Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification and analysis of retinal interneurons by computational structure under natural scenes

Inhibitory neurons are diverse across the brain, but for the visual system we lack the ability to functionally classify these neurons under complex natural stimuli. Here we take the approach of classifying retinal amacrine cell responses to natural scenes using optical recording and an interpretable neural network model. We fit mouse amacrine cell responses to a two-layer convolutional neural network model of a class shown previously to accurately capture salamander ganglion cell responses to natural scenes. Using an approach from interpretable machine learning, we determined for each stimulus the model interneurons that generated each amacrine response, analogous to the set of bipolar cells that target the amacrine population. From this analysis we clustered amacrine cells not by their natural scene responses, but by the model presynaptic neurons that constructed those responses, conservatively finding approximately seven groups by this approach. By analyzing the set of model presynaptic input neurons for each amacrine cluster, we find that distributed rather than dedicated inputs generate natural scene responses for different amacrine cell types. Additional analyses revealed distinct transient and sustained modes exhibited by the network during the response to simple flashes. These results give insight into the computational structure of how the diverse amacrine cell population responds to natural scenes, and generate multiple quantitative hypotheses for how synaptic inputs generate those responses.
Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity

Long-read RNA sequencing has shed light on transcriptomic complexity, but questions remain about the functionality of downstream protein products. We introduce Biosurfer, a computational approach for comparing protein isoforms, while systematically tracking the transcriptional, splicing, and translational variations that underlie differences in the sequences of the protein products. Using Biosurfer, we analyzed the differences in 32,799 pairs of GENCODE annotated protein isoforms, finding a majority (70%) of variable N-termini are due to the alternative transcription start sites, while only 9% arise from 5’ UTR alternative splicing. Biosurfer’s detailed tracking of nucleotide-to-residue relationships helped reveal an uncommonly tracked source of single amino acid residue changes arising from the codon splits at junctions. For 17% of internal sequence changes, such split codon patterns lead to single residue differences, termed “ragged codons”. Of variable C-termini, 72% involve splice- or intron retention-induced reading frameshifts. We found an unusual pattern of reading frame changes, in which the first frameshift is closely followed by a distinct second frameshift that restores the original frame, which we term a “snapback” frameshift. We analyzed long read RNA-seq-predicted proteome of a human cell line and found similar trends as compared to our GENCODE analysis, with the exception of a higher proportion of isoforms predicted to undergo nonsense-mediated decay. Biosurfer’s comprehensive characterization of long-read RNA-seq datasets should accelerate insights of the functional role of protein isoforms, providing mechanistic explanation of the origins of the proteomic diversity driven by the alternative splicing. Biosurfer is available as a Python package at https://github.com/sheynkman-lab/biosurfer.
In Plant Activation (INPACT): An Inducible, Hyperexpression Platform for Recombinant Protein Production in PlantsW

In this study, we describe a novel protein production platform that provides both activation and amplification of transgene expression in planta. The In Plant Activation (INPACT) system is based on the replication machinery of tobacco yellow dwarf mastrevirus (TYDV) and is essentially transient gene expression from a stably transformed plant, thus combining the advantages of both means of expression. The INPACT cassette is uniquely arranged such that the gene of interest is split and only reconstituted in the presence of the TYDV-encoded Rep/RepA proteins. Rep/RepA expression is placed under the control of the AlcA:AlcR gene switch, which is responsive to trace levels of ethanol. Transgenic tobacco (Nicotiana tabacum cv Samsun) plants containing an INPACT cassette encoding the b-glucuronidase (GUS) reporter had negligible background expression but accumulated very high GUS levels (up to 10% total soluble protein) throughout the plant, within 3 d of a 1% ethanol application. The GUS reporter was replaced with a gene encoding a lethal ribonuclease, barnase, demonstrating that the INPACT system provides exquisite control of transgene expression and can be adapted to potentially toxic or inhibitory compounds. The INPACT gene expression platform is scalable, not host-limited, and has been used to express both a therapeutic and an industrial protein.
A mathematical model for pancreatic cancer during intraepithelial neoplasia

