Machine learning value in the diagnosis of vertebral fractures: A systematic review and meta-analysis.

PURPOSE: To evaluate the diagnostic accuracy of machine learning (ML) in detecting vertebral fractures, considering varying fracture classifications, patient populations, and imaging approaches. METHOD: A systematic review and meta-analysis were conducted by searching PubMed, Embase, Cochrane Library, and Web of Science up to December 31, 2023, for studies using ML for vertebral fracture diagnosis. Bias risk was assessed using QUADAS-2. A bivariate mixed-effects model was used for the meta-analysis. Meta-analyses were performed according to five task types (vertebral fractures, osteoporotic vertebral fractures, differentiation of benign and malignant vertebral fractures, differentiation of acute and chronic vertebral fractures, and prediction of vertebral fractures). Subgroup analyses were conducted by different ML models (including ML and DL) and modeling methods (including CT, X-ray, MRI, and clinical features). RESULTS: Eighty-one studies were included. ML demonstrated a diagnostic sensitivity of 0.91 and specificity of 0.95 for vertebral fractures. Subgroup analysis showed that DL (SROC 0.98) and CT (SROC 0.98) performed best overall. For osteoporotic fractures, ML showed a sensitivity of 0.93 and specificity of 0.96, with DL (SROC 0.99) and X-ray (SROC 0.99) performing better. For differentiating benign from malignant fractures, ML achieved a sensitivity of 0.92 and specificity of 0.93, with DL (SROC 0.96) and MRI (SROC 0.97) performing best. For differentiating acute from chronic vertebral fractures, ML showed a sensitivity of 0.92 and specificity of 0.93, with ML (SROC 0.96) and CT (SROC 0.97) performing best. For predicting vertebral fractures, ML had a sensitivity of 0.76 and specificity of 0.87, with ML (SROC 0.80) and clinical features (SROC 0.86) performing better. CONCLUSIONS: ML, especially DL models applied to CT, MRI, and X-ray, shows high diagnostic accuracy for vertebral fractures. ML also effectively predicts osteoporotic vertebral fractures, aiding in tailored prevention strategies. Further research and validation are required to confirm ML's clinical efficacy.

Characteristics and prognostic implications of a cohort of 50 Sertoli-Leydig cell tumors at a single center.

OBJECTIVE: The aim of the study was to investigate the clinical characteristics, therapy strategies and prognosis of Sertoli-Leydig cell tumors (SLCTs). METHODS: A total of 50 cases of ovarian SLCTs were retrospectively analyzed. We performed descriptive statistics to describe baseline characteristics. RESULTS: A total of 70% of SLCT patients were below the age of 45 years. The dominant pathologic types were poor (40%) and moderate (40%) differentiation. Retiform variant tumor is more aggressive and tends to appear in children. According to the 2014 FIGO (the International Federation of Gynecology and Obstetrics) classification, tumors were classified as Stage I (n = 46: well differentiated, n = 4; moderately differentiated, n = 19; poorly differentiated, n = 18; and retiform, n = 5), Stage II (n = 1, moderately differentiated), Stage III (n = 1, poorly differentiated), and Stage IV (n = 2: poorly differentiated, n = 1; and retiform, n = 1). Median follow-up was 58.1 months (2-132 months). A total of 45 patients (90%) achieved clinical remission. Four patients experienced a relapse (34.5 months, range: 7-58) and one patient died of the tumor at 10 months after initial treatment. All patients in grossly Stage IA achieved complete response, irrespective of the presence or absence of staging surgery or chemotherapy. After treatment, five patients successfully gave birth to healthy babies. CONCLUSION: The prognosis for women diagnosed with early stage (I-II) SLCT is generally favorable, especially Stage IA. while those with advanced stages, poorly differentiated, retiform variant, or tumors containing heterologous components exhibit a more aggressive clinical course. Fertility sparing surgery appears to represent a feasible treatment approach for early stage SLCTs.

Advanced core-shell hollow carbon nanofibers for ion and electron accessibility in sodium ion batteries.

