Intestinal permeability in human cardiovascular diseases: a systematic review and meta-analysis.

Background: There is a link between cardiovascular diseases and intestinal permeability, but it is not clear. This review aimed to elucidate intestinal permeability in cardiovascular diseases by meta-analysis. Methods: Multidisciplinary electronic databases were searched from the database creation to April 2023. All included studies were assessed for risk of bias according to the Joanna Briggs Institute Critical Appraisal Checklist. The heterogeneity of each study was estimated using the I2 statistic, and the data were analyzed using Review Manager 5.3 and Stata 16.0. Results: In total, studies in 13 pieces of literature were included in the quantitative meta-analysis. These studies were conducted among 1,321 subjects mostly older than 48. Patients had higher levels of intestinal permeability markers (lipopolysaccharide, d-lactate, zonulin, serum diamine oxidase, lipopolysaccharide-binding protein, intestinal fatty acid binding protein, and melibiose/rhamnose) than controls (standard mean difference SMD = 1.50; 95% CI = 1.31-1.88; p < 0.00001). Similarly, lipopolysaccharide levels were higher in patients than in controls (SMD = 1.61; 95% CI = 1.02-2.21; p < 0.00001); d-lactate levels were higher in patients than in controls (SMD = 1.16; 95% CI = 0.23-2.08; p = 0.01); zonulin levels were higher in patients than in controls (SMD = 1.74; 95% CI = 1.45-2.03; p < 0.00001); serum diamine oxidase levels were higher in patients than in controls (SMD = 2.51; 95% CI = 0.29-4.73; p = 0.03). Conclusion: The results of the meta-analysis verified that the intestinal barrier was damaged and intestinal permeability was increased in patients with cardiovascular diseases. These markers may become a means of the diagnosis and treatment of cardiovascular diseases. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=414296, identifier CRD42023414296.

The complete chloroplast genome of Blechnopsis orientalis (Linnaeus) C. Presl 1753 (Blechnaceae).

Blechnopsis orientalis (Linnaeus) C. Presl (1753) is a fern used both as food and medicine. It is found primarily in southern China and Southeast Asia, thriving in warm, humid shrublands or sparse forest. The total length of the chloroplast genome is 155,211 bp, including a large single-copy region (LSC, 81,877 bp), a small single-copy region (SSC, 21,500 bp), and two inverted repeat regions (IRs, 25,917 bp). The GC content is 41.3%. A total of 131 genes were annotated, including 88 protein-coding genes, eight rRNA genes, and 35 tRNA genes. The phylogenetic analysis using the maximum-likelihood method showed that B. orientalis and Oceaniopteris gibba were closely related. This study provides genomic resources for phylogenetic genetics and resource exploitation of B. orientalis.

Data-Driven Structure Recognition of Scanning Tunneling Microscopy Images in a Case of Iron Carbide.

Scanning tunneling microscopy (STM) serves as a critical tool for high-resolution surface imaging, yet deciphering the atomic structures from STM images on multielement surfaces, such as oxides and carbides, remains a challenging task that heavily relies on the expertise and intuition of researchers. In this study, we introduce a data-driven method for rapid structural recognition from STM images. This method involves extracting structural features, filtering through a structural database, and matching with simulated STM images and surface energy analyses, thereby providing researchers with several of the most probable structures. We demonstrate the capabilities of this technique using our previously reported iron carbide grown on an Fe(110) crystal. By proposing a candidate structure set and establishing a comprehensive database linking STM images to corresponding structures and surface energies, we selected 6 out of more than 10 000 possible surfaces. On the basis of these 6 recommendations, researchers can conveniently determine the real surface structures. Our work provides an efficient tool for the structure recognition of STM images to construct surface structures, potentially serving as a universal auxiliary tool for STM structural analysis.

The complete chloroplast genome of Leonurus sibiricus Linnaeus (Labiatae, Leonurus Miller).

