Machine learning based on optimal VOI of multi-sequence MR images to predict lymphovascular invasion in invasive breast cancer.

Objectives: Lymphovascular invasion serves as a crucial prognostic indicator in invasive breast cancer, influencing treatment decisions. We aimed to develop a machine learning model utilizing optimal volumes of interest extracted from multisequence magnetic resonance images to predict lymphovascular invasion in patients with invasive breast cancer. Materials and methods: This study comprised 191 patients postoperatively diagnosed with invasive breast cancer through multi-sequence magnetic resonance imaging. Independent predictors were identified through univariate and multivariate logistic regression analyses, culminating in the construction of a clinical model. Radiomic features were extracted from multi-sequence magnetic resonance imaging images across various volume of interest scales (-2 mm, entire, +2 mm, +4 mm, and +6 mm). Subsequently, various radiomic models were developed using machine learning model algorithms, including logistic regression, support vector machine, k-nearest neighbor, gradient boosting machine, classification and regression tree, and random forest. A hybrid model was then formulated, amalgamating optimal radiomic and clinical models. Results: The area under the curve of the clinical model was 0.757. Among the radiomic models, the most efficient diagnosis was achieved by the k-nearest neighbor-based radiomics-volume of interest (+2 mm), resulting in an area under the curve of 0.780. The hybrid model, integrating the k-nearest neighbor-based radiomics-volume of interest (+2 mm), and the clinical model surpassed the individual clinical and radiomics models, exhibiting a superior area under the curve of 0.864. Conclusion: Utilizing a hybrid approach integrating clinical data and multi-sequence magnetic resonance imaging-derived radiomics models based on the multiscale tumor region volume of interest (+2 mm) proved effective in determining lymphovascular invasion status in patients with invasive breast cancer. This innovative methodology may offer valuable insights for treatment planning and disease management.

Self-Assembly of Peptides as an Alluring Approach toward Cancer Treatment and Imaging.

Cancer is a severe threat to humans, as it is the second leading cause of death after cardiovascular diseases and still poses the biggest challenge in the world of medicine. Due to its higher mortality rates and resistance, it requires a more focused and productive approach to provide the solution for it. Many therapies promising to deliver favorable results, such as chemotherapy and radiotherapy, have come up with more negatives than positives. Therefore, a new class of medicinal solutions and a more targeted approach is of the essence. This review highlights the alluring properties, configurations, and self-assembly of peptide molecules which benefit the traditional approach toward cancer therapy while sparing the healthy cells in the process. As targeted drug delivery systems, self-assembled peptides offer a wide spectrum of conjugation, biocompatibility, degradability-controlled responsiveness, and biomedical applications, including cancer treatment and cancer imaging.

Propane-2-sulfonic acid octadec-9-enyl-amide, a novel PPARα/γ dual agonist, attenuates molecular pathological alterations in learning memory in AD mice.

OBJECTIVE: Previous studies have revealed that Propane-2-sulfonic acid octadec-9-enyl-amide(N15) exerts a protective role in the inflammatory response after ischemic stroke and in neuronal damage. However, little is known about N15 in Alzheimer's disease (AD). The aim of this study was to investigate the effects of N15 on AD and explore the underlying molecular mechanism. METHODS: AD mice model was established by lateral ventricular injection with Aß25-35. N15 was daily intraperitoneal administered for 28 days. Morris Water Maze was used to evaluate the neurocognitive function of the mice. The expression of PPARα/γ, brain-derived neurotrophic factor (BDNF), Neurotrophin-3 (NT3), ADAM10, PS1 and BACE1 were measured by qPCR. Aß amyloid in the hippocampus was measured by Congo red assay. Toluidine blue staining was used to detect the neuronal apoptosis. Protein levels of ADAM10, PS1 and BACE1 were determined using immunoblotting. RESULTS: N15 treatment significantly reduced neurocognitive dysfunction, which also significantly activated the expression of PPARα/γ at an optimal dose of 200 mg/kg. Administration of N15 alleviated the formation of Aß amyloid in the hippocampus of AD mice, enhanced the BDNF mRNA expression, decreased the mRNA and protein levels of PS1 and BACE1, upregulated ADAM10 mRNA and protein levels. CONCLUSION: N15 exerts its neuroprotective effects through the activation of PPARα/γ and may be a potential drug for the treatment of AD.

