TGF-ß1 and FOXM1 siRNA co-loaded nanoparticles by disulfide crosslinked PEG-PDMAEMA for the treatment of triple-negative breast cancer and its bone metastases in vitro.

INTRODUCTION: Triple-negative breast cancer (TNBC) is characterized by higher malignancy and mortality and is prone to distant metastasis, among which bone is the most common site. It's urgent to explore new strategies for the treatment of TNBC and its bone metastases. METHODS: A tumor environment responsive vector, poly-(dimethylaminoethyl methacrylate)-SS-poly(ethylene glycol)-SS-poly-(dimethylaminoethyl methacrylate) (PDMAEMA-SS-PEG-SS-PDMAEMA), was constructed to co-delivery transforming growth factor-ß1 (TGF-ß1) siRNA and forkhead box M1 (FOXM1) siRNA in MDA-MB-231 cells. The preparation, characterization, in vitro release, stability, and transfection efficiency of nanoparticles were measured. Cell viability, migration, and invasion of MDA-MB-231 cells were determined. Cell chemotactic migration and cell heterogeneity adhesion of MDA-MB-231 cells to the human osteoblast-like cell line MG-63 were determined. RESULTS: PDMAEMA-SS-PEG-SS-PDMAEMA self-assembled with siRNA at N/P of 15:1 into nanoparticles with a particle size of 122 nm. In vitro release exhibited redox and pH sensitivity, and the nanoparticles protected siRNA from degradation by RNase and serum protein, remaining stable at 4 °C with similar transfection efficiency with lipo2000. Nanoparticles co-loaded with TGF-ß1 siRNA and FOXM1 siRNA inhibited the cell viability, migration and invasion of MDA-MB-231 cells, as well as chemotactic migration and heterogeneous adhesion of MDA-MB-231 cells to MG-63 cells, showing a synergetic effect. After gene silencing on TGF-ß1 and FOXM1, the epithelial to mesenchymal transition (EMT) related molecules vimentin mRNA expression decreased while E-cadherin increased. CONCLUSIONS: PDMAEMA-SS-PEG-SS-PDMAEMA was suitable for TGF-ß1 siRNA and FOXM1 siRNA delivery, exhibiting a synergetic inhibition effect on TNBC and its bone metastases, which might be related to its synergetic inhibition on EMT.

Aspects of Nickel, Cobalt and Lithium, the Three Key Elements for Li-Ion Batteries: An Overview on Resources, Demands, and Production.

With the booming of renewable clean energies towards reducing carbon emission, demands for lithium-ion batteries (LIBs) in applications to transportation vehicles and power stations are increasing exponentially. As a consequence, great pressures have been posed on the technological development and production of valuable elements key to LIBs, in addition to concerns about depletion of natural resources, environmental impacts, and management of waste batteries. In this paper, we compile recent information on lithium, nickel, and cobalt, the three most crucial elements utilized in LIBs, in terms of demands, current identified terrestrial resources, extraction technologies from primary natural resources and waste. Most nickel and cobalt are currently produced from high-grade sulfide ores via a pyrometallurgical approach. Increased demands have stimulated production of Ni and Co from low-grade laterites, which is commonly performed through the hydrometallurgical process. Most lithium exists in brines and is extracted via evaporation-precipitation in common industrial practice. It is noteworthy that at present, the pyrometallurgical process is energy-intensive and polluting in terms of gas emissions. Hydrometallurgical processes utilize large amounts of alkaline or acidic media in combination with reducing agents, generating hazardous waste streams. Traditional evaporation-precipitation consumes time, water, and land. Extraction of these elements from deep seas and recycling from waste are emerging as technologies. Advanced energy-saving and environmentally friendly processes are under extensive research and development and are crucial in the process of renewable clean energy implementation.

Transformer-based AI technology improves early ovarian cancer diagnosis using cfDNA methylation markers.

Epithelial ovarian cancer (EOC) is the deadliest women's cancer and has a poor prognosis. Early detection is the key for improving survival (a 5-year survival rate in stage I/II is over 70% compared to that of 25% in stage III/IV) and can be achieved through methylation markers from circulating cell-free DNA (cfDNA) using a liquid biopsy. In this study, we first identify top 500 EOC markers differentiating EOC from healthy female controls from 3.3 million methylome-wide CpG sites and validated them in 1,800 independent cfDNA samples. We then utilize a pretrained AI transformer system called MethylBERT to develop an EOC diagnostic model which achieves 80% sensitivity and 95% specificity in early-stage EOC diagnosis. We next develop a simple digital droplet PCR (ddPCR) assay which archives good performance, facilitating early EOC detection.