Leonurus sibiricus Linnaeus 1753, an annual or biennial herb found in northern China, Mongolia, and Russia, typically grows in stony, sandy grasslands, and pine forests. This study sequenced and reported the complete chloroplast genome of L. sibiricus for the first time. The entire circular genome measures 151,689 bp in length, with a GC content of 38.4%. A total of 133 genes were annotated, including 88 protein-coding genes, 37 tRNAs, and eight rRNAs. The genome exhibits a typical quadripartite structure, comprising a large single-copy (LSC 82,820 bp) region, a small single-copy (SSC 17,619 bp) region, and a pair of inverted repeat (IR 25,625 bp each) regions. Phylogenetic analysis using the maximum-likelihood method indicates that L. sibiricus is most closely related to L. japonicus Houttuyn. This study provides valuable genomic resources for further research on the phylogenetics and biodiversity of the genus Leonurus.

Potential of Marine Bacterial Metalloprotease A69 in the Preparation of Peanut Peptides with Angiotensin-Converting Enzyme (ACE)-Inhibitory and Antioxidant Properties.

Marine bacterial proteases have rarely been used to produce bioactive peptides, although many have been reported. This study aims to evaluate the potential of the marine bacterial metalloprotease A69 from recombinant Bacillus subtilis in the preparation of peanut peptides (PPs) with antioxidant activity and angiotensin-converting enzyme (ACE)-inhibitory activity. Based on the optimization of the hydrolysis parameters of protease A69, a process for PPs preparation was set up in which the peanut protein was hydrolyzed by A69 at 3000 U g-1 and 60 °C, pH 7.0 for 4 h. The prepared PPs exhibited a high content of peptides with molecular weights lower than 1000 Da (>80%) and 3000 Da (>95%) and contained 17 kinds of amino acids. Moreover, the PPs displayed elevated scavenging of hydroxyl radical and 1,1-diphenyl-2-picryl-hydrazyl radical, with IC50 values of 1.50 mg mL-1 and 1.66 mg mL-1, respectively, indicating the good antioxidant activity of the PPs. The PPs also showed remarkable ACE-inhibitory activity, with an IC50 value of 0.71 mg mL-1. By liquid chromatography mass spectrometry analysis, the sequences of 19 ACE inhibitory peptides and 15 antioxidant peptides were identified from the PPs. These results indicate that the prepared PPs have a good nutritional value, as well as good antioxidant and antihypertensive effects, and that the marine bacterial metalloprotease A69 has promising potential in relation to the preparation of bioactive peptides from peanut protein.

Stabilized ε-Fe2C catalyst with Mn tuning to suppress C1 byproduct selectivity for high-temperature olefin synthesis.

Accurately controlling the product selectivity in syngas conversion, especially increasing the olefin selectivity while minimizing C1 byproducts, remains a significant challenge. Epsilon Fe2C is deemed a promising candidate catalyst due to its inherently low CO2 selectivity, but its use is hindered by its poor high-temperature stability. Herein, we report the successful synthesis of highly stable ε-Fe2C through a N-induced strategy utilizing pyrolysis of Prussian blue analogs (PBAs). This catalyst, with precisely controlled Mn promoter, not only achieved an olefin selectivity of up to 70.2% but also minimized the selectivity of C1 byproducts to 19.0%, including 11.9% CO2 and 7.1% CH4. The superior performance of our ε-Fe2C-xMn catalysts, particularly in minimizing CO2 formation, is largely attributed to the interface of dispersed MnO cluster and ε-Fe2C, which crucially limits CO to CO2 conversion. Here, we enhance the carbon efficiency and economic viability of the olefin production process while maintaining high catalytic activity.

Urea regulates soil nematode population by enhancing the nematode-trapping ability of nematode-trapping fungi.

As the most abundant animal in the soil, nematodes are directly or indirectly involved in almost all soil ecological processes. Studying soil nematode population regulation is essential to understanding soil ecological processes. This study found urea combines nematode-trapping fungi to regulate the population of soil nematodes. In soil, compared with no urea, adding 0.2 mg/mL urea after applying Arthrobotrys oligospora and Dactylellina ellipsospora reduced the number of nematodes by 34.7% and 31.7%. Further, the mechanism of urea couple nematode-trapping fungi to regulate the nematode population was explored in the medium environment. The results showed that the addition of 0.2 mg/ml urea accelerated the trap formation of A. oligospora and D. ellipsosporas by 50% and 46.5%, and increased the yield of traps of A. oligospora and D. ellipsosporas by 39.5% and 40.6%, thus, the predatory efficiency of A. oligospora and D. ellipsospora on nematodes was increased by 34.2% and 32.7%. In conclusion, urea regulates the predation ability of A. oligospora and D. ellipsosporas to regulate the soil nematode population. This study deepens the understanding of the regulatory pathways of the soil nematodes but also provides a potential new strategy for harmful nematode bio-control.

