Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic 3D neuron tracing using all-path pruning

Motivation: Digital reconstruction, or tracing, of 3D neuron structures is critical toward reverse engineering the wiring and functions of a brain. However, despite a number of existing studies, this task is still challenging, especially when a 3D microscopic image has low signal-to-noise ratio (SNR) and fragmented neuron segments. Published work can handle these hard situations only by introducing global prior information, such as where a neurite segment starts and terminates. However, manual incorporation of such global information can be very time consuming. Thus, a completely automatic approach for these hard situations is highly desirable. Results: We have developed an automatic graph algorithm, called the all-path pruning (APP), to trace the 3D structure of a neuron. To avoid potential mis-tracing of some parts of a neuron, an APP first produces an initial over-reconstruction, by tracing the optimal geodesic shortest path from the seed location to every possible destination voxel/pixel location in the image. Since the initial reconstruction contains all the possible paths and thus could contain redundant structural components (SC), we simplify the entire reconstruction without compromising its connectedness by pruning the redundant structural elements, using a new maximal-covering minimal-redundant (MCMR) subgraph algorithm. We show that MCMR has a linear computational complexity and will converge. We examined the performance of our method using challenging 3D neuronal image datasets of model organisms (e.g. fruit fly). Availability: The software is available upon request. We plan to eventually release the software as a plugin of the V3D-Neuron package at http://penglab.janelia. org/proj/v3d. Contact: pengh@janelia.hhmi. org
On the Relevance of Natural Stimuli for the Study of Brainstem Correlates: The Example of Consonance Perception

Some combinations of musical tones sound pleasing to Western listeners, and are termed consonant, while others sound discordant, and are termed dissonant. The perceptual phenomenon of consonance has been traced to the acoustic property of harmonicity. It has been repeatedly shown that neural correlates of consonance can be found as early as the auditory brainstem as reflected in the harmonicity of the scalp-recorded frequency-following response (FFR). “Neural Pitch Salience” (NPS) measured from FFRs—essentially a time-domain equivalent of the classic pattern recognition models of pitch—has been found to correlate with behavioral judgments of consonance for synthetic stimuli. Following the idea that the auditory system has evolved to process behaviorally relevant natural sounds, and in order to test the generalizability of this finding made with synthetic tones, we recorded FFRs for consonant and dissonant intervals composed of synthetic and natural stimuli. We found that NPS correlated with behavioral judgments of consonance and dissonance for synthetic but not for naturalistic sounds. These results suggest that while some form of harmonicity can be computed from the auditory brainstem response, the general percept of consonance and dissonance is not captured by this measure. It might either be represented in the brainstem in a different code (such as place code) or arise at higher levels of the auditory pathway. Our findings further illustrate the importance of using natural sounds, as a complementary tool to fully-controlled synthetic sounds, when probing auditory perception.
Computational analysis of the oscillatory behavior at the translation level induced by mRNA levels oscillations due to finite intracellular resources

Recent studies have demonstrated how the competition for the finite pool of available gene expression factors has important effect on fundamental gene expression aspects. In this study, based on a whole-cell model simulation of translation in S. cerevisiae, we evaluate for the first time the expected effect of mRNA levels fluctuations on translation due to the finite pool of ribosomes. We show that fluctuations of a single gene or a group of genes mRNA levels induce periodic behavior in all S. cerevisiae translation factors and aspects: the ribosomal densities and the translation rates of all S. cerevisiae mRNAs oscillate. We numerically measure the oscillation amplitudes demonstrating that fluctuations of endogenous and heterologous genes can cause a significant fluctuation of up to 50% in the steady-state translation rates of the rest of the genes. Furthermore, we demonstrate by synonymous mutations that oscillating the levels of mRNAs that experience high ribosomal occupancy (e.g. ribosomal “traffic jam”) induces the largest impact on the translation of the S. cerevisiae genome. The results reported here should provide novel insights and principles related to the design of synthetic gene expression circuits and related to the evolutionary constraints shaping gene expression of endogenous genes.
Assessment of remaining tumour involved lymph nodes with MRI in patients with complete luminal response after neoadjuvant treatment of rectal cancer.

