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.

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.

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.

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.

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.

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.

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.

Influence of Martensite/Bainite Dual Phase-Content on the Mechanical Properties of EA4T High-Speed Axle Steel.

In this work, we have investigated the effect of martensite/bainite dual phase content on the mechanical properties of EA4T high-speed axle steel. For evaluation and control of the strength, ductility, and toughness of steel, the microstructure of lath martensite (LM) and granular bainite (GB) was clarified through an optical microscope (OM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). Besides, the tensile fracture morphology was studied by scanning electron microscopy (SEM). For this purpose, this study conducted a quantitative analysis of the LM and GB fractions using the Pro Imaging software-2018 of OM. The remarkable effect of the LM/GB structure on mechanical properties is discussed. The results have shown that by increasing the volume fraction of the GB structure, the LM structure is refined and its microhardness and strength are improved. Meanwhile, the micro strength of LM follows the Hall-Petch relationship with the lath martensite packet size. Subsequently, the mechanical property prediction model of EA4T steel based on the LM/GB content was established by regression analysis of all experiment dates. When the LM fraction in the steel is about 40-70%, a superior combination of strength, ductility, and toughness can be obtained in EA4T steel.

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.

LncRNA WAC-AS1 expression in human tumors correlates with immune infiltration and affects prognosis.

BACKGROUND: WAC-antisense RNA1 (WAC-AS1) is a newly identified long non-coding RNA (lncRNA) implicated in the prognosis and development of a few types of tumors. However, the correlations of WAC-AS1 with immune infiltration and patient prognosis in pan-cancer remain unclear. In the present study, we aimed to investigate the prognostic value and immunological functions of WAC-AS1 across 33 different types of cancers. METHODS: To investigate the potential oncogenic roles of WAC-AS1, bioinformatics analyses were performed using the Cancer Genome Atlas (TCGA) and Genotype Tissue-Expression (GTEx) datasets. The correlations of WAC-AS1 with prognosis, clinical phenotype, tumor mutational burden (TMB), microsatellite instability (MSI), tumor regulation-related genes, tumor microenvironment, immune cell infiltration, and drug resistance to commonly used chemotherapy drugs in different types of tumors were explored. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed to explore the biological functions of WAC-AS1 in tumors. In situ hybridization (ISH) was performed in tissue microarray (TMA) to confirm the expression of WAC-AS1 in multiple tumor tissues. RESULTS: WAC-AS1 showed aberrant expression in most cancers when compared to the normal tissues. It also has prognostic value in multiple types of cancers. Elevated WAC-AS1 expression was associated with poor prognosis and overall survival in adrenocortical carcinoma (ACC), breast invasive carcinoma (BRCA), and liver hepatocellular carcinoma (LIHC). A significant negative correlation between WAC-AS1 expression and overall survival was observed in brain lower-grade glioma (LGG), pancreatic adenocarcinoma (PAAD), and skin cutaneous melanoma (SKCM). The expression of WAC-AS1 also showed a correlation with clinical stage in six types of tumors, and with tumor mutational burden and microsatellite instability in several different types of cancers. The immune scores of those cancers were found to be significant. Additionally, the effectiveness of fluorouracil and four other anticancer drugs was significantly different based on the expression of WAC-AS1 in these cancers. Moreover, the ISH results showed in six types of tumors, the expression of WAC-AS1 was consistent with the Pan-cancer analysis using TCGA and GTEx database. CONCLUSIONS: These results indicate an intensive involvement of WAC-AS1 in the regulation of immune responses, immune cell infiltration, and malignant properties in various types of cancers, suggesting that WAC-AS1 may serve as a prognostic marker across diverse types of cancers.

[Spatial-temporal Variation and Driving Factors of Ozone in China from 2019 to 2021 Based on EOF Technique and KZ Filter].

Based on the hourly O3 concentration data of 337 prefectural-level divisions and simultaneous surface meteorological data in China, we applied empirical orthogonal function (EOF) analysis to analyze the main spatial patterns, variation trends, and main meteorological driving factors of O3 concentration in China from March to August in 2019-2021. In this study, a KZ (Kolmogorov-Zurbenko) filter was used to decompose the time series of O3 concentration and simultaneous meteorological factors into corresponding short-term, seasonal, and long-term components in 31 provincial capitals.Then, the stepwise regression was used to establish the relationship between O3 and meteorological factors. Ultimately, the long-term component of O3 concentration after "meteorological adjustment" was reconstructed. The results indicated that the first spatial patterns of O3 concentration showed a convergent change, that is, the volatility of O3 concentration was weakened in the high-value region of variability and enhanced in the low-value region.Before and after the meteorological adjustment, the variation trend of O3 concentration in different cities was different to some extent. The adjusted curve was "flatter" in most cities. Among them, Fuzhou, Haikou, Changsha, Taiyuan, Harbin, and Urumqi were greatly affected by emissions. Shijiazhuang, Jinan, and Guangzhou were greatly affected by meteorological conditions. Beijing, Tianjin, Changchun, and Kunming were greatly affected by emissions and meteorological conditions.

