ALBERT

Description: Fine particulate matter (PM2.5) mainly originates from combustion emissions. On-road transportation is considered one of the primary sources of PM2.5 emission. The relationship between on-road transportation and PM2.5 concentration varies temporally and spatially, and the estimation for this variation is important for policymaking. Here, we reveal the quantitative association of PM2.5 concentration with on-road transportation by the spatial panel Durbin model and the geographical and temporal weighted regression. We find that 6.17 billion kilometres (km) per km2 on-road transportation increase is associated with a 1-μg/m3 county-level PM2.5 concentration increase in the contiguous United States. On-road transportation marginally contributes to PM2.5, only 1.09% on average. Approximately 3605 premature deaths are attributed to PM2.5 from on-road transportation in 2010, and about a total of 50,223 premature deaths ascribe to PM2.5 taking 6.49% from 2003 to 2016. Our findings shed light on the necessity of the county-level policies considering the temporal and spatial variability of the relationship to further mitigate PM2.5 from on-road transportation.

Description: Background One of the factors contributing to a high maternal mortality rate is the utilization of non-healthcare facilities as a birthplace for women. This study analyzed determinants affecting birthplace in middle-to lower-class women in Indonesia. Methods This study analyzed the 2017 Indonesian Demographic and Health Survey (IDHS) data. The total national sample size was 49,627 eligible women. Our sample included 11,104 women, aged 15–49, who had delivered babies and were of low-to-middle economic status. The type of survey dataset was individual record dataset. Data were analyzed with chi-square and multivariate logistic regression tests using Stata 16 software. Results About 64.99% middle to lower class women in Indonesia delivered in healthcare facilities. Women aged 45–49 (OR = 2.103; 95% CI = 1.13–3.93), who graduated from higher schools (OR = 2.885; 95% CI = 1.76–4.73), whose husbands had higher education (OR = 2.826; 95% CI = 1.69–4.74) and were employed (OR = 2.523; 95% CI = 1.23–5.17), who considered access to healthcare facilities was not a problem (OR = 1.528; 95% CI = 1.28–1.82), who had a single child (OR = 2.349; 95% CI = 1.97–2.80), and who lived in urban areas (OR = 2.930; 95% CI = 2.40–3.57) were determinants that significantly correlated with women giving birth in healthcare facilities. Conclusion This study provides insights for policymakers and healthcare centers in the community to strengthen access to healthcare services and devise health promotion strategies for pregnant mothers. Policy interventions designed for middle- to lower-class women should be implemented to support vulnerable groups.

Description: Background Adequate tumor tissue is required to make the best treatment choice for non-small cell lung cancer (NSCLC). Transbronchial biopsy (TBB) by endobronchial ultrasonography with a guide sheath (EBUS-GS) is useful to diagnose peripheral lung lesions. The data of tumor cell numbers obtained by two different sizes of GSs is limited. We conducted this study to investigate the utility of a large GS kit to obtain many tumor cells in patients with NSCLC. Methods Patients with a peripheral lung lesion and suspected of NSCLC were prospectively enrolled. They underwent TBB with a 5.9-mm diameter bronchoscope with a large GS. When the lesion was invisible in EBUS, we changed to a thinner bronchoscope and TBB was performed with a small GS. We compared the tumor cell number prospectively obtained with a large GS (prospective large GS group) and those previously obtained with a small GS (small GS cohort). The primary endpoint was the tumor cell number per sample, and we assessed characteristics of lesions that could be obtained by TBB with large GS. Results Biopsy with large GS was performed in 55 of 87 patients (63.2%), and 37 were diagnosed with NSCLC based on histological samples. The number of tumor cells per sample was not different between two groups (658±553 vs. 532±526, estimated difference between two groups with 95% confidence interval (CI); 125 (-125–376), p = 0.32). The sample size of the large GS group was significantly larger than that of the small GS cohort (1.75 mm2 vs. 0.83 mm2, estimated difference with 95% CI; 0.92 (0.60–1.23) mm2, p = 0.00000019). The lesion involving a third or less bronchus generation was predictive factors using large GS. Conclusions The sample size obtained with large GS was significantly larger compared to that obtained with small GS, but there was no significant difference in tumor cell number. The 5.9-mm diameter bronchoscope with large GS can be used for lesions involving a third or less bronchus generation.