Engineered nanovesicles from activated neutrophils with enriched bactericidal proteins have molecular debridement ability and promote infectious wound healing.

Background: Bacterial infections pose a considerable threat to skin wounds, particularly in the case of challenging-to-treat diabetic wounds. Systemic antibiotics often struggle to penetrate deep wound tissues and topically applied antibiotics may lead to sensitization, necessitating the development of novel approaches for effectively treating germs in deep wound tissues. Neutrophils, the predominant immune cells in the bloodstream, rapidly release an abundance of molecules via degranulation upon activation, which possess the ability to directly eliminate pathogens. This study was designed to develop novel neutrophil cell engineered nanovesicles (NVs) with high production and explore their bactericidal properties and application in promoting infectious wound healing. Methods: Neutrophils were isolated from peripheral blood and activated in vitro via phorbol myristate acetate (PMA) stimulation. Engineered NVs were prepared by sequentially extruding activated neutrophils followed by ultracentrifugation and were compared with neutrophil-derived exosomes in terms of morphology, size distribution and protein contents. The bactericidal effect of NVs in vitro was evaluated using the spread plate technique, LIVE/DEAD backlight bacteria assay and observation of bacterial morphology. The therapeutic effects of NVs in vivo were evaluated using wound contraction area measurements, histopathological examinations, assessments of inflammatory factors and immunochemical staining. Results: Activated neutrophils stimulated with PMA in vitro promptly release a substantial amount of bactericidal proteins. NVs are similar to exosomes in terms of morphology and particle size, but they exhibit a significantly higher enrichment of bactericidal proteins. In vitro, NVs demonstrated a significant bactericidal effect, presumably mediated by the enrichment of bactericidal proteins such as lysozyme. These NVs significantly accelerated wound healing, leading to a marked reduction in bacterial load, downregulation of inflammatory factors and enhanced collagen deposition in a full-thickness infectious skin defect model. Conclusions: We developed engineered NVs derived from activated neutrophils to serve as a novel debridement method targeting bacteria in deep tissues, ultimately promoting infectious wound healing.

PRDX1 exerts a photoprotection effect by inhibiting oxidative stress and regulating MAPK signaling on retinal pigment epithelium.

BACKGROUND: The purpose of this study was to investigate the photoprotection effect of peroxiredoxin 1 (PRDX1) protein in ultraviolet B (UVB) irradiation-induced damage of retinal pigment epithelium (RPE) and its possible molecular mechanism. METHODS: ARPE-19 cell viability and apoptosis were assessed by MTT assay and flow cytometry, respectively. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the PRDX1 expression. The corresponding kits were employed to measure the levels or activities of lactate dehydrogenase (LDH), 8-hydroxy-2-deoxyguanosine (8-OHdG), reactive oxygen species (ROS), malondialdehyde (MDA), glutathione peroxidase (GSH-Px), superoxide dismutase (SOD). Western blotting was applied to examine PRDX1 expression and mitogen-activated protein kinase (MAPK) signaling pathway-related proteins. RESULTS: After exposure to 20 mJ/cm2 intensity of UVB irradiation for 24 h, ARPE-19 cells viability was decreased, the leakage degree of LDH and 8-OHdG were increased, and cell apoptosis was elevated. The expression of PRDX1 was significantly down-regulated in UVB-induced ARPE-19 cells. The low expression of PRDX1 was involved in high irradiation intensity. Overexpression of PRDX1 increased cell activity, decreased cell apoptosis, and LDH as well as 8-OHdG leakage in UVB-induced ARPE-19 cells. In addition to alleviating UVB-induced cell damage, PRDX1 overexpression also inhibited UVB-induced oxidative stress (down-regulation of ROS and MDA levels, up-regulation of GSH-Px and SOD activities) and the activation of MAPK signaling pathway in ARPE-19 cells. CONCLUSION: PRDX1 exerts a photoprotection effect on RPE by attenuating UVB-induced cell damage and inhibiting oxidative stress, which can be attributed to the inhibition of MAPK signaling pathway activation.

