Simple, and highly efficient edge-effect surface acoustic wave atomizer.

Conventional surface acoustic wave (SAW) atomizers require a direct water supply on the surface, which can be complex and cumbersome. This paper presents a novel SAW atomizer that uses lateral acoustic wetting to achieve atomization without a direct water supply. The device works by simply pressing a piece of wetted paper strip against the bottom of an excited piezoelectric transducer. The liquid then flows along the side to the unmodified surface edge, where it is atomized into a well-converging mist in a stable and sustainable manner. We identified this phenomenon as the edge effect, using numerical simulation results of surface displacement mode. The feasibility of the prototype design was demonstrated by observing and investigating the integrated process of liquid extraction, transport, and atomization. We further explored the hydrodynamic principles of the change and breakup in liquid film geometry under different input powers. Experiments demonstrate that our atomizer is capable of generating high-quality fine liquid particles stably and rapidly even at very high input power. Compared to conventional SAW atomizer, the dispersion of mist width can be scaled down by 70%, while the atomization rate can be increased by 37.5%. Combined with the advantages of easy installation and robustness, the edge effect-based atomizer offers an attractive alternative to current counterparts for applications requiring high efficiency and miniaturization, such as simultaneous synthesis and encapsulation of nanoparticles, pulmonary drug delivery and portable inhalation therapy.

EndoPRS: Incorporating Endophenotype Information to Improve Polygenic Risk Scores for Clinical Endpoints.

Polygenic risk score (PRS) prediction of complex diseases can be improved by leveraging related phenotypes. This has motivated the development of several multi-trait PRS methods that jointly model information from genetically correlated traits. However, these methods do not account for vertical pleiotropy between traits, in which one trait acts as a mediator for another. Here, we introduce endoPRS, a weighted lasso model that incorporates information from relevant endophenotypes to improve disease risk prediction without making assumptions about the genetic architecture underlying the endophenotype-disease relationship. Through extensive simulation analysis, we demonstrate the robustness of endoPRS in a variety of complex genetic frameworks. We also apply endoPRS to predict the risk of childhood onset asthma in UK Biobank by leveraging a paired GWAS of eosinophil count, a relevant endophenotype. We find that endoPRS significantly improves prediction compared to many existing PRS methods, including multi-trait PRS methods, MTAG and wMT-BLUP, which suggests advantages of endoPRS in real-life clinical settings.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci.

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWASs) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N = 52) and nonsmokers (N = 171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and correcting for multiple testing using a two-stage procedure. We found >2 million significant meQTL variants (padj < 0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects, and five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTL variants for 958 unique eGenes (padj < 0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTN1 and ITIH4 colocalized across all data types (GWAS, meQTL, and eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

METTL5 promotes cell proliferation, invasion, and migration by up-regulating Toll-like receptor 8 expression in colorectal cancer.

BACKGROUND: N6-methyladenosine (m6A) modification represents the predominant alteration found in eukaryotic messenger RNA and plays a crucial role in the progression of various tumors. However, despite its significance, the comprehensive investigation of METTL5, a key m6A methyltransferase, in colorectal cancer (CRC) remains limited. AIM: To investigate the role of METTL5 in CRC. METHODS: We assessed METTL5 expression levels in clinical samples obtained from CRC patients as well as in CRC cell lines. To elucidate the downstream targets of METTL5, we performed RNA-sequencing analysis coupled with correlation analysis, leading us to identify Toll-like receptor 8 (TLR8) as a potential downstream target. In vitro functional assessments of METTL5 and TLR8 were conducted using CCK-8 assays, scratch assays, as well as assays measuring cell migration and invasion. RESULTS: Our findings reveal a pronounced upregulation of METTL5 expression in both CRC cells and tissues, which correlated significantly with an unfavorable prognosis. In vitro experiments unequivocally demonstrated the oncogenic role of METTL5, as evidenced by its promotion of CRC cell proliferation, invasion, and migration. Notably, we identified TLR8 as a downstream target of METTL5, and subsequent down-regulation of TLR8 led to a significant inhibition of CRC cell proliferation, invasion, and tumor growth. CONCLUSION: The heightened expression of METTL5 in CRC is strongly associated with clinicopathological features and a poor prognosis, thereby underscoring its potential utility as a critical marker for facilitating early diagnosis and prognostication in CRC.

