Identification of new subtypes of breast cancer based on vasculogenic mimicry related genes and a new model for predicting the prognosis of breast cancer.

Breast cancer is a malignant tumor that poses a serious threat to women's health, and vasculogenic mimicry (VM) is strongly associated with bad prognosis in breast cancer. However, the relationship between VM and immune infiltration in breast cancer and the underlying mechanisms have not been fully studied. On the basis of the Cancer Genome Atlas (TCGA), Fudan University Shanghai Cancer Center (FUSCC) database, GSCALite database, and gene set enrichment analysis (GSEA) datasets, we investigated the potential involvement of VM-related genes in the development and progression of breast cancer. We analyzed the differential expression, mutation status, methylation status, drug sensitivity, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoints, tumor microenvironment (TME), and immune cell infiltration levels associated with VM-related genes in breast cancer. We created two VM subclusters out of breast cancer patients using consensus clustering, and discovered that patients in Cluster 1 had better survival outcomes compared to those in Cluster 2. The infiltration levels of T cells CD4 memory resting and T cells CD8 were higher in Cluster 1, indicating an immune-active state in this cluster. Additionally, we selected three prognostic genes (LAMC2, PIK3CA, and TFPI2) using Lasso, univariate, and multivariate Cox regression and constructed a risk model, which was validated in an external dataset. The prognosis of patients is strongly correlated with aberrant expression of VM-related genes, which advances our knowledge of the tumor immune milieu and enables us to identify previously unidentified breast cancer subtypes. This could direct more potent immunotherapy approaches.

Electrochemical aptamer sensor based on AgNPs@PDANSs and "sandwich" structure guidance for the detection of tobramycin in water samples.

In this study, an ultrasensitive detection platform for tobramycin (TOB) was developed, featuring a "sandwich" structure guided by AgNCs@PDANSs and Thi-AuNCs@ZnONSs. To address the issue of large background current peak signals in tagless sensors, Thi-AuNCs@ZnONSs composites were synthesized as signal tags. Zinc oxide nanosheets (ZnONSs) served as the loading agent, and AuNCs with the electroactive molecule Thi acted as carriers. Furthermore, AgNPs@PDANSs nanocomposites, possessing excellent electrical conductivity and large specific surface areas, were prepared as substrate materials for the modified electrodes. A "sandwich" structure strategy was also introduced to enhance the accuracy of the electrochemical aptasensor. This strategy, utilizing a dual sequence for target labeling and capture, yielded higher sensitivity and simplified the sensor construction compared to methods employing a single sequence. Under optimal conditions, the detection limit for TOB was established at 1.41 pM, with a detection range of 0.05-5000 nM. The aptasensor was effectively applied in the detection of TOB in tap and lake water, demonstrating outstanding reproducibility, selectivity, and stability. These results may serve as a reference for environmental TOB detection.

Blockade of the lncRNA-PART1-PHB2 axis confers resistance to PARP inhibitor and promotes cellular senescence in ovarian cancer.

PARPi is currently the most important breakthrough in the treatment of ovarian cancer in decades, and it has been integrated into the initial maintenance therapy for ovarian cancer. However, the mechanism leading to PARPi resistance remains unelucidated. Our study aims to screen novel targets to better predict and reverse resistance to PARPi and explore the potential mechanism. Here, we conducted a comparative analysis of differentially expressed genes between platinum-sensitive and platinum-resistant groups within the TCGA ovarian cancer cohort. The analysis indicated that lncRNA PART1 was significantly highly expressed in platinum-sensitive patients compared to platinum-resistant individuals in TCGA-OV cohort and further validated in the GEO dataset and Qilu hospital cohort. Moreover, the upregulation of PART1 was positively correlated with a favorable prognosis in ovarian cancer. Furthermore, in vitro and in vivo experiments showed that inhibition of PART1 conferred resistance to both cisplatin and PARP inhibitor and promoted cellular senescence. Senescent cells are more resistant to chemotherapeutics. RNA antisense purification and RNA immunoprecipitation assays revealed an interaction between PART1 and PHB2, a crucial mitophagy receptor. Knockdown of PART1 could promote the degradation of PHB2, impairing mitophagy and leading to cellular senescence. Rescue assays indicated that overexpression of PHB2 remarkably diminished the resistance to PARPi and cellular senescence caused by PART1 knockdown. PDX models were utilized to further confirm the findings. Altogether, our study demonstrated that lncRNA PART1 has the potential to serve as a novel promising target to reverse resistance to PARPi and improve prognosis in ovarian cancer.

