ABSTRACT
Cellulose acetate (CA), a prominent water-soluble derivative of cellulose, is a promising biodegradable ingredient that has applications in films, membranes, fibers, drug delivery, and more. In this work, we present a molecularly informed field-theoretic model for CA to explore its phase behavior in aqueous solutions. By integrating atomistic details into large-scale field-theoretic simulations via the relative entropy coarse-graining framework, our approach enables efficient calculations of CA's miscibility window as a function of the degree of substitution (DS) of cellulose hydroxyl groups with acetate side chains. This allows us to capture the intricate phase behavior of CA, particularly its unique miscibility at intermediate substitution, without relying on experimental input. Additionally, the model directly probes CA solution behavior specific to the relative DS at C2, C3, and C6 alcohol sites, providing insights for the rational design of water-soluble CA for diverse applications. This work demonstrates a promising integration of molecularly informed field theories, complementing wet-lab experimentation, for engineering the next-generation polymeric materials with precisely tailored properties.
ABSTRACT
Trk (NTRK) receptor and NTRK gene fusions are oncogenic drivers of a wide variety of tumors. Although Trk receptors are typically activated at the cell surface, signaling of constitutive active Trk and diverse intracellular NTRK fusion oncogenes is barely investigated. Here, we show that a high intracellular abundance is sufficient for neurotrophin-independent, constitutive activation of TrkB kinase domains. In HEK293 cells, constitutive active TrkB kinase and an intracellular NTRK2-fusion oncogene (SQSTM1-NTRK2) reduced actin filopodia dynamics, phosphorylated FAK, and altered the cell morphology. Atypical cellular responses could be mimicked with the intracellular kinase domain, which did not activate the Trk-associated MAPK/ERK pathway. In glioblastoma-like U87MG cells, expression of TrkB or SQSTM1-NTRK2 reduced cell motility and caused drastic changes in the transcriptome. Clinically approved Trk inhibitors or mutating Y705 in the kinase domain, blocked the cellular effects and transcriptome changes. Atypical signaling was also seen for TrkA and TrkC. Moreover, hallmarks of atypical pTrk kinase were found in biopsies of Nestin-positive glioblastoma. Therefore, we suggest Western blot-like immunoassay screening of NTRK-related (brain) tumor biopsies to identify patients with atypical panTrk or phosphoTrk signals. Such patients could be candidates for treatment with NTRK inhibitors such as Larotrectinhib or Entrectinhib.
ABSTRACT
In the present study, naphthalimide-pyrazole-benzothiazole based fluorescent analogs were synthesized by substituting different primary and secondary amines on the naphthalimide nucleus and were evaluated for their sensitivity and selectivity towards serum albumin. Among various synthesized analogues compound 25 showed the most significant change with serum albumin and was further studied for selective detection and mode of interaction with serum albumin. Here, we compared the binding interaction of fluorescent probe 25 for variation/detection of two 76 % structurally resembling proteins HSA and BSA, by spectroscopic experiments. The compound shows more selectivity for HSA and BSA with a higher binding constant and evident visible change in the emission spectra of two serum albumins among different bioanalytes. The mode of interaction of 25 with human serum albumin and bovine serum albumin was investigated by FT-IR, circular dichroism, and DLS techniques to find out the change in the microenvironment and variation in the structure of serum albumin proteins. Higher binding affinity and specific selectivity of 25 with a limit of detection of 0.69â µM and 1.4â µM towards HSA and BSA compared to other bioanalytes make it a significant fluorescent probe for quantitatively detecting serum albumins at the very early stage of many fatal diseases.
