Medical image mis-segmentation region refinement framework based on dynamic graph convolution

In medical image segmentation tasks, it is hard for traditional Convolutional Neural Network (CNN) to capture essential information such as spatial structure and global contextual semantic features since it suffers from a limited receptive field. The deficiency weakens the CNN segmentation performance in the lesion boundary regions. To handle the aforementioned problems, a medical image mis-segmentation region refinement framework based on dynamic graph convolution is proposed to refine the boundary and under-segmentation regions. The proposed framework first employs a lightweight dual-path network to detect the boundaries and nearby regions, which can further obtain potentially misclassified pixels from the coarse segmentation results of the CNN. Then, we construct the pixels into the appropriate graphs by CNN-extracted features. Finally, we design a dynamic residual graph convolutional network to reclassify the graph nodes and generate the final refinement results. We chose UNet and its eight representative improved networks as the basic networks and tested them on the COVID, DSB, and BUSI datasets. Experiments demonstrated that the average Dice of our framework is improved by 1.79%, 2.29%, and 2.24%, the average IoU is improved by 2.30%, 3.53%, and 2.39%, and the Se is improved by 5.08%, 4.78%, and 5.31% respectively. The experimental results prove that the proposed framework has the refinement capability to remarkably strengthen the segmentation result of the basic network. Furthermore, the framework has the advantage of high portability and usability, which can be inserted into the end of mainstream medical image segmentation networks as a plug-and-play enhancement block.

Healthy City Community Space-Oriented Structural Planning and Management Optimization under COVID-19

This work studies ways of Healthy City Construction (HCC) and Urban Governance Optimization (UGO) during the COVID-19 pandemic. The specific urban community space planning structure is proposed following a literature review on the healthy city's theoretical basis and historical development. Then, the proposed HCC-oriented community space structure is tested by surveying residents' physical and mental health and infectious risk using a questionnaire survey and Particle Swarm Optimization (PSO). Specifically, the particle fitness is calculated according to the original data conditions, and the community space with the highest fitness is determined. Based on the calculation, the community space's neighbors are investigated from different aspects through a questionnaire survey on patients' daily activities and community health security coverage. The results showed that: (1) The score of daily activities of community patients with respiratory diseases was 2312 before the implementation of the proposed community structure and 2715 after the implementation. Therefore, the service quality of residents increases after implementation. (2) The proposed HCC-oriented community space structure improves the physical self-control ability of chronic patients and helps them reduce their pain. This work aims to create a people-oriented healthy city community space, improve the city's "immune system,” and regenerate the energy and environmental sustainability of the urban living environment.

Healthy City Community Space-Oriented Structural Planning and Management Optimization under COVID-19.

This work studies ways of Healthy City Construction (HCC) and Urban Governance Optimization (UGO) during the COVID-19 pandemic. The specific urban community space planning structure is proposed following a literature review on the healthy city's theoretical basis and historical development. Then, the proposed HCC-oriented community space structure is tested by surveying residents' physical and mental health and infectious risk using a questionnaire survey and Particle Swarm Optimization (PSO). Specifically, the particle fitness is calculated according to the original data conditions, and the community space with the highest fitness is determined. Based on the calculation, the community space's neighbors are investigated from different aspects through a questionnaire survey on patients' daily activities and community health security coverage. The results showed that: (1) The score of daily activities of community patients with respiratory diseases was 2312 before the implementation of the proposed community structure and 2715 after the implementation. Therefore, the service quality of residents increases after implementation. (2) The proposed HCC-oriented community space structure improves the physical self-control ability of chronic patients and helps them reduce their pain. This work aims to create a people-oriented healthy city community space, improve the city's "immune system," and regenerate the energy and environmental sustainability of the urban living environment.

Recent advances in ginsenosides against respiratory diseases: Therapeutic targets and potential mechanisms.

BACKGROUND: Respiratory diseases mainly include asthma, influenza, pneumonia, chronic obstructive pulmonary disease, pulmonary hypertension, lung fibrosis, and lung cancer. Given their high prevalence and poor prognosis, the prevention and treatment of respiratory diseases are increasingly essential. In particular, the development for the novel strategies of drug treatment has been a hot topic in the research field. Ginsenosides are the major component of Panax ginseng C. A. Meyer (ginseng), a food homology and well-known medicinal herb. In this review, we summarize the current therapeutic effects and molecular mechanisms of ginsenosides in respiratory diseases. METHODS: The reviewed studies were retrieved via a thorough analysis of numerous articles using electronic search tools including Sci-Finder, ScienceDirect, PubMed, and Web of Science. The following keywords were used for the online search: ginsenosides, asthma, influenza, pneumonia, chronic obstructive pulmonary disease (COPD), pulmonary hypertension (PH), lung fibrosis, lung cancer, and clinical trials. We summarized the findings and the conclusions from 176 manuscripts on ginsenosides, including research articles and reviews. RESULTS: Ginsenosides Rb1, Rg1, Rg3, Rh2, and CK, which are the most commonly reported ginsenosides for treating of respiratory diseases, and other ginsenosides such as Rh1, Rk1, Rg5, Rd and Re, all primarily reduce pneumonia, fibrosis, and inhibit tumor progression by targeting NF-κB, TGF-ß/Smad, PI3K/AKT/mTOR, and JNK pathways, thereby ameliorating respiratory diseases. CONCLUSION: This review provides novel ideas and important aspects for the future research of ginsenosides for treating respiratory diseases.

