MOICS, a novel classier deciphering immune heterogeneity and aid precise management of clear cell renal cell carcinoma at multiomics level

Recent studies have indicated that the tumor immune microenvironment plays a pivotal role in the initiation and progression of clear cell renal cell carcinoma (ccRCC). However, the characteristics and heterogeneity of tumor immunity in ccRCC, particularly at the multiomics level, remain poorly understood. We analyzed immune multiomics datasets to perform a consensus cluster analysis and validate the clustering results across multiple internal and external ccRCC datasets; and identified two distinctive immune phenotypes of ccRCC, which we named multiomics immune-based cancer subtype 1 (MOICS1) and subtype 2 (MOICS2). The former, MOICS1, is characterized by an immune-hot phenotype with poor clinical outcomes, marked by significant proliferation of CD4+ and CD8+ T cells, fibroblasts, and high levels of immune inhibitory signatures; the latter, MOICS2, exhibits an immune-cold phenotype with favorable clinical characteristics, characterized by robust immune activity and high infiltration of endothelial cells and immune stimulatory signatures. Besides, a significant negative correlation between immune infiltration and angiogenesis were identified. We further explored the mechanisms underlying these differences, revealing that negatively regulated endopeptidase activity, activated cornification, and neutrophil degranulation may promote an immune-deficient phenotype, whereas enhanced monocyte recruitment could ameliorate this deficiency. Additionally, significant differences were observed in the genomic landscapes between the subtypes: MOICS1 exhibited mutations in TTN, BAP1, SETD2, MTOR, MUC16, CSMD3, and AKAP9, while MOICS2 was characterized by notable alterations in the TGF-β pathway. Overall, our work demonstrates that multi-immune omics remodeling analysis enhances the understanding of the immune heterogeneity in ccRCC and supports precise patient management.

Burden of Stroke Attributable to Nonoptimal Temperature in 204 Countries and Territories: A Population-Based Study, 1990-2019

BACKGROUND AND OBJECTIVES

Stroke attributable to nonoptimal temperature needs more attention with dramatic climate change. The aim of this study was to estimate the global burden and distribution characteristics of the burden.

METHODS

In this ecological study, we collected data from the Climate Research Unit Gridded Time Series, the World Bank databases, and the Global Burden of Diseases study to estimate the distribution of burden. We used the joinpoint model, decomposition analysis, age-period-cohort model, panel data analysis, and health inequality analysis to assess the different types of stroke burden attributable to different climatic conditions.

RESULTS

The burden of stroke attributable to nonoptimal temperature continued to grow, and aging was a key factor in this increase. In 2019, 521,031 (95% uncertainty interval [UI] 402,433-663,996) deaths and 9,423,649 (95% UI 7,207,660-12,055,172) disability-adjusted life years [DALYs] attributable to stroke due to nonoptimal temperature were recorded globally. Globally, men (age-standardized mortality rate [ASMR] 7.70, 95% UI 5.80-9.73; age-standardized DALY rate [ASDR] 139.69, 95% UI 102.96-178.54 in 2019) had a heavier burden than women (ASMR 5.89, 95% UI 4.50-7.60; ASDR 96.02, 95% UI 72.62-123.85 in 2019). Central Asia (ASMR 18.12, 95% UI 13.40-24.53; ASDR 327.35, 95% UI 240.24-440.61 in 2019) had the heaviest burden at the regional level. In the national level, North Macedonia (ASMR 32.97, 95% UI 20.57-47.44 in 2019) and Mongolia (ASDR 568.54, 95% UI 242.03-1,031.14 in 2019) had the highest ASMR/ASDR, respectively. Low temperature currently contributes to the main burden (deaths 474,002, 95% UI 355,077-606,537; DALYs 8,357,198, 95% UI 6,186,217-10,801,911 attributable to low temperature vs deaths 48,030, 95% UI 5,630-104,370; DALYs 1,089,329, 95% UI 112,690-2,375,345 attributable to high temperature in 2019). However, the burden due to high temperature has increased rapidly, especially among people aged older than 10 years, and was disproportionately concentrated in low sociodemographic index (SDI) regions such as Africa. In addition, the rapid increase in the stroke burden due to high temperature in Central Asia also requires special attention.

DISCUSSION

This is the first study to assess the global stroke burden attributed to nonoptimal temperature. The dramatic increase in the burden due to high temperature requires special attention, especially in low-SDI countries.

Excitation functions for fast neutron induced reactions on iron and lead

Cross sections of the 54Fe(n,p)54Mn, 54Fe(n,α)51Cr, 56Fe(n,p)56Mn and 204Pb (n,2n)203Pb reactions induced by D-T neutrons were obtained with activation method and γ-ray spectrometry technique. Experimental values measured in this work are consistent with most of the previous literature data. These reactions cross sections were theoretically calculated by using the TALYS-1.96 and EMPIRE-3.2.3 codes from threshold up to 20 MeV, and significant discrepancies were found between calculated results and experiment data. In addition, experimental values are compared with evaluated nuclear data of the CENDL-3.2, ENDF/B-VIII.0, JENDL-5, BROND-3.1 and JEFF-3.3 libraries, and significant difference was found for the 54Fe(n,α)51Cr reaction in ENDF/B-VIII.0 library but not for other reactions.

PGR-KITLG signaling drives a tumor-mast cell regulatory feedback to modulate apoptosis of breast cancer cells

The immune microenvironment constructed by tumor-infiltrating immune cells and the molecular phenotype defined by hormone receptors (HRs) have been implicated as decisive factors in the regulation of breast cancer (BC) progression. Here, we found that the infiltration of mast cells (MCs) informed impaired prognoses in HR(+) BC but predicted improved prognoses in HR(-) BC. However, molecular features of MCs in different BC remain unclear. We next discovered that HR(-) BC cells were prone to apoptosis under the stimulation of MCs, whereas HR(+) BC cells exerted anti-apoptotic effects. Mechanistically, in HR(+) BC, the KIT ligand (KITLG), a major mast cell growth factor in recruiting and activating MCs, could be transcriptionally upregulated by the progesterone receptor (PGR), and elevate the production of MC-derived granulin (GRN). GRN attenuates TNFα-induced apoptosis in BC cells by competitively binding to TNFR1. Furthermore, disruption of PGR-KITLG signaling by knocking down PGR or using the specific KITLG-cKIT inhibitor iSCK03 potently enhanced the sensitivity of HR(+) BC cells to MC-induced apoptosis and exerted anti-tumor activity. Collectively, these results demonstrate that PGR-KITLG signaling in BC cells preferentially induces GRN expression in MCs to exert anti-apoptotic effects, with potential value in developing precision medicine approaches for diagnosis and treatment.

Study on the mechanism of arsenic-induced renal injury based on SWATH proteomics technology

BACKGROUND

Arsenic (As) poisoning is a worldwide endemic disease affecting thousands of people. As is excreted mainly through the renal system, and arsenic has toxic effects on the kidneys, but the mechanism has not been elucidated. In this study, the molecular basis of arsenic's nephrotoxicity was studied by using a high-throughput proteomics technique.

METHODS

Eight SD (Sprague-Dawley) rats, half male and half female, were fed an As diet containing 50 mg/kg NaAsO2. Age- and sex-matched rats fed with regular chow were used as controls. At the end of the experiment (90 days), kidney tissue samples were collected and assessed for pathological changes using hematoxylin-eosin staining. Proteomic methods were used to identify alterations in protein expression levels in kidney tissues, and bioinformatic analyses of differentially expressed proteins between arsenic-treated and control groups were performed. The expression of some representative proteins was validated by Western blot analysis.

RESULTS

NaAsO2 could induce renal injury. Compared with the control group, 112 proteins were up-regulated, and 46 proteins were down-regulated in the arsenic-treated group. These proteins were associated with the electron transport chain, oxidative phosphorylation, mitochondrial membrane, apoptosis, and proximal tubules, suggesting that the mechanisms associated with them were related to arsenic-induced kidney injury and nephrotoxicity. The expressions of Atp6v1f, Cycs and Ndufs1 were verified, consistent with the results of omics.