Enhancing reliability for AFB1 analysis in food: Ratiometric fluorescence/colorimetric dual-modal analysis platform using multifunctional GO-Fe3O4.

Adsorption of DNA fluorescent probes on GO-Fe3O4 is a promising strategy for establishing fluorescent bioassays, often using magnetic separation or fluorescence quenching to generate signals. However, there is a lack of systematic understanding of ssDNA-regulated changes in the enzyme-mimetic activity of GO-Fe3O4, and the accuracy of the results of single-mode fluorescence analysis is susceptible to environmental interference. These limit the rational design and scope of application of the methods. Herein, the force and the catalytic mechanism of ssDNA/GO-Fe3O4 interactions were explored in detail. On this basis, a ratiometric fluorescence/colorimetric dual-modal analysis platform was constructed based on the superparamagnetism and DNA controllable peroxidase-like activity of GO-Fe3O4. The ratiometric fluorescent signal was generated by combining 7-amino-4-methyl-3-coumarinylacetic acid (AMCA) labeled aptamer (AMCA-aptamer) with AT hairpin-synthesized copper nanoparticles, which has built-in correction and resistance to environmental interference. The aptamer-modulated peroxidase-like activity of GO-Fe3O4 generated the colorimetric signal. Two signals correct each other to further enhance the reliability of the results. The analytical platform performed satisfactorily for AFB1 detection in the range of 0.1-150 µg/L, and was successfully applied to real samples (peanut, milk powder, and wheat flour). With the support of ImageJ software, quantitative detection was achieved by RGB channel analysis for real-color images, which provides a potential pathway for the rapid detection of food safety.

Review of cathodic electroactive bacteria: Species, properties, applications and electron transfer mechanisms.

Cathodic electroactive bacteria (C-EAB) which are capable of accepting electrons from solid electrodes provide fresh avenues for pollutant removal, biosensor design, and electrosynthesis. This review systematically summarized the burgeoning applications of the C-EAB over the past decade, including 1) removal of nitrate, aromatic derivatives, and metal ions; 2) biosensing based on biocathode; 3) electrosynthesis of CH4, H2, organic carbon, NH3, and protein. In addition, the mechanisms of electron transfer by the C-EAB are also classified and summarized. Extracellular electron transfer and interspecies electron transfer have been introduced, and the electron transport mechanism of typical C-EAB, such as Shewanella oneidensis MR-1, has been combed in detail. By bringing to light this cutting-edge area of the C-EAB, this review aims to stimulate more interest and research on not only exploring great potential applications of these electron-accepting bacteria, but also developing steady and scalable processes harnessing biocathodes.

The Three-Dimensional Hierarchical Structure of Bi x -Sn1-x O2 Used for Ultrasensitive Detection of Butanone under UV Irradiation.

Recent studies have identified butanone as a promising biomarker in the breath of lung cancer patients, yet the understanding of its gas-sensing properties remains limited. A key challenge has been to enhance the gas-sensing performance of materials toward butanone, particularly under ultraviolet light exposure. Herein, we report the synthesis of a novel three-dimensional composite material composed of SnO2 incorporated with Bi2O3 using facile hydrothermal and impregnation precipitation methods. Detailed physical and chemical characterizations were performed to assess the properties of the developed material. Upon activation with ultraviolet light, our composite exhibited exceptionally high sensitivity to butanone. Remarkably, the butanone response was nearly 3 times greater for the Bi2O3-loaded SnO2 composite than for pristine SnO2, achieving a response value of 70. This substantial improvement is due to the synergistic effect of the material's distinctive three-dimensional architecture and the presence of Bi2O3, which significantly augmented the gas-sensing capability of butanone. To elucidate the underlying gas-sensing mechanism, we conducted first-principles calculations using density functional theory (DFT). The computational analysis revealed that the Bi2O3-containing system possesses superior adsorption energy for butanone. Ultimately, our findings suggest that the Bi-SnO2 composite holds great promise as an optimal sensing material for the detection of butanone under ultraviolet illumination.

