Miracle-dz/UniFAR-FTUs huggingface dataset:
Ancient DNA from an Early Neolithic Iberian population supports a pioneer colonization by first farmers

The Neolithic transition has been widely debated particularly regarding the extent to which this revolution implied a demographic expansion from the Near East. We attempted to shed some light on this process in northeastern Iberia by combining ancient DNA (aDNA) data from Early Neolithic settlers and published DNA data from Middle Neolithic and modern samples from the same region. We successfully extracted and amplified mitochondrial DNA from 13 human specimens, found at three archaeological sites dated back to the Cardial culture in the Early Neolithic (Can Sadurní and Chaves) and to the Late Early Neolithic (Sant Pau del Camp). We found that haplogroups with a low frequency in modern populations—N* and X1—are found at higher frequencies in our Early Neolithic population (∼31%). Genetic differentiation between Early and Middle Neolithic populations was significant (FST∼0.13, P < 10−5), suggesting that genetic drift played an important role at this time. To improve our understanding of the Neolithic demographic processes, we used a Bayesian coalescence‐based simulation approach to identify the most likely of three demographic scenarios that might explain the genetic data. The three scenarios were chosen to reflect archaeological knowledge and previous genetic studies using similar inferential approaches. We found that models that ignore population structure, as previously used in aDNA studies, are unlikely to explain the data. Our results are compatible with a pioneer colonization of northeastern Iberia at the Early Neolithic characterized by the arrival of small genetically distinctive groups, showing cultural and genetic connections with the Near East.
The spatio‐temporal and subcellular expression of the candidate Down syndrome gene Mnb/Dyrk1A in the developing mouse brain suggests distinct sequential roles in neuronal development

It is widely accepted that the neurological alterations in Down syndrome (DS) are principally due to modifications in developmental processes. Accordingly, a large part of the research on DS in recent years has focused on chromosome 21 genes that influence brain development. MNB/DYRK1A is one of the genes on human chromosome 21 that has raised most interest, due to its relationship with the brain functions that are altered in DS. Although a number of interesting experimental mouse models for DS are being developed, we still know little about the expression of Mnb/Dyrk1A during mouse brain development. Here, we report that Mnb/Dyrk1A displays a rather dynamic spatio‐temporal expression pattern during mouse central nervous system development. Our data indicate that Mnb/Dyrk1A is specifically expressed in four sequential developmental phases: transient expression in preneurogenic progenitors, cell cycle‐regulated expression in neurogenic progenitors, transient expression in recently born neurones, and persistent expression in late differentiating neurones. Our results also suggest that the subcellular localization of MNB/DYRK1A, including its translocation to the nucleus, is finely regulated. Thus, the MNB/DYRK1A protein kinase could be a key element in the molecular machinery that couples sequential events in neuronal development. This rich repertoire of potential functions in the developing central nervous system is suitable to be linked to the neurological alterations in DS through the use of mouse experimental models.
Intracellular MMP‐2 Activity in Skeletal Muscle Is Associated With Type II Fibers

Matrix metalloproteinase 2 (MMP‐2) is a proteolytic enzyme implicated in motility, differentiation, and regeneration of skeletal muscle fibers through processing of extracellular substrates. Although MMP‐2 has been found to be localized intracellularly in cardiomyocytes where the enzyme is thought to contribute to post‐ischemic loss of contractility, little is known about intracellular MMP‐2 activity in skeletal muscle fibers. In the present study we demonstrate intracellular MMP‐2 in normal skeletal muscle by immunohistochemical staining. Immunogold electron microscopic analyses indicated that the enzyme was concentrated in Z‐lines of the sarcomers, in the nuclear membrane, and in mitochondria. By use of in situ zymography, we found that gelatinolytic activity in muscle fibers was co‐localized with immunofluorecent staining for MMP‐2. Staining for MMP‐9, the other member of the gelatinase group of the MMPs, was negative. The broad‐spectrum metalloprotease inhibitor EDTA and the selective gelatinase inhibitor CTT2, but not the cysteine inhibitor E64, strongly reduced the gelatinolytic activity. The intracellular gelatinolytic activity was much more prominent in fast twitch type II fibers than in slow twitch type I fibers, and there was a decrease in intracellular gelatinolytic activity and MMP‐2 expression in muscles from mice exposed to high intensity interval training. Together our results indicate that MMP‐2 is part of the intracellular proteolytic network in normal skeletal muscle, especially in fast twitch type II fibers. Further, the results suggest that intracellular MMP‐2 in skeletal muscle fibers is active during normal homeostasis, and affected by the level of physical activity. J. Cell. Physiol. 230: 160–169, 2015. © 2014 Wiley Periodicals, Inc.
Sir2 mediates apoptosis through JNK-dependent pathways in Drosophila

