Thymic Rosai-Dorfmann disease: a case report.

BACKGROUND: Rosai-Dorfman disease (RDD), known as sinus histiocytosis with massive lymphadenopathy, commonly involves lymph nodes in the neck or mediastinum, although extranodal involvement is observed in approximately 40% of RDD patients. RDD involving only the thymus has rarely been reported. Here, we report a case of RDD originating in the thymus. The lesion was surgically removed, and a cure was finally achieved. There was no recurrence after telephone follow-up for 3 years. CASE PRESENTATION: A 52-year-old male was accidentally found to have a 7 × 6 cm anterior mediastinum lump by chest computed tomography (CT). The mediastinal lesion was resected by surgery, and postoperative pathology revealed RDD originating from the thymus. Regular telephone follow-up after surgery lasted 3 years and showed that the patient remained in good condition without any relevant symptoms. CONCLUSIONS: RDD originating in the thymus cannot be characterized from CT images and is easily misdiagnosed as a traditional mediastinal tumor. This is mainly because there is so little disease in this area that physicians are not aware of it. We report this case with the hope that clinicians will have a better understanding of this disease. According to our follow-up results, surgery is an effective means of treatment.

Ensemble multiclassification model for predicting developmental toxicity in zebrafish.

In recent years, with the rapid development of society, organic compounds have been released into aquatic environments in various forms, posing a significant threat to the survival of aquatic organisms. The assessment of developmental toxicity is an important part of environmental safety risk systems, helping to identify the potential impacts of organic compounds on the embryonic development of aquatic organisms and enabling early detection and warning of potential ecological risks. Additionally, binary classification models cannot accurately classify organic compounds. Therefore, it is crucial to construct a multiclassification model for predicting the developmental toxicity of organic compounds. In this study, binary and multiclassification models were developed based on the ToxCast™ Phase I chemical library and literature data. The random forest, support vector machine, extreme gradient boosting, adaptive gradient boosting, and C5.0 decision tree algorithms, as well as 8 types of molecular fingerprint were used to establish a multiclassification base model for predicting developmental toxicity through 5-fold cross-validation and external validation. Ultimately, a multiclassification ensemble model was derived through a voting method. The performance of the binary ensemble model, as measured by the balanced accuracy, was 0.918, while that of the multiclassification model was 0.819. The developmental toxicity voting ensemble model (DT-VEM) achieved accuracies of 0.804, 0.834, and 0.855. Furthermore, by utilizing the XGBoost machine learning algorithm to construct separate models for molecular descriptors and substructure molecular fingerprints, we identified several substructures and physical properties related to developmental toxicity. Our research contributes to a more detailed classification of developmental toxicity, providing a new and valuable tool for predicting the developmental toxicity effects of unknown compounds. This supplement addresses the limitations of previous tools, as it offers an enhanced ability to predict potential developmental toxicity in novel compounds.

Causal relationship between intervertebral disc degeneration and osteoporosis: a bidirectional two-sample Mendelian randomization study.

Introduction: The relationship between intervertebral disc degeneration (IVDD) and osteoporosis (OP), diagnosed primarily using bone mineral density (BMD), remains unclear so far. The present study, therefore, aimed to investigate the potential relationship between osteoporosis and intervertebral disc degeneration using Mendelian randomization and genome-wide association analyses. Specifically, the impact of bone mineral density on the development of intervertebral disc degeneration was evaluated. Materials and methods: The genome-wide association studies (GWAS) summary data of OP/BMDs and IVDD were collected from the FinnGen consortium, the GEFOS consortium, and MRC-IEU. The relationship between IVDD and OP was then explored using TSMR. The inverse-variance weighted (IVW) method was adopted as the primary effect estimate, and the reliability and stability of the results were validated using various methods, including MR-Egger, weighted median, simple mode, weighted mode, and MR-PRESSO. Results: No significant causal relationship was observed between OP and IVDD (IVW, P > 0.05) or between femoral neck BMD (FA-BMD) and IVDD when OP and FA-BMD were used as exposures. However, increased levels of total body BMD (TB-BMD) and lumbar spine BMD (LS-BMD) were revealed as significant risk factors for IVDD (TB-BMD: IVW, OR = 1.201, 95% CI: 1.123-1.284, P = 8.72 × 10-8; LS-BMD: IVW, OR = 1.179, 95% CI: 1.083-1.284, P = 1.43 × 10-4). Interestingly, both heel BMD (eBMD) and femur neck BMD (FN-BMD) exhibited potential causal relationships (eBMD: IVW, OR = 1.068, 95% CI: 1.008-1.131, P = 0.0248; FN-BMD, IVW, OR = 1.161, 95% CI: 1.041-1.295, P = 0.0074) with the risk of IVDD. The reverse MR analysis revealed no statistically causal impact of IVDD on OP and the level of BMD (P > 0.05). Conclusion: OP and the level of FA-BMD were revealed to have no causal relationship with IVDD. The increased levels of TB-BMD and LS-BMD could promote the occurrence of IVDD. Both eBMD and FN-BMD have potential causal relationships with the risk of IVDD. No significant relationship exists between IVDD and the risk of OP. Further research is warranted to comprehensively comprehend the molecular mechanisms underlying the impact of OP and BMD on IVDD and vice versa.

