Meta-Analysis of Platelet-Rich Plasma in the Treatment of Lower Extremity Venous Ulcer.

Objectives: The therapeutic effect of platelet-rich plasma on lower extremity venous ulcers was systematically analyzed. Methods: A computerized system search was conducted to screen literature that met the inclusion criteria using the method of "subject words + free words." Keywords included "platelet-rich plasma," "lower extremity venous disease," "lower extremity chronic venous insufficiency," "venous ulcer," and "lower extremity venous ulcer." Literature that met the inclusion criteria was searched in four commonly used Chinese databases (HowNet, Chinese biomedical literature, Wanfang, and VIP) and three commonly used foreign databases (Embase, PubMed, and Cochrane Library). The search period extended from the establishment of the databases to December 2021. After extracting the relevant data, a meta-analysis was performed using RevMan 5.3 software to compare the overall effective rate and adverse effects of platelet-rich plasma in the treatment of lower extremity venous ulcers. Results: The meta-analysis of the overall efficacy rate in the four selected papers showed no heterogeneity among the studies (P = .35 > 0.1, I2 = 0% < 50%); therefore, a fixed-effect model was used to combine the statistical data. The software analysis results indicated a significant difference in the overall efficacy rate between the experimental group and the control group (OR = 2.09, 95% CI = 1.23-3.34, P = .002), with the experimental group showing better results than the control group. The analysis of the four selected papers also suggested potential differences in adverse reactions between the two groups after treatment, but the comparison of safety differences was not significant (OR = 2.13, 95% CI = 0.45-6.79, P = .17). Conclusion: Platelet-rich plasma is effective in the treatment of lower extremity venous ulcers; however, there is no clear safety advantage. This finding needs to be confirmed by large-scale, multi-center research.

EMFSA: Emoji-based multifeature fusion sentiment analysis.

Short texts on social platforms often suffer from insufficient emotional semantic expressions, sparse features, and polysemy. To enhance the accuracy achieved by sentiment analysis for short texts, this paper proposes an emoji-based multifeature fusion sentiment analysis model (EMFSA). The model mines the sentiments of emojis, topics, and text features. Initially, a pretraining method for feature extraction is employed to enhance the semantic expressions of emotions in text by extracting contextual semantic information from emojis. Following this, a sentiment- and emoji-masked language model is designed to prioritize the masking of emojis and words with implicit sentiments, focusing on learning the emotional semantics contained in text. Additionally, we proposed a multifeature fusion method based on a cross-attention mechanism by determining the importance of each word in a text from a topic perspective. Next, this method is integrated with the original semantic information of emojis and the enhanced text features, attaining improved sentiment representation accuracy for short texts. Comparative experiments conducted with the state-of-the-art baseline methods on three public datasets demonstrate that the proposed model achieves accuracy improvements of 2.3%, 10.9%, and 2.7%, respectively, validating its effectiveness.

Clinical Factors Influencing the Radiation Dose of Circulating Immune Cells during Radiotherapy for Small Cell Lung Cancer.

Small cell lung cancer (SCLC) has garnered significant attention due to its high malignancy, propensity for distant metastasis, and poor prognosis. Radiotherapy remains the cornerstone of treatment for limited-stage small cell lung cancer (LS-SCLC). However, outcomes with radiotherapy alone or in combination with chemotherapy remain suboptimal. Radiotherapy can induce lymphopenia by directly irradiating hematopoietic organs or destroying mature circulating lymphocytes, leading to immunosuppression and consequently diminishing therapeutic efficacy. The estimated dose of radiation to immune cells (EDRIC) model integrates factors such as hemodynamics, lymphocyte radiosensitivity, and proliferation capacity. This study employs the EDRIC model with enhancements to calculate the circulating immune cell radiation dose. By utilizing the EDRIC methodology, the study explores the correlation between EDRIC and tumor target size, average lung dose, average heart dose, clinical features, and peripheral blood lymphocytopenia during radiotherapy for LS-SCLC, aiming to inform personalized patient treatment strategies. This study analyzed data from 64 LS-SCLC patients who met the inclusion criteria at the General Hospital of Ningxia Medical University from January 2023 to January 2024, all of whom received radical thoracic conventional fractionated radiotherapy. Lymphocyte counts were recorded at the following points: before radiotherapy, at the lowest observed value during radiotherapy, at the end of radiotherapy, and one-month post-radiotherapy. Dosimetric data, including average lung, heart, and body doses, were extracted from the treatment planning system, and the circulating EDRIC was calculated using this model. The relationship between EDRIC values and therapeutic outcomes was analyzed. In LS-SCLC, the EDRIC model effectively predicts lymphocyte count reduction, correlating with planning target volume (PTV; cm3), TNM stage, and the percentage of target lesion shrinkage. Post-radiotherapy, there was a significant decrease in peripheral blood lymphocyte counts, with greater EDRIC values indicating more pronounced lymphocyte reduction.