Associations between exposure to phthalates and liver function among women undergoing assisted reproductive technology.

Phthalates can induce hepatotoxicity in animal studies. We aimed to assess the associations of individual and mixture of urinary phthalate metabolites with serum liver function indicators among 764 women undergoing assisted reproductive technology (ART). In linear models, we observed inverse correlations between urinary mono-benzyl phthalate and serum total protein (TP) as well as globulin (ß=-0.27 and -0.23, respectively, P<0.05). Additionally, negative associations were identified between mono-isobutyl phthalate and mono-butyl phthalate (MBP) and aspartate aminotransferase-to-alanine transaminase ratio (AST/ALT) (P<0.05). MBP and the sum of all phthalate metabolites (∑all.phth.m) were positively associated with bilirubin, with ß ranging from 0.14 to 0.47. Most phthalate metabolites were also positively related to gamma-glutamyl transferase (GGT) (all P<0.05). In Bayesian kernel machine regression models, phthalate mixture was positively associated with bilirubin and GGT, whereas inversely associated with AST/ALT and TP. Our results suggest that phthalate exposure may impair liver function among women undergoing ART.

Hsa_circ_0007482 Promotes Proliferation and Differentiation of Chondrocytes in Knee Osteoarthritis.

OBJECTIVE: Knee osteoarthritis (KOA) is a complex degenerative joint disease and a major cause of joint dysfunction. This study aimed to explore the function of hsa_circ_0007482 on inflammation, proliferation, differentiation, and apoptosis in KOA. DESIGN: Real-time quantitative polymerase chain reaction (PCR) was performed to detect the expression of circ_0007482, inflammatory factors, and differentiation-related molecules in KOA chondrocytes and interleukin (IL)-1ß-stimulated chondrocytes. The correlation between the circ_0007482 expression and inflammatory factors was analyzed by the Pearson method. KOA cell model was established using IL-1ß for 24 hours. The proliferation activity of chondrocytes was evaluated by CCK-8 assay, and cell apoptosis rate was assessed by flow cytometry. The downstream miRNA of circ_0007482 was validated using dual-luciferase reporter assay. RESULTS: The circ_0007482 expression was elevated in both KOA cartilage tissues and IL-1ß-treated chondrocytes and positively correlated with inflammatory factors expression. In comparison to the control group, IL-1ß treatment diminished chondrocyte proliferation abilities and increased cell apoptosis and inflammatory factors IL-6, IL-8, and tumor necrosis factor (TNF)-α mRNA expression. Inhibition of circ_0007482 partially improved IL-1ß-induced inflammatory reaction. Circ_0007482 could negatively regulate the expression of miR-558. CONCLUSIONS: Interfering of circ_0007482 might partially promote cell proliferation and differentiation, while inhibit cell apoptosis to improve joint injury by regulating miR-558 in IL-1ß-treated chondrocyte cell model.

Surface Nanostructures Promote Droplet Splash on Hot Substrates.

Splash, one of the most visually apparent droplet dynamics, can manifest on any surface above a certain impact velocity, regardless of surface wettability. Previous studies demonstrate that elevating the substrate temperature can suppress droplet splash, which is unfavorable for many practical applications, such as spray cooling and combustion. Here, we report that the suppression effect of substrate temperature on splash is nullified by utilizing surfaces with nanostructures. By manipulating air evacuation time through surface nanostructures, we have identified a pathway for precise control over the splash threshold and the ability to tailor the dependence of the splash onset on surface temperature. We further propose a theoretical criterion to determine different splash regimes by considering the competition between air evacuation and the development of flow instabilities. Our findings underscore the crucial role of nanostructures in splash dynamics, offering valuable insights for the control of splash in various industrial scenarios.

Temporal change in multimorbidity prevalence, clustering patterns, and the association with mortality: findings from the China Kadoorie Biobank study in Jiangsu Province.

