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Frontiers in Artificial Intelligence 2024Mesoscale eddies, which are fast-moving rotating water bodies in the ocean with horizontal scales ranging from 10 km to 100 km and above, are considered to be the...
Mesoscale eddies, which are fast-moving rotating water bodies in the ocean with horizontal scales ranging from 10 km to 100 km and above, are considered to be the weather of the oceans. They are of interest to marine biologists, oceanographers, and geodesists for their impact on water mass, heat, and nutrient transport. Typically, gridded sea level anomaly maps processed from multiple radar altimetry missions are used to detect eddies. However, multi-mission sea level anomaly maps obtained by the operational processors have a lower effective spatiotemporal resolution than their grid spacing and temporal resolution, leading to inaccurate eddy detection. In this study, we investigate the use of higher-resolution along-track sea level anomaly data to infer daily two-dimensional segmentation maps of cyclonic, anticyclonic, or non-eddy areas with greater accuracy than using processed sea level anomaly grid map products. To tackle this challenge, we propose a deep neural network that uses spatiotemporal contextual information within the modality of along-track data. This network is capable of producing a two-dimensional segmentation map from data with varying sparsity. We have developed an architecture called Teddy, which uses a Transformer module to encode and process spatiotemporal information, and a sparsity invariant CNN to infer a two-dimensional segmentation map of classified eddies from the ground tracks of varying sparsity on the considered region. Our results show that Teddy creates two-dimensional maps of classified eddies from along-track data with higher accuracy and timeliness when compared to commonly used methods that work with less accurate preprocessed sea level anomaly grid maps. We train and test our method with a carefully curated and independent dataset, which can be made available upon request.
PubMed: 38455471
DOI: 10.3389/frai.2024.1298283 -
Microbiological Research May 2024In multinuclear and multicellular filamentous fungi little is known about how mRNAs encoding secreted enzymes are transcribed and localized spatiotemporally. To better...
In multinuclear and multicellular filamentous fungi little is known about how mRNAs encoding secreted enzymes are transcribed and localized spatiotemporally. To better understand this process we analyzed mRNA encoding GlaA, a glucoamylase secreted in large amounts by the industrial filamentous fungus Aspergillus oryzae, by the MS2 system, in which mRNA can be visualized in living cells. We found that glaA mRNA was significantly transcribed and localized near the hyphal tip and septum, which are the sites of protein secretion, in polarity-dependent expression and localization manners. We also revealed that glaA mRNA exhibits long-range dynamics in the vicinity of the endoplasmic reticulum (ER) in a manner that is dependent on the microtubule motor proteins kinesin-1 and kinesin-3, but independent of early endosomes. Moreover, we elucidated that although glaA mRNA localized to stress granules (SGs) and processing bodies (PBs) under high temperature, glaA mRNA was not seen under ER stress, suggesting that there are different regulatory mechanisms of glaA mRNA by SG and PB under high temperature and ER stress. Collectively, this study uncovers a dynamic regulatory mechanism of mRNA encoding a secretory enzyme in filamentous fungi.
Topics: Glucan 1,4-alpha-Glucosidase; Kinesins; Endoplasmic Reticulum; Protein Transport; Fungi; Fungal Proteins
PubMed: 38422859
DOI: 10.1016/j.micres.2024.127653 -
Journal of Biomedical Optics Feb 2024The imaging depth of microscopy techniques is limited by the ability of light to penetrate biological tissue. Recent research has addressed this limitation by combining...
SIGNIFICANCE
The imaging depth of microscopy techniques is limited by the ability of light to penetrate biological tissue. Recent research has addressed this limitation by combining a reflectance confocal microscope with the NIR-II (or shortwave infrared) spectrum. This approach offers significant imaging depth, is straightforward in design, and remains cost-effective. However, the imaging system, which relies on intrinsic signals, could benefit from adjustments in its optical design and post-processing methods to differentiate cortical cells, such as neurons and small blood vessels.
AIM
We implemented a phase contrast detection scheme to a reflectance confocal microscope using NIR-II spectral range as illumination.
APPROACH
We analyzed the features retrieved in the images while testing the imaging depth. Moreover, we introduce an acquisition method for distinguishing dynamic signals from the background, allowing the creation of vascular maps similar to those produced by optical coherence tomography.
