Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances with extended and controlled release formulations of antiepileptics in the elderly

ABSTRACT Introduction: As a matter of course, elderly people are more sensitive to both the pharmacological and toxicological effects of pharmacotherapy. A senior’s treatment, therefore, requires more attention compared to younger adults. Extended release (ER) formulations of anti-epileptic drugs (AEDs) have been developed to improve safety, efficacy and long-term adherence. In senior patients, ER AEDs are used to treat epilepsy, psychiatric conditions, and neuropathic pain. However, very limited clinical evidence is available on the use of these ER AEDs in these populations. Areas covered: The authors of this paper have identified clinical studies of ER AED formulations used in elderly populations through literature searches looking, both, at their use in epileptic and non-epileptic indications. Additionally, immediate release (IR) and ER formulations of AEDs were compared whenever possible. Expert opinion: The broad use of ER AED formulations in elderly patients with swallowing problems is limited by the fact that ER AED tablets (or capsules) must not be cut, crushed or chewed. The only exception is the ER formulation of valproate or topiramate which can be mixed with soft food. Although, the ER formulations of AEDs seem better tolerated than the IR equivalents, a possibility of numerous interactions with drugs prescribed for other reasons must be carefully considered.
Korean Journal for Food Science of Animal Resources

In this study, the antimicrobial activity of a bacteriocin produced by Enterococcus faecalis KT11, isolated from traditional Kargı Tulum cheese, was determined, and bacteriocin KT11 was partially characterized. The results showed that bacteriocin KT11 was antagonistically effective against various Gram-positive and Gramnegative test bacteria, including vancomycinand/or methicillin-resistant bacteria. The activity of bacteriocin KT11 was completely abolished after treatment with proteolytic enzymes (proteinase K, α-chymotrypsin, protease and trypsin), which demonstrates the proteinaceous nature of this bacteriocin. Additionally, bacteriocin KT11 remained stable at pH values ranging from 2 to 11 and after autoclaving at 121°C for 30 min. In addition, the activity of bacteriocin KT11 was stable after treatment with several surfactants (EDTA, SDS, Triton X-100, Tween 80 and urea) and organic solvents (chloroform, propanol, methanol, ethyl alcohol, acetone, hexane and ethyl ether). Cell-free supernatant of E. faecalis KT11 was subjected to ammonium sulfate precipitation and then desalted by using a 3.5-kDa cut-off dialysis membrane. The bacteriocin activity was determined to be 711 AU/mL in the dialysate. After tricine-SDS-PAGE analysis, one peptide band, which had a molecular weight of ~3.5 kDa, exhibited antimicrobial activity. Because the bacteriocin KT11, isolated from E. faecalis KT11, exhibits a broad antimicrobial spectrum, heat stability and stability over a wide pH range, this bacteriocin can be used as a potential bio-preservative in foods. Additionally, bacteriocin KT11 alone or in combination with conventional antibiotics may provide a therapeutic option for the treatment of multidrug-resistant clinical pathogens after further in vivo studies.
Induction of Mycobacterium Tuberculosis Lipid-Specific T Cell Responses by Pulmonary Delivery of Mycolic Acid-Loaded Polymeric Micellar Nanocarriers

Mycolic acid (MA), a major lipid component of Mycobacterium tuberculosis (Mtb) cell wall, can be presented by the non-polymorphic antigen presenting molecule CD1b to T cells isolated from Mtb-infected individuals. These MA-specific CD1b-restricted T cells are cytotoxic, produce Th1 cytokines, and form memory populations, suggesting that MA can be explored as a potential subunit vaccine candidate for TB. However, the controlled elicitation of MA-specific T cell responses has been challenging due to difficulties in the targeted delivery of lipid antigens and a lack of suitable animal models. In this study, we generated MA-loaded micellar nanocarriers (MA-Mc) comprised of self-assembled poly(ethylene glycol)-bl-poly(propylene sulfide; PEG-PPS) copolymers conjugated to an acid sensitive fluorophore to enhance intracellular delivery of MA to phagocytic immune cells. Using humanized CD1 transgenic (hCD1Tg) mice, we found these nanobiomaterials to be endocytosed by bone marrow-derived dendritic cells (DCs) and localized to lysosomal compartments. Additionally, MA-Mc demonstrated superior efficacy over free MA in activating MA-specific TCR transgenic (DN1) T cells in vitro. Following intranasal immunization, MA-Mc were primarily taken up by alveolar macrophages and DCs in the lung and induced activation and proliferation of adoptively transferred DN1 T cells. Furthermore, intranasal immunization with MA-Mc induced MA-specific T cell responses in the lungs of hCD1Tg mice. Collectively, our data demonstrates that pulmonary delivery of MA via PEG-PPS micelles to DCs can elicit potent CD1b-restricted T cell responses both in vitro and in vivo and MA-Mc could be explored as subunit vaccines against Mtb infection.
Correcting the Common Discourse Bias in Linear Representation of Sentences using Conceptors

