Miracle-dz/UniFAR-FTUs huggingface dataset:
Perspective: A Neuro-Hormonal Systems Approach to Understanding the Complexity of Cryptorchidism Susceptibility

Nonsyndromic cryptorchidism is a common multifactorial, condition with long-term risks of subfertility and testicular cancer. Revealing the causes of cryptorchidism will likely improve prediction and prevention of adverse outcomes. Herein we provide our current perspective of cryptorchidism complexity in a synthesis of cumulative clinical and translational data generated by ourselves and others. From our recent comparison of genome-wide association study (GWAS) data of cryptorchidism with or without testicular germ cell tumor, we identified RBFOX family genes as candidate susceptibility loci. Notably, RBFOX proteins regulate production of calcitonin gene-related peptide (CGRP), a sensory neuropeptide linked to testicular descent in animal models. We also re-analyzed existing fetal testis transcriptome data from a rat model of inherited cryptorchidism (the LE/orl strain) for enrichment of Leydig cell progenitor genes. The majority are coordinately downregulated, consistent with known reduced testicular testosterone levels in the LE/orl fetus, and similarly suppressed in the gubernaculum. Using qRT-PCR, we found dysregulation of dorsal root ganglia (DRG) sensory transcripts ipsilateral to undescended testes. These data suggest that LE/orl cryptorchidism is associated with altered signaling in possibly related cell types in the testis and gubernaculum as well as DRG. Complementary rat and human studies thus lead us to propose a multi-level, integrated neuro-hormonal model of testicular descent. Variants in genes encoding RBFOX family proteins and/or their transcriptional targets combined with environmental exposures may disrupt this complex pathway to enhance cryptorchidism susceptibility. We believe that a systems approach is necessary to provide further insight into the causes and consequences of cryptorchidism.
Large scale evaluation of local image feature detectors on homography datasets

We present a large scale benchmark for the evaluation of local feature detectors. Our key innovation is the introduction of a new evaluation protocol which extends and improves the standard detection repeatability measure. The new protocol is better for assessment on a large number of images and reduces the dependency of the results on unwanted distractors such as the number of detected features and the feature magnification factor. Additionally, our protocol provides a comprehensive assessment of the expected performance of detectors under several practical scenarios. Using images from the recently-introduced HPatches dataset, we evaluate a range of state-of-the-art local feature detectors on two main tasks: viewpoint and illumination invariant detection. Contrary to previous detector evaluations, our study contains an order of magnitude more image sequences, resulting in a quantitative evaluation significantly more robust to over-fitting. We also show that traditional detectors are still very competitive when compared to recent deep-learning alternatives.
Quantification of Pulse-Dependent Trabecular Meshwork Motion in Normal Humans Using Phase-Sensitive OCT

Purpose The purpose of this study was to characterize the pulsatile motion of trabecular meshwork (TM) in normal subjects and demonstrate its changes in accommodation with phase-sensitive optical coherence tomography (PhS-OCT). Methods A new PhS-OCT laboratory prototype was designed to measure pulsatile TM motion in 13 healthy humans. Two sets of images were captured in 10 subjects, first with best corrective refraction and the other with an additional 3.0 diopters of accommodation. In each image, both maximum velocity (MV) and cumulative displacement (CD) in two selected regions of TM, the internal (IMV and ICD) and external (EMV and ECD) region, were measured. Results For all parameters the intraclass correlation coefficient was >0.75. Neither MV nor CD was significantly different between eyes in individual subjects (PIMV = 0.967, PEMV = 0.391, PICD = 0.603, PECD = 0.482). In 26 eyes, with best corrective refraction, the EMV was higher than the IMV (23.9 ± 9.8 vs. 18.9 ± 8.08 μm/s; P = 0.0001), as was the ECD compared with the ICD (0.340 ±0.125 vs. 0.264 ± 0.111 μm; P = 0.000004). With accommodation, MV and CD significantly increased (PIMV = 0.0003, PEMV = 0.0003, PICD = 0.019, and PECD = 0.007), whereas MV and CD in the external region were still larger than those in the internal area (PEMV vs. IMV = 0.009, PECD vs. ICD = 0.023). Conclusions This study demonstrates the differences in TM motion between the internal and external regions of TM and displays its change with accommodation. The findings and good reproducibility suggest PhS-OCT helps to understand TM function in regulation of IOP, and, with further refinements, it may be useful in clinical management of glaucoma.
The Beneficial Effect of Human Amnion Mesenchymal Cells in Inhibition of Inflammation and Induction of Neuronal Repair in EAE Mice

Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS). Currently, there is still lack of curative treatment for MS. Mesenchymal stem cell- (MSC-) based therapy is recently the subject of intense interest in autoimmune diseases. Here, we investigated the therapeutic effect and potential mechanism of human amnion mesenchymal cells (hAMC) on inflammation and remyelination in experimental autoimmune encephalomyelitis (EAE) mice. C57BL/6 mice were immunized with myelin oligodendrocyte glycoprotein (MOG) 35–55 peptide. hAMC were injected intraperitoneal when EAE was successfully established. The results demonstrated that application of hAMC significantly ameliorated the disease severity and histopathological changes in EAE mice. The production of proinflammatory cytokines such as IFN-γ, TNF-α, IL-1β, and IL-17A in the spleen and CNS was dramatically inhibited. Moreover, CD4+ T cells and CD8+ T cells in the CNS were also significantly decreased in EAE mice after hAMC treatment. In addition, hAMC treatment also promoted the production of neuron-repair factors (NGF, CNTF, and BDNF) in the CNS of EAE mice. In conclusion, these results indicated that hAMC could attenuate the inflammation and promote the remyelination in EAE mice, which might be a promising cell source for the therapy of MS.
Exact minimum number of bits to stabilize a linear system

We consider an unstable scalar linear stochastic system, X<inf>n</inf>+<inf>1</inf>= aXn + Z<inf>n</inf>- U<inf>n</inf>. ; where <tex>$a$</tex> ≥ 1 is the system gain, Zn's are independent random variables with bounded α-th moments, and U<inf>n</inf>'S are the control actions that are chosen by a controller who receives a single element of a finite set {1, …, M} as its only information about system state X<inf>i</inf>. We show that M = [a] + 1 is necessary and sufficient for ß- moment stability, for any ß < a. Our achievable scheme is a uniform quantizer of the zoom-in / zoom-out type. We analyze its performance using probabilistic arguments. We prove a matching converse using information-theoretic techniques. Our results generalize to vector systems, to systems with dependent Gaussian noise, and to the scenario in which a small fraction of transmitted messages is lost.
Mining Big Neuron Morphological Data

The advent of automatic tracing and reconstruction technology has led to a surge in the number of neurons 3D reconstruction data and consequently the neuromorphology research. However, the lack of machine-driven annotation schema to automatically detect the types of the neurons based on their morphology still hinders the development of this branch of science. Neuromorphology is important because of the interplay between the shape and functionality of neurons and the far-reaching impact on the diagnostics and therapeutics in neurological disorders. This survey paper provides a comprehensive research in the field of automatic neurons classification and presents the existing challenges, methods, tools, and future directions for automatic neuromorphology analytics. We summarize the major automatic techniques applicable in the field and propose a systematic data processing pipeline for automatic neuron classification, covering data capturing, preprocessing, analyzing, classification, and retrieval. Various techniques and algorithms in machine learning are illustrated and compared to the same dataset to facilitate ongoing research in the field.
Second-line chemotherapy for the treatment of metastatic pancreatic cancer after first-line gemcitabine-based chemotherapy: a network meta-analysis

