Proteogenomic analysis identifies neoantigens and bacterial peptides as immunotherapy targets in colorectal cancer.

Considerable progress has recently been made in cancer immunotherapy, including immune checkpoint blockade, cancer vaccine, and adoptive T cell methods. The lack of effective targets is a major cause of the low immunotherapy response rate in colorectal cancer (CRC). Here, we used a proteogenomic strategy comprising immunopeptidomics, whole exome sequencing, and 16 S ribosomal DNA sequencing analyses of 8 patients with CRC to identify neoantigens and bacterial peptides that can serve as antitumor targets. This study directly identified several personalized neoantigens and bacterial immunopeptides. Immunoassays showed that all neoantigens and 5 of 8 bacterial immunopeptides could be recognized by autologous T cells. Additionally, T cell receptor (TCR) αß sequencing revealed the TCR repertoire of epitope-reactive CD8+ T cells. Functional studies showed that T cell receptor-T (TCR-T) could be activated by epitope pulsed lymphoblastoid cells. Overall, this study comprehensively profiled the CRC immunopeptidome, revealing several neoantigens and bacterial peptides with potential to serve as immunotherapy targets in CRC.

X-ray source motion blur modeling and deblurring with generative diffusion for digital breast tomosynthesis.

Objective. Digital breast tomosynthesis (DBT) has significantly improved the diagnosis of breast cancer due to its high sensitivity and specificity in detecting breast lesions compared to two-dimensional mammography. However, one of the primary challenges in DBT is the image blur resulting from x-ray source motion, particularly in DBT systems with a source in continuous-motion mode. This motion-induced blur can degrade the spatial resolution of DBT images, potentially affecting the visibility of subtle lesions such as microcalcifications.Approach. We addressed this issue by deriving an analytical in-plane source blur kernel for DBT images based on imaging geometry and proposing a post-processing image deblurring method with a generative diffusion model as an image prior.Main results. We showed that the source blur could be approximated by a shift-invariant kernel over the DBT slice at a given height above the detector, and we validated the accuracy of our blur kernel modeling through simulation. We also demonstrated the ability of the diffusion model to generate realistic DBT images. The proposed deblurring method successfully enhanced spatial resolution when applied to DBT images reconstructed with detector blur and correlated noise modeling.Significance. Our study demonstrated the advantages of modeling the imaging system components such as source motion blur for improving DBT image quality.

Birinapant Reshapes the Tumor Immunopeptidome and Enhances Antigen Presentation.

Birinapant, an antagonist of the inhibitor of apoptosis proteins, upregulates MHCs in tumor cells and displays a better tumoricidal effect when used in combination with immune checkpoint inhibitors, indicating that Birinapant may affect the antigen presentation pathway; however, the mechanism remains elusive. Based on high-resolution mass spectrometry and in vitro and in vivo models, we adopted integrated genomics, proteomics, and immunopeptidomics strategies to study the mechanism underlying the regulation of tumor immunity by Birinapant from the perspective of antigen presentation. Firstly, in HT29 and MCF7 cells, Birinapant increased the number and abundance of immunopeptides and source proteins. Secondly, a greater number of cancer/testis antigen peptides with increased abundance and more neoantigens were identified following Birinapant treatment. Moreover, we demonstrate the existence and immunogenicity of a neoantigen derived from insertion/deletion mutation. Thirdly, in HT29 cell-derived xenograft models, Birinapant administration also reshaped the immunopeptidome, and the tumor exhibited better immunogenicity. These data suggest that Birinapant can reshape the tumor immunopeptidome with respect to quality and quantity, which improves the presentation of CTA peptides and neoantigens, thus enhancing the immunogenicity of tumor cells. Such changes may be vital to the effectiveness of combination therapy, which can be further transferred to the clinic or aid in the development of new immunotherapeutic strategies to improve the anti-tumor immune response.

Model-based deep CNN-regularized reconstruction for digital breast tomosynthesis with a task-based CNN image assessment approach.