Cancer is the result of complex interactions of intrinsic and extrinsic cell processes, which promote sustained proliferation, resistance to apoptosis, reprogramming and reorganization. To understand the evolution of any type of cancer it is necessary to understand the role of the microenvironmental conditions and the impact of some molecular complexes and mechanisms on certain signalling pathways. As in most cancer quantitative models, the understanding of the early onset of cancer requires a multiscale analysis of the cellular microenvironment. In this paper we analyse a multiscale model of pancreatic adenocarcinoma by modelling the cellular microenvironment through elastic cell interactions and their intercellular communication mechanisms, such as growth factors and cytokines. We focus on the low-grade dysplasia (PanIN 1) and moderate dysplasia (PanIN 2) stages of the pancreatic adenocarcinoma. To this end we propose a gene regulatory network associated with the processes of proliferation and apoptosis of pancreatic cells and its kinetics in terms delayed differential equations to mimic cell development. Likewise, we couple the cell cycle with the spatial distribution of cells and the transport of growth factors to show that the adenocarcinoma evolution is triggered by inflammatory processes. We show that the oncogene RAS may be an important target to develop anti-inflammatory strategies that limit the emergence of more aggressive adenocarcinomas.
Endobronchial Ultrasound-guided Transbronchial Needle Biopsy for Diagnosis of Mediastinal Lymphadenopathy in Patients with Extrathoracic Malignancy

Mediastinal lymphadenopathy associated with extrathoracic malignancy or a metastasis of unknown origin (MUO) requires pathological verification. Surgical exploration or endoscopic ultrasound-guided fine needle aspiration is limited to application. We investigated the effectiveness of endobronchial ultrasound-guided transbronchial needle biopsy (EBUS-TBNA) for evaluating mediastinal lymphadenopathy in patients with an extrathoracic malignancy. We retrospectively analyzed data from 59 patients who underwent EBUS-TBNA with a core biopsy because of a suspected mediastinal metastasis between September 2008 and August 2010. All patients had previously been diagnosed with an extrathoracic malignancy (n = 39, 66.1%) or a suspected MUO without a thoracic lesion (n = 20, 33.9%). A total of 88 lymph nodes was analyzed. EBUS-TBNA findings indicated malignancies in 34 patients (57.6%). The EBUS-TBNA sensitivity and specificity for the detection of mediastinal malignancy in patients with a previous extrathoracic malignancy were 96.3% and 100%, respectively. For MUO patients without a thoracic lesion, the sensitivity and specificity were 61.5% and 100%, respectively. The overall sensitivity and specificity were 81.0% and 100%, respectively (P = 0.053). EBUS-TBNA is a safe and effective modality for evaluating mediastinal lymphadenopathy in patients with a previous extrathoracic malignancy or a MUO without a thoracic lesion. The application of this diagnostic tool is likely to have significant clinical implications.
Arbitrary Few Parameters are Good Enough for Adapting Large-scale Pre-trained Language Models

Parameter-efficient tuning (PET) methods can effectively drive extremely large pre-trained language models (PLMs) by only training minimal parameters. Different PET methods utilize different manually designed modules. In a small PLM, there are usually noticeable performance differences among PET methods. Never-theless, when a PLM’s scale grows up to tens of billions of parameters, all PET methods achieve almost the same performance and even perform on par with the full-parameter fine-tuning method. Hence, we hypothesize that model scaling can mitigate the design differences (the module structures and the number of trainable parameters) among PET methods. To study this hypothesis, we introduce a more flexible PET method – arbitrary PET (APET) method – to be compatible with arbitrary module structures and any number of trainable parameters. Then, we experiment on 11 NLP tasks of 5 types and 2 representative PLMs. From our investigations, we find that the model scaling (1) mitigates the effects of the arbitrary module structure on the performance of tuning methods, and (2) enables the tuning methods to optimize fewer parameters to achieve the full-parameter fine-tuning performance. Intriguingly, we also observe that all tuning methods require almost the same number of trainable parameters to drive PLMs. We discuss this phenomenon and the above two findings collectively from optimization perspectives to fathom the mechanisms behind them. These conclusions not only demonstrate the positive impact of model scaling on tuning methods but disclose its mechanisms, which help us design more effective and efficient tuning methods on larger-scale PLMs.
Very high resolution radar at 300 GHz