Subject(s)
Fluorescent Dyes , Molecular Docking Simulation , Naphthalimides , Serum Albumin, Bovine , Serum Albumin, Human , Spectrometry, Fluorescence , Naphthalimides/chemistry , Naphthalimides/chemical synthesis , Humans , Fluorescent Dyes/chemistry , Fluorescent Dyes/chemical synthesis , Serum Albumin, Bovine/chemistry , Serum Albumin, Human/chemistry , Serum Albumin, Human/metabolism , Binding Sites , Cattle , Molecular Structure , Animals , Protein Binding , Circular Dichroism , Benzothiazoles/chemistry , Benzothiazoles/chemical synthesis , Serum Albumin/chemistry , Serum Albumin/metabolismABSTRACT
The fusion of haemagglutinin-neuraminidase (HN) protein of peste des petits ruminant (PPR) virus with signaling lymphocyte activation molecules (SLAM) host cell receptor consequences the virus entry and multiplication inside the host cell. The use of synthetic SLAM homologous peptides (i.e., molecular decoy for HN protein of PPR virus) may check PPR infection at the preliminary stage. Hence, the predicted SLAM homologous peptides using bioinformatics tools were synthesized by solid phase chemistry with standard Merrifield's 9-fluorenylmethoxycarbonyl (Fmoc) chemistry and were purified by reverse phase high performance liquid chromatography. The secondary structures of synthesized peptides were elucidated by circular dichroism spectroscopy. The in vitro interactions of these peptides were studied through indirect Enzyme Linked Immuno Sorbent Assay (ELISA) and visual surface plasmon UV-visible spectroscopy. The SLAM homologous peptides were able to interact with the peste des petits ruminant virus (PPRV) with varying binding efficiency. The interaction of SLAM homologous peptide with the PPR virus was ascertained by the change in the plasmon color from red wine to purple during visual detection and also by bathochromic shift in absorbance spectra under UV-visible spectrophotometry. The cytotoxic and anti-PPRV effect of these peptides were also evaluated in B95a cell line using PPR virus (Sungri/96). The cytotoxic concentration 50 (CC50 ) value of each peptide was greater than 1000 µg mL-1 . The anti-PPRV efficiency of SLAM-22 was relatively high among SLAM homologous peptides, SLAM-22 at 25 µg mL-1 concentration showed a reduction of more than log10 3 virus titer by priming of B95a cell line while the use of SLAM-15 and Muco-17 at the same concentration dropped virus titer from log10 4.8 to log10 2.5 and log10 3.1 respectively. The concentration of SLAM homologous peptide (25 µg mL-1 ) to exert its anti-PPRV effect was much less than its CC50 level (>1000 µg mL-1 ). Therefore, the synthetic SLAM homologous peptides may prove to be better agents to target PPRV.
Subject(s)
Peste-des-Petits-Ruminants , Peste-des-petits-ruminants virus , Animals , Peste-des-petits-ruminants virus/metabolism , Peste-des-Petits-Ruminants/metabolism , Cell Line , Viral Proteins/metabolism , Peptides/pharmacology , Peptides/metabolism , GoatsABSTRACT
The critical micelle concentration (CMC) is a crucial parameter in understanding the self-assembly behavior of surfactants. In this study, we combine simulation and experiment to demonstrate the predictive capability of molecularly informed field theories in estimating the CMC of biologically based protein surfactants. Our simulation approach combines the relative entropy coarse-graining of small-scale atomistic simulations with large-scale field-theoretic simulations, allowing us to efficiently compute the free energy of micelle formation necessary for the CMC calculation while preserving chemistry-specific information about the underlying surfactant building blocks. We apply this methodology to a unique intrinsically disordered protein platform capable of a wide variety of tailored sequences that enable tunable micelle self-assembly. The computational predictions of the CMC closely match experimental measurements, demonstrating the potential of molecularly informed field theories as a valuable tool to investigate self-assembly in bio-based macromolecules systematically.
