Miracle-dz/UniFAR-FTUs huggingface dataset:
Malignant Pigmented Villonodular Synovitis in the Knee - Report of a Case with Rapid Clinical Progression

Malignant pigmented villonodular synovitis (PVNS) (or malignant giant cell tumor of tendon sheath (GCTTS) is an extremely rare condition defined as a malignant lesion occurring with concomitant or previously documented PVNS at the same site. To date, only less than 20 cases have been reported in English literatures. We report a case of malignant PVNS in the knee in a 56-year-old woman with unpredictable rapid progression. This case raised a caution that when atypical components in specimens of recurrent benign PVNS are detected, even if low-grade or tiny, both pathologists and surgeons should consider the risk of malignant PVNS, which could display aggressive clinical progression.
Joint angle and delay estimation using shift-invariance properties

Assuming a multipath propagation scenario, we derive a closed-form subspace-based method for the simultaneous estimation of arrival angles and path delays from measured channel impulse responses, using knowledge of the transmitted pulse shape function and assuming a uniform linear array and uniform sampling. The algorithm uses a two-dimensional (2-D) ESPRIT-like shift-invariance technique to separate and estimate the phase shifts due to delay and direction-of-incidence, with automatic pairing of the two parameter sets. A straightforward extension to the multiuser case allows to connect rays to users as well.
Lifestyle counselling targeting infant's mother during the child's first year and offspring weight development until 4 years of age: a follow-up study of a cluster RCT

Objective To investigate the effect of intensified lifestyle counselling targeting infants' mothers on offspring weight development during the first 4 years of life. Design and setting Follow-up of a cluster-randomised controlled trial in primary care child health clinics during 2004–2006 in Finland. Participants received a follow-up survey during 2010 concerning weight and height measurements of their offspring. Number of clusters was six and the response rate to the follow-up 71.9% (N=64/89). Participants The participants (N=89) were mothers of infants aged 2–10 months. Intervention The intervention included individual counselling on diet and physical activity when the infant was 2–10 months of age and an option to attend supervised group exercise sessions. Primary and secondary outcome measures The authors analysed the secondary outcome of the intervention study: the weight development of the offspring. The primary outcome was the proportion of women returning to their prepregnancy weight by 10 months post partum, reported earlier. Results Multilevel mixed effect non-linear regression models included group, age of the child and interaction between group and age of the child. The increase of BMI z-score between 24 and 48 months was slower among the intervention group offspring (−0.034 to −0.002, p=0.028) as compared with control group. Z-scores for weight-for-length/height did not differ between groups when the period 0–48 months was analysed (p=0.23) but for the period of 24–48 months, between-group differences were significant (p=0.012). Conclusions Lifestyle counselling targeting mothers during the child's first year may be effective in slowing offspring weight gain until 4 years of age. However, larger studies are needed to confirm the findings which may have the potential in combatting the obesity epidemic. Trial registration number Current Controlled Trials ISRCTN21512277.
Zertifizierte Fortbildung

Claudia Lichtenwald Suchttherapeutin M.sc., RauchfreiTrainerin IFT/BZgA, Spezialambulanz für Tabakabhängigkeit, Klinikum der Universität München Nach wie vor ist Tabakkonsum ein allgegenwärtiges Problem, das optimistisch und besorgt zugleich stimmt. Grund zu Optimismus gibt der deutliche Rückgang der Zahlen in den letzten Jahren – sicher nicht zuletzt dank zahlreicher gesundheitspolitischer Bemühungen, die das Ziel hatten, Ausbreitung und Folgen der Erkrankung mittels Primär-, Sekundärund Tertiärprävention und Tabakkontrollpolitik einzudämmen. So zeigen epidemiologische Erhebungen in den letzten Jahren rückläuge Zahlen. In Deutschland ließ sich ein Rückgang konsumierter Zigaretten von 139.625 Millionen im Jahr 2018 auf 74.360 Millionen im Jahr 2000 verzeichnen – was zunächst beeindruckend erscheint [1]. Besorgnis scheint dennoch nach wie vor angebracht: Immer noch ist gerauchter Tabak das am zweithäugsten konsumierte Suchtmittel, mit gravierenden Folgen: Schätzungsweise 13,5% aller Todesfälle lassen sich auf direkte und indirekte Folgen des Rauchens zurückführen [1]. In Deutschland sterben jährlich noch etwa 121.000 Menschen an den Folgen des Rauchens [2]. Der geschätzte sozioökonomische Schaden beträgt allein in Deutschland 79 Milliarden Euro [3]. Und immer noch wartet die Erkrankung Tabakabhängigkeit mit zahlreichen Superlativen auf: So übersteigt die Mortalität jedes Jahr die Summe aller Todesfälle, die von AIDS, Alkohol, illegalen Drogen, Verkehrsunfällen, Morden und Suiziden zusammen verursacht werden [4]. Darüber hinaus ist Tabakkonsum deutschlandweit die häugste Ursache für einen frühzeitigen Tod [4] und die häugste SubstanzTabakentwöhnung
Zertifizierte Fortbildung

