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Distinct phylogeographic distributions and frequencies of precore and basal core promoter mutations between HBV subgenotype C1 rt269L and rt269I types
Variable DPP4 expression in multiciliated cells of the human nasal epithelium as a determinant for MERS-CoV tropism
Transmissibility of respiratory viruses is a complex viral trait that is intricately linked to tropism. Several highly transmissible viruses, including severe acute respiratory syndrome coronavirus 2 and Influenza viruses, specifically target multiciliated cells in the upper respiratory tract to facilitate efficient human-to-human transmission. In contrast, the zoonotic Middle East respiratory syndrome coronavirus (MERS-CoV) generally transmits poorly between humans, which is largely attributed to the absence of its receptor dipeptidyl peptidase 4 (DPP4) in the upper respiratory tract. At the same time, MERS-CoV epidemiology is characterized by occasional superspreading events, suggesting that some individuals can disseminate this virus effectively. Here, we utilized well-differentiated human pulmonary and nasal airway organoid-derived cultures to further delineate the respiratory tropism of MERS-CoV. We find that MERS-CoV replicated to high titers in both pulmonary and nasal airway cultures. Using single-cell messenger-RNA sequencing, immunofluorescence, and immunohistochemistry, we show that MERS-CoV preferentially targeted multiciliated cells, leading to loss of ciliary coverage. MERS-CoV cellular tropism was dependent on the differentiation of the organoid-derived cultures, and replication efficiency varied considerably between donors. Similarly, variable and focal expression of DPP4 was revealed in human nose tissues. This study indicates that the upper respiratory tract tropism of MERS-CoV may vary between individuals due to differences in DPP4 expression, providing an explanation for the unpredictable transmission pattern of MERS-CoV.
Method for building segmentation and extraction from high-resolution remote sensing images based on improved YOLOv5ds
To address challenges in remote sensing images, such as the abundance of buildings, difficulty in contour extraction, and slow update speeds, a high-resolution remote sensing image building segmentation and extraction method based on the YOLOv5ds network structure was proposed using Gaofen-2 images. This method, named YOLOv5ds-RC, comprises three primary components: target detection, semantic segmentation, and edge optimization. In the semantic segmentation module, an upsampling and multiple convolutional layers branch out from the second feature fusion layer of the Feature Pyramid Networks (FPN), producing a category mapping image that matches the original image size. For edge optimization, a Raster compression module is incorporated at the end of the segmentation network to refine the segmentation contours. This approach enables effective segmentation of Gaofen-2 images, achieving detailed results at the individual building scale across urban areas and facilitating rapid contour optimization and extraction. Experimental results indicate that YOLOv5ds-RC achieves an accuracy of 0.8849, a recall of 0.63904, an average precision (AP) at 0.5 of 0.75863, and a mean average precision (mAP) from 0.5 to 0.95 of 0.47388. These metrics significantly surpass those of the original YOLOv5ds, which recorded values of 0.81483 for accuracy, 0.51332 for recall, 0.63552 for AP at 0.5, and 0.34922 for mAP. The algorithm effectively corrects target displacement deviations in non-orthogonal images and achieves more objective and accurate contour extraction, meeting the requirements for rapid extraction. Due to these features, YOLOv5ds-RC can further enhance fully automated rapid extraction and historical change analysis in land use change monitoring.
The Oomplet dataset toolkit as a flexible and extensible system for large-scale, multi-category image generation
Daily briefing: Iguanas from the Americas might have rafted to Fiji
Results from the <i>inSight</i> Mars mission do not require a water-saturated mid crust
A comprehensive survey and comparative analysis of time series data augmentation in medical wearable computing
Recent advancements in hardware technology have spurred a surge in the popularity and ubiquity of wearable sensors, opening up new applications within the medical domain. This proliferation has resulted in a notable increase in the availability of Time Series (TS) data characterizing behavioral or physiological information from the patient, leading to initiatives toward leveraging machine learning and data analysis techniques. Nonetheless, the complexity and time required for collecting data remain significant hurdles, limiting dataset sizes and hindering the effectiveness of machine learning. Data Augmentation (DA) stands out as a prime solution, facilitating the generation of synthetic data to address challenges associated with acquiring medical data. DA has shown to consistently improve performances when images are involved. As a result, investigations have been carried out to check DA for TS, in particular for TS classification. However, the current state of DA in TS classification faces challenges, including methodological taxonomies restricted to the univariate case, insufficient direction to select suitable DA methods and a lack of conclusive evidence regarding the amount of synthetic data required to attain optimal outcomes. This paper conducts a comprehensive survey and experiments on DA techniques for TS and their application to TS classification. We propose an updated taxonomy spanning across three families of Time Series Data Augmentation (TSDA): Random Transformation (RT), Pattern Mixing (PM), and Generative Models (GM). Additionally, we empirically evaluate 12 TSDA methods across diverse datasets used in medical-related applications, including OPPORTUNITY and HAR for Human Activity Recognition, DEAP for emotion recognition, BioVid Heat Pain Database (BVDB), and PainMonit Database (PMDB) for pain recognition. Through comprehensive experimental analysis, we identify the most optimal DA techniques and provide recommendations for researchers regarding the generation of synthetic data to maximize outcomes from DA methods. Our findings show that despite their simplicity, DA methods of the RT family are the most consistent in increasing performances compared to not using any augmentation.
