Engineering protein antigens to refocus the immune response

Infectious diseases continue to be a threat to millions globally – largely because of highly effective immune evasion mechanisms evolved in pathogens. Our work focuses on engineering proteins to shield selected epitopes thereby refocusing the immune response to other regions on the protein antigen. In the context of vaccine design, nanopatterning can help preferentially elicit broadly neutralizing antibodies while suppressing the response to epitopes that serve as immunological decoys. We have developed two approaches to achieve this shielding and refocusing – one referred to as “Nanopatterning” that uses site-specifically conjugated polymeric shields and a second approach that uses engineered antibody fragments (Fabs) as shielding agents. Using these tools, we have demonstrated the ability to refocus the immune response to broadly neutralizing epitopes of medically relevant antigens from diseases including Malaria, Influenza and Zika. In summary, this work explores two new approaches to achieve immunofocusing – allowing refocusing of the immune response to broadly neutralizing epitopes of protein antigens. These tools should be broadly applicable for the design of broadly protective vaccines against pathogens such as malarial parasites, influenza, flaviviruses and HIV.Ph.D

High-Throughput Workflow for Computer-Assisted Human Parsing of Biological Specimen Label Data

4th International Conference on Open RepositoriesThis presentation was part of the session : Conference PostersHundreds of thousands of specimens in herbaria and natural history museums worldwide are potential candidates for digitization, making them more accessible to researchers. An herbarium contains collections of preserved plant specimens created for scientific use. Herbarium specimens are ideal natural history objects for digitization, as the plants are pressed flat and dried, and mounted on individual sheets of paper, creating a nearly two-dimensional object. Building digital repositories of herbarium specimens can increase use and exposure of the collections while simultaneously reducing physical handling. As important as the digitized specimens are, the data contained on the associated specimen labels provide critical information about each specimen (e.g., scientific name, geographic location of specimen, etc.). The volume and heterogeneity of these printed label data present challenges in transforming them into meaningful digital form to support research. The Apiary Project is addressing these challenges by exploring and developing transformation processes in a systematic workflow that yields high-quality machine-processable label data in a cost- and time-efficient manner. The University of North Texas's Texas Center for Digital Knowledge (TxCDK) and the Botanical Research Institute of Texas (BRIT), with funding from an Institute of Museum and Library Services National Leadership Grant, are conducting fundamental research with the goal of identifying how human intelligence can be combined with machine processes for effective and efficient transformation of specimen label information. The results of this research will yield a new workflow model for effective and efficient label data transformation, correction, and enhancement.Institute of Museum and Library Services, National Leadership Gran

Machine Learning in Dentistry: A Scoping Review

Machine learning (ML) is being increasingly employed in dental research and application. We aimed to systematically compile studies using ML in dentistry and assess their methodological quality, including the risk of bias and reporting standards. We evaluated studies employing ML in dentistry published from 1 January 2015 to 31 May 2021 on MEDLINE, IEEE Xplore, and arXiv. We assessed publication trends and the distribution of ML tasks (classification, object detection, semantic segmentation, instance segmentation, and generation) in different clinical fields. We appraised the risk of bias and adherence to reporting standards, using the QUADAS-2 and TRIPOD checklists, respectively. Out of 183 identified studies, 168 were included, focusing on various ML tasks and employing a broad range of ML models, input data, data sources, strategies to generate reference tests, and performance metrics. Classification tasks were most common. Forty-two different metrics were used to evaluate model performances, with accuracy, sensitivity, precision, and intersection-over-union being the most common. We observed considerable risk of bias and moderate adherence to reporting standards which hampers replication of results. A minimum (core) set of outcome and outcome metrics is necessary to facilitate comparisons across studies

Benchmarking Deep Learning Models for Tooth Structure Segmentation.

A wide range of deep learning (DL) architectures with varying depths are available, with developers usually choosing one or a few of them for their specific task in a nonsystematic way. Benchmarking (i.e., the systematic comparison of state-of-the art architectures on a specific task) may provide guidance in the model development process and may allow developers to make better decisions. However, comprehensive benchmarking has not been performed in dentistry yet. We aimed to benchmark a range of architecture designs for 1 specific, exemplary case: tooth structure segmentation on dental bitewing radiographs. We built 72 models for tooth structure (enamel, dentin, pulp, fillings, crowns) segmentation by combining 6 different DL network architectures (U-Net, U-Net++, Feature Pyramid Networks, LinkNet, Pyramid Scene Parsing Network, Mask Attention Network) with 12 encoders from 3 different encoder families (ResNet, VGG, DenseNet) of varying depth (e.g., VGG13, VGG16, VGG19). On each model design, 3 initialization strategies (ImageNet, CheXpert, random initialization) were applied, resulting overall into 216 trained models, which were trained up to 200 epochs with the Adam optimizer (learning rate = 0.0001) and a batch size of 32. Our data set consisted of 1,625 human-annotated dental bitewing radiographs. We used a 5-fold cross-validation scheme and quantified model performances primarily by the F1-score. Initialization with ImageNet or CheXpert weights significantly outperformed random initialization (P < 0.05). Deeper and more complex models did not necessarily perform better than less complex alternatives. VGG-based models were more robust across model configurations, while more complex models (e.g., from the ResNet family) achieved peak performances. In conclusion, initializing models with pretrained weights may be recommended when training models for dental radiographic analysis. Less complex model architectures may be competitive alternatives if computational resources and training time are restricting factors. Models developed and found superior on nondental data sets may not show this behavior for dental domain-specific tasks