One-dimensional core-shell hollow carbon nanofibers (HCNFs) have been synthesized by coaxial electrospinning, deacetylation and carbonization, which exhibit multi-surface properties that enhance electrolyte infiltration and facilitate ion/electron transport. The nitrogen-doped hard carbon outer shell compensates for the low conductivity of amorphous carbon, and the inner core carbon supports the stability of core-shell hollow structures. This unique structure ensures the accessibility of electrons/ions during electrochemical reactions and contributes to the superior rate performance of HCNFs. Ultimately, a high retention rate of 77% of the initial capacity value (0.1 A g-1) was demonstrated at a current density of 2 A g-1. The core-shell hollow structure designed in this work greatly optimizes the sodium transport dynamics.

Association between arterial stiffness index and age-related diseases: A Mendelian randomization study.

Arterial stiffness is an emerging indicator of cardiovascular risk, but its causal relationship with a variety of age-related diseases is unclear. Objective is to assess the causal relationship between arterial stiffness index (ASI) and age-related diseases by Mendelian randomization (MR) analysis. We obtained instrumental variables associated with age-related diseases from genome-wide association studies (GWAS) of 484,598 European individuals, and data for ASI were obtained from the UK Biobank GWAS of 127,127 participants. We used the inverse variance-weighted (IVW) as the primary analysis method. In addition, several sensitivity analyses including MR-Egger, weighted-median (WM), MR-PRESSO and Cochran's Q test were performed to test the robustness of the results. Reverse MR analysis were also performed to assess reverse Causal relationships between age-related diseases and ASI. We verified causal relationship between eight age-related diseases and ASI, of which cardiovascular disease, gallbladder disease, Liver, biliary or pancreas problem, hypertension, joint disorder and esophageal disorder elevated ASI. In contrast, hyperthyroidism or thyrotoxicosis and bowel problem may reduce ASI. This MR analysis reveals causal relationships between ASI and several age-related diseases. ASI is expected to be a potential indicator of health conditions for older populations.

Tackling Event-Based Lip-Reading by Exploring Multigrained Spatiotemporal Clues.

Automatic lip-reading (ALR) is the task of recognizing words based on visual information obtained from the speaker's lip movements. In this study, we introduce event cameras, a novel type of sensing device, for ALR. Event cameras offer both technical and application advantages over conventional cameras for ALR due to their higher temporal resolution, less redundant visual information, and lower power consumption. To recognize words from the event data, we propose a novel multigrained spatiotemporal features learning framework, which is capable of perceiving fine-grained spatiotemporal features from microsecond time-resolved event data. Specifically, we first convert the event data into event frames of multiple temporal resolutions to avoid losing too much visual information at the event representation stage. Then, they are fed into a multibranch subnetwork where the branch operating on low-rate frames can perceive spatially complete but temporally coarse features, while the branch operating on high frame rate can perceive spatially coarse but temporally fine features. Thus, fine-grained spatial and temporal features can be simultaneously learned by integrating the features perceived by different branches. Furthermore, to model the temporal relationships in the event stream, we design a temporal aggregation subnetwork to aggregate the features perceived by the multibranch subnetwork. In addition, we collect two event-based lip-reading datasets (DVS-Lip and DVS-LRW100) for the study of the event-based lip-reading task. Experimental results demonstrate the superiority of the proposed model over the state-of-the-art event-based action recognition models and video-based lip-reading models.

TMP: Temporal Motion Propagation for Online Video Super-Resolution.

Online video super-resolution (online-VSR) highly relies on an effective alignment module to aggregate temporal information, while the strict latency requirement makes accurate and efficient alignment very challenging. Though much progress has been achieved, most of the existing online-VSR methods estimate the motion fields of each frame separately to perform alignment, which is computationally redundant and ignores the fact that the motion fields of adjacent frames are correlated. In this work, we propose an efficient Temporal Motion Propagation (TMP) method, which leverages the continuity of motion field to achieve fast pixel-level alignment among consecutive frames. Specifically, we first propagate the offsets from previous frames to the current frame, and then refine them in the neighborhood, significantly reducing the matching space and speeding up the offset estimation process. Furthermore, to enhance the robustness of alignment, we perform spatial-wise weighting on the warped features, where the positions with more precise offsets are assigned higher importance. Experiments on benchmark datasets demonstrate that the proposed TMP method achieves leading online-VSR accuracy as well as inference speed. The source code of TMP can be found at https://github.com/xtudbxk/TMP.