Development and validation of prognostic signatures of NAD+ metabolism and immune-related genes in colorectal cancer.

Background: Colorectal cancer (CRC) is a prevalent cause of death from malignant tumors. This study aimed to develop a nicotinamide adenine dinucleotide (NAD+) metabolism and immune-related prognostic signature, providing a theoretical foundation for prognosis and therapy in CRC patients. Methods: NAD + metabolism-related and immune-related subtypes of CRC patients were identified by consistent clustering. Differentially expressed genes (DEGs) between the two subtypes of CRC were identified by overlapping. A risk signature was constructed using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Independent prognostic predictors were authenticated by Cox analysis. Gene set variation analysis (GSVA) and single-sample gene set enrichment analysis (ssGSEA) were applied to investigate the connection between the prognostic signature and the immune microenvironment. Chemotherapy drug sensitivity and immunotherapy responsiveness were projected using the 'pRRophetic' package and Tumor Immune Dysfunction and Exclusion (TIDE) website. The Human Protein Atlas (HPA) database was used to assess the protein expression of prognostic genes in CRC and normal tissues. Results: Using bioinformatics methods, three prognostic genes related to immune-related NAD + metabolism were identified, and the results were used to establish and verify a prognostic signature related to immune-related NAD + metabolism in CRC patients. Cox regression analysis confirmed that the risk score was a reliable independent prognostic predictor. GSVA and ssGSEA indicated that the prognostic signature was associated with the immune microenvironment. TIDE analysis suggested that the signature might act as an immunotherapy predictor. Chemotherapy sensitivity analysis revealed that COMP was correlated with chemotherapy sensitivity in CRC patients and might be a potential therapeutic target. Conclusion: This study identified NAD + metabolism-immune-related prognostic genes (MOGAT2, COMP, and DNASE1L3) and developed a prognostic signature for CRC prognosis, which is significant for clinical prognosis prediction and treatment strategy decisions for CRC patients.

Development and Validation of a Carbohydrate Metabolism-Related Model for Predicting Prognosis and Immune Landscape in Hepatocellular Carcinoma Patients.

OBJECTIVE: The activities and products of carbohydrate metabolism are involved in key processes of cancer. However, its relationship with hepatocellular carcinoma (HCC) is unclear. METHODS: The cancer genome atlas (TCGA)-HCC and ICGC-LIRI-JP datasets were acquired via public databases. Differentially expressed genes (DEGs) between HCC and control samples in the TCGA-HCC dataset were identified and overlapped with 355 carbohydrate metabolism-related genes (CRGs) to obtain differentially expressed CRGs (DE-CRGs). Then, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were applied to identify risk model genes, and HCC samples were divided into high/low-risk groups according to the median risk score. Next, gene set enrichment analysis (GSEA) was performed on the risk model genes. The sensitivity of the risk model to immunotherapy and chemotherapy was also explored. RESULTS: A total of 8 risk model genes, namely, G6PD, PFKFB4, ACAT1, ALDH2, ACYP1, OGDHL, ACADS, and TKTL1, were identified. Moreover, the risk score, cancer status, age, and pathologic T stage were strongly associated with the prognosis of HCC patients. Both the stromal score and immune score had significant negative/positive correlations with the risk score, reflecting the important role of the risk model in immunotherapy sensitivity. Furthermore, the stromal and immune scores had significant negative/positive correlations with risk scores, reflecting the important role of the risk model in immunotherapy sensitivity. Eventually, we found that high-/low-risk patients were more sensitive to 102 drugs, suggesting that the risk model exhibited sensitivity to chemotherapy drugs. The results of the experiments in HCC tissue samples validated the expression of the risk model genes. CONCLUSION: Through bioinformatic analysis, we constructed a carbohydrate metabolism-related risk model for HCC, contributing to the prognosis prediction and treatment of HCC patients.

Cross-Priming-Linked Hierarchical Isothermal Amplification Programming Progressive Activating Clustered Regularly Interspaced Short Palindromic Repeats/Cas12a in miRNA Signaling.

