High-throughput screening of encapsulated islets using wide-field lens-free on-chip imaging

Islet microencapsulation is a promising solution to diabetes treatment, but its quality control based on manual microscopic inspection is extremely low-throughput, highly variable and laborious. This study presents a high-throughput islet-encapsulation quality screening system based on lens-free on-chip imaging with a wide field-of-view of 18.15 cm^2, which is more than 100 times larger than that of a lens-based optical microscope, enabling it to image and analyze ~8,000 microcapsules in a single frame. Custom-written image reconstruction and processing software provides the user with clinically important information, such as microcapsule count, size, intactness, and information on whether each capsule contains an islet. This high-throughput and cost-effective platform can be useful for researchers to develop better encapsulation protocols as well as perform quality control prior to transplantation

A mathematical framework for combining decisions of multiple experts toward accurate and remote diagnosis of malaria using tele-microscopy.

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing 'slide-level' diagnosis by using individual 'cell-level' diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform

Misclassification Risk and Uncertainty Quantification in Deep Classifiers

In this paper, we propose risk-calibrated evidential deep classifiers to reduce the costs associated with classification errors. We use two main approaches. The first is to develop methods to quantify the uncertainty of a classifier’s predictions and reduce the likelihood of acting on erroneous predictions. The second is a novel way to train the classifier such that erroneous classifications are biased towards less risky categories. We combine these two approaches in a principled way. While doing this, we extend evidential deep learning with pignistic probabilities, which are used to quantify uncertainty of classification predictions and model rational decision making under uncertainty.We evaluate the performance of our approach on several image classification tasks. We demonstrate that our approach allows to (i) incorporate misclassification cost while training deep classifiers, (ii) accurately quantify the uncertainty of classification predictions, and (iii) simultaneously learn how to make classification decisions to minimize expected cost of classification errors

Multi-spectral Vascular Oximetry of Rat Dorsal Spinal Cord

No abstract available

Lateral flow test engineering and lessons learned from COVID-19

The acceptability and feasibility of large-scale testing with lateral flow tests (LFTs) for clinical and public health purposes has been demonstrated during the COVID-19 pandemic. LFTs can detect analytes in a variety of samples, providing a rapid read-out, which allows self-testing and decentralized diagnosis. In this Review, we examine the changing LFT landscape with a focus on lessons learned from COVID-19. We discuss the implications of LFTs for decentralized testing of infectious diseases, including diseases of epidemic potential, the ‘silent pandemic’ of antimicrobial resistance, and other acute and chronic infections. Bioengineering approaches will play a key part in increasing the sensitivity and specificity of LFTs, improving sample preparation, incorporating nucleic acid amplification and detection, and enabling multiplexing, digital connection and green manufacturing, with the aim of creating the next generation of high-accuracy, easy-to-use, affordable and digitally connected LFTs. We conclude with recommendations, including the building of a global network of LFT research and development hubs to facilitate and strengthen future diagnostic resilience

Reactive Molecular Dynamics study on the first steps of DNA-damage by free hydroxyl radicals

We employ a large scale molecular simulation based on bond-order ReaxFF to simulate the chemical reaction and study the damage to a large fragment of DNA-molecule in the solution by ionizing radiation. We illustrate that the randomly distributed clusters of diatomic OH-radicals that are primary products of megavoltage ionizing radiation in water-based systems are the main source of hydrogen-abstraction as well as formation of carbonyl- and hydroxyl-groups in the sugar-moiety that create holes in the sugar-rings. These holes grow up slowly between DNA-bases and DNA-backbone and the damage collectively propagate to DNA single and double strand break.Comment: 6 pages and 8 figures. movies and simulations are available at: http://qmsimulator.wordpress.com

New Mediterranean Biodiversity Records (July 2015)

