FE-Net: Feature enhancement segmentation network.

Semantic segmentation is one of the directions in image research. It aims to obtain the contours of objects of interest, facilitating subsequent engineering tasks such as measurement and feature selection. However, existing segmentation methods still lack precision in class edge, particularly in multi-class mixed region. To this end, we present the Feature Enhancement Network (FE-Net), a novel approach that leverages edge label and pixel-wise weights to enhance segmentation performance in complex backgrounds. Firstly, we propose a Smart Edge Head (SE-Head) to process shallow-level information from the backbone network. It is combined with the FCN-Head and SepASPP-Head, located at deeper layers, to form a transitional structure where the loss weights gradually transition from edge labels to semantic labels and a mixed loss is also designed to support this structure. Additionally, we propose a pixel-wise weight evaluation method, a pixel-wise weight block, and a feature enhancement loss to improve training effectiveness in multi-class regions. FE-Net achieves significant performance improvements over baselines on publicly datasets Pascal VOC2012, SBD, and ATR, with best mIoU enhancements of 15.19%, 1.42% and 3.51%, respectively. Furthermore, experiments conducted on Pole&Hole match dataset from our laboratory environment demonstrate the superior effectiveness of FE-Net in segmenting defined key pixels.

PERP May Affect the Prognosis of Lung Adenocarcinoma by Inhibiting Apoptosis.

Background: PERP, a member of the peripheral myelin protein gene family, is a new therapeutic target in cancer. The relationships between PERP and immune cell infiltration in lung cancer have not been studied. Therefore, the role of PERP in the tumour microenvironment (TME) of lung cancer needs to be further explored. Methods: In this study, we explored the association between PERP expression and clinical characteristics by analysing data from the TCGA database. Cox regression and Kaplan‒Meier methods were used to investigate the relationship between the expression of PERP and overall survival in patients with lung adenocarcinoma (LUAD). The relationship between PERP expression and the degree of infiltration of specific immune cell subsets in LUAD was evaluated using the TIMER database and GEPIA. We also performed GO enrichment analysis and KEGG enrichment analysis to reveal genes coexpressed with PERP using the Coexpedia database. Finally, we verified the expression and function of PERP in LUAD tissues and the A549 cell line by RT‒PCR, Western blot, CCK-8, IHC, and wound healing assays. The mouse model was used to study the in vivo effects of PERP. Results: According to our results, PERP expression was significantly higher in LUAD tissues and associated with the clinical characteristics of the disease. Survival was independently associated with PERP in LUAD patients. We further verified that PERP might regulate B-cell infiltration in LUAD to affect the prognosis of LUAD. To identify PERP-related signalling pathways in LUAD, we performed a genome-aggregation analysis (GSEA) between low and high PERP expression datasets. LUAD cells express higher levels of PERP than paracarcinoma cells, and PERP inhibits the proliferation and metastasis of A549 cells through apoptosis. Conclusion: PERP may affect the prognosis of lung adenocarcinoma by inhibiting apoptosis and is associated with immune cell infiltration.

Single-cell analysis reveals changes in BCG vaccine-injected mice modeling tuberculous meningitis brain infection.

Tuberculous meningitis (TBM) is the most severe and deadly manifestation of tuberculosis. Neurological complications are observed in up to 50% of patients affected. Here, attenuated Mycobacterium bovis are injected into the cerebellum of mice, and histopathological images and cultured colonies confirm successful brain infection. Then, whole-brain tissue is dissected for 10X Genomics single-cell sequencing, and we acquire 15 cell types. Transcriptional changes of inflammation processes are found in multiple cell types. Specifically, Stat1 and IRF1 are shown to mediate inflammation in macrophages and microglia. For neurons, decreased oxidative phosphorylation activity in neurons is observed, which corresponds to TBM clinical symptoms of neurodegeneration. Finally, ependymal cells present prominent transcriptional changes, and decreased FERM domain containing 4A (Frmd4a) may contribute to TBM clinical symptoms of hydrocephalus and neurodegeneration. This study shows a single-cell transcriptome of M. bovis infection in mice and improves the understanding of brain infection and neurological complications in TBM.

Current status and future of anti-angiogenic drugs in lung cancer.