USP15 facilitates the progression of bladder cancer by amplifying the activation of the NF-κB signaling pathway.

USP15, a pivotal member of the deubiquitinase family, plays a crucial role in orchestrating numerous vital biological processes, including the regulation of NF-κB signaling pathway and deubiquitination of proto-oncogenes. In various cancers, USP15 has been validated to exhibit up-regulated expression, impacting the initiation and progression of cancer. However, its precise mechanism in bladder cancer remains elusive. Our study shed light on the significant overexpression of USP15 in bladder cancer cells compared to normal bladder cells, correlating with a poorer prognosis for bladder cancer patients. Strikingly, attenuation of USP15 expression greatly attenuated the proliferation, migration, and invasion of bladder cancer cells. Moreover, upregulation of USP15 was found to drive cancer progression through the activation of the NF-κB signaling pathway. Notably, USP15 directly deubiquitinates BRCC3, heightening its expression level, and subsequent overexpression of BRCC3 counteracted the antitumoral efficacy of USP15 downregulation. Overall, our findings elucidated the carcinogenic effects of USP15 in bladder cancer, primarily mediated by the excessive activation of the NF-κB signaling pathway, thereby promoting tumor development. These results underscore the potential of USP15 as a promising therapeutic target for bladder cancer in the future.

A four-gene signature predicts overall survival of patients with esophageal adenocarcinoma.

Background: Esophageal adenocarcinoma (EAC) is an aggressive cancer with poor prognosis. Thus, this study aimed to identify a prognostic molecular signature to predict the overall survival (OS) of patients with EAC. Methods: The mRNA microarray data sets GSE13898 and GSE26886 were downloaded from the Gene Expression Omnibus (GEO) database. RNA sequencing profile and clinical data of EAC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) between EAC tissues and adjacent non-cancerous tissues were obtained using R software. DEGs associated with prognosis of OS were assessed by univariate Cox analysis, and a prognostic signature was built using stepwise multivariate Cox analysis. Time-dependent receiver operating characteristic (ROC) analysis and stratification analysis were conducted to evaluate its predictive performance. Functional enrichment analysis was performed for genes co-expressed with the signature to explore its biological functions in EAC. Results: A total of 336 genes were identified to be differentially expressed between EAC tissues and adjacent non-cancerous tissues. After univariate and multivariate Cox regression analysis, four genes (ALAD, ABLIM3, IL17RB and IFI6) were screened out to construct a prognostic signature. According to this signature, patients could be assigned into high-risk and low-risk group with significantly different OS (P=4.92e-05<0.0001). Multivariate Cox regression analysis suggested that the four-gene signature served as an independent factor in OS prediction. In the time-dependent ROC analysis, the areas under the curves (AUCs) were 0.804, 0.792 and 0.695 for 1-, 3- and 5-year survival prediction, respectively, suggesting a good performance. Functional enrichment analysis showed that the signature was mainly clustered in cell proliferation related biological processes or pathways. Conclusions: The four-gene signature identified in the current study may be a potential prognostic factor for predicting OS of EAC patients.

Efficacy of acupoint injection of metoclopramide for post-chemotherapy vomiting: A systematic review and meta-analysis.

BACKGROUND: Vomiting is one of the most common adverse events of chemotherapy. The purpose of this study was to systematically review the clinical efficacy of acupoint injection of metoclopramide in the treatment of post-chemotherapy vomiting. METHODS: We searched 4 general English databases and 4 conventional Chinese databases, all with a time frame from database creation to December 2022. The retrieved clinical trials of acupoint injection of metoclopramide for post-chemotherapy vomiting were then subjected to meta-analysis and trial sequential analysis. RESULTS: A total of 12 studies were included, with a total sample size of 965 cases. Meta-analysis showed that acupoint injection of metoclopramide was effective in improving anti-vomiting effective rate [odds ratio = 5.67, 95% confidence interval = (3.80,8.47), P < .00001] compared with intramuscular/intravenous injection, and trial sequential analysis showed that this benefit was conclusive. Subgroup analysis demonstrated that acupoint injection significantly improved the anti-vomiting effective rate at doses of 10 mg qd, 20 mg qd, and 30 mg qd, as well as at durations of 1 day and 5 days. Subgroup analysis also indicated that injection at the Zusanli acupoint significantly increased the anti-vomiting effective rate, while injection at the Neiguan acupoint had an anti-vomiting effective rate comparable to that of the control group. Harbord regression showed no significant publication bias (P = .730). CONCLUSION: Acupoint injection of metoclopramide for post-chemotherapy vomiting is more effective than intramuscular and intravenous injections and is not limited by dose or duration of treatment, which may be the preferred way of administration.

