Miracle-dz/UniFAR-FTUs huggingface dataset:
Neurourology and Urodynamics

Funding information Shanghai Zhongshan Hospital Research Foundation of China, Grant/Award Number: (023); Shanghai Xuhui Medical Technology Fund of China, Grant/Award Number: (SHXH201601); National Natural Science Foundation of China, Grant/Award Numbers: (No.NSFC30700831), (No.NSFC81573418); Shanghai Municipal Health Bureau Youth Fund, Grant/Award Number: (2006Y16) Abstract Aims: The present study was designed to study changes and its potential mechanisms in human bladder smooth muscle subjected to stretch. Methods: Bioinformatics analyses including differential expression analysis, overrepresentation enrichment analysis, principal component analysis, and weighted gene coexpression network analysis were used to analyze a microarray dataset (GSE47080) of partial bladder outlet obstruction (pBOO) in rat to find the potential changes of gene expressions. Bladder from pBOOmodel and human bladder smooth muscle cells (HBSMCs) subjected to sustained prolonged stretch were collected for Western blot analysis, real‐time polymerase chain reaction, and fluorescence analysis to verify the changes of gene expressions and preliminarily study the potential role of signaling pathway regulation in treatment of pBOO. Results: The bioinformatics analysis showed that chronic obstruction activated mitogen‐activated protein kinase pathway and changed cytoskeleton structure in bladder smooth muscle. In in vivo experiments in mice, pBOO was verified by cystometry. Partial BOO activated the extracellular signal‐regulated kinase (ERK)/ p90 ribosomal S6 protein kinase (p90RSK)/nuclear factor‐κB (NF‐κB) signaling pathway in DM. The messenger RNA (mRNA) expressions of contractile phenotypic proteins increased after pBOO. In in vitro experiments of HBSMCs, mechanical stretch activated ERK/p90RSK/NF‐κB in HBSMCs in a time‐dependent manner. The mRNA expressions of α‐smooth muscle actin and SM22 also increased and filamentous actin (F‐actin) polymerization was enhanced as well. Inhibition of ERK/ p90RSK/NF‐κB pathway reversed mechanical stretch‐induced changes of contractile phenotypic expression and F‐action polymerization. Conclusions: Continuous stretch increases expressions of contractile phenotypic proteins and promotes the polymerization of F‐actin. This process partially goes through ERK/p90RSK/NF‐κB pathway.
Neurourology and Urodynamics

Correspondence Israel Franco, MD, 789 Howard St, FMP 300, New Haven, CT 06519. Email: Israel.franco@yale.edu Abstract Introduction: There is a large amount of intra and inter observer variability in defining curve shapes. This study aims to evaluate inter and intra rater reliability (RR) on evaluating uroflow curves in a broad spectrum of international practitioners. Methods: Eight hundred sixty‐four questionnaires were sent by email to health professionals that care for children with voiding dysfunction. It included demographic questions and 11 different uroflow curves and two duplicates. Results: Four hundred forty‐one emails were opened and 29.5% of those responded. Seventy percent of responders were physicians, including 46% pediatric urologists. Europe, South America, North America, Oceania, and Asia represented respondents. For the repeated bell smooth curve the intra rater agreement was 82.1% utilizing the International Children's Continence Society (ICCS) classification and 92.3% for the shape of the curve (bell, plateau, and tower [BPT]) (P= .04). For the repeated interrupted plateau curve it was 69.5% and 97.5% for ICCS and for the continuity of the curve (smooth or fractionated [SF]) classifications, respectively (P< .001). The curves were then divided into two groups for evaluation of inter RR. For the set of seven smooth curves, the inter RR was low in all classifications with α= . 282, . 497, and . 242 for ICCS, SF, and BPT, respectively. The group of six fractionated curves showed a slightly better agreement with α= . 533, . 404, and . 662 for ICCS, SF, and BPT, respectively. Conclusions: This is the largest study looking at inter and intra RR of uroflows in a disparate population of readers. It was evident from our findings that inter RR was poor and additionally intra RR was equally poor, indicating the unreliability of uroflow shapes to be used for research purposes.
VMNet: Realistic Emulation of Wireless Sensor Networks

