Survival benefits of human papillomavirus 16 infection in patients with esophageal squamous cell carcinoma undergoing chemoradiotherapy: A retrospective cohort study.

The role of human papillomavirus 16 (HPV 16) in esophageal squamous cell carcinoma (ESCC) remains uncertain. Therefore, this study aimed to investigate the prevalence of HPV 16 in patients with ESCC and its impact on theirprognosis. HPV 16 was detected using FISH, and TP53 status was evaluated via immunohistochemistry. The factors influencing prognosis were ananalyzed using the Log-rank test and Cox regression analyses. Among 178 patients with ESCC, 105 and 73 patients were categorized into concurrent chemoradiotherapy (CCRT) and postoperative chemoradiotherapy (POCRT) cohorts, respectively. Among 178 patients, 87 (48.87%) tested positive for HPV 16. Log-rank tests revealed that the overall survival (OS) of patients with ESCC who were HPV 16-positive was longer than that of those who were HPV 16-negative (median OS: 57 months vs. 27 months, p < 0.01**). HPV 16 infection and TP53 mutation status were identified as independent events. The OS of patients with mutant TP53 who were HPV 16-positive was longer than that of those who were HPV 16-negative in both CCRT and POCRT cohorts (p = 0.002** for CCRT cohorts and p = 0.0023** for POCRT cohorts). Conversely, HPV 16 infection had no effect on OS in the wild-type TP53 subgroup (p = 0.13 and 0.052 for CCRT and POCRT cohorts, respectively). As a conclusion, the positive rate of HPV 16 in ESCC in this study was 48.87% (87/178). Among the patients with ESCC who had TP53 mutation, those who were HPV 16-positive exhibited a better prognosis than those who were HPV 16-negative.

MACTFusion: Lightweight Cross Transformer for Adaptive Multimodal Medical Image Fusion.

Multimodal medical image fusion aims to integrate complementary information from different modalities of medical images. Deep learning methods, especially recent vision Transformers, have effectively improved image fusion performance. However, there are limitations for Transformers in image fusion, such as lacks of local feature extraction and cross-modal feature interaction, resulting in insufficient multimodal feature extraction and integration. In addition, the computational cost of Transformers is higher. To address these challenges, in this work, we develop an adaptive cross-modal fusion strategy for unsupervised multimodal medical image fusion. Specifically, we propose a novel lightweight cross Transformer based on cross multi-axis attention mechanism. It includes cross-window attention and cross-grid attention to mine and integrate both local and global interactions of multimodal features. The cross Transformer is further guided by a spatial adaptation fusion module, which allows the model to focus on the most relevant information. Moreover, we design a special feature extraction module that combines multiple gradient residual dense convolutional and Transformer layers to obtain local features from coarse to fine and capture global features. The proposed strategy significantly boosts the fusion performance while minimizing computational costs. Extensive experiments, including clinical brain tumor image fusion, have shown that our model can achieve clearer texture details and better visual quality than other state-of-the-art fusion methods.

Multi-omics cluster defines the subtypes of CRC with distinct prognosis and tumor microenvironment.

BACKGROUND: Colorectal cancer (CRC) is a complex malignancy characterized by diverse molecular profiles, clinical outcomes, and limited precision in prognostic markers. Addressing these challenges, this study utilized multi-omics data to define consensus molecular subtypes in CRC and elucidate their association with clinical outcomes and underlying biological processes. METHODS: Consensus molecular subtypes were obtained by applying ten integrated multi-omics clustering algorithms to analyze TCGA-CRC multi-omics data, including mRNA, lncRNA, miRNA, DNA methylation CpG sites, and somatic mutation data. The association of subtypes with prognoses, enrichment functions, immune status, and genomic alterations were further analyzed. Next, we conducted univariate Cox and Lasso regression analyses to investigate the potential prognostic application of biomarkers associated with multi-omics subtypes derived from weighted gene co-expression network analysis (WGCNA). The function of one of the biomarkers MID2 was validated in CRC cell lines. RESULTS: Two CRC subtypes linked to distinct clinical outcomes were identified in TCGA-CRC cohort and validated with three external datasets. The CS1 subtype exhibited a poor prognosis and was characterized by higher tumor-related Hallmark pathway activity and lower metabolism pathway activity. In addition, the CS1 was predicted to have less immunotherapy responder and exhibited more genomic alteration compared to CS2. Then a prognostic model comprising five genes was established, with patients in the high-risk group showing substantial concordance with the CS1 subtype, and those in the low-risk group with the CS2 subtype. The gene MID2, included in the prognostic model, was found to be correlated with epithelial-mesenchymal transition (EMT) pathway and distinct DNA methylation patterns. Knockdown of MID2 in CRC cells resulted in reduced colony formation, migration, and invasion capacities. CONCLUSION: The integrative multi-omics subtypes proposed potential biomarkers for CRC and provided valuable knowledge for precision oncology.