Lung cancer, as a malignant tumor with both high incidence and mortality in China, is one of the major causes of death in our population and one of the major public health problems in China. Effective treatment of lung cancer is a major public health task for all human beings. Angiogenesis plays an important role in the development of tumor, not only as a basic condition for tumor growth, but also as a significant factor to promote tumor metastasis. Therefore, anti-angiogenesis has become a vital means to inhibit tumor development, and anti-angiogenic drugs can rebalance pro- and anti-angiogenic factors to inhibit tumor cells. This article reviews the mechanism of blood vessel formation in tumor tissues and the mechanism of action of different anti-angiogenic drugs, the combination therapy of anti-angiogenic drugs and other anti-tumor drugs, and the mechanism of anti-angiogenic drug resistance.

Prediction and Optimization Algorithm for Intersection Point of Spatial Multi-Lines Based on Photogrammetry.

The basic theory of photogrammetry is mature and widely used in engineering. The environment in engineering is very complex, resulting in the corners or multi-line intersections being blocked and unable to be measured directly. In order to solve this problem, a prediction and optimization algorithm for intersection point of spatial multi-lines based on photogrammetry is proposed. The coordinates of points on space lines are calculated by photogrammetry algorithm. Due to the influence of image point distortion and point selection error, many lines do not strictly intersect at one point. The equations of many space lines are used to fit their initial value of intersection point. The initial intersection point is projected onto each image, and the distances between the projection point and each line on the image plane are used to weight the calculated spatial lines in combination with the information entropy. Then the intersection point coordinates are re-fitted, and the intersection point is repeatedly projected and recalculate until the error is less than the threshold value or reached the set number of iterations. Three different scenarios are selected for experiments. The experimental results show that the proposed algorithm significantly improves the prediction accuracy of the intersection point.

Risk Factors and Mental Health Status in Patients With Non-Tuberculous Mycobacterial Lung Disease: A Single Center Retrospective Study.

According to the existing data, the incidence and prevalence of non-tuberculous mycobacteria (NTM) are increasing worldwide. The risk factors and mental health status of patients with NTM lung disease are important and deserve our attention. A total of 180 patients with NTM lung disease hospitalized from January 2018 to December 2021 were selected as the NTM group, and 90 patients with non-severe community-acquired pneumonia (CAP) who were hospitalized during the same period were selected as the control group. The Symptom Checklist-90 (SCL-90) was used to assess the mental health status of the patients. The data were analyzed using descriptive statistics, logistic regression, and receiver operating characteristic (ROC) curves. There were no significant differences in age, sex, marital status, or smoking history between the two groups (p > 0.05), but there were significant differences in educational level, underlying diseases, occupation, living environment, and body mass index (BMI) (p < 0.01). According to the classification of basic diseases, bronchiectasis was found in 82 (45.6%) patients, followed by hypertension in 66 (36.7%) patients, and chronic obstructive pulmonary disease (COPD) in 39 (21.7%) patients. The NTM strains were identified M. intercelleulare caused 41 cases (22.8%), followed by Mycobacterium avium and Mycobacterium gordonae, each with 35 cases (19.4%), and Mycobacterium abscessus with 32 cases (17.8%). The SCL-90 found that 160 (88.9%) of 180 patients with NTM lung disease had developed mental health problems, among which the four highest-scoring factors were anxiety (ANX: 29.4%), depression (DEPR: 18.8%), sleep and diet (SD: 16.9%), and somatization (SOM: 11.3%). Through multivariate logistic regression analysis, it was found that educational level, underlying diseases, living environment, and BMI were independent risk factors for the occurrence of NTM lung disease (p < 0.01). The Hosmer-Lemeshow test was used to check the model's fitness. The ROC curve showed that the area under the curve (AUC) was 0.896, the sensitivity was 83.3%, and the specificity was 85.6%. Patients with NTM lung disease have many risk factors and prominent mental health problems that may require interventions during the process of clinical diagnosis and treatment.

Prognosis-related autophagy genes in female lung adenocarcinoma.