Increased atmospheric thallium threats to populated areas: A mini review.

Air pollutants combined with Hg, Cd, Cr, Pb, etc. in many global populated areas were studied comprehensively, while our understanding towards thallium (Tl), an extremely toxic heavy metal, remains very limited. Further, the knowledge on atmospheric emissions, distribution, and the hidden risks associated with Tl is of great scarcity. Hence, this work aims to review recent data on significant sources of ambient Tl resulting from industrial activities, including Pb/Zn/Cu/Fe sulfide ore smelting, steel-making, coal burning, and cement production that involves the use of Tl-bearing wastes. Through the examination of Tl emissions and transfer pathways in the atmosphere, it is found that Tl is present at lower than ng/m3 in aerosols and air particulates but can increase to much higher levels even at 1000 µg/m3 in atmospheric fine particulate matters near the mining and smelting industrialized zones located near populated areas. This study highlights the importance of creating a comprehensive emission inventory for Tl, particularly in developing countries where this data is currently lacking. The time has come to develop a precise national emission inventory for Tl in order to prevent and mitigate the risks associated with ambient exposure to this element. This review offers novel insights for the scientific community and policy-makers in establishing effective control and management strategies to curb hidden Tl hazards derived from industrial activities.

The Lack of Causal Link Between Myopia and Intraocular Pressure: Insights from Cross-Sectional Analysis and Mendelian Randomization Study.

OBJECTIVE: This study aimed to explore the potential causal relationship between intraocular pressure (IOP) and myopia. METHODS: The study included 3,459 patients who underwent corneal refractive surgery at our institution between 2021 and 2023. Preoperative data on IOP, spherical equivalent (SE), axial length (AL), and corneal thickness (CCT) were collected. The association between IOP and myopia was investigated through rank correlation analysis, and causal inference was examined using Mendelian randomization (MR) methods, including MR-Egger, weighted median, mode-based estimation, simple mode, and inverse variance weighted (IVW) approaches. Utilizing summary statistics from genome-wide association studies (GWAS), IOP was considered as the exposure, with myopia as the outcome variable. IVW method was employed for the primary analysis, supplemented by sensitivity analyses. RESULTS: Cross-sectional analysis revealed a non-significant association between corrected IOP (cIOP) and myopia (r = -0.019, P = 0.12). MR analysis indicated a non-significant genetic causal relationship between cIOP and myopia under the IVW method (OR = 1.001; 95% CI [0.999-1.003], P = 0.22), a finding corroborated in replication samples (OR = 0.98; 95% CI [0.96-1.00], P = 0.099). CONCLUSION: This study did not find a direct causal link between IOP and the development of myopia. These findings challenge the traditional role attributed to IOP in the progression of myopia and highlight the complex, multifactorial process of myopia development. This provides a new perspective on understanding the intricate mechanisms behind myopia progression.

SIRT1 mediates the inflammatory response of macrophages and regulates the TIMP3/ADAM17 pathway in atherosclerosis.

