scholarly journals Skin-Integrated Wearable Systems and Implantable Biosensors: A Comprehensive Review

Biosensors ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 79 ◽  
Author(s):  
Daniela Rodrigues ◽  
Ana I. Barbosa ◽  
Rita Rebelo ◽  
Il Keun Kwon ◽  
Rui L. Reis ◽  
...  
Keyword(s):  
Health Management ◽  
Active Material ◽  
Data Communication ◽  
Biological Response ◽  
Disease Diagnosis ◽  
Surrounding Tissue ◽  
Structural Support ◽  
Implantable Biosensors ◽  
Wearable Systems ◽  
Monitoring Treatment

Biosensors devices have attracted the attention of many researchers across the world. They have the capability to solve a large number of analytical problems and challenges. They are future ubiquitous devices for disease diagnosis, monitoring, treatment and health management. This review presents an overview of the biosensors field, highlighting the current research and development of bio-integrated and implanted biosensors. These devices are micro- and nano-fabricated, according to numerous techniques that are adapted in order to offer a suitable mechanical match of the biosensor to the surrounding tissue, and therefore decrease the body’s biological response. For this, most of the skin-integrated and implanted biosensors use a polymer layer as a versatile and flexible structural support, combined with a functional/active material, to generate, transmit and process the obtained signal. A few challenging issues of implantable biosensor devices, as well as strategies to overcome them, are also discussed in this review, including biological response, power supply, and data communication.

scholarly journals A Review on Biosensors and Recent Development of Nanostructured Materials-Enabled Biosensors

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1109
Author(s):  
Varnakavi. Naresh ◽  
Nohyun Lee
Keyword(s):  
High Surface ◽  
Three Dimensional ◽  
Biological Response ◽  
Volume Ratio ◽  
Recent Decade ◽  
Disease Diagnosis ◽  
Electrical Signal ◽  
Detection Sensitivity ◽  
Wide Range ◽  
Color Tunability

A biosensor is an integrated receptor-transducer device, which can convert a biological response into an electrical signal. The design and development of biosensors have taken a center stage for researchers or scientists in the recent decade owing to the wide range of biosensor applications, such as health care and disease diagnosis, environmental monitoring, water and food quality monitoring, and drug delivery. The main challenges involved in the biosensor progress are (i) the efficient capturing of biorecognition signals and the transformation of these signals into electrochemical, electrical, optical, gravimetric, or acoustic signals (transduction process), (ii) enhancing transducer performance i.e., increasing sensitivity, shorter response time, reproducibility, and low detection limits even to detect individual molecules, and (iii) miniaturization of the biosensing devices using micro-and nano-fabrication technologies. Those challenges can be met through the integration of sensing technology with nanomaterials, which range from zero- to three-dimensional, possessing a high surface-to-volume ratio, good conductivities, shock-bearing abilities, and color tunability. Nanomaterials (NMs) employed in the fabrication and nanobiosensors include nanoparticles (NPs) (high stability and high carrier capacity), nanowires (NWs) and nanorods (NRs) (capable of high detection sensitivity), carbon nanotubes (CNTs) (large surface area, high electrical and thermal conductivity), and quantum dots (QDs) (color tunability). Furthermore, these nanomaterials can themselves act as transduction elements. This review summarizes the evolution of biosensors, the types of biosensors based on their receptors, transducers, and modern approaches employed in biosensors using nanomaterials such as NPs (e.g., noble metal NPs and metal oxide NPs), NWs, NRs, CNTs, QDs, and dendrimers and their recent advancement in biosensing technology with the expansion of nanotechnology.

scholarly journals Quantifying 3D Strain in Scaffold Implants for Regenerative Medicine

Materials ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 3890 ◽  
Author(s):  
Jeffrey N. Clark ◽  
Saman Tavana ◽  
Agathe Heyraud ◽  
Francesca Tallia ◽  
Julian R. Jones ◽  
...  
Keyword(s):  
Regenerative Medicine ◽  
Local Level ◽  
Cell Lineage ◽  
Biological Response ◽  
Cartilage Regeneration ◽  
Ground Truth ◽  
Image Correlation ◽  
Surrounding Tissue ◽  
Materials Testing ◽  
Random Errors