Energy-transfer Enabled Divergent Synthesis of Polycyclic γ-Sultines.

A visible-light-initiated energy-transfer enabled radical cyclization for the divergent synthesis of polycyclic γ-sultine derivatives has been developed. The reaction provides an alternative and expeditious access to benzofused γ-sultine frameworks, the analogues of γ-lactones and γ-sultones, and features good functional group compatibility, mild reaction conditions and excellent diastereoselectivity. The robustness and application potential of this method have also been successfully displayed by two gram-scale reactions and the synthesis of polycyclic sultones. Mechanistic studies indicated the transformations through a possible energy-transfer enabled intramolecular radical homolytic substitution or hydrogen atom transfer process mainly.

Highly efficient esterification of carboxylic acids with O-H nucleophiles through acid/iodide cooperative catalysis.

The esterification of carboxylic acids is an important reaction for preparing esters which find wide applications in various research fields. In this manuscript, we report an acid/iodide cooperative catalytic method which enables highly efficient esterification of carboxylic acids with a wide range of equivalent O-H nucleophiles including both alcohols and weak nucleophilic phenols. Under the reaction conditions, both aromatic and aliphatic carboxylic acids including those bearing functional groups work well, furnishing the corresponding esters in good to high yields. Moreover, this reaction is scalable and applicable to the modification of bioactive molecules. These results demonstrate the synthetic value of this new reaction in organic synthesis.

BCAR3 and BCAR3-related competing endogenous RNA expression in hepatocellular carcinoma and their prognostic value.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant tumor that has a high incidence and mortality worldwide. Despite extensive studies, the detailed molecular mechanism of HCC development remains unclear. Studies have shown that the occurrence and development of HCC are closely related to abnormal gene expression. BCAR3 has been shown to be overexpressed in a variety of malignant tumors. However, the role of BCAR3 in HCC remains unclear. AIM: To investigate the expression of BCAR3 and BCAR3-related competing endogenous RNAs (ceRNAs) in HCC and their clinical significance, in order to provide new ideas for the diagnosis and treatment of HCC. METHODS: The data of HCC were obtained from the Cancer Genome Atlas database and The Genotype Tissue Expression, including transcriptome data and clinical information. Multiple common databases, including UALCAN, Timer 2.0, cBioPortal, LinkedOmics, starBase, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, were used to analyse the expression of BCAR3, prognostic value, genetic alteration, co-expressed genes, differentially expressed genes, BCAR3 gene-related ceRNAs and functional enrichment analysis in HCC patients. Kaplan-Meier analysis, univariate and multivariate Cox regression analysis were used to analyze survival prognosis and the Spearman test was used to measure correlations between BCAR3 and immune functions. And R language package was used to analyze the correlation between BCAR3 and immune invasion of HCC. RESULTS: Our study indicated that BCAR3 was differentially expressed in various tumor tissues. The over-expression of BCAR3 gene was an unfavorable prognostic indicator for HCC patients, and associated with unfavorable cytogenetic risk and gene mutations. Moreover, most immune cells were positively correlated with BCAR3 (P < 0.05). According to the results of functional enrichment analysis, BCAR3 was involved in the positive regulation of epidermal growth factor receptor signaling pathway and ERBB signaling pathway, and was related to DNA replication and GTPase regulator activity. Finally, our study found that based on RAB30-DT and miR-19b-3p pathways, targeting BCAR3 might promote the occurrence and development of HCC. CONCLUSION: Collectively, this study indicated that the BCAR3 gene was involved in the occurrence and development of HCC, and it might be a new biomarker and therapeutic target for HCC, but the specific mechanism remains to be further verified.

A Novel Ubiquitin Ligase Adaptor PTPRN Suppresses Seizure Susceptibility through Endocytosis of NaV1.2 Sodium Channels.

