Miracle-dz/UniFAR-FTUs huggingface dataset:
Delineation of an immunosuppressive gradient in hepatocellular carcinoma using high-dimensional proteomic and transcriptomic analyses

Significance The roles of tumor-infiltrating leukocytes in mediating cancer progression are well recognized, but a multidimensional analysis of the entire cancer immune system is lacking. Here, we dissected the cancer-immune landscape in hepatocellular carcinoma (HCC) across tumor, nontumor, and peripheral blood cells using time-of-flight mass cytometry, multiplex immunofluorescence tissue staining, and NanoString analysis. We identified various immune subsets that were enriched in the tumor microenvironment and their potential impact on the tumor immunity based on their detailed phenotypes. This study has validated the concept of a cancer-immune gradient and demonstrated in primary HCC that immune-cell subsets become progressively suppressive as they traverse the nontumor to tumor microenvironment. These data have opened avenues for the design of immunotherapeutics in HCC. The recent development of immunotherapy as a cancer treatment has proved effective over recent years, but the precise dynamics between the tumor microenvironment (TME), nontumor microenvironment (NTME), and the systemic immune system remain elusive. Here, we interrogated these compartments in hepatocellular carcinoma (HCC) using high-dimensional proteomic and transcriptomic analyses. By time-of-flight mass cytometry, we found that the TME was enriched in regulatory T cells (Tregs), tissue resident memory CD8+ T cells (TRMs), resident natural killer cells (NKRs), and tumor-associated macrophages (TAMs). This finding was also validated with immunofluorescence staining on Foxp3+CD4+ and PD-1+CD8+ T cells. Interestingly, Tregs and TRMs isolated from the TME expressed multiple markers for T-cell exhaustion, including PD-1, Lag-3, and Tim-3 compared with Tregs and TRMs isolated from the NTME. We found PD-1+ TRMs were the predominant T-cell subset responsive to anti–PD-1 treatment and significantly reduced in number with increasing HCC tumor progression. Furthermore, T-bet was identified as a key transcription factor, negatively correlated with PD-1 expression on memory CD8+ T cells, and the PD-1:T-bet ratio increased upon exposure to tumor antigens. Finally, transcriptomic analysis of tumor and adjacent nontumor tissues identified a chemotactic gradient for recruitment of TAMs and NKRs via CXCR3/CXCL10 and CCR6/CCL20 pathways, respectively. Taken together, these data confirm the existence of an immunosuppressive gradient across the TME, NTME, and peripheral blood in primary HCC that manipulates the activation status of tumor-infiltrating leukocytes and renders them immunocompromised against tumor cells. By understanding the immunologic composition of this gradient, more effective immunotherapeutics for HCC may be designed.
Challenges ahead for matchmaking

Abstract With every additional individual whose genome is sequenced thousands of novel variants enter the scene. It is these variants of unknown clinical significance, VUCS, that represent a great challenge to geneticists, who are dealing with high-throughput sequencing data sets. Especially in diagnostics of patients with unknown monogenic disease the joint effort of geneticists is required to find new disease gene associations. For this purpose, online platforms for matchmaking have been developed that allow clinician scientists to collaborate worldwide and to share medically relevant data. However, for a success of these tools, skills in deep phenotyping as well as new statistical approaches will be required.
Submodularity Cuts and Applications

Several key problems in machine learning, such as feature selection and active learning, can be formulated as submodular set function maximization. We present herein a novel algorithm for maximizing a submodular set function under a cardinality constraint — the algorithm is based on a cutting-plane method and is implemented as an iterative small-scale binary-integer linear programming procedure. It is well known that this problem is NP-hard, and the approximation factor achieved by the greedy algorithm is the theoretical limit for polynomial time. As for (non-polynomial time) exact algorithms that perform reasonably in practice, there has been very little in the literature although the problem is quite important for many applications. Our algorithm is guaranteed to find the exact solution finitely many iterations, and it converges fast in practice due to the efficiency of the cutting-plane mechanism. Moreover, we also provide a method that produces successively decreasing upper-bounds of the optimal solution, while our algorithm provides successively increasing lower-bounds. Thus, the accuracy of the current solution can be estimated at any point, and the algorithm can be stopped early once a desired degree of tolerance is met. We evaluate our algorithm on sensor placement and feature selection applications showing good performance.
Patch to the Future: Unsupervised Visual Prediction

