Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlation between malignant peritoneal cytology and survival in patients with uterine leiomyosarcoma and endometrial stromal sarcoma

Objective This study aimed to examine the correlation between malignant peritoneal cytology and overall survival among patients with uterine leiomyosarcoma and endometrial stromal sarcoma. Methods Patients with uterine leiomyosarcoma and endometrial stromal sarcoma between January 2010 and December 2016 were identified from the Surveillance, Epidemiology, and End Results database. The multiple imputation method was used to address missing values. Propensity score matching was conducted to balance baseline data between the malignant and negative peritoneal cytology groups. The prognostic significance of malignant peritoneal cytology was evaluated using Cox regression, random survival forest, and subgroup analyses. Results Among 733 eligible patients, 8% (59/733) had malignant peritoneal cytology, increasing to 20% (42/209) in advanced cases. Before and after propensity score matching, patients with malignant peritoneal cytology had significantly lower 5-year overall survival rates and shorter median survival time than patients with negative peritoneal cytology. Multivariate Cox regression revealed that malignant peritoneal cytology (hazard ratio 2.03, 95% confidence interval 1.29 to 3.20, p=0.002) was an independent prognostic factor for uterine leiomyosarcoma and endometrial stromal sarcoma. Random survival forest further indicated that, among the factors analyzed, peritoneal cytology status was second only to the International Federation of Gynecology and Obstetrics (FIGO) stage in terms of prognostic prediction. Finally, subgroup analyses substantiated the correlation between malignant peritoneal cytology and unfavorable overall survival in most subgroups. Conclusions Malignant peritoneal cytology status was an important prognostic factor complementing FIGO stage and was associated with a reduction in overall survival. Peritoneal cytology evaluation during hysterectomy may be recommended for prognosis estimation for uterine leiomyosarcoma and endometrial stromal sarcoma.
Kiroll: A Gaze-Based Instrument for Quadriplegic Musicians Based on the Context-Switching Paradigm

In recent years, Accessible Digital Musical Instruments (ADMIs) designed for motor-impaired individuals that incorporate gaze-tracking technologies have become more prevalent. To ensure a reliable user experience and minimize delays between actions and sound production, interaction methods must be carefully studied. This paper presents Kiroll, an affordable and open-source software ADMI specifically designed for quadriplegic users. Kiroll can be played by motor-impaired users through eye gaze for note selection and breath for sound control. The interface features the infinite keyboards context-switching interaction method, which exploits the smooth-pursuit capabilities of human eyes to provide an indefinitely scrolling layout so as to resolve the Midas Touch issue typical of gaze-based interaction. This paper outlines Kiroll’s interaction paradigm, features, implementation processes, and design approach.
Onset Detection for String Instruments Using Bidirectional Temporal and Convolutional Recurrent Networks

Recent work in note onset detection has centered on deep learning models such as recurrent neural networks (RNN), convolutional neural networks (CNN) and more recently temporal convolutional networks (TCN), which achieve high evaluation accuracies for onsets characterized by clear, well-defined transients, as found in percussive instruments. However, onsets with less transient presence, as found in string instrument recordings, still pose a relatively difficult challenge for state-of-the-art algorithms. This challenge is further exacerbated by a paucity of string instrument data containing expert annotations. In this paper, we propose two new models for onset detection using bidirectional temporal and recurrent convolutional networks, which generalise to polyphonic signals and string instruments. We perform evaluations of the proposed methods alongside state-of-the-art algorithms for onset detection on a benchmark dataset from the MIR community, as well as on a test set from a newly proposed dataset of string instrument recordings with note onset annotations, comprising approximately 40 minutes and over 8,000 annotated onsets with varied expressive playing styles. The results demonstrate the effectiveness of both presented models, as they outperform the state-of-the-art algorithms on string recordings while maintaining comparative performance on other types of music.
Impact of an audio-haptic strap to augment immersion in VR video gaming: a pilot study