Mechanochemical Synthesis of Thiadiazole Functionalized COF as Oil-Based Lubricant Additive for Reducing Friction and Wear.

In this work, the functionalized covalent organic framework (COF) was prepared via a convenient ball milling process. The aldehyde group terminated COF-F reacted with amino thiadiazole in the ball milling jar under mechanical forces; hence, the thiadiazole functionalized COF-F was obtained and denoted as Thdz@COF-F. The as-prepared Thdz@COF-F serves as an oil-based lubricant additive and exhibits remarkable tribological properties, which can reduce the average friction coefficient of base oil from 0.169 to 0.102 and decrease the wear volume by 87.0%. The antifriction and antiwear performances are mainly due to the repairing effect of Thdz@COF-F nanoparticles and the protective tribo-film that averts the direct contact of friction pairs. In addition, through the ball milling method, triazole and thiazole functionalized COF-F were also prepared and represented good lubrication performance, demonstrating the feasibility of this mechanochemical synthesis method for functionalized COFs.

Coherent X-ray Spectroscopy Elucidates Nanoscale Dynamics of Plasma-Enhanced Thin-Film Growth.

Sophisticated thin film growth techniques increasingly rely on the addition of a plasma component to open or widen a processing window, particularly at low temperatures. Taking advantage of continued increases in accelerator-based X-ray source brilliance, this real-time study uses X-ray Photon Correlation Spectroscopy (XPCS) to elucidate the nanoscale surface dynamics during Plasma-Enhanced Atomic Layer Deposition (PE-ALD) of an epitaxial indium nitride film. Ultrathin films are synthesized from repeated cycles of alternating self-limited surface reactions induced by temporally separated pulses of the material precursor and plasma reactant, allowing the influence of each on the evolving morphology to be examined. During the heteroepitaxial 3D growth examined here, sudden changes in the surface structure during initial film growth, consistent with numerous overlapping stress-relief events, are observed. When the film becomes continuous, the nanoscale surface morphology abruptly becomes long-lived with a correlation time spanning the period of the experiment. Throughout the growth experiment, there is a consistent repeating pattern of correlations associated with the cyclic growth process, which is modeled as transitions between different surface states. The plasma exposure does not simply freeze in a structure that is then built upon in subsequent cycles, but rather, there is considerable surface evolution during all phases of the growth cycle.

A key sphingolipid pathway gene, MoDES1, regulates conidiation, virulence and plasma membrane tension in Magnaporthe oryzae.

Rice blast, caused by the plant pathogenic fungus Magnaporthe oryzae, is a destructive disaster all over the earth that causes enormous losses in crop production. Sphingolipid, an important biological cell membrane lipid, is an essential structural component in the plasma membrane (PM) and has several biological functions, including cell mitosis, apoptosis, stress resistance, and signal transduction. Previous studies have suggested that sphingolipid and its derivatives play essential roles in the virulence of plant pathogenic fungi. However, the functions of sphingolipid biosynthesis-related proteins are not fully understood. In this article, we identified a key sphingolipid synthesis enzyme, MoDes1, and found that it is engaged in cell development and pathogenicity in M. oryzae. Deletion of MoDES1 gave rise to pleiotropic defects in vegetative growth, conidiation, plant penetration, and pathogenicity. MoDes1 is also required for lipid homeostasis and participates in the cell wall integrity (CWI) and Osm1-MAPK pathways. Notably, our results showed that there is negative feedback in the TORC2 signaling pathway to compensate for the decreased sphingolipid level due to the knockout of MoDES1 by regulating the phosphorylated Ypk1 level and PM tension. Furthermore, protein structure building has shown that MoDes1 is a potential drug target. These findings further refine the function of Des1 and deepen our understanding of the sphingolipid biosynthesis pathway in M. oryzae, laying a foundation for developing novel and specific drugs for rice blast control.

