2D Reconfigurable Memory Device Enabled by Defect Engineering for Multifunctional Neuromorphic Computing.

In this era of artificial intelligence and Internet of Things, emerging new computing paradigms such as in-sensor and in-memory computing call for both structurally simple and multifunctional memory devices. Although emerging two-dimensional (2D) memory devices provide promising solutions, the most reported devices either suffer from single functionalities or structural complexity. Here, this work reports a reconfigurable memory device (RMD) based on MoS2/CuInP2S6 heterostructure, which integrates the defect engineering-enabled interlayer defects and the ferroelectric polarization in CuInP2S6, to realize a simplified structure device for all-in-one sensing, memory and computing. The plasma treatment-induced defect engineering of the CuInP2S6 nanosheet effectively increases the interlayer defect density, which significantly enhances the charge-trapping ability in synergy with ferroelectric properties. The reported device not only can serve as a non-volatile electronic memory device, but also can be reconfigured into optoelectronic memory mode or synaptic mode after controlling the ferroelectric polarization states in CuInP2S6. When operated in optoelectronic memory mode, the all-in-one RMD could diagnose ophthalmic disease by segmenting vasculature within biological retinas. On the other hand, operating as an optoelectronic synapse, this work showcases in-sensor reservoir computing for gesture recognition with high energy efficiency.

Utility of Second-look Ultrasonography in Distinguishing BI-RADS 4 Calcifications Detected on Mammography: An observational study.

This study aimed to assess the utility of second-look ultrasonography (US) in differentiating breast imaging reporting and data system (BI-RADS) 4 calcifications initially detected on mammography (MG). BI-RADS 4 calcifications have a wide range of positive predictive values. We hypothesized that second-look US would help distinguish BI-RADS 4 calcifications without clinical manifestations and other abnormalities on MG. This study included 1622 pure BI-RADS 4 calcifications in 1510 women (112 patients with bilateral calcifications). The cases were randomly divided into training (85%) and testing (15%) datasets. Two nomograms were developed to differentiate BI-RADS 4 calcifications in the training dataset: the MG-US nomogram, based on multifactorial logistic regression and incorporated clinical information, MG, and second-look US characteristics, and the MG nomogram, based on clinical information and mammographic characteristics. Calibration of the MG-US nomogram was performed using calibration curves. The discriminative ability and clinical utility of both nomograms were compared using the area under the receiver operating characteristic curve (AUC) and the decision analysis curve (DCA) in the test dataset. The clinical information and imaging characteristics were comparable between the training and test datasets. The bias-corrected calibration curves of the MG-US nomogram closely approximate the ideal line for both datasets. In the test dataset, the MG-US nomogram exhibited a higher AUC than the MG nomogram (0.899 vs 0.852, P = .01). DCA demonstrated the superiority of the MG-US nomogram over the MG nomogram. Second-look US features, including ultrasonic calcifications, lesions, and moderate or marked color flow, were valuable for distinguishing BI-RADS 4 calcifications without clinical manifestations and other abnormalities on MG.

Advancing driver fatigue detection in diverse lighting conditions for assisted driving vehicles with enhanced facial recognition technologies.

Against the backdrop of increasingly mature intelligent driving assistance systems, effective monitoring of driver alertness during long-distance driving becomes especially crucial. This study introduces a novel method for driver fatigue detection aimed at enhancing the safety and reliability of intelligent driving assistance systems. The core of this method lies in the integration of advanced facial recognition technology using deep convolutional neural networks (CNN), particularly suited for varying lighting conditions in real-world scenarios, significantly improving the robustness of fatigue detection. Innovatively, the method incorporates emotion state analysis, providing a multi-dimensional perspective for assessing driver fatigue. It adeptly identifies subtle signs of fatigue in rapidly changing lighting and other complex environmental conditions, thereby strengthening traditional facial recognition techniques. Validation on two independent experimental datasets, specifically the Yawn and YawDDR datasets, reveals that our proposed method achieves a higher detection accuracy, with an impressive 95.3% on the YawDDR dataset, compared to 90.1% without the implementation of Algorithm 2. Additionally, our analysis highlights the method's adaptability to varying brightness levels, improving detection accuracy by up to 0.05% in optimal lighting conditions. Such results underscore the effectiveness of our advanced data preprocessing and dynamic brightness adaptation techniques in enhancing the accuracy and computational efficiency of fatigue detection systems. These achievements not only showcase the potential application of advanced facial recognition technology combined with emotional analysis in autonomous driving systems but also pave new avenues for enhancing road safety and driver welfare.