Riddle of the Sphinx: Emerging role of circular RNAs in cervical cancer.

Cervical cancer is a prominent cause of cancer-related mortality among women, with recent attention directed toward exploring the involvement of circular RNAs (circRNAs) in this particular cancer. CircRNAs, characterized by a covalently closed loop structure, belong to a class of single-stranded non-coding RNA (ncRNA) molecules that play crucial roles in cancer development and progression through diverse mechanisms. The abnormal expression of circRNAs in vivo is significantly associated with the development of cervical cancer. Notably, circRNAs actively interact with miRNAs in cervical cancer, leading to the regulation of diverse signaling pathways, and they can contribute to cancer hallmarks such as self-sufficiency in growth signals, insensitivity to antigrowth signals, limitless proliferation, evading apoptosis, tissue invasion and metastasis, and sustained angiogenesis. Moreover, the distinctive biomedical attributes exhibited by circRNAs, including their abundance, conservation, and stability in body fluids, position them as promising biomarkers for various cancers. In this review, we elucidate the tremendous potential of circRNAs as diagnostic markers or therapeutic targets in cervical cancer by expounding upon their biogenesis, characteristics, functions, and databases, highlighting the novel advances in the signaling pathways associated with circRNAs in cervical cancer.

A Novel Strategy for Extracting Richer Semantic Information Based on Fault Detection in Power Transmission Lines.

With the development of the smart grid, the traditional defect detection methods in transmission lines are gradually shifted to the combination of robots or drones and deep learning technology to realize the automatic detection of defects, avoiding the risks and computational costs of manual detection. Lightweight embedded devices such as drones and robots belong to small devices with limited computational resources, while deep learning mostly relies on deep neural networks with huge computational resources. And semantic features of deep networks are richer, which are also critical for accurately classifying morphologically similar defects for detection, helping to identify differences and classify transmission line components. Therefore, we propose a method to obtain advanced semantic features even in shallow networks. Combined with transfer learning, we change the image features (e.g., position and edge connectivity) under self-supervised learning during pre-training. This allows the pre-trained model to learn potential semantic feature representations rather than relying on low-level features. The pre-trained model then directs a shallow network to extract rich semantic features for downstream tasks. In addition, we introduce a category semantic fusion module (CSFM) to enhance feature fusion by utilizing channel attention to capture global and local information lost during compression and extraction. This module helps to obtain more category semantic information. Our experiments on a self-created transmission line defect dataset show the superiority of modifying low-level image information during pre-training when adjusting the number of network layers and embedding of the CSFM. The strategy demonstrates generalization on the publicly available PASCAL VOC dataset. Finally, compared with state-of-the-art methods on the synthetic fog insulator dataset (SFID), the strategy achieves comparable performance with much smaller network depths.

Bakuchiol inhibits lung cancer by modulating tumor microenvironment and the expression of PD-L1.