With the development, for the general public, of haptic devices allowing to transform audio signals into vibrations, the question of their capacity to immerse users or players more is raised. This study aims to evaluate how haptic feedback associated with audio reinforces our immersion in a virtual space, more specifically, in VR video games. A preliminary study was carried out with an haptic belt: the Woojer’s Strap Edge. 17 participants had to play two VR shooting games, with and without haptic feedback, and then answer questionnaires between each session. A post-hoc questionnaire was proposed to get free feedback from the participants. Results show no significant differences between with and without haptic feedback conditions in the between-session questionnaires, however the final questionnaire reveals a very strong inter-subject variability when it comes to the perception and appreciation of haptic feedback.
Evaluating the Total Phenolic, Protein Contents, Antioxidant and Pharmacological Effects of Cynodon dactylon Extracts Against Escherichia coli and Staphylococcus aureus

Abstract The study was aimed to characterize the antioxidant and anti-microbial activities of Cynodon dactylon with special reference on its precise biochemical analysis. Physiological analysis that total carotenoids content (0.3884 ± 0.0172 mg/g), total chlorophyll content (6.1460 ± 0.2915 mg/g), total phenolic contents (13.4703 ± 0.1494 mg/g), chlorophyll a (3.7708 ± 0.1528 mg/g, catalase (CAT) contents (40.2844 ± 0.1515 units/mg), total anthocyanin contents (5.0166 ± 0.2966 g–1 FW) total soluble proteins (2.9916 ± 0.1734 mg/g) and total flavonoids content (TFC) (4.7863 ± 0.0442 μg/g) was found higher in the leaves of the Cynodon dactylon whereas, chlorophyll b (2.4881 ± 0.1326 mg/g) was found higher in the stem of Cynodon dactylon, while, peroxidase (POD) contents (81.8763 ± 4.6609 units/mg) and superoxidase dismutase (SOD) activity (80.4346 ± 5.9367 units/mg) was investigated higher in roots of Cynodon dactylon. The anti-microbial activity of Cynodon dactylon extracts was performed using a good diffusion technique against two microbial strains. Among all the plant extracts, the methanolic extracts showed a maximum inhibition zone (26.87 mm) against anti-bacterial strain Escherichia coli whereas n-hexane extract showed a maximum inhibition zone (17.88 mm) against anti-fungal strain Candida albicans. This study reported the antimicrobial activity of Cynodon dactylon against some common pathogens such as Staphylococcus aureus, Escherichia coli, and Candida albicans, which are highly associated with nosocomial infection. From the given results it is concluded that Cynodon dactylon could be exploited in pharmacology due to its antioxidant and anti-microbial properties.
Punctuated global tropical cyclone activity over the past 5,000 years

There are now a substantial number of millennial scale records of tropical cyclones from a variety of locations globally. Some of these, such as those in the Atlantic and Gulf of Mexico, show patterns of long‐term, generally intense, tropical cyclone (TC) behaviour that have been suggested to be due to either variations in ENSO or shifts in the position of the Atlantic High pressure system and the jet stream. Comparisons are made here of the sedimentary overwash records from the Gulf of Mexico and Atlantic Ocean Basin with the overwash records from the north‐west Pacific and beach ridge records from the south‐west Pacific and south east Indian Ocean basins. There is a substantial degree of synchroneity in global intense TC behaviour over the past 3,000 to 5,000 years. One of the most striking aspects of these records is they all display extended alternating periods (centuries to millennia) of relative quiescence and heightened intense TC activity irrespective of both the resolution and type of long‐term TC record. The cause(s) of this punctuated activity are at present difficult to identify but are likely exogenic in origin rather than due to an intrinsic aspect of the records or the methods used to derive them. The identification of punctuated global long‐term TC behaviour is important for understanding future TC activity and for assessing risk to coastal communities.
Stratigraphy and geologic history of Mercury

The geologic evolution of Mercury based on the Mariner-10 mission data is discussed. As reconstructed through photogeological analysis of global geologic relations of rock-stratigraphic units, Mercury's geologic history is shown to involve intensive early impact bombardment and widespread resurfacing by volcanic lavas. Evidence is presented to indicate that this volcanic activity essentially ended as much as 3 Gyr ago, with most of the major geologic events being completed within the first 1 to 1.5 Gyr of Mercurian history.
Distributional Impact of Globalization-Induced Migration