Bibliometric analysis of bone metastases from lung cancer research from 2004 to 2023.

Background: Bone metastases of lung cancer (BMLC) severely diminish patients' quality of life due to bone-related events, and the lack of clear guidelines globally regarding medical and surgical treatment significantly reduces patient survival. While knowledge about BMLC has grown exponentially over the past two decades, a comprehensive and objective bibliometric analysis remains absent. Methods: A comprehensive bibliometric analysis was conducted on relevant literature on BMLC extracted from the Web of Science database from 2004 to 2023 by Biblioshiny, VOSviewer, Scimago Graphica, CiteSpace, and Microsoft Office Excel Professional Plus 2016 software. 936 papers related to BMLC were extracted from the Web of Science Core Collection (WoSCC). The number of publications, countries, institutions, global collaborations, authors, journals, keywords, thematic trends, and cited references were then visualized. Finally, the research status and development direction in the last 20 years were analyzed. Results: This study included a total of 936 papers on BMLC from 2004 to 2023. There has been a steady increase in global publications each year, peaking in 2021. China had the highest number of publications, followed by Japan and the United States. Additionally, China had the most citations with an H-index of 35, while the US followed with an H-index of 34, highlighting their significant contributions to the field. "Frontiers in Oncology" had the highest number of publications. CiteSpace analysis identified "lung cancer," "bone metastasis," and "survival" as the top high-frequency keywords, encapsulating the core research focus. Keyword clustering analysis revealed six main clusters representing the primary research directions. Burst analysis of keywords showed that "skeletal complications" had the highest burst intensity from 2005 to 2013, while recent research trends include "immunotherapy" and "denosumab," with bursts from 2021 to 2023. Trend topic analysis indicated that "non-small cell lung cancer," "immunotherapy," and "immune checkpoint inhibitors" represent the cutting-edge research directions in this field. Conclusion: This article reveals the current status and trend of research on BMLC, which is increasing worldwide. China and the United States have contributed the most, but international cooperative research on BMLC should be strengthened. The pathogenesis, early prevention, and individualized treatment of BMLC need to be strengthened for further study, and immunotherapy is the next hotspot of lung cancer bone metastasis research.

Time-reversion Fast-sampling Score-based Model for Limited-angle CT Reconstruction.

The score-based generative model (SGM) has received significant attention in the field of medical imaging, particularly in the context of limited-angle computed tomography (LACT). Traditional SGM approaches achieved robust reconstruction performance by incorporating a substantial number of sampling steps during the inference phase. However, these established SGM-based methods require large computational cost to reconstruct one case. The main challenge lies in achieving high-quality images with rapid sampling while preserving sharp edges and small features. In this study, we propose an innovative rapid-sampling strategy for SGM, which we have aptly named the time-reversion fast-sampling (TIFA) score-based model for LACT reconstruction. The entire sampling procedure adheres steadfastly to the principles of robust optimization theory and is firmly grounded in a comprehensive mathematical model. TIFA's rapid-sampling mechanism comprises several essential components, including jump sampling, time-reversion with re-sampling, and compressed sampling. In the initial jump sampling stage, multiple sampling steps are bypassed to expedite the attainment of preliminary results. Subsequently, during the time-reversion process, the initial results undergo controlled corruption by introducing small-scale noise. The re-sampling process then diligently refines the initially corrupted results. Finally, compressed sampling fine-tunes the refinement outcomes by imposing regularization term. Quantitative and qualitative assessments conducted on numerical simulations, real physical phantom, and clinical cardiac datasets, unequivocally demonstrate that TIFA method (using 200 steps) outperforms other state-of-the-art methods (using 2000 steps) from available [0°, 90°] and [0°, 60°]. Furthermore, experimental results underscore that our TIFA method continues to reconstruct high-quality images even with 10 steps. Our code at https://github.com/tianzhijiaoziA/TIFADiffusion.

