scholarly journals Nanostructures for Biosensing, with a Brief Overview on Cancer Detection, IoT, and the Role of Machine Learning in Smart Biosensors

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1253
Author(s):  
Aishwaryadev Banerjee ◽  
Swagata Maity ◽  
Carlos H. Mastrangelo
Keyword(s):  
Machine Learning ◽  
Cancer Detection ◽  
Industrial Process ◽  
Clinical Diagnostics ◽  
Widespread Application ◽  
Military Health ◽  
Simple Detection ◽  
And Performance

Biosensors are essential tools which have been traditionally used to monitor environmental pollution and detect the presence of toxic elements and biohazardous bacteria or virus in organic matter and biomolecules for clinical diagnostics. In the last couple of decades, the scientific community has witnessed their widespread application in the fields of military, health care, industrial process control, environmental monitoring, food-quality control, and microbiology. Biosensor technology has greatly evolved from in vitro studies based on the biosensing ability of organic beings to the highly sophisticated world of nanofabrication-enabled miniaturized biosensors. The incorporation of nanotechnology in the vast field of biosensing has led to the development of novel sensors and sensing mechanisms, as well as an increase in the sensitivity and performance of the existing biosensors. Additionally, the nanoscale dimension further assists the development of sensors for rapid and simple detection in vivo as well as the ability to probe single biomolecules and obtain critical information for their detection and analysis. However, the major drawbacks of this include, but are not limited to, potential toxicities associated with the unavoidable release of nanoparticles into the environment, miniaturization-induced unreliability, lack of automation, and difficulty of integrating the nanostructured-based biosensors, as well as unreliable transduction signals from these devices. Although the field of biosensors is vast, we intend to explore various nanotechnology-enabled biosensors as part of this review article and provide a brief description of their fundamental working principles and potential applications. The article aims to provide the reader a holistic overview of different nanostructures which have been used for biosensing purposes along with some specific applications in the field of cancer detection and the Internet of things (IoT), as well as a brief overview of machine-learning-based biosensing.

scholarly journals Nanotechnology for Biosensors: A Review

2021 ◽  
Author(s):  
Aishwaryadev Banerjee ◽  
Swagata Maity ◽  
Carlos H. Mastrangelo
Keyword(s):  
Industrial Process ◽  
Clinical Diagnostics ◽  
Widespread Application ◽  
Military Health ◽  
Simple Detection ◽  
Potential Applications ◽  
Industrial Process Control ◽  
And Performance

Biosensors are essential tools which have been traditionally used to monitor environmental pollution, detect the presence of toxic elements and biohazardous bacteria or virus in organic matter and biomolecules for clinical diagnostics. In the last couple of decades, the scientific community has witnessed their widespread application in the fields of military, health care, industrial process control, environmental monitoring, food-quality control, and microbiology. Biosensor technology has greatly evolved from the in vitro studies based on the biosensing ability of organic beings to the highly sophisticated world of nanofabrication enabled miniaturized biosensors. The incorporation of nanotechnology in the vast field of biosensing has led to the development of novel sensors and sensing mechanisms, as well as an increase in the sensitivity and performance of the existing biosensors. Additionally, the nanoscale dimension further assists the development of sensors for rapid and simple detection in vivo as well as the ability to probe single-biomolecules and obtain critical information for their detection and analysis. However, the major drawbacks of this include, but are not limited to potential toxicities associated with the unavoidable release of nanoparticles into the environment, miniaturization induced unreliability, lack of automation, and difficulty of integrating the nanostructured-based biosensors as well as unreliable transduction signals from these devices. Although the field of biosensors is vast, we intend to explore various nanotechnology enabled biosensors as part of this review article and provide a brief description of their fundamental working principles and potential applications.

scholarly journals Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2505
Author(s):  
Raheem Remtulla ◽  
Sanjoy Kumar Das ◽  
Leonard A. Levin
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
In Silico ◽  
Disulfide Bonds ◽  
Oral Absorption ◽  
In Vivo Studies ◽  
Drug Candidates ◽  
In Silico Methods