ARCUNet: enhancing skin lesion segmentation with residual convolutions and attention mechanisms for improved accuracy and robustness
Correction: The cost of doing nothing about a sleeper weed–Nassella neesiana in New Zealand
Glycemic control and associated factors among type 2 diabetes patients attending at Dessie comprehensive specialized hospital outpatient department
Prevalence, risk factors, and treatment methods of thirst in critically ill patients: A systematic review and meta-analysis
Critically ill patients admitted to the intensive care unit (ICU) experience various symptoms and discomfort. Although thirst is a typical distressing symptom and should be assessed daily, it is crucial to understand its prevalence and risk factors in the ICU setting. Nevertheless, currently, systematic reviews of prevalence and risk factors are lacking. This study evaluated the prevalence and risk factors of thirst in critically ill patients. We conducted a comprehensive search of the MEDLINE, Cochrane Library, and CINAHL databases. The study design included cohort, cross-sectional, and intervention studies, including randomized and non-randomized controlled trials with control groups. The point estimates from each study were combined using a random-effects meta-analysis model. We aggregated the prevalence of thirst in ICU patients and calculated the point estimates and 95% confidence intervals. The risk of bias was assessed using the Cochrane Risk of Bias 2 tool and Newcastle-Ottawa Scale. Fifteen studies were eligible for inclusion, of which seven reported the prevalence of thirst. A total of 2,204 patients were combined, with a prevalence estimate of 0.70. The risk factors for thirst were categorized as patient and treatment factors: four patient factors (e.g., serum sodium concentration and severity of illness) and six treatment factors (e.g., nil per os and use of diuretics) were identified. However, the results showed high heterogeneity in the prevalence of thirst among critically ill patients. It was established that 70% of critically ill patients experienced thirst. Additional investigations are required to obtain a more comprehensive overview of thirst among these patients. Systematic review registration number The protocol was registered in PROSPERO (ID: CRD42023428619) on June 6, 2023. (URL: https://www.crd.york.ac.uk)
Differences in muscle morphology assessed by ultrasound at various muscle regions and their impact on voluntary and involuntary force production
Abstract The primary aim of this study was to investigate how measurements from different regions along the rectus femoris (RF) and vastus lateralis (VL) influence muscle morphology, including muscle thickness (MT), muscle stiffness, and muscle quality. An exploratory aim was to examine whether an association exists between voluntary and involuntary force and muscle morphology across the same regions. In one session, participants (n = 13) underwent ultrasound imaging (US), followed by knee extension maximal isometric voluntary contractions and evoked contractions. US recordings (at rest) and testing were conducted while participants were seated at 90º knee flexion (dominant leg) on an isokinetic dynamometer. Muscle morphology was recorded at proximal, medial, and distal regions of RF and VL. During maximum contractions, participants were instructed to exert maximal effort as fast and as forcefully as possible for 5 s, while evoked contractions were performed via femoral nerve stimulation. A one-way repeated measures ANOVA was used for the main aim, while Spearman bivariate correlations were used for the exploratory aim. The primary findings showed that the RF and VL muscles were significantly larger in the medial region (P ≤ 0.023), with no significant differences in muscle quality or stiffness within the same muscle. Additionally, a significant overall relationship was observed between muscle quality and the rate of force development in both muscles (P ≤ 0.037). In conclusion, muscle size varies across the length of the VL and RF muscles, with no changes in muscle quality or stiffness. Furthermore, muscle quality demonstrates a significant association with rate of force development.
Retraction: Measuring convergence in the sugarcane industry in China’s Guangxi province
Impact of various drying technologies for evaluation of drying kinetics, energy consumption, physical and bioactive properties of Rose flower
Abstract The process after harvesting medicinal plants, such as drying, is very important in the production cycle of these plants. The study’s objective is to evaluate the effect of different drying methods on some thermodynamic properties, qualitative and bioactive attributes, and yield of rose essential oil in form of a completely randomized design. The treatments of this study included drying in refractance window (RW), infrared (IR), and convective (CV) at three drying temperatures of 50, 60, and 70 °C, as well as fresh plants. The results showed that different drying methods and temperatures significantly affected the essential oil, thermodynamic, qualitative, bioactive, and yield characteristics. The lowest drying time, energy consumption, and the highest energy efficiency and rehydration ratio in the dried rose samples were related to the drying temperature of 70 °C in the RW method. The reduction of drying time by RW method compared to IR and CV methods was between 11.1–21.40 and 45.9–50%, respectively. The highest amount of antioxidant activity, total phenol, flavonoid and essential oil yield was observed in the RW drying method and at the drying temperature of 60 °C. This study showed that compared to other drying methods, the RW method showed a high quality in drying Rose flowers.