Many research activities on wireless sensor networks (WSNs) need detailed performance statistics about protocols, systems, and applications; however, current simulation tools and testbeds lack mechanisms to report these statistics realistically and conveniently. To address this need, we have developed a WSN emulator, VMNet. VMNet emulates networked sensor nodes at the level of CPU clock cycles and executes the binary code of real applications directly. It emulates the radio channel with loss and noise as well as emulates the peripherals in sufficient detail. Moreover, VMNet takes parameter values from the real world and logs detailed runtime information of emulated nodes. Consequently, the application performance, both in response time and in power consumption, is reported realistically in VMNet, as demonstrated by our comparison studies with real sensor networks
Statistical Model for the Mobile Channel Composite Envelope

Currently, among the main three affectors of transmission quality (represented by the mean probability of a bit error) for a particular digital modulation format, such as eg. GMSK, fast fading seems to be by far mostly dealt with, in particular, analytically, while such an analysis for the other two aspects, namely, slow fading and quasideterministic attenuation of the signal is usually too complex, often resulting with analytic solutions of mainly academic relevance, rather than practical, while numerical and/or simulation methods are very time-consuming and not explicitly conclusive. Therefore, in this paper, we focus simultaneous fast Nakagamian and slow (shadowing) fading, providing the explicit analytical expression for the probability density function of a mobile channel signal composite envelope, and consequently the according assessment of the transmission performance, that is finally supported by extensive computer experiments for characteristic parameter values of fast and slow fading.
Improvements in the channel Equalizer Performance Using Modified LMS and BP Algorithms

This paper introduces a comparative study in the communication channel equalization problem. Different types of linear and nonlinear channel models including linear and nonlinear phase are considered in this study. Adaptive linear filter and neural networks are used to imitate different equalizer models. The equalizer models are tested using different transmitted signals with different characteristics. A modification in the learning algorithm driving each model is proposed to obtain the minimum mean-squared error in the recovery process of transmitted signals. The modified algorithms have demonstrated their effectiveness compared to other conventional techniques especially in the noisy environment.
Audio Information Retrieval (AIR) Tools

Most of the work in music Information Retrieval (MIR) and analysis has been performed using symbolic representation like MIDI. The recent advances in computing power and network connectivity have made large amounts of raw digital audio data available in the form of unstructured monolithic sound files. In this work the focus is on tools that work directly on real world audio data without attempting to transcribe the music. To distinguish from symbolic−based music IR for the remainder of the paper we use the term audio IR (AIR) to refer to techniques that work directly on raw audio signals. Obviously these signals can contain music as well as other types of audio like speech. We describe a series of tools based on current and newly developed techniques for AIR integrated under MARSYAS, our framework for audio analysis. For related work refer to (Foote, 1999). The tools developed are based on Signal Processing, Pattern Recognition and Visualization techniques. Finally, due to the immature state of the available techniques and to the inherent complexity of the task it is important to take advantage of the human user in the system. We have developed two user interfaces to integrate and improve our techniques: an augmented sound editor and TimbreGrams a novel graphical representation for soundfiles. The previously unpublished contributions of this paper are the genre classification method, the segmentation− based retrieval and summarization, and the definition of the TimbreGram. Feature−based audio analysis The developed analysis tools are based on the calculation of short−time feature vectors. The signal is processed in small chunks so that its statistical characteristics are relativily stable. For each chunk some form of spectral analysis is performed and based on that analysis a vector of feature values is calculated. In our system features based on FFT (Fast Fourier Transform) analysis, MPEG filterbank analysis, LPC (Linear Predictive Coding) and MFCC (Mel−Frequency cepstrum coefficients) are supported. In addition derivatives and running statistics are used to express temporal changes. The flexible architecture of MARSYAS allows the easy integration and experimentation of new features. Based on the calculated features different types of audio analysis processes can be performed.
Effects of Beetroot Juice Supplementation on a 30-s High-Intensity Inertial Cycle Ergometer Test