ABSTRACT: To screen the prognosis-related autophagy genes of female lung adenocarcinoma by the transcriptome data and clinical data from The Cancer Genome Atlas (TCGA) database.In this study, screen meaningful female lung adenocarcinoma differential genes in TCGA, use univariate Cox proportional regression model to select genes related to prognosis, and establish the best risk model. In this study, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were applied for carrying out bioinformatics analysis of gene function.The gene expression and clinical data of 264 female lung adenocarcinoma patient samples were downloaded from TCGA. Twelve down-regulated genes: NRG3, DLC1, NLRC4, DAPK2, HSPB8, PPP1R15A, FOS, NRG1, PRKCQ, GRID1, MAP1LC3C, GABARAPL1. Up-regulated 15 genes: PARP1, BNIP3, P4HB, ATIC, IKBKE, ITGB4, VMP1, PTK6, EIF4EBP1, GAPDH, ATG9B, ERO1A, TMEM74, CDKN2A, BIRC5. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that these genes were significantly associated with autophagy and mitochondria (animals). Multifactor Cox analysis of autophagy-related genes showed that ITGA6, ERO1A, FKBP1A, BAK1, CCR2, FADD, EDEM1, ATG10, ATG4A, DLC1, VAMP7, ST13 were identified as independent prognostic indicators. According to the multivariate Cox proportional hazard regression model, there was a significant difference in the survival rate observed between the high-risk group (n = 124) and the low-risk group (n = 126) during the 10-year follow-up (P < .05). Univariate Cox analysis showed that tumor stage, T, M, and N stages, and risk score were all related to the survival rate of female lung adenocarcinoma patients. Multivariate Cox analysis found that autophagy-related risk scores were independent predictors, with an area under curve (AUC) value of 0.842. At last, there is autophagy genes differentially expressed among various clinicopathological parameters: ATG4A, BAK1, CCR2, DLC1, ERO1A, FKBP1A, ITGA6.The risk score can be used as an independent prognostic indicator for female patients with lung adenocarcinoma. The autophagy genes ITGA6, ERO1A, FKBP1A, BAK1, CCR2, FADD, EDEM1, ATG10, ATG4A, DLC1, VAMP7, ST13 were identified as prognostic genes in female lung adenocarcinoma, which may be the targets of treatment in the future.

The CPNE Family and Their Role in Cancers.

Lung cancer is the leading cause of cancer-related deaths worldwide. Despite significant advances in cancer research and treatment, the overall prognosis of lung cancer patients remains poor. Therefore, the identification for novel therapeutic targets is critical for the diagnosis and treatment of lung cancer. CPNEs (copines) are a family of membrane-bound proteins that are highly conserved, soluble, ubiquitous, calcium dependent in a variety of eukaryotes. Emerging evidences have also indicated CPNE family members are involved in cancer development and progression as well. However, the expression patterns and clinical roles in cancer have not yet been well understood. In this review, we summarize recent advances concerning CPNE family members and provide insights into new potential mechanism involved in cancer development.

Analysis of pathogens and risk factors of secondary pulmonary infection in patients with COVID-19.

To investigate the distribution and risk factors of pathogens in secondary pulmonary infection in patients with COVID-19.142 patients with confirmed COVID-19 from Shanghai Public Health Clinical Center were collected, and 32 patients with pulmonary infection were taken as the infection group. The distribution of pathogens in the sputum specimens was applied for retrospective analysis. Meanwhile, 110 patients diagnosed with COVID-19, but without pulmonary infection were regarded as the asymptomatic group. The risk factors of pulmonary infection were analyzed with generalized linear models and logistic regression. The pathogens in the lung infection group were mainly gram-negative bacteria (22, 68.8%), especially Klebsiella pneumoniae. Gram-positive bacteria and fungi accounted for 13 (40.6%), mainly Staphylococcus aureus, and 11 (34.4%), mainly Candida albicans. There were 14 cases (43.8%) infected with two or more pathogens. The comparison between the two groups found that, patients with elder age, underlying diseases, more lung lesions and low protein contents, were more likely to develop lung infections. At last, univariate analysis showed that 6 factors, including indwelling gastric catheter, the number of deep vein catheters, tracheal intubation tracheotomy, invasive mechanical ventilation, hormonal application, and the use of more than three antibacterial drugs, are risk factors for COVID-19 secondary pulmonary infection. Generalized linear models and logistic regression analysis showed antimicrobial use as an independent risk factor for COVID-19 secondary lung infection. There are many risk factors for secondary lung infection in severe COVID-19 patients, and it is recommended to use antibiotics reasonably.

Safety Evaluation of Recombinant Fusion Protein RP22 as a Skin Test Reagent for Tuberculosis Diagnosis: A Phase I Clinical Trial.

