DBPNDNet: dual-branch networks using 3DCNN toward pulmonary nodule detection.

With the advancement of artificial intelligence, CNNs have been successfully introduced into the discipline of medical data analyzing. Clinically, automatic pulmonary nodules detection remains an intractable issue since those nodules existing in the lung parenchyma or on the chest wall are tough to be visually distinguished from shadows, background noises, blood vessels, and bones. Thus, when making medical diagnosis, clinical doctors need to first pay attention to the intensity cue and contour characteristic of pulmonary nodules, so as to locate the specific spatial locations of nodules. To automate the detection process, we propose an efficient architecture of multi-task and dual-branch 3D convolution neural networks, called DBPNDNet, for automatic pulmonary nodule detection and segmentation. Among the dual-branch structure, one branch is designed for candidate region extraction of pulmonary nodule detection, while the other incorporated branch is exploited for lesion region semantic segmentation of pulmonary nodules. In addition, we develop a 3D attention weighted feature fusion module according to the doctor's diagnosis perspective, so that the captured information obtained by the designed segmentation branch can further promote the effect of the adopted detection branch mutually. The experiment has been implemented and assessed on the commonly used dataset for medical image analysis to evaluate our designed framework. On average, our framework achieved a sensitivity of 91.33% false positives per CT scan and reached 97.14% sensitivity with 8 FPs per scan. The results of the experiments indicate that our framework outperforms other mainstream approaches.

Anti-Hyperlipidemic Effect of Fucoidan Fractions Prepared from Iceland Brown Algae Ascophyllum nodosum in an Hyperlipidemic Mice Model.

Ascophyllum nodosum, a brown algae abundantly found along the North Atlantic coast, is recognized for its high polysaccharide content. In this study, we investigated the anti-hyperlipidemic effect of fucoidans derived from A. nodosum, aiming to provide information for their potential application in anti-hyperlipidemic therapies and to explore comprehensive utilization of this Iceland brown seaweed. The crude fucoidan prepared from A. nodosum was separated using a diethylethanolamine column, resulting in two fucoidan fractions, AFC-1 and AFC-2. Both fractions were predominantly composed of fucose and xylose. AFC-1 exhibited a higher sulfate content of 27.8% compared to AFC-2 with 17.0%. AFC-2 was primarily sulfated at the hydroxy group of C2, whereas AFC-1 was sulfated at both the hydroxy groups of C2 and C4. To evaluate the anti-hyperlipidemic effect, a hyperlipidemia mouse model was established by feeding mice a high-fat diet. The effects of AFC-1, AFC-2, and the crude extract were investigated, with the drug atorvastatin used as a positive comparison. Among the different fucoidan fractions and doses, the high dose of AFC-2 administration demonstrated the most significant anti-hyperlipidemic effect across various aspects, including physiological parameters, blood glucose levels, lipid profile, histological analysis, and the activities of oxidative stress-related enzymes and lipoprotein-metabolism-related enzymes (p < 0.05 for the final body weight and p < 0.01 for the rest indicators, compared with the model group), and its effect is comparable to the atorvastatin administration. Furthermore, fucoidan administration resulted in a lower degree of loss in gut flora diversity compared to atorvastatin administration. These findings highlight the significant biomedical potential of fucoidans derived from A. nodosum as a promising therapeutic solution for hypolipidemia.

Multiscale Cascaded Attention Network for Saliency Detection Based on ResNet.

Saliency detection is a key research topic in the field of computer vision. Humans can be accurately and quickly mesmerized by an area of interest in complex and changing scenes through the visual perception area of the brain. Although existing saliency-detection methods can achieve competent performance, they have deficiencies such as unclear margins of salient objects and the interference of background information on the saliency map. In this study, to improve the defects during saliency detection, a multiscale cascaded attention network was designed based on ResNet34. Different from the typical U-shaped encoding-decoding architecture, we devised a contextual feature extraction module to enhance the advanced semantic feature extraction. Specifically, a multiscale cascade block (MCB) and a lightweight channel attention (CA) module were added between the encoding and decoding networks for optimization. To address the blur edge issue, which is neglected by many previous approaches, we adopted the edge thinning module to carry out a deeper edge-thinning process on the output layer image. The experimental results illustrate that this method can achieve competitive saliency-detection performance, and the accuracy and recall rate are improved compared with those of other representative methods.