Guidelines for treatment of metastatic pancreatic cancer recommend a second line based on Fluoropyrimidine (FP) alone or in combination with Oxaliplatin (OXA) or Irinotecan (IRI) after a first line treatment based on Gemcitabine (GEM). We conducted a Bayesian network meta-analysis to compare currently available therapies to treat metastatic pancreatic cancer in the second line, considering as efficacy measures overall survival (OS) and progression free survival (PFS). Published randomized trials were identified using electronic databases (MEDLINE, PubMed, https://clinicaltrials.gov/ and American Society of clinical oncology). 8 studies met the inclusion criteria for a total of 1,587 patients and 7 different therapeutic schemes. The results suggested that the use of IRI-FP-Folinic Acid scheme in the second-line treatment of metastatic pancreatic cancer may offer a benefit in terms of OS and PFS for patients not previously treated with these drugs.
Differential Regulation of the Phenazine Biosynthetic Operons by Quorum Sensing in Pseudomonas aeruginosa PAO1-N

The Pseudomonas aeruginosa quorum sensing (QS) network plays a key role in the adaptation to environmental changes and the control of virulence factor production in this opportunistic human pathogen. Three interlinked QS systems, namely las, rhl, and pqs, are central to the production of pyocyanin, a phenazine virulence factor which is typically used as phenotypic marker for analysing QS. Pyocyanin production in P. aeruginosa is a complex process involving two almost identical operons termed phzA1B1C1D1E1F1G1 (phz1) and phzA2B2C2D2E2F2G2 (phz2), which drive the production of phenazine-1-carboxylic acid (PCA) which is further converted to pyocyanin by two modifying enzymes PhzM and PhzS. Due to the high sequence conservation between the phz1 and phz2 operons (nucleotide identity > 98%), analysis of their individual expression by RNA hybridization, qRT-PCR or transcriptomics is challenging. To overcome this difficulty, we utilized luminescence based promoter fusions of each phenazine operon to measure in planktonic cultures their transcriptional activity in P. aeruginosa PAO1-N genetic backgrounds impaired in different components of the las, rhl, and pqs QS systems, in the presence or absence of different QS signal molecules. Using this approach, we found that all three QS systems play a role in differentially regulating the phz1 and phz2 phenazine operons, thus uncovering a higher level of complexity to the QS regulation of PCA biosynthesis in P. aeruginosa than previously appreciated. Importance The way the P. aeruginosa QS regulatory networks are intertwined creates a challenge when analysing the mechanisms governing specific QS-regulated traits. Multiple QS regulators and signals have been associated with the production of phenazine virulence factors. In this work we designed experiments where we dissected the contribution of specific QS switches using individual mutations and complementation strategies to gain further understanding of the specific roles of these QS elements in controlling expression of the two P. aeruginosa phenazine operons. Using this approach we have teased out which QS regulators have either indirect or direct effects on the regulation of the two phenazine biosynthetic operons. The data obtained highlight the sophistication of the QS cascade in P. aeruginosa and the challenges in analysing the control of phenazine secondary metabolites.
Follicular Helper T Cells in DiGeorge Syndrome

DiGeorge syndrome is an immunodeficiency characterized by thymic dysplasia resulting in T cell lymphopenia. Most patients suffer from increased susceptibility to infections and heightened prevalence of autoimmune disorders, such as autoimmune thrombocytopenia. B cells in DiGeorge syndrome show impaired maturation, with low switched-memory B cells and a wide spectrum of antibody deficiencies or dysgammaglobulinemia, presumably due to impaired germinal center responses. We set out to evaluate circulating follicular helper T cells (cTFHs) in DiGeorge syndrome, as markers of T–B interaction in the germinal centers in a cohort of 17 patients with partial DiGeorge and 21 healthy controls of similar age. cTFHs were characterized as CXCR5+CD45RA− CD4+ T cells using flow cytometry. We verify previous findings that the population of memory CD4+ T cells is relatively increased in diGeorge patients, corresponding to low naïve T cells and impaired T cell production in the thymus. The population of CXCR5+ memory CD4+ T cells (cTFHs) was significantly expanded in patients with DiGeorge syndrome, but only healthy controls and not DiGeorge syndrome patients showed gradual increase of CXCR5 expression on cTFHs with age. We did not observe correlation between cTFHs and serum IgG levels or population of switched memory B cells. There was no difference in cTFH numbers between DiGeorge patients with/without thrombocytopenia and with/without allergy. Interestingly, we show strong decline of PD1 expression on cTFHs in the first 5 years of life in DiGeorge patients and healthy controls, and gradual increase of PD1 and ICOS expression on CD4− T cells in healthy controls later in life. Thus, here, we show that patients with DiGeorge syndrome have elevated numbers of cTFHs, which, however, do not correlate with autoimmunity, allergy, or production of immunoglobulins. This relative expansion of cTFH cells may be a result of impaired T cell development in patients with thymic dysplasia.
Baidu Apollo EM Motion Planner