Sebastian Heiderich · Börge Bastian · Stephan Johannsen · Werner Klingler · Henrik Rüffert · Frank Schuster 1 Klinik für Anästhesiologie und Intensivmedizin, Medizinische Hochschule Hannover, Hannover, Deutschland 2 Klinik und Poliklinik für Anästhesiologie und Intensivtherapie, Universitätsklinikum Leipzig, Leipzig, Deutschland 3 Klinik und Poliklinik für Anästhesiologie, Intensivmedizin, Notfallmedizin und Schmerztherapie, UniversitätsklinikumWürzburg, Würzburg, Deutschland 4 Fachabteilung für Anästhesie, Intensivmedizin und Schmerztherapie, SRH Kliniken Landkreis Sigmaringen, Sigmaringen, Deutschland 5 Klinik für Anästhesie, Intensivmedizin und Schmerztherapie, Helios Klinikum Schkeuditz, Schkeuditz, Deutschland 6 Institut für Anästhesiologie, Intensivmedizin und Notfallmedizin, Donau-Isar-Klinikum DeggendorfDingolfing-Landau, Deggendorf, Deutschland
A statistical method of evaluating pronunciation proficiency for presentation in English

In this paper, we propose a statistical method of evaluating the pronunciation proficiency for presentation in English. We statistically analyze the utterances to find a combination that has a high correlation between an English teacher’s score and some acoustic features. We found that ratio of the likelihoods of free phoneme recognition by using native English HMMs and nonnative English HMMs was the best measure of pronunciation proficiency. The combination of likelihood ratio between native English HMMs and non-native English HMMs (concatenation of correct phone HMMs ), likelihood ratio between native English HMMs and non-native English HMMs (phoneme recognition ), phoneme recognition rate (correct rate) and word recognition rate (correct rate) are highly related to the English teacher’s score. We obtained a correlation coefficient of 0.781 with closed data and 0.743 with open data for speaker at sentence level, respectively. The coefficient was near the correlation between human’s scores; 0.691‘0.791. Index Terms: evaluation of pronunciation, English, HMM, statistical method
Development and experimental verification of a prognosis model for disulfidptosis-associated genes in HNSCC