Dion-Jacobson Type Lead-Free Double Perovskite with Ultra-Narrow Aromatic Interlayer Spacing for Highly Sensitive and Stable X-ray Detection.

The low-toxic and environmentally friendly 2D lead-free perovskite has made significant progress in the exploration of "green" X-ray detectors. However, the gap in detection performance between them and their lead-based analogues remains a matter of concern that cannot be ignored. To reduce this gap, shortening the interlayer spacing to accelerate the migration and collection of X-ray carriers is a promising strategy. Herein, a Dion-Jacobson (DJ) lead-free double perovskite (4-AP)2 AgBiBr8 (1, 4-AP = 4-amidinopyridine) with an ultra-narrow interlayer spacing of 3.0 Å, is constructed by utilizing π-conjugated aromatic spacers. Strikingly, the subsequent enhanced carrier transport and increased crystal density lead to X-ray detectors based on bulk single crystals of 1 with a high sensitivity of 1117.3 µC Gy-1  cm-2 , superior to the vast majority of similar double perovskites. In particular, the tight connection of the inorganic layers by the divalent cations enhances structural rigidity and stability, further endowing 1 detector with ultralow dark current drift (3.06 × 10-8  nA cm-1  s-1  V-1 , 80 V), excellent multiple cycles switching X-ray irradiation stability, as well as long-term environmental stability (maintains over 94% photoresponse after 90 days). This work brings lead-free double perovskites one step closer to realizing efficient practical green applications.

Low albumin combined with low-molecular-weight heparin as risk factors for liver injury using azvudine: Evidence from an analysis of COVID-19 patients in a national prospective pharmacovigilance database.

OBJECTIVE: Azvudine is an effective treatment for patients infected with common COVID-19. However, physicians have reported a series of adverse reactions, including multiple cases of liver injury, caused by azvudine in clinical practice. This study assessed the incidence, clinical features, and associated risk factors of liver injury induced by azvudine in real-world settings, offering guidance for safe clinical use. MATERIALS AND METHODS: This study utilized the Chinese Hospital Pharmacovigilance System (CHPS) to retrospectively analyze the treatment of COVID-19 patients with azvudine at Changsha Central Hospital from December 19, 2022, to June 6, 2023. A case-control study was conducted to analyze the occurrence of azvudine-induced liver injury in COVID-19 patients who triggered a CHPS alert compared to normal COVID-19 patients. RESULTS: Among the total of 2,141 COVID-19 patients, 31 (1.45%) developed azvudine-induced liver injury, which is classified as an occasional adverse reaction. Liver injury was observed in 93.55% of patients between days 4 and 12 of the azvudine treatment, with elevated transaminases as the primary clinical manifestation. Univariate and binary logistic regression analyses indicated that low albumin levels and co-administration of low-molecular-weight heparin were statistically significant risk factors (p < 0.05). CONCLUSION: This study represents the first investigation of azvudine-induced liver injury and high-risk patients using the CHPS. The findings provide valuable insights to promote the safety of anti-COVID-19 drugs, serving as an important reference for future drug safety measures.

The effects of Fc fusion protein glucagon-like peptide-1 and glucagon dual receptor agonist with different receptor selectivity in vivo studies.