Cascade isothermal nucleic acid amplification, which integrates several different amplification protocols to enhance the assay performance, is widely utilized in biosensing, particularly for detecting microRNAs (miRNAs), crucial biomarkers associated with tumor initiation and progression. However, striking a balance between a high amplification efficiency and simplicity in design remains a challenge. Therefore, methods achieving high amplification efficiency without significantly increasing complexity are highly favored. In this study, we propose a novel approach for miRNA detection, employing cross-priming-linked hierarchical isothermal amplification (CP-HIA) to progressively activate the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a system. The CP-HIA method strategically combines nicking-rolling circle amplification (n-RCA) and palindrome-aided circular strand displacement amplification (p-CSDA) for miRNA detection. Remarkably, this method utilizes only two main probes. Its key innovation lies in the interactive cross-priming strategy, wherein the amplification product from n-RCA is recycled to further drive p-CSDA, and vice versa. This interactive process establishes a hierarchical amplification, significantly enriching the activation probes for progressive CRISPR/Cas12a activation and subsequent target signal amplification. Consequently, the method exhibits greatly enhanced analytical performance, including high sensitivity and specificity in detecting low concentrations of miRNA. As low as 1.06 fM miRNA can thus be quantitatively detected, and the linear response of the miRNA is from 10 fM to 10 nM. These features demonstrate its potential for early disease diagnosis and monitoring. We anticipate that the CP-HIA method will serve as a promising platform for developing advanced molecular diagnostic tools for biomedical research.

Ovarian stimulation response and fertility outcomes in patients with breast cancer across different stages, grades, and hormone receptor status for fertility preservation.

BACKGROUND: This study aimed to explore the potential impact of stage, grade, and hormone receptor profile on ovarian stimulation response and fertility preservation outcomes. METHODS: This retrospective cohort study evaluated data from breast cancer patients who underwent fertility preservation at a tertiary medical center between 2014 and 2022. The outcomes of women with low-stage cancer (stages I and II) were compared with those of women with high-stage disease (stages III and IV or lymph node metastasis). Similarly, we compared those with low-grade (grades 1 and 2) and high-grade (grade 3) malignancies. In addition, we compared different hormone statuses of breast cancer (1) estrogen receptor (ER) positive vs. ER-negative and (2) triple-negative breast cancer (TNBC) vs. non-TNBC. The primary outcome measured was the number of mature oocytes, while the secondary outcomes included the numbers of total oocytes retrieved, peak estradiol levels, and subsequent fertility preservation outcomes. RESULTS: A total of 47 patients were included. Patients with high-grade tumors had a comparable number of mature oocytes (8 vs. 10, p = 0.08) compared to patients with low grade cancers. The stage-based analysis revealed a similar number of mature oocytes (8 vs. 10, p = 0.33) between high/low stage patients. In the hormone receptor-based analysis, no differences were seen in mature oocytes collected between the ER-positive/ER-negative group (9 vs. 9, p = 0.87) and the TNBC/non-TNBC group (11 vs. 9, p = 0.13). The utilization rate was 27.6% (13/47). CONCLUSION: Our study showed similar ovarian stimulation response and fertility preservation outcomes among breast cancer patients with different prognostic factors.

Hyperhomocysteine promotes cataract development through mTOR-mediated inhibition of autophagy and connexins expression.

AIM: Hyperhomocysteine has been recognized as an independent risk factor of multiple diseases, including several eye diseases. In this study, we aim to investigate whether increased homocysteine (Hcy) is related to cataracts, and to explore whether dysregulation of mTOR-mediated autophagy and connexin expression are underlying mechanisms. METHOD: We first developed a method of liquid chromatography tandem mass spectrometry to accurately measure serum concentrations of Hcy in 287 cataract patients and 334 healthy controls. Next, we treated human lens epithelial (HLC-B3) cells with Hcy at different concentrations and durations, and then analyzed expression of autophagy-related markers and connexins, as well as phosphorylated mTOR (p-mTOR) in these cells by Western blotting. Formation of autophagic vacuoles and intracellular Ca2+ in the Hcy-treated cells were observed by fluorescence microscopy. Further, we performed a rescue experiment in the Hcy-treated HLC-B3 cells by pre-incubation with rapamycin, an mTOR inhibitor. RESULTS: The serum levels of Hcy in patients with cataracts were significantly increased compared to those in healthy controls. In cultured HLC-B3 cells, expression of autophagy related markers (LC3B and Beclin1) and connexins (Cx43 and Cx50) was inhibited by Hcy treatment in a dose- and duration-dependent manner. Accumulation of Ca2+ in the Hcy-treated lens epithelial cells was observed as a consequence of reduced connexin expression. Meanwhile, expression of p-mTOR increased, representing up-regulation of the mTOR pathway. Importantly, inhibition of autophagy and connexin expression due to hyperhomocysteine was rescued via mTOR suppression by pretreatment with rapamycin in HLC-B3 cells. CONCLUSION: Our results demonstrate that hyperhomocysteine might promote cataract development through two mTOR-mediated pathways in the lens epithelial cells: 1) dysregulation of autophagy and 2) accumulation of intracellular calcium via decreased connexin expression.