Subject(s)
Intrinsically Disordered Proteins , Micelles , Surface-Active Agents , Computer SimulationABSTRACT
Increasing irrigation demand has heavily relied on groundwater use, especially in places with highly variable water supplies that are vulnerable to drought. Groundwater management in agriculture is becoming increasingly challenging given the growing effects from overdraft and groundwater depletion worldwide. However, multiple challenges emerge when seeking to develop sustainable groundwater management in irrigated systems, such as trade-offs between the economic revenues from food production and groundwater resources, as well as the broad array of uncertainties in food-water systems. In this study we explore the applicability of Evolutionary Multi-Objective Direct Policy Search (EMODPS) to identify adaptive irrigation policies that water agencies and farmers can implement including operational decisions related to land use and groundwater use controls as well as groundwater pumping fees. The EMODPS framework yields state-aware, adaptive policies that respond dynamically as system state conditions change, for example with variable surface water (e.g., shifting management strategies across wet versus dry years). For this study, we focus on the Semitropic Water Storage district located in the San Joaquin Valley, California to provide broader insights relevant to ongoing efforts to improve groundwater sustainability in the state. Our findings demonstrate that adaptive irrigation policies can achieve sufficiently flexible groundwater management to acceptably balance revenue and sustainability goals across a wide range of uncertain future scenarios. Among the evaluated policy decisions, pumping restrictions and reductions in inflexible irrigation demands from tree crops are actions that can support dry-year pumping while maximizing groundwater storage recovery during wet years. Policies suggest that an adaptive pumping fee is the most flexible decision to control groundwater pumping and land use.
Subject(s)
Conservation of Natural Resources , Groundwater , Water Supply , Agriculture , UncertaintyABSTRACT
The self-assembly and phase separation of mixtures of polyelectrolytes and surfactants are important to a range of applications, from formulating personal care products to drug encapsulation. In contrast to systems of oppositely charged polyelectrolytes, in polyelectrolyte-surfactant systems the surfactants micellize into structures that are highly responsive to solution conditions. In this work, we examine how the morphology of micelles and degree of polyelectrolyte adsorption dynamically change upon varying the mixing ratio of charged and neutral surfactants. Specifically, we consider a solution of the cationic polyelectrolyte polydiallyldimethylammonium, anionic surfactant sodium dodecyl sulfate, neutral ethoxylated surfactants (C[Formula: see text]EO[Formula: see text]), sodium chloride salt, and water. To capture the chemical specificity of these species, we leverage recent developments in constructing molecularly informed field theories via coarse-graining from all-atom simulations. Our results show how changing the surfactant mixing ratios and the identity of the nonionic surfactant modulates micelle size and surface charge, and as a result dictates the degree of polyelectrolyte adsorption. These results are in semi-quantitative agreement with experimental observations on the same system.
ABSTRACT
The lack of specific antiviral therapy and complications associated with the existing peste des petits ruminants (PPR) vaccines accentuates the search of novel antiviral blocking agents in order to curtail the PPR infection at initial level. The synthetic hemagglutinin-neuraminidase (HN) homologous peptides may compete with the natural HN protein of PPR virus for binding to signaling lymphocytic activation molecule (SLAM) receptor, consequently, may disrupt peste des petits ruminants virus (PPRV) at entry level. Therefore, insilico analysis, synthesis, purification and subsequent characterization of HN homologous peptides were conducted in this study. The HN homologous peptides were synthesized by means of solid phase chemistry and were purified by reversed-phase-high performance liquid chromatography. The mass as well as sequence of HN homologous peptides were assessed by mass spectroscopy while its secondary structure was elucidated by circular dichroism spectroscopy. The binding (interaction) efficacy of HN homologous peptides with PPRV antibodies was assessed via indirect enzyme linked immunosorbent assay, visual detection test (red wine to purple), bathochromic shift under UV-Vis spectrophotometry and lateral flow immunochromatographic strip test. The antiviral properties and cytotoxicity of these peptides were also assessed in B95a cell line with changes in cytopathic effect and titer of PPRV (Sungri/96). The presence of green fluorescein isothiocyanate over the B95a cell surface pointed towards the binding of HN homologous peptides with surface SLAM receptor. Moreover, the intact beta sheet configuration in water and lower cytotoxicity [cytotoxic concentration 50 (CC50) > 1000 µg/ml] of these peptides signifies its in vivo use. Among HN homologous peptides, the binding efficacy and antiviral properties of pep A was relatively high in comparison to pep B and Pep ppr peptides. The prerequisite concentration of HN homologous peptides (pep A = 12.5 µg/ml; pep B = 25 µg/ml; pep ppr = 25 µg/ml) to exemplify its antiviral effect was much lower than its CC50 level. Hence, this study signifies the therapeutic potential of synthetic HN homologous peptides.