The role of transforming growth factor-ß (TGF-ß) in the formation of exhausted CD8 + T cells.

CD8 + T cells exert a critical role in eliminating cancers and chronic infections, and can provide long-term protective immunity. However, under the exposure of persistent antigen, CD8 + T cells can differentiate into terminally exhausted CD8 + T cells and lose the ability of immune surveillance and disease clearance. New insights into the molecular mechanisms of T-cell exhaustion suggest that it is a potential way to improve the efficacy of immunotherapy by restoring the function of exhausted CD8 + T cells. Transforming growth factor-ß (TGF-ß) is an important executor of immune homeostasis and tolerance, inhibiting the expansion and function of many components of the immune system. Recent studies have shown that TGF-ß is one of the drivers for the development of exhausted CD8 + T cells. In this review, we summarized the role and mechanisms of TGF-ß in the formation of exhausted CD8 + T cells and discussed ways to target those to ultimately enhance the efficacy of immunotherapy.

The Efficacy of Diabetic Foot Treatment in a "TOSF" Pattern: A Five-Year Retrospective Study.

Aim: To evaluate the advantages and problems in the diagnosis and treatment of diabetic foot (DF) patients by analyzing the results of a 5-year follow-up of the organ system based (TOSF) treatment model. Methods: A retrospective study was conducted in 229 patients with diabetic foot. Chi-square test and rank-sum test were used to analyze the effects of patients' general condition, behavioral and nutritional status, degree of infection (inflammatory markers), comorbidity, diabetic foot grade/classification, and revascularization on readmission rate, amputation rate, all-cause mortality, incidence of other complications, and wound healing time. Logistic regression was used to analyze the risk factors affecting the prognosis of diabetic foot. Kaplan-Meier survival curve was used to analyze the differences in amputation rate and mortality rate at each time point. Results: This study showed that nutritional status, degree of infection, and revascularization influenced readmission rates. General condition, behavior and nutritional status, degree of infection, Wagner grade and revascularization affect the amputation rate. General conditions, behavioral and nutritional status, degree of infection, comorbidities, classification and revascularization affect the mortality of patients. Age and white blood cell(WBC) count affected the incidence of other complications. Influence of infection degree and Wagner grade and revascularization in patients with wound healing time. Revascularization was an independent protective factor for readmission, amputation, and mortality.Elevated serum inflammatory markers are an independent risk factor for amputation. Hypoproteinemia is an independent risk factor for mortality. Conclusion: In the "TOSF" diagnosis and treatment pattern, diabetic foot patients have a good prognosis. Special attention should be paid to the screening and revascularization of lower extremity vascular disease in patients with diabetic foot.

Non­coding RNA: A promising diagnostic biomarker and therapeutic target for esophageal squamous cell carcinoma (Review).