Treatment of Parkinson's disease model with human umbilical cord mesenchymal stem cell-derived exosomes loaded with BDNF.

AIMS: Parkinson's disease (PD) is a common neurodegenerative disease that has received widespread attention; however, current clinical treatments can only relieve its symptoms, and do not effectively protect dopaminergic neurons. The purpose of the present study was to investigate the therapeutic effects of human umbilical cord mesenchymal stem cell-derived exosomes loaded with brain-derived neurotrophic factor (BDNF-EXO) on PD models and to explore the underlying mechanisms of these effects. MAIN METHODS: 6-Hydroxydopamine was used to establish in vivo and in vitro PD models. Western blotting, flow cytometry, and immunofluorescence were used to detect the effects of BDNF-EXO on apoptosis and ferroptosis in SH-SY5Y cells. The in vivo biological distribution of BDNF-EXO was detected using a small animal imaging system, and dopaminergic neuron improvements in brain tissue were detected using western blotting, immunofluorescence, immunohistochemistry, and Nissl and Prussian blue staining. KEY FINDINGS: BDNF-EXO effectively suppressed 6-hydroxydopamine-induced apoptosis and ferroptosis in SH-SY5Y cells. Following intravenous administration, BDNF-EXO crossed the blood-brain barrier to reach afflicted brain regions in mice, leading to a notable enhancement in neuronal survival. Furthermore, BDNF-EXO modulated microtubule-associated protein 2 and phosphorylated tau expression, thereby promoting neuronal cytoskeletal stability. Additionally, BDNF-EXO bolstered cellular antioxidant defense mechanisms through the activation of the nuclear factor erythroid 2-related factor 2 signaling pathway, thereby conferring neuroprotection against damage. SIGNIFICANCE: The novel drug delivery system, BDNF-EXO, had substantial therapeutic effects in both in vivo and in vitro PD models, and may represent a new treatment strategy for PD.

SIRT3 sulfhydration using hydrogen sulfide inhibited angiotensin II-induced atrial fibrosis and vulnerability to atrial fibrillation via suppression of the TGF-ß1/smad2/3 signalling pathway.

Atrial fibrosis is associated with the occurrence of atrial fibrillation (AF) and regulated by the transforming growth factor-ß1 (TGF-ß1)/Smad2/3 signalling pathway. Unfortunately, the mechanisms of regulation of TGF-ß1/Smad2/3-induced atrial fibrosis and vulnerability to AF remain still unknown. Previous studies have shown that sirtuin3 (SIRT3) sulfhydration has strong anti-fibrotic effects. We hypothesised that SIRT3 sulfhydration inhibits angiotensin II (Ang-II)-induced atrial fibrosis via blocking the TGF-ß1/Smad2/3 signalling pathway. In this study, we found that SIRT3 expression was decreased in the left atrium of patients with AF compared to that in those with sinus rhythm (SR). In vitro, SIRT3 knockdown by small interfering RNA significantly expanded Ang-II-induced atrial fibrosis and TGF-ß1/Smad2/3 signalling pathway activation, whereas supplementation with Sodium Hydrosulfide (NaHS, exogenous hydrogen sulfide donor and sulfhydration agonist) and SIRT3 overexpression using adenovirus ameliorated Ang-II-induced atrial fibrosis. Moreover, we observed suppression of the TGF-ß1/Smad2/3 pathway when Ang-II was combined with NaHS treatment, and the effect of this co-treatment was consistent with that of Ang-II combined with LY3200882 (Smad pathway inhibitor) on reducing atrial fibroblast proliferation and cell migration in vitro. Supplementation with dithiothreitol (DTT, a sulfhydration inhibitor) and adenovirus SIRT3 shRNA blocked the ameliorating effect of NaHS and AngII co-treatment on atrial fibrosis in vitro. Finally, continued treatment with NaHS in rats ameliorated atrial fibrosis and remodelling, and further improved AF vulnerability induced by Ang-II, which was reversed by DTT and adenovirus SIRT3 shRNA, suggesting that SIRT3 sulfhydration might be a potential therapeutic target in atrial fibrosis and AF.