Background: Beetroot juice (BJ) is rich in inorganic nitrates and has proved effective at increasing blood nitric oxide (NO) levels. When used as a supplement BJ has shown an ergogenic effect on cardiorespiratory resistance exercise modalities, yet few studies have examined its impact on high intensity efforts. Objective: To assess the effects of BJ intake on anaerobic performance in a Wingate test. Methods: Fifteen trained men (age 21.46 ± 1.72 years, height 1.78 ± 0.07 cm and weight 76.90 ± 8.67 kg) undertook a 30-s maximum intensity test on an inertial cycle ergometer after drinking 70 mL of BJ (5.6 mmol NO3−) or placebo. Results: Despite no impacts of BJ on the mean power recorded during the test, improvements were produced in peak power (6%) (p = 0.034), average power 0–15 s (6.7%) (p = 0.048) and final blood lactate levels (82.6%) (p < 0.001), and there was a trend towards a shorter time taken to attain peak power (−8.4%) (p = 0.055). Conclusions: Supplementation with BJ has an ergonomic effect on maximum power output and on average power during the first 15 s of a 30-s maximum intensity inertial cycle ergometer test.
Aging amplifies a gut microbiota immunogenic signature linked to heightened inflammation

Aging is associated with low-grade inflammation that increases the risk of infection and disease, yet the underlying mechanisms remain unclear. Gut microbiota composition shifts with age, harboring microbes with varied immunogenic capacities. We hypothesized the gut microbiota acts as an active driver of low-grade inflammation during aging. Microbiome patterns in aged mice strongly associated with signs of bacterial-induced barrier disruption and immune infiltration, including marked increased levels of circulating lipopolysaccharide (LPS)-binding protein (LBP) and colonic calprotectin. Ex vivo immunogenicity assays revealed that both colonic contents and mucosa of aged mice harbored increased capacity to activate toll-like receptor 4 (TLR4) whereas TLR5 signaling was unchanged. We found patterns of elevated innate inflammatory signaling (colonic Il6, Tnf, Tlr4) and endotoxemia (circulating LBP) in young germ-free mice after 4 weeks of colonization with intestinal contents from aged mice compared with young counterparts, thus providing a direct link between aging-induced shifts in microbiota immunogenicity and host inflammation. Additionally, we discovered that the gut microbiota of aged mice exhibited unique responses to a broad-spectrum antibiotic challenge (Abx), with sustained elevation in Escherichia (Proteobacteria) and altered TLR5 immunogenicity 7 days post-Abx cessation. Together, these data indicate that old age results in a gut microbiota that differentially acts on TLR signaling pathways of the innate immune system. We found that these age-associated microbiota immunogenic signatures are less resilient to challenge and strongly linked to host inflammatory status. Gut microbiota immunogenic signatures should be thus considered as critical factors in mediating chronic inflammatory diseases disproportionally impacting older populations.
The white matter fiber tract deforms most in the perpendicular direction during in vivo volunteer impacts

White matter (WM) tract-related strains are increasingly used to quantify brain mechanical responses, but their dynamics in live human brains during in vivo impact conditions remain largely unknown. Existing research primarily looked into the normal strain along the WM fiber tracts (i.e., tract-oriented normal strain), but it is rarely the case in reality that the fiber tract only endures tract-oriented normal strain. In this study, we aim to extend the measurement of WM deformation by quantifying the normal strain perpendicular to the fiber tract (i.e., tract-perpendicular normal strain) and the shear strain along and perpendicular to the fiber tract (i.e., tract-oriented shear strain and tract-perpendicular shear strain, respectively). To achieve this, we combine the three-dimensional strain tensor from the tagged magnetic resonance imaging (tMRI) with the diffuse tensor imaging (DTI) from an open-access dataset, including 44 volunteer impacts under neck rotations (N = 30, peak angular acceleration: 228.6 ± 8.3 rad/s2) and neck extensions (N = 14, peak angular acceleration: 185.5 ± 59.2 rad/s2). The strain tensor is rotated to the coordinate system with one axis aligned with DTI-revealed fiber orientation and then four tract-related strain measures are calculated. The results show that tract-perpendicular normal strain peaks are the largest among the four strain types and tract-oriented normal strains are the lowest. The peak values for tract-oriented normal strain, tract-perpendicular normal strain, tract-oriented shear strain, and tract-perpendicular shear strain are 0.020 ± 0.005, 0.028 ± 0.007, 0.024 ± 0.006 and 0.023 ± 0.006 under the neck rotation, and 0.013 ± 0.002, 0.019 ± 0.004, 0.016 ± 0.003, and 0.017 ± 0.003 under the neck extension, respectively. The distribution of tract-related strains is affected by the head loading mode. Our study presents a comprehensive in vivo strain quantification towards a multifaceted understanding of WM dynamics. For the first time, we find the WM fiber tract deforms most in the perpendicular direction, illuminating new fundamental of brain mechanics. The reported strain results can be used to evaluate the biofidelity of computational head models, especially those intended to predict brain strains under non-injurious conditions. Highlights We combine multimodal imaging analyses with continuum mechanics to quantify in vivo white matter tract-related deformation. We present three-dimensional, full-field normal and shear strains along and perpendicular to the white matter fiber tracts in 44 volunteer impacts. We find the white matter fiber tract deforms most in the perpendicular direction.
FLIGHTED: Inferring Fitness Landscapes from Noisy High-Throughput Experimental Data