Automated characterization and analysis of expression compatibility between regulatory sequences and metabolic genes in Escherichia coli.

Utilizing standardized artificial regulatory sequences to fine-tuning the expression of multiple metabolic pathways/genes is a key strategy in the creation of efficient microbial cell factories. However, when regulatory sequence expression strengths are characterized using only a few reporter genes, they may not be applicable across diverse genes. This introduces great uncertainty into the precise regulation of multiple genes at multiple expression levels. To address this, our study adopted a fluorescent protein fusion strategy for a more accurate assessment of target protein expression levels. We combined 41 commonly-used metabolic genes with 15 regulatory sequences, yielding an expression dataset encompassing 520 unique combinations. This dataset highlighted substantial variation in protein expression level under identical regulatory sequences, with relative expression levels ranging from 2.8 to 176-fold. It also demonstrated that improving the strength of regulatory sequences does not necessarily lead to significant improvements in the expression levels of target proteins. Utilizing this dataset, we have developed various machine learning models and discovered that the integration of promoter regions, ribosome binding sites, and coding sequences significantly improves the accuracy of predicting protein expression levels, with a Spearman correlation coefficient of 0.72, where the promoter sequence exerts a predominant influence. Our study aims not only to provide a detailed guide for fine-tuning gene expression in the metabolic engineering of Escherichia coli but also to deepen our understanding of the compatibility issues between regulatory sequences and target genes.

Human papillomavirus infection and the risk of cancer at specific sites other than anogenital tract and oropharyngeal region: an umbrella review.

BACKGROUND: Despite numerous studies having evaluated the associations between human papillomavirus (HPV) infection and risk of specific cancers other than anogenital tract and oropharyngeal, the findings are inconsistent and the quality of evidence has not been systematically quantified. We aimed to summarise the existing evidence as well as to evaluate the strength and credibility of these associations. METHODS: We conducted an umbrella review of systematic reviews and meta-analyses of observational studies. PubMed, EMBASE, and Web of Science were searched from inception to March 2024. Studies with systematic reviews and meta-analyses that examined associations between HPV or HPV-associated genotypes infection and specific cancers were eligible for this review. The quality of the methodology was evaluated using A Measurement Tool to Assess systematic Reviews (AMSTAR). The credibility of the evidence was assessed using GRADE. The protocol was preregistered with PROSPERO (CRD42023439070). FINDINGS: The umbrella review identified 31 eligible studies reporting 87 associations with meta-analytic estimates, including 1191 individual studies with 336,195 participants. Of those, 29 (93.5%) studies were rated as over moderate quality by AMSTAR. Only one association indicating HPV-18 infection associated with an increased risk of breast cancer (odds ratio [OR] = 3.48, 95% confidence interval [CI] = 2.24-5.41) was graded as convincing evidence. There were five unique outcomes identified as highly suggestive evidence, including HPV infection increased the risk of oral squamous cell carcinoma (OR = 7.03, 95% CI = 3.87-12.76), oesophageal cancer (OR = 3.32, 95% CI = 2.54-4.34), oesophageal squamous cell carcinoma (OR = 2.69, 95% CI = 2.05-3.54), lung cancer (OR = 3.60, 95% CI = 2.59-5.01), and breast cancer (OR = 6.26, 95% CI = 4.35-9.00). According to GRADE, one association was classified as high, indicating that compared with the controls in normal tissues, HPV infection was associated with an increased risk of breast cancer. INTERPRETATION: The umbrella review synthesised up-to-date observational evidence on HPV infection with the risk of breast cancer, oral squamous cell carcinoma, oesophageal cancer, oesophageal squamous cell carcinoma, and lung cancer. Further larger prospective cohort studies are needed to verify the associations, providing public health recommendations for prevention of disease. FUNDING: National Key Research and Development Program of China, Natural Science Foundation of China, Outstanding Scientific Fund of Shengjing Hospital of China Medical University, and 345 Talent Project of Shengjing Hospital of China Medical University.