One of the contentious issues about the globalization process is the mechanism by which globalization affects poverty and inequality. This paper explores one of the various strands of the globalization–inequality–poverty nexus. Using microlevel survey data from over 300 poor households in the small village of Umuluwe (about 30 miles west of the regional capital of Owerri) in Southeast Nigeria, the paper investigates whether individuals who migrate from the village to take advantage of the urban-biased globalization process do better than non-migrant villagers. The paper concludes that …/
An ultrasensitive genetically encoded voltage indicator uncovers the electrical activity of non-excitable cells

Genetically encoded voltage indicators (GEVIs) are powerful, non-invasive tools for recording action potentials in excitable cells. However, most animal cell types are non-excitable, and yet variations in the membrane potential are biologically relevant in these cells as well. Resolving such small voltage signals demands GEVIs with exceptionally high sensitivity. In this study, we applied structure-guided engineering to the GEVI ASAP3 to generate rEstus, a sensor with optimized brightness, voltage sensitivity, and voltage range. rEstus is most sensitive in the resting voltage range of non-excitable cells, exhibits a 3.6-fold improvement in fast voltage spike detection, and allows for absolute voltage calibration at the single-cell level. Using rEstus, we resolved endogenous voltage fluctuations in several non-excitable cell types and demonstrate that correlation analysis of these optically recorded fluctuations provides an easy, non-invasive, real-time readout of electrical gap-junction coupling. Our work provides greatly enhanced tools and methods for the non-invasive study of electrical signaling in excitable and non-excitable cells.
A Confounder Controlled Machine Learning Approach: Group Analysis and Classification of Schizophrenia and Alzheimer’s Disease using Resting-State Functional Network Connectivity

Resting-state functional magnetic resonance imaging (rs-fMRI) has increasingly been used to study both Alzheimer’s disease (AD) and schizophrenia (SZ). While most rs-fMRI studies being conducted in AD and SZ compare patients to healthy controls, it is also of interest to directly compare AD and SZ patients with each other to identify potential biomarkers shared between the disorders. However, comparing patient groups collected in different studies can be challenging due to potential confounds, such as differences in the patient’s age, scan protocols, etc. In this study, we compared and contrasted resting-state functional network connectivity (rs-FNC) of 162 patients with AD and late mild cognitive impairment (LMCI), 181 schizophrenia patients, and 315 cognitively normal (CN) subjects. We used confounder-controlled rs-FNC and applied machine learning algorithms (including support vector machine, logistic regression, random forest, and k-nearest neighbor) and deep learning models (i.e., fully-connected neural networks) to classify subjects in binary and three-class categories according to their diagnosis labels (e.g., AD, SZ, and CN). Our statistical analysis revealed that FNC between the following network pairs is stronger in AD compared to SZ: subcortical-cerebellum, subcortical-cognitive control, cognitive control-cerebellum, and visual-sensory motor networks. On the other hand, FNC is stronger in SZ than AD for the following network pairs: subcortical-visual, subcortical-auditory, subcortical-sensory motor, cerebellum-visual, sensory motor-cognitive control, and within the cerebellum networks. Furthermore, we observed that while AD and SZ disorders each have unique FNC abnormalities, they also share some common functional abnormalities that can be due to similar neurobiological mechanisms or genetic factors contributing to these disorders’ development. Moreover, we achieved an accuracy of 85% in classifying subjects into AD and SZ where default mode, visual, and subcortical networks contributed the most to the classification and accuracy of 68% in classifying subjects into AD, SZ, and CN with the subcortical domain appearing as the most contributing features to the three-way classification. Finally, our findings indicated that for all classification tasks, except AD vs. SZ, males are more predictable than females.
Novel Cyclic Homogeneous Oscillation Detection Method for High Accuracy and Specific Characterization of Neural Dynamics