BACKGROUND: Glucagon-like peptide-1 (GLP-1)/glucagon (GCG) dual receptor agonists with different receptor selectivity are under investigation and have shown significant improvement in both weight loss and glycemic control, but the optimal potency ratio between the two receptors to balance efficacy and safety remains unclear. EXPERIMENTAL APPROACH: We designed and constructed several dual receptor agonists with different receptor potency ratios using Fc fusion protein technology. The long-term effects of the candidates on body weight and metabolic dysfunction-associated steatotic liver disease (MASLD) were evaluated in diet-induced obese (DIO) model mice, high-fat diet (HFD)-ob/ob mice and AMLN diet-induced MASLD mice. Repeat dose toxicity assays were performed to investigate the safety profile of the candidate (HEC-C070) in Sprague Dawley (SD) rats. KEY RESULTS: The high GCG receptor (GCGR) selectivity of HEC-C046 makes it more prominent than other compounds for weight loss and most MASLD parameters but may lead to safety concerns. The weight change of HEC-C052 with the lowest GCG agonism was inferior to that of selective GLP-1 receptor agonist (GLP-1RA) semaglutide in DIO model mice. The GLP-1R selectivity of HEC-C070 with moderate GCG agonism has a significant effect on weight loss and liver function in obese mice, and its lowest observed adverse effect level (LOAEL) was 30 nmol/kg in the repeat dose toxicity study. CONCLUSION: We compared the potential of the Fc fusion protein GLP-1/GCG dual receptor agonists with different receptor selectivity to provide the setting for future GLP-1/GCG dual receptor agonists to treat obesity and MASLD.

Interventions to Improve Endoscopic Screening Adherence of Cancer in High-Risk Populations: A Scoping Review.

Background: Colorectal, and gastric cancers have the second, and fourth mortality rates worldwide, respectively. Endoscopic screening is a crucial diagnostic tool for colorectal, and gastric cancers. Effective interventions can improve adherence to endoscopic screening in high-risk populations, which is important for cancer prevention and mortality reduction. This study aimed to identify interventions that could improve adherence to endoscopic screening for cancer in high-risk populations. Methods: Combination keywords including colorectal cancer, gastric cancer, screening adherence, and interventions were used to search for articles in PubMed, Web of Science, Cochrane Library, and MEDLINE Complete. The review methodology was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-SCR). Results: A total of 12 articles were included in this review: 9 randomized controlled trials(RCT) and 3 quasi-experimental studies(QEDs). Among the extracted studies, 11 were about colorectal cancer, and 1 was about gastric cancer. Most studies used lecture-based or Information Technology-based health education interventions. Narrative interventions have proven to be novel and effective approaches for promoting adherence to endoscopic screening. Health education interventions included cancer epidemiology, cancer risk factors, warning symptoms, and screening methods. Conclusion: All interventions involved were effective in increasing individual knowledge of cancer-related endoscopic screening, willingness to undergo screening, and screening behaviors. These findings provide a reference for designing endoscopy-related cancer screening interventions.

Factors affecting the compliance of hepatocellular carcinoma screening among high-risk populations: A systematic review and meta-analysis.

BACKGROUND: Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the third leading cause of cancer mortality. HCC has high morbidity, high mortality, and low survival rates. Screening is one of the most significant methods of lowering incidence and death while also increasing survival. OBJECTIVES: The aim of this study was to identify the facilitators and barriers to participation in HCC screening among high-risk populations. METHODS: A comprehensive and systematic search was undertaken in PubMed, Web of Science, MEDLINE, EMBACE, EBSCOhost and the Cochrane Library. A combination of synonyms of the keywords including HCC, screening, factors and adherence were used for searching. Studies addressing the facilitators and barriers to HCC screening compliance in at-risk individuals were included. Data were synthesized using Review Manager version 5.4. A random/fixed effects model meta-analysis was performed to estimate the pooled data and expressed with odds ratio (OR) and 95% confidence interval (CI). RESULTS: A total of seven articles met the inclusion criteria. Qualitative (n = 1) and quantitative (n = 6) studies using various types of surgery were conducted. The most commonly mentioned barriers were insufficient knowledge and awareness of HCC screening, unawareness of the necessity for early detection of HCC and lack of physician recommendation. A meta-analysis of seven studies showed that individuals with a family history of HCC increased screening uptake by nearly three times (OR: 2.69, 95% CI: 1.93, 3.75). Other most frequently reported facilitators include age, education level, and perceived risk et al. CONCLUSIONS: Many barriers to HCC screening were found. Meanwhile, this review points out that improving the awareness of high-risk populations toward HCC screening is expected to enhance compliance, thereby promoting early diagnosis of liver cancer, reducing mortality, and alleviating the burden of HCC.

Classification and hemodynamic characteristics of delayed intracerebral hemorrhage following stent-assisted coil embolism in unruptured intracranial aneurysms.