Beyond Mechanical Protection: The Electron-Shielding Effect of SWCNT for the Stabilized SiO Interface.

The single-walled carbon nanotube (SWCNT) commonly serves as a conductive additive for SiO-based anode materials due to the excellent conductivity and mechanical properties. However, the potential action mechanisms for the SWCNT beyond conductivity and mechanical features have rarely been studied. Herein, an interfacial electron-shielding effect and preferential adsorption to the electrolyte components for the SWCNT are revealed through a series of advanced characterizations and density functional theory (DFT) simulations. It can be determined that SWCNT networks could restrict the transmission of the electron from SiO interface to electrolyte with the reduced decomposition, because of the typical axial conductivity of the SWCNT. Moreover, the SWCNT shows stronger adsorption energy for LiPF6 and ethylene carbonate (EC) molecules, rather than nonselectivity of traditional carbon additives, facilitating the generation of inorganic-rich and denser solid electrolyte interface (SEI) film. As a result, benefiting from the electron-shielding effect, preferential adsorption, and mechanical protection, the SWCNT endows the SiO@C anode with a higher average Coulombic efficiency (CE) value of 99.4% over 100 cycles and a long cycling stability.

Melt Compounding of Poly(lactic acid)-Based Composites: Blending Strategies, Process Conditions, and Mechanical Properties.

Polylactic acid (PLA), derived from renewable resources, has the advantages of rigidity, thermoplasticity, biocompatibility, and biodegradability, and is widely used in many fields such as packaging, agriculture, and biomedicine. The excellent processability properties allow for melt processing treatments such as extrusion, injection molding, blow molding, and thermoforming in the preparation of PLA-based materials. However, the low toughness and poor thermal stability of PLA limit its practical applications. Compared with pure PLA, conditions such as processing technology, filler, and crystallinity affect the mechanical properties of PLA-based materials, including tensile strength, Young's modulus, and elongation at break. This review systematically summarizes various technical parameters for melt processing of PLA-based materials and further discusses the mechanical properties of PLA homopolymers, filler-reinforced PLA-based composites, PLA-based multiphase composites, and reactive composite strategies for PLA-based composites.

Screening Methods for Cervical Cancer.

Cervical cancer seriously affects the health of women worldwide. Persistent infection of high-risk HPV (Human Papilloma Virus) can lead to cervical cancer. There is a great need for timely and efficient screening methods for cervical cancer. The current screening methods for cervical cancer are mainly based on cervical cytology and HPV testing. Cervical cytology is made of Pap smear and liquid-based cytology, while HPV testing is based on immunological and nucleic acid level detection methods. This review introduces cervical cancer screening methods based on cytology and human papillomavirus testing in detail. The advantages and limitations of the screening methods are also summarized and compared.

Quality markers of Polygala fallax Hemsl decoction based on qualitative and quantitative analysis combined with network pharmacology and chemometric analysis.