Phosphine-borane complexes are novel chemical entities with preclinical efficacy in neuronal and ophthalmic disease models. In vitro and in vivo studies showed that the metabolites of these compounds are capable of cleaving disulfide bonds implicated in the downstream effects of axonal injury. A difficulty in using standard in silico methods for studying these drugs is that most computational tools are not designed for borane-containing compounds. Using in silico and machine learning methodologies, the absorption-distribution properties of these unique compounds were assessed. Features examined with in silico methods included cellular permeability, octanol-water partition coefficient, blood-brain barrier permeability, oral absorption and serum protein binding. The resultant neural networks demonstrated an appropriate level of accuracy and were comparable to existing in silico methodologies. Specifically, they were able to reliably predict pharmacokinetic features of known boron-containing compounds. These methods predicted that phosphine-borane compounds and their metabolites meet the necessary pharmacokinetic features for orally active drug candidates. This study showed that the combination of standard in silico predictive and machine learning models with neural networks is effective in predicting pharmacokinetic features of novel boron-containing compounds as neuroprotective drugs.

scholarly journals The Implications of Regulatory Framework for Topical Semisolid Drug Products: From Critical Quality and Performance Attributes towards Establishing Bioequivalence

Pharmaceutics ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 710
Author(s):  
Tanja Ilić ◽  
Ivana Pantelić ◽  
Snežana Savić
Keyword(s):  
Statistical Power ◽  
Failure Modes ◽  
In Vitro Release ◽  
Optimal Number ◽  
Drug Products ◽  
Pharmaceutical Equivalence ◽  
And Performance ◽  
Low Sensitivity

Due to complex interdependent relationships affecting their microstructure, topical semisolid drug formulations face unique obstacles to the development of generics compared to other drug products. Traditionally, establishing bioequivalence is based on comparative clinical trials, which are expensive and often associated with high degrees of variability and low sensitivity in detecting formulation differences. To address this issue, leading regulatory agencies have aimed to advance guidelines relevant to topical generics, ultimately accepting different non-clinical, in vitro/in vivo surrogate methods for topical bioequivalence assessment. Unfortunately, according to both industry and academia stakeholders, these efforts are far from flawless, and often upsurge the potential for result variability and a number of other failure modes. This paper offers a comprehensive review of the literature focused on amending regulatory positions concerning the demonstration of (i) extended pharmaceutical equivalence and (ii) equivalence with respect to the efficacy of topical semisolids. The proposed corrective measures are disclosed and critically discussed, as they span from mere demands to widen the acceptance range (e.g., from ±10% to ±20%/±25% for rheology and in vitro release parameters highly prone to batch-to-batch variability) or reassess the optimal number of samples required to reach the desired statistical power, but also rely on specific data modeling or novel statistical approaches.

scholarly journals The Topical Nanodelivery of Vismodegib Enhances Its Skin Penetration and Performance In Vitro While Reducing Its Toxicity In Vivo

Pharmaceutics ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 186
Author(s):  
Maria Natalia Calienni ◽  
Daniela Maza Vega ◽  
C. Facundo Temprana ◽  
María Cecilia Izquierdo ◽  
David E. Ybarra ◽  
...  
Keyword(s):  
Side Effects ◽  
Water Solubility ◽  
Polymeric Micelles ◽  
Skin Penetration ◽  
Distribution Volume ◽  
And Performance ◽  
Oral Doses ◽  
Advanced Basal Cell Carcinoma

Vismodegib is a first-in-class inhibitor for advanced basal cell carcinoma treatment. Its daily oral doses present a high distribution volume and several side effects. We evaluated its skin penetration loaded in diverse nanosystems as potential strategies to reduce side effects and drug quantities. Ultradeformable liposomes, ethosomes, colloidal liquid crystals, and dendrimers were able to transport Vismodegib to deep skin layers, while polymeric micelles failed at this. As lipidic systems were the most effective, we assessed the in vitro and in vivo toxicity of Vismodegib-loaded ultradeformable liposomes, apoptosis, and cellular uptake. Vismodegib emerges as a versatile drug that can be loaded in several delivery systems for topical application. These findings may be also useful for the consideration of topical delivery of other drugs with a low water solubility.

scholarly journals Biological nanoscale fluorescent probes: From structure and performance to bioimaging