IMPDH2 suppression impedes cell proliferation by instigating cell cycle arrest and stimulates apoptosis in pediatric hepatoblastoma.

BACKGROUND: Hepatoblastoma (HB) is the most common pediatric liver tumor, presenting significant therapeutic challenges due to its high rates of recurrence and metastasis. While Inosine Monophosphate Dehydrogenase 2(IMPDH2) has been associated with cancer progression, its specific role and clinical implications in HB have not been fully elucidated. METHODS: This study utilized Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and Tissue Microarray (TMA) for validation. Following this, IMPDH2 was suppressed, and a series of in vitro assays were conducted. Flow cytometry was employed to assess apoptosis and cell cycle arrest. Additionally, the study explored the synergistic therapeutic effects of mycophenolate mofetil (MMF) and doxorubicin (DOX) on HB cell lines. RESULTS: The study identified a marked overexpression of IMPDH2 in HB tissues, which was strongly correlated with reduced Overall Survival (OS) and Event-Free Survival (EFS). IMPDH2 upregulation was also found to be associated with key clinical-pathological features, including pre-chemotherapy alpha-fetoprotein (AFP) levels, presence of preoperative metastasis, and the pre-treatment extent of tumor (PRETEXT) staging system. Knockdown of IMPDH2 significantly inhibited HB cell proliferation and tumorigenicity, inducing cell cycle arrest at the G0/G1 phase. Notably, the combination of MMF, identified as a specific IMPDH2 inhibitor, with DOX, substantially enhanced the therapeutic response. CONCLUSION: The overexpression of IMPDH2 was closely linked to adverse outcomes in HB patients and appeared to accelerate cell cycle progression. These findings suggest that IMPDH2 may serve as a valuable prognostic indicator and a potential therapeutic target for HB. IMPACT: The present study unveiled a significant overexpression of inosine monophosphate dehydrogenase 2 (IMPDH2) in hepatoblastoma (HB) tissues, particularly in association with metastasis and recurrence of the disease. The pronounced upregulation of IMPDH2 was found to be intimately correlated with adverse outcomes in HB patients. This overexpression appears to accelerate the progression of the cell cycle, suggesting that IMPDH2 may serve as a promising candidate for both a prognostic marker and a therapeutic target in the context of HB.

A Novel Amino Acid-Related Gene Signature Predicts Overall Survival in Patients With Hepatocellular Carcinoma.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is an extremely harmful malignant tumor in the world. Since the energy metabolism and biosynthesis of HCC cells are closely related to amino acids, it is necessary to further explore the relationship between amino acid-related genes and the prognosis of HCC to achieve individualized treatment. We herein aimed to develop a prognostic model for HCC based on amino acid genes. METHODS: In this study, RNA-sequencing data of HCC patients were downloaded from the TCGA-LIHC cohort as the training cohort and the GSE14520 cohort as the validation cohort. Amino acid-related genes were derived from the Molecular Signatures Database. Univariate Cox and Lasso regression analysis were used to construct an amino acid-related signature (AARS). The predictive value of this risk score was evaluated by Kaplan-Meier (K-M) curve, receiver operating characteristic (ROC) curve, univariate and multivariate Cox regression analysis. Gene set variation analysis (GSVA) and immune characteristics evaluation were used to explore the underlying mechanisms. Finally, a nomogram was established to help the personalized prognosis assessment of patients with HCC. RESULTS: The AARS comprises 14 amino acid-related genes to predict overall survival (OS) in HCC patients. HCC patients were divided into AARS-high group and AARS-low group according to the AARS scores. The K-M curve, ROC curve, and univariate and multivariate Cox regression analysis verified the good prediction efficiency of the risk score. Using GSVA, we found that AARS variants were concentrated in four pathways, including cholesterol metabolism, delayed estrogen response, fatty acid metabolism, and myogenesis metabolism. CONCLUSION: Our results suggest that the AARS as a prognostic model based on amino acid-related genes is of great value in the prediction of survival of HCC, and can help improve the individualized treatment of patients with HCC.