The protective effects of baicalin for respiratory diseases: an update and future perspectives.

Background: Respiratory diseases are common and frequent diseases. Due to the high pathogenicity and side effects of respiratory diseases, the discovery of new strategies for drug treatment is a hot area of research. Scutellaria baicalensis Georgi (SBG) has been used as a medicinal herb in China for over 2000 years. Baicalin (BA) is a flavonoid active ingredient extracted from SBG that BA has been found to exert various pharmacological effects against respiratory diseases. However, there is no comprehensive review of the mechanism of the effects of BA in treating respiratory diseases. This review aims to summarize the current pharmacokinetics of BA, baicalin-loaded nano-delivery system, and its molecular mechanisms and therapeutical effects for treating respiratory diseases. Method: This review reviewed databases such as PubMed, NCBI, and Web of Science from their inception to 13 December 2022, in which literature was related to "baicalin", "Scutellaria baicalensis Georgi", "COVID-19", "acute lung injury", "pulmonary arterial hypertension", "asthma", "chronic obstructive pulmonary disease", "pulmonary fibrosis", "lung cancer", "pharmacokinetics", "liposomes", "nano-emulsions", "micelles", "phospholipid complexes", "solid dispersions", "inclusion complexes", and other terms. Result: The pharmacokinetics of BA involves mainly gastrointestinal hydrolysis, the enteroglycoside cycle, multiple metabolic pathways, and excretion in bile and urine. Due to the poor bioavailability and solubility of BA, liposomes, nano-emulsions, micelles, phospholipid complexes, solid dispersions, and inclusion complexes of BA have been developed to improve its bioavailability, lung targeting, and solubility. BA exerts potent effects mainly by mediating upstream oxidative stress, inflammation, apoptosis, and immune response pathways. It regulates are the NF-κB, PI3K/AKT, TGF-ß/Smad, Nrf2/HO-1, and ERK/GSK3ß pathways. Conclusion: This review presents comprehensive information on BA about pharmacokinetics, baicalin-loaded nano-delivery system, and its therapeutic effects and potential pharmacological mechanisms in respiratory diseases. The available studies suggest that BA has excellent possible treatment of respiratory diseases and is worthy of further investigation and development.

Disinfectants facilitate the transformation of exogenous antibiotic resistance genes via multiple pathways.

The prevalence and spread of multidrug-resistant (MDR) bacteria pose a global challenge to public health. Natural transformation is one of the essential ways for horizontal transfer of antibiotic resistance genes (ARGs). Although disinfectants are frequently used during COVID-19, little is known about whether these disinfectants are associated with the transformation of plasmid-borne ARGs. In our study, we assessed the effect of some disinfectants on bacterial transformation using resistance plasmids as extracellular DNA and E. coli DH5α as the recipient bacteria. The results showed that these disinfectants at environmentally relevant concentrations, including benzalkonium bromide (BB), benzalkonium chloride (BC) and polyhexamethylene guanidine hydrochloride (PHMG), significantly enhanced the transformation of plasmid-encoded ARGs. Furthermore, we investigated the mechanisms underlying the promotive effect of disinfectants on transformation. We revealed that the addition of disinfectants significantly increased the membrane permeability and promoted membrane-related genes expression. Moreover, disinfectants led to the boosted bacterial respiration, ATP production and flagellum motility, as well as increased expression of bacterial secretion system-related genes. Together, our findings shed insights into the spread of ARGs through bacterial transformation and indicate potential risks associated with the widespread use of disinfectants.

Qimai Feiluoping decoction inhibits mitochondrial complex I-mediated oxidative stress to ameliorate bleomycin-induced pulmonary fibrosis.