Increased expression of the histone deacetylase sir2 has been reported to extend the life span of diverse organisms including yeast, Caenorhabditis elegans, and Drosophila melanogaster. A small molecule activator of Sir2, resveratrol, has also been suggested to extend the fitness and survival of these simple model organisms as well as mice fed high calorie diets. However, other studies in yeast have shown that Sir2 itself may prevent life extension, and high expression levels of Sir2 can be toxic to yeast and mouse cells. This conflicting evidence highlights the importance of understanding the mechanisms by which Sir2 expression or activation affects survival of organisms. To investigate the downstream signaling pathways affected by Sir2 in Drosophila, we generated transgenic flies expressing sir2. Here, we show that overexpression of sir2 in Drosophila promotes caspase-dependent but p53-independent apoptosis that is mediated by the JNK and FOXO signaling pathways. Furthermore, we find that a loss-of-function sir2 mutant partially prevents apoptosis induced by UV irradiation in the eye. Together, these results suggest that Sir2 normally participates in the regulation of cell survival and death in Drosophila.
Transcription of a vaccinia virus late promoter template: requirement for the product of the A2L intermediate-stage gene

Evidence is presented that a 26-kDa protein encoded by the vaccinia virus A2L open reading frame, originally shown to be one of three intermediate-stage genes that together can transactivate late-stage gene expression in transfection assays (J. G. Keck, C. J. Baldick, and B. Moss, Cell 61:801-809, 1990), is required for in vitro transcription of a template with a late promoter. The critical step in this analysis was the preparation of an extract containing all the required factors except for the A2L protein. This extract was prepared from cells infected with a recombinant vaccinia virus expressing the bacteriophage T7 RNA polymerase in the presence of the DNA synthesis inhibitor cytosine arabinoside and transfected with plasmids containing the two other known transactivator genes, A1L and G8R, under T7 promoter control. Reaction mixtures made with extracts of these cells had background levels of late transcription activity, unless they were supplemented with extracts of cells transfected with the A2L gene. Active transcription mixtures were also made by mixing extracts from three sets of cells, each transfected with a gene (A1L, A2L, or G8R) encoding a separate factor, indicating the absence of any requirement for their coexpression. To minimize the possibility that the A2L protein functions indirectly by activating another viral or cellular protein, this gene was expressed in insect cells by using a baculovirus vector. The partially purified recombinant protein complemented the activity of A2L-deficient cell extracts. Recombinant A1L, A2L, and G8R proteins, all produced in insect cells, together complemented extracts from mammalian cells containing only viral early proteins, concordant with previous in vivo transfection data.
A time‐dependent discrimination index for survival data

To derive models suitable for outcome prediction, a crucial aspect is the availability of appropriate measures of predictive accuracy, which have to be usable for a general class of models. The Harrell's C discrimination index is an extension of the area under the ROC curve to the case of censored survival data, which owns a straightforward interpretability. For a model including covariates with time‐dependent effects and/or time‐dependent covariates, the original definition of C would require the prediction of individual failure times, which is not generally addressed in most clinical applications. Here we propose a time‐dependent discrimination index Ctd where the whole predicted survival function is utilized as outcome prediction, and the ability to discriminate among subjects having different outcome is summarized over time. Ctd is based on a novel definition of concordance: a subject who developed the event should have a less predicted probability of surviving beyond his/her survival time than any subject who survived longer. The predicted survival function of a subject who developed the event is compared to: (1) that of subjects who developed the event before his/her survival time, and (2) that of subjects who developed the event, or were censored, after his/her survival time. Subjects who were censored are involved in comparisons with subjects who developed the event before their observed times. The index reduces to the previous C in the presence of separation between survival curves on the whole follow‐up. A confidence interval for Ctd is derived using the jackknife method on correlated one‐sample U‐statistics.
Energy Saving With Network Coding Design Over Rayleigh Fading Channel