Bioinformatics analysis of an immunotherapy responsiveness-related gene signature in predicting lung adenocarcinoma prognosis.

Background: Immune therapy has become first-line treatment option for patients with lung cancer, but some patients respond poorly to immune therapy, especially among patients with lung adenocarcinoma (LUAD). Novel tools are needed to screen potential responders to immune therapy in LUAD patients, to better predict the prognosis and guide clinical decision-making. Although many efforts have been made to predict the responsiveness of LUAD patients, the results were limited. During the era of immunotherapy, this study attempts to construct a novel prognostic model for LUAD by utilizing differentially expressed genes (DEGs) among patients with differential immune therapy responses. Methods: Transcriptome data of 598 patients with LUAD were downloaded from The Cancer Genome Atlas (TCGA) database, which included 539 tumor samples and 59 normal control samples, with a mean follow-up time of 29.69 months (63.1% of patients remained alive by the end of follow-up). Other data sources including three datasets from the Gene Expression Omnibus (GEO) database were analyzed, and the DEGs between immunotherapy responders and nonresponders were identified and screened. Univariate Cox regression analysis was applied with the TCGA cohort as the training set and GSE72094 cohort as the validation set, and least absolute shrinkage and selection operator (LASSO) Cox regression were applied in the prognostic-related genes which fulfilled the filter criteria to establish a prognostic formula, which was then tested with time-dependent receiver operating characteristic (ROC) analysis. Enriched pathways of the prognostic-related genes were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and tumor immune microenvironment (TIME), tumor mutational burden, and drug sensitivity tests were completed with appropriate packages in R (The R Foundation of Statistical Computing). Finally, a nomogram incorporating the prognostic formula was established. Results: A total of 1,636 DEGs were identified, 1,163 prognostic-related DEGs were extracted, and 34 DEGs were selected and incorporated into the immunotherapy responsiveness-related risk score (IRRS) formula. The IRRS formula had good performance in predicting the overall prognoses in patients with LUAD and had excellent performance in prognosis prediction in all LUAD subgroups. Moreover, the IRRS formula could predict anticancer drug sensitivity and immunotherapy responsiveness in patients with LUAD. Mechanistically, immune microenvironments varied profoundly between the two IRRS groups; the most significantly varied pathway between the high-IRRS and low-IRRS groups was ribonucleoprotein complex biogenesis, which correlated closely with the TP53 and TTN mutation burdens. In addition, we established a nomogram incorporating the IRRS, age, sex, clinical stage, T-stage, N-stage, and M-stage as predictors that could predict the prognoses of 1-year, 3-year, and 5-year survival in patients with LUAD, with an area under curve (AUC) of 0.718, 0.702, and 0.68, respectively. Conclusions: The model we established in the present study could predict the prognosis of LUAD patients, help to identify patients with good responses to anticancer drugs and immunotherapy, and serve as a valuable tool to guide clinical decision-making.

What enlightenment has the development of lung cancer bone metastasis brought in the last 22 years.

BACKGROUND: Lung cancer bone metastasis (LCBM) is a disease with a poor prognosis, high risk and large patient population. Although considerable scientific output has accumulated on LCBM, problems have emerged, such as confusing research structures. AIM: To organize the research frontiers and body of knowledge of the studies on LCBM from the last 22 years according to their basic research and translation, clinical treatment, and clinical diagnosis to provide a reference for the development of new LCBM clinical and basic research. METHODS: We used tools, including R, VOSviewer and CiteSpace software, to measure and visualize the keywords and other metrics of 1903 articles from the Web of Science Core Collection. We also performed enrichment and protein-protein interaction analyses of gene expression datasets from LCBM cases worldwide. RESULTS: Research on LCBM has received extensive attention from scholars worldwide over the last 20 years. Targeted therapies and immunotherapies have evolved into the mainstream basic and clinical research directions. The basic aspects of drug resistance mechanisms and parathyroid hormone-related protein may provide new ideas for mechanistic study and improvements in LCBM prognosis. The produced molecular map showed that ribosomes and focal adhesion are possible pathways that promote LCBM occurrence. CONCLUSION: Novel therapies for LCBM face animal testing and drug resistance issues. Future focus should centre on advancing clinical therapies and researching drug resistance mechanisms and ribosome-related pathways.