B7-H3 targeted CAR-T cells show highly efficient anti-tumor function against osteosarcoma both in vitro and in vivo.

BACKGROUND: Osteosarcoma (OS) mainly happens in children and youths. Surgery, radiotherapy and chemotherapy are the common therapies for osteosarcoma treatment but all their anti-tumor effects are limited. In recent years, a new cellular therapy, CAR-T, a cellular immunotherapy with genetically engineered T cells bearing chimeric antigen receptor targeting specific tumor-associated antigen, has been proved to be an effective therapy against acute lymphoblastic leukemia. Thus, CAR-T is a potentially effective therapy for osteosarcoma treatment. METHODS: A CAR gene targeting B7-H3 antigen was constructed into lentiviral vector through molecular biology techniques. Then, the CAR gene was transferred to T cells through lentiviral delivery system, and the CAR-T cells were largely expanded using in vitro culture technology. The in vitro anti-tumor effect of CAR-T cells was evaluated through Real Time Cell Analysis system (RTCA) and ELISA assay. The in vivo anti-tumor capabilities of CAR-T cells were evaluated using the patient-derived xenografts (PDX) model of osteosarcoma. RESULTS: The third-generation CAR-T cells we constructed could target the B7-H3 antigen, and the phenotype of CAR-T cells was consistent with normal T cells; The CAR-T cells showed superior antitumor effects both in vitro and in vivo. CONCLUSION: Our study showed that B7-H3 targeted CAR-T cells had high anti-tumor efficacy against osteosarcoma both in vitro and in vivo, which proved that B7-H3 targeted CAR-T therapy is potentially effective for osteosarcoma treatment.

Retrospective Study of Aging and Sex-Specific Risk Factors of COVID-19 with Hypertension in China.

Background: Coronavirus disease 2019 (COVID-19) has been a global threat that pushes healthcare to its limits. Hypertension is one of the most common risk factors for cardiovascular complications in COVID-19 and is strongly associated with disease severity and mortality. To date, clinical mechanisms by which hypertension leads to increased risk in COVID-19 are still unclear. Furthermore, additional factors might increase these risks, such as the consideration of age and sex, which are of interest when in search of personalized treatments for hypertensive COVID-19 patients. Methods: We conducted a retrospective cohort study of 543 COVID-19 patients in seven provinces of China to examine the epidemiological and clinical characteristics of COVID-19 in this population and to determine risk factors of hypertensive COVID-19 patients. We also used univariable and multivariable logistic regression methods to explore the risk factors associated with hypertensive COVID-19 patients in different age and sex subgroups. Results: Among the enrolled COVID-19 patients, the median age was 47 years (interquartile range (IQR) 34.0-57.0), and 99 patients (18.23%) were over 60 years old. With regard to comorbidities, 91 patients (16.75%) were diagnosed with hypertension, followed by diabetes, coronary disease, and cerebrovascular disease. Of the hypertensive COVID-19 patients, 51 (56.04%) were male. Multivariable analysis showed that old age, comorbid diabetes or coronary heart disease on admission, increased D-dimer, increased glucose, and decreased lymphocyte count were independent risk factors associated with hypertensive COVID-19 patients. Elevated total bilirubin (odds ratio [OR]: 1.014, 95% confidence interval [CI]: 0.23-1.05; p = 0.043) and triglycerides (OR: 1.173, 95% CI: 0.049-1.617; p = 0.007) were found to be associated with elderly hypertensive COVID-19 patients. In addition, we found that decreased lymphocytes, basophil, high-density lipoprotein, and increased fibrinogen and creatinine were related to a higher risk of disease severity in male patients. The most common abnormal clinical findings pertaining to female hypertensive COVID-19 patients were hemoglobin, total bile acid, total protein, and low-density lipoprotein. Conclusions: Factors associated with increased risk of hypertensive COVID-19 patients were identified. Results to the different age and sex subgroups in our study will allow for better possible personalized care and also provide new insights into specific risk stratification, disease management, and treatment strategies for COVID-19 patients with hypertension in the future.