Immune checkpoint therapy is an emerging frontier in cancer therapy. With the aim to develop an efficient herb derived compound to facilitate immune checkpoint therapy, here we investigate if a herb-derived compound, Bakuchiol (BAK), can be used to treat lung cancer and elucidate if BAK could serve as a PD-L1 regulator. To this end, a murine lung cancer model was established by subcutaneously inoculating murine Lewis lung carcinoma (LLC) cells. BAK of 5 to 40 mg/kg was used for treatment in vivo for 15 days. On Day 15, the population of CD4+ and CD8+ T cells, Treg cells. BAK could effectively inhibit tumor growth by starting treatment either on Day 0 or 6 after tumor inoculation at doses of 5-40 mg/kg. BAK treatment increased the population of cytotoxic immune cells (i.e., CD8+ T cells, and M1 macrophages), meanwhile decreasing pro-tumor immune cells (i.e., CD3+ T cells, Treg cells, and M2 macrophages). Anti-inflammatory cytokines, including IL1ß, IL2, IFNγ, TNF-α, IL4 and IL10 were upregulated by BAK. PD-L1 expression in the tumor was also lowered by BAK. AKT and STAT3 signaling were inhibited by BAK. BAK is an efficient agent in reducing LLC tumor growth. These data support the potential of BAK as a new drug for treating lung cancer by serving as a PD-L1 inhibitor that suppresses the activation of AKT and STAT3.

The three steps method for uniportal video-assisted thoracoscopic right upper lobectomy.

BACKGROUND: The uniportal video-assisted thoracoscopic right upper lobectomy (UVATRUL), as a common procedure for thoracic surgeons, is difficult to manipulate and has some inherent challenges. To solve both of problems, we summarized a series of techniques as the three steps method and investigated its feasibility on the patients of right upper lung cancer. METHODS: Forty-eight patients with right upper lobe lung cancer who underwent the three steps method UVATRUL in our hospital from January 2020 to May 2022 were selected as the three steps method group. Forty-seven patients who underwent the traditional UVATRUL were selected as the traditional method group. The intraoperative condition and postoperative condition of the two groups were retrospectively analysed. Multiple linear regression analysis was carried out to analyze the relationship between positive results and surgical method. RESULTS: All patients had successfully completed their surgeries. There was no significant difference between the two groups in respect of intraoperative blood loss, rate of conversion, day one thoracic drainage volume, chest tube indwelling time, incidence of postoperative complications, number of lymph node, and postoperative hospital stay (P > 0.05). Operative time of the three steps method group was significantly shorter than the traditional method group (P < 0.001), and number of reloads used was also significantly less than the traditional method group (P = 0.014). Multiple linear regression analysis showed that operative time (ß = - 0.470, P < 0.001), and number of reloads (ß = - 0.254, P = 0.007) correlated with surgical method. CONCLUSION: Compared with the traditional UVATRUL, the three steps method trims the surgery procedures, shortens the operative time, and reduces the use of reloads which makes it an effective procedure for UVATRUL.

Single-port thoracoscopic removal of an azygos vein aneurysm: a case report and literature review.

BACKGROUND: Azygos vein aneurysms (AVAs) are extremely rare. The majority of patients have no obvious clinical symptoms, so they are found by physical examination or by chance. There is limited clinical treatment experience that can be referred to, and there are no clear guidelines or research evidence standardizing the surgical and interventional therapy. Here, we report a patient with idiopathic AVA whose three-dimensional reconstruction of the tumor was completed before surgery. On the basis of three-dimensional reconstruction, single-port thoracoscopic resection of the AVA was successfully completed and reported for the first time. The previously reported cases are summarized to provide guidance for the diagnosis and treatment of patients with AVAs. CASE PRESENTATION: A 56-year-old man was transferred to our hospital due to "dysphagia". The diagnosis of AVA was made after enhanced computed tomography, gastroscopy, fiberoptic bronchoscopy, and three-dimensional reconstruction. Congenital weakness or degenerative changes causes the vein walls to be extremely thin that the AVA had the risk of ruptur. Furthermore, the patient had symptoms of dysphagia, he received single-port thoracoscopic surgery. After the operation, his dysphagia disappeared. The postoperative pathology confirmed hemangioma. The patient was discharged 3 days after surgery without any complications. CONCLUSIONS: AVAs are rare. Preoperative three-dimensional reconstruction can greatly help surgeons clarify the disease diagnosis, formulate the surgical plan, avoid damage to the surrounding vital organs, and reduce intraoperative bleeding. Thoracoscopic surgery to remove AVAs is difficult and has a high risk of bleeding, while more minimally invasive single-port thoracoscopic surgery is also safe and effective for the treatment of AVAs.

Ensemble multiclassification model for aquatic toxicity of organic compounds.