Disulfidptosis is a newly discovered cell death pattern that has been less studied in head and neck squamous carcinoma (HNSCC). Exploring the molecular features of different subtypes of HNSCC based on disulfidptosis-associated genes (DAGs) is important for HNSCC. In addition, immunotherapy plays a pivotal role in the treatment of HNSCC. Exploring the sensitivity of immunotherapies and developing predictive models is essential for HNSCC. We analyzed the expression and mutational status of DAGs in 790 HNSCC patients and correlated the dates with clinical prognosis. HNSCC patients were divided into 2 groups based on their DAG expression. The relationship between DAGs, risk genes, and the immune microenvironment was analyzed using the CIBERSORT algorithm. A disulfidptosis risk model was constructed based on 5 risk genes using the LASSO COX method. To facilitate the clinical applicability of the proposed risk model, we constructed column line plots and performed stem cell correlation analysis and antitumor drug sensitivity analysis. Two different disulfidptosis-associated clusters were identified using consistent unsupervised clustering analysis. Correlations between multilayer DAG alterations and clinical characteristics and prognosis were observed. Then, a well-performing disulfidptosis-associated risk model (DAG score) was developed to predict the prognosis of HNSCC patients. We divided patients into high-risk and low-risk groups based on the DAG score and found that patients in the low-risk group were more likely to survive than those in the high-risk group (P < .05). A high DAG score implies higher immune cell infiltration and increased mutational burden. Also, univariate and multivariate Cox regression analyses revealed that the DAG score was an independent prognostic predictor for patients with HNSCC. Subsequently, a highly accurate predictive model was developed to facilitate the clinical application of DAG scores, showing good predictive and calibration power. Overall, we present a comprehensive overview of the DAG profile in HNSCC and develop a new risk model for the therapeutic status and prognosis of patients with HNSCC. Our findings highlight the potential clinical significance of DAG and suggest that disulfidptosis may be a potential therapeutic target for patients with HNSCC.
Overexpression of 14-3-3ζ Promotes Tau Phosphorylation at Ser262 and Accelerates Proteosomal Degradation of Synaptophysin in Rat Primary Hippocampal Neurons

β-amyloid peptide accumulation, tau hyperphosphorylation, and synapse loss are characteristic neuropathological symptoms of Alzheimer’s disease (AD). Tau hyperphosphorylation is suggested to inhibit the association of tau with microtubules, making microtubules unstable and causing neurodegeneration. The mechanism of tau phosphorylation in AD brain, therefore, is of considerable significance. Although PHF-tau is phosphorylated at over 40 Ser/Thr sites, Ser262 phosphorylation was shown to mediate β-amyloid neurotoxicity and formation of toxic tau lesions in the brain. In vitro, PKA is one of the kinases that phosphorylates tau at Ser262, but the mechanism by which it phosphorylates tau in AD brain is not very clear. 14-3-3ζ is associated with neurofibrillary tangles and is upregulated in AD brain. In this study, we show that 14-3-3ζ promotes tau phosphorylation at Ser262 by PKA in differentiating neurons. When overexpressed in rat hippocampal primary neurons, 14-3-3ζ causes an increase in Ser262 phosphorylation, a decrease in the amount of microtubule-bound tau, a reduction in the amount of polymerized microtubules, as well as microtubule instability. More importantly, the level of pre-synaptic protein synaptophysin was significantly reduced. Downregulation of synaptophysin in 14-3-3ζ overexpressing neurons was mitigated by inhibiting the proteosome, indicating that 14-3-3ζ promotes proteosomal degradation of synaptophysin. When 14-3-3ζ overexpressing neurons were treated with the microtubule stabilizing drug taxol, tau Ser262 phosphorylation decreased and synaptophysin level was restored. Our data demonstrate that overexpression of 14-3-3ζ accelerates proteosomal turnover of synaptophysin by promoting the destabilization of microtubules. Synaptophysin is involved in synapse formation and neurotransmitter release. Our results suggest that 14-3-3ζ may cause synaptic pathology by reducing synaptophysin levels in the brains of patients suffering from AD.
ORIGIN-DESTINATION MATRIX ESTIMATION FOR SRI LANKA USING MOBILE NETWORK BIG DATA

In this paper we discuss the potential of mobile network big data (MNBD) for providing insights for transportation planning that can supplement traditional methodologies. Adapting recently developed techniques for analyzing Big Data, we demonstrate their applicability to the Sri Lankan context. The paper assess the efficacy of two different methodologies for providing insights related to transportation planning from MNBD, and we validate the results using data from traditional transportation forecasting methods. We discuss the resultant limitations and the issues of attempting to leverage such data and propose various methods to address the constraints.
Altered fMRI Connectivity Dynamics in Temporal Lobe Epilepsy Might Explain Seizure Semiology