Objective. Digital breast tomosynthesis (DBT) is a quasi-three-dimensional breast imaging modality that improves breast cancer screening and diagnosis because it reduces fibroglandular tissue overlap compared with 2D mammography. However, DBT suffers from noise and blur problems that can lower the detectability of subtle signs of cancers such as microcalcifications (MCs). Our goal is to improve the image quality of DBT in terms of image noise and MC conspicuity.Approach. We proposed a model-based deep convolutional neural network (deep CNN or DCNN) regularized reconstruction (MDR) for DBT. It combined a model-based iterative reconstruction (MBIR) method that models the detector blur and correlated noise of the DBT system and the learning-based DCNN denoiser using the regularization-by-denoising framework. To facilitate the task-based image quality assessment, we also proposed two DCNN tools for image evaluation: a noise estimator (CNN-NE) trained to estimate the root-mean-square (RMS) noise of the images, and an MC classifier (CNN-MC) as a DCNN model observer to evaluate the detectability of clustered MCs in human subject DBTs.Main results. We demonstrated the efficacies of CNN-NE and CNN-MC on a set of physical phantom DBTs. The MDR method achieved low RMS noise and the highest detection area under the receiver operating characteristic curve (AUC) rankings evaluated by CNN-NE and CNN-MC among the reconstruction methods studied on an independent test set of human subject DBTs.Significance. The CNN-NE and CNN-MC may serve as a cost-effective surrogate for human observers to provide task-specific metrics for image quality comparisons. The proposed reconstruction method shows the promise of combining physics-based MBIR and learning-based DCNNs for DBT image reconstruction, which may potentially lead to lower dose and higher sensitivity and specificity for MC detection in breast cancer screening and diagnosis.

Advances in understanding the role of dendritic cells in aplastic anaemia.

Aplastic anaemia (AA) is an autoimmune disease characterized by haematopoietic failure in the bone marrow. Abnormal activation and hyperfunction of T lymphocytes are believed to cause bone marrow damage, which plays a major role in AA pathogenesis. Dendritic cells (DCs) play a vital role in the immune system by processing antigens for presentation to T cells and regulating their differentiation and function. DC dysfunction may cause abnormal T-cell activation. Recent studies have associated the occurrence and development of AA with DC function. In this review, we have discussed the role of DCs in AA pathogenesis and their potential as putative therapeutic targets for AA.

Review of molecular biological studies on acute lymphoblastic leukemia treated by modified shengmaiyin.

The objective was to explore the pharmacological mechanism of modified shengmaiyin (MSMY) in the treatment of acute lymphoblastic leukemia (ALL) by network pharmacology analysis. The effective components and predicted targets of MSMY were collected from TCMSP and Swiss target prediction databases, and the related targets of ALL were screened by GeneCards and DisGeNET. The core targets and related signaling pathways of MSMY active ingredients for the treatment of ALL were predicted by protein-protein interaction network (PPI), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis. We identified 172 potential targets for the active components of MSMY, 538 disease targets associated with ALL, and 59 common gene targets. PPI network showed that 27 targets such as triptolide, RAC-alpha serine/threonine-protein kinase (AKT1), vascular endothelial growth factor A and Caspase-3 (CASP3) were the core targets. KEGG enrichment analysis related signaling pathways included cancer pathway, phosphatidylinositol 3 kinase, PI-3K/protein kinase B (PI3K-Akt) signaling pathway, apoptosis and mitogen-activated protein kinase (MAPK) signaling pathway and IL-17 signaling pathway. The effective active components and potential therapeutic targets of MSMY in the treatment of ALL were initially identified by comprehensive network pharmacology, which provides a theoretical basis for further study of the material basis and molecular mechanism of MSMY in the treatment of ALL.

Effects of dexmedetomidine at different dosages on perioperative haemodynamics and postoperative recovery quality in elderly patients undergoing hip replacement surgery under general anaesthesia: a randomized controlled trial.