In this paper we present a conceptually simple but surprisingly powerful method for visual prediction which combines the effectiveness of mid-level visual elements with temporal modeling. Our framework can be learned in a completely unsupervised manner from a large collection of videos. However, more importantly, because our approach models the prediction framework on these mid-level elements, we can not only predict the possible motion in the scene but also predict visual appearances - how are appearances going to change with time. This yields a visual "hallucination" of probable events on top of the scene. We show that our method is able to accurately predict and visualize simple future events, we also show that our approach is comparable to supervised methods for event prediction.
A syntactic approach for searching similarities within sentences

Textual data is the main electronic form of knowledge representation. Sentences, meant as logic units of meaningful word sequences, can be considered its backbone. In this paper, we propose a solution based on a purely syntactic approach for searching similarities within sentences, named approximate sub2sequence matching. This process being very time consuming, efficiency in retrieving the most similar parts available in large repositories of textual data is ensured by making use of new filtering techniques. As far as the design of the system is concerned, we chose a solution that allows us to deploy approximate sub2 sequence matching without changing the underlying database.
Release of interleukin-6 by human thyroid epithelial cells immortalized by simian virus 40 DNA transfection.

Interleukin-6 (IL-6) has actions on a variety of endocrine tissues. The cytokine is secreted by cells of the anterior pituitary and endocrine pancreas and has recently been shown to be produced by cultures of thyroid epithelial cells. In this study we have examined some of the factors which regulate IL-6 release from an immortalized human thyroid line (HTori3). IL-6 release over 24 h was stimulated by TSH (5000 microU/ml), by forskolin (0.01 mmol/l), by fetal calf serum (1-20%) and by epidermal growth factor (20 ng/ml). Stimulation was also apparent with gamma-interferon and with tumour necrosis factor at concentrations known to enhance class II major histocompatibility antigen expression by thyroid epithelium. The most potent factor tested was interleukin-1 (IL-1), which controls IL-6 release from other cell types. Threefold stimulation was found with 1 U/ml rising to 350-fold with 1000 U/ml. The effect of IL-1 took 2 h to develop and was blocked by cycloheximide (100 mumol/l). Stimulation was not markedly inhibited by pertussis toxin. Many of the actions of IL-1 are mediated by prostaglandin E2 (PGE2). At concentrations as low as 30 nmol/l, PGE2 stimulated IL-6 release but the maximum stimulation obtained with PGE2 was only threefold. The effect of IL-1 was not inhibited by indomethacin. These data provide further evidence that IL-6 is produced by human thyrocytes. The effect of IL-1 has not been demonstrated previously. Stimulation of IL-6 release by IL-1 did not appear to be mediated by prostaglandin. (ABSTRACT TRUNCATED AT 250 WORDS)
Direct Interaction of the N-Terminal Domain of Ribosomal Protein S1 with Protein S2 in Escherichia coli

Despite of the high resolution structure available for the E. coli ribosome, hitherto the structure and localization of the essential ribosomal protein S1 on the 30 S subunit still remains to be elucidated. It was previously reported that protein S1 binds to the ribosome via protein-protein interaction at the two N-terminal domains. Moreover, protein S2 was shown to be required for binding of protein S1 to the ribosome. Here, we present evidence that the N-terminal domain of S1 (amino acids 1–106; S1106) is necessary and sufficient for the interaction with protein S2 as well as for ribosome binding. We show that over production of protein S1106 affects E. coli growth by displacing native protein S1 from its binding pocket on the ribosome. In addition, our data reveal that the coiled-coil domain of protein S2 (S2α2) is sufficient to allow protein S1 to bind to the ribosome. Taken together, these data uncover the crucial elements required for the S1/S2 interaction, which is pivotal for translation initiation on canonical mRNAs in Gram-negative bacteria. The results are discussed in terms of a model wherein the S1/S2 interaction surface could represent a possible target to modulate the selectivity of the translational machinery and thereby alter the translational program under distinct conditions.
A New Combined Particle Swarm Optimization Algorithm Based Golden Section Strategy