INTRODUCTION: Polygala fallax Hemsl (PFH) is a widely used herbal medicine in Guangxi, China. At present, research on PFH mainly focuses on extraction technology and cultivation, lacking quality control standards for systematic evaluation. OBJECTIVES: The study aimed to assess the quality of PFH from different sources and to predict markers that would help assess quality. METHODS: Fingerprinting of 15 batches of PFH samples was performed by ultra-high performance liquid chromatography (UPLC) and similarity was assessed using hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discrimination (OPLS-DA). Differential components were screened by mathematical analysis, and a "component-target-pathway" network map was constructed in combination with network pharmacology, quality markers (Q-markers) of PFH were predicted, and quantitative analysis was performed. RESULTS: Fifteen batches were fingerprinted for PFH, with 11 common peaks, and peak 5 was identified as 4-hydroxybenzoic acid, which was generally consistent with the results of HCA, PCA, and OPLS-DA. Network pharmacology screened 18 potential compounds, 45 core targets, and 20 key pathways, integrating fingerprinting, pattern recognition, and network pharmacology methods. One of the potential Q-markers that can identify the principle of testability, efficacy, and specificity is 4-hydroxybenzoic acid, whose content ranges from 0.0188 to 1.4517 mg/g. CONCLUSION: The potential Q-markers of PFH were predicted by integrating fingerprinting, pattern recognition, and network pharmacological analysis, which provided a scientific basis for the overall control and evaluation of the quality of PFH and a theoretical reference for the study of the quality standard of multi-base traditional Chinese medicine.

Epitope binning for multiple antibodies simultaneously using mammalian cell display and DNA sequencing.

Epitope binning, an approach for grouping antibodies based on epitope similarities, is a critical step in antibody drug discovery. However, conventional methods are complex, involving individual antibody production. Here, we established Epitope Binning-seq, an epitope binning platform for simultaneously analyzing multiple antibodies. In this system, epitope similarity between the query antibodies (qAbs) displayed on antigen-expressing cells and a fluorescently labeled reference antibody (rAb) targeting a desired epitope is analyzed by flow cytometry. The qAbs with epitope similar to the rAb can be identified by next-generation sequencing analysis of fluorescence-negative cells. Sensitivity and reliability of this system are confirmed using rAbs, pertuzumab and trastuzumab, which target human epidermal growth factor receptor 2. Epitope Binning-seq enables simultaneous epitope evaluation of 14 qAbs at various abundances in libraries, grouping them into respective epitope bins. This versatile platform is applicable to diverse antibodies and antigens, potentially expediting the identification of clinically useful antibodies.

Dual-Function Electrolyte Additive Design for Long Life Alkaline Zinc Flow Batteries.

Alkaline zinc-based flow batteries (AZFBs) have emerged as a promising electrochemical energy storage technology owing to Zn abundance, high safety, and low cost. However, zinc dendrite growth and the formation of dead zinc greatly impede the development of AZFBs. Herein, a dual-function electrolyte additive strategy is proposed to regulate zinc nucleation and mitigate the hydroxide corrosion of zinc depositions for stable AZFBs. This strategy, as exemplified by urea, introduces an electrolyte additive to coordinate with Zn2+/Zn with proper strength, slowing zinc deposition kinetics to induce uniform nucleation and protecting the deposited zinc surface from attack by hydroxide ions through preferable adsorption. The zincate complexes with urea are identified to be Zn(OH)2(urea)(H2O)2 and Zn2(OH)4(H2O)4(urea), which exhibit slow zinc deposition kinetics, allowing instantaneous nucleation. Calculation results reveal an additional energy barrier of 1.29 eV for the subsequent adsorption of an OH- group when a urea molecule absorbs on the zinc cluster, significantly mitigating the formation of dead zinc. Consequently, prolonged cell cycling of the prototype alkaline zinc-iron flow battery demonstrates stable operation for over 130 h and an average coulombic efficiency of 98.5%. It is anticipated that this electrolyte additive strategy will pave the way for developing highly stable AZFBs.

Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach.

