In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level.

The mouse embryo has long been central to the study of mammalian development; however, elucidating the cell behaviors governing gastrulation and the formation of tissues and organs remains a fundamental challenge. A major obstacle is the lack of live imaging and image analysis technologies capable of systematically following cellular dynamics across the developing embryo. We developed a light-sheet microscope that adapts itself to the dramatic changes in size, shape, and optical properties of the post-implantation mouse embryo and captures its development from gastrulation to early organogenesis at the cellular level. We furthermore developed a computational framework for reconstructing long-term cell tracks, cell divisions, dynamic fate maps, and maps of tissue morphogenesis across the entire embryo. By jointly analyzing cellular dynamics in multiple embryos registered in space and time, we built a dynamic atlas of post-implantation mouse development that, together with our microscopy and computational methods, is provided as a resource. VIDEO ABSTRACT.

Connectome-constrained networks predict neural activity across the fly visual system.

We can now measure the connectivity of every neuron in a neural circuit1-9, but we cannot measure other biological details, including the dynamical characteristics of each neuron. The degree to which measurements of connectivity alone can inform the understanding of neural computation is an open question10. Here we show that with experimental measurements of only the connectivity of a biological neural network, we can predict the neural activity underlying a specified neural computation. We constructed a model neural network with the experimentally determined connectivity for 64 cell types in the motion pathways of the fruit fly optic lobe1-5 but with unknown parameters for the single-neuron and single-synapse properties. We then optimized the values of these unknown parameters using techniques from deep learning11, to allow the model network to detect visual motion12. Our mechanistic model makes detailed, experimentally testable predictions for each neuron in the connectome. We found that model predictions agreed with experimental measurements of neural activity across 26 studies. Our work demonstrates a strategy for generating detailed hypotheses about the mechanisms of neural circuit function from connectivity measurements. We show that this strategy is more likely to be successful when neurons are sparsely connected-a universally observed feature of biological neural networks across species and brain regions.

Local shape descriptors for neuron segmentation.

We present an auxiliary learning task for the problem of neuron segmentation in electron microscopy volumes. The auxiliary task consists of the prediction of local shape descriptors (LSDs), which we combine with conventional voxel-wise direct neighbor affinities for neuron boundary detection. The shape descriptors capture local statistics about the neuron to be segmented, such as diameter, elongation, and direction. On a study comparing several existing methods across various specimen, imaging techniques, and resolutions, auxiliary learning of LSDs consistently increases segmentation accuracy of affinity-based methods over a range of metrics. Furthermore, the addition of LSDs promotes affinity-based segmentation methods to be on par with the current state of the art for neuron segmentation (flood-filling networks), while being two orders of magnitudes more efficient-a critical requirement for the processing of future petabyte-sized datasets.

Deep learning enables fast and dense single-molecule localization with high accuracy.

Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but standard analysis algorithms require sparse emitters, which limits imaging speed and labeling density. Here, we overcome this major limitation using deep learning. We developed DECODE (deep context dependent), a computational tool that can localize single emitters at high density in three dimensions with highest accuracy for a large range of imaging modalities and conditions. In a public software benchmark competition, it outperformed all other fitters on 12 out of 12 datasets when comparing both detection accuracy and localization error, often by a substantial margin. DECODE allowed us to acquire fast dynamic live-cell SMLM data with reduced light exposure and to image microtubules at ultra-high labeling density. Packaged for simple installation and use, DECODE will enable many laboratories to reduce imaging times and increase localization density in SMLM.

Automatic detection of synaptic partners in a whole-brain Drosophila electron microscopy data set.

We develop an automatic method for synaptic partner identification in insect brains and use it to predict synaptic partners in a whole-brain electron microscopy dataset of the fruit fly. The predictions can be used to infer a connectivity graph with high accuracy, thus allowing fast identification of neural pathways. To facilitate circuit reconstruction using our results, we develop CIRCUITMAP, a user interface add-on for the circuit annotation tool CATMAID.

Assessment of cutaneous disease activity in early lupus and its correlation with quality of life: a cross-sectional study.