Heterogeneous Cu2O-SnO2 doped polydopamine fenton-like nanoenzymes for synergetic photothermal-chemodynamic antibacterial application.

Wound infections caused by drug-resistant bacteria pose a great threat to human health, and the development of non-drug-resistant antibacterial approaches has become a research priority. In this study, we developed Cu2O-SnO2 doped polydopamine (CSPDA) triple cubic antibacterial nanoenzymes with high photothermal conversion efficiency and good Fenton-like catalase performance. CSPDA antibacterial nanoplatform can catalyze the generation of hydroxyl radical (·OH) from H2O2 at low concentration (50 µg∙mL-1) under 808 nm near-infrared (NIR) irradiation to achieve a combined photothermal therapy (PTT) and chemodynamic therapy (CDT). And the CSPDA antibacterial nanoplatform displays broad-spectrum and long-lasting antibacterial effects against both Gram-negative Escherichia coli (100 %) and Gram-positive Staphylococcus aureus (100 %) in vitro. Moreover, in a mouse wound model with mixed bacterial infection, the nanoplatform demonstrates a significant in vivo bactericidal effect while remaining good cytocompatible. To conclude, this study successfully develops an efficient and long-lasting bacterial infection treatment system. This system provided different options for future studies on the design of synergistic antimicrobial therapy. Hence, the as-synthesized synergetic photothermal therapy and chemodynamic therapy nanoenzymes have rapid and long-term bactericidal ability, well-conglutinant performance and effectively preventing wound infection for clinical application. STATEMENT OF SIGNIFICANCE: Wound infections caused by drug-resistant bacteria pose a great threat to human health, and the development of non-drug-resistant antibacterial approaches has become a research priority. In this study, we developed Cu2O-SnO2 doped polydopamine (CSPDA) triple cubic yolk-like antibacterial nanoenzymes with high photothermal conversion efficiency and Fenton-like catalase effect for photothermal and Chemodynamic antibacterial therapy, Meanwhile, the nanocomposites exhibit good antibioadhesion in a natural water environment for a long-time immersion. In conclusion, this study successfully develops an efficient and long-lasting bacterial infection treatment system. These findings present a pioneering strategy for future research on the design of synergistic antibacterial and antibioadhesive systems.

Size-Regulated Metal-Organic Frameworks with Mercaptobenzothiazole for Ga-Based Liquid Metal Encapsulation: A High Performance Oil-Based Additive.

In this study, size-regulated MOFs (MZ) with high MBT loading were successfully synthesized by combining mercaptobenzothiazole (MBT), zinc salt, and 2-methylimidazole (2-MI). Subsequently, the MZ structure was utilized to encapsulate tannic acid-modified gallium-based liquid metal (GLM-TA), thereby acquiring a novel heterogeneous nanocomposite (GLM-TA@MZ). The results revealed that the as-prepared GLM-TA@MZ shows good antiwear and friction-reducing performance as an oil-based lubricant additive, the average friction coefficient was decreased to 0.091, and a wear volume was reduced to 0.95 × 104 µm3, which corresponds to a decrease of 52.3 and 97.2% as compared to base oil PAO. The excellent tribological properties of GLM-TA@MZ can be attributed to physical adsorption on the friction pair, followed by tribochemical reactions. As a result, a thick friction protection film (thickness of about 100 nm) containing Ga, Zn, and S elements was formed, which effectively reduced the contact area between the friction pairs, resulting in improved tribological performance. This study provides insights into the design of MOF-based nanocomposites for lubricating applications.

Epidemiologic trends of and factors associated with overall survival in patients with neuroendocrine tumors over the last two decades in the USA.