In this paper the setup and measurements of a high resolution millimeter wave FMCW radar is presented. The system is operated at 300 GHz providing a maximum bandwidth of more than 40 GHz leading to a range resolution of 3.7 mm. The capability of the radar has been investigated in ISAR measurements by means of a turntable. The presented results demonstrate the high image quality and the richness of details up to a distance of 140 m. With its excellent performance, the system covers a wide range of applications in the security and safety sector.
Lack of dominant-negative activity for tumor-related ZNRF3 missense mutations at endogenous levels

ZNRF3, a negative regulator of β-catenin signaling, removes Wnt receptors from the membrane. Currently, it is unknown which tumor-associated variants can be considered driver mutations and through which mechanisms they contribute to cancer. Here we show that all truncating mutations analyzed at endogenous levels exhibit loss-of-function, with longer variants retaining partial activity. Regarding missense mutations, we show that 27/82 ZNRF3 variants in the RING and R-Spondin domain structures, lead to (partial) loss-of-function/hyperactivation. Mechanistically, defective R-spondin domain variants appear to undergo endoplasmic-reticulum-associated degradation due to protein misfolding. They show reduced stability and fail to reach the membrane correctly, which can be partially restored for several variants by culturing cells at 27°C. Although RING and R-spondin domain mutations in RNF43/ZNRF3 are often considered to possess dominant-negative oncogene-like activity in cancers, our findings challenge this notion. When representative variants are heterozygously introduced into endogenous ZNRF3, their impact on β-catenin signaling mirrors that of heterozygous knockout, suggesting that the supposed dominant-negative effect is non-existent. In other words, so-called “hyperactivating” ZNRF3/RNF43 mutations behave as classical loss-of-function mutations at endogenous levels.
A New Model of Development of the Mammalian Ovary and Follicles

Ovarian follicular granulosa cells surround and nurture oocytes, and produce sex steroid hormones. It is believed that during development the ovarian surface epithelial cells penetrate into the ovary and develop into granulosa cells when associating with oogonia to form follicles. Using bovine fetal ovaries (n = 80) we identified a novel cell type, termed GREL for Gonadal Ridge Epithelial-Like. Using 26 markers for GREL and other cells and extracellular matrix we conducted immunohistochemistry and electron microscopy and chronologically tracked all somatic cell types during development. Before 70 days of gestation the gonadal ridge/ovarian primordium is formed by proliferation of GREL cells at the surface epithelium of the mesonephros. Primordial germ cells (PGCs) migrate into the ovarian primordium. After 70 days, stroma from the underlying mesonephros begins to penetrate the primordium, partitioning the developing ovary into irregularly-shaped ovigerous cords composed of GREL cells and PGCs/oogonia. Importantly we identified that the cords are always separated from the stroma by a basal lamina. Around 130 days of gestation the stroma expands laterally below the outermost layers of GREL cells forming a sub-epithelial basal lamina and establishing an epithelial-stromal interface. It is at this stage that a mature surface epithelium develops from the GREL cells on the surface of the ovary primordium. Expansion of the stroma continues to partition the ovigerous cords into smaller groups of cells eventually forming follicles containing an oogonium/oocyte surrounded by GREL cells, which become granulosa cells, all enclosed by a basal lamina. Thus in contrast to the prevailing theory, the ovarian surface epithelial cells do not penetrate into the ovary to form the granulosa cells of follicles, instead ovarian surface epithelial cells and granulosa cells have a common precursor, the GREL cell.
Comparison of C - reactive protein Levels in Chronic Periodontitis Patients with Normal Subjects