Detecting temporal and spectral features of neural oscillations is essential to understanding dynamic brain function. Traditionally, the presence and frequency of neural oscillations are determined by identifying peaks over 1/f noise within the power spectrum. However, this approach solely operates within the frequency domain and thus cannot adequately distinguish between the fundamental frequency of a non-sinusoidal oscillation and its harmonics. Non-sinusoidal signals generate harmonics, significantly increasing the false-positive detection rate — a confounding factor in the analysis of neural oscillations. To overcome these limitations, we define the fundamental criteria that characterize a neural oscillation and introduce the Cyclic Homogeneous Oscillation (CHO) detection method that implements these criteria based on an auto-correlation approach that determines the oscillation’s periodicity and fundamental frequency. We evaluated CHO by verifying its performance on simulated sinusoidal and non-sinusoidal oscillatory bursts convolved with 1/f noise. Our results demonstrate that CHO outperforms conventional techniques in accurately detecting oscillations. Specifically, we determined the sensitivity and specificity of CHO as a function of signal-to-noise ratio (SNR). We further assessed CHO by testing it on electrocorticographic (ECoG, 8 subjects) and electroencephalographic (EEG, 7 subjects) signals recorded during the pre-stimulus period of an auditory reaction time task and on electrocorticographic signals (6 SEEG subjects and 6 ECoG subjects) collected during resting state. In the reaction time task, the CHO method detected auditory alpha and pre-motor beta oscillations in ECoG signals and occipital alpha and pre-motor beta oscillations in EEG signals. Moreover, CHO determined the fundamental frequency of hippocampal oscillations in the human hippocampus during the resting state (6 SEEG subjects). In summary, CHO demonstrates high precision and specificity in detecting neural oscillations in time and frequency domains. The method’s specificity enables the detailed study of non-sinusoidal characteristics of oscillations, such as the degree of asymmetry and waveform of an oscillation. Furthermore, CHO can be applied to identify how neural oscillations govern interactions throughout the brain and to determine oscillatory biomarkers that index abnormal brain function.
Surface boundary layer evolution and near‐inertial wind power input

Deep weakly stratified surface layers in the Southern Ocean complicate the identification of the mixed-layer base, which is critical in estimating the wind power input through the ocean surface. Typically used mixed-layer depth criteria often ignore weak stratification, which traps momentum near the surface and significantly enhances the near-inertial-band wind power input. The thickness of the active mixing-layer, the turbulent layer in contact with wind stress, is needed to accurately estimate wind power input. A fine-density-threshold criterion of 0.005 kg m−3, just above the noise floor of most autonomous instruments, was applied to observed profiles of potential density to estimate the thickness of the actively mixing-layer. Vertical shear, Langmuir cells, and buoyant convection are investigated as possible mechanisms maintaining turbulence within the mixing-layer. Over 90% of the observed variance of the mixing-layer thickness is explained by either shear-driven entrainment, which is simulated using the Price-Weller-Pinkel model, or by a parameterization of downwelling plumes due to Langmuir cell convergence. In general, surface buoyancy fluxes are too weak to drive mixed-layer turbulence. Comparison of National Oceanographic Data Center (NODC) climatological mixed-layer thickness to those determined using the 0.005 kg m−3 density threshold suggests a multiplicative seasonally varying correction of 1.5–3.5 should be applied to wind work estimates made using the NODC climatological mixed-layer thickness in the Southern Ocean.
Heparan-6-O-Endosulfatase 2 Promotes Invasiveness of Head and Neck Squamous Carcinoma Cell Lines in Co-Cultures with Cancer-Associated Fibroblasts

Local invasiveness of head and neck squamous cell carcinoma (HNSCC) is a complex phenomenon supported by interaction of the cancer cells with the TME. We and others have shown that CAFs are a component of the TME that can promote local invasion in HNSCC and other cancers. Here we report that the secretory enzyme Sulf-2 directly affects the CAF-supported invasion of HNSCC cell lines SCC35 and Cal33 into Matrigel. The Sulf-2 knockout (KO) cells differ from their wild type counterparts in their spheroid growths and formation, and the Sulf-2-KO leads to decreased invasion in a spheroid co-culture model with the CAF. Next, we investigated whether a fucosylated chondroitin sulfate isolated from the sea cucumber Holothuria Floridana (HfFucCS), affects activity of the Sulf-2 enzyme. Our results show that HfFucCS not only inhibits efficiently the Sulf-2 enzymatic activity but, like the Sulf-2 knockout, inhibits Matrigel invasion of the SCC35 and Cal33 cells co-cultured with the primary HNSCC CAF. These findings suggest that the heparan 6-O-endosulfatases regulate local invasion and could be therapeutically targeted with the inhibitory activity of a marine glycosaminoglycan. Simple Summary Local invasion of cancer cells is an early step in the cascade of metastasis that requires cooperation of multiple factors and cell types in the tumor microenvironment (TME). One important factor is the crosstalk of cancer cells with cancer associated fibroblasts (CAF). Here we explore the impact of a secretory enzyme heparan-6-O-endosulfatase 2 (Sulf-2) on the CAF-assisted invasion of head and neck squamous carcinoma cells into matrigel. We show that Sulf-2 knock out inhibits cancer cell invasion in a spheroid co-culture model and we identified a novel Sulf-2 inhibitor that, in the same model, limits cancer cell invasion.
Neither Williston nor Dollo: mandibular complexity from stem tetrapods to modern amphibians