With environmental pollution becoming increasingly serious, organic compounds have become the main hazard of environmental pollution and exert substantial negative impacts on aquatic organisms. In research pertaining to the acute toxicity of organic compounds, traditional biological experimental methods are time-consuming and expensive. In addition, computer-aided binary classification models cannot accurately classify acute toxicity. Therefore, the multiclassication model is necessary for more accurate classification of acute toxicity. In this study, median lethal concentrations of 373 organic compounds in the environmental toxicology datasets ECOTOX and EAT5 were used. These chemicals were classified into four categories based on the European Economic Community criteria. Then the random forest, support vector machine, extreme gradient boosting, adaptive gradient boosting, and C5.0 decision tree algorithms and eight molecular fingerprints were used to build a multiclassification base model for the acute toxicity of organic compounds. The base models were repeated 100 times with fivefold cross-validation and external validation. The ensemble model was obtained by the voting method. The best base classifier was ExtendFP-C5.0, which had an accuracy, sensitivity and specificity values of 87.30%, 87.32% and 95.76% for external validation, and the voting ensemble model performance of 96.92%, 96.93% and 98.97%, respectively. The ensemble model achieved a higher accuracy than previously reported studies. Our study will help to further classify the acute toxicity of organic compounds to aquatic organisms and predict the hazard classes of organic compounds.

Synergism Effect of Dendrobine on Cisplatin in Treatment of H1299 by Modulating the Balance of Treg/Th17.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for about 80% of lung cancers. Cisplatin is a broad-spectrum anti-cancer drug and is often used in combination with other drugs. Research suggests that dendrobine, a pyrrolizidine derivative alkaloid, exhibits antitumor activity in various cancers. This study explores the effect of dendrobine combined with cisplatin on NSCLC and its underlying molecular mechanism. METHODS: The effects of dendrobine combined with cisplatin on tumor progression were evaluated by xenograft model (in vivo) and clonogenic survival assay (in vitro) using H1299 cell line. Annexin V staining was used for detecting apoptotic cells. The population of T cells, B cells and other subpopulations in the peripheral blood was determined by flow cytometry. RESULTS: Dendrobine combined with cisplatin prolonged the survival of mice implanted with H1299 cells and reduced tumor volume compared with single drug application. However, dendrobine exhibited no effect on H1299 cells in clonal survival assays with or without cisplatin treatment and did not promote cisplatin-induced apoptosis in vitro. Importantly, dendrobine suppressed the regulatory T cells (Treg cells) and enhanced the T helper 17 cells (Th17 cells). Treatment of dendrobine significantly reduced Foxp3, and increased the level of IL-17 in serum. CONCLUSION: Dendrobine displayed a synergistic effect with cisplatin to exert anti-tumor effect in vivo, which might be achieved by modulating the balance of Treg/Th17 cells rather than regulating cell apoptosis.

Overexpressed SNRPB/D1/D3/E/F/G correlate with poor survival and immune infiltration in hepatocellular carcinoma.

BACKGROUND: Prior reports have indicated that the abnormal expression of small nuclear ribonucleoproteins (snRNPs) genes is related to malignant tumors. However, in hepatocellular carcinoma (HCC), the precise role of snRNPs is not well understood. Therefore, the purpose of this study was to evaluate the prognostic roles of SNRPB/D1/D2/D3/E/F/G and their correlation to immune infiltration in HCC. METHODS: The study was carried out via the following databases, software, and experimental validation: ONCOMINE, GEPIA2, UALCAN, The Cancer Genome Atlas, Gene Expression Omnibus, ArrayExpress, Kaplan-Meier plotter, cBioPortal, STRING, DAVID 6.8, TIMER, Cytoscape software, and immunohistochemistry experiments. RESULTS: Overexpressed SNRPB/D1/D2/D3/E/F/G proteins were found in HCC tissues. The transcription levels of 7 snRNPs genes were related to the TP53 mutation and tumor grades. SNRPB/D1/D2/D3/F/G expression was significantly correlated with cancer staging, whereas SNRPE was not. Moreover, Kaplan-Meier survival analysis showed that upregulation of SNRPB/D1/D2/E/G was relevant to worse OS in HCC patients, especially in patients with alcohol consumption and those without viral hepatitis. Multivariate Cox regression analysis indicated that expression of SNRPB/D1/D3/E/F/G were independent prognostic factors for unfavorable OS in HCC. In addition, a high mutation rate of snRNPs genes (44%) was also found in HCC. The mRNA expression levels of snRNPs were meaningfully and positively related to six types of infiltrating immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophil, macrophage, and dendritic cells). Also, SNRPB/D1/G genes were significantly associated with molecular markers of various immune cells in HCC. CONCLUSIONS: SNRPB/D1/D3/E/F/G are potential prognostic biomarkers for a short OS in HCC, and SNRPB/D1/G were novel immune therapy targets in HCC patients.