Machine learning (ML) for protein design requires large protein fitness datasets generated by high-throughput experiments for training, fine-tuning, and bench-marking models. However, most models do not account for experimental noise inherent in these datasets, harming model performance and changing model rankings in benchmarking studies. Here, we develop FLIGHTED, a Bayesian method for generating fitness landscapes with calibrated errors from noisy high-throughput experimental data. We apply FLIGHTED to single-step selection assays such as phage display and to a novel high-throughput assay DHARMA that ties fitness to base editing activity. Our results show that FLIGHTED robustly generates fitness landscapes with accurate errors. We demonstrate that FLIGHTED improves model performance and enables the generation of protein fitness datasets of up to 106 variants with DHARMA. FLIGHTED can be used on any high-throughput assay and makes it easy for ML scientists to account for experimental noise when modeling protein fitness.
ChemPrint: An AI-Driven Framework for Enhanced Drug Discovery

In the evolving landscape of drug discovery, traditional methods face significant challenges due to low efficiency and high resource demands. This study introduces our GALILEO AI drug discovery platform and its foundational ChemPrint model, designed to improve the efficiency of drug discovery. Addressing the challenges of low hit rates and the difficulty in exploring novel chemical spaces, this platform adopts adaptive molecular embeddings and stringent model training environments to enhance predictive capabilities and navigate uncharted molecular territories. We validate this approach through a case study targeting the AXL and BRD4 oncology targets, where ChemPrint achieved a 45.5% in vitro hit rate and identified 20 novel acting compounds. These compounds exhibited substantial chemical novelty, with an average Tanimoto similarity score of 0.32 to their training set, significantly diverging from known compounds and demonstrating ChemPrint’s capability to extrapolate, surpassing traditional benchmarks and industry standards. This underscores the platform’s ability to bridge the gap between the potential of AI and its practical application in therapeutic discovery.
BAX and BAK expression triggers multiple IRE1 signaling outputs under ER stress

Adaptation to endoplasmic reticulum (ER) stress depends on the activation of the unfolded protein response (UPR) stress sensor inositol-requiring enzyme 1 alpha (IRE1). IRE1 is a central ER stress sensors, that signals through the activation of its RNase domain to catalyze the splicing the mRNA encoding the transcription factor X-box binding protein 1 (XBP1), resulting on the expression of a stable and active transcription factor termed XBP1s. The kinetics and amplitude of IRE1 signaling are regulated by different posttranslational modifications and the physical interaction of different factors. Early studies demonstrated that the expression of the proapoptotic proteins BAX and BAX enhance UPR signaling. However, the possible effects on the RNase activity were not defined. Here we provide preliminary evidence indicating that BAX and BAK deficiency increases the in 10 folds the threshold of ER stress to induce XBP1 mRNA splicing, and the upregulation of its target genes. In addition, the degradation of RIDD substrates was strongly reduced in BAX and BAK null cells. BAX and BAK double deficiency also attenuated the levels of IRE1 phosphorylation under mild ER stress. These results reinforce previous findings indicating that proapoptotic BAX and BAK have alternative functions at the ER regulating the UPR.
Feedback and Feedforward Regulation of Interneuronal Communication

