Gastroesophageal reflux disease and the risk of respiratory diseases: a Mendelian randomization study.

BACKGROUND: Observational studies have suggested a suspected association between gastroesophageal reflux disease (GERD) and respiratory diseases, but the causality remains equivocal. The goal of this study was to evaluate the causal role of GERD in respiratory diseases by employing Mendelian randomization (MR) studies. METHODS: We conducted Mendelian randomization analysis based on summary data of genome-wide association studies (GWASs) and three MR statistical techniques (inverse variance weighted, weighted median and MR-Egger) were employed to assess the probable causal relationship between GERD and the risk of respiratory diseases. Sensitivity analysis was also carried out to ensure more trustworthy results, which involves examining the heterogeneity, pleiotropy and leave-one-SNP-out method. We also identified 33 relevant genes and explored their distribution in 26 normal tissues. RESULTS: In the analysis, for every unit increase in developing GERD, the odds ratio for developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism rose by 72% (ORIVW = 1.72, 95% CI 1.50; 1.99), 19% (ORIVW = 1.19, 95% CI 1.11; 1.28), 16% (ORIVW = 1.16, 95% CI 1.07; 1.26), 0. 3% (ORIVW = 1.003, 95% CI 1.0012; 1.0043) and 33% (ORIVW = 1.33, 95% CI 1.12; 1.58), respectively, in comparison with non-GERD cases. In addition, neither heterogeneity nor pleiotropy was found in the study. This study also found that gene expression was higher in the central nervous system and brain tissue than in other normal tissues. CONCLUSIONS: This study provided evidence that people who developed GERD had a higher risk of developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism. Our research suggests physicians to give effective treatments for GERD on respiratory diseases. By exploring the gene expression, our study may also help to reveal the role played by the central nervous system and brain tissue in developing respiratory diseases caused by GERD.

Crop pest image classification based on improved densely connected convolutional network.

Introduction: Crop pests have a great impact on the quality and yield of crops. The use of deep learning for the identification of crop pests is important for crop precise management. Methods: To address the lack of data set and poor classification accuracy in current pest research, a large-scale pest data set named HQIP102 is built and the pest identification model named MADN is proposed. There are some problems with the IP102 large crop pest dataset, such as some pest categories are wrong and pest subjects are missing from the images. In this study, the IP102 data set was carefully filtered to obtain the HQIP102 data set, which contains 47,393 images of 102 pest classes on eight crops. The MADN model improves the representation capability of DenseNet in three aspects. Firstly, the Selective Kernel unit is introduced into the DenseNet model, which can adaptively adjust the size of the receptive field according to the input and capture target objects of different sizes more effectively. Secondly, in order to make the features obey a stable distribution, the Representative Batch Normalization module is used in the DenseNet model. In addition, adaptive selection of whether to activate neurons can improve the performance of the network, for which the ACON activation function is used in the DenseNet model. Finally, the MADN model is constituted by ensemble learning. Results: Experimental results show that MADN achieved an accuracy and F1Score of 75.28% and 65.46% on the HQIP102 data set, an improvement of 5.17 percentage points and 5.20 percentage points compared to the pre-improvement DenseNet-121. Compared with ResNet-101, the accuracy and F1Score of MADN model improved by 10.48 percentage points and 10.56 percentage points, while the parameters size decreased by 35.37%. Deploying models to cloud servers with mobile application provides help in securing crop yield and quality.

The Prognostic Value of the GNRI in Patients with Stomach Cancer Undergoing Surgery.