ABSTRACT
Most soft robots are pneumatically actuated and fabricated by molding and assembling processes that typically require many manual operations and limit complexity. Furthermore, complex control components (for example, electronic pumps and microcontrollers) must be added to achieve even simple functions. Desktop fused filament fabrication (FFF) three-dimensional printing provides an accessible alternative with less manual work and the capability of generating more complex structures. However, because of material and process limitations, FFF-printed soft robots often have a high effective stiffness and contain a large number of leaks, limiting their applications. We present an approach for the design and fabrication of soft, airtight pneumatic robotic devices using FFF to simultaneously print actuators with embedded fluidic control components. We demonstrated this approach by printing actuators an order of magnitude softer than those previously fabricated using FFF and capable of bending to form a complete circle. Similarly, we printed pneumatic valves that control a high-pressure airflow with low control pressure. Combining the actuators and valves, we demonstrated a monolithically printed electronics-free autonomous gripper. When connected to a constant supply of air pressure, the gripper autonomously detected and gripped an object and released the object when it detected a force due to the weight of the object acting perpendicular to the gripper. The entire fabrication process of the gripper required no posttreatment, postassembly, or repair of manufacturing defects, making this approach highly repeatable and accessible. Our proposed approach represents a step toward complex, customized robotic systems and components created at distributed fabricating facilities.
ABSTRACT
Pressure-sensitive adhesives (PSAs) based on poly(acrylate) chemistry are common in a wide variety of applications, but the absence of backbone degradability causes issues with recycling and sustainability. Here, we report a strategy to create degradable poly(acrylate) PSAs using simple, scalable, and functional 1,2-dithiolanes as drop-in replacements for traditional acrylate comonomers. Our key building block is α-lipoic acid, a natural, biocompatible, and commercially available antioxidant found in various consumer supplements. α-Lipoic acid and its derivative ethyl lipoate efficiently copolymerize with n-butyl acrylate under conventional free-radical conditions leading to high-molecular-weight copolymers (Mn > 100 kg mol-1) containing a tunable concentration of degradable disulfide bonds along the backbone. The thermal and viscoelastic properties of these materials are practically indistinguishable from nondegradable poly(acrylate) analogues, but a significant reduction in molecular weight is realized upon exposure to reducing agents such as tris (2-carboxyethyl) phosphine (e.g., Mn = 198 kg mol-1 â 2.6 kg mol-1). By virtue of the thiol chain ends produced after disulfide cleavage, degraded oligomers can be further cycled between high and low molecular weights through oxidative repolymerization and reductive degradation. Transforming otherwise persistent poly(acrylates) into recyclable materials using simple and versatile chemistry could play a pivotal role in improving the sustainability of contemporary adhesives.
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Land surface models such as the Community Land Model Version 5 (CLM5) are essential tools for simulating the behavior of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrological parameters and how these uncertainties affect water resource applications. To address this long-standing issue, we use five meteorological datasets to conduct a comprehensive hydrological parameter uncertainty characterization of CLM5 over the hydroclimatic gradients of the conterminous United States. Key datasets produced from the uncertainty characterization experiment include: a benchmark dataset of CLM5 default hydrological performance, parameter sensitivities for 28 hydrological metrics, and large-ensemble outputs for CLM5 hydrological predictions. The presented datasets will assist CLM5 calibration and support broad applications, such as evaluating drought and flood vulnerabilities. The datasets can be used to identify the hydroclimatological conditions under which parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how hydrological prediction uncertainties interact with other Earth system processes.