CONCLUSION

These results provide important evidence for arsenic-induced kidney injury and provide new insights into the molecular mechanism of arsenic-induced kidney injury.

Integrated Exploration of Epigenetic Dysregulation Reveals a Stemness/EMT Subtype and MMP12 Linked to the Progression and Prognosis in Hepatocellular Carcinoma

Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.

A hyper-knowledge graph system for research on AI ethics cases

Current studies on the artificial intelligence (AI) ethics focus either on very broad guidelines or on a very special domain. Therefore, the research outcome can hardly be converted into actionable measures or transferred to other domains. Potential correlations between various cases of AI ethics at different granularity levels are unexplored. To overcome these deficiencies, the authors designed a case-oriented ontological model (COOM) and a hyper-knowledge graph system (HKGS) for the research of collected AI ethics cases. COOM describes criteria for modelling cases by attributes from three perspectives: event attributes, relational attributes, and positional attributes on the value chain. Based on it, HKGS stores the correlation between cases as knowledge and allows advanced visual analysis. The correlations between cases and their dynamic changes on value chain can be observed and explored. In HKGS's implementation part, one of the collected ethics cases is used as an example to demonstrate how to generate a hyper-knowledge graph and to visually analyze it. The authors also anticipated how different practitioners of AI ethics, can achieve the desired outputs from HKGS in their diverse scenarios.

FBL Promotes LPS-Induced Neuroinflammation by Activating the NF-κB Signaling Pathway

Purpose

Neuroinflammation occurs in response to central nervous system (CNS) injury, infection, stimulation by toxins, or autoimmunity. We previously analyzed the downstream molecular changes in HT22 cells (mouse hippocampal neurons) upon lipopolysaccharide (LPS) stimulation. We detected elevated expression of Fibrillarin (FBL), a nucleolar methyltransferase, but the associated proinflammatory mechanism was not systematically elucidated. The aim of this study was to investigate the underlying mechanisms by which FBL affects neuroinflammation.

Methods

RT-real-time PCR, Western blotting and immunofluorescence were used to assess the mRNA and protein expression of FBL in HT22 cells stimulated with LPS, as well as the cellular localization and fluorescence intensity of FBL. BAY-293 (a son of sevenless homolog 1 (SOS1) inhibitor), SR11302 (an activator protein-1 (AP-1) inhibitor) and KRA-533 (a KRAS agonist) were used to determine the molecular mechanisms underlying the effect of FBL. AP-1 was predicted to be the target protein of FBL by molecular docking analysis, and validation was performed with T-5224 (an AP-1 inhibitor). In addition, the downstream signaling pathways of FBL were identified by transcriptome sequencing and verified by RT-real-time PCR.

Results

LPS induced FBL mRNA and protein expression in HT22 cells. In-depth mechanistic studies revealed that when we inhibited c-Fos, AP-1, and SOS1, FBL expression decreased, whereas FBL expression increased when KRAS agonists were used. In addition, the transcript levels of inflammatory genes in the NF-kB signaling pathway (including CD14, MYD88, TNF, TRADD, and NFKB1) were elevated after the overexpression of FBL.

Conclusion

LPS induced the expression of FBL in HT22 cells through the RAS/MAPK signaling pathway, and FBL further activated the NF-kB signaling pathway, which promoted the expression of relevant inflammatory genes and the release of cytokines. The present study reveals the mechanism by which FBL promotes neuroinflammation and offers a potential target for the treatment of neuroinflammation.

Microdroplets Encapsulated with NFATc1-siRNA and Exosomes-Derived from MSCs Onto 3D Porous PLA Scaffold for Regulating Osteoclastogenesis and Promoting Osteogenesis

Introduction

Osteoporotic-related fractures remains a significant public health concern, thus imposing substantial burdens on our society. Excessive activation of osteoclastic activity is one of the main contributing factors for osteoporosis-related fractures. While polylactic acid (PLA) is frequently employed as a biodegradable scaffold in tissue engineering, it lacks sufficient biological activity. Microdroplets (MDs) have been explored as an ultrasound-responsive drug delivery method, and mesenchymal stem cell (MSC)-derived exosomes have shown therapeutic effects in diverse preclinical investigations. Thus, this study aimed to develop a novel bioactive hybrid PLA scaffold by integrating MDs-NFATc1-silencing siRNA to target osteoclast formation and MSCs-exosomes (MSC-Exo) to influence osteogenic differentiation (MDs-NFATc1/PLA-Exo).

Methods

Human bone marrow-derived mesenchymal stromal cells (hBMSCs) were used for exosome isolation. Transmission electron microscopy (TEM) and confocal laser scanning microscopy were used for exosome and MDs morphological characterization, respectively. The MDs-NFATc1/PLA-Exo scaffold was fabricated through poly(dopamine) and fibrin gel coating. Biocompatibility was assessed using RAW 264.7 macrophages and hBMSCs. Osteoclast formations were examined via TRAP staining. Osteogenic differentiation of hBMSCs and cytokine expression modulation were also investigated.

Results

MSC-Exo exhibited a cup-shaped structure and effective internalization into cells, while MDs displayed a spherical morphology with a well-defined core-shell structure. Following ultrasound stimulation, the internalization study demonstrated efficient delivery of bioactive MDs into recipient cells. Biocompatibility studies indicated no cytotoxicity of MDs-NFATc1/PLA-Exo scaffolds in RAW 264.7 macrophages and hBMSCs. Both MDs-NFATc1/PLA and MDs-NFATc1/PLA-Exo treatments significantly reduced osteoclast differentiation and formation. In addition, our results further indicated MDs-NFATc1/PLA-Exo scaffold significantly enhanced osteogenic differentiation of hBMSCs and modulated cytokine expression.

Discussion

These findings suggest that the bioactive MDs-NFATc1/PLA-Exo scaffold holds promise as an innovative structure for bone tissue regeneration. By specifically targeting osteoclast formation and promoting osteogenic differentiation, this hybrid scaffold may address key challenges in osteoporosis-related fractures.

Development and validation of a radiosensitivity model to evaluate radiotherapy benefits in pan-cancer

Radiotherapy, one of the most fundamental cancer treatments, is confronted with the dilemma of treatment failure due to radioresistance. To predict the radiosensitivity and improve tumor treatment efficiency in pan-cancer, we developed a model called Radiation Intrinsic Sensitivity Evaluation (RISE). The RISE model was built using cell line-based mRNA sequencing data from five tumor types with varying radiation sensitivity. Through four cell-derived datasets, two public tissue-derived cohorts, and one local cohort of 42 nasopharyngeal carcinoma patients, we demonstrated that RISE could effectively predict the level of radiation sensitivity (area under the ROC curve [AUC] from 0.666 to 1 across different datasets). After the verification by the colony formation assay and flow cytometric analysis of apoptosis, our four well-established radioresistant cell models successfully proved higher RISE values in radioresistant cells by RT-qPCR experiments. We also explored the prognostic value of RISE in five independent TCGA cohorts consisting of 1137 patients who received radiation therapy and found that RISE was an independent adverse prognostic factor (pooled multivariate Cox regression hazard ratio [HR]: 1.84, 95% CI 1.39-2.42; p < 0.01). RISE showed a promising ability to evaluate the radiotherapy benefit while predicting the prognosis of cancer patients, enabling clinicians to make individualized radiotherapy strategies in the future and improve the success rate of radiotherapy.

A TGF-β signaling-related lncRNA signature for prediction of glioma prognosis, immune microenvironment, and immunotherapy response

AIMS

The dysregulation of TGF-β signaling is a crucial pathophysiological process in tumorigenesis and progression. LncRNAs have diverse biological functions and are significant participants in the regulation of tumor signaling pathways. However, the clinical value of lncRNAs related to TGF-β signaling in glioma is currently unclear.