Based the defects of global optimal model falling into local optimum easily and local model with slow convergence speed during traditional PSO algorithm solving a complex high-dimensional and multi-peak function, a two sub-swarms particle optimization algorithm is proposed. All particles are divided into two equivalent parts. One part particles adopts global evolution model, while the other part uses local evolution model. If the global optimal fitness of the whole population stagnates for some iteration, a golden rule is introduced into local evolution model. This strategy can substitute the partial perfect particles of local evolution for the equivalent worse particles of global evolution model. So, some particles with advantage are joined into the whole population to make the algorithm keep active all the time. Compared with classic PSO and PSO-GL(A dynamic global and local combined particle swarm optimization algorithm, PSO-GL), the results show that the proposed PSO in this paper can get more effective performance over the other two algorithm in the simulation experiment for four benchmark testing function.
Spherical Demons: Fast Diffeomorphic Landmark-Free Surface Registration

We present the Spherical Demons algorithm for registering two spherical images. By exploiting spherical vector spline interpolation theory, we show that a large class of regularizors for the modified Demons objective function can be efficiently approximated on the sphere using iterative smoothing. Based on one parameter subgroups of diffeomorphisms, the resulting registration is diffeomorphic and fast. The Spherical Demons algorithm can also be modified to register a given spherical image to a probabilistic atlas. We demonstrate two variants of the algorithm corresponding to warping the atlas or warping the subject. Registration of a cortical surface mesh to an atlas mesh, both with more than 160 k nodes requires less than 5 min when warping the atlas and less than 3 min when warping the subject on a Xeon 3.2 GHz single processor machine. This is comparable to the fastest nondiffeomorphic landmark-free surface registration algorithms. Furthermore, the accuracy of our method compares favorably to the popular FreeSurfer registration algorithm. We validate the technique in two different applications that use registration to transfer segmentation labels onto a new image (1) parcellation of in vivo cortical surfaces and (2) Brodmann area localization in ex vivo cortical surfaces.
Rapid presumptive identification of anaerobes in blood cultures by gas-liquid chromatography

Production of volatile and nonvolatile metabolic acids in blood culture broths by aerobic, facultative anaerobic, and obligate anaerobic bacteria was analyzed by gas-liquid chromatography. Anaerobic blood culture isolates were presumptively identified by the qualitative analysis of volatile fatty acids. Isolates, with a characteristic Gram stain reaction and cellular morphology, were identified by the following acid patterns: Bacteriodes fragilis group with acetic and propionic acids; Fusobacterium with acetic, butyric, and usually propionic acids; Veillonella with acetic and propionic acids; gram-positive cocci with acetic and butyric acids; and Clostridium with acetic and butyric acids.
Local Variables with Compound Names and Comments as Signs of Fault-Prone Java Methods

This paper focuses on two types of artifacts—local variables and comments in a method (function). Both of them are usually used at the programer’s discretion. Thus, naming local variables and commenting code can vary among individuals, and such an individual difference may cause a dispersion in quality. This paper conducts an empirical analysis on the fault-proneness of Java methods which are collected from nine popular open source products. The results report the following three findings: (1) Methods having local variables with compound names are more likely to be faulty than the others; (2) Methods having local variables with simple and short names are unlikely to be faulty, but their positive effects tend to be decayed as their scopes get wider; (3) The presence of comments within a method body can also be useful sign of fault-prone method.
Modeling complex packing structures and their thermal properties