Genetic Variants Associated with Chronic Obstructive Pulmonary Disease Risk: Cumulative Epidemiological Evidence from Meta-Analyses and Genome-Wide Association Studies.

Background: Last two decades, many association studies on genetic variants and chronic obstructive pulmonary disease (COPD) risk have been published. But results from different studies are inconsistent. Therefore, we performed this article to systematically evaluate results from previous meta-analyses and genome-wide association studies (GWASs). Material and Methods. Firstly, we retrieved meta-analyses in PubMed, Embase, and China National Knowledge Infrastructure and GWASs in PubMed and GWAS catalog on or before April 7th, 2022. Then, data were extracted and screened. Finally, two main methods-Venice criteria and false-positive report probability test-were used to evaluate significant associations. Results: As a result, eighty-eight meta-analyses and 5 GWASs were deemed eligible for inclusion. Fifty variants in 26 genes obtained from meta-analyses were significantly associated with COPD risk. Cumulative epidemiological evidence of an association was graded as strong for 10 variants in 8 genes (GSTM1, CHRNA, ADAM33, SP-D, TNF-α, VDBP, HMOX1, and HHIP), moderate for 6 variants in 5 genes (PI, GSTM1, ADAM33, TNF-α, and VDBP), and weak for 40 variants in 23 genes. Five variants in 4 genes showed convincing evidence of no association with COPD risk in meta-analyses. Additionally, 29 SNPs identified in GWASs were proved to be noteworthy based on the FPRP test. Conclusion: In summary, more than half (52.38%) of genetic variants reported in previous meta-analyses showed no association with COPD risk. However, 13 variants in 9 genes had moderate to strong evidence for an association. This article can serve as a useful reference for further studies.

SNRPD1/E/F/G Serve as Potential Prognostic Biomarkers in Lung Adenocarcinoma.

Objectives: Sm proteins (SNRPB/D1/D2/D3/E/F/G), involved in pre-mRNA splicing, were previously reported in the tumorigenesis of several cancers. However, their specific role in lung adenocarcinoma (LUAD) remains obscure. Our study aims to feature abnormal expressions and mutations of genes for Sm proteins and assess their potential as therapeutic targets via integrated bioinformatics analysis. Methods: In this research, we explored the expression pattern and prognostic worth of genes for Sm proteins in LUAD across TCGA, GEO, UALCAN, Oncomine, Metascape, David 6.8, and Kaplan-Meier Plotter, and confirmed its independent prognostic value via univariate and multivariate cox regression analysis. Meanwhile, their expression patterns were validated by RT-qPCR. Gene mutations and co-expression of genes for Sm proteins were analyzed by the cBioPortal database. The PPI network for Sm proteins in LUAD was visualized by the STRING and Cytoscape. The correlations between genes for Sm proteins and immune infiltration were analyzed by using the "GSVA" R package. Results: Sm proteins genes were found upregulated expression in both LUAD tissues and LUAD cell lines. Moreover, highly expressed mRNA levels for Sm proteins were strongly associated with short survival time in LUAD. Genes for Sm proteins were positively connected with the infiltration of Th2 cells, but negatively connected with the infiltration of mast cells, Th1 cells, and NK cells. Importantly, Cox regression analysis showed that high SNRPD1/E/F/G expression were independent risk factors for the overall survival of LUAD. Conclusion: Our study showed that SNRPD1/E/F/G could independently predict the prognostic outcome of LUAD and was correlated with immune infiltration. Also, this report laid the foundation for additional exploration on the potential treatment target's role of SNRPD1/E/F/G in LUAD.

PRPS2 Enhances Resistance to Cisplatin via Facilitating Exosomes-mediated Macrophage M2 Polarization in Non-small Cell Lung Cancer.