Background: In the central nervous system, glioma is the most common malignant tumor, and patients have a poor prognosis. Identification of novel marker genes and establishment of prognostic models are important for early diagnosis and prognosis determination. Methods: Download glioma data from the CGGA and TCG databases. Application of bioinformatics to analyze the impact of CYBB on the clinicopathological characteristics, immunological features and prognosis of gliomas. Using single-cell sequencing data from 7 glioblastoma patients in the CGGA database, the role of CYBB in the tumor microenvironment was analyzed. In addition, a prognostic model was constructed based on CYBB high and low differentially expressed genes and mitochondrial genes. Results: The expression of CYBB is closely related to various clinical features, immune cell infiltration level, immune checkpoint and survival time of patients. A 10-gene prediction model was constructed based on the differentially expressed genes of low and high CYBB and mitochondria-related genes. Glioma patients with higher risk scores had significantly lower survival probabilities. Receiver operating characteristic curves and nomograms were plotted over time to show the predictive accuracy and predictive value of the 10-gene prognostic model. Conclusions: Our study shows that CYBB is strongly correlated with clinical characteristics features and prognosis of glioma patients, and can be used as a potential therapeutic target. Prognostic models based on CYBB and mitochondrial genes have good performance in predicting prognosis of glioma patients.

NAD-Dependent Protein Deacetylase Sirtuin-1 Mediated Mitophagy Regulates Early Brain Injury After Subarachnoid Hemorrhage.

Background: This study focuses on the role of SIRT1 in neuroinflammation caused by early brain injury (EBI) after subarachnoid hemorrhage (SAH), and explores its mechanism in mitophagy after SAH. Methods: C57BL/6J mice and primary microglia SAH in vivo and in vitro models were constructed to explore the expression level of SIRT1 in neuroinflammation after SAH. Subsequently, the brain edema content, blood-brain barrier (BBB) damage and neurological function scores of the mice were observed after using the SIRT1 inhibitor EX-527. q-PCR and Western blot were used to detect relevant genes and proteins, and enzyme-linked immunosorbent assay (ELISA) was used to detect the levels of IL-6, IL-1ß, and TNF-α inflammatory factors. Immunofluorescence staining was used to observe the positive level of SIRT1 and the degree of mitochondria-lysosome fusion, and transmission electron microscopy was used to observe mitochondrial damage and autophagosome levels. Results: In in vivo and in vitro experiments, we found that SIRT1 expression increased after SAH, and neurological deficits, brain edema, and blood-brain barrier damage after SAH were aggravated. Inhibiting SIRT1 further aggravates the aforementioned damage. In addition, EX-527 can also inhibit the level of mitophagy and aggravate neuroinflammation after SAH. Conclusion: Our results indicated that SIRT1 promotes mitophagy and alleviates neuroinflammation after SAH.

Oscillatory Neural Network-Based Ising Machine Using 2D Memristors.

Neural networks are increasingly used to solve optimization problems in various fields, including operations research, design automation, and gene sequencing. However, these networks face challenges due to the nondeterministic polynomial time (NP)-hard issue, which results in exponentially increasing computational complexity as the problem size grows. Conventional digital hardware struggles with the von Neumann bottleneck, the slowdown of Moore's law, and the complexity arising from heterogeneous system design. Two-dimensional (2D) memristors offer a potential solution to these hardware challenges, with their in-memory computing, decent scalability, and rich dynamic behaviors. In this study, we explore the use of nonvolatile 2D memristors to emulate synapses in a discrete-time Hopfield neural network, enabling the network to solve continuous optimization problems, like finding the minimum value of a quadratic polynomial, and tackle combinatorial optimization problems like Max-Cut. Additionally, we coupled volatile memristor-based oscillators with nonvolatile memristor synapses to create an oscillatory neural network-based Ising machine, a continuous-time analog dynamic system capable of solving combinatorial optimization problems including Max-Cut and map coloring through phase synchronization. Our findings demonstrate that 2D memristors have the potential to significantly enhance the efficiency, compactness, and homogeneity of integrated Ising machines, which is useful for future advances in neural networks for optimization problems.

Integrative analysis of bulk RNA-seq and scRNA-seq data indicates the prognostic and immunologic values of SERPINH1 in glioma.