A packing algorithm for particles of complex shapes and a method to use the packing structure directly to predict its thermal properties are described. A novel aspect of the packing algorithm is that the particles, their movements and the packing space are all digitized. Using this approach, some major difficulties encountered by traditional packing algorithms can be avoided, for example, handling non-spherical and complex shapes, and detection of collision or overlap between the particles. The digital algorithm is capable of generating packing of particles of arbitrary shapes and sizes in a packing space or container of an arbitrary geometry. To predict effective thermal conductivity of the packing structure, an iterative finite difference method is used. The formulation is performed directly on the individual building blocks using fundamental laws of heat transfer. By performing the calculations at such a microscopic level, only the basic information about the material is needed and the influence of the microstructure on thermal properties can be assessed directly.
Plasticity of lumbosacral propriospinal neurons is associated with the development of autonomic dysreflexia after thoracic spinal cord transection

Complete thoracic (T) spinal cord injury (SCI) above the T6 level typically results in autonomic dysreflexia, an abnormal hypertensive condition commonly triggered by nociceptive stimuli below the level of SCI. Overexpression of nerve growth factor in the lumbosacral spinal cord induces profuse sprouting of nociceptive pelvic visceral afferent fibers that correlates with increased hypertension in response to noxious colorectal distension. After complete T4 SCI, we evaluated the plasticity of propriospinal neurons conveying visceral input rostrally to thoracic sympathetic preganglionic neurons. The anterograde tracer biotinylated dextran amine (BDA) was injected into the lumbosacral dorsal gray commissure (DGC) of injured/nontransected rats immediately after injury (acute) or 2 weeks later (delayed). At 1 or 2 weeks after delayed or acute injections, respectively, a higher density (P < 0.05) of BDA+ fibers was found in thoracic dorsal gray matter of injured vs. nontransected spinal cords. For corroboration, fast blue (FB) or cholera toxin subunit beta (CTb) was injected into the T9 dorsal horns 2 weeks postinjury/nontransection. After 1 week transport, more retrogradely labeled (P < 0.05) DGC propriospinal neurons (T13–S1) were quantified in injured vs. nontransected cords. We also monitored immediate early gene c‐fos expression following colorectal distension and found increased (P < 0.01) c‐Fos+ cell numbers throughout the DGC after injury. Collectively, these results imply that, in conjunction with local primary afferent fiber plasticity, injury‐induced sprouting of DGC neurons may be a key constituent in relaying visceral sensory input to sympathetic preganglionic neurons that elicit autonomic dysreflexia after high thoracic SCI. J. Comp. Neurol. 509:382–399, 2008. © 2008 Wiley‐Liss, Inc.
Illuminated lines revisited

For the rendering of vector and tensor fields, several texture-based volumetric rendering methods were presented in recent years. While they have indisputable merits, the classical vertex-based rendering of integral curves has the advantage of better zooming capabilities as it is not bound to a fixed resolution. It has been shown that lighting can improve spatial perception of lines significantly, especially if lines appear in bundles. Although OpenGL does not directly support lighting of lines, fast rendering of illuminated lines can be achieved by using basic texture mapping. This existing technique is based on a maximum principle which gives a good approximation of specular reflection. Diffuse reflection however is essentially limited to bidirectional lights at infinity. We show how the realism can be further increased by improving diffuse reflection. We present simplified expressions for the Phong/Blinn lighting of infinitesimally thin cylindrical tubes. Based on these, we propose a fast rendering technique with diffuse and specular reflection for orthographic and perspective views and for multiple local and infinite lights. The method requires commonly available programmable vertex and fragment shaders and only two-dimensional lookup textures.
Estimating the Empirical Null Distribution of Maxmean Statistics in Gene Set Analysis

Gene Set Analysis (GSA) is a framework for testing the association of a set of genes and the outcome, e.g. disease status or treatment group. The method replies on computing a maxmean statistic and estimating the null distribution of the maxmean statistics via a restandardization procedure. In practice, the pre-determined gene sets have stronger intra-correlation than genes across sets. This may result in biases in the estimated null distribution. We derive an asymptotic null distribution of the maxmean statistics based on sparsity assumption. We propose a flexible two group mixture model for the maxmean statistics. The mixture model allows us to estimate the null parameters empirically via maximum likelihood approach. Our empirical method is compared with the restandardization procedure of GSA in simulations. We show that our method is more accurate in null density estimation when the genes are strongly correlated within gene sets.
Building a Multilingual Lexical Resource for Named Entity Disambiguation, Translation and Transliteration