OBJECTIVE: Macrophage polarization and the resulting phenotype have versatile roles in atherosclerosis. The study aims to decipher the role of SIRT1 in regulating macrophage phenotypes and atherosclerosis development. METHODS: Two mouse lines of SIRT1△Mac/ApoE-/- and SIRT1fl/fl/ApoE-/- were fed with high-fat diet to generate atherosclerotic lesion. Mouse peritoneal macrophages were isolated and transfected with SIRT1-overexpressing vector or vector-null. RESULTS: The SIRT1△Mac/ApoE-/- mice exhibited greater atherosclerotic lesions, stronger immunofluorescence staining for M1-like macrophage marker, iNOS, and weaker immunofluorescence staining for M2-like macrophage marker, Arginase-1, than the SIRT1fl/fl/ApoE-/- littermates. The gene expressions of M1 markers (IL-1ß, IL-6, and iNOS) were increased and those of M2 markers (IL-10 and Arg-1) decreased in both aortic roots and peritoneal macrophages from SIRT1△Mac/ApoE-/- mice, whereas SIRT1 overexpression rectified the changes in M1/M2 expression. A declined expression of TIMP3 with an increased expression of ADAM17 was noted in SIRT1△Mac/ApoE-/- macrophages, whereas SIRT1 overexpression rescued TIMP3 expression and inhibited ADAM17 expression. CONCLUSION: Our data suggest that SIRT1 deficiency may promote macrophage M1 polarization and regulate the TIMP3/ADAM17 pathway thus favoring atherosclerosis development, indicating an anti-atherosclerotic role of macrophage SIRT1.

The Effect of Mulberry Silage Supplementation on the Carcass Fatness and Long-Chain Fatty Acid Composition of Growing Lambs Compared with Traditional Corn Silage.

Lamb meat has become very popular with consumers in recent years due to its nutritional benefits. As a lean red meat, lamb is an important natural source of polyunsaturated and saturated fatty acids, which can be modified by adjustments in livestock feed. This study used proteomic and metabolic analyses to compare a basal ration supplemented with either mulberry silage or corn silage. Supplementation with mulberry silage led to a reduction in subcutaneous carcass fatness compared with corn silage. Additionally, changes in the proteome associated with fatty acid metabolism and oxidation resulted in decreased levels of saturated and trans fatty acids, while significantly increasing the levels of α-linolenic acid (ALA) and oleic acid and reducing linoleic acid content.

A Point Cloud Graph Neural Network for Protein-Ligand Binding Site Prediction.

Predicting protein-ligand binding sites is an integral part of structural biology and drug design. A comprehensive understanding of these binding sites is essential for advancing drug innovation, elucidating mechanisms of biological function, and exploring the nature of disease. However, accurately identifying protein-ligand binding sites remains a challenging task. To address this, we propose PGpocket, a geometric deep learning-based framework to improve protein-ligand binding site prediction. Initially, the protein surface is converted into a point cloud, and then the geometric and chemical properties of each point are calculated. Subsequently, the point cloud graph is constructed based on the inter-point distances, and the point cloud graph neural network (GNN) is applied to extract and analyze the protein surface information to predict potential binding sites. PGpocket is trained on the scPDB dataset, and its performance is verified on two independent test sets, Coach420 and HOLO4K. The results show that PGpocket achieves a 58% success rate on the Coach420 dataset and a 56% success rate on the HOLO4K dataset. These results surpass competing algorithms, demonstrating PGpocket's advancement and practicality for protein-ligand binding site prediction.

SCGB1A1 as a novel biomarker and promising therapeutic target for the management of HNSCC.

Head and neck cancer (HNC) is the sixth most common type of cancer worldwide, and head and neck squamous cell carcinoma (HNSCC) accounts for 90% of HNC cases. Furthermore, HNSCC accounts for 400,000 cancer-associated deaths worldwide each year. However, at present there is an absence of a versatile biomarker that can be used for diagnosis, prognosis evaluation and as a therapeutic target for HNSCC. In the present study, bioinformatics analysis was used to assess the relationship between hub genes and the clinical features of patients with HNSCC. The findings from the bioinformatics analysis were then verified using clinical samples and in vitro experiments. A total of 51 overlapping genes were identified from the intersection of differentially expressed genes and co-expressed genes. The top 10 hub genes were obtained from a protein-protein interaction network of overlapping genes. Among the hub genes, only secretoglobin family 1A member 1 (SCGB1A1) was significantly associated with both overall and disease-free survival. Specifically, upregulated SCGB1A1 expression levels were associated with prolonged overall and disease-free survival. Moreover, the SCGB1A1 expression levels were negatively correlated with drug sensitivity. Notably, it was demonstrated that SCGB1A1 was involved in tumor immunoreaction by affecting the infiltration of cells and checkpoint regulation of immune cells. Additionally, it was shown that SCGB1A1 regulated multiple key cancer-related signaling pathways, including extracellular matrix receptor interaction, transforming growth factor-ß and tumor metabolism signaling pathways. Based on the results of the present study, SCGB1A1 may serve as a novel biomarker for predicting the diagnosis, prognosis and therapeutic effectiveness of certain drugs in patients with HNSCC. Moreover, SCGB1A1 may serve as a potential therapeutic target for the management of HNSCC.