Disruption of adenosine 2A receptor improves the anti-tumor function of anti-mesothelin CAR T cells both in vitro and in vivo.

Chimeric antigen receptor (CAR) T cells have been successfully used for the treatment of hematological malignancies including acute and chronic lymphoblastic leukemia. However, results of CAR T cell projects in solid tumors have been less impressive to date, partly because of immunosuppressive tumor microenvironment (TME). It is widely known that high adenosine production is an important factor causing tumor-induced immunosuppression in TME, and adenosine mediates the suppression of anti-tumor T cell responses via binding and signaling through adenosine 2a receptor (A2aR). Previous studies have shown that adenosine generated by cancer cells significantly inhibits T cell anti-tumor activity through binding and then activating adenosine 2A receptors (A2aRs) of T cells. Based on the previous work, in our study, we evaluated whether A2aR disruption by shRNA could enhance the anti-tumor function of anti-mesothelin (MSLN) CAR T cells both in vitro and in vivo. For this goal above, we used MSLN-positive human ovarian serous carcinoma cells (SKOV3) and human colon cancer cells (HCT116) as target cancer cells while MSLN-negative human ovarian cancer cells (ES2) as non-target cancer cells. We observed that targeting cell-intrinsic A2aR through shRNA overexpression caused significant A2aR disruption in CAR T cells and profoundly increased CAR T cell efficacy in both CAR T cell cytokine production and cytotoxicity towards MSLN-positive cancer cells in vitro. More importantly, in SKOV3 xenograft mouse models, anti-MSLN CAR-T cells significantly reduced the tumor burden compared with non-transduced T cells, and the anti-tumor activity of A2aR-disrupted anti-MSLN CAR-T cells was stronger than that of wild-type anti-MSLN CAR-T cells. Altogether, our study showed enhanced anti-tumor efficacy caused by shRNA-mediated A2aR disruption in anti-MSLN CAR T cells both in vitro and in vivo, which proved that shRNA-mediated modification of gene expression might be an excellent strategy for improving CAR T cell function in immunosuppressive tumor microenvironment (TME) and could potentially improve the outcome of treatment in clinical trials.

The antitumor capacity of mesothelin-CAR-T cells in targeting solid tumors in mice.

Since the approval of chimeric antigen receptor (CAR) T cell therapy targeting CD19 by the FDA, CAR-T cell therapy has received increasing attention as a new method for targeting tumors. Although CAR-T cell therapy has a good effect against hematological malignancies, it has been less effective against solid tumors. In the present study, we selected mesothelin (MSLN/MESO) as a target for CAR-T cells because it is highly expressed by solid tumors but only expressed at low levels by normal tissues. We engineered a third generation MSLN-CAR comprising a single-chain variable fragment (scFv) targeting MSLN (MSLN-scFv), a CD8 transmembrane domain, the costimulatory domains from CD28 and 4-1BB, and the activating domain CD3ζ. In vitro, MSLN-CAR-T cells killed various solid tumor cell lines, demonstrating that it could specifically kill MSLN-positive cells and release cytokines. In vivo, we investigated the effects of MSLN-CAR-T cell therapy against ovarian, breast, and colorectal cancer cell-line-derived xenografts (CDX) and MSLN-positive colorectal and gastric cancer patient-derived xenografts (PDX). MSLN-CAR decreased the growth of MSLN-positive tumors concomitant with significantly increased T cells and cytokine levels compared to the control group. These results indicated that modified MSLN-CAR-T cells could be a promising therapeutic approach for solid tumors.

Detection of residual E. coli host cell DNA by 23S ribosomal RNA gene-targeted quantitative polymerase chain reactions.