Background and objective: Stent-assisted coil (SAC) embolization is a commonly used endovascular treatment for unruptured intracranial aneurysms (UIAs) but can be associated with symptomatic delayed intracerebral hemorrhage (DICH). Our study aimed to investigate the hemodynamic risk factors contributing to DICH following SAC embolization and to establish a classification for DICH predicated on hemodynamic profiles. Methods: This retrospective study included patients with UIAs located in the internal carotid artery (ICA) treated with SAC embolization at our institution from January 2021 to January 2022. We focused on eight patients who developed postoperative DICH and matched them with sixteen control patients without DICH. Using computational fluid dynamics, we evaluated the hemodynamic changes in distal arteries [terminal ICA, the anterior cerebral artery (ACA), and middle cerebral artery (MCA)] pre-and post-embolization. We distinguished DICH-related arteries from unrelated ones (ACA or MCA) and compared their hemodynamic alterations. An imbalance index, quantifying the differential in flow velocity changes between ACA and MCA post-embolization, was employed to gauge the flow distribution in distal arteries was used to assess distal arterial flow distribution. Results: We identified two types of DICH based on postoperative flow alterations. In type 1, there was a significant lower in the mean velocity increase rate of the DICH-related artery compared to the unrelated artery (-47.25 ± 3.88% vs. 42.85 ± 3.03%; p < 0.001), whereas, in type 2, there was a notable higher (110.58 ± 9.42% vs. 17.60 ± 4.69%; p < 0.001). Both DICH types demonstrated a higher imbalance index than the control group, suggesting an association between altered distal arterial blood flow distribution and DICH occurrence. Conclusion: DICH in SAC-treated UIAs can manifest as either a lower (type 1) or higher (type 2) in the rate of velocity in DICH-related arteries. An imbalance in distal arterial blood flow distribution appears to be a significant factor in DICH development.

Drug-eluting stents for coronary artery disease in the perspective of bibliometric analysis.

Drug-eluting stents (DES) play a crucial role in treating coronary artery disease (CAD) by preventing restenosis. These stents are coated with drug carriers that release antiproliferative drugs within the vessel. Over the past two decades, DES have been employed in clinical practice using various materials, polymers, and drug types. Despite optimizations in their design and materials to enhance biocompatibility and antithrombotic properties, evaluating their long-term efficacy and safety necessitates improved clinical follow-up and monitoring. To delineate future research directions, this study employs a bibliometric analysis approach. We comprehensively surveyed two decades' worth of literature on DES for CAD using the Web of Science Core Collection (WOSCC). Out of 5,778 articles, we meticulously screened them based on predefined inclusion and exclusion criteria. Subsequently, we conducted an in-depth analysis encompassing annual publication trends, authorship affiliations, journal affiliations, keywords, and more. Employing tools such as Excel 2021, CiteSpace 6.2R3, VOSviewer 1.6.19, and Pajek 5.17, we harnessed bibliometric methods to derive insights from this corpus. Analysis of annual publication data indicates a recent stabilisation or even a downward trend in research output in this area. The United States emerged as the leading contributor, with Columbia University and CRF at the forefront in both publication output and citation impact. The most cited document pertained to standardized definitions for clinical endpoints in coronary stent trials. Our author analysis identifies Patrick W. Serruys as the most prolific contributor, underscoring a dynamic exchange of knowledge within the field.Moreover, the dual chart overlay illustrates a close interrelation between journals in the "Medicine," "Medical," and "Clinical" domains and those in "Health," "Nursing," and "Medicine." Frequently recurring keywords in this research landscape include DES coronary artery disease, percutaneous coronary intervention, implantation, and restenosis. This study presents a comprehensive panorama encompassing countries, research institutions, journals, keyword distributions, and contributions within the realm of DES therapy for CAD. By highlighting keywords exhibiting recent surges in frequency, we elucidate current research hotspots and frontiers, thereby furnishing novel insights to guide future researchers in this evolving field.

Exosomes containing miR-1469 regulate natural killer cells by targeting CD122 in non-segmental vitiligo.