METHODS

Data on glioma's RNA-seq transcriptome, somatic mutation, DNA methylation data, and clinicopathological information were derived from the CGGA and TCGA databases. A prognostic lncRNA signature was constructed by Cox and LASSO regression analyses. TIMER2.0 database was utilized to deduce immune infiltration characteristics. "ELMER v.2" was used to reconstruct TF-methylation-gene regulatory network. Immunotherapy and chemotherapy response predictions were implemented by the TIDE algorithm and GDSC database, respectively. In vitro and in vivo experiments were conducted to verify the results and clarify the regulatory mechanism of lncRNA.

RESULTS

In glioma, a TGF-β signaling-related 15-lncRNA signature was constructed, including AC010173.1, HOXA-AS2, AC074286.1, AL592424.1, DRAIC, HOXC13-AS, AC007938.1, AC010729.1, AC013472.3, AC093895.1, AC131097.4, AL606970.4, HOXC-AS1, AGAP2-AS1, and AC002456.1. This signature proved to be a reliable prognostic tool, with high risk indicating an unfavorable prognosis and being linked to malignant clinicopathological and genomic mutation traits. Risk levels were associated with different immune infiltration landscapes, where high risk was indicative of high levels of macrophage infiltration. In addition, high risk also suggested better immunotherapy and chemotherapy response. cg05987823 was an important methylation site in glioma progression, and AP-1 transcription factor family participated in the regulation of signature lncRNA expression. AGAP2-AS1 knockdown in in vitro and in vivo experiments inhibited the proliferation, migration, and invasion of glioma cells, as well as the growth of glioma, by downregulating the expression levels of NF-κB and ERK 1/2 in the TGF-β signaling pathway.

CONCLUSIONS

A prognostic lncRNA signature of TGF-β signaling was established in glioma, which can be used for prognostic judgment, immune infiltration status inference, and immunotherapy response prediction. AGAP2-AS1 plays an important role in glioma progression.

The regulatory role and clinical application prospects of circRNA in the occurrence and development of CNS tumors

BACKGROUND

Central nervous system (CNS) tumors originate from the spinal cord or brain. The study showed that even with aggressive treatment, malignant CNS tumors have high mortality rates. However, CNS tumor risk factors and molecular mechanisms have not been verified. Due to the reasons mentioned above, diagnosis and treatment of CNS tumors in clinical practice are currently fraught with difficulties. Circular RNAs (circRNAs), single-stranded ncRNAs with covalently closed continuous structures, are essential to CNS tumor development. Growing evidence has proved the numeral critical biological functions of circRNAs for disease progression: sponging to miRNAs, regulating gene transcription and splicing, interacting with proteins, encoding proteins/peptides, and expressing in exosomes.

AIMS

This review aims to summarize current progress regarding the molecular mechanism of circRNA in CNS tumors and to explore the possibilities of clinical application based on circRNA in CNS tumors.

METHODS

We have summarized studies of circRNA in CNS tumors in Pubmed.

RESULTS

This review summarized their connection with CNS tumors and their functions, biogenesis, and biological properties. Furthermore, we introduced current advances in clinical RNA-related technologies. Then we discussed the diagnostic and therapeutic potential (especially for immunotherapy, chemotherapy, and radiotherapy) of circRNA in CNS tumors in the context of the recent advanced research and application of RNA in clinics.

CONCLUSIONS

CircRNA are increasingly proven to participate in decveloping CNS tumors. An in-depth study of the causal mechanisms of circRNAs in CNS tomor progression will ultimately advance their implementation in the clinic and developing new strategies for preventing and treating CNS tumors.

Mathematical definition and rules of the splitting/merging patterns in bundles of human peripheral nerve segment

Accurately measuring the spatial extension distance of nerve bundles in completing a split/merge is impossible because no clear mathematical definition exists for the starting and ending positions in nerve-bundle splitting/merging. We manually count the number of nerve-bundle splits/merges in long nerve segments, which is labor-intensive, inefficient, and prone to counting errors. Currently, the mathematics are unclear for the nerve-bundle diameter before and after splitting/merging. This paper explores these problems and proposes nerve-bundle splitting/merging rules. Based on the method of defining the beginning and ending positions of nerve-bundle splitting/merging, we explored the mathematical law of equivalent diameter of nerve bundles before and after splitting/merging. The experimental results revealed that the moving average of circularity of nerve bundle accurately defines the beginning and ending positions of nerve-bundle splitting/merging. The diameter of the nerve bundles before and after split/merge approximately conforms to the principles of the Da Vinci formula. The proposed automatic counting algorithm based on centroid offset matching obtains the number of split/merged nerve bundles in the sequence scan images with 100 % accuracy. The mathematical definition of the starting and ending positions of nerve-bundle splitting/merging proposed in this paper is accurate and strict and is the foundation of subsequent research. The proposed automatic counting algorithm based on centroid offset matching (ACA-COM) can accurately and efficiently count the number of times the nerve bundles split and merge in sequential images. The mathematical law satisfied by the diameter of the nerve bundles before and after splitting/merging reflects that the nerve bundles tend to have better capability to resist breaking.

Structural and functional basis of bacteriophage K64-ORF41 depolymerase for capsular polysaccharide degradation of Klebsiella pneumoniae K64

Capsule polysaccharide is an important virulence factor of Klebsiella pneumoniae (K. pneumoniae), which protects bacteria against the host immune response. A promising therapeutic approach is using phage-derived depolymerases to degrade the capsular polysaccharide and expose and sensitize the bacteria to the host immune system. Here we determined the cryo-electron microscopy (cryo-EM) structures of a bacteriophage tail-spike protein against K. pneumoniae K64, ORF41 (K64-ORF41) and ORF41 in EDTA condition (K64-ORF41EDTA), at 2.37 Å and 2.50 Å resolution, respectively, for the first time. K64-ORF41 exists as a trimer and each protomer contains a β-helix domain including a right-handed parallel β-sheet helix fold capped at both ends, an insertion domain, and one β-sheet jellyroll domain. Moreover, our structural comparison with other depolymerases of K. pneumoniae suggests that the catalytic residues (Tyr528, His574 and Arg628) are highly conserved although the substrate of capsule polysaccharide is variable. Besides that, we figured out the important residues involved in the substrate binding pocket including Arg405, Tyr526, Trp550 and Phe669. This study establishes the structural and functional basis for the promising phage-derived broad-spectrum activity depolymerase therapeutics and effective CPS-degrading agents for the treatment of carbapenem-resistant K. pneumoniae K64 infections.

SPCS, a Novel Classifier System Based on Senescence Axis Regulators Reveals Tumor Microenvironment Heterogeneity and Guides Frontline Therapy for Clear Cell Renal Carcinoma

RATIONALE

The emerging evidence suggested that senescence regulator genes were involved in multi cancers, which may be utilized as new targets for cancers. However, the dysregulation and clinical impact of senescence regulator genes in clear cell renal cell cancer (ccRCC) were still in foggy.

METHODS

Using multiomics data from TCGA-KIRC and other datasets, we comprehensively investigated the function of senescence regulator genes in ccRCC. ccRCC patients could be remodeled into 2 significant different groups basing on senescence regulators expression: senescence-pattern cancer subtype1 (SPCS1) and subtype2 (SPCS2). We further explored clinical characteristics, functional analysis, tumor immune microenvironment, immunotherapy response, genomic mutation and drug sensitivity between the 2 subtypes. Besides, senescence-pattern related risk model was established to determine the patient's prognosis of ccRCC. Finally, the overview of MECP2 function was investigated in multi cancers.