Regenerative medicine solutions require thoughtful design to elicit the intended biological response. This includes the biomechanical stimulus to generate an appropriate strain in the scaffold and surrounding tissue to drive cell lineage to the desired tissue. To provide appropriate strain on a local level, new generations of scaffolds often involve anisotropic spatially graded mechanical properties that cannot be characterised with traditional materials testing equipment. Volumetric examination is possible with three-dimensional (3D) imaging, in situ loading and digital volume correlation (DVC). Micro-CT and DVC were utilised in this study on two sizes of 3D-printed inorganic/organic hybrid scaffolds (n = 2 and n = 4) with a repeating homogenous structure intended for cartilage regeneration. Deformation was observed with a spatial resolution of under 200 µm whilst maintaining displacement random errors of 0.97 µm, strain systematic errors of 0.17% and strain random errors of 0.031%. Digital image correlation (DIC) provided an analysis of the external surfaces whilst DVC enabled localised strain concentrations to be examined throughout the full 3D volume. Strain values derived using DVC correlated well against manually calculated ground-truth measurements (R2 = 0.98, n = 8). The technique ensures the full 3D micro-mechanical environment experienced by cells is intimately considered, enabling future studies to further examine scaffold designs for regenerative medicine.

scholarly journals Bioinformatics: scope and challenges in aquaculture research of Bangladesh- a review

2021 ◽  
Vol 10 (2) ◽  
pp. 137-145
Author(s):  
KMS Rana ◽  
K Ahammad ◽  
MA Salam
Keyword(s):  
Health Management ◽  
National Level ◽  
Work Force ◽  
Disease Diagnosis ◽  
Software Tools ◽  
Biological Data ◽  
Biological Information ◽  
Biological Research ◽  
Future Research ◽  
Data Set

Bioinformatics is one of the ongoing trends of biological research integrating gene based information and computational technology to produce new knowledge. It works to synthesize complex biological information from multiomics data (results of high throughput technologies) by employing a number of bioinformatics tools (software). User convenience and availability are the determining factors of these tools being widely used in bioinformatics research. BLAST, FASTA (FAST-All), EMBOSS, ClustalW, RasMol and Protein Explorer, Cn3D, Swiss PDB viewer, Hex, Vega, Bioeditor etc. are commonly operated bioinformatics software tools in fisheries and aquaculture research. By default, these software tools mine and analyze a vast biological data set using the available databases. However, aquaculture scientists can use bioinformatics for genomic data manipulation, genome annotation and expression profiling, molecular folding, modeling, and design as well as generating biological network and system biology. Therefore, they can contribute in specified fields of aquaculture such as disease diagnosis and aquatic health management, fish nutritional aspects and culture-able strain development. Although having huge prospects, Bangladesh is still in infancy of applying bioinformatics in aquaculture research with limited resources. Research council at national level should be formed to bring all the enthusiastic scientists and skilled manpower under a single umbrella and facilitate to contribute in a collaborative platform. Besides, fully-fledged bioinformatics degree should be launched at University levels to produce knowledgeable and trained work force for future research. This review was attempted to shed light on bioinformatics, as young integrated field of bio-computational research, and its significance in aquaculture research of Bangladesh. Int. J. Agril. Res. Innov. Tech. 10(2): 137-145, December 2020

scholarly journals Visualization and application of disease diagnosis codes for population health management using porcine diseases as a model

2021 ◽  
pp. 104063872199578
Author(s):  
Giovani Trevisan ◽  
Kent J. Schwartz ◽  
Eric R. Burrough ◽  
Bailey Arruda ◽  
Rachel J. Derscheid ◽  
...  
Keyword(s):  
Health Management ◽  
Animal Health ◽  
Laboratory Data ◽  
Disease Diagnosis ◽  
Diagnostic Code ◽  
Diagnostic Laboratory ◽  
Diagnosis Codes ◽  
Animal Populations ◽  
Diagnostic Report ◽  
Visualization Tools