Retraction: A study on interannual change features of soil salinity of cotton field with drip irrigation under mulch in Southern Xinjiang
International expert consensus on the current status and future prospects of artificial intelligence in metabolic and bariatric surgery
Removal of hexavalent chromium from wastewater by chelating resin supported Fe/Cu bimetallic nanoparticles: Characterization, performance and mechanisms
In this work, Bimetallic Fe/Cu nanoparticles were successfully stabilized by chelating resin, which was specifically employed for the remediation of hexavalent chromium contaminated wastewater. Based on the characterization results, it was observed that the Fe/Cu bimetallic nanoparticles were uniformly and well distributed on the surface of the resin DOW M4195. The results demonstrated that the supported bimetallic Fe/Cu nanoparticles exhibited an excellent performance for Cr(VI) removal efficiency, reaching up to 99.4%. A series of factors, including initial pH, initial concentration of Cr(VI), co-exciting ions and humic acid were systematically evaluated to ascertain their respective impacts on Cr(VI) removal. The kinetics study followed intra-particle diffusion model demonstrated that both the adsorption and diffusion processes of Cr(VI) by the DOW M4195 resin played an important role in the overall removal of Cr(VI). The analytical results derived from XPS spectra at specific reaction times revealed the underlying removal mechanism of Cr(VI): Cr(VI) was adsorbed onto M-Fe/Cu due to the rich porous structure of the chelating resin DOW M4195. Additionally, the presence of the second metal, Cu, was found to significantly enhance the reduction performance of Fe0 and Fe(II) during the Cr(VI) removal process. The Cr(VI) removal mechanism was determined to involve a combination of physical adsorption, redox reactions and co-precipitation.
Author Correction: Clinical spectrum of adult-onset leukoencephalopathy with axonal spheroids and pigmented glia in individuals of Korean ancestry
Coronavirus disease 2019 (COVID-19) vaccine acceptability in Ghana: An urban-based population study
Introduction Coronavirus disease 2019 (COVID-19) vaccine hesitancy is a complex health challenge characterized by a delay in the acceptance or refusal of the vaccination with context-specific determinants. Our study, therefore, assessed the COVID-19 vaccine acceptance among urban dwellers in the Central Region, of Ghana. Methods A cross sectional study was conducted between September and November, 2022 using a multi-stage cluster sampling procedure among 377 participants. A modified World Health Organization pretested paper-based questionnaire was administered to study participants. The data was analyzed using Statistical Package for Social Sciences (SPSS) version 26. Descriptive and inferential statistics were carried out and results were summarized into frequencies, percentages, tables, and charts for clarity. A conventional p-value < 0.05 was considered statistically significant. Results The study revealed that COVID-19 vaccine acceptance was 20.0% (76/377) and vaccine hesitancy was 80.0% (301/377). Out of the 377 participants, their socio-demographic characteristics showed that the majority were below 25 years 53.8% (203/377), [vaccine acceptance; 36.84% (28/76) vs vaccine hesitancy; 58.14% (175/301)], and females 50.1% (189/377), [vaccine acceptance; 56.58% (43/76) vs vaccine hesitancy; 48.50% (146/301)]. Common reasons for COVID-19 vaccine hesitancy included mistrust of the source of the vaccine, personal belief and experience, mistrust of the drug development process, mistrust in the health system, and mistrust of the pharmaceutical company. Age above 25 years, female, educational levels, senior high school and above, being employed, and hearing of new vaccine had a significance influence on COVID-19 vaccine acceptance. Conclusion COVID-19 vaccine acceptance was low with high vaccine hesitancy among participants. The study’s findings highlights the importance of addressing vaccine hesitancy through building trust in the vaccine development processes, including the provision of accurate information about the vaccine safety and efficacy. Resolving concerns related to the source of the vaccine and the overall healthcare system are important to address vaccine hesitancy. Policy makers could adopt tailored interventions targeting specific demographic groups, such as the younger population and females to increase vaccine acceptance. Ghana’s public health authorities could adopt the findings to re-strategize its urban COVID-19 vaccine campaigns to address misconceptions and misinformation to increase vaccine acceptance.