BACKGROUND: Phosphoribosyl pyrophosphate synthetases 2 (PRPS2) is reported as an oncogene in various cancers. However, the role of PRPS2 in cisplatin (DDP) resistance of non-small cell lung cancer (NSCLC) remains unclear. The present study aimed to explore the effect of PRPS2 in DDP resistance of NSCLC. METHODS: mRNA expression levels of genes were detected by RT-PCR. Enzyme-linked immunosorbent assay (ELISA) and Western blot were used to detect protein expression levels. Cell viability was determined by the MTT assay and colony formation assay. Cell apoptosis was detected using nucleosome ELISA assay and caspase-3 activity assay. PRPS2 silencing was achieved using siRNA transfection. Exosomes of cultured cells were isolated through ultracentrifugation. RESULTS: Elevated PRPS2 was correlated with DDP resistance and poor prognosis in NSCLC patients. PRPS2 silencing enhanced sensitivity of DDP-resistant cells to DDP treatment. NSCLC cell-derived exosome induced M2 macrophage polarization. PRPS2 was enriched in the exosomes of NSCLC cells. Exosomal PRPS2 mediated M2 macrophage polarization to promote DDP resistance of NSCLC cells. CONCLUSIONS: In conclusion, PRPS2 potentiates resistance to DDP by promoting exosome-mediated macrophage M2 polarization in NSCLC.

Assessment of prediction methods for protein structures determined by NMR in CASP14: Impact of AlphaFold2.

NMR studies can provide unique information about protein conformations in solution. In CASP14, three reference structures provided by solution NMR methods were available (T1027, T1029, and T1055), as well as a fourth data set of NMR-derived contacts for an integral membrane protein (T1088). For the three targets with NMR-based structures, the best prediction results ranged from very good (GDT_TS = 0.90, for T1055) to poor (GDT_TS = 0.47, for T1029). We explored the basis of these results by comparing all CASP14 prediction models against experimental NMR data. For T1027, NMR data reveal extensive internal dynamics, presenting a unique challenge for protein structure prediction methods. The analysis of T1029 motivated exploration of a novel method of "inverse structure determination," in which an AlphaFold2 model was used to guide NMR data analysis. NMR data provided to CASP predictor groups for target T1088, a 238-residue integral membrane porin, was also used to assess several NMR-assisted prediction methods. Most groups involved in this exercise generated similar beta-barrel models, with good agreement with the experimental data. However, as was also observed in CASP13, some pure prediction groups that did not use any NMR data generated models for T1088 that better fit the NMR data than the models generated using these experimental data. These results demonstrate the remarkable power of modern methods to predict structures of proteins with accuracies rivaling solution NMR structures, and that it is now possible to reliably use prediction models to guide and complement experimental NMR data analysis.

Role of backbone strain in de novo design of complex α/ß protein structures.

We previously elucidated principles for designing ideal proteins with completely consistent local and non-local interactions which have enabled the design of a wide range of new αß-proteins with four or fewer ß-strands. The principles relate local backbone structures to supersecondary-structure packing arrangements of α-helices and ß-strands. Here, we test the generality of the principles by employing them to design larger proteins with five- and six- stranded ß-sheets flanked by α-helices. The initial designs were monomeric in solution with high thermal stability, and the nuclear magnetic resonance (NMR) structure of one was close to the design model, but for two others the order of strands in the ß-sheet was swapped. Investigation into the origins of this strand swapping suggested that the global structures of the design models were more strained than the NMR structures. We incorporated explicit consideration of global backbone strain into the design methodology, and succeeded in designing proteins with the intended unswapped strand arrangements. These results illustrate the value of experimental structure determination in guiding improvement of de novo design, and the importance of consistency between local, supersecondary, and global tertiary interactions in determining protein topology. The augmented set of principles should inform the design of larger functional proteins.

Massive hemothorax caused by intercostal artery pseudoaneurysm:a case report.