OBJECTIVE To assess the accuracy of MRI to predict remaining lymph node metastases in patients with complete pathological luminal response (ypT0) after neoadjuvant therapy. METHODS Data from a national registry were used. 19 patients with histopathologically remaining lymph node metastases (ypT0N+) were identified. Another 19 patients without lymph node metastases (ypT0N0) were used as matched controls. Two radiologists blinded to all patient information evaluated staging and restaging MRI that was compared to histopathological findings of the resected specimen. RESULTS The average size of the largest lymph node on restaging MRI was significantly larger (4.5 mm) in the ypT0N+ group than in the ypT0N0 group (2.6 mm) (p = 0.04). Presence of ypN+ was correctly predicted by MRI in 7 of 19 patients. In patients without lymph node metastases (ypT0N0), these were correctly classified by MRI in 16 of 19 patients. All patients who had MR-identified lymph nodes larger than 8 mm at restaging were ypTN+. The sensitivity, specificity, positive predictive value and negative for prediction of remaining lymph node metastasis with MRI were 37, 84, 70 and 57%. CONCLUSION In patients with ypT0 in rectal cancer after neoadjuvant treatment, remaining regional lymph node metastases cannot safely be predicted by restaging MRI alone using presently known criteria. Presence of a lymph node over 8 mm on restaging MRI strongly indicates yPN+. Advances in knowledge: This is one of the first studies on MRI lymph node assessment after chemo-radiotherapy (CRT) in luminal complete response.
Developing quantitative physiological phenotypes of sleep apnea for epidemiological studies

Existing physiological databases have not been sufficiently detailed to provide relevant and important information for characterizing the pathophysiology of obstructive sleep apnea. Critical collapsing pressure (PcRit) is a standard method for determining upper airway patency during sleep, however is labor intensive and prohibits large-scale studies. Based on previously published data indicating R<inf>US</inf> does not significantly vary between groups, our aim was to develop an approach to estimate the P<inf>CRIT</inf> from airflow at atmospheric pressure (V<inf>atm</inf>). In a dataset of 126 subjects, where Pcrit and R<inf>US</inf> were measured using standard techniques. We then determined the minimum sample size required to estimate the R<inf>US</inf> mean and variance by utilizing a bootstrap procedure (30 times for n=3 to 126). We first estimated the minimum number of subjects needed for obtaining a group for a two-tailed (z=1.96) standard error for R<inf>US</inf> in the population. Then in 75 individuals, quantitative estimates of airflow were obtained at atmospheric pressure. Using the estimated R<inf>US</inf> and atmospheric, we determined an estimated P<inf>CRIT</inf> (ЄPcrit). Bland-Altman plots were generated to determine the agreement between the measured P<inf>CRIT</inf> and ЄPcrit. For the entire population the mean±SEM R<inf>US</inf> was 23±1cmH<inf>2</inf>O/L/s (±95% CI: 21, 25). ∼40 subjects represent the minimum sample required to estimate the population variance within ±2 SEM. In the subsample with atmospheric flow measurements, a linear regression model (ЄPcrit [cmH<inf>2</inf>O]=V<inf>@PN</inf> [L/s]x−23[cmH<inf>2</inf>O/L/s]), ЄPcrit ranged from 0 to −9.6cmH<inf>2</inf>O. In the Bland-Altman analysis there was no mean difference between the measured Pcrit and ЄPcrit (−0.01cmH<inf>2</inf>O; p=0.8) with upper and lower limits of agreement at ±2.3cmH<inf>2</inf>O. The variance of upstream resistance approaches a constant value in groups with approximately 40 subjects. Utilizing a fixed up-stream resistance to estimate Pcrit from the airflow at atmospheric pressure agrees with the measured values. These data suggest that measurements of quantitative airflow during standard polysomnography can be used to determine upper airway properties in large cohorts.
Structural Basis of Transcription: RNA Polymerase II at 2.8 Ångstrom Resolution

Structures of a 10-subunit yeast RNA polymerase II have been derived from two crystal forms at 2.8 and 3.1 angstrom resolution. Comparison of the structures reveals a division of the polymerase into four mobile modules, including a clamp, shown previously to swing over the active center. In the 2.8 angstrom structure, the clamp is in an open state, allowing entry of straight promoter DNA for the initiation of transcription. Three loops extending from the clamp may play roles in RNA unwinding and DNA rewinding during transcription. A 2.8 angstrom difference Fourier map reveals two metal ions at the active site, one persistently bound and the other possibly exchangeable during RNA synthesis. The results also provide evidence for RNA exit in the vicinity of the carboxyl-terminal repeat domain, coupling synthesis to RNA processing by enzymes bound to this domain.
GNAS: A Greedy Neural Architecture Search Method for Multi-Attribute Learning