Multifunctional fluorescence/photoacoustic bimodal imaging of γ-glutamyltranspeptidase in liver disorders under different triggering conditions.

Hepatocellular carcinoma (HCC) seriously threatens the human health. Previous investigations revealed that γ-glutamyltranspeptidase (GGT) was tightly associated with the chronic injury, hepatic fibrosis, and the development of HCC, therefore might act as a potential indicator for monitoring the HCC-related processes. Herein, with the contribution of a structurally optimized probe ETYZE-GGT, the bimodal imaging in both far red fluorescence (FL) and photoacoustic (PA) modes has been achieved in multiple HCC-related models. To our knowledge, this work covered the most comprehensive models including the fibrosis and developed HCC processes as well as the premonitory induction stages (autoimmune hepatitis, drug-induced liver injury, non-alcoholic fatty liver disease). ETYZE-GGT exhibited steady and practical monitoring performances on reporting the HCC stages via visualizing the GGT dynamics. The two modes exhibited working consistency and complementarity with high spatial resolution, precise apparatus and desirable biocompatibility. In cooperation with the existing techniques including testing serum indexes and conducting pathological staining, ETYZE-GGT basically realized the universal application for the accurate pre-clinical diagnosis of as many HCC stages as possible. By deeply exploring the mechanically correlation between GGT and the HCC process, especially during the premonitory induction stages, we may further raise the efficacy for the early diagnosis and treatment of HCC.

Machine Learning Model for Predicting Axillary Lymph Node Metastasis in Clinically Node Positive Breast Cancer Based on Peritumoral Ultrasound Radiomics and SHAP Feature Analysis.

OBJECTIVE: This study seeks to construct a machine learning model that merges clinical characteristics with ultrasound radiomic analysis-encompassing both the intratumoral and peritumoral-to predict the status of axillary lymph nodes in patients with early-stage breast cancer. METHODS: The study employed retrospective methods, collecting clinical information, ultrasound data, and postoperative pathological results from 321 breast cancer patients (including 224 in the training group and 97 in the validation group). Through correlation analysis, univariate analysis, and Lasso regression analysis, independent risk factors related to axillary lymph node metastasis in breast cancer were identified from conventional ultrasound and immunohistochemical indicators, and a clinical feature model was constructed. Additionally, features were extracted from ultrasound images of the intratumoral and its 1-5 mm peritumoral to establish a radiomics feature formula. Furthermore, by combining clinical features and ultrasound radiomics features, six machine learning models (Logistic Regression, Decision Tree, Support Vector Machine, Extreme Gradient Boosting, Random Forest, and K-Nearest Neighbors) were compared for diagnostic efficacy, and constructing a joint prediction model based on the optimal ML algorithm. The use of Shapley Additive Explanations (SHAP) enhanced the visualization and interpretability of the model during the diagnostic process. RESULTS: Among the 321 breast cancer patients, 121 had axillary lymph node metastasis, and 200 did not. The clinical feature model had an AUC of 0.779 and 0.777 in the training and validation groups, respectively. Radiomics model analysis showed that the model including the Intratumor +3 mm peritumor area had the best diagnostic performance, with AUCs of 0.847 and 0.844 in the training and validation groups, respectively. The joint prediction model based on the XGBoost algorithm reached AUCs of 0.917 and 0.905 in the training and validation groups, respectively. SHAP analysis indicated that the Rad Score had the highest weight in the prediction model, playing a significant role in predicting axillary lymph node metastasis in breast cancer. CONCLUSION: The predictive model, which integrates clinical features and radiomic characteristics using the XGBoost algorithm, demonstrates significant diagnostic value for axillary lymph node metastasis in breast cancer. This model can provide significant references for preoperative surgical strategy selection and prognosis evaluation for breast cancer patients, helping to reduce postoperative complications and improve long-term survival rates. Additionally, the utilization of SHAP enhancing the global and local interpretability of the model.

Establishment of an immortalized yak granulosa cell line: in vitro tool for understanding the molecular processes of ovarian follicle development.