Subject(s)
Hydrology , Rivers , Uncertainty , Water Resources , FloodsABSTRACT
With the exception of plants, almost all living organisms synthesize neuraminidase/sialidase. It is a one among the crucial proteins that controls how virulent a microorganism is. An essential enzyme in orthomyxoviruses and paramyxoviruses that destroys receptors is neuraminidase. It plays a number of roles throughout the viral life cycle in addition to one that involves the release of progeny virus particles. This protein is an important target for therapeutic interventions and diagnostic assays. Neuraminidase inhibitors effectively prevent the spread of disease and viral infection. Sensitive, quick, and inexpensive high throughput assays are needed to screen for specific neuraminidase inhibitory chemicals. To characterize the neuraminidase catalytic activity, however, the traditional assays are still the most common in laboratories. This review gives a brief overview of these neuraminidase assays and recent, innovative developments, particularly those involving biosensors.
Subject(s)
Neuraminidase , Orthomyxoviridae , Animals , Humans , Antiviral Agents , Enzyme Inhibitors/pharmacology , Enzyme Inhibitors/chemistry , GuanidinesABSTRACT
CONTEXT: Non-alcoholic fatty liver disease (NAFLD) is considered a potential independent risk factor for cardiovascular disease. Increased carotid intima-media thickness (CIMT) is a sign of early atherosclerosis and is linked to an increased risk of myocardial infarction, stroke, and peripheral vascular disease. AIM: To study correlation between CIMT and NAFLD and its association with increase in grades of NAFLD. Material and Study Design: An observational case control study of 40 cases and 40 controls (age and sex matched) was done. The difference of CIMT between the two groups was analysed. CIMT was also measured among the various grades of NAFLD cases. MATERIALS AND METHODS: 40 cases with NAFLD and 40 controls falling within the age group of 18-45 years were taken in the study. Patients with history of significant alcohol consumption, acute or chronic liver disease, diabetes mellitus, hypertension, malignancy, hypothyroidism and having dyslipidaemia, CAD and stroke were excluded from the study. All the subjects underwent abdominal and carotid ultrasound in order to assess NAFLD and CIMT measurement. The left and right common carotid artery was examined using PHILIPS HD11XE high-definition ultrasound system equipped with a 3-12 MHz linear array transducer in B mode. OBSERVATION AND RESULTS: There was a statistically significant difference between the 2 groups in terms of CIMT with a p value of <0.001. The mean CIMT in the Case group was 0.86 mm while in Control group was 0.52 mm. There was a significant difference between the 3 Grades of NAFLD in terms of CIMT with a p value of <0.001 with maximum CIMT being in Grade 3 of NAFLD. Body Mass Index, Alanine Transaminase, Aspartate Transaminase, Alkaline Phosphatase, Total Cholesterol, Triglycerides, Low Density Lipoprotein were also found to have statistical significant difference between cases and controls. Age, gender, Blood pressure, Fasting Blood Sugar, HbA1c, Hemoglobin, Total leucocyte Count, Platelet count, Serum Bilirubin, Total protein and Albumin were found to be statistically insignificantly different between cases and controls. CONCLUSION: CIMT is increased in NAFLD patients. Increase in CIMT is significantly correlated with increasing grades of NAFLD. Hence CIMT can be used as screening tests in NALFD patients to assess cardiovascular risks.