BACKGROUND: Dexmedetomidine could provide some advantages to prevent postoperative complications in elderly patients undergoing under general anaesthesia. However, dexmedetomidine inhibits haemodynamics to some extent due to its sympathetic inhibition. OBJECTIVE: To evaluate the effects of different doses of dexmedetomidine on haemodynamics during surgery and recovery after general anaesthesia in elderly patients undergoing hip replacement. METHODS: This was a prospective randomized double-blind controlled clinical trial. Eligible patients were randomly allocated into comparative groups (normal saline (NS) and midazolam (MD), n = 30) and dexmedetomidine groups at different doses (D0.25/D0.5/D0.75, n = 30). In the D0.25/D0.5/D0.75 groups, dexmedetomidine was administered at different initial loading doses (0.25/0.5/0.75 µg/kg for 15 min) following 0.5 µg/kg/h continuous infusion until the end of the operation. In the MD group, patients were administered 0.03 mg/kg midazolam at the beginning of anaesthesia induction. RESULTS: Compared to the MD and NS groups, there were significant decreases in MAP in the D0.5 and D0.75 groups at many time points, such as skin incision, end of operation, and from extubation until 30 min after extubation (P < 0.05); there were also significant decreases in HR in the D0.5 and D0.75 groups at time points including anaesthesia induction, end of operation, and from extubation to 2 h after operation (P < 0.05). In the D0.25 group, there were few differences in the changes in MAP and HR compared to the MD and NS groups during the entire perioperative period (P > 0.05). Moreover, the percentage of patients whose MAP and HR decreased > 20% of baseline was higher in the D0.75 and D0.5 groups than that in all other groups. Compared to the NS group, from the beginning to the end of the operation, the 95% confidence interval (CI) of RR for MAP below > 20% of baseline in the D0.5 and D0.75 groups was greater than 1. In particular, the CI of the RR in the D0.75 group was greater than 1 until the patient awoke from general anaesthesia (P < 0.05). In addition, the CI of the RR for HR below > 20% of baseline in the D0.5 group was greater than 1 compared to the NS group at the time of induction and extubation (P < 0.05). There was no significant difference in the possibility of developing hypotension or bradycardia in the MD or D0.25 groups compared to the NS group (P > 0.05). The recovery quality of patients during the post-anaesthesia period was also observed. No differences were observed among all the groups in the time to awakening or extubation after general anaesthesia (P > 0.05). According to the Riker Sedation-agitated Scale, dexmedetomidine significantly alleviated emergency agitation or delirium compared to NS (P < 0.05). In addition, the scores in the D0.5 and D0.75 groups were lower than those in the D0.25 group (P < 0.05). CONCLUSION: Dexmedetomidine could alleviate the agitation of elderly patients undergoing hip replacement after intravenous general anaesthesia combined with inhaled sevoflurane without delayed recovery. However, it is necessary to be vigilant about the haemodynamic inhibition of the drug at high dosages throughout the perioperative period. Dexmedetomidine 0.25-0.5 µg/kg as the initial loading dose followed by 0.5 µg/kg/h continuous infusion might provide comfortable recovery after general anaesthesia with slight haemodynamic inhibition. TRAIL REGISTRATION: ClinicalTrial.gov, No. NCT05567523. Registered 05 October 2022, https://clinicaltrials.gov/ct2/show/NCT05567523?term=NCT05567523&draw=2&rank=1 .

Deep learning denoising of digital breast tomosynthesis: Observer performance study of the effect on detection of microcalcifications in breast phantom images.