The Collective Article ‘New Mediterranean Biodiversity Records’ of the Mediterranean Marine Science journal offers the means to publish biodiversity records in the Mediterranean Sea. The current article is divided in two parts, for records of native and alien species respectively. The new records of native species include: the neon flying squid Ommastrephes bartramii in Capri Island, Thyrrenian Sea; the bigeye thresher shark Alopias superciliosus in the Adriatic Sea; a juvenile basking shark Cetorhinus maximus caught off Piran (northern Adriatic); the deep-sea Messina rockfish Scorpaenodes arenai in the National Marine Park of Zakynthos (East Ionian Sea, Greece); and the oceanic puffer Lagocephalus lagocephalus in the Adriatic Sea.The new records of alien species include: the red algae Antithamnionella elegans and Palisada maris-rubri, found for the first time in Israel and Greece respectively; the green alga Codium parvulum reported from Turkey (Aegean Sea); the first record of the alien sea urchin Diadema setosum in Greece; the nudibranch Goniobranchus annulatus reported from South-Eastern Aegean Sea (Greece); the opisthobranch Melibe viridis found in Lebanon; the new records of the blue spotted cornetfish Fistularia commersonii in the Alicante coast (Eastern Spain); the alien fish Siganus luridus and Siganus rivulatus in Lipsi Island, Dodecanese (Greece); the first record of Stephanolepis diaspros from the Egadi Islands Marine Protected Area (western Sicily); a northward expansion of the alien pufferfish Torquigener flavimaculosus along the southeastern Aegean coasts of Turkey; and data on the occurrence of the Lessepsian immigrants Alepes djedaba, Lagocephalus sceleratus and Fistularia commersonii in Zakynthos Island (SE Ionian Sea, Greece)

Lensfree Fluorescent On-Chip Imaging of Transgenic Caenorhabditis elegans Over an Ultra-Wide Field-of-View

We demonstrate lensfree on-chip fluorescent imaging of transgenic Caenorhabditis elegans (C. elegans) over an ultra-wide field-of-view (FOV) of e.g., >2–8 cm2 with a spatial resolution of ∼10µm. This is the first time that a lensfree on-chip platform has successfully imaged fluorescent C. elegans samples. In our wide-field lensfree imaging platform, the transgenic samples are excited using a prism interface from the side, where the pump light is rejected through total internal reflection occurring at the bottom facet of the substrate. The emitted fluorescent signal from C. elegans samples is then recorded on a large area opto-electronic sensor-array over an FOV of e.g., >2–8 cm2, without the use of any lenses, thin-film interference filters or mechanical scanners. Because fluorescent emission rapidly diverges, such lensfree fluorescent images recorded on a chip look blurred due to broad point-spread-function of our platform. To combat this resolution challenge, we use a compressive sampling algorithm to uniquely decode the recorded lensfree fluorescent patterns into higher resolution images, demonstrating ∼10 µm resolution. We tested the efficacy of this compressive decoding approach with different types of opto-electronic sensors to achieve a similar resolution level, independent of the imaging chip. We further demonstrate that this wide FOV lensfree fluorescent imaging platform can also perform sequential bright-field imaging of the same samples using partially-coherent lensfree digital in-line holography that is coupled from the top facet of the same prism used in fluorescent excitation. This unique combination permits ultra-wide field dual-mode imaging of C. elegans on a chip which could especially provide a useful tool for high-throughput screening applications in biomedical research

Temporal bone verrucous carcinoma: outcomes and treatment controversy

Verrucous carcinoma is a rare tumor that presents in the head and neck with the most common sites being the oral cavity and larynx. Fourteen cases of verrucous carcinoma of the temporal bone have been described in literature; this study aims to examine treatment outcomes and discuss the controversy surrounding postoperative radiation. The study design included a literature review along with individual case report in the setting of a tertiary care medical center. Outcome analysis of all cases of verrucous carcinoma of the temporal bone, which are documented in the English literature, and presentation of a single patient report including gross, histologic and radiologic analyses were performed. The longest recorded survival for verrucous carcinoma of the temporal bone occurs in patients treated with surgery alone. Poorer outcomes for patients treated with adjuvant (chemo)radiation may be due to more advanced stage of disease at the time of treatment. Early reports of radiation leading to tumor dedifferentiation or early recurrence are not supported by more recent studies. Whether adjuvant radiation therapy is indicated in verrucous carcinoma of the temporal bone remains controversial