g.55088 C>T (rs322138947). Hardy-Weinberg equilibrium (p > 0.05) was found for the four SNPs, and linkage disequilibrium (LD) analysis revealed a strong LD between g.55035 T>C (rs333279910) and g.55088 C>T (rs322138947) (r 2 = 1.000). Association analysis showed that g.48810 A>G (rs343060194), g.51546 T>C (rs319197012), g.55035 T>C (rs333279910), and g.55088 C>T (rs322138947) varied in body weight, body length, body height, abdominal circumference, leg and hip circumference and living backfat thickness between 6-month-old and 12-month-old Xiangsu pigs. Conclusion: These findings strongly demonstrate that the ACAA1 gene can be exploited for marker-assisted selection to improve growth-related phenotypes in Xiangsu pigs and present new candidate genes for molecular pig breeding.

Leaf nutrient traits of planted forests demonstrate a heightened sensitivity to environmental changes compared to natural forests.

Leaf nutrient content (nitrogen, phosphorus) and their stoichiometric ratio (N/P) as key functional traits can reflect plant survival strategies and predict ecosystem productivity responses to environmental changes. Previous research on leaf nutrient traits has primarily focused on the species level with limited spatial scale, making it challenging to quantify the variability and influencing factors of forest leaf nutrient traits on a macro scale. This study, based on field surveys and literature collected from 2005 to 2020 on 384 planted forests and 541 natural forests in China, investigates the differences in leaf nutrient traits between forest types (planted forests, natural forests) and their driving factors. Results show that leaf nutrient traits (leaf nitrogen content (LN), leaf phosphorus content (LP), and leaf N/P ratio) of planted forests are significantly higher than those of natural forests (P< 0.05). The impact of climatic and soil factors on the variability of leaf nutrient traits in planted forests is greater than that in natural forests. With increasing forest age, natural forests significantly increase in leaf nitrogen and phosphorus content, with a significant decrease in N/P ratio (P< 0.05). Climatic factors are key environmental factors dominating the spatial variability of leaf nutrient traits. They not only directly affect leaf nutrient traits of planted and natural forest communities but also indirectly through regulation of soil nutrients and stand factors, with their direct effects being more significant than their indirect effects.

Guided Design of Efficient Oxygen Evolution Catalysts Using Patent Analysis.

The facile and rapid design of efficient oxygen evolution reaction (OER) catalysts holds paramount significance for energy conversion devices, such as water electrolyzers and fuel cells. Despite substantial progress in catalyst synthesis and performance exploration, the design and selection processes remain inefficient. In this context, we integrate patent analysis with catalyst design, leveraging the scholarly research functionalities within patent analyses to aid in the design and synthesis of a NiFeRu-carbon catalyst as a high-performance OER catalyst. The results demonstrate that the NiFeRu-Carbon catalyst with low Ru loading (0.3 wt %) exhibits an overpotential of only 219 mV at 10 mA cm-2 under alkaline conditions, and after continuous operation for 200 h, the overpotential only attenuates by 15 mV. The incorporation of high-valence Ru dopants elevated the intrinsic activity of individual catalytic sites within NiFe-layered double hydroxides (LDHs). During the catalytic process, the partial dissolution of Ru might lead to the generation of numerous oxygen vacancies within NiFe- LDH, thereby enhancing the catalyst's activity and stability.

Circulating microRNA-33b levels are associated with the presence and severity of coronary heart disease.

MicroRNA-33b (miR-33b) affected various biological pathways in regulating cholesterol homeostasis which may link to the pathogenesis of atherosclerotic lesions. However, whether this marker is associated with the presence and severity of coronary heart disease (CHD) is undetermined. We aim to explore the diagnostic value of circulating miR-33b level in the presence and severity of CHD. Altogether 320 patients were enrolled, including 240 patients diagnosed with CHD while 80 were classified as controls after CAG examination. Circulating miR-33b level was analyzed in all subjects, the Gensini score was calculated to assess the severity of stenotic lesions. The association between miR-33b and the presence and severity of CHD was analyzed, and the diagnostic potential of miR-33b of CHD was performed by the receiver operating characteristic (ROC) analysis. The CHD group had higher miR-33b levels (p < 0.001), and the miR-33b content significantly elevated following an increasing Gensini score (p for trend < 0.001). After adjustments for potential risk factors, such as several blood lipid markers, miR-33b remained a significant determinant for CHD (p < 0.001). ROC analysis disclosed that the AUC was 0.931. The optimal cutoff value of miR-33b was with a sensitivity of 81.3% and a specificity of 98.7% in differentiating CHD. It can prognosticate that the higher level of miR-33b was linked to increased severity of disease in CHD patients. Thus, the application of this marker might assist in the diagnosis and classification of CHD patients. Nevertheless, additional studies with larger sample sizes will be required to verify these results.