BACKGROUND: The noise in digital breast tomosynthesis (DBT) includes x-ray quantum noise and detector readout noise. The total radiation dose of a DBT scan is kept at about the level of a digital mammogram but the detector noise is increased due to acquisition of multiple projections. The high noise can degrade the detectability of subtle lesions, specifically microcalcifications (MCs). PURPOSE: We previously developed a deep-learning-based denoiser to improve the image quality of DBT. In the current study, we conducted an observer performance study with breast radiologists to investigate the feasibility of using deep-learning-based denoising to improve the detection of MCs in DBT. METHODS: We have a modular breast phantom set containing seven 1-cm-thick heterogeneous 50% adipose/50% fibroglandular slabs custom-made by CIRS, Inc. (Norfolk, VA). We made six 5-cm-thick breast phantoms embedded with 144 simulated MC clusters of four nominal speck sizes (0.125-0.150, 0.150-0.180, 0.180-0.212, 0.212-0.250 mm) at random locations. The phantoms were imaged with a GE Pristina DBT system using the automatic standard (STD) mode. The phantoms were also imaged with the STD+ mode that increased the average glandular dose by 54% to be used as a reference condition for comparison of radiologists' reading. Our previously trained and validated denoiser was deployed to the STD images to obtain a denoised DBT set (dnSTD). Seven breast radiologists participated as readers to detect the MCs in the DBT volumes of the six phantoms under the three conditions (STD, STD+, dnSTD), totaling 18 DBT volumes. Each radiologist read all the 18 DBT volumes sequentially, which were arranged in a different order for each reader in a counter-balanced manner to minimize any potential reading order effects. They marked the location of each detected MC cluster and provided a conspicuity rating and their confidence level for the perceived cluster. The visual grading characteristics (VGC) analysis was used to compare the conspicuity ratings and the confidence levels of the radiologists for the detection of MCs. RESULTS: The average sensitivities over all MC speck sizes were 65.3%, 73.2%, and 72.3%, respectively, for the radiologists reading the STD, dnSTD, and STD+ volumes. The sensitivity for dnSTD was significantly higher than that for STD (p < 0.005, two-tailed Wilcoxon signed rank test) and comparable to that for STD+. The average false positive rates were 3.9 ± 4.6, 2.8 ± 3.7, and 2.7 ± 3.9 marks per DBT volume, respectively, for reading the STD, dnSTD, and STD+ images but the difference between dnSTD and STD or STD+ did not reach statistical significance. The overall conspicuity ratings and confidence levels by VGC analysis for dnSTD were significantly higher than those for both STD and STD+ (p ≤ 0.001). The critical alpha value for significance was adjusted to be 0.025 with Bonferroni correction. CONCLUSIONS: This observer study using breast phantom images showed that deep-learning-based denoising has the potential to improve the detection of MCs in noisy DBT images and increase radiologists' confidence in differentiating noise from MCs without increasing radiation dose. Further studies are needed to evaluate the generalizability of these results to the wide range of DBTs from human subjects and patient populations in clinical settings.

Promoted Generation of T Helper 1-Like Regulatory T Cells After Transient Middle Cerebral Artery Occlusion in Type-2 Diabetic Mice.

BACKGROUND: Regulatory T cells (Tregs) play a remarkable role in modulating post-ischemic neuroinflammation. However, the characteristics of Tregs in diabetic ischemic stroke remain unknown. METHODS: Transient middle cerebral artery occlusion (MCAO) was conducted on leptin receptor-mutated db/db mice and db/+ mice. The number, cytokine production, and signaling features of Tregs in peripheral blood and ipsilateral hemispheres were evaluated by flow cytometry. Treg plasticity was assessed by the adoptive transfer of splenic Tregs into mice. The effect of ipsilateral macrophages/microglia on Treg plasticity was determined by in vitro co-culture analysis. RESULTS: db/db mice had more infiltrating Tregs in their ipsilateral hemispheres than db/+ mice. Infiltrating Tregs in db/db mice expressed higher transforming growth factor-ß (TGF-ß), interleukin-10 (IL-10), forkhead box P3 (Foxp3), interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), and T-box expressed in T cells (T-bet) in comparison to infiltrating Tregs in db/+ mice, suggesting promoted generation of T helper 1 (Th1)-like Tregs in the brains of db/db mice after stroke. The post-ischemic brain microenvironment of db/db mice significantly up-regulated IFN-γ, TNF-α, T-bet, IL-10, and TGF-ß in infiltrating Tregs. Moreover, ipsilateral macrophages/microglia remarkably enhanced the expression of IFN-γ, TNF-α, and T-bet but not IL-10 and TGF-ß in Tregs. db/db macrophages/microglia were more potent in up-regulating IFN-γ, TNF-α, and T-bet than db/+ macrophages/microglia. Interleukin-12 (IL-12) blockage partially abolished the modulatory effect of macrophages/microglia on Tregs. CONCLUSION: The generation of Th1-like Tregs was promoted in the brains of type 2 diabetic mice after stroke. Our study reveals significant Treg plasticity in diabetic stroke.Abbreviations: Foxp3: forkhead box P3; IFN-γ: interferon-γ; IL-10: interleukin-10; IL-12: interleukin-12; MCAO: middle cerebral artery occlusion; PBS: phosphate-buffered saline; STAT1: Signal transducer and activator of transcription 1; STAT5: Signal transducer and activator of transcription 1; T-bet: T-box expressed in T cells; TGF-ß: transforming growth factor-ß; Th1: T helper 1; TNF-α: tumor necrosis factor-α; Tregs: regulatory T cells. Foxp3: forkhead box P3; IFN-γ: interferon-γ; IL-10: interleukin-10; IL-12: interleukin-12; MCAO: middle cerebral artery occlusion; PBS: phosphate-buffered saline; STAT1: Signal transducer and activator of transcription 1; STAT5: Signal transducer and activator of transcription 1; T-bet: T-box expressed in T cells; TGF-ß: transforming growth factor-ß; Th1: T helper 1; TNF-α: tumor necrosis factor-α; Tregs: regulatory T cells.