Objectives: The characteristics of multimorbidity in the Chinese population are currently unclear. We aimed to determine the temporal change in multimorbidity prevalence, clustering patterns, and the association of multimorbidity with mortality from all causes and four major chronic diseases. Methods: This study analyzed data from the China Kadoorie Biobank study performed in Wuzhong District, Jiangsu Province. A total of 53,269 participants aged 30-79 years were recruited between 2004 and 2008. New diagnoses of 15 chronic diseases and death events were collected during the mean follow-up of 10.9 years. Yule's Q cluster analysis method was used to determine the clustering patterns of multimorbidity. A Cox proportional hazards model was used to estimate the associations of multimorbidity with mortalities. Results: The overall multimorbidity prevalence rate was 21.1% at baseline and 27.7% at the end of follow-up. Multimorbidity increased more rapidly during the follow-up in individuals who had a higher risk at baseline. Three main multimorbidity patterns were identified: (i) cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), (ii) respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), and (iii) mental, kidney and arthritis multimorbidity (neurasthenia, psychiatric disorders, chronic kidney disease, and rheumatoid arthritis). There were 3,433 deaths during the follow-up. The mortality risk increased by 24% with each additional disease [hazard ratio (HR) = 1.24, 95% confidence interval (CI) = 1.20-1.29]. Compared with those without multimorbidity at baseline, both cardiometabolic multimorbidity and respiratory multimorbidity were associated with increased mortality from all causes and four major chronic diseases. Cardiometabolic multimorbidity was additionally associated with mortality from cardiovascular diseases and diabetes, with HRs of 2.64 (95% CI = 2.19-3.19) and 28.19 (95% CI = 14.85-53.51), respectively. Respiratory multimorbidity was associated with respiratory disease mortality, with an HR of 9.76 (95% CI = 6.22-15.31). Conclusion: The prevalence of multimorbidity has increased substantially over the past decade. This study has revealed that cardiometabolic multimorbidity and respiratory multimorbidity have significantly increased mortality rates. These findings indicate the need to consider high-risk populations and to provide local evidence for intervention strategies and health management in economically developed regions.

Large-scale alternative polyadenylation-wide association studies to identify putative cancer susceptibility genes.

Alternative polyadenylation (APA) modulates mRNA processing in the 3' untranslated regions (3' UTR), affecting mRNA stability and translation efficiency. Research into genetically regulated APA has the potential to provide insights into cancer risk. Herein, we conducted large alternative polyadenylation-wide association studies (APA-WAS) to investigate associations of APA levels with cancer risk. Genetic models were built to predict APA levels in multiple tissues using genotype and RNA-sequencing data from 1,337 samples from the Genotype-Tissue Expression Project. Associations of genetically predicted APA levels with cancer risk were assessed by applying the prediction models to data from large genome-wide association studies of six common cancers among European-ancestry populations, including breast, ovary, prostate, colorectum, lung, and pancreas. A total of 58 risk genes (corresponding to 76 APA sites) were associated with at least one type of cancer, including 25 genes previously not linked to cancer susceptibility. Of the identified risk APAs, 97.4% and 26.3% were supported by 3' UTR APA quantitative trait loci and co-localization analyses, respectively. Luciferase reporter assays for four selected putative regulatory 3' UTR variants demonstrated that the risk alleles of 3' UTR variants, rs324015 (STAT6), rs2280503 (DIP2B), rs1128450 (FBXO38), and rs145220637 (LDHA), significantly increased the post-transcriptional activities of their target genes compared to reference alleles. Furthermore, knockdown of the target genes confirmed their ability to promote proliferation and migration. Overall, this study provides insights into the role of APA in the genetic susceptibility to common cancers.

Deuteration-Induced Energy Level Structure Reconstruction of Carbon Dots for Enhancing Photoluminescence.

Constrained by a limited understanding of the structure and luminescence mechanisms of carbon dots (CDs), achieving precise enhancement of their photoluminescence (PL) performance without altering the emission wavelength and color remains a challenge. In this work, a deuterated CD is first achieved by simply replacing the reaction solvent from H2O to D2O. The substitution of D atoms for H atoms is not limited on the surface but also within the internal structure of CDs. Deuteration affects the formation of the π-conjugated network structure by altering the content of sp2 carbon and sp3 carbon, ultimately inducing a reconstruction for energy level structure of CDs. Both the intrinsic state and surface state emission, including quantum yield, emission intensity and lifetime, are significantly enhanced after deuteration. It benefits from the reduction in non-radiative transitions, since the lowered vibrational frequencies of D atoms and optimized local energy level distribution in CDs structure. The deuterated CDs are applied in the fabrication of white-light-emitting diodes to show their application potential. This work provides a highly versatile route for improving and controlling photoluminescence performance of CDs and has opportunities to guide the development of CDs for practical applications.

Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood.

The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.

Relationship of TAPSE Normalized by Right Ventricular Area With Pulmonary Compliance, Exercise Capacity, and Clinical Outcomes.

BACKGROUND: While tricuspid annular plane systolic excursion (TAPSE) captures the predominant longitudinal motion of the right ventricle (RV), it does not account for ventricular morphology and radial motion changes in various forms of pulmonary hypertension. This study aims to account for both longitudinal and radial motions by dividing TAPSE by RV area and to assess its clinical significance. METHODS: We performed a retrospective analysis of 71 subjects with New York Heart Association class II to III dyspnea who underwent echocardiogram and invasive cardiopulmonary exercise testing (which defined 4 hemodynamic groups: control, isolated postcapillary pulmonary hypertension, combined postcapillary pulmonary hypertension, and pulmonary arterial hypertension). On the echocardiogram, TAPSE was divided by RV area in diastole (TAPSE/RVA-D) and systole (TAPSE/RVA-S). Analyses included correlations (Pearson and linear regression), receiver operating characteristic, and survival curves. RESULTS: On linear regression analysis, TAPSE/RVA metrics (versus TAPSE) had a stronger correlation with pulmonary artery compliance (r=0.48-0.54 versus 0.38) and peak VO2 percentage predicted (0.23-0.30 versus 0.18). Based on the receiver operating characteristic analysis, pulmonary artery compliance ≥3 mL/mm Hg was identified by TAPSE/RVA-D with an under the curve (AUC) of 0.79 (optimal cutoff ≥1.1) and by TAPSE/RVA-S with an AUC of 0.83 (optimal cutoff ≥1.5), but by TAPSE with only an AUC of 0.67. Similarly, to identify peak VO2 <50% predicted, AUC of 0.66 for TAPSE/RVA-D and AUC of 0.65 for TAPSE/RVA-S. Death or cardiovascular hospitalization at 12 months was associated with TAPSE/RVA-D ≥1.1 (HR, 0.38 [95% CI, 0.11-0.56]) and TAPSE/RVA-S ≥1.5 (HR, 0.44 [95% CI, 0.16-0.78]), while TAPSE was not associated with adverse outcomes (HR, 0.99 [95% CI, 0.53-1.94]). Among 31 subjects with available cardiac magnetic resonance imaging, RV ejection fraction was better correlated with novel metrics (TAPSE/RVA-D r=0.378 and TAPSE/RVA-S r=0.328) than TAPSE (r=0.082). CONCLUSIONS: In a broad cohort with suspected pulmonary hypertension, TAPSE divided by RV area was superior to TAPSE alone in correlations with pulmonary compliance and exercise capacity. As a prognostic marker of right heart function, TAPSE/RVA-D <1.1 and TAPSE/RVA-S <1.5 predicted adverse cardiovascular outcomes.

Relationship Learning From Multisource Images via Spatial-Spectral Perception Network.

Advances in multisource remote sensing have allowed for the development of more comprehensive observation. The adoption of deep convolutional neural networks (CNN) naturally includes spatial-spectral information, which has achieved promising performance in multisource data classification. However, challenges are still found with the extraction of spatial distribution and spectrum relationships, which eventually limit the classification performance. To solve the issue, a spatial-spectral perception network (S2PNet) is proposed to extract the advantages of different data sources and the cross information between data sources in a targeted manner. Specifically, the spatial perception network is developed to build the spatial distribution relationship from high-resolution images, while the spectral perception network extracts the spectrum relationship from spectral images. For perceiving cross information, a memory unit is utilized to store the features from different data sources in succession. In addition, the distance loss and reconstruction loss are introduced to keep the feature integrity, and the cross-entropy loss ensures that features can distinguish different classes. The comprehensive experiments are conducted on several datasets to validate the superiority of the proposed algorithm. The proposed S2PNet outperforms the considered classifiers with an average improvement of +0.77%, +5.62%, +1.58%, and +1.79% for overall accuracy values.

Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction.