We formulate a mechanistic model capturing the dynamics of neurotransmitter release in a chemical synapse. The proposed modeling framework captures key aspects such as the random arrival of action potentials (AP) in the presynaptic (input) neuron, probabilistic docking and release of neurotransmitter-filled vesicles, and clearance of the released neurotransmitter from the synaptic cleft. Feedback regulation is implemented by having the released neurotransmitter impact the vesicle docking rate that occurs biologically through “autoreceptors” on the presynaptic membrane. Our analytical results show that these feedbacks can amplify or buffer fluctuations in neurotransmitter levels depending on the relative interplay of neurotransmitter clearance rate with the AP arrival rate and the vesicle replenishment rate, with faster clearance rates leading to noise amplification. We next consider a postsynaptic (output) neuron that fires an AP based on integrating upstream neurotransmitter activity. Investigating the postsynaptic AP firing times, we identify scenarios that lead to band-pass filtering, i.e., the output neuron frequency is maximized at intermediate input neuron frequencies. We extend these results to consider feedforward regulation where in addition to a direct excitatory synapse, the input neuron also impacts the output indirectly via an inhibitory interneuron, and we identify parameter regimes where feedforward neuronal networks result in band-pass filtering.
A self-organizing semantic map for information retrieval

Self-organizing Semantic Map for Information Retrieval Xia Lin Dagobert Soergel Gary Marchionini College of Library and Information Services University of Maryland College Park, A neural network’s unsupervised learning algorithm, Kohonen’s feature map, is applied to constructing a selforganizing semantic map for information retrieval. The semantic map visualizes semantic relationships between input documents, and has properties of economic representation of data with their interrelationships. The potentials of the semantic map include using the map as a retrieval interface for an online bibliographic system. A prototype system that demonstrates this potential is described.
Asynchronous Decentralized 20 Questions for Adaptive Search

This paper considers the problem of adaptively searching for an unknown target using multiple agents connected through a time-varying network topology. Agents are equipped with sensors capable of fast information processing, and we propose a decentralized collaborative algorithm for controlling their search given noisy observations. Specifically, we propose decentralized extensions of the adaptive query-based search strategy that combines elements from the 20 questions approach and social learning. Under standard assumptions on the time-varying network dynamics, we prove convergence to correct consensus on the value of the parameter as the number of iterations go to infinity. The convergence analysis takes a novel approach using martingale-based techniques combined with spectral graph theory. Our results establish that stability and consistency can be maintained even with one-way updating and randomized pairwise averaging, thus providing a scalable low complexity method with performance guarantees. We illustrate the effectiveness of our algorithm for random network topologies.
Stratigraphical studies on Lake Iidesjärvi sediments. Part II. Geological and mineralogical characteristics of the sedimentary sequence

VUORINEN, ANTTI, UUSINOKA, RAIMO AND ALHONEN, PENTTI 1983: Stratigraphical studies on Lake Iidesjärvi sediments. Part II. Geochemical and mineralogical characteristics of the sedimentary sequence. Bull. Geol. Soc. Finland 55, 2, 141-156. This paper presents data on the geochemical and mineralogical characteristics of a core pertinent to the limnological history of Lake Iidesjärvi in the town of Tampere (S. Finland). The geochronology together with the pollen and diatom stratigraphy of its sediment sequence have been given earlier (Alhonen 1981). The new palaeolimnological results from Lake Iidesjärvi show the anthropogenic enrichment of heavy metals such as Cd, Cu, Hg, P b and Zn in the topmost sulphide-banded clay-gyttja of its lithostratigraphy. This cultural eutrophication was interpreted by studying extraction kinetics of Fe, Si, Ca, Mg, K, Cu and Zn using ammonium oxalate and hydroxylammonium chloride plus acetic acid solutions. The productivity history of Lake Iidesjärvi was studied by the determinations of ignition loss, sedimentary chlorophyll and sedimentary humus. The mineralogical composition of the lithostratigraphy shows that the presence of clay minerals, particularly vermiculite, with extractable Mg, Fe and Na has probably led to minero-eutrophy of Lake Iidesjärvi since its isolation from the Ancylus Lake in agreement with the results of the diatom stratigraphy.