Accurate and timely results of diagnostic investigations and laboratory testing guide clinical interventions for the continuous improvement of animal health and welfare. Infectious diseases can severely limit the health, welfare, and productivity of populations of animals. Livestock veterinarians submit thousands of samples daily to veterinary diagnostic laboratories (VDLs) for disease diagnosis, pathogen monitoring, and surveillance. Individual diagnostic laboratory reports are immediately useful; however, aggregated historical laboratory data are increasingly valued by clinicians and decision-makers to identify changes in the health status of various animal populations over time and geographical space. The value of this historical information is enhanced by visualization of trends of agent detection, disease diagnosis, or both, which helps focus time and resources on the most significant pathogens and fosters more effective communication between livestock producers, veterinarians, and VDL professionals. Advances in data visualization tools allow quick, efficient, and often real-time scanning and analysis of databases to inform, guide, and modify animal health intervention algorithms. Value is derived at the farm, production system, or regional level. Visualization tools allow client-specific analyses, benchmarking, formulation of research questions, and monitoring the effects of disease management and precision farming practices. We present here the approach taken to visualize trends of disease occurrence using porcine disease diagnostic code data for the period 2010 to 2019. Our semi-automatic standardized creation of a visualization platform allowed the transformation of diagnostic report data into aggregated information to visualize and monitor disease diagnosis.

scholarly journals Comparison of spectral characteristics in human and pig biliary system with hyperspectral imaging (HSI)

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Gary Sean Cooney ◽  
Manuel Barberio ◽  
Michele Diana ◽  
Robert Sucher ◽  
Claire Chalopin ◽  
...  
Keyword(s):  
Gall Bladder ◽  
Hyperspectral Imaging ◽  
Spectral Characteristics ◽  
Biliary Tree ◽  
Disease Diagnosis ◽  
Surrounding Tissue ◽  
Bile Pigment ◽  
Biliary Anatomy ◽  
Therapeutic Procedures ◽  
Absorbance Spectra

AbstractInjuries to the biliary tree during surgical, endoscopic or invasive radiological diagnostic or therapeutic procedures involving the pancreas, liver or organs of the upper gastrointestinal tract give rise to the need to develop a method for clear discrimination of biliary anatomy from surrounding tissue. Hyperspectral imaging (HSI) is an emerging optical technique in disease diagnosis and image-guided surgery with inherent advantages of being a non-contact, non-invasive, and non-ionizing technique. HSI can produce quantitative diagnostic information about tissue pathology, morphology, and chemical composition. HSI was applied in human liver transplantation and compared to porcine model operations to assess the capability of discriminating biliary anatomy from surrounding biological tissue. Absorbance spectra measured from bile ducts, gall bladder, and liver show a dependence on tissue composition and bile concentration, with agreement between human and porcine datasets. The bile pigment biliverdin and structural proteins collagen and elastin were identified as contributors to the bile duct and gall bladder absorbance spectra.

scholarly journals Mobile Veterinary Clinic: an innovative approach to promote calf health

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
A. Khair ◽  
E. H. Chowdhury ◽  
A. K. M. A. Rahman ◽  
M. T. Islam ◽  
M. M. Alam
Keyword(s):  
Health Management ◽  
Disease Diagnosis ◽  
Morbidity And Mortality ◽  
Unknown Etiology ◽  
Veterinary Clinic ◽  
Herd Level ◽  
Calf Health ◽  
Project Coordinator ◽  
Routine Surveillance ◽  
Calf Mortality

Background: Calf morbidity and mortality are of great concern for dairyman all over the world including Bangladesh. A mobile Veterinary Clinic (MVC) was established to identify the diseases associated with morbidity and mortality and provide veterinary services at farmers’ door step to promote calf health. Methods: A MVC was established and run from October 2011 to October 2014 to promote calf health. A total of 500 farmers from small and large holder private farms having at least two crossbred cattle were selected. A motorcycle and a mobile phone were provided to each research assistant (RA). The farmers were linked with RAs through mobile number. The ULO/VS were linked with the RA of the respective upazila for immediate treatment of the affected animal(s). The farms were under routine surveillance of the RA. In case of sickness or mortality, RA immediately contacted with ULO/VS and project coordinator/principal investigator at Bangladesh Agricultural University. Necessary advices were given by ULO/VS/consultants to solve the problem as required. Health cards were distributed to the selected farmers for recording the health status of cattle. Diseases were confirmed by clinical and laboratory methods. Farmers were trained on better calf health management. Early disease diagnosis and treatment, routine de-worming and vaccination of cows and calves were performed regularly. Results: Before implementing MVC services, the overall mortality at herd level was 11.5% which was 8.2% and 14.7% in Muktagacha and Shahjadpur respectively. The overall morbidity was 48.5% which was higher in Shahjadpur (57.94%) than Muktagacha (33.81%). The most common causes of calf mortality were pneumonia (66.2%), unknown (17.4%), adverse drug effect (5.3%), FMD (2.6%) and sudden death (2.4%). Due to MVC at farmers’ door step, the overall herd level mortality reduced significantly from 11.5 to 2.9% which were 8.2 to 2.3% in Muktagacha and 14.7 to 3.6% in Shahjadpur. Conclusion: Measures to control pneumonia and FMD in calves should be undertaken. The unknown etiology of mortality should be explored. Cautions should be taken before administering drugs in calves. As MVC was successful in reducing calf mortality, we recommend replicating in other parts of the country.