RESULTS

ccRCC patients could be divided into SPCS1 (normal aging group) and SPCS2 (Aging disorder group). The 2 subtypes showed significant different clinical characteristics and biological process in ccRCC. SPCS2, an aggressive subtype, comprised higher clinical stage and worse prognosis of ccRCC patients. SPCS2 subtype indicated activated oncogenic signaling pathway and metabolic signatures to prompt cancer expansion. SPCS2 subgroup owned immunocompromised status, which induced immune dysfunction and low ICI therapy response. The genome-copy numbers of SPCS2, including arm-gain and arm-loss was significantly more frequent than SPCS1. In addition, the 2 subtypes argue contrasting drug sensitivity profiles in clinical specimens and matched cell lines. Finally, we constructed a prognostic risk model consisted of each subtype's leading biomarkers, which exerted a satisfied performance for ccRCC patients.

CONCLUSION

Senescence regulator-related signature could modify functional pathways and tumor immune microenvironment by genome mutation and pathway interaction. Senescence regulator-related molecular subtype strengthen the understanding of ccRCC' characterization and guide clinical treatment. Targeting senescence regulators may be regard as a proper way in ccRCC.

Nanointegrative Glycoengineering-Activated Necroptosis of Triple Negative Breast Cancer Stem Cells Enables Self-Amplifiable Immunotherapy for Systemic Tumor Rejection

Triple-negative breast cancer stem cells (TCSCs) are considered as the origin of recurrence and relapse. It is difficult to kill not only for its resistance, but also the lacking of targetable molecules on membrane. Here, it is confirmed that ST6 β-galactoside alpha-2,6-sialyltransferase 1 (ST6Gal-1) is highly expressed in TCSCs that may be the key enzyme involved in glycoengineering via sialic acid (SA) metabolism. SA co-localizes with a microdomain on cell membrane termed as lipid rafts that enrich CSCs marker and necroptosis proteins mixed lineage kinase domain-like protein (MLKL), suggesting that TCSCs may be sensitive to necroptosis. Thus, the triacetylated N-azidoacetyl-d-mannosamine (Ac3ManNAz) is synthesized as the glycoengineering substrate and applied to introduce artificial azido receptors, dibenzocyclooctyne (DBCO)-modified liposome is used to deliver Compound 6i (C6), a receptor-interacting serine/threonine protein kinase 1(RIPL1)-RIP3K-mixed lineage kinase domain-like protein(MLKL) activator, to induce necroptosis. The pro-necroptosis effect is aggravated by nitric oxide (NO), which is released from NO-depot of cholesterol-NO integrated in DBCO-PEG-liposome@NO/C6 (DLip@NO/C6). Together with the immunogenicity of necroptosis that releases high mobility group box 1(HMGB1) of damage-associated molecular patterns, TCSCs are significantly killed in vitro and in vivo. The results suggest a promising strategy to improve the therapeutic effect on the non-targetable TCSCs with high expression of ST6Gal-1 via combination of glycoengineering and necroptosis induction.

Application of Fenton chemistry in electrochemical determination of pyrophosphatase activity and fluoride

Fenton chemistry has aroused widespread concern due to its application in the green oxidation and mineralization of organic wastes. Inorganic pyrophosphatase (PPase) catalyzes the hydrolysis of pyrophosphate ions (PPi) and provides a thermodynamic driving force for many biosynthetic reactions. Fluoride (F-) is widely applied to fight against tooth decay and reduce cavities. The electrochemical determination of PPase activity and F- was realized based on Fenton chemistry in this work. Glassy carbon electrode modified with poly (azure A) and acetylene black (GCE/PAA-AB) was fabricated. Hydroxyl radicals (∙OH) that were generated from a Cu2+-catalyzed Fenton-type reaction could oxidize PAA in the near-neutral medium, leading to a great increase of the cathodic peak current (Ipc). A coordination reaction between PPi and Cu2+ exerted a negative effect on Fenton reaction and hindered the Ipc enhancement. Cu2+-PPi complex was decomposed due to the hydrolysis of PPi induced by PPase, which caused the reappearance of the notably increased current response. F- could effectively inhibit PPase activity. As a result, the stable Cu2+-PPi complex remained and the high Ipc suffered from the decline again. The Ipc difference was used for the highly sensitive determination of PPase activity in the content range of 0.001-20 mU mL-1 with a detection of limit (LOD) at 0.6 μU mL-1 and that of F- in the concentration range of 0.01-100 μM with a LOD at 7 nM. The proposed PPase and F- sensor displayed a good selectivity, stability and reproducibility, and a high accuracy.

MOCS, a novel classifier system integrated multimoics analysis refining molecular subtypes and prognosis for skin melanoma

PURPOSE

The present investigation focuses on Skin Cutaneous Melanoma (SKCM), a melanocytic carcinoma characterized by marked aggression, significant heterogeneity, and a complex etiological background, factors which collectively contribute to the challenge in prognostic determinations. We defined a novel classifier system specifically tailored for SKCM based on multiomics.

METHODS

We collected 423 SKCM samples with multi omics datasets to perform a consensus cluster analysis using 10 machine learning algorithms and verified in 2 independent cohorts. Clinical features, biological characteristics, immune infiltration pattern, therapeutic response and mutation landscape were compared between subtypes.

RESULTS

Based on consensus clustering algorithms, we identified two Multi-Omics-Based-Cancer-Subtypes (MOCS) in SKCM in TCGA project and validated in GSE19234 and GSE65904 cohorts. MOCS2 emerged as a subtype with poor prognosis, characterized by a complex immune microenvironment, dysfunctional anti-tumor immune state, high cancer stemness index, and genomic instability. MOCS2 exhibited resistance to chemotherapy agents like erlotinib and sunitinib while sensitive to rapamycin, NSC87877, MG132, and FH355. Additionally, ELSPBP1 was identified as the target involving in glycolysis and M2 macrophage infiltration in SKCM.

CONCLUSIONS

MOCS classification could stably predict prognosis of SKCM; patients with a high cancer stemness index combined with genomic instability may be predisposed to an immune exhaustion state.Communicated by Ramaswamy H. Sarma.

Simultaneous determination of 28 illegal drugs in sewage by high throughput online SPE-ISTD-UHPLC-MS/MS

This study developed an online solid-phase extraction ultra-high performance liquid chromatography-tandem mass spectrometry (Online-SPE-UHPLC-MS/MS) method for the analysis of 28 illegal drugs in sewage. To achieve this, 28 isotope internal standards (ISTDs) were added to 3 mL sewage samples, the pH was adjusted to 7-8 using hydrochloric acid or 20% ammonia water, followed by centrifugation, filtration, and analysis using UHPLC-MS/MS. The results indicated an excellent linearity of 1-300 ng L-1, and cotinine in the concentration range of 20-6000 ng L-1, linear correlation coefficient R2 > 0.995, with the limit of detection (LOD) of 0.01-6 ng L-1, and a limit of quantification (LOQ) of 0.1-20 ng L-1. The addition of three concentrates of low (2 ng L-1/40 ng L-1), medium (20 ng L-1/400 ng L-1), and high concentration (200 ng L-1/4000 ng L-1) demonstrated the matrix effect of the target compound between ± 22.0%. The extraction recovery was 70.0-119.4%, and a percent accuracy of 75.7-118.1%. Similarly, the intra- and inter-day precisions were 1.8-20.0% and 1.5-18.9%, respectively. The results cemented the sensitivity, accuracy, reliability, strong specificity, and reproducibility, which can be used to screen 28 illegal drugs in sewage for trace analysis.

Role of body mass index and weight change in the risk of cancer: A systematic review and meta-analysis of 66 cohort studies

Background

This study was designed to evaluate the effects of body mass index (BMI) and weight change on the risk of developing cancer overall and cancer at different sites.