Malnutrition often induces an adverse prognosis in cancer surgery patients. The elderly nutrition risk index (GNRI) is an example of the objective indicators of nutrition-related risks. We performed a meta-analysis to thoroughly examine the evidence for the GNRI in predicting the outcomes of patients undergoing stomach cancer surgery. Eligible articles were retrieved using PubMed, the Cochrane Library, EMBASE, and Google Scholar by 24 October 2022. The clinical outcomes were overall survival (OS), cancer-specific survival (CSS), and post-operative complications. A total of 11 articles with 5593 patients were included in this meta-analysis. The combined forest plot showed that for every unit increase in the preoperative GNRI score in patients with stomach cancer, their postoperative mortality was reduced by 5.6% (HR: 0.944; 95% CI: 0.933−0.956, p < 0.001). The pooled results also demonstrated that a low GNRI was correlated with poor OS (HR: 2.052; 95% CI: 1.726−2.440, p < 0.001) and CSS (HR: 1.684; 95% CI: 1.249−2.270, p = 0.001) in patients who underwent stomach cancer surgery. Postoperative complications were more likely to occur in patients with a low GNRI, as opposed to those with a high GNRI (OR: 1.768; 95% CI: 1.445−2.163, p < 0.001). There was no evidence of significant heterogeneity, and the sensitivity analysis supported the stability and dependability of the above results. the GNRI is a valuable predictor of long-term outcomes and complications in stomach cancer patients undergoing surgery.

[Sini Decoction inhibits TLR4/NF-κB signaling pathway to improve airway remodeling of allergic asthmatic mice].

This study aims to explore the effect of Sini Decoction on Toll-like receptor 4(TLR4)/nuclear factor-κB(NF-κB) signaling pathway in the mice with allergic asthma(AA). Forty-eight SPF-grade BALB/c mice were randomly assigned into a blank control group, a model group, a dexamethasone group, and high-, medium-, and low-dose Sini Decoction groups, with 8 mice in each group. The sensitization solution made of ovalbumin and aluminum hydroxide powder was injected intraperitoneally in other groups except the blank control group which was injected with an equal volume of normal saline. The solution(or normal saline) was injected three times in total with an interval of 7 days. At the same time of sensitization, external cold stimulation and ice water were administered in a 4 ℃ climate box for 20 min every day. After modeling, the mice in each group were administrated with corresponding drugs by gavage for 3 weeks. At the end of administration, pentobarbital sodium(30 mg·kg~(-1)) was used for anesthesia, and then the samples were collected for the determination of various indexes. The phenol red test was conducted to evaluate tracheal excretion function. The histopathological changes of lung tissue were observed via hematoxylin-eosin(HE) staining. Masson staining was employed to reveal the deposition of blue collagen fibers around bronchi in lung tissue and the area occupied by blue collagen fibers was calculated. Immunofluorescence method was used to measure the expression of bronchial type Ⅰ collagen(Col-Ⅰ) and α-smooth muscle actin(α-SMA). The protein and mRNA levels of TLR4, NF-κB, cysteinyl aspartate specific proteinase-1(caspase-1), and interleukin-13(IL-13) were determined by Western blot and real-time fluorescence quantitative polymerase chain reaction(real-time PCR), respectively. Compared with the model group, Sini Decoction significantly increased the phenol red excretion from trachea, lowered the lung inflammation score, reduced subepithelial collagen deposition, and decreased Col-Ⅰ and α-SMA levels. Furthermore, the decoction down-regulated the protein and mRNA levels of TLR4, NF-κB, caspase-1, and IL-13 in mouse lung tissue. In conclusion, Sini Decoction can improve air remodeling by inhibiting the TLR4/NF-κB signaling pathway.

Relationship between Antithrombin III Activity and Mortality in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