2020 ◽  
Vol 39 (1) ◽  
pp. 209-221
Author(s):  
Jiafeng Wan ◽  
Xiaoyuan Zhang ◽  
Kai Zhang ◽  
Zhiqiang Su
Keyword(s):  
Fluorescent Probes ◽  
Organic Dyes ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
High Sensitivity ◽  
Biological Imaging ◽  
Fluorescent Materials ◽  
And Performance

Abstract In recent years, nanomaterials have attracted lots of attention from researchers due to their unique properties. Nanometer fluorescent materials, such as organic dyes, semiconductor quantum dots (QDs), metal nano-clusters (MNCs), carbon dots (CDs), etc., are widely used in biological imaging due to their high sensitivity, short response time, and excellent accuracy. Nanometer fluorescent probes can not only perform in vitro imaging of organisms but also achieve in vivo imaging. This provides medical staff with great convenience in cancer treatment. Combined with contemporary medical methods, faster and more effective treatment of cancer is achievable. This article explains the response mechanism of three-nanometer fluorescent probes: the principle of induced electron transfer (PET), the principle of fluorescence resonance energy transfer (FRET), and the principle of intramolecular charge transfer (ICT), showing the semiconductor QDs, precious MNCs, and CDs. The excellent performance of the three kinds of nano fluorescent materials in biological imaging is highlighted, and the application of these three kinds of nano fluorescent probes in targeted biological imaging is also introduced. Nanometer fluorescent materials will show their significance in the field of biomedicine.

The Role of microRNAs in Osteoporosis Diagnostics

2021 ◽  
Vol 30 (03) ◽  
pp. 222-229
Author(s):  
Matthias Hackl ◽  
Elisabeth Semmelrock ◽  
Johannes Grillari
Keyword(s):  
Bone Mass ◽  
Bone Metabolism ◽  
Messenger Rna ◽  
Biological Fluids ◽  
Clinical Diagnostics ◽  
Bone Architecture ◽  
Estrogen Metabolism ◽  
Age Related

AbstractMicroRNAs (miRNAs) are short (18–24 nucleotides) non-coding RNA sequences that regulate gene expression via binding of messenger RNA. It is estimated that miRNAs co-regulate the expression of more than 70% of all human genes, many of which fulfil important roles in bone metabolism and muscle function. In-vitro and in-vivo experiments have shown that the targeted loss of miRNAs in distinct bone cell types (osteoblasts and osteoclasts) results in altered bone mass and bone architecture. These results emphasize the biological relevance of miRNAs for bone health.MiRNAs are not only considered as novel bone biomarkers because of their biological importance to bone metabolism, but also on the basis of other favorable properties: 1) Secretion of miRNAs from cells enables “minimally invasive” detection in biological fluids such as serum. 2) High stability of miRNAs in serum enables the retrospective analysis of frozen blood specimens. 3) Quantification of miRNAs in the serum is based on the RT-PCR - a robust method that is considered as the gold standard for the analysis of nucleic acids in clinical diagnostics.With regard to osteoporosis, it has been shown that many of the known risk factors are characterized by distinct miRNA profiles in the affected tissues: i) age-related loss of bone mass, ii) sarcopenia, iii) changes in estrogen metabolism and related changes Loss of bone mass, and iv) diabetes. Therefore, numerous studies in recent years have dealt with the characterization of miRNAs in the serum of osteoporosis patients and healthy controls, and were able to identify recurring miRNA patterns that are characteristic of osteoporosis. These novel biomarkers have great potential for the diagnosis and prognosis of osteoporosis and its clinical outcomes.The aim of this article is to give a summary of the current state of knowledge on the research and application of miRNA biomarkers in osteoporosis.

scholarly journals Application of multi-omics data integration and machine learning approaches to identify epigenetic and transcriptomic differences between in vitro and in vivo produced bovine embryos

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252096
Author(s):  
Maria B. Rabaglino ◽  
Alan O’Doherty ◽  
Jan Bojsen-Møller Secher ◽  
Patrick Lonergan ◽  
Poul Hyttel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Integration ◽  
Focal Adhesion ◽  
Learning Approach ◽  
Omics Data ◽  
Machine Learning Approach ◽  
Cluster 2 ◽  
Omics Data Integration