Systemic lupus erythematosus (SLE) is a multi-system autoimmune disease with varied dermatological manifestations that are almost universal. Overall, lupus disease has a major effect on the quality of life in these patients. We assessed the extent of cutaneous disease in early lupus and correlated it with the SLE quality-of-life (SLEQoL) index and disease activity measures. Patients diagnosed as SLE with the skin involved were recruited at the first presentation and were assessed for cutaneous and systemic disease activity using the cutaneous lupus erythematosus disease area and severity index (CLASI) and the Mexican-SLE disease activity index (Mex-SLEDAI), respectively. Quality of life was assessed with the SLEQoL tool while systemic damage was captured by the SLICC damage index. Fifty-two patients with SLE who had cutaneous involvement were enrolled (40, 76.9% females) with a median disease duration of 1 month (1-3.7). The median age was 27.5 years (IQR: 20-41). Median Mex-SLEDAI and SLICC damage index were 8(IQR: 4.5-11) and 0 (0-1), respectively. The median CLASI activity and damage scores were 3 (1-5) and 1 (0-1), respectively. Overall, there was no correlation between SLEQoL with CLASI or CLASI damage. Only the self-image domain of SLEQoL correlated with total CLASI (ρ = 0.32; p = 0.01) and CLASI-D (ρ = 0.35; p = 0.02). There was a weak correlation of CLASI with the Mexican-SLEDAI score (ρ = 0.30; p = 0.03) but not with the SLICC damage index. In this cohort of early lupus, cutaneous disease activity in lupus had a weak correlation with systemic disease. Cutaneous features did not appear to influence the quality of life except in the self-image domain.

High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor.

Despite the recent availability of vaccines against the acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the search for inhibitory therapeutic agents has assumed importance especially in the context of emerging new viral variants. In this paper, we describe the discovery of a novel noncovalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (Mpro) by employing a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased. Our HTVS framework leverages the U.S. supercomputing infrastructure achieving nearly 91% resource utilization and nearly 126 million docking calculations per hour. Downstream biochemical assays validate this Mpro inhibitor with an inhibition constant (Ki) of 2.9 µM (95% CI 2.2, 4.0). Furthermore, using room-temperature X-ray crystallography, we show that MCULE-5948770040 binds to a cleft in the primary binding site of Mpro forming stable hydrogen bond and hydrophobic interactions. We then used multiple µs-time scale molecular dynamics (MD) simulations and machine learning (ML) techniques to elucidate how the bound ligand alters the conformational states accessed by Mpro, involving motions both proximal and distal to the binding site. Together, our results demonstrate how MCULE-5948770040 inhibits Mpro and offers a springboard for further therapeutic design.

Space-time wiring specificity supports direction selectivity in the retina.

How does the mammalian retina detect motion? This classic problem in visual neuroscience has remained unsolved for 50 years. In search of clues, here we reconstruct Off-type starburst amacrine cells (SACs) and bipolar cells (BCs) in serial electron microscopic images with help from EyeWire, an online community of 'citizen neuroscientists'. On the basis of quantitative analyses of contact area and branch depth in the retina, we find evidence that one BC type prefers to wire with a SAC dendrite near the SAC soma, whereas another BC type prefers to wire far from the soma. The near type is known to lag the far type in time of visual response. A mathematical model shows how such 'space-time wiring specificity' could endow SAC dendrites with receptive fields that are oriented in space-time and therefore respond selectively to stimuli that move in the outward direction from the soma.

Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques.

Warm-season legumes have been receiving increased attention as forage resources in the southern United States and other countries. However, the near infrared spectroscopy (NIRS) technique has not been widely explored for predicting the forage quality of many of these legumes. The objective of this research was to assess the performance of NIRS in predicting the forage quality parameters of five warm-season legumes-guar (Cyamopsis tetragonoloba), tepary bean (Phaseolus acutifolius), pigeon pea (Cajanus cajan), soybean (Glycine max), and mothbean (Vigna aconitifolia)-using three machine learning techniques: partial least square (PLS), support vector machine (SVM), and Gaussian processes (GP). Additionally, the efficacy of global models in predicting forage quality was investigated. A set of 70 forage samples was used to develop species-based models for concentrations of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), and in vitro true digestibility (IVTD) of guar and tepary bean forages, and CP and IVTD in pigeon pea and soybean. All species-based models were tested through 10-fold cross-validations, followed by external validations using 20 samples of each species. The global models for CP and IVTD of warm-season legumes were developed using a set of 150 random samples, including 30 samples for each of the five species. The global models were tested through 10-fold cross-validation, and external validation using five individual sets of 20 samples each for different legume species. Among techniques, PLS consistently performed best at calibrating (R2c = 0.94-0.98) all forage quality parameters in both species-based and global models. The SVM provided the most accurate predictions for guar and soybean crops, and global models, and both SVM and PLS performed better for tepary bean and pigeon pea forages. The global modeling approach that developed a single model for all five crops yielded sufficient accuracy (R2cv/R2v = 0.92-0.99) in predicting CP of the different legumes. However, the accuracy of predictions of in vitro true digestibility (IVTD) for the different legumes was variable (R2cv/R2v = 0.42-0.98). Machine learning algorithms like SVM could help develop robust NIRS-based models for predicting forage quality with a relatively small number of samples, and thus needs further attention in different NIRS based applications.

Protein kinases orchestrate cell cycle regulators in differentiating BeWo choriocarcinoma cells.