We performed genome-wide association studies of breast cancer including 18,034 cases and 22,104 controls of African ancestry. Genetic variants at 12 loci were associated with breast cancer risk (P < 5 × 10-8), including associations of a low-frequency missense variant rs61751053 in ARHGEF38 with overall breast cancer (odds ratio (OR) = 1.48) and a common variant rs76664032 at chromosome 2q14.2 with triple-negative breast cancer (TNBC) (OR = 1.30). Approximately 15.4% of cases with TNBC carried six risk alleles in three genome-wide association study-identified TNBC risk variants, with an OR of 4.21 (95% confidence interval = 2.66-7.03) compared with those carrying fewer than two risk alleles. A polygenic risk score (PRS) showed an area under the receiver operating characteristic curve of 0.60 for the prediction of breast cancer risk, which outperformed PRS derived using data from females of European ancestry. Our study markedly increases the population diversity in genetic studies for breast cancer and demonstrates the utility of PRS for risk prediction in females of African ancestry.

Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes.

African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3' UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

Targeted multispectral filter array design for the optimization of endoscopic cancer detection in the gastrointestinal tract.

Significance: Color differences between healthy and diseased tissue in the gastrointestinal (GI) tract are detected visually by clinicians during white light endoscopy; however, the earliest signs of cancer are often just a slightly different shade of pink compared to healthy tissue making it hard to detect. Improving contrast in endoscopy is important for early detection of disease in the GI tract during routine screening and surveillance. Aim: We aim to target alternative colors for imaging to improve contrast using custom multispectral filter arrays (MSFAs) that could be deployed in an endoscopic "chip-on-tip" configuration. Approach: Using an open-source toolbox, Opti-MSFA, we examined the optimal design of MSFAs for early cancer detection in the GI tract. The toolbox was first extended to use additional classification models (k-nearest neighbor, support vector machine, and spectral angle mapper). Using input spectral data from published clinical trials examining the esophagus and colon, we optimized the design of MSFAs with three to nine different bands. Results: We examined the variation of the spectral and spatial classification accuracies as a function of the number of bands. The MSFA configurations tested showed good classification accuracies when compared to the full hyperspectral data available from the clinical spectra used in these studies. Conclusion: The ability to retain good classification accuracies with a reduced number of spectral bands could enable the future deployment of multispectral imaging in an endoscopic chip-on-tip configuration using simplified MSFA hardware. Further studies using an expanded clinical dataset are needed to confirm these findings.

Boosting the immunogenicity of the CoronaVac SARS-CoV-2 inactivated vaccine with Huoxiang Suling Shuanghua Decoction: a randomized, double-blind, placebo-controlled study.

Introduction: In light of the public health burden of the COVID-19 pandemic, boosting the safety and immunogenicity of COVID-19 vaccines is of great concern. Numerous Traditional Chinese medicine (TCM) preparations have shown to beneficially modulate immunity. Based on pilot experiments in mice that showed that supplementation with Huoxiang Suling Shuanghua Decoction (HSSD) significantly enhances serum anti-RBD IgG titers after inoculation with recombinant SARS-CoV-2 S-RBD protein, we conducted this randomized, double-blind, placebo-controlled clinical trial aimed to evaluate the potential immunogenicity boosting effect of oral HSSD after a third homologous immunization with Sinovac's CoronaVac SARS-CoV-2 (CVS) inactivated vaccine. Methods: A total of 70 participants were randomly assigned (1:1 ratio) to receive a third dose of CVS vaccination and either oral placebo or oral HSSD for 7 days. Safety aspects were assessed by recording local and systemic adverse events, and by blood and urine biochemistry and liver and kidney function tests. Main outcomes evaluated included serum anti-RBD IgG titer, T lymphocyte subsets, serum IgG and IgM levels, complement components (C3 and C4), and serum cytokines (IL-6 and IFN-γ). In addition, metabolomics technology was used to analyze differential metabolite expression after supplementation with HSSD. Results: Following a third CVS vaccination, significantly increased serum anti-RBD IgG titer, reduced serum IL-6 levels, increased serum IgG, IgM, and C3 and C4 levels, and improved cellular immunity, evidenced by reduce balance deviations in the distribution of lymphocyte subsets, was observed in the HSSD group compared with the placebo group. No serious adverse events were recorded in either group. Serum metabolomics results suggested that the mechanisms by which HSSD boosted the immunogenicity of the CVS vaccine are related to differential regulation of purine metabolism, vitamin B6 metabolism, folate biosynthesis, arginine and proline metabolism, and steroid hormone biosynthesis. Conclusion: Oral HSSD boosts the immunogenicity of the CVS vaccine in young and adult individuals. This trial provides clinical reference for evaluation of TCM immunomodulators to improve the immune response to COVID-19 vaccines.