BACKGROUND: Plasma exosomal microRNAs (miRNAs) have been used as potential biomarkers for various diseases and have been investigated for their possible involvement in the pathogenesis of vitiligo. However, the miRNA expression profile of plasma exosomes in patients with non-segmental vitiligo (NSV) has not been determined yet. OBJECTIVE: To screen differentially expressed microRNAs in plasma exosomes derived from patients with NSV and explore their roles in the pathogenesis of NSV. METHODS: High-throughput sequencing was performed to determine the expression profiles of exosomal miRNAs in NSV. The effect of upregulated miR-1469 in NSV circulating exosomes on natural killer (NK) cells was further investigated using various molecular biological techniques. RESULTS: MiR-1469 was identified as a candidate biomarker whose expression was significantly increased in circulating exosomes of NSV patients. Circulating exosomes were internalized by NK cells and increased NK cell proliferation viability and IFN-γ secretion capacity delivering miR-1469. Further studies revealed that the upregulation of CD122, the predicted target of miR-1469, could partially reverse the effect of miR-1469 on natural killer cells. CONCLUSION: Alterations in plasma exosomal cargo occur in NSV and appear to contribute to NK cell dysfunction. Exosomal miR-1469 may be a biomarker of disease activity and could be used as a therapeutic drug target against innate immunity in NSV patients. The present study provides new insights into the role of exosomal miRNAs in NSV and suggests a novel miR-1469-CD122-IFN-γ pathway of NK cell underlying pathogenesis of NSV.

Leveraging multimodal MRI-based radiomics analysis with diverse machine learning models to evaluate lymphovascular invasion in clinically node-negative breast cancer.

Objective: This study aimed to investigate and validate the effectiveness of diverse radiomics models for preoperatively differentiating lymphovascular invasion (LVI) in clinically node-negative breast cancer (BC). Methods: This study included 198 patients diagnosed with clinically node-negative bc and pathologically confirmed LVI status from January 2018-July 2023. The training dataset consisted of 138 patients, while the validation dataset included 60. Radiomics features were extracted from multimodal magnetic resonance imaging obtained from T1WI, T2WI, DCE, DWI, and ADC sequences. Dimensionality reduction and feature selection techniques were applied to the extracted features. Subsequently, machine learning approaches, including logistic regression, support vector machine, classification and regression trees, k-nearest neighbors, and gradient boosting machine models (GBM), were constructed using the radiomics features. The best-performing radiomic model was selected based on its performance using the confusion matrix. Univariate and multivariable logistic regression analyses were conducted to identify variables for developing a clinical-radiological (Clin-Rad) model. Finally, a combined model incorporating both radiomics and clinical-radiological model features was created. Results: A total of 6195 radiomic features were extracted from multimodal magnetic resonance imaging. After applying dimensionality reduction and feature selection, seven valuable radiomics features were identified. Among the radiomics models, the GBM model demonstrated superior predictive efficiency and robustness, achieving area under the curve values (AUC) of 0.881 (0.823,0.940) and 0.820 (0.693,0.947) in the training and validation datasets, respectively. The Clin-Rad model was developed based on the peritumoral edema and DWI rim sign. In the training dataset, it achieved an AUC of 0.767 (0.681, 0.854), while in the validation dataset, it achieved an AUC of 0.734 (0.555-0.913). The combined model, which incorporated radiomics and the Clin-Rad model, showed the highest discriminatory capability. In the training dataset, it had an AUC value of 0.936 (0.892, 0.981), and in the validation dataset, it had an AUC value of 0.876 (0.757, 0.995). Additionally, decision curve analysis of the combined model revealed its optimal clinical efficacy. Conclusion: The combined model, integrating radiomics and clinical-radiological features, exhibited excellent performance in distinguishing LVI status. This non-invasive and efficient approach holds promise for aiding clinical decision-making in the context of clinically node-negative BC.

In vivo assembly enhanced binding effect augments tumor specific ferroptosis therapy.