Esophageal cancer (EC) is a common form of malignant tumor in the digestive system that is classified into two types: Esophageal squamous cell carcinomas (ESCC) and esophageal adenocarcinoma. ESCC is known for its early onset of symptoms, which can be difficult to identify, as well as its rapid progression and tendency to develop drug resistance to chemotherapy and radiotherapy. These factors contribute to the high incidence of disease and low cure rate. Therefore, a diagnostic biomarker and therapeutic target need to be identified for ESCC. Non-coding RNAs (ncRNAs) are a class of molecules that are transcribed from DNA but do not encode proteins. Initially, ncRNAs were considered to be non-functional segments generated during transcription. However, with advancements in high-throughput sequencing technologies in recent years, ncRNAs have been associated with poor prognosis, drug resistance and progression of ESCC. The present study provides a comprehensive overview of the biogenesis, characteristics and functions of ncRNAs, particularly focusing on microRNA, long ncRNAs and circular RNAs. Furthermore, the ncRNAs that could potentially be used as diagnostic biomarkers and therapeutic targets for ESCC are summarized to highlight their application value and prospects in ESCC.

Valvar bypass surgery to ameliorate persistent lower limb edema caused by post-thrombotic syndrome: a case report and literature review.

Obstruction and/or reflux compromise during venous emptying can facilitate different pathophysiologies in chronic venous insufficiency (CVI). We present a patient with persistent lower limb CVI edema caused by post-thrombotic syndrome (PTS), who responded well to femoral vein valve therapy via axillary vein bypass after unsuccessful valvuloplasty, and led a normal life. During a 12 month observation period, bridging vessels completely restored original anatomical structures. In a literature study, no similar surgeries were reported, but we show that this operation may be feasible in selected patients.

Molecular engineering of AIE-active boron clustoluminogens for enhanced boron neutron capture therapy.

The development of boron delivery agents bearing an imaging capability is crucial for boron neutron capture therapy (BNCT), yet it has been rarely explored. Here we present a new type of boron delivery agent that integrates aggregation-induced emission (AIE)-active imaging and a carborane cluster for the first time. In doing so, the new boron delivery agents have been rationally designed by incorporating a high boron content unit of a carborane cluster, an erlotinib targeting unit towards lung cancer cells, and a donor-acceptor type AIE unit bearing naphthalimide. The new boron delivery agents demonstrate both excellent AIE properties for imaging purposes and highly selective accumulation in tumors. For example, at a boron delivery agent dose of 15 mg kg-1, the boron amount reaches over 20 µg g-1, and both tumor/blood (T/B) and tumor/normal cell (T/N) ratios reach 20-30 times higher than those required by BNCT. The neutron irradiation experiments demonstrate highly efficient tumor growth suppression without any observable physical tissue damage and abnormal behavior in vivo. This study not only expands the application scopes of both AIE-active molecules and boron clusters, but also provides a new molecular engineering strategy for a deep-penetrating cancer therapeutic protocol based on BNCT.

Multi-channel Optimization Generative Model for Stable Ultra-Sparse-View CT Reconstruction.

Score-based generative model (SGM) has risen to prominence in sparse-view CT reconstruction due to its impressive generation capability. The consistency of data is crucial in guiding the reconstruction process in SGM-based reconstruction methods. However, the existing data consistency policy exhibits certain limitations. Firstly, it employs partial data from the reconstructed image of iteration process for image updates, which leads to secondary artifacts with compromising image quality. Moreover, the updates to the SGM and data consistency are considered as distinct stages, disregarding their interdependent relationship. Additionally, the reference image used to compute gradients in the reconstruction process is derived from intermediate result rather than ground truth. Motivated by the fact that a typical SGM yields distinct outcomes with different random noise inputs, we propose a Multi-channel Optimization Generative Model (MOGM) for stable ultra-sparse-view CT reconstruction by integrating a novel data consistency term into the stochastic differential equation model. Notably, the unique aspect of this data consistency component is its exclusive reliance on original data for effectively confining generation outcomes. Furthermore, we pioneer an inference strategy that traces back from the current iteration result to ground truth, enhancing reconstruction stability through foundational theoretical support. We also establish a multi-channel optimization reconstruction framework, where conventional iterative techniques are employed to seek the reconstruction solution. Quantitative and qualitative assessments on 23 views datasets from numerical simulation, clinical cardiac and sheep's lung underscore the superiority of MOGM over alternative methods. Reconstructing from just 10 and 7 views, our method consistently demonstrates exceptional performance.