AI-Based multimodal Multi-tasks analysis reveals tumor molecular heterogeneity, predicts preoperative lymph node metastasis and prognosis in papillary thyroid carcinoma: A retrospective study.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the predominant form of thyroid cancer globally, especially when lymph node metastasis (LNM) occurs. Molecular heterogeneity, driven by genetic alterations and tumor microenvironment components, contributes to the complexity of PTC. Understanding these complexities is essential for precise risk stratification and therapeutic decisions. METHODS: This study involved a comprehensive analysis of 521 patients with PTC from our hospital and 499 patients from The Cancer Genome Atlas (TCGA). The real-world cohort 1 comprised 256 patients with stage I-III PTC. Tissues from 252 patients were analyzed by DNA-based next-generation sequencing, and tissues from four patients were analyzed by single-cell RNA sequencing (scRNA-seq). Additionally, 586 PTC pathological sections were collected from TCGA, and 275 PTC pathological sections were collected from the real-world cohort 2. A deep learning multimodal model was developed using matched histopathology images, genomic, transcriptomic, and immune cell data to predict LNM and disease-free survival (DFS). RESULTS: This study included a total of 1,011 PTC patients, comprising 256 patients from cohort 1, 275 patients from cohort 2, and 499 patients from TCGA. In cohort 1, we categorized PTC into four molecular subtypes based on BRAF, RAS, RET, and other mutations. BRAF mutations were significantly associated with LNM and impacted DFS. ScRNA-seq identified distinct T cell subtypes and reduced B cell diversity in BRAF-mutated PTC with LNM. The study also explored cancer-associated fibroblasts and macrophages, highlighting their associations with LNM. The deep learning model was trained using 405 pathology slides and RNA sequences from 328 PTC patients and validated with 181 slides and RNA sequences from 140 PTC patients in the TCGA cohort. It achieved high accuracy, with an AUC of 0.86 in the training cohort, 0.84 in the validation cohort, and 0.83 in the real-world cohort 2. High-risk patients in the training cohort had significantly lower DFS rates (P<0.001). Model AUCs were 0.91 at 1 year, 0.93 at 3 years, and 0.87 at 5 years. In the validation cohort, high-risk patients also had lower DFS (P<0.001); the AUCs were 0.89, 0.87, and 0.80 at 1, 3, and 5 years. We utilized the GradCAM algorithm to generate heatmaps from pathology-based deep learning models, which visually highlighted high-risk tumor areas in PTC patients. This enhanced clinicians' understanding of the model's predictions and improved diagnostic accuracy, especially in cases with lymph node metastasis. CONCLUSION: The AI-based analysis uncovered vital insights into PTC molecular heterogeneity, emphasizing BRAF mutations' impact. The integrated deep learning model shows promise in predicting metastasis, offering valuable contributions to improved diagnostic and therapeutic strategies.

Biocontrol potential of plant growth-promoting rhizobacteria against plant disease and insect pest.

Biological control is a promising approach to enhance pathogen and pest control to ensure high productivity in cash crop production. Therefore, PGPR biofertilizers are very suitable for application in the cultivation of tea plants (Camellia sinensis) and tobacco, but it is rarely reported so far. In this study, production of a consortium of three strains of PGPR were applied to tobacco and tea plants. The results demonstrated that plants treated with PGPR exhibited enhanced resistance against the bacterial pathogen Pseudomonas syringae (PstDC3000). The significant effect in improving the plant's ability to resist pathogen invasion was verified through measurements of oxygen activity, bacterial colony counts, and expression levels of resistance-related genes (NPR1, PR1, JAZ1, POD etc.). Moreover, the application of PGPR in the tea plantation showed significantly reduced population occurrences of tea green leafhoppers (Empoasca onukii Matsuda), tea thrips (Thysanoptera:Thripidae), Aleurocanthus spiniferus (Quaintanca) and alleviated anthracnose disease in tea seedlings. Therefore, PGPR biofertilizers may serve as a viable biological control method to improve tobacco and tea plant yield and quality. Our findings revealed part of the mechanism by which PGPR helped improve plant biostresses resistance, enabling better application in agricultural production.

Identification of a novel prognostic signature based on vitamin metabolism clustering-related genes in lung adenocarcinoma.