Intrinsic plasticity, a fundamental process enabling neurons to modify their intrinsic properties, plays a crucial role in shaping neuronal input-output function and is implicated in various neurological and psychiatric disorders. Despite its importance, the underlying molecular mechanisms of intrinsic plasticity remain poorly understood. In this study, a new ubiquitin ligase adaptor, protein tyrosine phosphatase receptor type N (PTPRN), is identified as a regulator of intrinsic neuronal excitability in the context of temporal lobe epilepsy. PTPRN recruits the NEDD4 Like E3 Ubiquitin Protein Ligase (NEDD4L) to NaV1.2 sodium channels, facilitating NEDD4L-mediated ubiquitination, and endocytosis of NaV1.2. Knockout of PTPRN in hippocampal granule cells leads to augmented NaV1.2-mediated sodium currents and higher intrinsic excitability, resulting in increased seizure susceptibility in transgenic mice. Conversely, adeno-associated virus-mediated delivery of PTPRN in the dentate gyrus region decreases intrinsic excitability and reduces seizure susceptibility. Moreover, the present findings indicate that PTPRN exerts a selective modulation effect on voltage-gated sodium channels. Collectively, PTPRN plays a significant role in regulating intrinsic excitability and seizure susceptibility, suggesting a potential strategy for precise modulation of NaV1.2 channels' function.

Performance of low shrinkage Bis-EFMA based bulk-fill dental resin composites.

OBJECTIVES: The purpose of this study was evaluating the performance of new Bis-EFMA based bulk-fill composites with common methacrylate based composites and commercial dental composites. METHODS: The Bis-EFMA monomer was synthesized and the novel Bis-EFMA based bulk-fill composites were prepared. The resin composite samples were co-cultured with human gingival epithelial cells and human dental pulp stem cells to test the biocompatibility. The edge adaptation was observed under a combination of stereoscope and scanning electron microscope. The internal hardness was measured using a Vickers microhardness tester after one-time filling of cavities prepared in extracted teeth. After friction and wear test on the surface of the resin composites, the surface morphology and volume wear of each group were measured by the optical profilometer. The color stability was measured by a colorimeter. RESULTS: Direct contact with human gingival epithelial cells and human dental pulp stem cells did not cause significant changes in their growth density and morphology, indicating good biocompatibility of Bis-EFMA group (p > 0.05). The continuous margin proportion of the Bis-EFMA group was as good as commercial bulk-fill composites (p > 0.05). The sectional microhardness results showed that the Bis-EFMA group had the highest microhardness. After the friction and wear test, the volume wear of the Bis-EFMA group was minimal, indicating its good wear resistance and mechanical strength. Color changes in all resin groups after 28 days of immersion were within the clinically acceptable range. SIGNIFICANCE: The addition of Bis-EFMA demonstrated excellent biocompatibility, edge adaptation and color stability comparable to commonly used clinical bulk-fill composites, along with preferable mechanical strength, friction and wear resistance. Bis-EFMA based bulk-fill composites have the potential to be employed as a bulk filling material in commercial dental composite applications.

ElecFeX is a user-friendly toolbox for efficient feature extraction from single-cell electrophysiological recordings.

Characterizing neurons by their electrophysiological phenotypes is essential for understanding the neural basis of behavioral and cognitive functions. Technological developments have enabled the collection of hundreds of neural recordings; this calls for new tools capable of performing feature extraction efficiently. To address the urgent need for a powerful and accessible tool, we developed ElecFeX, an open-source MATLAB-based toolbox that (1) has an intuitive graphical user interface, (2) provides customizable measurements for a wide range of electrophysiological features, (3) processes large-size datasets effortlessly via batch analysis, and (4) yields formatted output for further analysis. We implemented ElecFeX on a diverse set of neural recordings; demonstrated its functionality, versatility, and efficiency in capturing electrical features; and established its significance in distinguishing neuronal subgroups across brain regions and species. ElecFeX is thus presented as a user-friendly toolbox to benefit the neuroscience community by minimizing the time required for extracting features from their electrophysiological datasets.

Predicting Risk of Alzheimer's Diseases and Related Dementias with AI Foundation Model on Electronic Health Records.