In this paper, we investigate the energy minimization problem with and without network coding (NC) while satisfying the transmission rate requirements in a bidirectional cellular relay network, where a group of mobile users communicate with a base station across a relay node. In particular, we consider the Rayleigh fading channel model and adopt a comprehensive power consumption model in the radio frequency transmission. We show that the problem of minimizing the energy consumption of the bidirectional cellular relay network in NC and non-NC (NNC) schemes can be formulated as a unified sum of fractional programming problem, which is of high complexity to solve in general. Fortunately, we derive the sufficient condition under which the problem is a convex optimization problem, and thus can be solved quite efficiently. In the case that the energy minimizing problem is not convex, we decompose it into two subproblems, and propose an iterative algorithm to solve it. Simulation results show that in NNC and NC schemes, under all configurations of power parameters, the performance of the iterative algorithm is close to the exhaustive search method; but its running time is much shorter than the exhaustive search method. Furthermore, compared with the maximum power transmission policy, the iterative algorithm achieves a maximum energy reduction of 75%–82%. Last but not least, we compare the energy performance of NNC and NC schemes and discuss the effect of the iteration number and the relay node placement.
ARIMA modeling of the performance of different photovoltaic technologies

In this paper, the performance of different technology photovoltaic (PV) systems was modeled using autoregressive integrated moving average (ARIMA) processes. Measurements from mono-crystalline (mono-c-Si), multi-crystalline (multi-c-Si) and amorphous (a-Si) silicon, cadmium telluride (CdTe) and copper indium gallium diselenide (CIGS) systems were used to construct monthly dc performance ratio (PR) time-series, from outdoor measurements. Each PR time-series was modeled a) with multiplicative ARIMA, b) with linear regression and c) with Seasonal-Trend Decomposition by Loess (STL) using the first 4 years of each time-series in order to compare the accuracy of the different methods. The models were used to forecast the PR of the 5th year of the different PV technologies and the results from the aforementioned statistical methods were compared based on the root-mean-square error (RMSE). The results showed that ARIMA produced the lowest RMSE for crystalline silicon (c-Si) technologies, whereas for thin-film technologies, STL was more accurate. The results from ARIMA also showed that thin-film technologies were optimally modeled with identical model orders, whereas for c-Si, each technology required a different optimal model order.
Clopidogrel inhibits platelet-leukocyte adhesion and plateletdependent leukocyte activation

Summary Clopidogrel is considered to be an important therapeutic advance in anti-platelet therapy. We investigated whether inhibition by clopidogrel results in a reduced capacity of platelets to adhere and stimulate pro-atherothrombotic and inflammatory functions in polymorphonuclear leukocytes (PMN) and in monocytes (MN). An eventual effect on these processes could further substantiate anti-atherothrombotic properties of this drug. The effects of clopidogrel or of its active metabolite were investigated on ADP or thrombin receptor-induced platelet activation and on platelet-leukocyte interactions ex vivo in the mouse or in vitro in isolated human cells or whole blood, respectively. Clopidogrel inhibited platelet aggregation, expression of P-selectin, platelet-PMN adhesion and platelet-dependent ROS production in mouse PMN. Similarly pretreatment of human platelets with the active metabolite of clopidogrel in vitro resulted in a profound inhibition of platelet P-selectin expression, platelet-PMN adhesion and production of ROS by PMN. Pretreatment with the active metabolite of clopidogrel significantly impaired the ability of platelets to up-regulate the expression of TF procoagulant activity in MN, in a washed cell system. Moreover, the active metabolite of clopidogrel inhibited rapidTF exposure on platelet as well as on leukocyte surfaces in whole blood. By reducing platelet-dependent up-regulation of inflammatory and pro-atherothrombotic functions in leukocytes, clopidogrel may reduce inflammation that underlies the chronic process of atherosclerosis and its acute complications.
Identifying potentially shockable rhythms without interrupting cardiopulmonary resuscitation*