BACKGROUND: Qimai Feiluoping decoction (QM), a Traditional Chinese Medicine formula, has been included in rehabilitation program for functional disorders of discharged COVID-19 patients. QM has been proved to effectively improve the clinical symptoms and imaging signs of PF in COVID-19 convalescent patients. PURPOSE: This study to explore the pharmacological effect of QM against PF from the perspectives of imaging, pathological staining, and molecular mechanisms, and identify possible active components. METHODS: Micro-CT imaging and immunohistochemical staining were investigated to verify the therapeutic effect of QM in the bleomycin (BLM)-induced PF mouse model. The 4D-label-free proteomics analysis of lung tissues was then conducted to explore the novel mechanisms of QM against PF, which were further validated by a series of experiments. The possible components of QM in plasma and lung tissues were identified with UHPLC/IM-QTOF-MS analysis. RESULTS: The results from micro-CT imaging and pathological staining revealed that QM treatment can inhibit BLM-induced lung injury, extracellular matrix accumulation and TGF-ß expression in the mouse model with PF. The 4D-label-free proteomics analysis demonstrated that the partial subunit proteins of mitochondrial complex I and complex II might be potential targets of QM against PF. Furthermore, QM treatment can inhibit BLM-induced mitochondrial ROS content to promote ATP production and decrease oxidative stress injury in the mouse and cell models of PF, which was mediated by the inhibition of mitochondrial complex I. Finally, a total of 13 protype compounds and 15 metabolites from QM in plasma and lung tissues were identified by UHPLC/IM-QTOF-MS, and liquiritin and isoliquiritigenin from Glycyrrhizae radix et rhizoma could be possible active compounds against PF. CONCLUSION: It concludes that QM treatment could treat PF by inhibiting mitochondrial complex I-mediated mitochondrial oxidated stress injury, which could offer new insights into the pharmacological mechanisms of QM in the clinical application of PF patients.

Large-scale measurement of aggregate human colocation patterns for epidemiological modeling.

To understand and model public health emergencies, epidemiologists need data that describes how humans are moving and interacting across physical space. Such data has traditionally been difficult for researchers to obtain with the temporal resolution and geographic breadth that is needed to study, for example, a global pandemic. This paper describes Colocation Maps, which are spatial network datasets that have been developed within Meta's Data For Good program. These Maps estimate how often people from different regions are colocated: in particular, for a pair of geographic regions x and y, these Maps estimate the rate at which a randomly chosen person from x and a randomly chosen person from y are simultaneously located in the same place during a randomly chosen minute in a given week. These datasets are well suited to parametrize metapopulation models of disease spread or to measure temporal changes in interactions between people from different regions; indeed, they have already been used for both of these purposes during the COVID-19 pandemic. In this paper, we show how Colocation Maps differ from existing data sources, describe how the datasets are built, provide examples of their use in compartmental modeling, and summarize ideas for further development of these and related datasets. Among the findings of this study, we observe that a pair of regions can exhibit high colocation despite few people moving between those regions. Additionally, for the purposes of clarifying how to interpret and utilize Colocation Maps, we scrutinize the Maps' built-in assumptions about representativeness and contact heterogeneity.

Molecular insight into pentraxin-3: Update advances in innate immunity, inflammation, tissue remodeling, diseases, and drug role.

Pentraxin-3 (PTX3) is the prototype of the long pentraxin subfamily, an acute-phase protein consisting of a C-terminal pentraxin domain and a unique N-terminal domain. PTX3 was initially isolated from human umbilical vein endothelial cells and human FS-4 fibroblasts. It was subsequently found to be also produced by synoviocytes, chondrocytes, osteoblasts, smooth muscle cells, myeloid dendritic cells, epithelial cells, and tumor cells. Various modulatory factors, such as miRNAs, cytokines, drugs, and hypoxic conditions, could regulate the expression level of PTX3. PTX3 is essential in regulating innate immunity, inflammation, angiogenesis, and tissue remodeling. Besides, PTX3 may play dual (pro-tumor and anti-tumor) roles in oncogenesis. PTX3 is involved in the occurrence and development of many non-cancerous diseases, including COVID-19, and might be a potential biomarker indicating the prognosis, activity,and severity of diseases. In this review, we summarize and discuss the potential roles of PTX3 in the oncogenesis and pathogenesis of non-cancerous diseases and potential targeted therapies based on PTX3.

Network Pharmacology and Experimental Assessment to Explore the Pharmacological Mechanism of Qimai Feiluoping Decoction Against Pulmonary Fibrosis.

Pulmonary fibrosis (PF) is one of the pathologic changes in COVID-19 patients in convalescence, and it is also a potential long-term sequela in severe COVID-19 patients. Qimai Feiluoping decoction (QM) is a traditional Chinese medicine formula recommended in the Chinese national medical program for COVID-19 convalescent patients, and PF is one of its indications. Through clinical observation, QM was found to improve the clinical symptoms and pulmonary function and reduce the degree of PF of COVID-19 convalescent patients. To further explore the pharmacological mechanisms and possible active components of QM in anti-PF effect, UHPLC/Q-TOF-MS was used to analyze the composition of the QM extract and the active components that can be absorbed into the blood, leading to the identification of 56 chemical compounds and 10 active components. Then, network pharmacology was used to predict the potential mechanisms and targets of QM; it predicted that QM exerts its anti-PF effects via the regulation of the epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) degradation, and TGF-ß signaling pathway. Finally, TGF-ß1-induced A549 cells were used to verify and explore the pharmacological effects of QM and found that QM could inhibit the proliferation of TGF-ß1-induced A549 cells, attenuate EMT, and promote ECM degradation by inhibiting the TGF-ß/Smad3 pathway.