HyperCys: A Structure- and Sequence-Based Predictor of Hyper-Reactive Druggable Cysteines.

The cysteine side chain has a free thiol group, making it the amino acid residue most often covalently modified by small molecules possessing weakly electrophilic warheads, thereby prolonging on-target residence time and reducing the risk of idiosyncratic drug toxicity. However, not all cysteines are equally reactive or accessible. Hence, to identify targetable cysteines, we propose a novel ensemble stacked machine learning (ML) model to predict hyper-reactive druggable cysteines, named HyperCys. First, the pocket, conservation, structural and energy profiles, and physicochemical properties of (non)covalently bound cysteines were collected from both protein sequences and 3D structures of protein-ligand complexes. Then, we established the HyperCys ensemble stacked model by integrating six different ML models, including K-nearest neighbors, support vector machine, light gradient boost machine, multi-layer perceptron classifier, random forest, and the meta-classifier model logistic regression. Finally, based on the hyper-reactive cysteines' classification accuracy and other metrics, the results for different feature group combinations were compared. The results show that the accuracy, F1 score, recall score, and ROC AUC values of HyperCys are 0.784, 0.754, 0.742, and 0.824, respectively, after performing 10-fold CV with the best window size. Compared to traditional ML models with only sequenced-based features or only 3D structural features, HyperCys is more accurate at predicting hyper-reactive druggable cysteines. It is anticipated that HyperCys will be an effective tool for discovering new potential reactive cysteines in a wide range of nucleophilic proteins and will provide an important contribution to the design of targeted covalent inhibitors with high potency and selectivity.

Liquid-solid ratio during hydrothermal carbonization affects hydrochar application potential in soil: Based on characteristics comparison and economic benefit analysis.

Returning straw-like agricultural waste to the field by converting it into hydrochar through hydrothermal carbonization (HTC) is an important way to realize resource utilization of waste, soil improvement, and carbon sequestration. However, the large-scale HTC is highly limited by the large water consumption and waste liquid pollution. Here, we propose strategies to optimize the liquid-solid ratio (LSR) of HTC, and comprehensively evaluate the stability, soil application potential, and economic benefits of corn stover-based hydrochar under different LSRs. The results showed that the total amount of dissolved organic carbon of hydrochars increased by 55.0% as LSR reducing from 10:1 to 2:1, while the element content, thermal stability, carbon fixation potential, specific surface area, pore volume, and functional group type were not obviously affected. The specific surface area and pore volume of hydrochar decreased by 61.8% and 70.9% as LSR reduced to 1:1, due to incomplete carbonization. According to the gray relation, hydrochar derived at LSR of 10:1 and followed by 2:1 showed greatest relation degree of 0.80 and 0.70, respectively, indicating better soil application potential. However, reducing LSR from 10:1 to 2:1 made the income of single process production increased from -388 to 968 ¥, and the wastewater generation decreased by 80%. Considering the large-scale application of HTC in fields for farmland improvement and environmental remediation, the comprehensive advantages of optimized LSR will be further highlighted.