Emerging evidence indicates that the activation of ferroptosis by glutathione peroxidase 4 (GPX4) inhibitors may be a prominent therapeutic strategy for tumor suppression. However, the wide application of GPX4 inhibitors in tumor therapy is hampered due to poor tumor delivery efficacy and the nonspecific activation of ferroptosis. Taking advantage of in vivo self-assembly, we develop a peptide-ferriporphyrin conjugate with tumor microenvironment specific activation to improve tumor penetration, endocytosis and GPX4 inhibition, ultimately enhancing its anticancer activity via ferroptosis. Briefly, a GPX4 inhibitory peptide is conjugated with an assembled peptide linker decorated with a pH-sensitive moiety and ferriporphyrin to produce the peptide-ferriporphyrin conjugate (Gi-F-CAA). Under the acidic microenvironment of the tumor, the Gi-F-CAA self-assembles into large nanoparticles (Gi-F) due to enhanced hydrophobic interaction after hydrolysis of CAA, improving tumor endocytosis efficiency. Importantly, Gi-F exhibits substantial inhibition of GPX4 activity by assembly enhanced binding (AEB) effect, augmenting the oxidative stress of ferriporphyrin-based Fenton reaction, ultimately enabling antitumor properties in multiple tumor models. Our findings suggest that this peptide-ferriporphyrin conjugate design with AEB effect can improve the therapeutic effect via induction of ferroptosis, providing an alternative strategy for overcoming chemoresistance.

MST-net: A multi-scale swin transformer network for EEG-based cognitive load assessment.

Cognitive load assessment plays a crucial role in monitoring safe production, resource allocation, and subjective initiative in human-computer interaction. Due to its high time resolution and convenient acquisition, Electroencephalography (EEG) is widely applied in brain monitoring and cognitive state assessment. In this study, a multi-scale Swin Transformer network (MST-Net) was proposed for cognitive load assessment, which extracts local features with different sensory fields using a multi-scale parallel convolution model and introduces the attention mechanism of the Swin Transformer to obtain the feature correlations among multi-scale local features. The performance of the proposed network was validated using the EEG signals collected during cognitive tasks and N-back tasks with three different load levels. Results show that the MST-Net network achieved the best classification accuracy on both local and public datasets, and was higher than the mainstream Swin Transformer and CNN. Furthermore, results of ablation experiments and feature visualization revealed that the proposed MST-Net could well characterize different cognitive loads, which not only provided novel and powerful tools for cognitive load assessment but also showed potential for broad application in brain-computer interface (BCI) systems.

Covalent drugs based on small molecules and peptides for disease theranostics.

Biomacromolecules, such as proteins, nucleic acids and polysaccharides, are widely distributed in the human body, and some of them have been recognized as the targets of drugs for disease theranostics. Drugs typically act on targets in two ways: non-covalent bond and covalent bond. Non-covalent bond-based drugs have some disadvantages, such as structural instability and environmental sensitivity. Covalent interactions between drugs and targets have a longer action time, higher affinity and controllability than non-covalent interactions of conventional drugs. With the development of artificial intelligence, covalent drugs have received more attention and have been developed rapidly in pharmaceutical research in recent years. From the perspective of covalent drugs, this review summarizes the design methods and the effects of covalent drugs. Finally, we discuss the application of covalent peptide drugs and expect to provide a new reference for cancer treatment.

Extracellular vesicle-encapsulated microRNA-296-3p from cancer-associated fibroblasts promotes ovarian cancer development through regulation of the PTEN/AKT and SOCS6/STAT3 pathways.

Cancer-associated fibroblasts (CAFs), as important components of the tumor microenvironment, can regulate intercellular communication and tumor development by secreting extracellular vesicles (EVs). However, the role of CAF-derived EVs in ovarian cancer has not been fully elucidated. Here, using an EV-microRNA sequencing analysis, we reveal specific overexpression of microRNA (miR)-296-3p in activated CAF-derived EVs, which can be transferred to tumor cells to regulate the malignant phenotypes of ovarian cancer cells. Moreover, overexpression of miR-296-3p significantly promotes the proliferation, migration, invasion, and drug resistance of ovarian cancer cells in vitro, as well as tumor growth in vivo, while its inhibition has the opposite effects. Further mechanistic studies reveal that miR-296-3p promotes ovarian cancer progression by directly targeting PTEN and SOCS6 and activating AKT and STAT3 signaling pathways. Importantly, increased expression of miR-296-3p encapsulated in plasma EVs is closely correlated with tumorigenesis and chemoresistance in patients with ovarian cancer. Our results highlight the cancer-promoting role of CAF-derived EVs carrying miR-296-3p in ovarian cancer progression for the first time, and suggest that miR-296-3p encapsulated in CAF-derived EVs could be a diagnostic biomarker and therapeutic target for ovarian cancer.