In this paper, we present HeiNER, the multilingual Heidelberg Named Entity Resource. HeiNER contains 1,547,586 disambiguated English Named Entities together with translations and transliterations to 15 languages. Our work builds on the approach described in (Bunescu and Pasca, 2006), yet extends it to a multilingual dimension. Translating Named Entities into the various target languages is carried out by exploiting crosslingual information contained in the online encyclopedia Wikipedia. In addition, HeiNER provides linguistic contexts for every NE in all target languages which makes it a valuable resource for multilingual Named Entity Recognition, Disambiguation and Classification. The results of our evaluation against the assessments of human annotators yield a high precision of 0.95 for the NEs we extract from the English Wikipedia. These source language NEs are thus very reliable seeds for our multilingual NE translation method.
Power/Area Efficient Low Noise Amplifier for Ultra-Low Amplitude Recording from Amputee Intrafascicular Nerve

Advanced hand-prostheses that can be interfaced directly with the nervous system are being developed to capture motor intent from upper limb amputees. One approach is to record neural activity of peripheral nerves (PN) in the residual limb using longitudinal intrafascicular electrodes (LIFEs). LIFE recordings using commercial recording systems from amputated human nerves show broad spikes with amplitudes in the low microvolt ranges. Current custom integrated circuits for PN recording using cuffs that include a low noise amplifier, are not monolithic and do not meet the power/area requirements for an embedded system. We are designing an implantable neural recording amplifier for LIFEs that meets the low noise and low power/area consumption specifications for low amplitude recordings. The post-layout performance from Monte Carlo simulations indicates that we can achieve a mid-gain of 36.7±0.9% dB, input-referred noise of 2.3±7% μVrms on 10-10k Hz at 37oC, power of 194±3% μW. The low noise amplifier area is 0.15mm2, designed with a 0. 18μm CMOS process. This design offers lower power/area consumption for equivalent noise performance of the integrated circuits for cuff recordings.
OSPF Stub Router Advertisement

This memo describes a backward-compatible technique that may be used by OSPF (Open Shortest Path First) implementations to advertise unavailability to forward transit traffic or to lower the preference level for the paths through such a router. In some cases, it is desirable not to route transit traffic via a specific OSPF router. However, OSPF does not specify a standard way to accomplish this.
Use of tissue water as a concentration reference for proton spectroscopic imaging

A strategy for using tissue water as a concentration standard in 1H magnetic resonance spectroscopic imaging studies on the brain is presented, and the potential errors that may arise when the method is used are examined. The sensitivity of the method to errors in estimates of the different water compartment relaxation times is shown to be small at short echo times (TEs). Using data from healthy human subjects, it is shown that different image segmentation approaches that are commonly used to account for partial volume effects (SPM2, FSL's FAST, and K‐means) lead to different estimates of metabolite levels, particularly in gray matter (GM), owing primarily to variability in the estimates of the cerebrospinal fluid (CSF) fraction. While consistency does not necessarily validate a method, a multispectral segmentation approach using FAST yielded the lowest intersubject variability in the estimates of GM metabolites. The mean GM and white matter (WM) levels of N‐acetyl groups (NAc, primarily N‐acetylaspartate), choline (Ch), and creatine (Cr) obtained in these subjects using the described method with FAST multispectral segmentation are reported: GM [NAc] = 17.16 ± 1.19 mM; WM [NAc] = 14.26 ± 1.38 mM; GM [Ch] = 3.27 ± 0.47 mM; WM [Ch] = 2.65 ± 0.25 mM; GM [Cr] = 13.98 ± 1.20 mM; and WM [Cr] = 7.10 ± 0.67 mM. Magn Reson Med, 2006. © 2006 Wiley‐Liss, Inc.