Methods

We searched PubMed and other databases up to July 2023 using the keywords related to 'risk', 'cancer', 'weight', 'overweight', and 'obesity'. We identified eligible studies, and the inclusion criteria encompassed cohort studies in English that focused on cancer diagnosis and included BMI or weight change as an exposure factor. Multiple authors performed data extraction and quality assessment, and statistical analyses were carried out using RevMan and R software. We used random- or fixed-effects models to calculate the pooled relative risk (RR) or hazard ratio along with 95% confidence intervals (CIs). We used the Newcastle-Ottawa Scale to assess study quality.

Results

Analysis included 66 cohort studies. Compared to underweight or normal weight, overweight or obesity was associated with an increased risk of endometrial cancer, kidney cancer, and liver cancer but a decreased risk of prostate cancer and lung cancer. Being underweight was associated with an increased risk of gastric cancer and lung cancer but not that of postmenopausal breast cancer or female reproductive cancer. In addition, weight loss of more than five kg was protective against overall cancer risk.

Conclusions

Overweight and obesity increase the risk of most cancers, and weight loss of >5 kg reduces overall cancer risk. These findings provide insights for cancer prevention and help to elucidate the mechanisms underlying cancer development.

Registration

Reviewregistry1786.

Preso enhances mGluR1-mediated excitotoxicity by modulating the phosphorylation of mGluR1-Homer1 complex and facilitating an ER stress after traumatic brain injury

Glutamate receptor (GluR)-mediated excitotoxicity is an important mechanism causing delayed neuronal injury after traumatic brain injury (TBI). Preso, as a core scaffolding protein of postsynaptic density (PSD), is considered an important regulator during excitotoxicity and TBI and combines with glutamate receptors to form functional units for excitatory glutamatergic neurotransmission, and elucidating the mechanisms of these functional units will provide new targets for the treatment of TBI. As a multidomain scaffolding protein, Preso directly interacts with metabotropic GluR (mGluR) and another scaffold protein, Homer. Because the mGluR-Homer complex plays a crucial role in TBI, modulation of this complex by Preso may be an important mechanism affecting the excitotoxic damage to neurons after TBI. Here, we demonstrate that Preso facilitates the interaction between metabotropic mGluR1 and Homer1 to activate mGluR1 signaling and cause excitotoxic neuronal injury and endoplasmic reticulum (ER) stress after TBI. The regulatory effect of Preso on the mGluR1-Homer1 complex is dependent on the direct association between Preso and this complex and also involves the phosphorylation of the interactive binding sites of mGluR1 and Homer1 by Preso. Further studies confirmed that Preso, as an adaptor of cyclin-dependent kinase 5 (CDK5), promotes the phosphorylation of the Homer1-binding site on mGluR1 by CDK5 and thereby enhances the interaction between mGluR1 and Homer1. Preso can also promote the formation of the mGluR1-Homer1 complex by inhibiting the phosphorylation of the Homer1 hinge region by Ca2+/calmodulin-dependent protein kinase IIα (CaMKIIα). Based on these molecular mechanisms, we designed several blocking peptides targeting the interaction between Preso and the mGluR1-Homer1 complex and found that directly disrupting the association between mGluR1 and scaffolding proteins significantly promotes the recovery of motor function after TBI.

Wavelength encoding spectral imaging based on the combination of deeply learned filters and an RGB camera

Hyperspectral imaging is a critical tool for gathering spatial-spectral information in various scientific research fields. As a result of improvements in spectral reconstruction algorithms, significant progress has been made in reconstructing hyperspectral images from commonly acquired RGB images. However, due to the limited input, reconstructing spectral information from RGB images is ill-posed. Furthermore, conventional camera color filter arrays (CFA) are designed for human perception and are not optimal for spectral reconstruction. To increase the diversity of wavelength encoding, we propose to place broadband encoding filters in front of the RGB camera. In this condition, the spectral sensitivity of the imaging system is determined by the filters and the camera itself. To achieve an optimal encoding scheme, we use an end-to-end optimization framework to automatically design the filters' transmittance functions and optimize the weights of the spectral reconstruction network. Simulation experiments show that our proposed spectral reconstruction network has excellent spectral mapping capabilities. Additionally, our novel joint wavelength encoding imaging framework is superior to traditional RGB imaging systems. We develop the deeply learned filter and conduct actual shooting experiments. The spectral reconstruction results have an attractive spatial resolution and spectral accuracy.

CTLs heterogeneity and plasticity: implications for cancer immunotherapy

Cytotoxic T lymphocytes (CTLs) play critical antitumor roles, encompassing diverse subsets including CD4+, NK, and γδ T cells beyond conventional CD8+ CTLs. However, definitive CTLs biomarkers remain elusive, as cytotoxicity-molecule expression does not necessarily confer cytotoxic capacity. CTLs differentiation involves transcriptional regulation by factors such as T-bet and Blimp-1, although epigenetic regulation of CTLs is less clear. CTLs promote tumor killing through cytotoxic granules and death receptor pathways, but may also stimulate tumorigenesis in some contexts. Given that CTLs cytotoxicity varies across tumors, enhancing this function is critical. This review summarizes current knowledge on CTLs subsets, biomarkers, differentiation mechanisms, cancer-related functions, and strategies for improving cytotoxicity. Key outstanding questions include refining the CTLs definition, characterizing subtype diversity, elucidating differentiation and senescence pathways, delineating CTL-microbe relationships, and enabling multi-omics profiling. A more comprehensive understanding of CTLs biology will facilitate optimization of their immunotherapy applications. Overall, this review synthesizes the heterogeneity, regulation, functional roles, and enhancement strategies of CTLs in antitumor immunity, highlighting gaps in our knowledge of subtype diversity, definitive biomarkers, epigenetic control, microbial interactions, and multi-omics characterization. Addressing these questions will refine our understanding of CTLs immunology to better leverage cytotoxic functions against cancer.

Potential anti-tumor effects of regulatory T cells in the tumor microenvironment: a review

Regulatory T cells (Tregs) expressing the transcription factor FoxP3 are essential for maintaining immunological balance and are a significant component of the immunosuppressive tumor microenvironment (TME). Single-cell RNA sequencing (ScRNA-seq) technology has shown that Tregs exhibit significant plasticity and functional diversity in various tumors within the TME. This results in Tregs playing a dual role in the TME, which is not always centered around supporting tumor progression as typically believed. Abundant data confirms the anti-tumor activities of Tregs and their correlation with enhanced patient prognosis in specific types of malignancies. In this review, we summarize the potential anti-tumor actions of Tregs, including suppressing tumor-promoting inflammatory responses and boosting anti-tumor immunity. In addition, this study outlines the spatial and temporal variations in Tregs function to emphasize that their predictive significance in malignancies may change. It is essential to comprehend the functional diversity and potential anti-tumor effects of Tregs to improve tumor therapy strategies.

Di-(2-ethylhexyl) phthalate exposure induces premature testicular senescence by disrupting mitochondrial respiratory chain through STAT5B-mitoSTAT3 in Leydig cell

Di-(2-ethylhexyl) phthalate (DEHP), a prevalent plasticizer, is known to have endocrine-disrupting effects on males and cause reproductive toxicity. There were causal effects of DEHP on testosterone levels in the real world by Mendelian randomization analysis. Exposure to DEHP during the preadult stage might lead to premature testicular senescence, but the mechanisms responsible for this have yet to be determined. In this study, we administered DEHP (300 mg/kg/day) to male C57BL/6 mice from postnatal days 21 to 49. The mice were kept for 6 months without DEHP. RNA sequencing was conducted on testicular tissue at PNM6. The results indicated that DEHP hindered testicular development, lowered serum testosterone levels in male mice, and induced premature testicular senescence. TM3 Leydig cells were exposed to 300 μM of mono(2-ethylhexyl) phthalate (MEHP), the bioactive metabolite of DEHP, for 72 h. The results also found that DEHP/MEHP induced senescence in vivo and in vitro. The mitochondrial respiratory chain was disrupted in Leydig cells. The expression and stability of STAT5B were elevated by MEHP treatment in TM3 cells. Furthermore, p-ERK1/2 was significantly decreased by STAT5B, and mitochondria-STAT3 (p-STAT3 ser727) was significantly decreased due to the decrease of p-ERK1/2. Additionally, the senescence level of TM3 cells was decreased and treated with 5 mM NAC for 1 h after MEHP treatment. In conclusion, these findings provided a novel mechanistic understanding of Leydig cells by disrupting the mitochondrial respiratory chain through STAT5B-mitoSTAT3.