A key problem in deep multi-attribute learning is to effectively discover the inter-attribute correlation structures. Typically, the conventional deep multi-attribute learning approaches follow the pipeline of manually designing the network architectures based on task-specific expertise prior knowledge and careful network tunings, leading to the inflexibility for various complicated scenarios in practice. Motivated by addressing this problem, we propose an efficient greedy neural architecture search approach (GNAS) to automatically discover the optimal tree-like deep architecture for multi-attribute learning. In a greedy manner, GNAS divides the optimization of global architecture into the optimizations of individual connections step by step. By iteratively updating the local architectures, the global tree-like architecture gets converged where the bottom layers are shared across relevant attributes and the branches in top layers more encode attribute-specific features. Experiments on three benchmark multi-attribute datasets show the effectiveness and compactness of neural architectures derived by GNAS, and also demonstrate the efficiency of GNAS in searching neural architectures.
Spectrally stabilized high-power high-brightness DBR-tapered lasers in the VIS and NIR range

A promising concept to achieve high-output power together with a narrow spectral line-width and a diffraction limited beam quality is the use of tapered diode lasers consisting of a distributed Bragg reflector (DBR) mirror as rear side wavelength selective mirror. The DBR mirror provides high reflectivity for the selected emission wavelength and besides contributes to spatial mode filtering. A ridge waveguide (RW) section supports the fundamental lateral mode suppressing higher order modes and the tapered gain region is used for amplification. The taper angle had to be designed with respect to the properties of the RW section. The implementation of separate electrical contacts allows a flexible output power together with fundamental mode operation. In this work, high brightness DBR tapered diode lasers with separate electrical contacts for the wavelength range between 630 nm and 1180 nm will be presented. For red emitting devices, around 637 nm an output power up to about 1 W is achieved, limited by the properties of the semiconductor material. Devices emitting in the longer wavelength range around 1000 nm reach output powers up to 15 W. For all the above manufactured diode lasers about 80% of the emitted laser light is within the diffraction limited central lobe. Here, e.g. 10 W diffraction limited power was measured. The devices are successfully implemented into experiments for non-linear frequency conversion, e.g. SHG and the pumping of an OPO, as an excitation source for absorption spectroscopy, as pump source for fs-lasers, and their emission is efficiently coupled into single mode fibers.
Aerosol Effects on Microstructure and Intensity of Tropical Cyclones

Improving the forecasts of the intensity of tropical cyclones (TCs) remains a major challenge. One possibility for improvement is consideration of the effects that aerosols have on tropical clouds and cyclones. The authors have been pursuing this under the Hurricane Aerosol and Microphysics Program, supported by the U.S. Department of Homeland Security. This was done through observations of aerosols and resulting cloud microphysical structure within tropical cyclones and simulating their effects using high-resolution TC models that treat cloud internal processes explicitly. In addition to atmospheric aerosols, special attention was given also to the impact of the intense sea-spray-generated aerosols and convective rolls in the hurricane boundary layer (BL) under hurricane- force winds. The results of simulations and observations show that TC ingestion of aerosols that serve as cloud condensation nuclei can lead to significant reductions in their intensities. This is caused by redistribution of the precipi.
Developing Two Spectral Disease Indices for Detection of Wheat Leaf Rust (Pucciniatriticina)

Spectral vegetation indices (SVIs) have been widely used to detect different plant diseases. Wheat leaf rust manifests itself as an early symptom with the leaves turning yellow and orange. The sign of advancing disease is the leaf colour changing to brown while the final symptom is when the leaf becomes dry. The goal of this work is to develop spectral disease indices for the detection of leaf rust. The reflectance spectra of the wheat’s infected and non-infected leaves at different disease stages were collected using a spectroradiometer. As ground truth, the ratio of the disease-affected area to the total leaf area and the fractions of the different symptoms were extracted using an RGB digital camera. Fractions of the various disease symptoms extracted by the digital camera and the measured reflectance spectra of the infected leaves were used as input to the spectral mixture analysis (SMA). Then, the spectral reflectance of the different disease symptoms were estimated using SMA and the least squares method. The reflectance of different disease symptoms in the 450~1000 nm were studied carefully using the Fisher function. Two spectral disease indices were developed based on the reflectance at the 605, 695 and 455 nm wavelengths. In both indices, the R2 between the estimated and the observed was as highas 0.94.
p 53 shapes genome-wide and cell type-specific changes in microRNA expression during the human DNA damage response

p53 shapes genome-wide and cell type-specific changes in microRNA expression during the human DNA damage response Hiroyoshi Hattori, Rekin’s Janky, Wilfried Nietfeld, Stein Aerts, M Madan Babu & Ashok R Venkitaraman a University of Cambridge; Medical Research Council Cancer Unit; Hutchison/MRC Research Center; Cambridge, UK b Medical Research Council Laboratory of Molecular Biology; Cambridge, UK c Center for Human Genetics; KU Leuven; Campus Gasthuisberg; Leuven, Belgium d Max Planck Institute for Molecular Genetics; Berlin-Dahlem, Germany e These authors contributed equally to the work. f Present address: Laboratory of Advanced Therapy; Clinical Research Center; National Hospital Organization; Nagoya Medical Center; Aichi, Japan Published online: 30 Oct 2014.
A Review on Cybersickness and Usability in Virtual Environments