Deep learning for cephalometric landmark detection: systematic review and meta-analysis

Objectives: Deep learning (DL) has been increasingly employed for automated landmark detection, e.g., for cephalometric purposes. We performed a systematic review and meta-analysis to assess the accuracy and underlying evidence for DL for cephalometric landmark detection on 2-D and 3-D radiographs. Methods: Diagnostic accuracy studies published in 2015-2020 in Medline/Embase/IEEE/arXiv and employing DL for cephalometric landmark detection were identified and extracted by two independent reviewers. Random-effects meta-analysis, subgroup, and meta-regression were performed, and study quality was assessed using QUADAS-2. The review was registered (PROSPERO no. 227498). Data: From 321 identified records, 19 studies (published 2017-2020), all employing convolutional neural networks, mainly on 2-D lateral radiographs (n=15), using data from publicly available datasets (n=12) and testing the detection of a mean of 30 (SD: 25; range.: 7-93) landmarks, were included. The reference test was established by two experts (n=11), 1 expert (n=4), 3 experts (n=3), and a set of annotators (n=1). Risk of bias was high, and applicability concerns were detected for most studies, mainly regarding the data selection and reference test conduct. Landmark prediction error centered around a 2-mm error threshold (mean; 95% confidence interval: (-0.581; 95 CI: -1.264 to 0.102 mm)). The proportion of landmarks detected within this 2-mm threshold was 0.799 (0.770 to 0.824). Conclusions: DL shows relatively high accuracy for detecting landmarks on cephalometric imagery. The overall body of evidence is consistent but suffers from high risk of bias. Demonstrating robustness and generalizability of DL for landmark detection is needed. Clinical significance: Existing DL models show consistent and largely high accuracy for automated detection of cephalometric landmarks. The majority of studies so far focused on 2-D imagery; data on 3-D imagery are sparse, but promising. Future studies should focus on demonstrating generalizability, robustness, and clinical usefulness of DL for this objective

Kupffer Cells and Blood Monocytes Orchestrate the Clearance of Iron-Carbohydrate Nanoparticles from Serum.

Intravenous (IV) iron nanoparticle preparations are widely used to treat iron deficiency. The mechanism of mononuclear phagocyte system-mediated clearance of IV iron nanoparticles is unknown. The early uptake and homeostasis of iron after injection of ferric carboxymaltose (FCM) in mice was studied. An increase in serum iron was observed at 2.5 h followed by a return to baseline by 24 h. An increase in circulating monocytes was observed, particularly Ly6Chi and Ly6Clow. FCM was also associated with a time-dependent decrease in liver Kupffer cells (KCs) and increase in liver monocytes. The increase in liver monocytes suggests an influx of iron-rich blood monocytes, while some KCs underwent apoptosis. Adoptive transfer experiments demonstrated that following liver infiltration, blood monocytes differentiated to KCs. KCs were also critical for IV iron uptake and biodegradation. Indeed, anti-Colony Stimulating Factor 1 Receptor (CSF1R)-mediated depletion of KCs resulted in elevated serum iron levels and impaired iron uptake by the liver. Gene expression profiling indicated that C-C chemokine receptor type 5 (CCR5) might be involved in monocyte recruitment to the liver, confirmed by pharmaceutical inhibition of CCR5. Liver KCs play a pivotal role in the clearance and storage of IV iron and KCs appear to be supported by the expanded blood monocyte population

Expert consensus on the management of acne in India

Acne, a common cutaneous disorder, is estimated to affect a significant proportion of the population at some point in their lifetime. It is one of the most common presentations reported in dermatological consultations in India. Treatment options for acne include topical, oral and procedural therapies. Patients with mild acne can be treated with topical therapies; however, those with moderate to severe acne require systemic cure. Oral antibiotic treatment, hormonal therapies and isotretinoin are the mainstay systemic therapies for acne. Additionally, procedural therapeutic modalities in dermatology include chemical peels, laser therapy, micro needling techniques, to name a few. Scientific advances are continually improving knowledge of acne and contributing to refinement of treatment options. Hence, it is vital for clinicians to regularly update their clinical practice patterns to reflect current standard. An experts’ panel discussion involving dermatologists from across India was conducted, to outline a practical approach for the management of acne. The present consensus document focuses on the assessment of acne, use of topical treatments, role of systemic therapy and procedures in treating acne and post-inflammatory hyperpigmentation. It also emphasizes the role of patient education and counselling on prophylactic and treatment strategies in acne management