Choriocarcinoma, a trophoblastic neoplasia, occurs in women as an incidence of abnormal pregnancy. BeWo choriocarcinoma cells derived from the abnormal placentation are a suitable model system to study the factors associated with differentiation, invasion and other cellular events as an alternative to clinical samples. Many protein kinases orchestrate the complex events of cell cycle and in case of malignancy such regulators are found to be mutated. In the present study, BeWo cells treated with forskolin (Fo) and phorbol 12-myristate 13-acetate (PMA) were used to study the role of PKA (protein kinase A) and PKC (protein kinase C), respectively, on the expression pattern of differentiation-related genes, membrane markers, PKC isoforms and cell cycle regulators. The effect of Fo and PMA on the cell proliferation was assessed. Progressive induction of alkaline phosphatase level and formation of multinucleated differentiated cells were observed in the cells treated with Fo. Exposure of cells to Fo and PMA induced the mRNA transcripts of α-hCG, ß-hCG and endoglin and down-regulates E-cadherin at mRNA and protein levels. Synergistic levels of both up- and down-regulated genes/proteins were observed when cells were treated with the combination of Fo and PMA. The mRNA levels of cyclin D1, cyclin E1, p21, Rb, p53, caspase-3 and caspase-8 decreased gradually during differentiation. Fo significantly inhibited the protein levels of PCNA, Rb, PKC-α and PMA stimulated mRNA expression of PKC-ε and PKC-δ. Further, failure in the activation of essential components of the cell cycle machinery caused G2/M phase arrest in differentiating BeWo cells.

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data.

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

Connectomic reconstruction of the inner plexiform layer in the mouse retina.

Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer--the main computational neuropil region in the mammalian retina--the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.

Predictors of Post-operative Pain and Opioid Consumption in Patients Undergoing Liver Surgery.

BACKGROUND: Post-operative pain management is a critical component of perioperative care. Patients at risk of poorly controlled post-operative pain may benefit from early measures to optimize pain management. We sought to identify risk factors for post-operative pain and opioid consumption in patients undergoing liver resection. METHODS: This is a multi-institutional prospective nested cohort study of patients undergoing open liver resection. Opioid consumption and pain scores were collected following surgery. To estimate the effects of patient factors on opioid consumption (oral morphine equivalents-OME) and on pain scores (NRS-11), we used generalized linear models and multivariable linear regression model, respectively. RESULTS: One hundred and fifty-three patients who underwent open liver resection between 2013 and 2016 were included in the study. The mean patient age was 62.2 years, and 43.3% were female. Younger patients were significantly more likely to use more opioids in the early post-operative period (16.7 OME/10 years, p < 0.001). Patient factors that were significantly associated with increased NRS-11 pain scores also included younger patient age (difference in pain score of 0.3/10 years with cough and 0.2/10 years at rest, p < 0.01 for both) as well as a history of analgesic use (difference in pain score of 0.9 with cough and 0.6 at rest, p < 0.01 and p = 0.07, respectively). CONCLUSION: Younger patients and those with a history of analgesic use are more likely to report higher post-operative pain and require higher doses of opioids. Early identification of these patients, and measures to better manage their pain, may contribute to optimal perioperative care.

Use of prothrombin complex concentrate for management of coagulopathy after cardiac surgery: a propensity score matched comparison to plasma.

BACKGROUND: An important cause of coagulopathy in cardiac surgery is impaired thrombin generation. While plasma is often used to correct this element of the coagulopathy, studies in vitro suggest that prothrombin complex concentrates (PCCs) might be more effective. Comparative data, however, are scant. METHODS: We compared the outcomes of those who received only plasma with those who received PCCs (with or without plasma) for management of coagulopathy in patients who underwent cardiac surgery with cardiopulmonary bypass at a single institution from 2012 to 2016. Propensity score matching was used to obtain between-group balance. Primary outcome was avoidance of perioperative red cell transfusions. Other outcomes were incidence of massive transfusion (more than nine red cell units), refractory bleeding (requiring factor VIIa), and adverse events. RESULTS: Of 6362 patients, 1151 (18.2%) received plasma without any PCCs, and 204 (3.2%) received PCCs, either with (n=125) or without plasma (n=79). Overall, patient risk-profile was higher in the PCCs group. In a well-balanced propensity score match that included 117 patients per group, the odds ratio (OR) for red cell avoidance was 2.4-fold [95% confidence interval (CI) 1.2-4.8] higher in the PCCs group. Massive transfusion (OR 0.58; 95% CI 0.33-1.0) and refractory bleeding (OR 0.49; 95% CI 0.24-1.03) incidences were almost significantly lower in the PCCs group. The adverse event profiles were similar. CONCLUSIONS: Our exploratory study suggests that the use of PCCs as part of a multifaceted coagulation management strategy may have blood-sparing effects. Their incorporation into clinical practice, however, must await determination of their risk-benefit profile via multicentre randomised trials.