Objective:Current versions of automated external defibrillators (AEDs) mandate interruptions of chest compression for rhythm analyses because of artifacts produced by chest compressions. Interruption of chest compressions reduces likelihood of successful resuscitation by as much as 50%. We sought a method to identify a shockable rhythm without interrupting chest compressions during cardiopulmonary resuscitation (CPR). Design:Experimental study. Setting:Weil Institute of Critical Care Medicine, Rancho Mirage, CA. Subjects:None. Interventions:Electrocardiographs (ECGs) were recorded in conjunction with AEDs during CPR in human victims. A shockable rhythm was defined as disorganized rhythm with an amplitude >0.1 mV or, if organized, at a rate of ≥180 beats/min. Wavelet-based transformation and shape-based morphology detection were used for rhythm classification. Morphologic consistencies of waveform representing QRS components were analyzed to differentiate between disorganized and organized rhythms. For disorganized rhythms, the amplitude spectrum area was computed in the frequency domain to distinguish between shockable ventricular fibrillation and nonshockable asystole. For organized rhythms, in victims in whom the absence of a heartbeat was independently confirmed, the heart rate was estimated for further classification. Measurements and Main Results:To derive the algorithm, we used 29 recordings on 29 patients from the Creighton University ventricular tachyarrhythmia database. For validation, the algorithm was tested on an independent population of 229 victims, including recordings of both ECG and depth of chest compressions obtained during suspected out-of-hospital sudden death. The recordings included 111 instances in which the ECG was corrupted during chest compressions. A shockable rhythm was identified with a sensitivity of 93% and a specificity of 89%, yielding a positive predictive value of 91%. A nonshockable rhythm was identified with a sensitivity of 89%, a specificity of 93%, and a positive predictive value of 91% during uninterrupted chest compression. Conclusions:The algorithm fulfilled the potential lifesaving advantages of allowing for uninterrupted chest compression, avoiding pauses for automated rhythm analyses before prompting delivery of an electrical shock.
OLE: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning

Deep neural networks trained using a softmax layer at the top and the cross-entropy loss are ubiquitous tools for image classification. Yet, this does not naturally enforce intra-class similarity nor inter-class margin of the learned deep representations. To simultaneously achieve these two goals, different solutions have been proposed in the literature, such as the pairwise or triplet losses. However, these carry the extra task of selecting pairs or triplets, and the extra computational burden of computing and learning for many combinations of them. In this paper, we propose a plug-and-play loss term for deep networks that explicitly reduces intra-class variance and enforces inter-class margin simultaneously, in a simple and elegant geometric manner. For each class, the deep features are collapsed into a learned linear subspace, or union of them, and inter-class subspaces are pushed to be as orthogonal as possible. Our proposed Orthogonal Low-rank Embedding (OLÃ‰) does not require carefully crafting pairs or triplets of samples for training, and works standalone as a classification loss, being the first reported deep metric learning framework of its kind. Because of the improved margin between features of different classes, the resulting deep networks generalize better, are more discriminative, and more robust. We demonstrate improved classification performance in general object recognition, plugging the proposed loss term into existing off-the-shelf architectures. In particular, we show the advantage of the proposed loss in the small data/model scenario, and we significantly advance the state-of-the-art on the Stanford STL-10 benchmark.
Adsorption of fibronectin onto polymethylmethacrylate and promotion of Staphylococcus aureus adherence