INTRODUCTION: This phase I clinical trial was conducted to evaluate the safety of RP22 as a skin test reagent for tuberculosis (TB) diagnosis and to explore the appropriate dosage. METHODS: We used a randomized, double-blind, placebo-controlled identification allergen (IA) skin test. A total of 72 healthy adult volunteers with negative chest X-ray results were randomized into six groups and given a QuantiFERON-TB Gold (QFT) test. Of the 12 participants in each group, eight received RP22 and four received placebo. The doses of RP22 in the six experimental groups ranged from 0.1 to 4.0 µg in a single intradermal injection of 0.1 ml. Skin reactions and adverse events were recorded at intervals. RESULTS: All doses of RP22 except the highest were well tolerated and safe. No serious adverse events associated with the injection were observed in all groups. There were 11 participants who had positive QFT results, eight had a skin reaction with a redness or induration area diameter of greater than 10 mm at 48-72 h, one had no skin reaction. Among the 60 negative-QFT participants, none had a reaction area diameter of greater than 10 mm. CONCLUSION: The RP22 skin test was well tolerated and safe, it could play a key role in screening for latent tuberculosis infection (LTBI) by providing a much-wanted alternative to the tuberculin skin test (TST) and interferon-γ release assays (IGRAs).

Integrated bioinformatics analysis and validation revealed potential immune-regulatory miR-892b, miR-199b-5p and miR-582-5p as diagnostic biomarkers in active tuberculosis.

Tuberculosis (TB) is one of the most prevalent pulmonary diseases caused by Mycobacterium tuberculosis (Mtb). MiRNAs (miRNAs) participate in TB progression by modulating the host-pathogen interaction. Bioinformatics advancements provide basis for exploring novel immunoregulatory miRNAs and their performance as diagnostic biomarkers. Gene and miRNA expression datasets, GSE29190 and GSE54992, were downloaded from Gene Expression Omnibus (GEO) database. Based on fold changes and statistical significance, a total of 7463 differentially expressed mRNAs (DE-mRNAs) and 38 differentially expressed miRNAs (DE-miRNAs) were screened. Function annotation and protein-protein interaction (PPI) network were constructed to reveal underlying mechanisms of TB pathogenesis. Functional annotation identified the MAPK signalling pathway and leukocyte migration as the top enriched processes. The PPI and MGIP networks indicated that chemokine ligands like CXCL1/CXCL2 and receptors, like CCR7 were important down-regulated genes, implying that a protective mechanism against overdue inflammation induced cell death. MiRNA-gene-immune processes (MGIP) network enriched 7 deregulated miRNAs, and their expression was further examined with quantitative real-time PCR (qRT-PCR), in PBMC samples of 20 active TB patients and 20 healthy donors. The diagnostic performance was evaluated with ROC curves. MiR-892b; miR-199b-5p and miR-582-5p were significantly deregulated in TB patients, compared with healthy participants. The best overall performance was from miR-892b, with an area under curve (AUC) of 0.77, 55% sensitivity and 90% specificity. AUC of miR-199b-5p and miR-582-5p were 0.71 and 0.70, respectively. MiR-892b, miR-199b-5p and miR-582-5p could be considered promising novel diagnostic biomarkers for active tuberculosis.

Acetal-Linked Hyperbranched Polyphosphoester Nanocarriers Loaded with Chlorin e6 for pH-Activatable Photodynamic Therapy.

Nanocarrier-mediated photodynamic therapy (PDT), which involves the systemic delivery of photosensitizers (PSs) into tumor tissue and tumor cells, has emerged as an attractive treatment for cancer. However, insufficient PS release limits intracellular cytotoxic reactive oxygen species (ROS) generation, which has become a major obstacle to improving the PDT therapeutic efficacy. Herein, a novel hyperbranched polyphosphoester (hbPPE) containing numerous acetal bonds (S-hbPPE/Ce6) was explored as a chlorin e6 (Ce6) nanocarrier for PDT. S-hbPPE/Ce6 with a branched topological structure efficiently encapsulated Ce6 and then significantly enhanced its internalization by tumor cells. Subsequently, the endo-/lysosomal acid microenvironment rapidly cleaved the acetal linkage of S-hbPPE and destroyed the nanostructure of S-hbPPE/Ce6, resulting in increased Ce6 release and obviously elevated the intracellular ROS generation under illumination. Therefore, treatment with S-hbPPE/Ce6 noticeably enhanced the PDT therapeutic efficacy, indicating that such a pH-sensitive hbPPE nanocarrier has great potential to improve the PDT therapeutic efficacy for cancer therapy.