The yak, a unique species of cattle found exclusively on the western plateau of China, is a valuable source of livelihood for local residents. However, their low fecundity restricts the expansion of yak farming, whereas regional factors limit studies on yak breeding. Granulosa cells (GCs), which provide essential steroid hormones and growth factors for oocytes, have been the focus of many studies on the mechanisms of follicular growth and atresia. This study aimed to establish an immortalized cell line model that could serve as a tool for future studies on the mechanisms of ovarian follicle development in yaks. First, we isolated primary yak granulosa cells (yGCs) and evaluated their replicative senescence after continuous in vitro subculturing. Subsequently, an immortalized culture method for primary yGC was explored, and a new cell line model was established to study the mechanism of follicular development in vitro. We used a mammalian gene expression lentivirus vector to transfer the simian virus 40 large T antigen (SV40T) into primary yGC to obtain an immortalized cell line. The immortalized yGCs were morphologically identical to the primary yGCs, and cell proliferation and growth were normal within a limited number of generations. Follicle-stimulating hormone receptor (FSHR), a specific marker for GCs, was positively expressed in immortalized yGCs. Furthermore, the immortalized yGCs retained the ability of GCs to synthesize estradiol and progesterone and expressed genes related to steroid synthesis. The establishment of immortalized yGC opens up a myriad of possibilities for advancing our understanding of yak reproductive biology and improving yak breeding strategies.

Gastric-type endocervical adenocarcinoma: a case report and literature review.

Gastric-type endocervical adenocarcinoma (G-EAC) represents a rare variant of cervical mucinous adenocarcinoma that is typically unrelated to human papillomavirus (HPV) infection. G-EAC exhibits highly atypical clinical presentations and characteristics, and aggressive biological behavior often leads to challenges in timely diagnosis. Here, we present a case study involving a 74-year-old Chinese woman who experienced urinary incontinence for one month. Biopsy pathology confirmed the diagnosis of G-EAC, revealing stage IVa by imaging examinations. The patient subsequently underwent three cycles of chemotherapy, followed by adjuvant radiotherapy and surgical excision of residual tumor foci. This comprehensive treatment approach yielded a favorable survival outcome. For patients with advanced G-EAC, a multimodal therapeutic approach holds promise and warrants further exploration.

High-order rogue wave and mixed interaction patterns for the three-component Gross-Pitaevskii equations in F=1 spinor Bose-Einstein condensates.

Under investigation are the three-component Gross-Pitaevskii equations in F=1 spinor Bose-Einstein condensates. Various localized waves' generation mechanisms have been derived from plane wave solutions using modulation instability. The perturbed continuous waves produce a large number of rogue wave structures through the split-step Fourier numerical method. Based on the known Lax pair, we construct the generalized iterative (n,N-n)-fold Darboux transformation to generate various high-order solutions, including the bright-dark-bright structure of rogue waves, periodic waves, and their mixed interaction structures. Numerical simulations show that rogue waves with a two-peaked structure have robust noise resistance and stable dynamical behavior. The asymptotic states of high-order rogue waves as the parameter approaches infinity are also predicted using the large parameter asymptotic technique. In addition, the position of these localized wave patterns can be controlled by some special parameters. These results may help us understand the dynamic behavior of spinor condensates for the mean-field approximation.

Characterization of Sand and Dust Pollution Degradation Based on Sensitive Structure of Microelectromechanical System Flow Sensor.

The effect of sand and dust pollution on the sensitive structures of flow sensors in microelectromechanical systems (MEMS) is a hot issue in current MEMS reliability research. However, previous studies on sand and dust contamination have only searched for sensor accuracy degradation due to heat conduction in sand and dust cover and have yet to search for other failure-inducing factors. This paper aims to discover the other inducing factors for the accuracy failure of MEMS flow sensors under sand and dust pollution by using a combined model simulation and sample test method. The accuracy of a flow sensor is mainly reflected by the size of its thermistor, so in this study, the output value of the thermistor value was chosen as an electrical characterization parameter to verify the change in the sensor's accuracy side by side. The results show that after excluding the influence of heat conduction, when sand particles fall on the device, the mutual friction between the sand particles will produce an electrostatic current; through the principle of electrostatic dissipation into the thermistor, the principle of measurement leads to the resistance value becoming smaller, and when the sand dust is stationary for some time, the resistance value returns to the expected level. This finding provides theoretical guidance for finding failure-inducing factors in MEMS failure modes.