BACKGROUND: SERPINH1 is abnormally expressed in multiple cancers and is associated with malignant progression. However, few reports detail its role in the etiopathogenesis of glioma. Hence, the aim of this article was to investigate the potential value of SERPINH1 in glioma using an integrative analysis. METHODS: Data of RNA-seq and scRNA-seq was obtained and evaluated using online databases. The expression of SERPINH1 was confirmed by qRT-PCR and immunohistochemistry. The prognostic value of SERPINH1 was evaluated using univariate and multivariate Cox regression analyses. SERPINH1-related signaling pathways and the interaction of SERPINH1 with immunity were also investigated. RESULTS: SERPINH1 exhibited a markedly elevated expression in glioma compared to normal brain tissues in the online databases. Similar results were confirmed by qRT-PCR and immunohistochemistry. SERPINH1 was found to be an independent prognosis factor, and high expression of SERPINH1 indicated poor survival. Moreover, a nomogram was constructed to predict prognosis more accurately and intuitively. GSEA analysis showed that SERPINH1 was involved in seven signaling pathways, including JAK-STAT pathway. Further analysis indicated SERPINH1 was significantly associated with immunity, especially in low-grade glioma. Additionally, an examination of scRNA-seq data revealed that SERPINH1 was primarily expressed in T cells of the CD4+ and CD8+ subsets. CONCLUSIONS: SERPINH1 is a key biomarker of glioma prognosis and is immunologically relevant, which provides additional options for targeted therapy of glioma.

Repressing miR-23a promotes the transdifferentiation of pancreatic α cells to ß cells via negatively regulating the expression of SDF-1α.

Pancreatic ß-cell failure is a pathological feature in type 1 diabetes. One promising approach involves inducing transdifferentiation of related pancreatic cell types, specifically α cells that produce glucagon. The chemokine stromal cell-derived factor-1 alpha (SDF-1α) is implicated in pancreatic α-to-ß like cell transition. Here, the serum level of SDF-1α was lower in T1D with C-peptide loss, the miR-23a was negatively correlated with SDF-1α. We discovered that exosomal miR-23a, secreted from ß cells, functionally downregulates the expression of SDF-1α, leading to increased Pax4 expression and decreased Arx expression in vivo. Adenovirus-vectored miR-23a sponge and mimic were constructed to further explored the miR-23a on pancreatic α-to-ß like cell transition in vitro, which yielded results consistent with our cell-based assays. Suppression of miR-23a upregulated insulin level and downregulated glucagon level in STZ-induced diabetes mice models, effectively promoting α-to-ß like cell transition. Our findings highlight miR-23a as a new therapeutic target for regenerating pancreatic ß cells from α cells.

Investigating fungal community characteristics in co-composted cotton stalk and various livestock manure products.

Agricultural wastes, comprising cotton straw and livestock manure, can be effectively managed through aerobic co-composting. Nevertheless, the quality and microbial characteristics of co-composting products from different sources remain unclear. Therefore, this study utilized livestock manure from various sources in Xinjiang, China, including herbivorous sheep manure (G), omnivorous pigeon manure (Y), and pigeon-sheep mixture (GY) alongside cotton stalks, for a 40-day co-composting process. We monitored physicochemical changes, assessed compost characteristics, and investigated fungal community. The results indicate that all three composts met established composting criteria, with compost G exhibiting the fastest microbial growth and achieving the highest quality. Ascomycota emerged as the predominant taxon in three compost products. Remarkably, at the genus level, the biomarker species for G, Y, and GY are Petromyces and Cordyceps, Neurospora, and Neosartorya, respectively. Microorganisms play a pivotal role in organic matter degradation, impacting nutrient composition, demonstrating significant potential for the decomposition and transformation of compost components. Redundancy analysis indicates that potassium, total organic carbon, and C:N are key factors influencing fungal communities. This study elucidates organic matter degradation in co-composting straw and livestock manure diverse sources, optimizing treatment for efficient agricultural waste utilization and sustainable practices.

Glucose regulates the HMGB1 signaling pathway through SIRT1 in glioma.