Advances in predictive biomarkers associated with immunotherapy in extensive-stage small cell lung cancer.

Small cell lung cancer (SCLC) is a highly malignant and poor-prognosis cancer, with most cases diagnosed at the extensive stage (ES). Amidst a landscape marked by limited progress in treatment modalities for ES-SCLC over the past few decades, the integration of immune checkpoint inhibitors (ICIs) with platinum-based chemotherapy has provided a milestone approach for improving prognosis, emerging as the new standard for initial therapy in ES-SCLC. However, only a minority of SCLC patients can benefit from ICIs, which frequently come with varying degrees of immune-related adverse events (irAEs). Therefore, it is crucial to investigate predictive biomarkers to screen potential beneficiaries of ICIs, mitigate the risk of side effects, and improve treatment precision. This review summarized potential biomarkers for predicting ICI response in ES-SCLC, with a primary focus on markers sourced from tumor tissue or peripheral blood samples. The former mainly included PD-L1 expression, tumor mutational burden (TMB), along with cellular or molecular components related to the tumor microenvironment (TME) and antigen presentation machinery (APM), molecular subtypes of SCLC, and inflammatory gene expression profiles. Circulating biomarkers predominantly comprised circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), cytokines, plasma autoantibodies, inflammation-related parameters, and blood TMB. We synthesized and analyzed the research progress of these potential markers. Notably, investigations into PD-L1 expression and TMB have been the most extensive, exhibiting preliminary predictive efficacy in salvage immunotherapy; however, consistent conclusions have yet to be reached across studies. Additionally, novel predictive markers developed based on TME composition, APM, transcriptomic and genomic features provide promising tools for precision immunotherapy. Circulating biomarkers offer the advantages of convenience, non-invasiveness, and a comprehensive reflection of tumor molecular characteristics. They may serve as alternative options for predicting immunotherapy efficacy in SCLC. However, there is a scarcity of studies, and the significant heterogeneity in research findings warrants attention.

The emerging role of neutrophil extracellular traps in the progression of rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disease with a complex etiology. Neutrophil extracellular traps (NETs are NETwork protein structures activated by neutrophils to induce the cleavage and release of DNA-protein complexes). Current studies have shown the critical involvement of NETs in the progression of autoimmune diseases, Neutrophils mostly gather in the inflammatory sites of patients and participate in the pathogenesis of autoimmune diseases in various ways. NETs, as the activated state of neutrophils, have attracted much attention in immune diseases. Many molecules released in NETs are targeted autoantigens in autoimmune diseases, such as histones, citrulline peptides, and myeloperoxidase. All of these suggest that NETs have a direct causal relationship between the production of autoantigens and autoimmune diseases. For RA in particular, as a disorder of the innate and adaptive immune response, the pathogenesis of RA is inseparable from the generation of RA. In this article, we investigate the emerging role of NETs in the pathogenesis of RA and suggest that NETs may be an important target for the treatment of inflammatory autoimmune diseases.

HPV 16/18 E7 oncoprotein detection as a promising triage strategy for HPV 16/18-positive patients: A prospective multicenter study with a 2-year follow up.

