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1. A high-throughput method to deliver targeted optogenetic stimulation to moving C. elegans populations

   https://doi.org/10.1371/journal.pbio.3001524  

   Liu, Mochi; Kumar, Sandeep; Sharma, Anuj K.; Leifer, Andrew M. (January 2022, PLOS Biology)

   Sengupta, Piali (Ed.)

   We present a high-throughput optogenetic illumination system capable of simultaneous closed-loop light delivery to specified targets in populations of moving Caenorhabditis elegans . The instrument addresses three technical challenges: It delivers targeted illumination to specified regions of the animal’s body such as its head or tail; it automatically delivers stimuli triggered upon the animal’s behavior; and it achieves high throughput by targeting many animals simultaneously. The instrument was used to optogenetically probe the animal’s behavioral response to competing mechanosensory stimuli in the the anterior and posterior gentle touch receptor neurons. Responses to more than 43,418 stimulus events from a range of anterior–posterior intensity combinations were measured. The animal’s probability of sprinting forward in response to a mechanosensory stimulus depended on both the anterior and posterior stimulation intensity, while the probability of reversing depended primarily on the anterior stimulation intensity. We also probed the animal’s response to mechanosensory stimulation during the onset of turning, a relatively rare behavioral event, by delivering stimuli automatically when the animal began to turn. Using this closed-loop approach, over 9,700 stimulus events were delivered during turning onset at a rate of 9.2 events per worm hour, a greater than 25-fold increase in throughput compared to previous investigations. These measurements validate with greater statistical power previous findings that turning acts to gate mechanosensory evoked reversals. Compared to previous approaches, the current system offers targeted optogenetic stimulation to specific body regions or behaviors with many fold increases in throughput to better constrain quantitative models of sensorimotor processing. 

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2. Ultradeep sequencing differentiates patterns of skin clonal mutations associated with sun-exposure status and skin cancer burden

   https://doi.org/10.1126/sciadv.abd7703  

   Wei, Lei; Christensen, Sean R.; Fitzgerald, Megan E.; Graham, James; Hutson, Nicholas D.; Zhang, Chi; Huang, Ziyun; Hu, Qiang; Zhan, Fenglin; Xie, Jun; et al (January 2021, Science Advances)

   null (Ed.)

   In ultraviolet (UV) radiation–exposed skin, mutations fuel clonal cell growth. The relationship between UV exposure and the accumulation of clonal mutations (CMs) and the correlation between CMs and skin cancer risk are largely unexplored. We characterized 450 individual-matched sun-exposed (SE) and non-SE (NE) normal human skin samples. The number and relative contribution of CMs were significantly different between SE and NE areas. Furthermore, we identified hotspots in TP53 , NOTCH1 , and GRM3 where mutations were significantly associated with UV exposure. In the normal skin from patients with cutaneous squamous cell carcinoma, we found that the cancer burden was associated with the UV-induced mutations, with the difference mostly conferred by the low-frequency CMs. These findings provide previously unknown information on UV’s carcinogenic effect and pave the road for future development of quantitative assessment of subclinical UV damage and skin cancer risk. 

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3. Numerical Modeling of Plasma Assisted Pyrolysis and Combustion of Ammonia

   https://doi.org/10.2514/6.2021-1972  

   Taneja, Taaresh Sanjeev; Yang, Suo (January 2021, AIAA Scitech 2021 Forum)

   This work aims at studying the combustion and pyrolysis characteristics of ammonia (NH3) using non-equilibrium plasma. The well known challenges of ammonia combustion and the advantages of using non-equilibrium plasma are discussed using results of zero-dimensional and one-dimensional coupled simulations. Periodic nanosecond pulsed discharges of plasma are interspersed with microsecond gaps of combustion to assess the assistance provided by plasma on overall combustion characteristics of ammonia fuel, such as ignition delay and flammability limit. Due to the lack of a reliable plasma mechanism for ammonia, a validated plasma kinetic mechanism of methane and oxygen is transformed to that of ammonia and oxygen, and is coupled with an experimentally validated ammonia combustion mechanism in this work. Another NH3 / O2 / He plasma mechanism that was recently assembled and published is also used to study the discharge and inter-pulse kinetics. A 0D model is developed to compute the rates of the electron impact reactions during the discharge, and ion-electron recombination reactions and quenching reactions along with the combustion reactions during the gap. Finally, the species concentrations and temperatures from this model are compared with those obtained using a detailed 1D model which solves for the transient electric field in addition to the species concentrations and temperature. 