Case report: A rare case of omental extrarenal rhabdoid tumor and review of the literature.

Extrarenal rhabdoid tumor of the greater omentum is extremely rare, with only sporadic reports and limited documentation of its ultrasonographic findings. Here, we report a case of an extrarenal rhabdoid tumor of the greater omentum in a 16-year-old girl and review the relevant literature. It was found that the disease mainly occurred in female children and adolescents, and mainly manifested as lower abdominal pain and a large abdominal cystic or solid hemorrhagic mass. The clinical characteristics include a high degree of malignancy and mortality. Ultrasound shows some malignant features, but it is not specific; thus, it is easy to be misdiagnosed in the clinic.

Analysis of related factors of CRA in lung cancer patients with different serum iron levels: A retrospective cohort study.

BACKGROUND: Serum iron, an essential component of hemoglobin (Hb) synthesis in vivo, is a crucial parameter for evaluating the body's iron storage and metabolism capacity. Iron deficiency leads to reduced Hb synthesis in red blood cells and smaller red blood cell volume, ultimately resulting in iron-deficiency anemia. Although serum iron cannot independently evaluate iron storage or metabolism ability, it can reflect iron concentration in vivo and serve as a good predictor of iron-deficiency anemia. Therefore, exploring the influence of different serum iron levels on anemia and diagnosing and treating iron deficiency in the early stages is of great significance for patients with lung cancer. AIM: This study aims to explore the related factors of cancer-related anemia (CRA) in lung cancer and construct a nomogram prediction model to evaluate the risk of CRA in patients with different serum iron levels. METHODS: A single-center retrospective cohort study was conducted, including 1610 patients with lung cancer, of whom 1040 had CRA. The relationship between CRA and its influencing factors was analyzed using multiple linear regression models. Lung cancer patients were divided into two groups according to their serum iron levels: decreased serum iron and normal serum iron. Each group was randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The influencing factors were screened by univariate and multivariate logistic regression analyses, and nomogram models were constructed. The area under the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the models. RESULTS: CRA in lung cancer is mainly related to surgery, chemotherapy, Karnofsky Performance Status (KPS) score, serum iron, C-reactive protein (CRP), albumin, and total cholesterol (p < 0.05). CRA in lung cancer patients with decreased serum iron is primarily associated with albumin, age, and cancer staging, while CRA in lung cancer patients with normal serum iron is mainly related to CRP, albumin, total cholesterol, and cancer staging. The area under the ROC curve of the training cohort and validation cohort for the prediction model of lung cancer patients with decreased serum iron was 0.758 and 0.760, respectively. Similarly, the area under the ROC curve of the training cohort and validation cohort for the prediction model of lung cancer patients with normal serum iron was 0.715 and 0.730, respectively. The calibration curves of both prediction models were around the ideal 45° line, suggesting good discrimination and calibration. DCA showed that the nomograms had good clinical utility. CONCLUSION: Both models have good reliability and validity and have significant clinical value. They can help doctors better assess the risk of developing CRA in lung cancer patients. CRP is a risk factor for CRA in lung cancer patients with normal serum iron but not in patients with decreased serum iron. Therefore, whether CRP and the inflammatory state represented by CRP will further aggravate the decrease in serum iron levels, thus contributing to anemia, warrants further study.

Bird's-Eye View of the Activity Distribution on a Catalyst Surface via a Machine Learning-Driven Adequate Sampling Algorithm.

Rational design of catalysts relies on a deep understanding of the active centers. The structure and activity distribution of active centers on a surface are two of the central issues in catalysis and important targets of theoretical and experimental investigations. Herein, we report a machine learning-driven adequate sampling (MLAS) framework for obtaining a statistical understanding of the chemical environment near catalyst sites. Combined strategies were implemented to achieve highly efficient sampling, including the decomposition of degrees of freedom, stratified sampling, Gaussian process regression, and well-designed constraint optimization. The MLAS framework was applied to the rate-determining step in NH3 synthesis, namely the N2 activation process. We calculated the produced population function, PA, which provides a comprehensive and intuitive understanding of active centers. The MLAS framework can be broadly applied to other more complicated catalyst materials and reaction networks.