Application of two glycosylated Lactobacillus surface layer proteins in coating cationic liposomes.

The ability of isolated surface layer proteins (SLPs) to reassemble on suitable surfaces enables the application of SLPs in various fields of nanotechnology. In this work, SLPs from Lactobacillus buchneri BNCC 187,964 and L. kefir BNCC 190,565 were extracted and verified as glycosylated proteins. They were applied to coat on the surface of cationic liposomes. The absorption of the two SLPs on liposomes induced the zeta potential reduction and particle size increase. The two kinds of SLP-coated liposomes demonstrated better thermal, light and pH stability than the control liposomes. And the L. kefir SLP showed better protective effects than the L. buchneri SLP. Moreover, both of the SLPs could endow liposomes with the function of binding ferritin as observed by transmission electron microscope. Fourier transform infrared spectroscopy illustrated that the interaction between the two SLPs and liposomes was similar. The recrystallization of the two SLPs on the liposomes might drive the lipid into a higher order state and hydrogen bonds were formed between the two SLPs and the liposomes. All the findings demonstrated that L. kefir SLP and L. buchneri SLP had great potential to be explored as effective coating agents to improve the stability and function of cationic liposomes.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.Yes, all have been checked.

Silencing UBQLN2 Enhances the Radiosensitivity of Esophageal Squamous Cell Carcinoma (ESCC) via Activating p38 MAPK.

Background: Ubiquilin 2 (UBQLN2) is an adaptor of ubiquitinated proteins and the proteasome. The potential role of UBQLN2 in carcinogenesis has been demonstrated. However, its role in modulating the radiosensitivity of cancer is not clear. Here, we explored the radiosensitizing effect of silencing UBQLN2 on esophageal squamous cell carcinoma (ESCC) and its mechanisms. Methods: We analyzed the prognostic role of UBQLN2 in the ESCC patient cohort from the Cancer Genomic Atlas (TCGA) database and our hospital. We also conducted a series of experiments in vivo and in vitro to investigate the effect of silencing UBQLN2 on ESCC radiosensitivity and its mechanisms. Results: UBQLN2 is highly expressed in ESCC tissues and positively correlated with poor overall survival (OS). The knockdown of UBQLN2 dramatically increased the radiosensitivity of ESCC cells. Mechanically, UBQLN2 suppression substantially upregulated p38 mitogen-activated protein kinases (MAPK). The p38 MAPK inhibitor SB203580 could reverse the radiation-enhancing effect induced by UBQLN2 knockdown. The direct interaction between UBQLN2 and p38 MAPK was confirmed by co-immunoprecipitation (CO-IP) assay. Furthermore, silencing UBQLN2 also inhibited the expression of phosphorylated DNA-dependent protein kinase catalytic subunit (p-DNA-PKcs) after irradiation. Finally, the xenografted tumor experiment confirmed the radiosensitizing effect of silencing UBQLN2 on ESCC in vivo. Conclusion: Our results suggest that silencing UBQLN2 enhances the radiosensitivity of ESCC by activating p38 MAPK, and UBQLN2 may be a potential target to enhance the radiosensitivity of ESCC.

Recall of reactive cutaneous capillary endothelial proliferation (RCCEP) induced by stereotactic body radiation therapy (SBRT) in a patient with lung squamous cell carcinoma.

Camrelizumab (SHR-1210) is a humanized IgG4 monoclonal anti-programmed cell death protein 1 (PD-1) antibody that has been shown to inhibit the binding of PD-1 to PD-L1, thereby blocking the immune escape of various types of cancer, including lung squamous cell carcinoma (LSCC). Reactive cutaneous capillary endothelial proliferation (RCCEP) is the most common adverse event in camrelizumab-treated patients. Here, we introduce a case of LSCC with recall RCCEP induced by stereotactic body radiation therapy (SBRT). A 76-year-old LSCC patient developed RCCEP when he received camrelizumab and chemotherapy. After discontinuing camrelizumab treatment, the RCCEP lesions spontaneously regressed and fell off. However, when the patient received subsequent SBRT, the RCCEP occurred again at the same sites. This case may provide clues for additional study of the immune reactivation effect of SBRT or the underlying mechanism of RCCEP.