Research on joint model relation extraction method based on entity mapping.

Relationship Extraction (RE) is a central task in information extraction. The use of entity mapping to address complex scenarios with overlapping triples, such as CasRel, is gaining traction, yet faces challenges such as inadequate consideration of sentence continuity, sample imbalance and data noise. This research introduces an entity mapping-based method CasRelBLCF building on CasRel. The main contributions include: A joint decoder for the head entity, utilizing Bi-LSTM and CRF, integration of the Focal Loss function to tackle sample imbalance and a reinforcement learning-based noise reduction method for handling dataset noise. Experiments on relation extraction datasets indicate the superiority of the CasRelBLCF model and the enhancement on model's performance of the noise reduction method.

A new strategy for intervertebral disc regeneration: The synergistic potential of mesenchymal stem cells and their extracellular vesicles with hydrogel scaffolds.

Intervertebral disc degeneration (IDD) is a disease that severely affects spinal health and is prevalent worldwide. Mesenchymal stem cells (MSCs) and their derived extracellular vesicles (EVs) have regenerative potential and have emerged as promising therapeutic tools for treating degenerative discs. However, challenges such as the harsh microenvironment of degenerated intervertebral discs and EVs' limited stability and efficacy have hindered their clinical application. In recent years, hydrogels have attracted much attention in the field of IDD therapy because they can mimic the physiologic microenvironment of the disc and provide a potential solution by providing a suitable growth environment for MSCs and EVs. This review introduced the biological properties of MSCs and their derived EVs, summarized the research on the application of MSCs and EVs in IDD, summarized the current clinical trial studies of MSCs and EVs, and also explored the mechanism of action of MSCs and EVs in intervertebral discs. In addition, plenty of research elaborated on the mechanism of action of different classified hydrogels in tissue engineering, the synergistic effect of MSCs and EVs in promoting intervertebral disc regeneration, and their wide application in treating IDD. Finally, the challenges and problems still faced by hydrogel-loaded MSCs and EVs in the treatment of IDD are summarized, and potential solutions are proposed. This paper outlines the synergistic effects of MSCs and EVs in treating IDD in combination with hydrogels and aims to provide theoretical references for future related studies.

Wavelet-Improved Score-Based Generative Model for Medical Imaging.

The score-based generative model (SGM) has demonstrated remarkable performance in addressing challenging under-determined inverse problems in medical imaging. However, acquiring high-quality training datasets for these models remains a formidable task, especially in medical image reconstructions. Prevalent noise perturbations or artifacts in low-dose Computed Tomography (CT) or under-sampled Magnetic Resonance Imaging (MRI) hinder the accurate estimation of data distribution gradients, thereby compromising the overall performance of SGMs when trained with these data. To alleviate this issue, we propose a wavelet-improved denoising technique to cooperate with the SGMs, ensuring effective and stable training. Specifically, the proposed method integrates a wavelet sub-network and the standard SGM sub-network into a unified framework, effectively alleviating inaccurate distribution of the data distribution gradient and enhancing the overall stability. The mutual feedback mechanism between the wavelet sub-network and the SGM sub-network empowers the neural network to learn accurate scores even when handling noisy samples. This combination results in a framework that exhibits superior stability during the learning process, leading to the generation of more precise and reliable reconstructed images. During the reconstruction process, we further enhance the robustness and quality of the reconstructed images by incorporating regularization constraint. Our experiments, which encompass various scenarios of low-dose and sparse-view CT, as well as MRI with varying under-sampling rates and masks, demonstrate the effectiveness of the proposed method by significantly enhanced the quality of the reconstructed images. Especially, our method with noisy training samples achieves comparable results to those obtained using clean data. Our code at https://zenodo.org/record/8266123.

Protein Dynamics Mediated by Cardiolipin in Bacteria.