Background: Updated epidemiological data of neuroendocrine tumors are currently lacking. Thus, we performed epidemiological and survival analyses on a large cohort of patients with neuroendocrine tumors and developed a new nomogram to predict survival. Methods: This population-based study examined 112,256 patients with neuroendocrine tumors between 2000 and 2018 using data from the Surveillance, Epidemiology, and End Results program. Results: The age-adjusted incidence per 100,000 persons of neuroendocrine tumors increased from 4.90 in 2000 to 8.19 in 2018 (annual percentage change, 3.40; 95% confidence interval, 3.13-3.67), with the most significant increases in grade 1, localized stage, and appendix neuroendocrine tumors. The age-adjusted mortality rate increased 3.1-fold from 2000 to 2018 (annual percentage change, 4.14; 95% confidence interval, 3.14-5.15). The 1-, 5-, and 10-year relative survival rates for all neuroendocrine tumors were 80.5%, 68.4%, and 63.5%, respectively. Multivariate analyses showed that male sex; older age; Black, American Indian, and Alaska Native populations; earlier year of diagnosis; lung neuroendocrine tumors; higher grades; and later stage were associated with a worse prognosis and that disease stage and grade were the most important risk factors for prognosis. Furthermore, we established a nomogram to predict the 3-, 5-, and 10-year survival rates, and its discrimination ability was better than that of the TNM classification. Conclusions: The incidence, prevalence, and mortality rate of neuroendocrine tumors continued to increase over the last two decades. Additionally, the nomogram could accurately quantify the risk of death in patients with neuroendocrine tumors and had good clinical practicability.

The AEG-1-USP10-PARP1 axis confers radioresistance in esophageal squamous cell carcinoma via facilitating homologous recombination-dependent DNA damage repair.

Radiotherapy is the standard adjuvant treatment for esophageal squamous cell carcinoma (ESCC), yet radioresistance remains a major obstacle leading to treatment failure and unfavorable prognosis. Previous reports have demonstrated the involvement of astrocyte elevated gene-1 (AEG-1) in tumorigenesis and progression of multiple malignancies. Nevertheless, the precise role of AEG-1 in the radioresistance of ESCC remains elusive. Here, we unveiled a strong correlation between aberrant AEG-1 gene overexpression and malignant progression as well as adverse prognosis in ESCC patients. Moreover, both in vitro and in vivo investigations revealed that AEG-1 significantly alleviated irradiation-induced DNA damage and enhanced radiation resistance in ESCC cells. Mechanistically, AEG-1 recruited the deubiquitinase USP10 to remove the K48-linked polyubiquitin chains at the Lys425 of PARP1, thus preventing its proteasomal degradation. This orchestrated process facilitated homologous recombination-mediated DNA double-strand breaks (DSBs) repair, culminating in mitigated DNA damage and acquired radioresistance in ESCC cells. Notably, PARP1 overexpression reversed the radiosensitizing effect caused by AEG-1 deficiency. Collectively, these findings shed new light on the mechanism of ESCC radioresistance, providing potential therapeutic targets to enhance the efficacy of radiotherapy in ESCC.

Fabrication of Zwitterionic Polymer-Functionalized Onion-like Carbon Nanoparticles as Aqueous Lubricant Additives.

Onion-like carbon (OLC) is a kind of carbon material with a graphene-like structure and large interlayer spacing, favorable to a good lubricating performance. Herein, a facile method is presented for the preparation of functionalized OLC nanoparticles from candle soot with surface modification. The OLC nanoparticles are collected from combustion soot with candle burning via a simple heat treatment, and then the zwitterionic polymer (polyethylenimine-quaternized derivative, PEIS) can self-assemble onto the OLC surface with epigallocatechin gallate via Michael addition and Schiff-base reaction, thus obtaining PEIS-functionalized OLC nanoparticles (PEIS@OLC). The grafting zwitterionic polymer PEIS endows the OLC nanoparticles with good hydrophilic performance, so the as-obtained PEIS@OLC exhibits outstanding dispersion and lubricating property as a water-based lubricant additive. Compared to pure water, the average coefficient of friction decreases to 0.110 from 0.512, and the corresponding wear volume is reduced by 61.02% with 1.5 wt % addition. The improved lubricating property is mainly due to the synergetic effect of the protective film induced by the tribochemical reaction and the hydration film of zwitterionic polymer PEIS. Besides, the OLC nanoparticles could also display the nanoscale rolling and repairing effects at the friction contact interface, resulting in reduction of friction and wear.

Effects of iron additives on the removal of antibiotics and antibiotic resistance genes in anaerobic fermentation of food waste.