Among the many systems available for heterologous protein production gram-negative bacterium Escherichia coli (E. coli) has long been widely used because of its ability to grow rapidly with a high density on inexpensive substrates. The use of E. coli as the host system has many regulatory issues, one of which is the residual host cell DNA. Residual DNA carried by biological products may lead to carcinogenicity and immunomodulation risks. The World Health Organization (WHO) for the acceptable amounts of residual host cell DNA is less than 10 ng per dose. Therefore, it is important to keep an extremely low level of residual host DNA in the biological products derived from E. coli. In this study, we designed primer/probe sets targeting E. coli 23S ribosomal RNA gene to quantify the residual DNA of E. coli by quantitative polymerase chain reactions (qPCR). Result showed that this primer/probe has high species specificity. The limit of detection (LOD) in this method is 0.01 pg/µl and this allowed for detection of residual host DNA of much lower concentrations. We assessed accuracy by calculating the recovery (92.1∼140.1 %) of the spiked DNA in plasmids which were produced from E. coli. We also checked intra-assay precision (9.8∼15.1 %) and inter-assay precision (10.9∼18.3 %) by repeatedly measuring the four different concentration standards. In addition, the robustness assay was performed by generating standard curve using short length E. coli DNA. The result showed that appropriate degree of DNA fragmentation will not affect tests. These validation studies demonstrated that our method has excellent specificity, linearity, accuracy, precision and robustness.

Risk Factors in Patients with Diabetes Hospitalized for COVID-19: Findings from a Multicenter Retrospective Study.

METHODS: In this multicenter retrospective study, patients with COVID-19 in China were included and classified into two groups according to whether they were complicated with diabetes or not. Demographic symptoms and laboratory data were extracted from medical records. Univariable and multivariable logistic regression methods were used to explore the risk factors. RESULTS: 538 COVID-19 patients were finally included in this study, of whom 492 were nondiabetes and 46 were diabetes. The median age was 47 years (IQR 35.0-56.0). And the elderly patients with diabetes were more likely to have dry cough, and the alanine aminotransferase, lactate dehydrogenase, Ca, and mean hemoglobin recovery rate were higher than the other groups. Furthermore, we also found the liver and kidney function of male patients was worse than that of female patients, while female cases should be paid more attention to the occurrence of bleeding and electrolyte disorders. Moreover, advance age, blood glucose, gender, prothrombin time, and total cholesterol could be considered as risk factors for COVID-19 patients with diabetes through the multivariable logistic regression model in our study. CONCLUSION: The potential risk factors found in our study showed a major piece of the complex puzzle linking diabetes and COVID-19 infection. Meanwhile, focusing on gender and age factors in COVID-19 patients with or without diabetes, specific clinical characteristics, and risk factors should be paid more attention by clinicians to figure out a targeted intervention to improve clinical efficacy worldwide.

Functional characterization of an unknown soybean intrinsically disordered protein in vitro and in Escherichia coli.

Intrinsically disordered proteins (IDPs) possess a wide range of biological function in all organisms, however the specific functions of most IDPs are still unknown. Soybean LOC protein, LOC for short, is a heat-stable protein, which is more abundant in the stress-resistant radicles. Sequence alignment and phylogenetic analysis showed that LOC is a functionally unknown protein and conserved in Fabaceae. LOC, being enriched in most disorder-promoting residues and depleted in most order-promoting residues, was predicted to contain high levels of intrinsic disorder by several commonly used computational tools. However, it was also predicted to contain two disorder-based protein-protein binding sites and two short α-helical segments. The circular dichroism spectroscopic analysis showed that this protein is mostly disordered in water, but can form more α-helical structure in the presence of SDS and TFE. Functional in vitro studies showed that the LOC protein is able to prevent lactate dehydrogenase inactivation by freeze-thaw at a molar ratio of 10:1. Furthermore, in vivo analyses revealed the survival rate of Escherichia coli over-expressing LOC protein under the conditions of osmotic stress was noticeably increased in comparison with the control. These observations suggest that the intrinsically disordered protein LOC might serve as a chaperone and/or cell protector.