Temporal lobe epilepsy (TLE) can be conceptualized as a network disease. The network can be characterized by inter-regional functional connectivity, i.e., blood oxygen level-dependent (BOLD) signal correlations between any two regions. However, functional connectivity is not constant over time, thus computing correlation at a given time and then at some later time could give different results (non-stationarity). We hypothesized (1) that non-stationarities can be induced by epilepsy (e.g., interictal epileptic activity) increasing local signal variance and that (2) these transient events contribute to fluctuations in connectivity leading to pathological functioning, i.e., TLE semiology. We analyzed fMRI data from 27 patients with TLE and 22 healthy controls focusing on EEG-confirmed wake epochs only to protect against sleep-induced connectivity changes. Testing hypothesis (1), we identified brain regions where the BOLD signal variance was significantly greater in TLE than in controls: the temporal pole – including the hippocampus. Taking the latter as the seed region and testing hypothesis (2), we calculated the time-varying inter-regional correlation values (dynamic functional connectivity) to other brain regions and found greater connectivity variance in the TLE than the control group mainly in the precuneus, the supplementary and sensorimotor, and the frontal cortices. We conclude that the highest BOLD signal variance in the hippocampi is highly suggestive of a specific epilepsy-related effect. The altered connectivity dynamics in TLE patients might help to explain the hallmark semiological features of dyscognitive seizures including impaired consciousness (precuneus, frontal cortex), sensory disturbance, and motor automatisms (sensorimotor cortices, supplementary motor cortex). Accounting for the non-stationarity and state-dependence of functional connectivity are a prerequisite in the search for potential connectivity-derived biomarkers in TLE.
Cardiovascular Development and Disease Mvp-associated Filamin a Mutations Affect Flna-ptpn12 (ptp-pest) Interactions

Although the genetic basis of mitral valve prolapse (MVP) has now been clearly established, the molecular and cellular mechanisms involved in the pathological processes associated to a specific mutation often remain to be determined. The FLNA gene (encoding Filamin A; FlnA) was the first gene associated to non-syndromic X-linked myxomatous valvular dystrophy, but the impacts of the mutations on its function remain un-elucidated. Here, using the first repeats (1–8) of FlnA as a bait in a yeast two-hybrid screen, we identified the tyrosine phosphatase PTPN12 (PTP-PEST) as a specific binding partner of this region of FlnA protein. In addition, using yeast two-hybrid trap assay pull down and co-immunoprecipitation experiments, we showed that the MVP-associated FlnA mutations (G288R, P637Q, H743P) abolished FlnA/PTPN12 interactions. PTPN12 is a key regulator of signaling pathways involved in cell-extracellular matrix (ECM) crosstalk, cellular responses to mechanical stress that involve integrins, focal adhesion transduction pathways, and actin cytoskeleton dynamics. Interestingly, we showed that the FlnA mutations impair OPEN ACCESS 234 the activation status of two PTPN12 substrates, the focal adhesion associated kinase Src, and the RhoA specific activating protein p190RhoGAP. Together, these data point to PTPN12/FlnA interaction and its weakening by FlnA mutations as a mechanism potentially involved in the physiopathology of FlnA-associated MVP.
Dystrophic Spinal Deformities in a Neurofibromatosis Type 1 Murine Model

Despite the high prevalence and significant morbidity of spinal anomalies in neurofibromatosis type 1 (NF1), the pathogenesis of these defects remains largely unknown. Here, we present two murine models: Nf1flox/−;PeriCre and Nf1flox/−;Col.2. 3Cre mice, which recapitulate spinal deformities seen in the human disease. Dynamic histomorphometry and microtomographic studies show recalcitrant bone remodeling and distorted bone microarchitecture within the vertebral spine of Nf1flox/−;PeriCre and Nf1flox/−;Col2.3Cre mice, with analogous histological features present in a human patient with dystrophic scoliosis. Intriguingly, 36–60% of Nf1flox/−;PeriCre and Nf1flox/−;Col2.3Cre mice exhibit segmental vertebral fusion anomalies with boney obliteration of the intervertebral disc (IVD). While analogous findings have not yet been reported in the NF1 patient population, we herein present two case reports of IVD defects and interarticular vertebral fusion in patients with NF1. Collectively, these data provide novel insights regarding the pathophysiology of dystrophic spinal anomalies in NF1, and provide impetus for future radiographic analyses of larger patient cohorts to determine whether IVD and vertebral fusion defects may have been previously overlooked or underreported in the NF1 patient population.
Inconsistencies, Negations and Changes in Ontologies