The presence of antibiotics and antibiotic resistance genes (ARGs) in food waste (FW) during anaerobic fermentation poses significant environmental and health risks. This study elucidated the potential of iron additives, specifically 500-nm and 50-nm zero-valent iron (ZVI) and magnetite, in mitigating these contaminants. These findings revealed that 500-nm magnetite significantly reduced tetracyclines by 81.04%, while 500-nm ZVI effectively reduced cefotaxime by 89.90%. Furthermore, both 500-nm and 50-nm ZVI were observed to decrease different types and abundance of heavy metal resistance and virulence genes. Interestingly, while 500-nm ZVI reduced the overall abundance of ARGs by 50%, 500-nm magnetite primarily reduced the diversity of ARGs without significantly impacting their abundance. These results elucidate the efficacy of iron additives in addressing antibiotic contamination and resistance during the anaerobic fermentation process of FW. The findings acquired from this study mitigate the development of innovative and environmentally sustainable technologies for FW treatment, emphasizing the reduction of environmental risks and enhancement of treatment efficiency.

Effects of zero-valent iron and magnetite on ethanol and lactic acid production in the anaerobic fermentation of food waste.

With the increasing global concern about food waste management, finding efficient ways to convert it into valuable products is crucial. The addition of zero-valent iron and magnetite to enhance ethanol and lactic acid fermentation yields from food waste emerges as a potential solution. This study compared the effects of 50-nm and 500-nm particle sizes of zero-valent iron and magnetite on ethanol and lactic acid fermentation and analyzed the mechanism of action from the perspective of organic matter material transformation and microbiology. The experimental results showed that 500-nm particle size magnetite and zero-valent iron could promote the hydrolysis of polysaccharides and proteins. 500-nm particle size magnetite could increase ethanol production (1.4-fold of the control), while 500-nm particle size zero-valent iron could increase lactic acid production (2.8-fold of the control). Metagenomic analysis showed that 500-nm magnetite increased the abundance of genes for amino acid metabolic functions, while 500-nm zero-valent iron increased the abundance of glycoside hydrolase genes (1.3-fold of the control). It's worth noting that while these findings are promising, they are based on controlled experimental conditions, and real-world applications may vary. his research not only offers a novel approach to augmenting anaerobic fermentation yields but also contributes to sustainable food waste management practices, potentially reducing environmental impacts and creating valuable products.

Identification of m5C-related lncRNAs signature to predict prognosis and therapeutic responses in esophageal squamous cell carcinoma patients.

Esophageal squamous cell carcinoma (ESCC) has a dismal prognosis because of atypical early symptoms and heterogeneous therapeutic responses. 5-methylcytosine (m5C) modification plays an important role in the onset and development of many tumors and is widespread in long non-coding RNA (lncRNA) transcripts. However, the functions of m5C and lncRNAs in ESCC have not been completely elucidated. Herein, this study aimed to explore the role of m5C-related lncRNAs in ESCC. The RNA-seq transcriptome profiles and clinical information were downloaded from the TCGA-ESCC database. Pearson analysis was used to identify m5C-related lncRNAs. Then we established the m5C-related lncRNAs prognostic signature (m5C-LPS) using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis. Then, the prognostic value of m5C-LPS was evaluated internally and externally using the TCGA-ESCC and GSE53622 databases through multiple methods. We also detected the expression of these lncRNAs in ESCC cell lines and patient tissues. Fluorescence in situ hybridization (FISH) was used to detect the prognostic value of specific lncRNA. In addition, clinical parameters, immune status, genomic variants, oncogenic pathways, enrichment pathways, and therapeutic response features associated with m5C-LPS were explored using bioinformatics methods. We constructed and validated a prognostic signature based on 9 m5C-related lncRNAs (AC002091.2, AC009275.1, CAHM, LINC02057.1, AC0006329.1, AC037459.3, AC064807.1, ATP2B1-AS1, and UBAC2-AS1). The quantitative real-time polymerase chain reaction (qRT-PCR) revealed that most lncRNAs were upregulated in ESCC cell lines and patient tissues. And AC002091.2 was validated to have significant prognostic value in ESCC patients. A composite nomogram was generated to facilitate clinical practice by integrating this signature with the N stage. Besides, patients in the low-risk group were characterized by good clinical outcomes, favorable immune status, and low oncogenic alteration. Function enrichment analysis indicated that the risk score was associated with mRNA splicing, ncRNA processing, and DNA damage repair response. At the same time, we found significant differences in the responses to chemoradiotherapy between the two groups, proving the value of m5C-LPS in treatment decision-making in ESCC. This study established a novel prognostic signature based on 9 m5C-related lncRNAs, which is a promising biomarker for predicting clinical outcomes and therapeutic response in ESCC.