Digital measurement and correlation analysis of coronal and sagittal anatomic parameters in the radiographs of adolescent patients with idiopathic scoliosis.

OBJECTIVE: To use digital software to measure the morphologic and anatomic parameters of adolescent idiopathic scoliosis (AIS). Differences and correlations among different parameters were compared to provide an anatomic basis for the selection of treatment methods and preoperative evaluation of AIS. METHODS: Spinal radiographs were taken from 300 boys and girls (age, 10-18 years) suffering from idiopathic scoliosis in four grade-A hospitals in Inner Mongolia. After screening, 120 cases with complete imaging data were assessed. Imaging data were transferred to a work station (Dr Wise™). The anatomic indices of the Cobb Angle, CVA, AVT, TS, CA, CPT, CSI, FPT, CCA, TK, LL, SS, PT, and PI were measured. RESULTS: There were significant differences in AVT between different grades and types of scoliosis (F = 34.079, P = 0.000; χ2 = 23.379, P = 0.000). AVT was a protective factor, and the smaller the AVT, the less severe was the scoliosis. Compared with adolescents with mild or moderate scoliosis, the Cobb angle of adolescents with severe scoliosis was negatively correlated with CCA, LL, and SS (r = - 0.641, p < 0.05; r = - 0.695, p < 0.01; r = - 0.814, p < 0.01). CONCLUSIONS: Some of the anatomic parameters in the coronal and sagittal planes of adolescents with idiopathic scoliosis were significantly different according to the severity and type of scoliosis. Significant correlations were found between more anatomic indices in adolescents with severe scoliosis than in adolescents suffering from mild or moderate scoliosis.

Enhanced biological phosphorus removal in low-temperature sewage with iron-carbon SBR system.

This study proposed an AO-SBR (Anaerobic Aerobic Sequencing Batch Reactor) combined with iron-carbon micro-electrolysis (ICME) particles system for sewage treatment at low temperature and explored the dephosphorisation mechanism and microbial community structure. The experimental results illustrated that ICME particles contributed to phosphorus removal, metabolic mechanism of poly-phosphorus accumulating organism (PAO) and microbial community structure in the AO-SBR system. The optimal treatment effect was achieved under the conditions of pH 7, DO 3.0 mg/L and particle dosage of 2.6 g Fe-C/g MLSS, and the removal rates of COD, TP, NH4+-N and TN reached 80.56%, 91.46%, 69.42% and 57.57%. The proportion of phosphorus accumulating organisms (PAOs) increased from 4.54% in the SBR system to 10.89% in the ICME-SBR system at 10°C. Additionally, the metabolic rate of PAOs was promoted, and the activities of DHA and ETS both reached the maximum value of 13.34 and 102.88 µg·mg-1VSS·h-1. These results suggest that the ICME particles could improve the performance of activated sludge under low-temperature conditions. This technology provides a new way for upgrading the performance of sewage treatment in the cold area.

Targeted Recruitment and Degradation of Estrogen Receptor α by Photothermal Polydopamine Nanoparticles for Breast Tumor Ablation.

The major challenges of photothermal therapy (PTT) toward clinical application are the severe skin injury and inflammation response associated with high power laser irradiation. Herein, polydopamine nanoparticles (PDA-EST and PDA-RAL) targeted to estrogen receptor α (ERα) for efficient ablation of breast tumor under a low irradiation density of 0.1 W cm-2 are reported. These nanoparticles are capable of recruiting ERα on their surface and induce a complete ERα degradation via localized heat. Owing to the ERα targetability, PDA-EST and PDA-RAL strongly suppress the proliferation of breast cancer cells without causing significant inflammation. This work provides a generalized method for enhancing PTT efficacy under low irradiation density.

Bioinformatics identifies predictors of arteriovenous fistula maturation.