RESULTS
The phase contrast implementation is successful to retrieve deep images in the cortex up to using a cranial window. Vascular maps were retrieved at similar cortical depth and the possibility of combining multiple images can provide a vessel network.
CONCLUSIONS
Phase contrast reflectance confocal microscopy can improve the outlining of cortical cell bodies. With the presented framework, angiograms can be retrieved from the dynamic signal in the biological tissue. Our work presents an optical implementation and analysis techniques from a former microscope design.
Topics: Microscopy; Tomography, Optical Coherence; Microscopy, Phase-Contrast; Neuroimaging; Microscopy, Confocal
PubMed: 38414657
DOI: 10.1117/1.JBO.29.2.026501 -
Overcoming ethical and legal obstacles to data linkage in health research: stakeholder perspectives.International Journal of Population... 2023Data linkage for health research purposes enables the answering of countless new research questions, is said to be cost effective and less intrusive than other means of...
INTRODUCTION
Data linkage for health research purposes enables the answering of countless new research questions, is said to be cost effective and less intrusive than other means of data collection. Nevertheless, health researchers are currently dealing with a complicated, fragmented, and inconsistent regulatory landscape with regard to the processing of data, and progress in health research is hindered.
AIM
We designed a qualitative study to assess what different stakeholders perceive as ethical and legal obstacles to data linkage for health research purposes, and how these obstacles could be overcome.
METHODS
Two focus groups and eighteen semi-structured in-depth interviews were held to collect opinions and insights of various stakeholders. An inductive thematic analysis approach was used to identify overarching themes.
RESULTS
This study showed that the ambiguity regarding the 'correct' interpretation of the law, the fragmentation of policies governing the processing of personal health data, and the demandingness of legal requirements are experienced as causes for the impediment of data linkage for research purposes by the participating stakeholders. To remove or reduce these obstacles authoritative interpretations of the laws and regulations governing data linkage should be issued. The participants furthermore encouraged the harmonisation of data linkage policies, as well as promoting trust and transparency and the enhancement of technical and organisational measures. Lastly, there is a demand for legislative and regulatory modifications amongst the participants.
CONCLUSIONS
To overcome the obstacles in data linkage for scientific research purposes, perhaps we should shift the focus from adapting the current laws and regulations governing data linkage, or even designing completely new laws, towards creating a more thorough understanding of the law and making better use of the flexibilities within the existing legislation. Important steps in achieving this shift could be clarification of the legal provisions governing data linkage by issuing authoritative interpretations, as well as the strengthening of ethical-legal oversight bodies.
PubMed: 38414541
DOI: 10.23889/ijpds.v8i1.2151 -
Journal of Ethnobiology and... Feb 2024Plants deliver livelihood and food for millions of people in the world. Indeed, wild edible plants support rural communities in developing countries to overcome seasonal...
BACKGROUND
Plants deliver livelihood and food for millions of people in the world. Indeed, wild edible plants support rural communities in developing countries to overcome seasonal unfavorable conditions. In rural areas of Ethiopia, wild edible plants play an indispensable role in fighting food insecurity as emergency or supplementary foods. Hence, this research was aimed at studying the ethnobotanical assessment of wild edible plants in Dibatie district, Metekel zone, western Ethiopia.
METHODS
Ethnobotanical data was collected using a semi-structured interview, field observation, focus group discussions, a market survey, and the ranking of selected plants. Besides, voucher specimens were collected and stored at the National Herbarium of Ethiopia. Descriptive statistics, preference ranking, direct matrix ranking, and familiarity index were computed for data analysis.
RESULTS
This study has documented 54 wild edible plant species belonging to 33 plant families and 46 genera. Of these, most (38.90%) had tree growth habits. Wild edible plants bear mostly fruits (72.20%) as edible parts. Local people usually consume these plants freshly raw as complementary foods, though some wild edibles require processing. They were mostly harvested in the January (31.48%) and May (27.78%) months, with the least collected in September (7.41%). Most wild edible plants (78.57%) were available in uncontrolled habitats, while others (21.43%) live in farmlands, home gardens, and as live fences. Out of the recorded plants, about 98% had additional uses besides their nutritional values.