OBJECTIVE: To explore the effectiveness of HPV 16/18 E7 oncoprotein in detecting high-grade cervical intraepithelial neoplasia (CIN) and predicting disease outcomes in HPV 16/18-positive patients. METHODS: The present study was a cross-sectional study with a 2-year follow up. We collected 915 cervical exfoliated cell samples from patients who tested positive for HPV 16/18 in gynecologic clinics of three tertiary hospitals in Beijing from March 2021 to October 2022 for HPV 16/18 E7 oncoprotein testing. Subsequently, 2-year follow up of 408 patients with baseline histologic CIN1 or below were used to investigate the predictive role of HPV 16/18 E7 oncoprotein in determining HPV persistent infection and disease progression. RESULTS: The positivity rate of the HPV 16/18 E7 oncoprotein assay was 42.06% (249/592) in the inflammation/CIN 1 group and 85.45% (277/324) in the CIN2+ group. For CIN2+ detection, using the HPV 16/18 E7 oncoprotein assay combined with HPV 16/18 testing, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 85.45%, 57.94%, 52.57%, and 87.95%, respectively. During the 2-year follow up, the sensitivity, specificity, PPV, and NPV for predicting persistent HPV infection were 48.44%, 58.21%, 34.64%, and 71.18% in the baseline inflammation and CIN1 group. CONCLUSIONS: As a triage method for high-grade CIN screening in HPV 16/18-positive patients, HPV 16/18 E7 oncoprotein demonstrated a relatively high NPV, making it suitable for clinical use in triaging HPV 16/18-positive cases and potentially reducing the colposcopic referral rate. HPV 16/18 E7 oncoprotein exhibited a preferably predictive value in determining HPV infection outcomes and disease progression.

Melatonin alleviates apple replant disease by regulating the endophytic microbiome of roots and phloridzin accumulation.

Melatonin administration is an environmentally effective strategy to mitigate apple replant disease (ARD), but its mechanism of action is unknown. This study investigated the protective effect of melatonin on ARD and the underlying mechanism. In field experiments, melatonin significantly reduced phloridzin levels in apple roots and rhizosphere soil. A correlation analysis indicated that a potential antagonistic interaction between melatonin and phloridzin was crucial for improving soil physicochemical properties, increasing the diversity of endophytic bacterial communities in roots of apple seedlings, and promoting mineral element absorption by the plants. Melatonin also reduced the abundance of Fusarium in roots. The ability of melatonin to reduce phloridzin levels both in soil and in plants was also demonstrated in a pot experiment. Azovibrio were specifically recruited in response to melatonin and their abundance was negatively correlated with phloridzin levels. Fusarium species that have a negative impact on plant growth were also inhibited by melatonin. Our results show that melatonin improves the rhizosphere environment as well as the structure of the endophytic microbiota community, by reducing phloridzin levels in rhizosphere soil and roots. These regulatory effects of melatonin support its use to improve the physiological state of plants under ARD conditions and thereby overcome the barriers of perennial cropping systems.

Cardiovascular and diabetes outcomes among patients with obesity and type 2 diabetes after metabolic bariatric surgery or glucagon-like peptide 1 receptor agonist treatment.

BACKGROUND: With the increasing prevalence of obesity and type 2 diabetes, the availability of different treatment options remains essential. Studies comparing the outcomes of glucagon-like peptide 1 receptor agonists with those of metabolic bariatric surgery in patients with type 2 diabetes and obesity are lacking. METHODS: Using propensity score matching, based on data from several nationwide clinical registries, patients who underwent primary metabolic bariatric surgery (Roux-en-Y gastric bypass or sleeve gastrectomy) were matched with patients who received glucagon-like peptide 1 receptor agonists. Outcome measures included the occurrence of major cardiovascular events, microvascular complications, and potential side effects (alcohol/substance abuse, self-harm, and fractures). RESULTS: Over a mean follow-up of 7 years, major cardiovascular events occurred in 191 of 2039 patients (cumulative incidence 14.5%) in the surgery group compared with 247 of 2039 patients (19.6%) in the glucagon-like peptide 1 receptor agonist group (HR 0.75 (95% c.i. 0.62 to 0.91), P = 0.003). Patients in the surgery group had lower haemoglobin A1c values 5 years after treatment (mean difference 9.82 (95% c.i. 8.51 to 11.14) mmol/mol, P < 0.001) and fewer microvascular complications (retinopathy HR 0.88 (95% c.i. 0.79 to 0.99), P = 0.039; nephropathy HR 0.72 (95% c.i. 0.66 to 0.80), P < 0.001; and neuropathy or leg ulcers HR 0.82 (95% c.i. 0.74 to 0.92), P < 0.001), but a higher risk of alcohol/substance abuse (HR 2.56 (95% c.i. 1.87 to 3.50), P < 0.001), self-harm (HR 1.41 (95% c.i. 1.17 to 1.71), P < 0.001), and fractures (HR 1.86 (95% c.i. 1.11 to 3.12), P = 0.019). CONCLUSION: Compared with glucagon-like peptide 1 receptor agonist treatment, metabolic bariatric surgery is associated with superior metabolic outcomes and a lower risk of major cardiovascular events in patients with type 2 diabetes and obesity, but a higher risk of alcohol/substance abuse, self-harm, and fractures.