In this manuscript, we introduce a real-time motion planning system based on the Baidu Apollo (open source) autonomous driving platform. The developed system aims to address the industrial level-4 motion planning problem while considering safety, comfort and scalability. The system covers multilane and single-lane autonomous driving in a hierarchical manner: (1) The top layer of the system is a multilane strategy that handles lane-change scenarios by comparing lane-level trajectories computed in parallel. (2) Inside the lane-level trajectory generator, it iteratively solves path and speed optimization based on a Frenet frame. (3) For path and speed optimization, a combination of dynamic programming and spline-based quadratic programming is proposed to construct a scalable and easy-to-tune framework to handle traffic rules, obstacle decisions and smoothness simultaneously. The planner is scalable to both highway and lower-speed city driving scenarios. We also demonstrate the algorithm through scenario illustrations and on-road test results. The system described in this manuscript has been deployed to dozens of Baidu Apollo autonomous driving vehicles since Apollo v1.5 was announced in September 2017. As of May 16th, 2018, the system has been tested under 3,380 hours and approximately 68,000 kilometers (42,253 miles) of closed-loop autonomous driving under various urban scenarios. The algorithm described in this manuscript is available at this https URL.
Impact of ecological redundancy on the performance of machine learning classifiers in vegetation mapping

Abstract Vegetation maps are models of the real vegetation patterns and are considered important tools in conservation and management planning. Maps created through traditional methods can be expensive and time‐consuming, thus, new more efficient approaches are needed. The prediction of vegetation patterns using machine learning shows promise, but many factors may impact on its performance. One important factor is the nature of the vegetation–environment relationship assessed and ecological redundancy. We used two datasets with known ecological redundancy levels (strength of the vegetation–environment relationship) to evaluate the performance of four machine learning (ML) classifiers (classification trees, random forests, support vector machines, and nearest neighbor). These models used climatic and soil variables as environmental predictors with pretreatment of the datasets (principal component analysis and feature selection) and involved three spatial scales. We show that the ML classifiers produced more reliable results in regions where the vegetation–environment relationship is stronger as opposed to regions characterized by redundant vegetation patterns. The pretreatment of datasets and reduction in prediction scale had a substantial influence on the predictive performance of the classifiers. The use of ML classifiers to create potential vegetation maps shows promise as a more efficient way of vegetation modeling. The difference in performance between areas with poorly versus well‐structured vegetation–environment relationships shows that some level of understanding of the ecology of the target region is required prior to their application. Even in areas with poorly structured vegetation–environment relationships, it is possible to improve classifier performance by either pretreating the dataset or reducing the spatial scale of the predictions.
Imaging Violence in Schizophrenia: A Systematic Review and Critical Discussion of the MRI Literature