Directional trends in evolution have long captured the attention of biologists, and are particularly interesting when they reflect fundamental developmental processes that underlie morphological change. Here, we apply deep time data and a phylogenetic comparative framework to assess two fundamental “laws” – Williston’s law of phenotypic simplification and Dollo’s law of irreversibility – in the tetrapod mandible, a structure that has sustained the same primary function of feeding for nearly 400 million years. In spite of this conserved function, the tetrapod mandible has undergone numerous morphological and compositional changes during and since the initial water-to-land transition around 390Ma. To quantify these shifts, we reconstructed the compositional ev olution of the mandible with 31 traits scored in 568 species from early tetrapods through to modern amphibians, thereby capturing immense developmental and ecological diversity as well as an excellent fossil record. Mandibular complexity and jaw disparity are highest at the base of the tetrapod tree and generally decrease through time, with stasis dominating over the last ~160M years. Nonetheless, we find a lack of support for Williston’s and Dollo’s laws, with loss and gain of jaw components equally likely throughout the course of early tetrapod and amphibian evolution. Combined, our results demonstrate that evolutionary patterns of mandibular complexity are more nuanced than either Williston’s or Dollo’s laws allow. Thus, laws of simplification are too crude to capture the evolutionary processes underlying the evolution of even a functionally conserved structure through deep time. Summary The lower jaw is a key innovation in vertebrate evolution with a unifying primary function: feeding. In spite of this conserved function, the jaw is extremely diverse in shape and composition. In limbed vertebrates (tetrapods), the jaw evolves from a complex structure comprising multiple elements and high numbers of teeth towards a simpler structure comprising few elements and generally fewer teeth. Superficially, this pattern suggests support for both Williston’s and Dollo’s laws of phenotypic simplification and irreversibility, respectively. However, we find a lack of support for either law in the jaw of the earliest tetrapods and amphibians, adding to growing literature refuting overly simplified “laws” governing organismal evolution.
Rupture model of the 2011 Mineral, Virginia, earthquake from teleseismic and regional waveforms

We independently invert teleseismic P waveforms and regional crustal phases to examine the finite fault slip model for the 2011 Mw 5.8 Mineral, Virginia, earthquake. Theoretical and empirical Green's functions are used for the teleseismic and regional models, respectively. Both solutions show two distinct sources each about 2 km across and separated by 2.5 km. The source at the hypocenter is more localized in the regional model leading to a higher peak slip of 130 cm and higher average stress drop of 250 bars compared with 86 cm and 150 bars for the same source in the teleseismic model. Both sources are centered at approximately 8 km depth in the regional model, largely below the aftershock distribution. In the teleseismic model, the sources extend updip to approximately 6 km depth, into the depth range of the aftershocks. The rupture velocity is not well resolved but appears to be near 2.7 km/s.
Subthreshold dynamics of Hodgkin-Huxley and Izhikevich spiking neuron models

We compare the subthreshold dynamics of the conductance-based Hodgkin-Huxley neuron model commonly used for accurate biological modelling, with those of the computationally simpler model proposed by E.M. Izhikevich for inclusion in large neural network simulations. We ﬁnd that both models deliver similar results under a variety of inputs, with the maximal membrane potential difference less than 1 mV for a step input of 10, and nearly an order of magnitude lower for an alpha input. We also ﬁnd that both models exhibit a low sensitivity to high frequency noise.