Cardiovascular complications after non-cardiac surgery.

Cardiac complications are common after non-cardiac surgery. Peri-operative myocardial infarction occurs in 3% of patients undergoing major surgery. Recently, however, our understanding of the epidemiology of these cardiac events has broadened to include myocardial injury after non-cardiac surgery, diagnosed by an asymptomatic troponin rise, which also carries a poor prognosis. We review the causation of myocardial injury after non-cardiac surgery, with potential for prevention and treatment, based on currently available international guidelines and landmark studies. Postoperative arrhythmias are also a frequent cause of morbidity, with atrial fibrillation and QT-prolongation having specific relevance to the peri-operative period. Postoperative systolic heart failure is rare outside of myocardial infarction or cardiac surgery, but the impact of pre-operative diastolic dysfunction and its ability to cause postoperative heart failure is increasingly recognised. The latest evidence regarding diastolic dysfunction and the impact on non-cardiac surgery are examined to help guide fluid management for the non-cardiac anaesthetist.

Expert Consensus on The Management of Dermatophytosis in India (ECTODERM India).

BACKGROUND: Dermatophytosis management has become an important public health issue, with a large void in research in the area of disease pathophysiology and management. Current treatment recommendations appear to lose their relevance in the current clinical scenario. The objective of the current consensus was to provide an experience-driven approach regarding the diagnosis and management of tinea corporis, cruris and pedis. METHODS: Eleven experts in the field of clinical dermatology and mycology participated in the modified Delphi process consisting of two workshops and five rounds of questionnaires, elaborating definitions, diagnosis and management. Panel members were asked to mark "agree" or "disagree" beside each statement, and provide comments. More than 75% of concordance in response was set to reach the consensus. RESULT: KOH mount microscopy was recommended as a point of care testing. Fungal culture was recommended in chronic, recurrent, relapse, recalcitrant and multisite tinea cases. Topical monotherapy was recommended for naïve tinea cruris and corporis (localised) cases, while a combination of systemic and topical antifungals was recommended for naïve and recalcitrant tinea pedis, extensive lesions of corporis and recalcitrant cases of cruris and corporis. Because of the anti-inflammatory, antibacterial and broad spectrum activity, topical azoles should be preferred. Terbinafine and itraconazole should be the preferred systemic drugs. Minimum duration of treatment should be 2-4 weeks in naïve cases and > 4 weeks in recalcitrant cases. Topical corticosteroid use in the clinical practice of tinea management was strongly discouraged. CONCLUSION: This consensus guideline will help to standardise care, provide guidance on the management, and assist in clinical decision-making for healthcare professionals.

Lumbar lipomeningomyelocele associated with multiple café au lait spots: a case report.

We report on a child with several café au lait spots in association with a lumbar lipomeningomyelocele as an apparently new association. Cutaneous markers, the identification of which plays a crucial role in the early diagnosis and management of spinal malformations, can accompany occult spinal dysraphism. Herein we report a case of lumbar lipomeningomyelocele associated with an overlying café au lait spot that served as a marker of occult spinal dysraphism. The patient also had segmental café au lait spots on the face, making the association unique.

Neuroprotective effects of bikaverin on H2O2-induced oxidative stress mediated neuronal damage in SH-SY5Y cell line.

The generation of free radicals and oxidative stress has been linked to several neurodegenerative diseases including Parkinson's disease, Alzheimer's disease, Huntington's disease, and Amyotrophic lateral sclerosis. The use of free radical scavenging molecules for the reduction of intracellular reactive oxygen species is one of the strategies used in the clinical management of neurodegeneration. Fungal secondary metabolism is a rich source of novel molecules with potential bioactivity. In the current study, bikaverin was extracted from Fusarium oxysporum f. sp. lycopersici and its structural characterization was carried out. Further, we explored the protective effects of bikaverin on oxidative stress and its anti-apoptotic mechanism to attenuate H2O2-induced neurotoxicity using human neuroblastoma SH-SY5Y cells. Our results elucidate that pretreatment of neurons with bikaverin attenuates the mitochondrial and plasma membrane damage induced by 100 µM H2O2 to 82 and 26% as evidenced by MTT and LDH assays. H2O2 induced depletion of antioxidant enzyme status was also replenished by bikaverin which was confirmed by Realtime Quantitative PCR analysis of SOD and CAT genes. Bikaverin pretreatment efficiently potentiated the H2O2-induced neuronal markers, such as BDNF, TH, and AADC expression, which orchestrate the neuronal damage of the cell. The H2O2-induced damage to cells, nuclear, and mitochondrial integrity was also restored by bikaverin. Bikaverin could be developed as a preventive agent against neurodegeneration and as an alternative to some of the toxic synthetic antioxidants.