OralExplorer: a web server for exploring the mechanisms of oral inflammatory diseases

BACKGROUND

Oral inflammatory diseases are localized infectious diseases primarily caused by oral pathogens with the potential for serious systemic complications. However, publicly available datasets for these diseases are underutilized. To address this issue, a web tool called OralExplorer was developed. This tool integrates the available data and provides comprehensive online bioinformatic analysis.

METHODS

Human oral inflammatory disease-related datasets were obtained from the GEO database and normalized using a standardized process. Transcriptome data were then subjected to differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis, and visualization. The single-cell sequencing data was visualized as cluster plot, feature plot, and heatmaps. The web platform was primarily built using Shiny. The biomarkers identified in OralExplorer were validated using local clinical samples through qPCR and IHC.

RESULTS

A total of 35 human oral inflammatory disease-related datasets, covering 6 main disease types and 901 samples, were included in the study to identify potential molecular signatures of the mechanisms of oral diseases. OralExplorer consists of 5 main analysis modules (differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis and single-cell analysis), with multiple visualization options. The platform offers a simple and intuitive interface, high-quality images for visualization, and detailed analysis results tables for easy access by users. Six markers (IL1β, SRGN, CXCR1, FGR, ARHGEF2, and PTAFR) were identified by OralExplorer. qPCR- and IHC-based experimental validation showed significantly higher levels of these genes in the periodontitis group.

CONCLUSIONS

OralExplorer is a comprehensive analytical platform for oral inflammatory diseases. It allows users to interactively explore the molecular mechanisms underlying the action and regression of these diseases. It also aids dental researchers in unlocking the potential value of transcriptomics data related to oral diseases. OralExplorer can be accessed at https://smuonco.shinyapps.io/OralExplorer/  (Alternate URL: http://robinl-lab.com/OralExplorer ).

Comprehensive bioinformatics analysis of co-expressed genes of post-traumatic stress disorder and major depressive disorder

BACKGROUND

Post-traumatic stress disorder (PTSD) is one of the most serious sequelae of trauma with serious impact worldwide. Studies have suggested an association between PTSD and major depressive disorder (MDD), but the underlying common mechanisms remain unclear. This study aimed to further explore the molecular mechanism between PTSD and MDD via comprehensive bioinformatics analysis.

METHODS

The microarray data of PTSD and MDD were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify the co-expressed genes associated with PTSD and MDD. Gene Set Enrichment Analysis (GSEA), enrichment analyses based on Disease Ontology (DO), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed using R software. Then, R software was used for single-sample gene set enrichment analysis (ssGSEA) and immune infiltration analysis on the co-expressed genes in the two datasets., Therefore, a logistic regression model was constructed to predict PTSD and MDD using the R language. Ultimately, this study employed PTSD and MDD models to assess alterations in the expression of target genes within the mouse hippocampus.

RESULTS

Four core genes (GNAQ, DPEP3, ICAM2, PACSIN2) were obtained through different analyses, and these genes had predictive validity for PTSD and MDD, playing an important role in the common mechanism of PTSD and MDD. The study findings reveal decreased expression levels of DPEP3, GNAQ, and PACDIN2 in PTSD samples, accompanied by an increased expression of ICAM2. In MDD samples, the expression of DPEP3 and ICAM2 is reduced, whereas GNAQ and PACDIN2 show an increase in expression.

CONCLUSIONS

This study provides a new perspective on the common molecular mechanisms of PTSD and MDD. These common pathways and core genes may provide promising clues for further experimental studies.

PMI-controlled mannose metabolism and glycosylation determines tissue tolerance and virus fitness

Host survival depends on the elimination of virus and mitigation of tissue damage. Herein, we report the modulation of D-mannose flux rewires the virus-triggered immunometabolic response cascade and reduces tissue damage. Safe and inexpensive D-mannose can compete with glucose for the same transporter and hexokinase. Such competitions suppress glycolysis, reduce mitochondrial reactive-oxygen-species and succinate-mediated hypoxia-inducible factor-1α, and thus reduce virus-induced proinflammatory cytokine production. The combinatorial treatment by D-mannose and antiviral monotherapy exhibits in vivo synergy despite delayed antiviral treatment in mouse model of virus infections. Phosphomannose isomerase (PMI) knockout cells are viable, whereas addition of D-mannose to the PMI knockout cells blocks cell proliferation, indicating that PMI activity determines the beneficial effect of D-mannose. PMI inhibition suppress a panel of virus replication via affecting host and viral surface protein glycosylation. However, D-mannose does not suppress PMI activity or virus fitness. Taken together, PMI-centered therapeutic strategy clears virus infection while D-mannose treatment reprograms glycolysis for control of collateral damage.

Periodic changes of cyclin D1 mRNA stability are regulated by PC4 modifications in the cell cycle

The cell cycle is a highly regulated process in which proteins involved in cell cycle progression exhibit periodic expression patterns, controlled by specific mechanisms such as transcription, translation, and degradation. However, the precise mechanisms underlying the oscillations of mRNA levels in cell cycle regulators are not fully understood. In this study, we observed that the stability of cyclin D1 (CCND1) mRNA fluctuates during the cell cycle, with increased stability during interphase and decreased stability during the M phase. Additionally, we identified a key RNA binding protein, positive coactivator 4 (PC4), which plays a crucial role in stabilizing CCND1 mRNA and regulating its periodic expression. Moreover, the binding affinity of PC4 to CCND1 mRNA is modulated by two cell cycle-specific posttranslational modifications: ubiquitination of K68 enhances binding and stabilizes the CCND1 transcript during interphase, while phosphorylation of S17 inhibits binding during the M phase, leading to degradation of CCND1 mRNA. Remarkably, PC4 promotes the transition from G1 to S phase in the cell cycle, and depletion of PC4 enhances the efficacy of CDK4/6 inhibitors in hepatocellular carcinoma, suggesting that PC4 could serve as a potential therapeutic target. These findings provide valuable insights into the intricate regulation of cell cycle dynamics.

Two-dimensional speckle tracking imaging analyses of the correlations between left atrial appendage function and stroke risk in nonvalvular atrial fibrillation patients

Stroke incidence is the most severe complication associated with atrial fibrillation (AF), and the most common site of thrombus formation in AF patients is the left atrial appendage (LAA). This study was developed to use two-dimensional speckle tracking imaging (2D-STI) to explore associations between LAA strain/strain rate and stroke incidence and to evaluate the value of utilizing LAA strain and strain rate values to support the stratification of nonvalvular AF (NVAF) patients based on stroke risk. A total of 486 AF patients who had undergone transesophageal echocardiography to exclude potential intracardiac thrombosis between March 2021 and November 2022 were consecutively enrolled. Patients meeting the inclusion criteria were separated into two groups according to their history of stroke/transient ischemic attack (TIA). LAA strain and strain rate values in these patients were measured via 2D-STI. Multivariable logistic regression analysis was employed to determine independent risk factors for the construction of a combined predictive model. Of the 333 analyzed patients (134 females, aged 65 (56,72) years), 39 (11.71%, 39/333) had a history of stroke at the time of evaluation. Multivariate logistic regression analysis demonstrated that nonparoxysmal AF, CHA2DS2VASc score, LAA thrombus/spontaneous echo contrast (SEC), LAA strain, and strain rate were all predictors of stroke incidence among NVAF patients. The combined predictive model demonstrated excellent discriminative ability, with an AUC of 0.91 (95%CI 0.87-0.95, P < 0.001), and a sensitivity and specificity of 79.49% and 89.46%, respectively. The Hosmer-Lemeshow test confirmed good calibration, yielding a value of 0.98. Comparative decision curve analysis showed that the model provided superior net benefits compared to the CHA2DS2VASc score. Furthermore, the model exhibited improved predictive performance and reclassification for stroke when compared to the CHA2DS2VASc score (AUC 0.91 vs. 0.88, Z = 2.32, P = 0.02), accompanied by a significant increase in the net reclassification index (+ 5.44%, P < 0.001) and integrated discrimination improvement (8.21%, P < 0.001). These data demonstrate that LAA strain and strain rate, as measured via 2D-STI, can offer value when assessing LAA function in AF patients, potentially providing further predictive value to extant clinical risk scoring strategies.

Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity

As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.

Burden of cardiovascular disease among elderly: based on the Global Burden of Disease Study 2019

BACKGROUND

The burden of elderly cardiovascular disease (CVD) has received increasing attention with population ageing worldwide.

AIMS

We reported on the global CVD burden in elderly individuals over 70, 1990-2019.

METHODS AND RESULTS

Based on the Global Burden of Disease Study 2019, elderly CVD burden data were analysed. Temporal burden trends were analysed with the joinpoint model. The slope index and concentration index were used to evaluate health inequality. From 1990 to 2019, the global elderly CVD incidence, prevalence, death, and disability-adjusted life year rates generally decreased. However, the current burden remains high. The rapid growth in burden in parts of sub-Saharan Africa and Asia is a cause for concern. Countries with a higher socio-demographic index (SDI) have generally seen a greater decrease in burden, while countries with a lower SDI have generally experienced increases or smaller declines in burden. Health inequality analysis confirmed that the burden was gradually concentrating towards countries with a low SDI. Among the different CVDs, ischaemic heart disease causes the greatest burden in elderly individuals. Most CVD burdens increase with age, but stroke and peripheral vascular disease show markedly different distributional characteristics. In addition, the burden of hypertensive heart disease shows an unusual shift towards high-SDI countries. High systolic blood pressure was consistently the leading risk factor for CVD among elderly individuals.

CONCLUSION

The burden of CVD in older people remains severe and generally tends to shift to lower-SDI countries. Policymakers need to take targeted measures to reduce its harm.

Body mass index, weight change, and cancer prognosis: a meta-analysis and systematic review of 73 cohort studies

BACKGROUND

Identifying the association between body mass index (BMI) or weight change and cancer prognosis is essential for the development of effective cancer treatments. We aimed to assess the strength and validity of the evidence of the association between BMI or weight change and cancer prognosis by a systematic evaluation and meta-analysis of relevant cohort studies.

METHODS

We systematically searched the PubMed, Web of Science, EconLit, Embase, Food Sciences and Technology Abstracts, PsycINFO, and Cochrane databases for literature published up to July 2023. Inclusion criteria were cohort studies with BMI or weight change as an exposure factor, cancer as a diagnostic outcome, and data type as an unadjusted hazard ratio (HR) or headcount ratio. Random- or fixed-effects models were used to calculate the pooled HR along with the 95% confidence interval (CI).

RESULTS

Seventy-three cohort studies were included in the meta-analysis. Compared with normal weight, overweight or obesity was a risk factor for overall survival (OS) in patients with breast cancer (HR 1.37, 95% CI 1.22-1.53; P < 0.0001), while obesity was a protective factor for OS in patients with gastrointestinal tumors (HR 0.67, 95% CI 0.56-0.80; P < 0.0001) and lung cancer (HR 0.67, 95% CI 0.48-0.92; P = 0.01) compared with patients without obesity. Compared with normal weight, underweight was a risk factor for OS in patients with breast cancer (HR 1.15, 95% CI 0.98-1.35; P = 0.08), gastrointestinal tumors (HR 1.54, 95% CI 1.32-1.80; P < 0.0001), and lung cancer (HR 1.28, 95% CI 1.22-1.35; P < 0.0001). Compared with nonweight change, weight loss was a risk factor for OS in patients with gastrointestinal cancer.

CONCLUSIONS

Based on the results of the meta-analysis, we concluded that BMI, weight change, and tumor prognosis were significantly correlated. These findings may provide a more reliable argument for the development of more effective oncology treatment protocols.

Identification of hypoxia- and immune-related biomarkers in patients with ischemic stroke

Background

The immune microenvironment and hypoxia play crucial roles in the pathophysiology of ischemic stroke (IS). Hence, in this study, we aimed to identify hypoxia- and immune-related biomarkers in IS.

Methods

The IS microarray dataset GSE16561 was examined to determine differentially expressed genes (DEGs) utilizing bioinformatics-based analysis. The intersection of hypoxia-related genes and DEGs was conducted to identify differentially expressed hypoxia-related genes (DEHRGs). Then, using weighted correlation network analysis (WGCNA), all of the genes in GSE16561 dataset were examined to create a co-expression network, and module-clinical trait correlations were examined for the purpose of examining the genes linked to immune cells. The immune-related DEHRGs were submitted to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A protein-protein interaction (PPI) network was constructed by Cytoscape plugin MCODE, in order to extract hub genes. The miRNet was used to predict hub gene-related transcription factors (TFs) and miRNAs. Finally, a diagnostic model was developed by least absolute shrinkage and selection operator (LASSO) logistic regression.

Results

Between the control and IS samples, 4171 DEGs were found. Thereafter, the intersection of hypoxia-related genes and DEGs was conducted to obtain 45 DEHRGs. Ten significantly differentially infiltrated immune cells were found-namely, CD56dim natural killer cells, activated CD8 T cells, activated dendritic cells, activated B cells, central memory CD8 T cells, effector memory CD8 T cells, natural killer cells, gamma delta T cells, plasmacytoid dendritic cells, and neutrophils-between IS and control samples. Subsequently, we identified 27 immune-related DEHRGs through the intersection of DEHRGs and genes in important modules of WGCNA. The immune-related DEHRGs were primarily enriched in response to hypoxia, cellular polysaccharide metabolic process, response to decreased oxygen levels, polysaccharide metabolic process, lipid and atherosclerosis, and HIF-1 signaling pathway H. Using MCODE, FOS, DDIT3, DUSP1, and NFIL3 were found to be hub genes. In the validation cohort and training set, the AUC values of the diagnostic model were 0.9188034 and 0.9395085, respectively.

Conclusion

In brief, we identified and validated four hub genes-FOS, DDIT3, DUSP1, and NFIL3-which might be involved in the pathological development of IS, potentially providing novel perspectives for the diagnosis and treatment of IS.

High-density stable glasses formed on soft substrates

Enabled by surface-mediated equilibration, physical vapour deposition can create high-density stable glasses comparable with liquid-quenched glasses aged for millions of years. Deposition is often performed at various rates and temperatures on rigid substrates to control the glass properties. Here we demonstrate that on soft, rubbery substrates, surface-mediated equilibration is enhanced up to 170 nm away from the interface, forming stable glasses with densities up to 2.5% higher than liquid-quenched glasses within 2.5 h of deposition. Gaining similar properties on rigid substrates would require 10 million times slower deposition, taking ~3,000 years. Controlling the modulus of the rubbery substrate provides control over the glass structure and density at constant deposition conditions. These results underscore the significance of substrate elasticity in manipulating the properties of the mobile surface layer and thus the glass structure and properties, allowing access to deeper states of the energy landscape without prohibitively slow deposition rates.