With the emerge of new technologies many systems are presented to a wider range of users at reasonable costs. Virtual Reality (VR) technology has also entered many new economical areas such as tourism, business, online games, and also cultural heritage. The new advancement in VR and its availability to the end user in many forms necessitates considering the health issues because cybersickness is one of the drawbacks of Virtual Environments (VE). In addition, usability of the VE and the provided VR technology and system is of paramount importance in the market to attract the user. However, usability measurement of the VE also has become a difficult issue due to the vast range of products and users. A review on the cybersickness and usability issues in VE is prepared and presented in this paper.
Brain metastasis from large cell neuroendocrine carcinoma of the urinary bladder

Background In patients with urinary bladder cancer, brain metastases are quite rare and occur in only 1–7% of these patients. Of the urinary bladder cancers, large cell neuroendocrine carcinoma (LCNEC) is extremely rare; only 16 cases have been reported to date. In this report, a case of brain metastasis from LCNEC of the urinary bladder is described. Case Description A 74-year-old man was admitted with confusion and left-sided hemiparesis. Head magnetic resonance imaging demonstrated a ring-enhancing lesion in the right frontal lobe. Whole body computed tomography revealed a suspicious lesion in the urinary bladder. These findings were considered consistent with metastatic brain tumor. Craniotomy and tumor removal were performed. After craniotomy, the patient underwent cystoscopy and the bladder mass was biopsied. Histological and immunohistochemical examination of both the brain tumor and bladder mass revealed LCNEC. According to these findings, the patient was diagnosed with a brain metastasis from LCNEC of the urinary bladder. Conclusion To our knowledge, this is the first report of a patient with a brain metastasis from LCNEC of the urinary bladder.
Cross-Lingual Learning-to-Rank with Shared Representations

Cross-lingual information retrieval (CLIR) is a document retrieval task where the documents are written in a language different from that of the user’s query. This is a challenging problem for data-driven approaches due to the general lack of labeled training data. We introduce a large-scale dataset derived from Wikipedia to support CLIR research in 25 languages. Further, we present a simple yet effective neural learning-to-rank model that shares representations across languages and reduces the data requirement. This model can exploit training data in, for example, Japanese-English CLIR to improve the results of Swahili-English CLIR.
Incorporating self-assembly into robocasting for applications in hard tissue engineering

High cost coupled with limited supply of hard tissue substitutes make necessary the development of synthetic biomaterials, as well as economical and reproducible manufacturing techniques that can be easily scaled up. Multiple and often conflicting requirements have so far impeded the application of polymer/ceramic composites in large load-bearing defects. Although porosity is a crucial biological requirement, it has a detrimental effect on their mechanical performance. This thesis emphasizes upon methods for structuring bioceramic materials at different orders of magnitude - termed structural hierarchy. In bones, this constitutes the main mechanism contributing to their remarkable strength and fracture resistance. This can be achieved through combining AM with physical processes that cause the material to self-assemble into various configurations during or following its deposition. The first part of this research explores the potential of Low-Temperature Deposition Modelling (LDM) in fabricating scaffolds with tailorable bimodal porosity. More specifically, LDM is treated as a hybrid technique, in which robocasting is combined with freezing-induced self-assembly. For the purposes of this study, a highly versatile and economical print-head was fabricated that can be operated at ambient temperatures down to -20oC. In addition, a highly thixotropic β-TCP paste formulation of high water content (80% v/v) was developed that takes advantage of a synergy existing between Sodium Alginate and Xanthan Gum. The findings suggest that chamber temperature and water content have the most marked effect on pore morphology. Ordered micro-architectures comprising lamellar pores with a high degree of alignment were obtained at low freezing rates (-5oC). Most importantly, this research evidences for the first time that their direction is not only dictated by toolpath geometry, but also by the ice structure in preceding layers (epitaxy). The second part of this thesis demonstrates the combination of robocasting with a heating process to produce planar hollow-tube lattices that can be manipulated into various configurations. This technique makes use of a novel Sodium Alginate-based β-TCP slurry reinforced with cellulose nano-fibrils. When heated rapidly, it forms hollow-shell structures, which can be cross-linked in Ca2+-rich solutions to produce flexible yet strong particle-reinforced gels. Optimal results were achieved at 3 and 4% w/w alginate content, where the paste’s loss tangent reaches its maximum value. This research demonstrates that such combinational approaches to AM can successfully produce hard tissue substitutes that exhibit multiple levels of structural hierarchy. This constitutes a first step towards achieving biomimetic bone scaffolds with superior mechanical performance.