Subject(s)
Myocardial Infarction , Non-alcoholic Fatty Liver Disease , Stroke , Adolescent , Adult , Carotid Arteries/diagnostic imaging , Carotid Intima-Media Thickness , Case-Control Studies , Humans , Middle Aged , Myocardial Infarction/complications , Non-alcoholic Fatty Liver Disease/complications , Non-alcoholic Fatty Liver Disease/diagnostic imaging , Risk Factors , Stroke/complications , Young AdultABSTRACT
How homeostatic ER calcium fluxes shape cellular calcium signals is still poorly understood. Here we used dual-color calcium imaging (ER-cytosol) and transcriptome analysis to link candidates of the calcium toolkit of astrocytes with homeostatic calcium signals. We found molecular and pharmacological evidence that P/Q-type channel Cacna1a contributes to depolarization-dependent calcium entry in astrocytes. For stimulated ER calcium release, the cells express the phospholipase Cb3, IP3 receptors Itpr1 and Itpr2, but no ryanodine receptors (Ryr1-3). After IP3-induced calcium release, Stim1/2 - Orai1/2/3 most likely mediate SOCE. The Serca2 (Atp2a2) is the candidate for refilling of the ER calcium store. The cells highly express adenosine receptor Adora1a for IP3-induced calcium release. Accordingly, adenosine induces fast ER calcium release and subsequent ER calcium oscillations. After stimulation, calcium refilling of the ER depends on extracellular calcium. In response to SOCE, astrocytes show calcium-induced calcium release, notably even after ER calcium was depleted by extracellular calcium removal in unstimulated cells. In contrast, spontaneous ER-cytosol calcium oscillations were not fully dependent on extracellular calcium, as ER calcium oscillations could persist over minutes in calcium-free solution. Additionally, cell-autonomous calcium oscillations show a second-long spatial and temporal delay in the signal dynamics of ER and cytosolic calcium. Our data reveal a rather strong contribution of homeostatic calcium fluxes in shaping IP3-induced and calcium-induced calcium release as well as spatiotemporal components of intracellular calcium oscillations.
Subject(s)
Calcium Signaling , Calcium , Astrocytes/metabolism , Calcium/metabolism , Cytosol/metabolism , Homeostasis , ORAI1 Protein/metabolism , Stromal Interaction Molecule 1/metabolismABSTRACT
Emerging pathogens have been an eternal threat to mankind. In a series of pandemics caused by notorious coronaviruses, a newly emerged SARS-CoV2 virus is creating panic among the world population. The unavailability of reliable theranostics insists the exploration of antigenic determinants in spike glycoprotein of SARS-CoV2. The four novel inserts ('70VSGTNGT76', '150KSWM153', 247SYLTPG252 and 674QTQTNSPRR682) in SARS-CoV2 spike protein were unraveled via multiple sequence alignment of spike proteins of SARS-CoV2, SARS-CoV, and MERS-CoV. The three-dimension (3D) modeling of the spike protein of the SARS-CoV2 and their interaction with the ACE2 receptor was delineated with the help of SWISS-MODEL and 3DLigandSite web servers. The predicted 3D model of SARS-CoV2 was further verified by SAVES, RAMPAGE, and ProSA-web tools. The potential B-cell immunogenic epitopes of SARS-CoV2 were predicted out by using various software viz. IEDB B-cell epitopes prediction tool, BepiPred linear epitope prediction tool, Emini Surface Accessibility Prediction tool, and Kolaskar-Tongaonkar antigenicity web tool. The five epitopes (i.e. '71SGTNGTKRFDN81, 247SYLTPG252, 634RVYST638, 675QTQTNSPRRARSV687, and 1054QSAPH1058) were selected as potent antigenic determinants. The quantum of information generated by this study will prove beneficial for the development of effective therapeutics, diagnostics, and multi-epitopic vaccines to combat this ongoing menace.
ABSTRACT
8-Hydroxyquinoline (8-HQ) is a significant heterocyclic scaffold in organic and analytical chemistry because of the properties of chromophore and is used to detect various metal ions and anions. But from the last 2 decades, this moiety has been drawn great attention of medicinal chemists due to its significant biological activities. Synthetic modification of 8-hydroxyquinoline is under exploration on large scale to develop more potent target-based broad spectrum drug molecules for the treatment of several life-threatening diseases such as anti-cancer, HIV, neurodegenerative disorders, etc. Metal chelation properties of 8-hydroxyquinoline and its derivatives also make these potent drug candidates for the treatment of various diseases. This review comprises 8-hydroxyquinoline derivatives reported in the literature in last five years (2016-2020) and we anticipate that it will assist medicinal chemists in the synthesis of novel and pharmacologically potent agents for various therapeutic targets, mainly anti-proliferative, anti-microbial, anti-fungal and anti-viral as well as for the treatment of neurodegenerative disorders.