Do Habitat MRI and Fractal Analysis Help Distinguish Triple-Negative Breast Cancer From Non-Triple-Negative Breast Carcinoma

Purpose: To determine whether multiparametric MRI-based spatial habitats and fractal analysis can help distinguish triple-negative breast cancer (TNBC) from non-TNBC. Method: Multiparametric DWI and DCE-MRI at 3T were obtained from 142 biopsy- and surgery-proven breast cancer with 148 breast lesions (TNBC = 26 and non-TNBC = 122). The contrast-enhancing lesions were divided into 3 spatial habitats based on perfusion and diffusion patterns using K-means clustering. The fractal dimension (FD) of the tumour subregions was calculated. The accuracy of the habitat segmentation was measured using the Dice index. Inter- and intra-reader reliability were evaluated with the intraclass correlation coefficient (ICC). The ability to predict TNBC status was assessed using the receiver operating characteristic curve. Results: The Dice index for the whole tumour was 0.81 for inter-reader and 0.88 for intra-reader reliability. The inter- and intra-reader reliability were excellent for all 3 tumour habitats and fractal features (ICC > 0.9). TNBC had a lower hypervascular cellular habitat and higher FD 1 compared to non-TNBC (all P < .001). Multivariate analysis confirmed that hypervascular cellular habitat (OR = 0.88) and FD 1 (OR = 1.35) were independently associated with TNBC (all P < .001) after adjusting for rim enhancement, axillary lymph nodes status, and histological grade. The diagnostic model combining hypervascular cellular habitat and FD 1 showed excellent discriminatory ability for TNBC, with an AUC of 0.951 and an accuracy of 91.9%. Conclusions: The fraction of hypervascular cellular habitat and its FD may serve as useful imaging biomarkers for predicting TNBC status.

Identifying the oral microbiome of adolescents with and without dental fluorosis based on full-length 16S rRNA gene sequencing

Dental fluorosis, resulting from long-term environmental exposure to fluoride, is prevalent among diverse populations worldwide. Severe fluorosis not only compromises the aesthetic appeal of teeth but also impairs their functionality. This study aims to investigate the oral microbiome in dental fluorosis and the health individuals of adolescents living in the endemic fluorosis area of Guizhou, China through full-length 16S rDNA sequencing. Fourty-six individuals meet the sampling criteria, and we divided these samples into the following groups: a healthy group (H = 23) and a dental fluorosis group (F = 23), and two subgroups of Miao ethnicity: a healthy Miao group (Hm = 13) and a dental fluorosis Miao group (Fm = 15). A total of 660,389 high-quality sequences were obtained, and 12,007 Amplicon Sequence Variants (ASVs) were identified, revealing significant variations in oral microbiome between Fm and Hm groups. The composition of oral microbiota was similar between the H and F groups. At the genus level, Pseudopropionibacterium and at the species level, Streptococcus oralis_subsp.dentisani_clade_058 were less abundant in group F than in group H (P < 0.05). Further analysis revealed that the abundance of Capnocytophaga gingivalis and Kingella denitrificans was significantly lower in Fm fluorosis patients than in the Hm group (P < 0.05). Based on the LEfSe analysis, the potential core biomarkers in the oral of Fm fluorosis patients were identified at different taxonomic levels, ranging from phylum to species. These include Gammaproteobacteria, Prevotella sp_HMT_304, Gemella sanguinis, and Gracilibacteria_(GN02). Network analysis revealed that the microbiota in the fluorosis group exhibited more complex interactions with each other than the healthy group. Notably, within the Hm group, the potential biomarkers Capnocytophaga gingivalis and Kingella denitrificans exhibited a positive correlation. Finally, we employed PICRUSt2 analysis to explore the abundance clustering of the top 30 functional units in each sample, and we found that the metabolic pathway compositions of the four groups were similar. In summary, our findings suggest that the microbial composition of plaque in Hm patients with dental fluorosis is significantly altered, and we identified the potential marker microorganisms that contribute to these changes.

Cellular Ligand-Receptor Perturbations Unravel MEIS2 as a Key Factor for the Aggressive Progression and Prognosis in Stage II/III Colorectal Cancer

Approximately 10-15% of stage II and 25-30% of stage III colorectal cancer (CRC) patients experience recurrence within 5 years after surgery, and existing taxonomies are insufficient to meet the needs of clinical precision treatment. Thus, robust biomarkers and precise management were urgently required to stratify stage II and III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alongside, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated. Herein, based on multiple large-sample multicenter cohorts and perturbations of the ligand-receptor interaction network, four well-characterized ligand-receptor-driven subtypes (LRDS) were established and further validated. These molecular taxonomies perform with unique heterogeneity in terms of molecular characteristics, immune and mutational landscapes, and clinical features. Specifically, MEIS2, a key LRDS4 factor, performs significant associations with proliferation, invasion, migration, and dismal prognosis of stage II/III CRC, revealing promising directions for prognostic assessment and individualized treatment of CRC patients. Overall, our study sheds novel insights into the implications of intercellular communication on stage II/III CRC from a ligand-receptor interactome perspective and revealed MEIS2 as a key factor in the aggressive progression and prognosis for stage II/III CRC.

X-ray-triggered through-space charge transfer and photochromism in silver nanoclusters

Materials exhibiting X-ray-induced photochromism have consistently piqued the interest of researchers. Exploring the photochromic properties of such materials is valuable for understanding the structural changes and electron transfer processes that occur under high energy radiation, such as X-ray irradiation. Here, a crystalline silver(I) nanocluster synthesized from tert-butylacetylene silver was found to have the ability to exhibit color and photoluminescence changes upon exposure to X-ray radiation. The responsive behavior was observed across a wide temperature range of 100-300 K, with the ability to respond particularly well to soft X-rays (λ > 1 Å) and exhibit light responsiveness to hard X-rays (λ < 1 Å). By combining experimental findings including X-ray diffraction, X-ray photoelectron spectroscopy, electron spin resonance, etc. with theoretical calculations, we have proposed that X-ray irradiation induces electron transfer from chloride (Cl-) located in the center of the silver(I) nanocluster to the surrounding Ag14 in the skeleton. This represents the first documented example in which electron transfer induced by X-ray excitation has been observed, accompanied by a photochromism process, in silver nanoclusters. This study contributes to our understanding of X-ray-induced photochromism and the electron transfer process in silver cluster compounds. It also provides valuable insights and potential design strategies for applications such as photochromism, photoluminescence color change, and photoenergy conversion.

Pirfenidone inhibits TGF-β1-induced metabolic reprogramming during epithelial-mesenchymal transition in non-small cell lung cancer

Metastasis is an important contributor to increased mortality rates in non-small cell lung cancer (NSCLC). The TGF-β signalling pathway plays a crucial role in facilitating tumour metastasis through epithelial-mesenchymal transition (EMT). Glycolysis, a key metabolic process, is strongly correlated with NSCLC metastasis. Pirfenidone (PFD) has been shown to safely and effectively inhibit TGF-β1 in patients with lung diseases. Furthermore, TGF-β1 and glycolysis demonstrate an interdependent relationship within the tumour microenvironment. Our previous study demonstrated that PFD effectively inhibited glycolysis in NSCLC cells, prompting further investigation into its potential antitumour effects in this context. Therefore, the present study aims to investigate the potential antitumour effect of PFD in NSCLC and explore the relationship among TGF-β1, glycolysis and EMT through further experimentation. The antitumour effects of PFD were evaluated using five different NSCLC cell lines and a xenograft tumour model. Notably, PFD demonstrated a significant antitumour effect specifically in highly glycolytic H1299 cells. To elucidate the underlying mechanism, we compared the efficacy of PFD after pretreatment with either TGF-β1 or a TGF-β receptor inhibitor (LY2109761). The energy metabolomics analysis of tumour tissue demonstrated that PFD, a chemosensitizing agent, reduced lactate and ATP production, thereby inhibiting glycolysis and exerting synergistic antineoplastic effects. Additionally, PFD combined with cisplatin targeted TGF-β1 to inhibit glycolysis during EMT and enhanced the chemosensitization of A549 and H1299 cells. The magnitude of the anticancer effect exhibited by PFD was intricately linked to its metabolic properties.