CONCLUSION
Wild edible plants assist the livelihoods of the local people in food security, agriculture, energy sources, construction, medicines, ecological services, aesthetics, income generation, and household utensils. Nevertheless, wild edible plants are recently threatened due to various anthropogenic factors in the study area. Thus, they need wise use and in-situ and ex-situ conservation measures from all the concerned bodies for sustainable use in the future.
Topics: Humans; Plants, Edible; Ethiopia; Ethnobotany; Ecosystem; Food
PubMed: 38413982
DOI: 10.1186/s13002-024-00671-2 -
Shaping high-performance wearable robots for human motor and sensory reconstruction and enhancement.Nature Communications Feb 2024Most wearable robots such as exoskeletons and prostheses can operate with dexterity, while wearers do not perceive them as part of their bodies. In this perspective, we... (Review)
Review
Most wearable robots such as exoskeletons and prostheses can operate with dexterity, while wearers do not perceive them as part of their bodies. In this perspective, we contend that integrating environmental, physiological, and physical information through multi-modal fusion, incorporating human-in-the-loop control, utilizing neuromuscular interface, employing flexible electronics, and acquiring and processing human-robot information with biomechatronic chips, should all be leveraged towards building the next generation of wearable robots. These technologies could improve the embodiment of wearable robots. With optimizations in mechanical structure and clinical training, the next generation of wearable robots should better facilitate human motor and sensory reconstruction and enhancement.
Topics: Humans; Robotics; Electronics; Exoskeleton Device; Technology; Wearable Electronic Devices
PubMed: 38409128
DOI: 10.1038/s41467-024-46249-0 -
Sensors (Basel, Switzerland) Feb 2024Hyperspectral image (HSI) classification is a highly challenging task, particularly in fields like crop yield prediction and agricultural infrastructure detection. These...
Hyperspectral image (HSI) classification is a highly challenging task, particularly in fields like crop yield prediction and agricultural infrastructure detection. These applications often involve complex image types, such as soil, vegetation, water bodies, and urban structures, encompassing a variety of surface features. In HSI, the strong correlation between adjacent bands leads to redundancy in spectral information, while using image patches as the basic unit of classification causes redundancy in spatial information. To more effectively extract key information from this massive redundancy for classification, we innovatively proposed the CESA-MCFormer model, building upon the transformer architecture with the introduction of the Center Enhanced Spatial Attention (CESA) module and Morphological Convolution (MC). The CESA module combines hard coding and soft coding to provide the model with prior spatial information before the mixing of spatial features, introducing comprehensive spatial information. MC employs a series of learnable pooling operations, not only extracting key details in both spatial and spectral dimensions but also effectively merging this information. By integrating the CESA module and MC, the CESA-MCFormer model employs a "Selection-Extraction" feature processing strategy, enabling it to achieve precise classification with minimal samples, without relying on dimension reduction techniques such as PCA. To thoroughly evaluate our method, we conducted extensive experiments on the IP, UP, and Chikusei datasets, comparing our method with the latest advanced approaches. The experimental results demonstrate that the CESA-MCFormer achieved outstanding performance on all three test datasets, with Kappa coefficients of 96.38%, 98.24%, and 99.53%, respectively.
PubMed: 38400345
DOI: 10.3390/s24041187 -
Nature Communications Feb 2024Liquid-liquid phase separation is the key process underlying formation of membrane-less compartments in cells. A highly dynamic cellular body with rapid component...
Liquid-liquid phase separation is the key process underlying formation of membrane-less compartments in cells. A highly dynamic cellular body with rapid component exchange is Cajal body (CB), which supports the extensive compositional dynamics of the RNA splicing machinery, spliceosome. Here, we select an arginine-glycine (RG)-rich segment of coilin, the major component of CB, establish its RNA-induced phase separation, and through combined use of nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) probes, interrogate its dynamics within the crowded interior of formed droplets. Taking advantage of glycine-based singlet-states, we show that glycines retain a large level of sub-nanoseconds dynamics inside the coilin droplets. Furthermore, the continuous-wave (CW) and electron-electron dipolar (PELDOR) and electron-nucleus hyperfine coupling EPR data (HYSCORE) support the RNA-induced formation of dynamic coilin droplets with high coilin peptide concentrations. The combined NMR and EPR data reveal the high dynamics of the RG-rich coilin within droplets and suggest its potential role in the large dynamics of CBs.