Subject(s)
Anti-Infective Agents/pharmacology , Antineoplastic Agents/pharmacology , Neoplasms/drug therapy , Neuroprotective Agents/pharmacology , Oxyquinoline/pharmacology , Anti-Infective Agents/chemistry , Antineoplastic Agents/chemistry , Bacteria/drug effects , Chemistry, Pharmaceutical , Fungi/drug effects , Humans , Neurodegenerative Diseases/drug therapy , Neuroprotective Agents/chemistry , Oxyquinoline/chemistry , Viruses/drug effectsABSTRACT
Bioimage analysis of fluorescent labels is widely used in the life sciences. Recent advances in deep learning (DL) allow automating time-consuming manual image analysis processes based on annotated training data. However, manual annotation of fluorescent features with a low signal-to-noise ratio is somewhat subjective. Training DL models on subjective annotations may be instable or yield biased models. In turn, these models may be unable to reliably detect biological effects. An analysis pipeline integrating data annotation, ground truth estimation, and model training can mitigate this risk. To evaluate this integrated process, we compared different DL-based analysis approaches. With data from two model organisms (mice, zebrafish) and five laboratories, we show that ground truth estimation from multiple human annotators helps to establish objectivity in fluorescent feature annotations. Furthermore, ensembles of multiple models trained on the estimated ground truth establish reliability and validity. Our research provides guidelines for reproducible DL-based bioimage analyses.
Research in biology generates many image datasets, mostly from microscopy. These images have to be analyzed, and much of this analysis relies on a human expert looking at the images and manually annotating features. Image datasets are often large, and human annotation can be subjective, so automating image analysis is highly desirable. This is where machine learning algorithms, such as deep learning, have proven to be useful. In order for deep learning algorithms to work first they have to be 'trained'. Deep learning algorithms are trained by being given a training dataset that has been annotated by human experts. The algorithms extract the relevant features to look out for from this training dataset and can then look for these features in other image data. However, it is also worth noting that because these models try to mimic the annotation behavior presented to them during training as well as possible, they can sometimes also mimic an expert's subjectivity when annotating data. Segebarth, Griebel et al. asked whether this was the case, whether it had an impact on the outcome of the image data analysis, and whether it was possible to avoid this problem when using deep learning for imaging dataset analysis. For this research, Segebarth, Griebel et al. used microscopy images of mouse brain sections, where a protein called cFOS had been labeled with a fluorescent tag. This protein typically controls the rate at which DNA information is copied into RNA, leading to the production of proteins. Its activity can be influenced experimentally by testing the behaviors of mice. Thus, this experimental manipulation can be used to evaluate the results of deep learning-based image analyses. First, the fluorescent images were interpreted manually by a group of human experts. Then, their results were used to train a large variety of deep learning models. Models were trained either on the results of an individual expert or on the results pooled from all experts to come up with a consensus model, a deep learning model that learned from the personal annotation preferences of all experts. This made it possible to test whether training a model on multiple experts reduces the risk of subjectivity. As the training of deep learning models is random, Segebarth, Griebel et al. also tested whether combining the predictions from multiple models in a so-called model ensemble improves the consistency of the analyses. For evaluation, the annotations of the deep learning models were compared to those of the human experts, to ensure that the results were not influenced by the subjective behavior of one person. The results of all bioimage annotations were finally compared to the experimental results from analyzing the mice's behaviors in order to check whether the models were able to find the behavioral effect on cFOS. Segebarth, Griebel et al. concluded that combining the expert knowledge of multiple experts reduces the subjectivity of bioimage annotation by deep learning algorithms. Combining such consensus information in a group of deep learning models improves the quality of bioimage analysis, so that the results are reliable, transparent and less subjective.