BACKGROUND: Glucose is a fundamental substance for numerous cancers, including glioma. However, its influence on tumor cells regulatory mechanisms remains uncertain. SIRT1 is a regulator of deacetylation and a key player in the progression of malignant tumors. The objective of this study was to examine the role of glucose and SIRT1 in glioma. METHODS: This study investigated the association of SIRT1 expression with clinicopathological features and prognosis in glioma patients using the TCGA database. The Western blotting technique was used to identify the expression of SIRT1 protein in glioma cells. The study also examined the impact of differing glucose concentrations on the biological functions of glioma cells. The study investigated the expression of SIRT1 and HMGB1 signaling pathways in glioma. Additionally, resilience experiments were conducted utilizing SRT1720. RESULTS: SIRT1 is a gene that suppresses tumors and is low expressed in gliomas. Low expression of this gene is strongly linked to a poor prognosis in patients with glioma. High concentrations of glucose can promote the proliferation, migration, and invasion of glioma cells, while also inhibiting apoptosis. The findings of this mechanistic study provide evidence that glucose can down-regulate SIRT1 expression, leading to increased levels of acetylated HMGB1. This in turn promotes the ex-nuclear activation of HMGB1 and associated signaling pathways, ultimately driving glioma malignancy. CONCLUSION: Glucose has the ability to regulate the HMGB1 associated signaling pathway through SIRT1, thus promoting glioma progression. This holds significant research value.

Non-sweep DC component estimation method for a virtual-carrier assisted Kramers-Kronig receiver.

The Kramers-Kronig (KK) receiver has attracted much attention in short-range optical interconnection because of its ability to recover the phase of the signal from the intensity information through KK algorithm. In high-speed KK systems, such as virtual-carrier (VC) assisted ones, an alternating current (AC) coupled photo-detector (PD) is preferred due to relaxing the requirements of analog-to-digital converter (ADC) and electronic amplifier by filtering direct current (DC) component. However, the loss of the DC component will cause the KK algorithm to break down, so it is necessary to accurately recover DC value in the digital domain with multiple-sweep. In this paper, we propose what we believe is a novel non-sweep DC component estimation scheme based on optimized digital carrier-to-signal power ratio (OD-CSPR) method, which can accurately estimate the DC component with only 3-4 iterations in the scenario of VC-assisted KK receiver optical transmission. The scheme utilizes the one-dimensional search optimization algorithm based on golden section search and parabolic interpolation without sweeping. The simulation and experimental results of the proposed non-sweep OD-CSPR method show that the DC component can be estimated accurately in a large CSPR range, and the system performance is close to that of the conventional DC-sweep method. Compared with the typical defined digital CSPR (DD-CSPR) based optimization method, the proposed one can realize optical signal-to-noise ratio (OSNR) gains of 0.9 dB in the back-to-back (B2B) and 0.7 dB under 80 km fiber transmission scenarios respectively with a total bit rate of 160Gb/s.

Resveratrol ameliorates glioblastoma inflammatory response by reducing NLRP3 inflammasome activation through inhibition of the JAK2/STAT3 pathway.