DSA-Net: Infrared and Visible Image Fusion via Dual-Stream Asymmetric Network.

Infrared and visible image fusion technologies are used to characterize the same scene using diverse modalities. However, most existing deep learning-based fusion methods are designed as symmetric networks, which ignore the differences between modal images and lead to source image information loss during feature extraction. In this paper, we propose a new fusion framework for the different characteristics of infrared and visible images. Specifically, we design a dual-stream asymmetric network with two different feature extraction networks to extract infrared and visible feature maps, respectively. The transformer architecture is introduced in the infrared feature extraction branch, which can force the network to focus on the local features of infrared images while still obtaining their contextual information. The visible feature extraction branch uses residual dense blocks to fully extract the rich background and texture detail information of visible images. In this way, it can provide better infrared targets and visible details for the fused image. Experimental results on multiple datasets indicate that DSA-Net outperforms state-of-the-art methods in both qualitative and quantitative evaluations. In addition, we also apply the fusion results to the target detection task, which indirectly demonstrates the fusion performances of our method.

A method for selecting reference beam model of VMAT plans with three 6MV beam-matched linear accelerators during radiation oncology.

Our objective was to provide a method for selecting reference beam model and evaluating the dosimetric accuracy of volumetric modulated arc therapy (VMAT) plans delivered on three Elekta beam-matched linacs during radiation oncology. Beam data was measured on three beam-matched linacs including Synergy1, Synergy2 and VersaHD. For eighteen lung and esophagus cases, fifty-four plans were generated using VMAT technique with three linac beam models respectively for point dose measurement and three-dimensional dose measurement. Each VMAT plan was executed sequentially on three linacs respectively. Measurement results were compared with treatment planning system (TPS) calculation results for all VMAT plans. Among three beam-matched linacs, discrepancy in beam output factor, percentage depth dose at 5 cm, 10 cm, 20 cm depth and MLC leaf offset are all within 1% except 20 × 20 cm2 and 30 × 30 cm2 field sizes, and discrepancy in beam profile is all within 2%. With comparison between measurement result and TPS calculation result, the absolute dose deviations are within the range of ± 3%, and the gamma passing rates are all over 95% for all VMAT plans, which are within the tolerance of clinical acceptability. Compared with all plans delivered on Synegy1 and VersaHD, the point dose discrepancy between measured results and TPS calculated results for plans delivered on Synergy2 is smallest, and the gamma passing rate between measured results and TPS calculated results for plans delivered on Synergy2 is highest. The beam-matched linacs demonstrate good agreement between measurement result and TPS calculation result for VMAT plans. The method can be used for selecting reference beam model for VMAT plans.

In Situ Surface-Initiated ATRP Mediated by Gallium-Based Liquid Metal Nanodroplets.

Surface-initiated atom transfer radical polymerization (SI-ATRP) is one of the most popular methods for surface modifications with functional polymer films, which has attracted significant attention in recent years. Herein, a facile method of gallium-based liquid metal (GLM) nanodroplets mediated SI-ATRP to prepare polymer brushes on GLM surfaces is reported. The ATRP initiator modified GLM (GLM-Br) nanodroplets act as a substrate for the in situ SI-ATRP and participate as a reducing agent to reduce Cu(II) deactivators to Cu(I) activators. UV-vis spectra confirm the feasibility of the in situ SI-ATRP and indicate that the thickness and density of polymer brushes play an important role in performing a successful ATRP on GLM nanodroplets surfaces. Homo- and block copolymers, poly(3-sulfopropyl methacrylate potassium salt) (PSPMA) and poly((2-dimethylamino)ethyl methacrylate-b-(3-sulfopropyl methacrylate potassium salt)) P(DMAEMA-b-SPMA) are successfully grafted to the GLM nanodroplets. Polymer brushes modified GLM nanodroplets show potential applications such as friction reduction and oil-water emulsion separation. GLM nanodroplets mediated SI-ATRP provides a novel and robust approach to preparing multifunctional GLM nanodroplets for different applications.