Description: Tendinopathy is a complex multifaceted tendinopathy often associated with overuse and with its high prevalence resulting in significant health care costs. At present, the pathogenesis and effective treatment of tendinopathy are still not sufficiently elucidated. The purpose of this research is to intensely explore the genes, functional pathways, and immune infiltration characteristics of the occurrence and development of tendinopathy. The gene expression profile of GSE106292, GSE26051 and GSE167226 are downloaded from GEO (NCBI comprehensive gene expression database) and analyzed by WGCNA software bag using R software, GSE26051, GSE167226 data set is combined to screen the differential gene analysis. We subsequently performed gene enrichment analysis of Gene Ontology (GO) and "Kyoto Encyclopedia of Genes and Genomes" (KEGG), and immune cell infiltration analysis. By constructing the LASSO regression model, Support vector machine (SVM-REF) and Gaussian mixture model (GMMs) algorithms are used to screen, to identify early diagnostic genes. We have obtained a total of 171 DEGs through WGCNA analysis and differentially expressed genes (DEGs) screening. By GO and KEGG enrichment analysis, it is found that these dysregulated genes were related to mTOR, HIF-1, MAPK, NF-κB and VEGF signaling pathways. Immune infiltration analysis showed that M1 macrophages, activated mast cells and activated NK cells had infiltration significance. After analysis of THE LASSO SVM-REF and GMMs algorithms, we found that the gene MACROD1 may be a gene for early diagnosis. We identified the potential of tendon disease early diagnosis way and immune gene regulation MACROD1 key infiltration characteristics based on comprehensive bioinformatics analysis. These hub genes and functional pathways may as early biomarkers of tendon injuries and molecular therapy level target is used to guide drug and basic research.

Description: Environmental DNA (eDNA) is nuclear or mitochondrial DNA shed into the environment, and amplifying this DNA can serve as a reliable, noninvasive way to monitor aquatic systems for the presence of an invasive species. Assays based on the collection of eDNA are becoming increasingly popular, and, when optimized, can aid in effectively and efficiently tracking invasion fronts. We set out to update an eDNA assay to detect the invasive rusty crayfish, Faxonius rusticus. We tested for species specificity compared to other stream crayfish and field tested the assay at sites with known presence (N = 3) and absence (N = 4) in the Juniata River watershed in central Pennsylvania, USA. To maximize sensitivity, we field tested different storage buffers (Longmire’s buffer and ethanol), DNA extraction methods (Qiagen’s DNEasy and PowerWater kits), and quantitative polymerase chain reaction (qPCR) chemistries (TaqMan and SYBR green). Our assay confirmed the presence data and performed optimally when filter samples were stored in Longmire’s buffer, DNA was extracted with DNeasy Blood and Tissue Kit, and TaqMan qPCR chemistry was utilized. With proper sample processing, our assay allows for accurate, noninvasive detection of F. rusticus in streams.

Description: Background Women not only have worse diabetes complications, but also have menstrual cycle, pregnancy, and menopause which can make managing diabetes more difficult. The aim of this study was to investigate if radial pressure wave analysis may non-invasively screen for women’s risk of type 2 diabetes. Methods Spectrum analysis of the radial pressure wave was performed to evaluate the first five harmonic components, C1 to C5. The study consisted of a total of 808 non-pregnant female subjects aged 20–95 over the period of 4 years, and 404 of them were diagnosed with Type 2 diabetes as the case group. Result The first five harmonic components are significantly different in a comparison of the case group and the control group. In the logistic regression analysis, T2DM was found to be associated with C1 (OR = 1.055, CI = 1.037–1.074, p 〈 0.001), C2 (OR = 1.051, CI = 1.019–1.085, p = 0.002), and C3 (OR = 0.972, CI = 0.950–0.994, p = 0.013). In the Receiver Operating Characteristic curve analysis, the Area Under Curve of using C3 only (70%, p

Description: Widespread adoption of MON 87701 × MON 89788 soybean, expressing Cry1Ac Bt protein and glyphosate tolerance, has been observed in Brazil. A proactive program was implemented to phenotypically and genotypically monitor Cry1Ac resistance in Chrysodeixis includens (Walker). Recent cases of unexpected injury in MON 87701 × MON 89788 soybean were investigated and a large-scale sampling of larvae on commercial soybean fields was performed to assess the efficacy of this technology and the distribution of lepidopteran pests in Brazil. No significant shift in C. includens susceptibility to Cry1Ac was observed eight years after commercial introduction of this technology in Brazil. F2 screen results confirmed that the frequency of Cry1Ac resistance alleles remains low and stable in C. includens. Unexpected injury caused by Rachiplusia nu (Guenée) and Crocidosema aporema (Walsingham) in MON 87701 × MON 89788 soybean was detected during the 2020/21 season, and studies confirmed a genetically based alteration in their susceptibility to Cry1Ac. MON 87701 × MON 89788 soybean remains effective against Anticarsia gemmatalis (Hübner), C. includens, Chloridea virescents (Fabricius) and Helicoverpa armigera (Hübner) in Brazil. However, there is evidence of field-evolved resistance to MON 87701 × MON 89788 soybean by the secondary soybean pests R. nu and C. aporema.