Background: Chronic periodontitis causes systemic inflammation and increases C-reactive protein (CRP). CRP has been implicated as a possible mediator of associating periodontitis and several systemic diseases. The aim of the present study was to investigate systemic levels of CRP in patients with chronic periodontitis in comparison to periodontally healthy individuals. Materials and methods: A total of 80 individuals were included in this study. 40 patients with severe chronic periodontitis aged 40, and 40 sex matched periodontally healthy subjects were recruited from the patients attending Dpartment of Periodontics, Faculty of Dentistry, Zahedan. Body Mass Index (BMI) was under 25 kg/m2 in all the patients and controls. Peripheral blood samples were taken and CRP levels were estimated in serum samples using the C - reactive protein – hs (CRP-hs) LATEX – High sensitivity (Biosystem S.A). Result: CRP levels in women in the test group (3.64 +- 2.77 mg/l) was significantly higher than the women in the control group (p < 0.001); however, the difference between males in the two study groups was not significant (p=0.13). Conclusion: Periodontitis results in higher systemic levels of CRP. Elevated inflammatory factor may increase inflammatory activity in atherosclerotic lesions and potentially increase the risk for cardiovascular events.
Inhibition of glycogen synthase kinase 3β induces dermal fibrosis by activation of the canonical Wnt pathway

Objective Glycogen synthase kinase 3β (GSK-3) regulates the phosphorylation and subsequent degradation of β-catenin, thereby preventing aberrant activation of the canonical Wnt pathway. A study was undertaken to define the role of GSK-3 in fibroblast activation and in experimental models of systemic sclerosis (SSc). Methods siRNA and specific inhibitors were used to inhibit GSK-3 in cultured fibroblasts and in mice. Activation of the canonical Wnt signalling was analysed by determining the levels of nuclear β-catenin and by measuring the mRNA levels of the Wnt target gene Axin2. The effects of GSK-3 on the release of collagen were evaluated in human dermal fibroblasts and in the mouse model of bleomycin-induced skin fibrosis in tight-skin-1 (tsk-1) mice. Results Targeting GSK-3 potently activated the canonical Wnt pathway in fibroblasts in vitro and in vivo. Inactivation of GSK-3 dose-dependently stimulated the release of collagen from cultured fibroblasts in a β-catenin-dependent manner and further resulted in progressive accumulation of collagen and dermal thickening in mice. Inhibition of GSK-3 aggravated experimental fibrosis in bleomycin-challenged mice and in tsk-1 mice. Conclusion Inhibition of GSK-3 activates the canonical Wnt pathway in fibroblasts, stimulates the release of collagen from fibroblasts, exacerbates experimental fibrosis and is sufficient to induce fibrosis. GSK-3 is therefore a key regulator of the canonical Wnt signalling in fibroblasts and inhibition of GSK-3 results in fibroblast activation and increased release of collagen.
International Journal of Recent Trends in Engineering , Vol 2 , No . 2 , November 2009 233 Classification of Microcalcifications Using Multi-Dimensional Genetic Association Rule

Breast cancer is a most common disease diagnosed in women. The Microcalcification Clusters (MCs) in the mammograms are one of the important early sign. The accurate detection of microcalcifications is a key problem in Computer Aided Detection (CAD). In this paper, we have proposed a novel association rule mining approach for classification of microcalcifications. Initially, the shape features are extracted from the digital mammograms. With these feature values association rules are constructed to develop a rule based system for classification of microcalcifications. A novel Multidimensional Genetic Association Rule Miner (MGARM) is proposed for rule construction. The result shows that the proposed rule-based approach reaches the classification accuracy over 85% and also demonstrates the use and effectiveness of association rule mining in image classification. Index terms – Mammograms, Microcalcification Clusters, Shape Features, Classification, Association Rule Mining, Genetic Algorithm.
Memory enhancement in Korsakoff's psychosis by clonidine: Further evidence for a noradrenergic deficit