A Prototype of Reflection Pulse Oximeter Designed for Mobile Healthcare.

This paper introduces a pulse oximeter prototype designed for mobile healthcare. In this prototype, a reflection pulse oximeter is embedded into the back cover of a smart handheld device to offer the convenient measurement of both heart rate (HR) and SpO2 (estimation of arterial oxygen saturation) for home or mobile applications. Novel and miniaturized circuit modules including a chopper network and a filtering amplifier were designed to overcome the influence of ambient light and interferences that are caused by embedding the sensor into a flat cover. A method based on adaptive trough detection for improved HR and SpO2 estimation is proposed with appropriate simplification for its implementation on mobile devices. A fast and effective photoplethysmogram validation scheme is also proposed. Clinical experiments have been carried out to calibrate and test our oximeter. Our prototype oximeter can achieve comparable performance to a clinical oximeter with no significant difference revealed by paired t -tests ( p = 0.182 for SpO2 measurement and p = 0.496 for HR measurement). The design of this pulse oximeter will facilitate fast and convenient measurement of SpO2 for mobile healthcare.

[CW bio-radar vital sign detector and experiment study].

Non-contact vital sign detection technique provides an effective usage in health monitoring applications. A vital sign detector was designed based on microwave bio-radar technique. Using Doppler principle, continuous wave bioradar was designed for tiny body movement detection, short-time Fourier transform and interpolation algorithm were adopted for heart and respiration rate extraction, embedded system was used for system integration, real-time signal processing software was designed on it. Experiments were done by using simulation device and human body for research and performance evaluation. The result shows that the proposed prototype can be used for single target vital signs detection at the distance of 90 cm, and the heart rate result shows a 96% recognition rate.

Noncontact accurate measurement of cardiopulmonary activity using a compact quadrature Doppler radar sensor.

The designed sensor enables accurate reconstruction of chest-wall movement caused by cardiopulmonary activities, and the algorithm enables estimation of respiration, heartbeat rate, and some indicators of heart rate variability (HRV). In particular, quadrature receiver and arctangent demodulation with calibration are introduced for high linearity representation of chest displacement; 24-bit ADCs with oversampling are adopted for radar baseband acquisition to achieve a high signal resolution; continuous-wavelet filter and ensemble empirical mode decomposition (EEMD) based algorithm are applied for cardio/pulmonary signal recovery and separation so that accurate beat-to-beat interval can be acquired in time domain for HRV analysis. In addition, the wireless sensor is realized and integrated on a printed circuit board compactly. The developed sensor system is successfully tested on both simulated target and human subjects. In simulated target experiments, the baseband signal-to-noise ratio (SNR) is 73.27 dB, high enough for heartbeat detection. The demodulated signal has 0.35% mean squared error, indicating high demodulation linearity. In human subject experiments, the relative error of extracted beat-to-beat intervals ranges from 2.53% to 4.83% compared with electrocardiography (ECG) R-R peak intervals. The sensor provides an accurate analysis for heart rate with the accuracy of 100% for p = 2% and higher than 97% for p = 1%.

[Research on finger key-press gesture recognition based on surface electromyographic signals].

This article reported researches on the pattern recognition of finger key-press gestures based on surface electromyographic (SEMG) signals. All the gestures were defined referring to the PC standard keyboard, and totally 16 sorts of key-press gestures relating to the right hand were defined. The SEMG signals were collected from the forearm of the subjects by 4 sensors. And two kinds of pattern recognition experiments were designed and implemented for exploring the feasibility and repeatability of the key-press gesture recognition based on SEMG signals. The results from 6 subjects showed, by using the same-day templates, that the average classification rates of 16 defined key-press gestures reached above 75.8%. Moreover, when the training samples added up to 5 days, the recognition accuracies approached those obtained with the same-day templates. The experimental results confirm the feasibility and repeatability of SEMG-based key-press gestures classification, which is meaningful for the implementation of myoelectric control-based virtual keyboard interaction.