Ontology management and maintenance are considered cornerstone issues in current Semantic Web applications in which semantic integration and ontological reasoning play a fundamental role. The ability to deal with inconsistency and to accommodate change is of utmost importance in real-world applications of ontological reasoning and management, wherein the need for expressing negated assertions also arises naturally. For this purpose, precise, formal definitions of the the different types of inconsistency and negation in ontologies are required. Unfortunately, ontology languages based on Description Logics (DLs) do not provide enough expressive power to represent axiom negations. Furthermore, there is no single, well-accepted notion of inconsistency and negation in the Semantic Web community, due to the lack of a common and solid foundational framework. In this paper, we propose a general framework accounting for inconsistency, negation and change in ontologies. Different levels of negation and inconsistency in DL-based ontologies are distinguished. We demonstrate how this framework can provide a foundation for reasoning with and management of dynamic ontologies.
Use of Accurate GPS Timing Based on Radial Basis Probabilistic Neural Network in Electric Systems

GPS based time reference provides inexpensive but highly-accurate timing and synchronization capability and meets requirements in power system fault location, monitoring, and control. In the present era of restructuring and modernization of electric power utilities, the applications of GIS/GPS technology in power industry are growing and covering several technical and management activities. Because of GPS receivers error sources are time variant, it is necessary to remove the GPS measurement noise. In this paper a Radial Basis Probabilistic Neural Network (RBPNN) has been applied to GPS receivers timing data for modeling of their timing error sources. This method estimates GPS receivers timing errors from their previous values. The efficiency of this algorithm is illustrated by experiments. For real-time restitution of GPS timing accuracy, the proposed method is implemented on designed hardwares. The experimental tests results on collected real data emphasizes that GPS timing RMS errors can be reduced from 300nsec and 200nsec to less than 160nsec and 41nsec, with and without SA, respectively.
Automatic gastroscopy video quality assessment

Automatic endoscope video analysis is an essential function for medical robot and computer-aided diagnosis system. However, the performance of these video analysis algorithms are often degraded by low quality endoscope images under the uncontrolled environment, where some of them are difficult even for human ourselves for analysis, such as over-saturated by reflection, too dark or obscure. In this paper, we formulate the problem of gastroscopy video quality evaluation as a supervised framework and detect non-informative frames from gastroscopy video sequence. In order to achieve this goal, HSV histograms, pyramid of histograms of orientation gradients and uniform Local Binary Pattern are extracted to represent frames. And then the Random Forests classifier is used to classify non-informative frames. Experimental results in our new gastroscopy video dataset with about 110000 frames demonstrate that the accuracy of our method is about 95% with the false positive rate lower than 1.3%.
A Study on the Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of Civil Structures

In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF) manner. In addition, the embedded software technology (EST) has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration) were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size.
Brain Protection During Surgery of the Aortic Arch

Abstract Deep hypothermia with circulatory arrest is the usual method of cerebral protection during replacement of the aortic arch. It has the enormous advantage of allowing the surgical repair to be carried out in a complete bloodless field with no aortic cross‐clamping. However, this method only gives the surgeon a limited period of time to carry out the aortic repair. It also requires that cardiopulmonary bypass be prolonged to cool and rewarm the patient which may be the cause of various complications. It has been proposed to improve the efficiency and the results of deep hypothermia, by associating it with retrograde cerebral perfusion of the brain with oxygenated blood through the superior vena cava. This technique improves the tolerance of the brain to cold ischemia and increases the time of repair allowed to the surgeon.
Channelizer structure in DRFM systems for real signals

In this paper, a channelized DRFM structure for DRFM(Digital Radio Frequency Memory) systems is presented. The novelty of this design is the modifications in the structure for supporting real signals without increasing the system delay. One of the most important parameters of a DRFMsystem is the system latency and the proposed architecture has less latency then the structures presented in the literature. The proposed architecture is implemented on a Virtex-6 SX475T and can run at 200 MHz clock speed.