Research progress on oncoprotein hepatitis B X­interacting protein (Review).

Hepatitis B X­interacting protein (HBXIP) is a membrane protein located on the lysosomal surface and encoded by the Lamtor gene. It is expressed by a wide range of tumor types, including breast cancer, esophageal squamous cell carcinoma and hepatocellular carcinoma, and its expression is associated with certain clinicopathological characteristics. In the past decade, research on the oncogenic mechanisms of HBXIP has increased and the function of HBXIP in normal cells has been gradually elucidated. In the present review, the following was discussed: The normal physiological role of the HBXIP carcinogenic mechanism; the clinical significance of high levels of HBXIP expression in different tumors; HBXIP regulation of transcription, post­transcription and post­translation processes in tumors; the role of HBXIP in improving the antioxidant capacity of tumor cells; the inhibition of ferroptosis of tumor cells and regulating the metabolic reprogramming of tumor cells; and the role of HBXIP in promoting the malignant progression of tumors. In conclusion, the present review summarized the existing knowledge of HBXIP, established its carcinogenic mechanism and discussed future related research on HBXIP.

Machine learning developed a fibroblast-related signature for predicting clinical outcome and drug sensitivity in ovarian cancer.

Ovarian cancer (OC) is the leading cause of gynecological cancer death. Cancer-associated fibroblasts (CAF) is involved in wound healing and inflammatory processes, tumor occurrence and progression, and chemotherapy resistance in OC. GSE184880 dataset was used to identify CAF-related genes in OC. CAF-related signature (CRS) was constructed using integrative 10 machine learning methods with the datasets from the Cancer Genome Atlas, GSE14764, GSE26193, GSE26712, GSE63885, and GSE140082. The performance of CRS in predicting immunotherapy benefits was verified using 3 immunotherapy datasets (GSE91061, GSE78220, and IMvigor210) and several immune calculating scores. The Lasso + StepCox[forward] method-based predicting model having a highest average C index of 0.69 was referred as the optimal CRS and it had a stable and powerful performance in predicting clinical outcome of OC patients, with the 1-, 3-, and 5-year area under curves were 0.699, 0.708, and 0.767 in the Cancer Genome Atlas cohort. The C index of CRS was higher than that of tumor grade, clinical stage, and many developed signatures. Low CRS score demonstrated lower tumor immune dysfunction and exclusion score, lower immune escape score, higher PD1&CTLA4 immunophenoscore, higher tumor mutation burden score, higher response rate and better prognosis in OC, suggesting a better immunotherapy response. OC patients with low CRS score had a lower half maximal inhibitory concentration value of some drugs (Gemcitabine, Tamoxifen, and Nilotinib, etc) and lower score of some cancer-related hallmarks (Notch signaling, hypoxia, and glycolysis, etc). The current study developed an optimal CRS in OC, which acted as an indicator for the prognosis, stratifying risk and guiding treatment for OC patients.

Development of a Monoclonal Antibody-Based Indirect Competitive Enzyme-Linked Immunosorbent Assay for the Rapid Detection of Gallic Acid.

Gallic acid (GA) is closely related to the quality of herbal medicines and other agricultural products. In order to facilitate the rapid detection of GA, we developed a monoclonal antibody-based ic-ELISA method. Antigens with and without connecting arms were prepared. It was found that the introduction of connecting arms (linear carbon chain) was beneficial for immune response. By utilizing hybridoma technology, a specific mAb (anti-GA-M702) was screened and identified, which exhibited a 1:40,500 antibody titer and IgG2b antibody subtype. The ic-ELISA assay was established based on anti-GA-M702. The optimal working concentrations of the encapsulated antigen and antibody were 0.5 µg/mL and 0.67 µg/mL, respectively. The ic-ELISA method showed a linear detection range of 297.17-2426.61 ng/mL for GA with a sensitivity of 849.18 ng/mL. It displayed a good applicability for the determination of GA in Galla chinensis. In conclusion, the ic-ELISA method provides an efficient approach to the rapid detection of GA in products.