Recent data suggest that fibronectin may favor Staphylococcus aureus infection by promoting attachment to either injured tissues or implanted foreign bodies. We studied the quantitative adsorption of fibronectin onto polymethylmethacrylate (PMMA) cover slips by using a 125I-labeled preparation of the purified plasma glycoprotein. Fibronectin in buffer solutions showed a high affinity to PMMA coverslips. Adherence of S. aureus Wood 46 was studied on PMMA pre-exposed to fibronectin, using an assay specifically adapted to the cover slip model. Whereas S. aureus adherence in an albumin-containing buffer was less than or equal to 10(3) CFU on control uncoated cover slips, adherence in the same medium increased up to maximum of 7.7 X 10(4) CFU on cover slips preincubated in a solution of fibronectin (125-micrograms/ml). At intermediate fibronectin concentrations, bacterial adherence was a linear function of both the quantity in solution and of the quantity adsorbed on the PMMA cover slips. The presence of human serum proteins, as represented by a fibronectin-depleted pool, essentially prevented adsorption of radiolabeled fibronectin on PMMA and subsequent bacterial adherence on the cover slips. Precoating of PMMA with denatured collagen resulted in increased fibronectin adsorption on PMMA, even in the presence of serum proteins, and S. aureus adherence was optimal on such surfaces. Collagen may therefore play a role as a cofactor contributing to S. aureus adherence onto fibronectin-coated substrata or foreign bodies.
Baicalin-loaded PEGylated lipid nanoparticles: characterization, pharmacokinetics, and protective effects on acute myocardial ischemia in rats

Abstract Context: Baicalin has many pharmacological activities, including protective function against myocardial ischemia by antioxidant effects and free radical scavenging activity. However, its rapid elimination half-life in plasma and poor water solubility limits its clinical efficacy. Objective: Novel baicalin-loaded PEGylated nanostructured lipid carriers (BN-PEG-NLC) were developed to improve bioavailability of BN, to prolong retention time in vivo and to enhance its protective effect. Methods: In this study, BN-PEG-NLC were prepared by the emulsion-evaporation and low temperature-solidification method using a mixture of glycerol monostearate and polyethylene glycol monostearate as solid lipids, and oleic acid as the liquid lipid. The physicochemical properties of NLC were characterized. The pharmacokinetic and pharmacodynamic behaviors of BN-PEG-NLC or BN-NLC were evaluated in acute MI rats. Results and discussion: The particle size, zeta potential, and entrapment efficiency for BN-PEG-NLC were observed as 83.9 nm, −32.1 mV, and 83.5%, respectively. The release profiles of BN from both BN-PEG-NLC and BN-NLC were fitted to the Ritger–Peppas modal, which presented burst release initially and prolonged release afterwards. Pharmacokinetics results indicated that BN-PEG-NLC exhibited a 7.2-fold increase in AUC in comparison to BN solution, while a 3-fold increase in comparison to BN-NLC. Biodistribution results revealed that BN-PEG-NLC exhibited higher heart drug concentration compared with BN-NLC as well as BN solution. In the present study, BN-PEG-NLC significantly ameliorated infarct size. Conclusion: The results of the present study imply that PEG-NLC could be the biocompatible carriers for heart-targeted drug delivery to improve myocardial ischemia.
Myocardial contractile and metabolic properties of familial hypertrophic cardiomyopathy caused by cardiac troponin I gene mutations: a simulation study

Familial hypertrophic cardiomyopathy (FHC) is an inherited disease that is caused by sarcomeric protein gene mutations. The mechanism by which these mutant proteins cause disease is uncertain. Experimentally, cardiac troponin I (CTnI) gene mutations mainly alter myocardial performance via increases in the Ca2+ sensitivity of cardiac contractility. In this study, we used an integrated simulation that links electrophysiology, contractile activity and energy metabolism of the myocardium to investigate alterations in myocardial contractile function and energy metabolism regulation as a result of increased Ca2+ sensitivity in CTnI mutations. Simulation results reproduced the following typical features of FHC: (1) slower relaxation (diastolic dysfunction) caused by prolonged [Ca2+]i and force transients; (2) higher energy consumption with the increase in Ca2+ sensitivity; and (3) reduced fatty acid oxidation and enhanced glucose utilization in hypertrophied heart metabolism. Furthermore, the simulation indicated that in conditions of high energy consumption (that is, more than an 18.3% increase in total energy consumption), the myocardial energetic metabolic network switched from a net consumer to a net producer of lactate, resulting in a low coupling of glucose oxidation to glycolysis, which is a common feature of hypertrophied hearts. This study provides a novel systematic myocardial contractile and metabolic analysis to help elucidate the pathogenesis of FHC and suggests that the alterations in resting heart energy supply and demand could contribute to disease progression.