Three drugs, d‐amphetamine, clonidine, and methysergide, which presumably enhance central noradrenergic activity by different pharmacological mechanisms, were administered to eight patients with the Korsakoff syndrome in a two‐week subacute, double‐blind, counterbalanced experiment to study the effects of these agents on memory function as measured by a neuropsychological test battery. Of the drugs tested, only clonidine, a putative alphanoradrenergic agonist, was associated with significant improvement in memory. The data are consistent with the hypothesis that damage to ascending norepinephrine‐containing neurons in the brainstem and diencephalon may be the basis for amnesia in Korsakoff's psychosis.
UV‐B‐type mutations and chromosomal imbalances indicate common pathways for the development of Merkel and skin squamous cell carcinomas

Two developmentally highly divergent nonmelanoma skin cancers, the epidermal squamous cell carcinomas (SCC) and the neuroendocrine Merkel cell carcinomas (MCC), occur late in life at sun‐exposed body sites. To determine whether these similarities may indicate common genetic alterations, we studied the genetic profile of 10 MCCs and analyzed 6 derived cell lines and 5 skin SCC lines by comparative genomic hybridization (CGH) and molecular genetic analyses. Although the MCCs were highly divergent—only 3 of the 10 tumors exhibited common gains and losses—they shared gain of 8q21‐q22 and loss of 4p15‐pter with the genetically much more homogeneous SCC lines. In addition, 2 of 5 SCC and 2 of 6 MCC lines exhibited UV‐B‐type‐specific mutations in the p53 tumor‐suppressor gene and a high frequency (9/11) of CC→TT double base changes in codon 27 of the Harvey (Ha)‐ras gene. Since 45% of the tumor lines were homozygous for this nucleotide substitution compared to 14% of the controls and in 1 MCC patient the wild‐type allele was lost in the tumor, this novel polymorphism may contribute to tumor development. On the other hand, loss of 3p, characteristic for SCCs, was rare in MCCs. Although in 2 of 3 SCC lines 3p loss was correlated with reduced expression of the FHIT (fragile histidine triad) gene, the potential tumor suppressor mapped to 3p14.2 and 2 MCC lines with normal 3p showed aberrant or no FHIT transcripts. Taken together, in addition to the common UV‐B‐specific mutations in the p53 and Ha‐ras gene, MCCs and SCCs also share chromosomal imbalances that may point to a common environmental‐derived (e.g., UV‐A) oxidative damage. © 2002 Wiley‐Liss, Inc.
Chemical Compound Classification with Automatically Mined Structure Patterns

In this paper we propose new methods of chemical structure classification based on the integration of graph database mining from data mining and graph kernel functions from machine learning. In our method, we first identify a set of general graph patterns in chemical structure data. These patterns are then used to augment a graph kernel function that calculates the pairwise similarity between molecules. The obtained similarity matrix is used as input to classify chemical compounds via a kernel machines such as the support vector machine (SVM). Our results indicate that the use of a pattern-based approach to graph similarity yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art approaches. In addition, the identification of highly discriminative patterns for activity classification provides evidence that our methods can make generalizations about a compound's function given its chemical structure. While we evaluated our methods on molecular structures, these methods are designed to operate on general graph data and hence could easily be applied to other domains in bioinformatics.
The Asymptotic IMSE of Averaging Series Regression

This paper investigates the asymptotic integrated mean squared error (IMSE) of series regression. Least-squares and averaging least-squares estimators are investigated. We characterize the optimal asymptotic IMSE using the optimal sequence of least-squares estimators and averaging weights. We find that under standard assumptions for series regression, the asymptotic IMSE of the optimal averaging estimator is considerably lower than that of the optimal least-squares estimator. The difference depends on the rate of decay of the series approximation error, the smoothness of the approximation error, and whether or not the averaging weights are constrained to be positive. When the approximation error is not smooth, we find significant reduction in asymptotic IMSE by allowing negative weights. ∗Research supported by the National Science Foundation. †Department of Economics, 1180 Observatory Drive, University of Wisconsin, Madison, WI 53706.