BACKGROUND: Arteriovenous fistulae (AVF) are the preferred access for hemodialysis but still have poor rates of maturation and patency limiting their clinical use. The underlying mechanisms of venous remodeling remain poorly understood, and only limited numbers of unbiased approaches have been reported. METHODS: Biological Gene Ontology (GO) term enrichment analysis and differentially expressed genes (DEG) analysis were performed for three AVF datasets. A microRNA enrichment analysis and L1000CDS2 query were performed to identify factors predicting AVF patency. RESULTS: The inflammatory and immune responses were activated during both early and late phases of AVF maturation, with upregulation of neutrophil and leukocyte regulation, cytokine production, and cytokine-mediated signaling. In men with failed AVF, negative regulation of myeloid-leukocyte differentiation and regulation of macrophage activation were significantly upregulated. Compared to non-diabetic patients, diabetic patients had significantly reduced immune response-related enrichment such as cell activation in immune response, regulation of immune-effector process, and positive regulation of defense response; in addition, diabetic patients showed no enrichment of the immune response-regulating signaling pathway. CONCLUSIONS: These data show coordinated, and differential regulation of genes associated with AVF maturation, and different patterns of several pathways are associated with sex differences in AVF failure. Inflammatory and immune responses are activated during AVF maturation and diabetes may impair AVF maturation by altering these responses. These findings suggest several novel molecular targets to improve sex specific AVF maturation.

Sex differences in arterial identity correlate with neointimal hyperplasia after balloon injury.

BACKGROUND: Endovascular treatment of atherosclerotic arterial disease exhibits sex differences in clinical outcomes including restenosis. However, sex-specific differences in arterial identity during arterial remodeling have not been described. We hypothesized that sex differences in expression of the arterial determinant erythropoietin-producing hepatocellular receptor interacting protein (Ephrin)-B2 occur during neointimal proliferation and arterial remodeling. METHODS AND RESULTS: Carotid balloon injury was performed in female and male Sprague-Dawley rats without or 14 days after gonadectomy; the left common carotid artery was injured and the right carotid artery in the same animal was used as an uninjured control. Arterial hemodynamics were evaluated in vivo using ultrasonography pre-procedure and post-procedure at 7 and 14 days and wall composition examined using histology, immunofluorescence and Western blot at 14 days after balloon injury. There were no significant baseline sex differences. 14 days after balloon injury, there was decreased neointimal thickness in female rats with decreased smooth muscle cell proliferation and decreased type I and III collagen deposition, as well as decreased TNFα- or iNOS-positive CD68+ cells and increased CD206- or TGM2-positive CD68+ cells. Female rats also showed less immunoreactivity of VEGF-A, NRP1, phosphorylated EphrinB2, and increased Notch1, as well as decreased phosphorylated Akt1, p38 and ERK1/2. These differences were not present in rats pretreated with gonadectomy. CONCLUSIONS: Decreased neointimal thickness in female rats after carotid balloon injury is associated with altered arterial identity that is dependent on intact sex hormones. Alteration of arterial identity may be a mechanism of sex differences in neointimal proliferation after arterial injury.

A multi-stage ensemble network system to diagnose adolescent idiopathic scoliosis.

OBJECTIVES: To develop a deep learning algorithm to automatically evaluate and diagnose scoliosis on full spinal X-ray images. METHODS: This retrospective study collected full spinal X-ray images (anteroposterior) from four hospital databases from January 1, 2018, to March 31, 2021. The data were divided into training and validation sets. Full spinal X-ray images for external validation were independently collected at one hospital from April 1, 2021, to June 30, 2021. Model effectiveness was validated with a public dataset. Statistical software R was used to analyze the accuracy and sensitivity of the model curvature and anatomical balance parameters and assess interrater consistency. RESULTS: This study included 788 and 185 training and test datasets, respectively. The accuracy and recall of the algorithm model for the Cobb angle, apical vertebrae (AV), upper vertebrae, and lower vertebrae were 89.36%, 85.71%, 77.2%, and 80.24% and 97.35%, 93.38%, 84.11%, and 87.42%, respectively. The symmetric mean absolute percentage error at the Cobb angle was 5.99%, and the automatic measurement time was 1.7 s. The mean absolute error values of the Cobb angle and the distances between the center sacral vertical line and AV and C7 plumb line were 1.07° and 1.12 and 1.38 mm, respectively. Statistical analysis confirmed that the Cobb angle results were in good agreement with the gold standard (interclass coefficients of 0.996, 0.978, and 0.825; p < 0.001). CONCLUSION: Our deep learning algorithm model had high sensitivity and accuracy for scoliosis, which could help radiologists improve their diagnostic efficiency. KEY POINTS: • Our deep learning algorithm model had high sensitivity and accuracy for scoliosis, which could help radiologists improve their diagnostic efficiency. • Multi-center validation data were used in this study to guarantee the reliability of the research. • Algorithmic model measures 200 times faster than radiologists.