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4. Biopsy-free virtual histology to discriminate benign from malignant squamous neoplasms

   Kokikian, N; Wahhab, R; Li, J; Martin, S; Beynet, D; Ozcan, A; Scumpia, P (April 2024, American Association for Cancer Research (AACR) Annual Meeting)

   Reflectance confocal microscopy (RCM) is a noninvasive optical imaging modality that allows for cellular-level resolution, in vivo images of skin without performing a traditional skin biopsy. RCM image interpretation currently requires specialized training to interpret the grayscale output images that are difficult to correlate with tissue pathology. Here, we use a deep learning-based framework that uses a convolutional neural network to transform grayscale output images into virtually-stained hematoxylin and eosin (H&E)-like images allowing for the visualization of various skin layers, including the epidermis, dermal-epidermal junction, and superficial dermis layers. To train the deep-learning framework, a stack of a minimum of 7 time-lapsed, successive RCM images of excised tissue were obtained from epidermis to dermis 1.52 microns apart to a depth of 60.96 microns using the Vivascope 3000. The tissue was embedded in agarose tissue and a curette was used to create a tunnel through which drops of 50% acetic acid was used to stain cell nuclei. These acetic acid-stained images were used as “ground truth” to train a deep convolutional neural network using a conditional generative adversarial network (GAN)-based machine learning algorithm to digitally convert the images into GAN-based H&E-stained digital images. We used the already trained machine learning algorithm and retrained the algorithm with new samples to include squamous neoplasms. Through further training and refinement of the algorithm, high-resolution, histological quality images can be obtained to aid in earlier diagnosis and treatment of cutaneous neoplasms. The overall goal of obtaining biopsy-free virtual histology images with this technology can be used to provide real-time outputs of virtually-stained H&E skin lesions, thus decreasing the need for invasive diagnostic procedures and enabling greater uptake of the technology by the medical community. 

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5. Insights on cold plasma ammonia synthesis and decomposition using alkaline earth metal-based perovskites

   https://doi.org/DOI: 10.1039/d1cy00729g  

   Fnu Gorky; Jolie M. Lucero; James M. Crawford, b Beth (October 2021, Catalysis science technology)

   The synergistic combination of solid catalysts and plasma for the synthesis of ammonia has recently attracted considerable scientific interest. Herein, we explore MgTiO3, CaTiO3, SrTiO3, and BaTiO3 perovskites as effective catalysts for the synthesis and decomposition of ammonia via cold plasma. MgTiO3 perovskite, which contains the most electronegative alkaline metal of all the studied perovskites, resulted in the highest ammonia synthesis rate with a value of 12.16 μmol min−1 m−2, which is around 50 times the value of only plasma, 0.24 μmol min−1. The high electronegativity of Mg can be assisting the dissociation of the triple nitrogen covalent bond. This intrinsic property of Mg perovskite added to the homogeneity of the plasma arising from the dielectric constant value of this perovskite might be synergistically responsible for the high ammonia synthesis rate observed. Interestingly, ammonia production over MgTiO3 perovskite is almost double the performance of traditional oxides and some microporous crystals. We also explored the ammonia decomposition reaction due to the possibility of the importance of the reversible reaction owing to the electron collision with the ammonia molecules formed. Ammonia decomposition increased as plasma power increased. This points out the benefit of running at low plasma power and the need to design plasma reactors where the newly formed ammonia molecules can be removed from the reaction system to avoid further electron collision. The highest ammonia decomposition yield was 44.37% at 20 W corresponding to an energy yield of 5.06 g-NH3 kW h−1. 

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