Effect of low voltage AC fields on cardiovascular implants

Coronary Artery Stents have been the preferred form of treatment for vascular occlusive disease, due to the minimally invasive surgical procedure, post-operative recovery time and cost, when compared to open coronary bypass surgery. The cellular response upon applying an AC electric field to type 316LM Stainless Steel stent mimics was investigated in this paper. The highest RBC adhesion was observed at voltages higher than 88 mV and lower than 74mV. Their unique alignment along the lines of fracture on the stent surface at 88 mV was a phenomenon caused by an increase in electrical conductivity in these regions. Being able to control RBC adhesion may have various clinical implications such as inhibition of thrombus formation, and provide a basis to analyse whether electric fields may be applied to cancer therapy as well

Design and testing of hydrophobic core/hydrophilic shell nano/micro particles for drug-eluting stent coating

In this study, we designed a novel drug-eluting coating for vascular implants consisting of a core coating of the anti-proliferative drug docetaxel (DTX) and a shell coating of the platelet glycoprotein IIb/IIIa receptor monoclonal antibody SZ-21. The core/shell structure was sprayed onto the surface of 316L stainless steel stents using a coaxial electrospray process with the aim of creating a coating that exhibited a differential release of the two drugs. The prepared stents displayed a uniform coating consisting of nano/micro particles. In vitro drug release experiments were performed, and we demonstrated that a biphasic mathematical model was capable of capturing the data, indicating that the release of the two drugs conformed to a diffusion-controlled release system. We demonstrated that our coating was capable of inhibiting the adhesion and activation of platelets, as well as the proliferation and migration of smooth muscle cells (SMCs), indicating its good biocompatibility and anti-proliferation qualities. In an in vivo porcine coronary artery model, the SZ-21/DTX drug-loaded hydrophobic core/hydrophilic shell particle coating stents were observed to promote re-endothelialization and inhibit neointimal hyperplasia. This core/shell particle-coated stent may serve as part of a new strategy for the differential release of different functional drugs to sequentially target thrombosis and in-stent restenosis during the vascular repair process and ensure rapid re-endothelialization in the field of cardiovascular disease

The Sirt1 activator SRT3025 provides atheroprotection in Apoe−/− mice by reducing hepatic Pcsk9 secretion and enhancing Ldlr expression

Aims The deacetylase sirtuin 1 (Sirt1) exerts beneficial effects on lipid metabolism, but its roles in plasma LDL-cholesterol regulation and atherosclerosis are controversial. Thus, we applied the pharmacological Sirt1 activator SRT3025 in a mouse model of atherosclerosis and in hepatocyte culture. Methods and results Apolipoprotein E-deficient (Apoe−/−) mice were fed a high-cholesterol diet (1.25% w/w) supplemented with SRT3025 (3.18 g kg−1 diet) for 12 weeks. In vitro, the drug activated wild-type Sirt1 protein, but not the activation-resistant Sirt1 mutant; in vivo, it increased deacetylation of hepatic p65 and skeletal muscle Foxo1. SRT3025 treatment decreased plasma levels of LDL-cholesterol and total cholesterol and reduced atherosclerosis. Drug treatment did not change mRNA expression of hepatic LDL receptor (Ldlr) and proprotein convertase subtilisin/kexin type 9 (Pcsk9), but increased their protein expression indicating post-translational effects. Consistent with hepatocyte Ldlr and Pcsk9 accumulation, we found reduced plasma levels of Pcsk9 after pharmacological Sirt1 activation. In vitro administration of SRT3025 to cultured AML12 hepatocytes attenuated Pcsk9 secretion and its binding to Ldlr, thereby reducing Pcsk9-mediated Ldlr degradation and increasing Ldlr expression and LDL uptake. Co-administration of exogenous Pcsk9 with SRT3025 blunted these effects. Sirt1 activation with SRT3025 in Ldlr−/− mice reduced neither plasma Pcsk9, nor LDL-cholesterol levels, nor atherosclerosis. Conclusion We identify reduction in Pcsk9 secretion as a novel effect of Sirt1 activity and uncover Ldlr as a prerequisite for Sirt1-mediated atheroprotection in mice. Pharmacological activation of Sirt1 appears promising to be tested in patients for its effects on plasma Pcsk9, LDL-cholesterol, and atherosclerosi