Elevation Influences Belowground Biomass Proportion in Forests by Affecting Climatic Factors, Soil Nutrients and Key Leaf Traits.

Forest biomass allocation is a direct manifestation of biological adaptation to environmental changes. Studying the distribution patterns of forest biomass along elevational gradients is ecologically significant for understanding the specific impacts of global change on plant resource allocation strategies. While aboveground biomass has been extensively studied, research on belowground biomass remains relatively limited. Furthermore, the patterns and driving factors of the belowground biomass proportion (BGBP) along elevational gradients are still unclear. In this study, we investigated the specific influences of climatic factors, soil nutrients, and key leaf traits on the elevational pattern of BGBP using data from 926 forests at 94 sites across China. In this study, BGBP data were calculated from the root biomass to the depth of 50 cm. Our findings indicate considerable variability in forest BGBP at a macro scale, showing a significant increasing trend along elevational gradients (p < 0.01). BGBP significantly decreases with increasing temperature and precipitation and increases with annual mean evapotranspiration (MAE) (p < 0.01). It decreases significantly with increasing soil phosphorus content and increases with soil pH (p < 0.01). Key leaf traits (leaf nitrogen (LN) and leaf phosphorus (LP)) are positively correlated with BGBP. Climatic factors (R2 = 0.46) have the strongest explanatory power for the variation in BGBP along elevations, while soil factors (R2 = 0.10) and key leaf traits (R2 = 0.08) also play significant roles. Elevation impacts BGBP directly and also indirectly through influencing such as climate conditions, soil nutrient availability, and key leaf traits, with direct effects being more pronounced than indirect effects. This study reveals the patterns and controlling factors of forests' BGBP along elevational gradients, providing vital ecological insights into the impact of global change on plant resource allocation strategies and offering scientific guidance for ecosystem management and conservation.

Long term for patients with futile endovascular reperfusion after stroke.

AIMS: With the progress of thrombectomy technology, the vascular recanalization rate of patients with stroke has been continuously improved, but the proportion of futile recanalization (FR) is still quite a few. The long-term prognosis and survival of patients with FR and its influencing factors remain unclear. METHODS: Consecutive patients who received endovascular treatment (EVT) for ischemic stroke were enrolled between 2013 and 2021 from a single-center prospectively registry study. We evaluated the long-term outcome of these patients by Kaplan-Meier survival analysis, and the multivariable logistic regression curve was performed to analyze influencing factors. RESULTS: Among 458 patients with FR, 56.4% of patients survived at 1 year, and 50.4% at 2 years. In the multivariate regression analysis, age, premorbid modified Rankin Scale (mRS), National Institutes of Health Stroke Scale (NIHSS), posterior circulation infarct, general anesthesia, symptomatic intracerebral hemorrhage (sICH), and decompressive craniectomy were found to be related to unfavorable outcomes in long-term. Age, premorbid mRS, NIHSS, general anesthesia, and sICH were predictors of long-term mortality. CONCLUSIONS: Futile recanalization accounts for a large proportion of stroke patients after thrombectomy. This study on the long-term prognosis of such patients is beneficial to the formulation of treatment plans and the prediction of therapeutic effects.

Distinguishing EGFR mutation molecular subtypes based on MRI radiomics features of lung adenocarcinoma brain metastases.

OBJECTIVE: To explore the feasibility of identifying epidermal growth factor receptor (EGFR) mutation molecular subtypes in primary lesions based on the radiomics features of lung adenocarcinoma brain metastases using magnetic resonance imaging (MRI). METHODS: We retrospectively analyzed clinical, imaging, and genetic testing data of patients with lung adenocarcinoma with EGFR gene mutations who had brain metastases. Three-dimensional radiomics features were extracted from contrast-enhanced T1-weighted images. The volume of interest was delineated and normalized using Z-score, dimensionality reduction was performed using principal component analysis, feature selection using Relief, and radiomics model construction using adaptive boosting as a classifier. Data were randomly divided into training and testing datasets at an 8:2 ratio. Five-fold cross-validation was conducted in the training set to select the optimal radiomics features and establish a predictive model for distinguishing between exon 19 deletion (19Del) and exon 21 L858R point mutation (21L858R), the two most common EGFR gene mutations. The testing set was used for external validation of the models. Model performance was evaluated using receiver operating characteristic curve and decision curve analyses. RESULTS: Overall, 86 patients with 228 brain metastases were included. Patient age was identified as an independent predictor for distinguishing between 19Del and 21L858R. The area under the curve (AUC) values of the radiomics model in the training and testing datasets were 0.895 (95% confidence interval [CI]: 0.850-0.939) and 0.759 (95% CI: 0.0.614-0.903), respectively. The AUC for diagnosis of all cases using a combined model of age and radiomics was 0.888 (95% CI: 0.846-0.930), slightly higher than that of the radiomics model alone (0.866, 95% CI: 0.820-0.913), but without statistical significance (p=0.1626). In the decision curve analysis, both models demonstrated clinical net benefits. CONCLUSIONS: The radiomics model based on MRI of lung adenocarcinoma brain metastases could distinguish between EGFR 19Del and 21L858R mutations in the primary lesion.