Bacterial proteins targeting the appropriate subcellular sites are the base for their proper function. Several studies have shown that the anionic phospholipid cardiolipin (CL), a conical lipid preferring negative membrane curvature, modulates the lipid bilayers' structure, which impacts the activity of their resident proteins. Due to the favor of negative membrane curvature, CL is not randomly distributed in the bacterial plasma membrane. In contrast, it gathers in particular parts of the cell membrane to form microdomains, in which many functional membrane proteins are accumulated and carry out diverse physiological processes of bacteria, such as cell division, metabolism, infection, and antibiotic residence. In addition, CL has a unique structure that carries two negative charges, which makes it play a pivotal role in protein assembly, interaction, and location. These characteristics of CL make it closely related to many crucial physiological functions of bacteria. Here, we have reviewed the mechanism of protein dynamics mediated by CL initiated on the bacterial membrane. Furthermore, we studied the effect of CL on bacterial infection and antibiotic residence. Finally, the CL-targeting therapeutic agents for antibacterial therapy are also examined.

Two-and-a-half order score-based model for solving 3D ill-posed inverse problems.

Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are crucial technologies in the field of medical imaging. Score-based models demonstrated effectiveness in addressing different inverse problems encountered in the field of CT and MRI, such as sparse-view CT and fast MRI reconstruction. However, these models face challenges in achieving accurate three dimensional (3D) volumetric reconstruction. The existing score-based models predominantly concentrate on reconstructing two-dimensional (2D) data distributions, resulting in inconsistencies between adjacent slices in the reconstructed 3D volumetric images. To overcome this limitation, we propose a novel two-and-a-half order score-based model (TOSM). During the training phase, our TOSM learns data distributions in 2D space, simplifying the training process compared to working directly on 3D volumes. However, during the reconstruction phase, the TOSM utilizes complementary scores along three directions (sagittal, coronal, and transaxial) to achieve a more precise reconstruction. The development of TOSM is built on robust theoretical principles, ensuring its reliability and efficacy. Through extensive experimentation on large-scale sparse-view CT and fast MRI datasets, our method achieved state-of-the-art (SOTA) results in solving 3D ill-posed inverse problems, averaging a 1.56 dB peak signal-to-noise ratio (PSNR) improvement over existing sparse-view CT reconstruction methods across 29 views and 0.87 dB PSNR improvement over existing fast MRI reconstruction methods with × 2 acceleration. In summary, TOSM significantly addresses the issue of inconsistency in 3D ill-posed problems by modeling the distribution of 3D data rather than 2D distribution which has achieved remarkable results in both CT and MRI reconstruction tasks.

Bibliometric and visual analysis of spinal cord injury-associated macrophages from 2002 to 2023.

Background: Spinal cord injury (SCI) triggers motor, sensory, and autonomic impairments that adversely damage patients' quality of life. Its pathophysiological processes include inflammation, oxidative stress, and apoptosis, although existing treatment options have little success. Macrophages have a vital function in controlling inflammation in SCI, with their M1-type and M2-type macrophages dominating early inflammatory effects and late brain tissue repair and regeneration, respectively. However, there is a dearth of rigorous bibliometric study in this sector to explore its dynamics and trends. This study intends to examine the current status and trends of macrophage usage in SCI using bibliometric methodologies, which may drive novel therapeutic options. Methods: In this study, the Web of Science Core Collection (WOSCC) was utilized to collect publications and reviews on macrophages in SCI from 2002 to 2023. Bibliometrics and visualization analyses were performed by VOSviewer, CiteSpace, the R package "bibliometrix", and online analytic platforms. These analyses covered a variety of aspects, including countries and institutions, authors and co-cited authors, journals and co-cited journals, subject categories, co-cited references, and keyword co-occurrences, in order to provide insights into the research trends and hotspots in this field. Results: 1,775 papers were included in the study, comprising 1,528 articles and 247 reviews. Our research analysis demonstrates that the number of relevant studies in this sector is expanding, specifically the number of publications in the United States and China has risen dramatically. However, there are fewer collaborations between institutions in different nations, and international cooperation needs to be reinforced. Among them, Popovich PG became the leader in the field, and significant journals include Experimental Neurology, Journal of Neurotrauma, and Journal of Neuroscience. Research hotspots involve macrophage polarization, microglia, astrocytes, signaling, cytokines, inflammation, and neuroprotection. Conclusions: This analysis gives, for the first time, a comprehensive overview of bibliometric studies on macrophages in SCI over the past 20 years. This study not only gives an extensive picture of the knowledge structure but also indicates trends in the subject. The systematic summarization gives a complete and intuitive understanding of the link between spinal cord damage and macrophages and provides a great reference for future related studies.