OBJECTIVES: The aim of this study was to investigate the anti-tumor effect of resveratrol (RSV) on glioblastoma (GBM) and its specific mechanism in improving the inflammatory response of the tumor microenvironment. The tumor microenvironment of GBM is highly neuroinflammatory, inducing tumor immunosuppression. Therefore, ameliorating the inflammatory response is an important focus for anti-tumor research. METHODS: The anti-tumor effect of RSV on GBM was demonstrated through in vitro cellular assays, including CCK-8, EdU, PI staining, Transwell, wound healing assay, and flow cytometry. Potential mechanisms of RSV's anti-GBM effects were identified through network pharmacological analysis. In addition, the relationship of RSV with the JAK2/STAT3 signaling pathway and the inflammasome NLRP3 was verified using Western blot. RESULTS: RSV significantly inhibited cell viability in GBM cell lines LN-229 and U87-MG. Furthermore, it inhibited the proliferation and invasive migration ability of GBM cells, while promoting apoptosis. Network pharmacological analysis revealed a close association between the anti-GBM effects of RSV and the JAK/STAT signaling pathway, as well as inflammatory responses. Western blot analysis confirmed that RSV inhibited the over-activation of the inflammasome NLRP3 through the JAK2/STAT3 signaling pathway. Partial reversal of RSV's inhibition of inflammasome NLRP3 was observed with the addition of the JAK/STAT agonist RO8191. CONCLUSIONS: In vitro, RSV can exert anti-tumor effects on GBM and improve the inflammatory response in the GBM microenvironment by inhibiting the activation of the JAK2/STAT3 signaling pathway. These findings provide new insights into potential therapeutic targets for GBM.

A mendelian randomization study investigates the causal relationship between immune cell phenotypes and cerebral aneurysm.

Background: Cerebral aneurysms (CAs) are a significant cerebrovascular ailment with a multifaceted etiology influenced by various factors including heredity and environment. This study aimed to explore the possible link between different types of immune cells and the occurrence of CAs. Methods: We analyzed the connection between 731 immune cell signatures and the risk of CAs by using publicly available genetic data. The analysis included four immune features, specifically median brightness levels (MBL), proportionate cell (PC), definite cell (DC), and morphological attributes (MA). Mendelian randomization (MR) analysis was conducted using the instrumental variables (IVs) derived from the genetic variation linked to CAs. Results: After multiple test adjustment based on the FDR method, the inverse variance weighted (IVW) method revealed that 3 immune cell phenotypes were linked to the risk of CAs. These included CD45 on HLA DR+NK (odds ratio (OR), 1.116; 95% confidence interval (CI), 1.001-1.244; p = 0.0489), CX3CR1 on CD14- CD16- (OR, 0.973; 95% CI, 0.948-0.999; p = 0.0447). An immune cell phenotype CD16- CD56 on NK was found to have a significant association with the risk of CAs in reverse MR study (OR, 0.950; 95% CI, 0.911-0.990; p = 0.0156). Conclusion: Our investigation has yielded findings that support a substantial genetic link between immune cells and CAs, thereby suggesting possible implications for future clinical interventions.

Comprehensive Analysis of the SUMO-related Signature: Implication for Diagnosis, Prognosis, and Immune Therapeutic Approaches in Cervical Cancer.

SUMOylation, an important post-translational protein modification, plays a critical role in cancer development and immune processes. This study aimed to construct diagnostic and prognostic models for cervical cancer (CC) using SUMOylation-related genes (SRGs) and explore their implications for novel clinical therapies. We analyzed the expression profiles of SRGs in CC patients and identified 15 SRGs associated with CC occurrence. After the subsequent qPCR verification of 20 cases of cancer and adjacent tissues, 13 of the 15 SRGs were differentially expressed in cancer tissues. Additionally, we identified molecular markers associated with the prognosis and recurrence of CC patients, based on SRGs. Next, a SUMOScore, based on SRG expression patterns, was generated to stratify patients into different subgroups. The SUMOScore showed significant associations with the tumor microenvironment, immune function features, immune checkpoint expression, and immune evasion score in CC patients, highlighting the strong connection between SUMOylation factors and immune processes. In terms of immune therapy, our analysis identified specific chemotherapy drugs with higher sensitivity in the subgroups characterized by high and low SUMOScore, indicating potential treatment options. Furthermore, we conducted drug sensitivity analysis to evaluate the response of different patient subgroups to conventional chemotherapy drugs. Our findings revealed enrichment of immune-related pathways in the low-risk subgroup identified by the prognostic model. In conclusion, this study presents diagnostic and prognostic models based on SRGs, accompanied by a comprehensive index derived from SRGs expression patterns. These findings offer valuable insights for CC diagnosis, prognosis, treatment, and immune-related analysis.