Background: Persons with schizophrenia have a small but significant increase in risk of violence, which remains after controlling for known environmental risk factors. In vivo MRI-studies may point toward the biological underpinnings of psychotic violence, and neuroimaging has increasingly been used in forensic and legal settings despite unclear relevance. Objectives: (1) To present the first systematic review, following standardized guidelines, of MRI studies of violence with schizophrenia. (2) To critically discuss the promises and pitfalls of using this literature to understand violence in schizophrenia in clinical, forensic, and legal settings. Methods: Following the PRISMA guidelines and literature searches until January 2018, we found 21 original studies that fulfilled the inclusion criteria: (1) Studies of persons with schizophrenia, (2) a history of violence or aggressive behavior, (3) the use of one or more MRI-modalities (sMRI, DTI, fMRI). Results: The most consistent findings from the structural studies were reduced volumes of the hippocampus and the frontal lobe (in particular the orbitofrontal and anterior cingulate cortex) in schizophrenia patients with a history of violence or higher aggression scores. The functional studies mainly showed differences and aggression correlates in the frontal lobe and amygdala. However, the studies were methodologically heterogeneous, with four particular areas of concern: different definitions of violence, region of interest vs. whole-brain studies, small subject samples, and group comparisons in a heterogeneous diagnostic category (schizophrenia). Conclusion: The literature reports subtle, but inconsistent group level differences in brain structure and function associated with violence and aggression with schizophrenia, in particular in areas involved in the formation of psychosis symptoms and affective regulation. Due to methodological challenges the results should be interpreted with caution. In order to come closer to the neurobiological underpinnings of violence in schizophrenia future studies could: (1) address the neurobiological differences of premeditated and reactive violence, (2) use RDoC criteria, for example, or other symptom-based systems to categorize psychosis patients, (3) increase subject cohorts and apply new data driven methods. In this perspective, MRI-studies of violence in schizophrenia have the potential to inform clinical violence prediction and legal evaluations in the future.
Pseudomonas aeruginosa LasB Subverts Alveolar Macrophage Activity by Interfering With Bacterial Killing Through Downregulation of Innate Immune Defense, Reactive Oxygen Species Generation, and Complement Activation

Pseudomonas aeruginosa (P.a) is a pathogen causing significant morbidity and mortality, in particular, in hospital patients undergoing ventilation and in patients with cystic fibrosis. Among the virulence factors secreted or injected into host cells, the physiopathological relevance of type II secretions system (T2SS) is less studied. Although there is extensive literature on the destructive role of LasB in vitro on secreted innate immune components and on some stromal cell receptors, studies on its direct action on myeloid cells are scant. Using a variety of methods, including the use of bacterial mutants, gene-targeted mice, and proteomics technology, we show here, using non-opsonic conditions (thus mimicking resting and naïve conditions in the alveolar space), that LasB, an important component of the P.a T2SS is highly virulent in vivo, and can subvert alveolar macrophage (AM) activity and bacterial killing, in vitro and in vivo by downregulating important secreted innate immune molecules (complement factors, cytokines, etc.) and receptors (IFNAR, Csf1r, etc.). In particular, we show that LasB downregulates the production of C3 and factor B complement molecules, as well as the activation of reactive oxygen species production by AM. In addition, we showed that purified LasB impaired significantly the ability of AM to clear an unrelated bacterium, namely Streptococcus pneumoniae. These data provide a new mechanism of action for LasB, potentially partly explaining the early onset of P.a, alone, or with other bacteria, within the alveolar lumen in susceptible individuals, such as ventilated, chronic obstructive pulmonary disease and cystic fibrosis patients.
Differential cellular contractility as a mechanism for stiffness sensing

The ability of cells to sense and respond to the mechanical properties of their environments is fundamental to a range of cellular behaviours, with substrate stiffness increasingly being found to be a key signalling factor. Although active contractility of the cytoskeleton is clearly necessary for stiffness sensing in cells, the physical mechanisms connecting contractility with mechanosensing and molecular conformational change are not well understood. Here we present a contractility-driven mechanism for linking changes in substrate stiffness with internal conformational changes. Cellular contractility is often assumed to imply an associated compressive strain. We show, however, that where the contractility is non-uniform, localized areas of internal stretch can be generated as stiffer substrates are encountered. This suggests a physical mechanism for the stretch-activation of mechanotransductive molecules on stiffer substrates. Importantly, the areas of internal stretch occur deep within the cell and not near the cellular perimeter, which region is more traditionally associated with stiffness sensing through e.g. focal adhesions. This supports recent experimental results on whole-cell mechanically-driven mechanotransduction. Considering cellular shape we show that aspect ratio acts as an additional control parameter, so that the onset of positive strain moves to higher stiffness values in elliptical cells.