Topics: Nuclear Proteins; Arginine; Glycine; Electrons; RNA; Coiled Bodies
PubMed: 38383529
DOI: 10.1038/s41467-024-45788-w -
PloS One 2024Optimal nutrition in early childhood increases growth and development while preventing morbidity and mortality in later life. This study focused on the quality and...
Optimal nutrition in early childhood increases growth and development while preventing morbidity and mortality in later life. This study focused on the quality and safety of 32 commercially produced complementary foods collected from supermarkets in Addis Ababa, Ethiopia. The proximate composition (moisture, protein, fat, crude fibre, and ash); and the mineral profile (calcium, iron, zinc, manganese, and magnesium) were determined using the AOAC method. The determination of antinutritional factors (Condensed tannin and oxalate) was done using a UV spectrophotometer. A rapid visco analyzer was used to measure the rheological property. The microbial load of commercially produced complimentary foods was identified using aerobic colony counts for mold and yeast. Labeling practice was evaluated using the WHO and Ethiopian standard tools. The results of proximate compositions were: protein (0.92-18.16 g/100g), fat (0.63-6.44 g/100g), crude fiber (1.04-13.2 g/100g), energy (410-337 kcal/100g), moisture (0.03-17 g/100g), and ash (0.60-4.67 g/100g). The protein and fat content of all the products is below international standards. Only three products met the standards for energy. Moisture and ash contents partially met the requirement, while all of the carbohydrate contents of the products fell under the specified standard. The lowest and highest mineral contents of the products were: Fe (1.38 to 15.10 mg/100g), Zn (0.64 to 6.78 mg/100g), Ca (30.55 to 364.45 mg/100g), Mg (1.2 to 34.2 mg/100g), and Mn (0.80 to 32 mg/100g). Based on these, 21.5% of the foods met the Fe standard, and 31.5% didn't meet the Zn standard. The Ca and Mg of all the products met the requirement. Except for one product, all met standards. The highest and lowest results for the tannin and oxalate content of the products were 49.20 to 90.09 mg/100g and 0.47 to 30.10 mg/100g, respectively and this shows that the products are below the permissible range for tannin and oxalate. The counts of yeast and mold were 0.00-2.95 log10 cfu/g and 0.00-2.91 log10 cfu/g, respectively. Only one product fell below the standard for yeast count, and none of the products showed a mold count that exceeded the standard. The final viscosity was 63.5-3476 RVU, and only 31.25% of the samples fell under the permissible peak viscosity range, of 83-250 RVU. Thus, regular monitoring of the raw material and processing trends and the inclusion of animal sources in the raw material are suggested for having well-enriched complementary foods. Regulatory bodies should also conduct frequent market surveillance to safeguard the health of the consumer.
Topics: Animals; Child, Preschool; Humans; Saccharomyces cerevisiae; Tannins; Ethiopia; Nutrients; Minerals; Oxalates
PubMed: 38381727
DOI: 10.1371/journal.pone.0294068 -
Sensors (Basel, Switzerland) Jan 2024The two-dimensional (2D) cross-hole seismic computed tomography (CT) imaging acquisition method has the potential to characterize the target zone optimally compared to...
The two-dimensional (2D) cross-hole seismic computed tomography (CT) imaging acquisition method has the potential to characterize the target zone optimally compared to surface seismic surveys. It has wide applications in oil and gas exploration, engineering geology, etc. Limited to 2D hole velocity profiling, this method cannot acquire three-dimensional (3D) information on lateral geological structures outside the profile. Additionally, the sensor data received by cross-hole seismic exploration constitute responses from geological bodies in 3D space and are potentially affected by objects outside the well profiles, distorting the imaging results and geological interpretation. This paper proposes a 3D cross-hole acoustic wave reverse-time migration imaging method to capture 3D cross-hole geological structures using sensor settings in multi-cross-hole seismic research. Based on the analysis of resulting 3D cross-hole images under varying sensor settings, optimizing the observation system can aid in the cost-efficient obtainment of the 3D underground structure distribution. To verify this method's effectiveness on 3D cross-hole structure imaging, numerical simulations were conducted on four typical geological models regarding layers, local high-velocity zones, large dip angles, and faults. The results verify the model's superiority in providing more reliable and accurate 3D geological information for cross-hole seismic exploration, presenting a theoretical basis for processing and interpreting cross-hole data.
PubMed: 38339533
DOI: 10.3390/s24030815