Association between polymorphisms in NOBOX and litter size traits in Xiangsu pigs.

The newborn ovary homeobox gene (NOBOX) regulates ovarian and early oocyte development, and thus plays an essential role in reproduction. In this study, the mRNA expression level and single nucleotide polymorphism (SNP) of NOBOX in various tissues of Xiangsu pigs were studied to explore the relationship between its polymorphism and litter size traits. Also, bioinformatics was used to evaluate the effects of missense substitutions on protein structure and function. The results revealed that NOBOX is preferentially expressed in the ovary. Six mutations were detected in the NOBOX sequence, including g.1624 T>C, g.1858 G>A, g.2770 G>A, g.2821 A>G, g.5659 A>G, and g.6025 T>A, of which g.1858 G>A was a missense mutation. However, only g.1858 G>A, g.5659 A>G, and g.6025 T>A were significantly associated with litter size traits (p < 0.05). Further prediction of the effect of the missense mutation g.1858 G>A on protein function revealed that p.V82M is a non-conservative mutation that significantly reduces protein stability and thus alters protein function. Overall, these findings suggest that NOBOX polymorphism is closely related to the litter size of Xiangsu pigs, which may provide new insights into pig breeding.

Relationship between a body shape index and muscle strength index in Chinese university students: a cross-sectional survey.

BACKGROUND: The problem of overweight obesity and decrease in muscle strength among university students has become an indisputable fact. In this study, a comprehensive index reflecting obesity degree a body shape index (ABSI) and a comprehensive index reflecting muscle strength muscle strength index (MSI) were studied to analyze the cross-sectional correlations existing between them. METHODS: This study began recruiting participants and conducting the test survey in April 2022 and closed in July 2022. Basic condition, height, weight, waist circumference, grip strength, pull-up (boys), bent-leg sit-up (girls), and standing long jump were tested on 12,046 (boys: 6011, 49.90%) university students aged 19-22 years in China, and ABSI and MSI were calculated separately. ABSI was categorized into 5 groups according to age and sex, namely ABSI < 5th percentile (A), 5th ≤ ABSI < 25th percentile (B), 25th ≤ ABSI < 75th percentile (C), 75th ≤ ABSI < 95th percentile (D) and ABSI ≥ 95th percentile (E). The comparison of MSI between different ABSI groups was performed using effect size, and the association between them was performed by curve estimation analysis. RESULTS: The association between ABSI and MSI of Chinese university students showed an inverted "U" curve. The effect of increased ABSI on MSI was greater in university girls compared to boys. The ABSI of boys was (0.080 ± 0.010) and MSI was (-0.005 ± 2.080); the ABSI of girls was (0.079 ± 0.008) and MSI was (-0.017 ± 1.867). Overall, university students ABSI was at a relatively high point for MSI between 0.050 and 0.100. The university students ABSI at 0.150 had an MSI of -1.229 for boys and - 2.779 for girls. CONCLUSION: The ABSI of Chinese university students showed an inverted "U"-shaped curve relationship with MSI, and university students with low or high ABSI had lower MSI. The effect of increasing ABSI on the decrease of MSI was more obvious for girls than for boys.

The communication of artificial intelligence and deep learning in computer tomography image recognition of epidemic pulmonary infectious diseases.

The objectives are to improve the diagnostic efficiency and accuracy of epidemic pulmonary infectious diseases and to study the application of artificial intelligence (AI) in pulmonary infectious disease diagnosis and public health management. The computer tomography (CT) images of 200 patients with pulmonary infectious disease are collected and input into the AI-assisted diagnosis software based on the deep learning (DL) model, "UAI, pulmonary infectious disease intelligent auxiliary analysis system", for lesion detection. By analyzing the principles of convolutional neural networks (CNN) in deep learning (DL), the study selects the AlexNet model for the recognition and classification of pulmonary infection CT images. The software automatically detects the pneumonia lesions, marks them in batches, and calculates the lesion volume. The result shows that the CT manifestations of the patients are mainly involved in multiple lobes and density, the most common shadow is the ground-glass opacity. The detection rate of the manual method is 95.30%, the misdetection rate is 0.20% and missed diagnosis rate is 4.50%; the detection rate of the DL-based AI-assisted lesion method is 99.76%, the misdetection rate is 0.08%, and the missed diagnosis rate is 0.08%. Therefore, the proposed model can effectively identify pulmonary infectious disease lesions and provide relevant data information to objectively diagnose pulmonary infectious disease and manage public health.