Exosomes in esophageal cancer: Promising nanocarriers in cancer progression, diagnosis, prognosis, and therapy.

Esophageal cancer (EC) is one of the most fatal cancers all over the world. Sensitive detection modalities for early-stage EC and efficient treatment methods are urgently needed for the improvement of the prognosis of EC. Exosomes are small vesicles for intercellular communication, mediating many biological responses including cancer progression, which are not only promising biomarkers for diagnosis and prognosis but also therapeutic tools for EC. This review provides an overview of the relationships between exosomes and EC progression, as well as the application of exosomes in the diagnosis, prognosis, and treatment of EC. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

An Oxidative Stress Nano-Amplifier for Improved Tumor Elimination and Combined Immunotherapy.

Amplifying oxidative stress to disrupt intracellular redox homeostasis can accelerate tumor cell death. In this work, an oxidative stress amplifier (PP@T) is prepared for enhanced tumor oxidation therapy to reduce tumor growth and metastases. The nano-amplifier has been successfully constructed by embedding MTH1 inhibitor (TH588) in the PDA-coated porphyrin metal-organic framework PCN-224. The controllable-released TH588 is demonstrated from pores can hinder MTH1-mediated damage-repairing process by preventing the hydrolysis of 8-oxo-dG, thereby amplifying oxidative stress and exacerbating the oxidative DNA damage induced by the sonodynamic therapy of PP@T under ultrasound irradiation. Furthermore, PP@T can effectively induce immunogenic cell death to trigger systemic anti-tumor immune response. When administered in combination with immune checkpoint blockade, PP@T not only impedes the progression of the primary tumor but also achieves obvious antimetastasis in breast cancer murine models, including orthotopic and artificial whole-body metastasis models. Furthermore, the nanoplatform also provides photoacoustic imaging for in vivo treatment guidance. In conclusion, by amplifying oxidative stress and reactive oxygen species sensitized immunotherapy, this image-guided nanosystem shows potential for highly specific, effective combined therapy against tumor cells with negligible side-effects to normal cells which will provide a new insight for precise tumor treatment.

Mendelian Randomization Studies: Opening a New Window in the Study of Metabolic Diseases and Chronic Kidney Disease.

It is widely recognized that a strong correlation exists between metabolic diseases and chronic kidney disease (CKD). Based on bibliometric statistics, the overall number of Mendelian randomization (MR) analysis in relation to metabolic diseases and CKD has increased since 2005. In recent years, this topic has emerged as a significant area of research interest. In clinical studies, RCTs are often limited due to the intricate causal interplay between metabolic diseases and CKD, which makes it difficult to ascertain the precise etiology of these conditions definitively. In MR studies, genetic variation is incorporated as an instrumental variable (IV). They elucidate the possible causal relationships between associated risk factors and disease risks by including individual innate genetic markers. It is widely believed that MR avoids confounding and can reverse effects to the greatest extent possible. As an increasingly popular technology in the medical field, MR studies have become a popular technology in causal relationships investigation, particularly in epidemiological etiology studies. At present, MR has been widely used for the investigation of medical etiologies, drug development, and decision-making in public health. The article aims to offer insights into the causal relationship between metabolic diseases and CKD, as well as strategies for prevention and treatment, through a summary of MR-related research on these conditions.