BACKGROUND: Intercostal artery pseudoaneurysm is rare and at the risk of rupture. The aetiology is always reported to be iatrogenic and traumatic injury. Embolisation is the most common therapeutic method. Here, we report a case of spontaneous intercostal artery pseudoaneurysm and cured by combining covered stent grafting and surgical management. CASE PRESENTATION: A 60-year-old man complained of acute right back pain for 5 h. Computed tomography showed right massive hemothorax and a giant mass with distinct feeding vessel originated from the thoracic aorta within the right hemithorax. Thoracocentesis was performed, and then a covered stent was positioned across the origin of the feeding vessel. The patient was diagnosed with intercostal artery pseudoaneurysm. Finally, we successfully resected the pseudoaneurysm and ligated the proximal part of the artery. Histologic examination have proved the diagnosis. The postoperative course was uneventful, and the patient was discharged on postoperative day 10. There is no recurrence reported during follow-up. CONCLUSIONS: Spontaneous intercostal artery pseudoaneurysm is extremly rare. Delayed hemothorax due to rupture of the pseudoaneurysm may occur years after the formation. Early diagnosis is important and a combined treatment of endovascular intervention and surgical management is feasible, especially for the case of ruptured large tumour-like mass presentation of the pseudoaneurysm.

REDCRAFT: A computational platform using residual dipolar coupling NMR data for determining structures of perdeuterated proteins in solution.

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the three primary experimental means of characterizing macromolecular structures, including protein structures. Structure determination by solution NMR spectroscopy has traditionally relied heavily on distance restraints derived from nuclear Overhauser effect (NOE) measurements. While structure determination of proteins from NOE-based restraints is well understood and broadly used, structure determination from Residual Dipolar Couplings (RDCs) is relatively less well developed. Here, we describe the new features of the protein structure modeling program REDCRAFT and focus on the new Adaptive Decimation (AD) feature. The AD plays a critical role in improving the robustness of REDCRAFT to missing or noisy data, while allowing structure determination of larger proteins from less data. In this report we demonstrate the successful application of REDCRAFT in structure determination of proteins ranging in size from 50 to 145 residues using experimentally collected data, and of larger proteins (145 to 573 residues) using simulated RDC data. In both cases, REDCRAFT uses only RDC data that can be collected from perdeuterated proteins. Finally, we compare the accuracy of structure determination from RDCs alone with traditional NOE-based methods for the structurally novel PF.2048.1 protein. The RDC-based structure of PF.2048.1 exhibited 1.0 Å BB-RMSD with respect to a high-quality NOE-based structure. Although optimal strategies would include using RDC data together with chemical shift, NOE, and other NMR data, these studies provide proof-of-principle for robust structure determination of largely-perdeuterated proteins from RDC data alone using REDCRAFT.

A common binding motif in the ET domain of BRD3 forms polymorphic structural interfaces with host and viral proteins.

The extraterminal (ET) domain of BRD3 is conserved among BET proteins (BRD2, BRD3, BRD4), interacting with multiple host and viral protein-protein networks. Solution NMR structures of complexes formed between the BRD3 ET domain and either the 79-residue murine leukemia virus integrase (IN) C-terminal domain (IN329-408) or its 22-residue IN tail peptide (IN386-407) alone reveal similar intermolecular three-stranded ß-sheet formations. 15N relaxation studies reveal a 10-residue linker region (IN379-388) tethering the SH3 domain (IN329-378) to the ET-binding motif (IN389-405):ET complex. This linker has restricted flexibility, affecting its potential range of orientations in the IN:nucleosome complex. The complex of the ET-binding peptide of the host NSD3 protein (NSD3148-184) and the BRD3 ET domain includes a similar three-stranded ß-sheet interaction, but the orientation of the ß hairpin is flipped compared with the two IN:ET complexes. These studies expand our understanding of molecular recognition polymorphism in complexes of ET-binding motifs with viral and host proteins.

A Time Delay Neural Network Based Technique for Nonlinear Microwave Device Modeling.

This paper presents a nonlinear microwave device modeling technique that is based on time delay neural network (TDNN). The proposed technique can accurately model the nonlinear microwave devices when compared to static neural network modeling method. A new formulation is developed to allow for the proposed TDNN model to be trained with DC, small-signal, and large signal data, which can enhance the generalization of the device model. An algorithm is formulated to train the proposed TDNN model efficiently. This proposed technique is verified by GaAs metal-semiconductor-field-effect transistor (MESFET), and GaAs high-electron mobility transistor (HEMT) examples. These two examples demonstrate that the proposed TDNN is an efficient and valid approach for modeling various types of nonlinear microwave devices.