Background: Vitamins, and their metabolic processes play essential regulatory roles in controlling proliferation, differentiation, and growth in carcinogenesis. However, the role of vitamin metabolism in lung adenocarcinoma (LUAD) has rarely been reported. Here, we established a novel prognostic model based on vitamin metabolism-related genes in LUAD. Methods: In this research, we aimed to identify vitamin metabolism associated with differentially expressed genes (DEGs) in LUAD utilizing The Cancer Genome Atlas (TCGA)-LUAD, GSE68465 and GSE72094 data. Unsupervised clustering classified patients into distinct subgroups. By utilizing least absolute shrinkage and selection operator (LASSO)-Cox regression analysis, vitamin metabolism-related genes could be used to construct prognostic model. Then the vitamin metabolism gene-related risk score (VRS) was calculated based on best cut-off splitting. Kaplan-Meier analysis, time-dependent receiver operating characteristic (ROC) analysis, univariate and multivariate Cox analyses, chemotherapeutic drugs sensitivity analysis, immune infiltration analysis and nomogram were conducted to verify our models' accuracy. Finally, CPS1 was identified as a relevant diagnostic marker using Random Forests algorithms, single-cell RNA sequencing data was used to confirm its expression. Results: We investigated the relationship between vitamin metabolism patterns, overall survival (OS), and immune infiltration levels of patients with LUAD. A prognostic signature consisting of 11 genes was developed, which was able to classify patients into high and low VRS groups. Through gene enrichment analysis, cell cycle was mainly enriched. Compared to the low VRS group, the high VRS group exhibited poorer OS, as demonstrated by the Kaplan-Meier survival analysis. Furthermore, VRS was identified as an independent predictor of poor prognosis and poor OS, as indicated by both univariate and multivariate Cox regression analyses. Additionally, a nomogram was constructed to improve the accuracy of survival predictions in LUAD patients. We also found that the two groups of patients might respond differently to immune targets and anti-tumor drugs. CPS1 was identified as a relevant diagnostic marker and the expression was also as confirmed by single-cell RNA sequencing data. Conclusions: Overall, our findings suggest that vitamin metabolism can influence the prognosis of LUAD patients, and our prognostic signature represents a potentially helpful resource for predicting patient outcomes and informing clinical decision-making.

Hsa_circ_0096157 silencing suppresses autophagy and reduces cisplatin resistance in non-small cell lung cancer by weakening the Nrf2/ARE signaling pathway.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of cancer morbidity and mortality worldwide, and new diagnostic markers are urgently needed. We aimed to investigate the mechanism by which hsa_circ_0096157 regulates autophagy and cisplatin (DDP) resistance in NSCLC. METHODS: A549 cells were treated with DDP (0 µg/mL or 3 µg/mL). Then, the autophagy activator rapamycin (200 nm) was applied to the A549/DDP cells. Moreover, hsa_circ_0096157 and Nrf2 were knocked down, and Nrf2 was overexpressed in A549/DDP cells. The expression of Hsa_circ_0096157, the Nrf2/ARE pathway-related factors Nrf2, HO-1, and NQO1, and the autophagy-related factors LC3, Beclin-1, and p62 was evaluated by qRT‒PCR or western blotting. Autophagosomes were detected through TEM. An MTS assay was utilized to measure cell proliferation. The associated miRNA levels were also tested by qRT‒PCR. RESULTS: DDP (3 µg/mL) promoted hsa_circ_0096157, LC3 II/I, and Beclin-1 expression and decreased p62 expression. Knocking down hsa_circ_0096157 resulted in the downregulation of LC3 II/I and Beclin-1 expression, upregulation of p62 expression, and decreased proliferation. Rapamycin reversed the effect of interfering with hsa_circ_0096157. Keap1 expression was lower, and Nrf2, HO-1, and NQO1 expression was greater in the A549/DDP group than in the A549 group. HO-1 expression was repressed after Nrf2 interference. In addition, activation of the Nrf2/ARE pathway promoted autophagy in A549/DDP cells. Moreover, hsa_circ_0096157 activated the Nrf2/ARE pathway. The silencing of hsa_circ_0096157 reduced Nrf2 expression by releasing miR-142-5p or miR-548n. Finally, we found that hsa_circ_0096157 promoted A549/DDP cell autophagy by activating the Nrf2/ARE pathway. CONCLUSION: Knockdown of hsa_circ_0096157 inhibits autophagy and DDP resistance in NSCLC cells by downregulating the Nrf2/ARE signaling pathway.