Nanomaterials for small diameter vascular grafts: overview and outlook.

Small-diameter vascular grafts (SDVGs) cannot meet current clinical demands owing to their suboptimal long-term patency rate. Various materials have been employed to address this issue, including nanomaterials (NMs), which have demonstrated exceptional capabilities and promising application potentials. In this review, the utilization of NMs in different forms, including nanoparticles, nanofibers, and nanofilms, in the SDVG field is discussed, and future perspectives for the development of NM-loading SDVGs are highlighted. It is expected that this review will provide helpful information to scholars in the innovative interdiscipline of cardiovascular disease treatment and NM.

Synthesis and Characterization of Zinc/Iron Composite Oxide Heterojunction Porous Anode Materials for High-Performance Lithium-Ion Batteries.

Environmental pollution caused by the use of fossil fuels is becoming increasingly serious, necessitating the adoption of clean energy solutions. Lithium-ion batteries (LIBs) have attracted great attention due to their high energy density and currently occupy a dominant commercial position. Metal oxide materials have emerged as promising anode materials for the next generation of LIBs, thanks to their high theoretical capacity. However, the practical application of these materials is hindered by their substantial volume expansion during lithium storage and poor electrical conductivity. In this work, a zinc/iron bimetallic hybrid oxide composite, ZnO/ZnFe2O4/NC, is prepared using ZIF-8 as a precursor (ZIF-8, one of the metal organic frameworks). The N-doped porous carbon composite improves the volume change and optimizes the lithium-ion and electron transport. Meanwhile, the ZnFe2O4 and ZnO synergistically enhance the electrochemical activity of the anode through the built-in heterojunction to promote the reaction kinetics at the interface. As a result, the material delivers an excellent cycling performance of 604.7 mAh g-1 even after 300 cycles of 1000 mA g-1. This study may provide a rational design for the heterostructure and doping engineering of anodes for high-performance lithium-ion batteries.

Prognostic factors in patients with thymoma who underwent surgery.

PURPOSE: Thymoma is the most common primary tumor in the anterior mediastinum. The prognostic factors of patients with thymoma still need to be clarified. In this study, we aimed to investigate the prognostic factors of patients with thymoma who received radical resection and establish the nomogram to predict the prognosis of these patients. MATERIALS AND METHODS: Patients who underwent radical resection for thymoma with complete follow-up data between 2005 and 2021 were enrolled. Their clinicopathological characteristics and treatment methods were retrospectively analyzed. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared by the log-rank test. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify the independent prognostic factors. According to the results of the univariate analysis in the Cox regression model, the predictive nomograms were created. RESULTS: A total of 137 patients with thymoma were enrolled. With a median follow-up of 52 months, the 5-year and 10-year PFS rates were 79.5% and 68.1%, respectively. The 5-year and 10-year OS rates were 88.4% and 73.1%, respectively. Smoking status (P = 0.022) and tumor size (P = 0.039) were identified as independent prognostic factors for PFS. Multivariate analysis showed that a high level of neutrophils (P = 0.040) was independently associated with OS. The nomogram showed that the World Health Organization (WHO) histological classification contributed more to the risk of recurrence than other factors. Neutrophil count was the most important predictor of OS in patients with thymoma. CONCLUSION: Smoking status and tumor size are risk factors for PFS in patients with thymoma. A high level of neutrophils is an independent prognostic factor for OS. The nomograms developed in this study accurately predict PFS and OS rates at 5 and 10 years in patients with thymoma based on individual characteristics.