We aimed to explore the role of antithrombin III (AT-III) activity in diagnosing patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and chronic bronchitis, and its relationship with all-cause mortality of AECOPD patients. We performed univariate and multivariate Cox regression analyses of the factors determining all-cause mortality. We recruited 279 patients with AECOPD and 91 with chronic bronchitis. On admission, patients with AECOPD had lower AT-III activity (80.7 vs. 86.35%, p = 0.002) and higher neutrophil percentages (70.12 vs. 66.40%, p = 0.02) than those with chronic bronchitis. The patients who died were older (78 vs. 73 years, p < 0.001); had higher CRP (39.05 vs. 5.65 mg/L, p < 0.001), D-dimer (1.72 vs. 0.46 mg/L, p < 0.001), FIB (3.56 vs. 3.05 g/L, p = 0.01) levels; and exhibited lower AT-III activity (71.29 vs. 82.94%, p < 0.001) than the survivors. The AT-III area under the receiver operating characteristic curve for predicting COPD all-cause mortality was 0.75 (p < 0.001), optimal cutoff point 79.75%, sensitivity 86.8%, and specificity 57.1%. Multivariate Cox regression analyses showed that increased levels of CRP (HR = 1.005, p = 0.02), D-dimer (HR = 1.17, p = 0.01), WBC count (HR = 1.11, p = 0.002), and reduced AT-III activity (HR = 0.97, p = 0.02) were independent prognostic factors for all-cause mortality. Patients with AT-III ≤ 79.75% were 4.52 times (p = 0.001) more likely to die than those with AT-III > 79.75%. AT-III activity was lower in patients with AECOPD than in those with chronic bronchitis and is potentially useful as an independent predictor of all-cause mortality in patients with AECOPD: reduced AT-III activity and increased CRP and D-dimer levels indicate a higher risk of all-cause mortality.

Combination of UAV and Raspberry Pi 4B: Airspace detection of red imported fire ant nests using an improved YOLOv4 model.

Red imported fire ants (RIFA) are an alien invasive pest that can cause serious ecosystem damage. Timely detection, location and elimination of RIFA nests can further control the spread of RIFA. In order to accurately locate the RIFA nests, this paper proposes an improved deep learning method of YOLOv4. The specific methods were as follows: 1) We improved GhostBottleNeck (GBN) and replaced the original CSP block of YOLOv4, so as to compress the network scale and reduce the consumption of computing resources. 2) An Efficient Channel Attention (ECA) mechanism was introduced into GBN to enhance the feature extraction ability of the model. 3) We used Equalized Focal Loss to reduce the loss value of background noise. 4) We increased and improved the upsampling operation of YOLOv4 to enhance the understanding of multi-layer semantic features to the whole network. 5) CutMix was added in the model training process to improve the model's ability to identify occluded objects. The parameters of improved YOLOv4 were greatly reduced, and the abilities to locate and extract edge features were enhanced. Meanwhile, we used an unmanned aerial vehicle (UAV) to collect images of RIFA nests with different heights and scenes, and we made the RIFA nests (RIFAN) airspace dataset. On the RIFAN dataset, through qualitative analysis of the evaluation indicators, mean average precision (MAP) of the improved YOLOv4 model reaches 99.26%, which is 5.9% higher than the original algorithm. Moreover, compared with Faster R-CNN, SSD and other algorithms, improved YOLOv4 has achieved excellent results. Finally, we transplanted the model to the embedded device Raspberry Pi 4B and assembled it on the UAV, using the model's lightweight and high-efficiency features to achieve flexible and fast flight detection of RIFA nests.

The role of elevated red blood cell distribution width in the prognosis of AECOPD patients: A retrospective study.

ABSTRACT: Chronic obstructive pulmonary disease (COPD) is still a constant threat to people's health. We aimed to identify the relationship between increased red cell distribution width (RDW) on admission and length of hospitalization in acute exacerbation of chronic obstructive pulmonary disease patients (AECOPD).Patients with AECOPD were recruited and divided into 3 groups based on RDW tertiles.Two hundred eighty six patients with AECOPD admitted to our department during January 1, 2017 and June 30, 2019 were enrolled in the study. According to the RDW tertiles (≤12.8%, 12.9% to 13.6%, >13.6%), the patients were divided into 3 groups. Length of stay was significantly related to RDW (P < .001) in AECOPD patients. Correlation analysis indicated that RDW was negatively associated with FEV1% predicted (r = -0.142, P = .016). However, RDW was positively associated with prolonged of stay (r = 0.298, P < .001) in AECOPD patients. Multivariate regression analysis discovered that RDW was independently associated with the length of hospitalization (P = .001). Receiver operating characteristic (ROC) curve showed that RDW was a good predictor of prolonged hospital stay in AECOPD patients, and the area under the curve (AUC) was 0.818 (95% CI: 0.769-0.868). The highest sensitivity to predict prolonged hospital stay was 83.8% and the specificity was 71.6% with the cut-off 13.35%.In conclusion, prolonged hospital stay in AECOPD patients was closely associated with increased RDW. Elevated RDW may be an independent predictor for prolonged hospitalization in AECOPD patients.