Mobile Health Application in China: Cross-sectional Study (Preprint)

2020 ◽  
Author(s):  
Le Yang ◽  
Jiadong Wu ◽  
Xiaoxiao Mo ◽  
Yaqin Chen ◽  
Shanshan Huang ◽  
...  
Keyword(s):  
Mobile Health ◽  
Health Management ◽  
Disease Diagnosis ◽  
Cross Sectional Study ◽  
Actual State ◽  
Primary Analysis ◽  
Cross Sectional ◽  
Mobile Health Application ◽  
Wide Range ◽  
Mhealth Apps

BACKGROUND Mobile health applications are emerging as a novel platform to obtain data pertinent to wellness and disease diagnosis, prevention, and management. As the future general trend of medical informatization, mobile health is an indispensable way to promote universal medical care to reduce disease burden. The features of these mHealth apps in China is unclear, so we collected a wide range of application information to evaluate these apps effectively. OBJECTIVE We aim to provide a landscape of mHealth apps on the existing market in China. We expect that based on the actual state, this study can give future development directions of mHealth apps. METHODS We searched mHealth apps from five android app stores (Huawei, Oppo, Vivo, Tencent, and 360), Apple App Store (IOS), and Baidu search engine up to October 25, 2019. We also searched the inventory of the top 100 Chinese hospitals in 2018 and four online shopping sites (Tmall, JD, Pinduoduo, and Suning) to identify apps of Internet hospitals and intelligent devices, respectively. RESULTS We identified 2425 mHealth apps (93.3% android, 69.2% iPhone) in the primary analysis, whose intentional users were ordinary consumers (Android 1808/2262, 79.9%; IOS 1350/1677, 80.5%). 56.1% (1168/2081) of app developers were Internet companies. More than 90% of apps were available free of cost (Android 2111/2262, 93.3%; IOS 1615/1677, 96.3%), but in-app purchases accounted for more than 60% (Android 1397/2262, 61.8%; IOS 1189/1677, 70.9%). Of the 1285 public available apps, 1248 were for health management, of which 26.3% (328/1248) were related to bodybuilding, and 13.7% (171/1248) were related to women's health. The other 697 apps were used for medical support, and 289 of them were related to inquiries. The permissions required by the apps include claiming the network (2081/2107), reading the status and identity of the phone (1881/2107) , and location (1799/2107). CONCLUSIONS With the increasing condition of the paid and membership system, rising profit of mHealth app drives various industries to move forward. This study guides research designs of future apps in mHealth field. The prospect of mHealth app is bright, but there exists a critical condition in claiming excessive permissions, security, and legal management, which need to be further strengthened.

scholarly journals Multi-Path Dilated Residual Network for Nuclei Segmentation and Detection

Cells ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 499 ◽  
Author(s):  
Eric Ke Wang ◽  
Xun Zhang ◽  
Leyun Pan ◽  
Caixia Cheng ◽  
Antonia Dimitrakopoulou-Strauss ◽  
...  
Keyword(s):  
Health Management ◽  
Disease Diagnosis ◽  
Detection Task ◽  
Cell Detection ◽  
Data Sets ◽  
Residual Network ◽  
Nuclei Segmentation ◽  
Nuclei Detection ◽  
Small Targets ◽  
Nuclear Segmentation

As a typical biomedical detection task, nuclei detection has been widely used in human health management, disease diagnosis and other fields. However, the task of cell detection in microscopic images is still challenging because the nuclei are commonly small and dense with many overlapping nuclei in the images. In order to detect nuclei, the most important key step is to segment the cell targets accurately. Based on Mask RCNN model, we designed a multi-path dilated residual network, and realized a network structure to segment and detect dense small objects, and effectively solved the problem of information loss of small objects in deep neural network. The experimental results on two typical nuclear segmentation data sets show that our model has better recognition and segmentation capability for dense small targets.

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