Pregnancy rates for in vitro produced (IVP) embryos are usually lower than for embryos produced in vivo after ovarian superovulation (MOET). This is potentially due to alterations in their trophectoderm (TE), the outermost layer in physical contact with the maternal endometrium. The main objective was to apply a multi-omics data integration approach to identify both temporally differentially expressed and differentially methylated genes (DEG and DMG), between IVP and MOET embryos, that could impact TE function. To start, four and five published transcriptomic and epigenomic datasets, respectively, were processed for data integration. Second, DEG from day 7 to days 13 and 16 and DMG from day 7 to day 17 were determined in the TE from IVP vs. MOET embryos. Third, genes that were both DE and DM were subjected to hierarchical clustering and functional enrichment analysis. Finally, findings were validated through a machine learning approach with two additional datasets from day 15 embryos. There were 1535 DEG and 6360 DMG, with 490 overlapped genes, whose expression profiles at days 13 and 16 resulted in three main clusters. Cluster 1 (188) and Cluster 2 (191) genes were down-regulated at day 13 or day 16, respectively, while Cluster 3 genes (111) were up-regulated at both days, in IVP embryos compared to MOET embryos. The top enriched terms were the KEGG pathway "focal adhesion" in Cluster 1 (FDR = 0.003), and the cellular component: "extracellular exosome" in Cluster 2 (FDR<0.0001), also enriched in Cluster 1 (FDR = 0.04). According to the machine learning approach, genes in Cluster 1 showed a similar expression pattern between IVP and less developed (short) MOET conceptuses; and between MOET and DKK1-treated (advanced) IVP conceptuses. In conclusion, these results suggest that early conceptuses derived from IVP embryos exhibit epigenomic and transcriptomic changes that later affect its elongation and focal adhesion, impairing post-transfer survival.

A Review of the In Vivo and In Vitro Biomechanical Behavior and Performance of Postoperative Abdominal Aortic Aneurysms and Implanted Stent-Grafts

2008 ◽  
Vol 15 (4) ◽  
pp. 468-484 ◽  
Author(s):  
Timothy J. Corbett ◽  
Anthony Callanan ◽  
Liam G. Morris ◽  
Barry J. Doyle ◽  
Pierce A. Grace ◽  
...  
Keyword(s):  
Abdominal Aortic Aneurysms ◽  
Aortic Aneurysms ◽  
Stent Grafts ◽  
Biomechanical Behavior ◽  
Abdominal Aortic ◽  
And Performance

scholarly journals A Higher Frequency Administration of the Nontoxic Cycloartane-Type Triterpene Argentatin A Improved Its Anti-Tumor Activity

Molecules ◽  
2020 ◽  
Vol 25 (8) ◽  
pp. 1780 ◽  
Author(s):  
Zaira Tavarez-Santamaría ◽  
Nadia J. Jacobo-Herrera ◽  
Leticia Rocha-Zavaleta ◽  
Alejandro Zentella-Dehesa ◽  
Beatriz del Carmen Couder-García ◽  
...  
Keyword(s):  
Waste Product ◽  
Industrial Process ◽  
Annexin V ◽  
Control Group ◽  
Healthy Control ◽  
Hct 116 ◽  
Hct 116 Cells ◽  
Induced Apoptosis

Parthenium argentatum (Gray), commonly known as guayule, has been used to obtain natural rubber since the beginning of the 20th century. Additionally, the so called “resin” is a waste product derived from the industrial process. The cycloartane-type triterpene Argentatin A (AA) is one of the main constituents of the industrial waste resin. In this study we evaluated the AA anticancer activity both in vitro and in vivo in the HCT116 colon cancer cells. The apoptosis promotion of AA was assessed by the annexin V/propidium iodide (PI) assay. The senescence was evaluated for SA-β-galactosidase, and PCNA was used as a marker of proliferation. Its antitumor activity was evaluated using a xenograft mouse model. The results indicated that AA-induced apoptosis in HCT-116 cells and was positively stained for SA-β-galactosidase. In the xenografted mice test, the administration of AA at the dose of 250 mg/kg three times a week for 21 days reduced tumor growth by 78.1%. A comparable tumor reduction was achieved with cisplatin at the dose of 2 mg/kg administered three times a week for 21 days. However, nude mice treated with AA did not lose weight, as they did remarkably when treated with cisplatin. Furthermore, the animals treated with AA showed similar blood profiles as the healthy control group. These data indicate the low toxicity of AA compared to that shown by cisplatin.

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