An artificial neural network-based radiomics model for predicting the radiotherapy response of advanced esophageal squamous cell carcinoma patients: a multicenter study.

Radiotherapy benefits patients with advanced esophageal squamous cell carcinoma (ESCC) in terms of symptom relief and long-term survival. In contrast, a substantial proportion of ESCC patients have not benefited from radiotherapy. This study aimed to establish and validate an artificial neural network-based radiomics model for the pretreatment prediction of the radiotherapy response of advanced ESCC by using integrated data combined with feasible baseline characteristics of computed tomography. A total of 248 patients with advanced ESCC who underwent baseline CT and received radiotherapy were enrolled in this study and were analyzed by two types of radiomics models, machine learning and deep learning. As a result, the Att. Resnet50 pretrained network model indicated superior performance, with AUCs of 0.876, 0.802 and 0.732 in the training, internal validation, and external validation cohorts, respectively. Similarly, our Att. Resnet50 pretrained network model showed excellent calibration and significant clinical benefit according to the C index and decision curve analysis. Herein, a novel pretreatment radiomics model was established based on deep learning methods and could be used for radiotherapy response prediction in advanced ESCC patients, thus providing reliable evidence for therapeutic decision-making.

Radiation induces IRAK1 expression to promote radioresistance by suppressing autophagic cell death via decreasing the ubiquitination of PRDX1 in glioma cells.

Radiotherapy is the standard adjuvant treatment for glioma patients; however, the efficacy is limited by radioresistance. The function of Interleukin-1 receptor associated kinase 1 (IRAK1) in tumorigenesis and radioresistance remains to be elucidated. IRAK1 expression and its correlation with prognosis were analyzed in glioma tissues. We found that glioma patients with overexpressed IRAK1 show a poor prognosis. Notably, ionizing radiation (IR) remarkably induces IRAK1 expression, which was decreased by STING antagonist H-151 treatment. JASPAR prediction, ChIP assays, and dual luciferase reporter assays indicated that transcription factor FOXA2, suppressed by STING inhibition, directly binds to the IRAK1 promoter region and activates its transcription. IRAK1 knockdown inhibits malignancy and enhances the radiosensitivity of glioma in vitro and in vivo. To explore the potential IRAK1 interacting targets mediating the radioresistance of glioma cells, IP/Co-IP, LC-MS/MS, GST pull-down, and ubiquitination analyses were conducted. Mechanistically, IRAK1 bound to PRDX1, a major member of antioxidant enzymes, and further prevents ubiquitination and degradation of PRDX1 mediated by E3 ubiquitin ligase HECTD3; Both the DOC and HECT domains of HECTD3 directly interacted with PRDX1 protein. Overexpression of PRDX1 reverses the radiotherapy sensitization effect of IRAK1 depletion by diminishing autophagic cell death. These results suggest the IRAK1-PRDX1 axis provides a potential therapeutic target for glioma patients.

Glucagon-modified Liposomes Delivering Thyroid Hormone for Anti-obesity Therapy.

BACKGROUND: Thyroid hormones (active form T3) are naturally potent compounds that influence energy expenditure, cholesterol metabolism, and fat oxidation. T3 would be an effective anti-obesity drug if it would not be delivered to the heart and bones, which leads to serious side effects, such as cardiovascular and bone thyrotoxicity, muscle wasting, and so on. METHODS: In this study, we designed a targeted drug delivery system that is a glucagon-modified liposome to deliver T3 to the liver and adipose tissues. RESULTS: The liposomes exhibited excellent properties, including uniform nanoscale particle size, good physicochemical stability, and adequate drug release behavior. More importantly, the glucagon-modified liposomes were enriched in the liver, which minimized the undesired bone and cardiovascular thyrotoxicity of T3. Compared to the control group, T3-loading glucagon-modified liposomes could effectively decrease body weight, reverse hepatic steatosis, and correct hyperlipidemia and hyperglycemia in ob/ob mice, without the undesired cardiovascular and bone thyrotoxicity. CONCLUSION: These findings indicate that delivery of thyroid hormone by glucagon-modified liposomes may provide an effective strategy for anti-obesity therapy.