Description: The placebo effect across psychiatric disorders is still not well understood. In the present study, we conducted meta-analyses including meta-regression, and machine learning analyses to investigate whether the power of placebo effect depends on the types of psychiatric disorders. We included 108 clinical trials (32,035 participants) investigating pharmacological intervention effects on major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SCZ). We developed measures based on clinical rating scales and Clinical Global Impression scores to compare placebo effects across these disorders. We performed meta-analysis including meta-regression using sample-size weighted bootstrapping techniques, and machine learning analysis to identify the disorder type included in a trial based on the placebo response. Consistently through multiple measures and analyses, we found differential placebo effects across the three disorders, and found lower placebo effect in SCZ compared to mood disorders. The differential placebo effects could also distinguish the condition involved in each trial between SCZ and mood disorders with machine learning. Our study indicates differential placebo effect across MDD, BD, and SCZ, which is important for future neurobiological studies of placebo effects across psychiatric disorders and may lead to potential therapeutic applications of placebo on disorders more responsive to placebo compared to other conditions.

Description: Participation and activity post stroke can be limited due to adverse weather conditions. This study aimed to: Quantify and compare summer and winter participation and activity, and explore how community dwelling people with stroke describe their feelings about their level of participation and activity by season. This embedded mixed-methods observational study took place in a city with weather extremes. Community dwelling individuals at least one year post-stroke, able to walk ≥50 metres +/- a walking aide were included. Evaluations and interviews occurred at participants’ homes in two seasons: Reintegration to Normal living Index (RNL), Activities-specific Balance Confidence (ABC) and descriptive outcomes. Participants wore activity monitors for one week each season. Analysis included descriptive statistics, non-parametric tests and an inductive approach to content analysis. Thirteen individuals participated in quantitative evaluation with eight interviewed. Mean age 61.5 years, 62% female and mean 6.2 years post-stroke. No differences between winter-summer values of RNL, ABC, or activity monitor outcomes. However, participants felt they could do more and were more independent in summer. The winter conditions such as ice, snow, cold and wind restricted participation and limited activities. Nonetheless, many participants were active and participated despite the winter challenges by finding other ways to be active, and relying on social supports and personal motivation. The qualitative findings explained unexpected quantitative results. Participants described many challenges with winter weather, but also ways they had discovered to participate and be active despite these challenges. Changes to future studies into seasonal differences are suggested.

Description: This exploration primarily aims to jointly apply the local FCN (fully convolution neural network) and YOLO-v5 (You Only Look Once-v5) to the detection of small targets in remote sensing images. Firstly, the application effects of R-CNN (Region-Convolutional Neural Network), FRCN (Fast Region-Convolutional Neural Network), and R-FCN (Region-Based-Fully Convolutional Network) in image feature extraction are analyzed after introducing the relevant region proposal network. Secondly, YOLO-v5 algorithm is established on the basis of YOLO algorithm. Besides, the multi-scale anchor mechanism of Faster R-CNN is utilized to improve the detection ability of YOLO-v5 algorithm for small targets in the image in the process of image detection, and realize the high adaptability of YOLO-v5 algorithm to different sizes of images. Finally, the proposed detection method YOLO-v5 algorithm + R-FCN is compared with other algorithms in NWPU VHR-10 data set and Vaihingen data set. The experimental results show that the YOLO-v5 + R-FCN detection method has the optimal detection ability among many algorithms, especially for small targets in remote sensing images such as tennis courts, vehicles, and storage tanks. Moreover, the YOLO-v5 + R-FCN detection method can achieve high recall rates for different types of small targets. Furthermore, due to the deeper network architecture, the YOL v5 + R-FCN detection method has a stronger ability to extract the characteristics of image targets in the detection of remote sensing images. Meanwhile, it can achieve more accurate feature recognition and detection performance for the densely arranged target images in remote sensing images. This research can provide reference for the application of remote sensing technology in China, and promote the application of satellites for target detection tasks in related fields.