Early identification of Alzheimer's disease (AD) and AD-related dementias (ADRD) has high clinical significance, both because of the potential to slow decline through initiating FDA-approved therapies and managing modifiable risk factors, and to help persons living with dementia and their families to plan before cognitive loss makes doing so challenging. However, substantial racial and ethnic disparities in early diagnosis currently lead to additional inequities in care, urging accurate and inclusive risk assessment programs. In this study, we trained an artificial intelligence foundation model to represent the electronic health records (EHR) data with a vast cohort of 1.2 million patients within a large health system. Building upon this foundation EHR model, we developed a predictive Transformer model, named TRADE, capable of identifying risks for AD/ADRD and mild cognitive impairment (MCI), by analyzing the past sequential visit records. Amongst individuals 65 and older, our model was able to generate risk predictions for various future timeframes. On the held-out validation set, our model achieved an area under the receiver operating characteristic (AUROC) of 0.772 (95% CI: 0.770, 0.773) for identifying the AD/ADRD/MCI risks in 1 year, and AUROC of 0.735 (95% CI: 0.734, 0.736) in 5 years. The positive predictive values (PPV) in 5 years among individuals with top 1% and 5% highest estimated risks were 39.2% and 27.8%, respectively. These results demonstrate significant improvements upon the current EHR-based AD/ADRD/MCI risk assessment models, paving the way for better prognosis and management of AD/ADRD/MCI at scale.

Versatile filter membrane for effective sampling and real-time quantitative detection of airborne pathogens.

Construction of air filter membranes bearing prominent collecting and transferring capability is highly desirable for detecting airborne pathogens but remains challenging. Here, a hyaluronic acid air filter membrane (HAFM) with tunable heterogeneous micro-nano porous structures is straightforwardly constructed through the ethanol-induced phase separation strategy. Airborne pathogens can be trapped and collected by HAFM with high performance due to the ideal trade-off between removal efficiency and pressure drop. By exempting the sample elution and extraction processes, the HAFM after filtration sampling can not only directly disperse on the agar plate for colony culture but also turn to an aqueous solution for centrifugal enrichment, which significantly reduces the damage and losses of the captured microorganisms. The following combination with ATP bioluminescence endows the HAFM with a real-time quantitative detection function for the captured airborne pathogens. Benefiting from high-efficiency sampling and non-traumatic transfer of airborne pathogens, the real-world bioaerosol concentration can be facilely evaluated by the HAFM-based ATP assay. This work thus not only provides a feasible strategy to fabricate air filter membranes for efficient microbial collection and enrichment but also sheds light on designing advanced protocols for real-time detection of bioaerosols in the field.

Gender disparity between first and senior authors on liver cancer research in the top journals of Gastroenterology and Hepatology.

BACKGROUND: Gender disparity is pervasive in academic medicine. This study aimed to assess the disparity between men and women with regard to first and senior author positions in primary studies on liver cancer over the last two decades. METHODS: We conducted a review of articles published in high-impact factor journals of the field of Gastroenterology and Hepatology in 2005, 2010, 2015 and 2020. First and senior authors of all ages were considered as the study population. The authors' genders were determined using the online artificial intelligence tool genderize.io (https://genderize.io/). The disparity between men and women authors was assessed using the linear-by-linear association test. RESULTS: 665 original articles from 10 journals were reviewed. The point prevalence of first women authors was 25.0% compared with 75.0% for men. The point prevalence of senior women authors was 16.3% compared with 83.7% for men. From 2000 to 2020, the proportion of first women authors increased 14.4% to 26.8% compared with 85.6%-73.2% for men (P = 0.009), and the proportion of senior women authors increased from 7.4% to 19.5%, compared with 92.6%-80.5% for men (P = 0.035). The factor independently associated with a reduced representation of women among first authors was the region of author. The factor independently associated with a reduced representation of women among senior authors was the impact factor of journals. CONCLUSION: The findings indicated a remarkable increase in the proportion of women, both first and senior authors, over the past two decades in the field of liver cancers. However, the representation of women authors in this area is far less than that of men.

Strictosamide promotes wound healing through activation of the PI3K/AKT pathway.

