A bronchogenic cyst, presenting as a retroperitoneal cystic mass

Bronchogenic cysts are mostly benign, congenital abnormalities originating from the remnants of the primitive foregut. A retroperitoneal location is rare. Due to the mostly asymptomatic behavior and the historical confusion regarding histology, an exact prevalence is not known. We present here a case report of a retroperitoneal bronchogenic cyst. A literature review was performed for cases of retroperitoneal bronchogenic cysts written in English. Anatomopathological criteria for inclusion were pseudo stratified, ciliated, columnar epithelium together with the presence of at least one of the following: cartilage, smooth muscle or seromucous glands. In addition, the embryology, pathogenesis, radiological, clinical and suggested treatment modalities are reviewed. We report the surgical excision of a retroperitoneal bronchogenic cyst that presented as a non-functioning left adrenal mass. Our review of literature revealed only 62 potential cases of retroperitoneal bronchogenic cysts. After applying the strict anatomopathological criteria, only 30 cases of true retroperitoneal bronchogenic cysts could be identified. Retroperitoneal location of a bronchogenic cyst is rare. Despite the rarity of this pathologic entity, bronchogenic cysts should be considered in the differential diagnosis of retroperitoneal cystic lesions. Only histology can confirm definitive diagnosis. Surgery remains the recommended treatment of choice

A fast VLSI architecture for full-search variable block size motion estimation in MPEG--4 AVC/H.264

We describe a fast VLSI architecture for full-search motion estimation for the blocks with 7 different sizes in MPEG-4 AVC/H.264. The proposed variable block size motion estimation (VBSME) architecture consists of a 16x16 PE array, an adder tree and comparators to find all 41 motion vectors and their minimum SADs for the blocks of 16x16, 16x8, 8x16, 8x8, 8x4, 4x8 and 4x4. It employs a 2-D datapath and its control of the search area data is simple and regular. The proposed VBSME can achieve 100% PE utilization by employing a preload register and a search data buffer inside each PE and allow real-time processing of 4CIF(704x576) video with 15 fps at 100 Mhz for a search range of [-32~+31]

Small Object Detection in Infrared Images: Learning from Imbalanced Cross-Domain Data via Domain Adaptation

Deep learning-based object detection is one of the most popular research topics. However, in cases where large-scale datasets are unavailable, the training of detection models remains challenging due to the data-driven characteristics of deep learning. Small object detection in infrared images is such a case. To solve this problem, we propose a YOLOv5-based framework with a novel training strategy based on the domain adaptation method. First, an auxiliary domain classifier is combined with the YOLOv5 architecture to compose a detection framework that is trainable using datasets from multiple domains while maintaining calculation costs in the inference stage. Secondly, a new loss function based on Wasserstein distance is proposed to deal with small-sized objects by overcoming the problem of the intersection over union sensitivity problem in small-scale cases. Then, a model training strategy inspired from domain adaptation and knowledge distillation is presented. Using the domain confidence output of the domain classifier as a soft label, domain confusion loss is backpropagated to force the model to extract domain-invariant features while training the model with datasets with imbalanced distributions. Additionally, we generate a synthetic dataset in both the visible light and infrared spectrum to overcome the data shortage. The proposed framework is trained on the MS COCO, VEDAI, DOTA, ADAS Thermal datasets along with a constructed synthetic dataset for human detection and vehicle detection tasks. The experimental results show that the proposed framework achieved the best mean average precision (mAP) of 64.7 and 57.5 in human and vehicle detection tasks. Additionally, the ablation experiment shows that the proposed training strategy can improve the performance by training the model to extract domain-invariant features

Quantifying the Public Health Benefits of Reducing Air Pollution: Critically Assessing the Features and Capabilities of WHO’s AirQ+ and U.S. EPA’s Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP—CE)

Scientific evidence spanning experimental and epidemiologic studies has shown that air pollution exposures can lead to a range of health effects. Quantitative approaches that allow for the estimation of the adverse health impacts attributed to air pollution enable researchers and policy analysts to convey the public health impact of poor air quality. Multiple tools are currently available to conduct such analyses, which includes software packages designed by the World Health Organization (WHO): AirQ+, and the U.S. Environmental Protection Agency (U.S. EPA): Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP—CE), to quantify the number and economic value of air pollution-attributable premature deaths and illnesses. WHO’s AirQ+ and U.S. EPA’s BenMAP—CE are among the most popular tools to quantify these effects as reflected by the hundreds of peer-reviewed publications and technical reports over the past two decades that have employed these tools spanning many countries and multiple continents. Within this paper we conduct an analysis using common input parameters to compare AirQ+ and BenMAP—CE and show that the two software packages well align in the calculation of health impacts. Additionally, we detail the research questions best addressed by each tool

Identification of ᴅ-amino acid-containing peptides in human serum

<div><p>Biologically uncommon d-aspartate (d-Asp) residues have been shown to accumulate in proteins associated with age-related human disorders, such as cataract and Alzheimer disease. Such d-Asp-containing proteins are unlikely to be broken down completely because metabolic enzymes recognize only proteins or peptides composed exclusively of l-amino acids. Therefore, undigested d-Asp-containing peptides may exist in blood and, if detectable, may be a useful biomarker for associated diseases. In this study, we investigated d-amino acid-containing peptides in adult human serum by a qualitative d-amino acid analysis based on a diastereomer method and LC-MS/MS method. As a result, two d-Asp-containing peptides were detected in serum, both derived from the fibrinogen β-chain, a glycoprotein that helps in the formation of blood clots. One of the peptides was fibrinopeptide B, which prevents fibrinogen from forming polymers of fibrin, and the other was same peptide with C-terminal Arginine missing. To our knowledge, this is the first report of the presence of d-amino acid-containing peptides in serum and the approach described will provide a new direction on the serum proteome and fragmentome.</p></div

Targeted inhibition of FAK, PYK2 and BCL-XL synergistically enhances apoptosis in ovarian clear cell carcinoma cell lines.

Ovarian clear cell carcinoma (OCCC) displays a higher resistance to first line chemotherapy, requiring the development of new therapeutics. We previously identified a frequent chromosomal gain at 8q24 that harbors the focal-adhesion kinase (FAK) gene; the potential of this gene as a therapeutic target remains to be evaluated in OCCCs. We first examined the dependence of OCCCs on FAK and the PI3K/AKT signaling pathway. FAK was overexpressed in 20% of 67 OCCC samples, and this overexpression was correlated with its copy number gain. FAK copy number gains and mutations in PIK3CA accounted for about 40% of OCCC samples, suggesting that the FAK/PI3K/AKT axis is an attractive candidate for targeted therapeutics. We, therefore, treated ovarian cancer cell lines, including OCCC subtypes, with the FAK inhibitors PF-562,271 (PF271), and PF-573,228 (PF228). Ovarian cancer cells were more sensitive to PF271 than PF228. We then searched for single agents that exhibited a synergistic effect on cell death in combination with PF271. We found that co-treatment of PF271 with ABT-737, a BCL-2/BCL-XL antagonist, was profoundly effective at inducing apoptosis. RMGI and OVISE cells were more sensitive to ABT-737 than OVMANA and SKOV3 cells, which have PIK3CA mutations. Mechanistically, PF271 treatment resulted in the transient down-regulation of the anti-apoptotic protein MCL1 via the PI3K/AKT pathway. Therefore, PF271/ABT-737 treatment led to the inhibition of the anti-apoptotic proteins MCL1 and BCL-XL/BCL-2. We suggest that pharmacological inhibition of BCL-XL and FAK/PYK2 can be a potential therapeutic strategy for the treatment of OCCC