Dynamic Increase of Red Cell Distribution Width Predicts Increased Risk of 30-Day Readmission in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

PURPOSE: Studies have demonstrated that red blood cell distribution width (RDW) is closely associated with the prognosis of patients with chronic obstructive pulmonary disease (COPD). In addition, the dynamic changes in RDW appear to play an important role. Thus, we aimed to investigate the relationship between dynamic changes in RDW and 30-day all-cause readmission of patients with acute exacerbation of COPD (AECOPD). METHODS: In this retrospective cohort study, we enrolled patients with AECOPD hospitalized in the Department of Respiratory Medicine in Liyuan Hospital (Wuhan China), a tertiary, university-affiliated, public hospital. Patients with AECOPD were divided into three groups based on their RDW values after the first and fourth days of admission. The normal range for RDW is 10-15%. Patients with normal RDW values were included in the normal group. Patients with an RDW value >15% on the first day, which subsequently decreased by >2% on the fourth day was included in the decreased group. The increased group was comprised of patients with an RDW value >15% on the first day which continued to increase, or those with a normal RDW value on the first day which increased >15% on the fourth day. RESULTS: A total of 239 patients (age: 72 years [range: 64-81 years]; male: n=199 [83.3%]) were included. There were 108, 72, and 59 patients in the RDW normal, decreased, and increased groups, respectively; the 30-day all-cause readmission rate was 9.3%, 9.7%, 27.1%, respectively; (p=0.003), being noticeably higher in the RDW increased group. Dynamic increase of RDW (OR:3.45, 95% CI: 1.39-8.58, p= 0.008) was independently correlated with 30-day all-cause readmission of patients with AECOPD. CONCLUSION: The dynamic increase of RDW is an independent prognostic factor of 30-day all-cause readmission of patients with AECOPD.

Effects of dietary supplementation with tribasic zinc sulfate or zinc sulfate on growth performance, zinc content and expression of zinc transporters in young pigs.

An experiment was conducted to compare the effects of zinc sulfate (ZS) and tribasic zinc sulfate (TBZ) as sources of supplemental zinc on growth performance, serum zinc (Zn) content and messenger RNA (mRNA) expression of Zn transporters (ZnT1/ZnT2/ZnT5/ZIP4/DMT1) of young growing pigs. A total of 96 Duroc × Landrace × Yorkshire pigs were randomly allotted to two treatments and were fed a basal diet supplemented with 100 mg/kg Zn from either ZS or TBZ for 28 days. Feed : gain ratio in pigs fed TBZ were lower (P < 0.05) than pigs fed ZS, and average daily weight gain tended to increase (0.05 ≤ P ≤ 0.10) in pigs fed TBZ. Compared with pigs fed ZS, pigs fed TBZ had a higher CuZn-superoxide dismutase and Zn content in serum (P < 0.05) while they had a lower Zn content in feces (P < 0.05). In addition, ZIP4 mRNA expression of zinc transporter in either duodenum or jejunum of pigs fed TBZ were higher (P < 0.05) than pigs fed ZS. These results indicate that TBZ is more effective in serum Zn accumulation and intestinal Zn absorption, and might be a potential substitute for ZS in young growing pigs.