Subject(s)
Image Processing, Computer-Assisted/methods , Animals , Deep Learning , Fear , Fluorescent Dyes , Male , Mice , Reproducibility of Results , Signal-To-Noise Ratio , ZebrafishABSTRACT
The WHO Integrated Management of Childhood Illnesses-HIV (IMCI-HIV) algorithm and its regional adaptation have shown variable performance in clinically identifying HIV-infected children with lack of validation in low prevalence areas. Addition of certain 'parental factors' (proxy indicators of parental HIV) may improve its utility. In this study, children aged 2 months to 5 years were enrolled into Group A (n = 1000, 'suspected symptomatic HIV infected' children as per the IMNCI-HIV algorithm) and group B (n = 50, children newly diagnosed with HIV infection). Parental factors were asked and HIV infection was tested for in Group A. For Group B, retrospective data were collected regarding IMNCI-HIV algorithm signs and parental factors. Utility of individual and various combinations of IMNCI-HIV signs and parental factors to predict HIV status was evaluated. Results showed that incorporating parental factors to IMNCI-HIV algorithm improved its sensitivity and positive predictive value in identifying HIV-infected children while maintaining the same sensitivity.
Subject(s)
Child Health Services/organization & administration , Delivery of Health Care, Integrated/methods , HIV Infections/diagnosis , Infectious Disease Transmission, Vertical/statistics & numerical data , Parents , Primary Health Care/methods , Adult , Algorithms , Child , Child, Preschool , Female , HIV Infections/epidemiology , HIV Infections/therapy , Humans , India/epidemiology , Infant , Infectious Disease Transmission, Vertical/prevention & control , Male , Retrospective StudiesABSTRACT
Colloidal particles at complex fluid interfaces and within films assemble to form ordered structures with high degrees of symmetry via interactions that include capillarity, elasticity, and other fields like electrostatic charge. Here we study microparticle interactions within free-standing smectic-A films, in which the elasticity arising from the director field distortion and capillary interactions arising from interface deformation compete to direct the assembly of motile particles. New colloidal assemblies and patterns, ranging from 1D chains to 2D aggregates, sensitive to the initial wetting conditions of particles at the smectic film, are reported. This work paves the way to exploiting LC interfaces as a means to direct spontaneously formed, reconfigurable, and optically active materials.
ABSTRACT
BACKGROUND: Children living with HIV (CLHIV) commonly experience growth failure. We report growth parameters in CLHIV at baseline and during 3 years of antiretroviral therapy (ART). METHODS: Records of CLHIV who had completed at least 3 years on ART were reviewed after excluding subjects who died, were lost to follow-up or developed treatment failure to assess impact of sustained administration of ART. Height-for-age (HFA) and body mass index for age (BFA) Z scores were calculated, and proportion of CLHIV with wasting and stunting estimated at baseline, 6, 12, 24 and 36 months after starting ART using the linear mixed model. Factors influencing significant changes in growth parameters were assessed. RESULTS: HFA Z score improved steadily from -3.12 at baseline to -2.33 at 36 months of ART. The prevalence of stunting declined from 77.7% to 59.2% during this period. BFA Z scores improved from -1.2 at baseline to -0.4 at12 months on ART but declined to -1.0 at 36 months. The proportion of subjects with wasting was 29.3%, 9.7% and 16.7% at baseline, 12 and 36 months, respectively. Baseline clinical stage (1 + 2), absence of wasting and lower HFA Z score had significant positive influence on changes in HFA Z score, while younger age at ART initiation and a low baseline BFA Z score had a positive influence on catch-up in body mass index. Including data of children who died or developed treatment failure did not impact upon the results. CONCLUSION: Majority of CLHIV are stunted at the start of ART. ART was only partially effective in countering malnutrition and growth failure in CLHIV.