Pre-procedural color duplex ultrasound evaluation predicts restenosis after long-segment superficial femoral artery stenting.

OBJECTIVES: Restenosis after stenting for superficial femoral artery atherosclerotic disease remains a significant clinical problem, especially for long-segment lesions. We assessed predictors of in-stent restenosis in patients with long-segment superficial femoral artery disease and hypothesized that pre-procedural ultrasound assessment would predict in-stent restenosis. METHODS: This single-center study retrospectively analyzed 283 limbs in 243 patients who treated with superficial femoral artery nitinol stent placement for long-segment (≥15 cm) lesions between 2015 and 2018. Color duplex ultrasound was performed pre-procedure and post-procedure at 3, 6, 12, 24, and 36 months. The endpoint was ≥50% in-stent restenosis in the superficial femoral artery. Primary patency rates were analyzed with Kaplan-Meier survival analysis and compared using the log-rank test. A multivariable Cox proportional hazards model was used to evaluate the risk factors for in-stent restenosis. RESULTS: The median length of lesions was 25.8 ± 8.1 cm. The cumulative freedom from ≥50% in-stent restenosis at 3, 6, 12, 24, and 36 months was 95.3%, 78.3%, 56.0%, 30.6%, and 15.9%, respectively. Univariate and multivariate Cox regression analysis showed that cumulative lesion length ≥ 25 cm (hazard ratio 1.681; p = 0.003), calcified plaque (hazard ratio 1.549, p = 0.006), poor runoff scores >10 (hazard ratio 1.870, p = 0.003), and chronic renal failure (hazard ratio 2.075, p = 0.009) were independent risk factors for in-stent restenosis. The agreement rate between ultrasound and angiography was 92.6% for cumulative lesion length (κ 0.851) and 91.9% for runoff score (κ 0.872). CONCLUSIONS: The results indicate that pre-procedural color duplex ultrasound evaluation is helpful for the selection of appropriate candidates for superficial femoral artery stent placement. Cumulative lesion length ≥25 cm, plaque calcification, poor distal runoff, and chronic renal failure independently predicted in-stent restenosis.

CovPDB: a high-resolution coverage of the covalent protein-ligand interactome.

In recent years, the drug discovery paradigm has shifted toward compounds that covalently modify disease-associated target proteins, because they tend to possess high potency, selectivity, and duration of action. The rational design of novel targeted covalent inhibitors (TCIs) typically starts from resolved macromolecular structures of target proteins in their apo or holo forms. However, the existing TCI databases contain only a paucity of covalent protein-ligand (cP-L) complexes. Herein, we report CovPDB, the first database solely dedicated to high-resolution cocrystal structures of biologically relevant cP-L complexes, curated from the Protein Data Bank. For these curated complexes, the chemical structures and warheads of pre-reactive electrophilic ligands as well as the covalent bonding mechanisms to their target proteins were expertly manually annotated. Totally, CovPDB contains 733 proteins and 1,501 ligands, relating to 2,294 cP-L complexes, 93 reactive warheads, 14 targetable residues, and 21 covalent mechanisms. Users are provided with an intuitive and interactive web interface that allows multiple search and browsing options to explore the covalent interactome at a molecular level in order to develop novel TCIs. CovPDB is freely accessible at http://www.pharmbioinf.uni-freiburg.de/covpdb/ and its contents are available for download as flat files of various formats.