Nauclea officinalis, as a Chinese medicine in Hainan province, had the effect of treating lower limb ulcers, burn infections. In this paper, we studied the effect of Strictosamide (STR), the main bioactive compound in Nauclea officinals, on wound healing and explored its internal mechanism. Firstly, the wound healing potential of STR was evaluated in a rat model, demonstrating its ability to expedite wound healing, mitigate inflammatory infiltration, and enhance collagen deposition. Additionally, immunofluorescence analysis revealed that STR up-regulated the expression of CD31 and PCNA. Subsequently, target prediction, protein-protein interaction (PPI), gene ontology (GO), and pathway enrichment analyses were used to obtain potential targets, specific biological processes, and molecular mechanisms of STR for the potential treatment of wound healing. Furthermore, molecular docking was conducted to predict the binding affinity between STR and its associated targets. Additionally, in vivo and in vitro experiments confirmed that STR could increase the expression of P-PI3K, P-AKT and P-mTOR by activating the PI3K/AKT signaling pathway. In summary, this study provided a new explanation for the mechanism by which STR promotes wound healing through network pharmacology, suggesting that STR may be a new candidate for treating wound.

Protocol for automated N-glycan sequencing using mass spectrometry and computer-assisted intelligent fragmentation.

Biological functions of glycans are intimately linked to fine details in branches and linkages, which make structural identification extremely challenging. Here, we present a protocol for automated N-glycan sequencing using multi-stage mass spectrometry (MSn). We describe steps for release/purification and derivation of glycans and procedures for MSn scanning. We then detail "glycan intelligent precursor selection" to computationally guide MSn experiments. The protocol can be used for both discrete individual glycans and isomeric glycan mixtures. For complete details on the use and execution of this protocol, please refer to Sun et al.,1 Huang et al.,2 and Huang et al.3.

Ligand-engineering Cu-based catalysts to accelerate the electrochemical reduction of CO2.

Two typical Cu-based complex catalysts with piperazine (PR) and p-phenylenediamine (pPDA) ligands were designed to elucidate whether the ligands can tailor the reduction behavior of the Cu species and thus modulate their electrochemical CO2 reduction reaction (eCO2RR) activity. Specifically, Cu-PR underwent a significant in situ transformation into Cu nanoparticles enriched with a Cuδ+/Cu0 interface for high eCO2RR activity, compared to Cu-pPDA. This finding reveals the importance of ligand engineering in modulating the eCO2RR performance of Cu-based complexes.

Determining Cognitive Workload Using Physiological Measurements: Pupillometry and Heart-Rate Variability.

The adoption of Industry 4.0 technologies in manufacturing systems has accelerated in recent years, with a shift towards understanding operators' well-being and resilience within the context of creating a human-centric manufacturing environment. In addition to measuring physical workload, monitoring operators' cognitive workload is becoming a key element in maintaining a healthy and high-performing working environment in future digitalized manufacturing systems. The current approaches to the measurement of cognitive workload may be inadequate when human operators are faced with a series of new digitalized technologies, where their impact on operators' mental workload and performance needs to be better understood. Therefore, a new method for measuring and determining the cognitive workload is required. Here, we propose a new method for determining cognitive-workload indices in a human-centric environment. The approach provides a method to define and verify the relationships between the factors of task complexity, cognitive workload, operators' level of expertise, and indirectly, the operator performance level in a highly digitalized manufacturing environment. Our strategy is tested in a series of experiments where operators perform assembly tasks on a Wankel Engine block. The physiological signals from heart-rate variability and pupillometry bio-markers of 17 operators were captured and analysed using eye-tracking and electrocardiogram sensors. The experimental results demonstrate statistically significant differences in both cardiac and pupillometry-based cognitive load indices across the four task complexity levels (rest, low, medium, and high). Notably, these developed indices also provide better indications of cognitive load responding to changes in complexity compared to other measures. Additionally, while experts appear to exhibit lower cognitive loads across all complexity levels, further analysis is required to confirm statistically significant differences. In conclusion, the results from both measurement sensors are found to be compatible and in support of the proposed new approach. Our strategy should be useful for designing and optimizing workplace environments based on the cognitive load experienced by operators.