Distributed representations of words, better known as word embeddings, have become important building blocks for natural language processing tasks. Numerous studies are devoted to transferring the success of unsupervised word embeddings to sentence embeddings. In this paper, we introduce a simple representation of sentences in which a sentence embedding is represented as a weighted average of word vectors followed by a soft projection. We demonstrate the effectiveness of this proposed method on the clinical semantic textual similarity task of the BioCreative/OHNLP Challenge 2018.
Ultrasound scanning for diagnosis of foetal abnormality and maternal anxieties in a longitudinal perspective

Ultrasound is a safe and non-invasive method for early prenatal detection of foetal malformation. We studied longitudinally the state anxiety in pregnant women who were examined by ultrasound scanning for foetal abnormality. Different high-risk sub-groups were compared with a non-risk control group of women with healthy uncomplicated pregnancies. The levels of anxiety of women ( N = 664) during early pregnancy were assessed. Data were collected at three points in time: immediately before the ultrasound scanning (T0), at 5-6 weeks (T1) and at 10-12 weeks (T2) after the prenatal examination for foetal malformation. Questionnaires were also used to collect information about socio-demographic data, critical life events, pregnancy data and personality. All women with high-risk pregnancies ( n = 497) showed high levels of state anxiety immediately before ultrasound scanning in comparison to the no-risk control group ( n = 167). Women with a suspected diagnosis of foetal malformation and those women with pathological endocrine testing had the highest levels of state anxiety at T0. There was a significant decrease in anxiety over the following 10-12 weeks. Only in the subgroup in which malformation was confirmed anxiety remained at a significantly higher level. Most women with risk-pregnancies had decreasing levels of anxiety longitudinally. But anxiety can remain elevated, especially when the diagnosis is confirmed. As reduced blood circulation in the placenta has been observed in pregnant women with high levels of anxiety, these women should be offered supportive care to minimize the risk for foetal development.
Evaluation of Prestress Loss Distribution during Pre-Tensioning and Post-Tensioning Using Long-Gauge Fiber Bragg Grating Sensors

Prestress loss evaluation in prestressed strands is essential for prestressed structures. However, the sensors installed outside the duct can only measure the total prestress loss. The sensors attached on strands inside the duct also have several problems, such as inadequate durability in an aggressive environment and vulnerability to damage during tensioning. This paper proposes a new installation method for long-gauge fiber Bragg grating (LFBG) sensors to prevent accidental damage. Then the itemized prestress losses were determined in each stage of the pre-tensioning and post-tensioning according to the LFBG measurements. We verified the applicability of the LFBG sensors for prestress monitoring and the accuracy of the proposed prestress loss calculation method during pre-tensioning and post-tensioning. In the pre-tensioning case, the calculated prestress losses had less deviation from the true losses than those obtained from foil-strain gauges, and the durability of the LFBG sensors was better than foil-strain gauges, whereas in post-tensioning case, the calculated prestress losses were close to those derived from theoretical predictions. Finally, we monitored prestress variation in the strand for 90 days. The itemized prestress losses at each stages of post-tensioning were obtained by the proposed calculation method to show the prospect of the LFBG sensors in practical evaluation.
Native reptiles alter their foraging in the presence of the olfactory cues of invasive mammalian predators

Invasive mammalian predators are linked to terrestrial vertebrate extinctions worldwide. Prey naïveté may explain the large impact invasive predators have on native prey; prey may fail to detect and react appropriately to the cues of novel predators, which results in high levels of depredation. In Australia, the feral cat (Felis catus) and the red fox (Vulpes vulpes) are implicated in more than 30 animal extinctions and the naïveté of native prey is often used to explain this high extinction rate. Reptiles are one group of animals that are heavily preyed upon by F. catus and V. vulpes. However, very few studies have examined whether reptiles are naive to their cues. In this study, we examine the ability of two native reptile species (Morethia boulengeri and Christinus marmoratus) to detect and distinguish between the chemical cues of two invasive predators (V. vulpes and F. catus) and three native predators (spotted-tailed quoll, Dasyurus maculatus; dingo, Canis lupus dingo; eastern brown snake, Pseudonaja textilis), as well as two non-predator controls (eastern grey kangaroo, Macropus giganteus and water). We conducted experiments to quantify the effects of predator scents on lizard foraging (the amount of food eaten) during 1 h trials within Y-maze arenas. We found both study species reduced the amount they consumed when exposed to predator scents—both native and invasive—indicating that these species are not naive to invasive predators. An evolved generalized predator-recognition system, rapid evolution or learned behaviour could each explain the lack of naïveté in some native Australian reptiles towards invasive predators.
Non-local RoI for Cross-Object Perception

We present a generic and flexible module that encodes region proposals by both their intrinsic features and the extrinsic correlations to the others. The proposed non-local region of interest (NL-RoI) can be seamlessly adapted into different generalized R-CNN architectures to better address various perception tasks. Observe that existing techniques from R-CNN treat RoIs independently and perform the prediction solely based on image features within each region proposal. However, the pairwise relationships between proposals could further provide useful information for detection and segmentation. NL-RoI is thus formulated to enrich each RoI representation with the information from all other RoIs, and yield a simple, low-cost, yet effective module for region-based convolutional networks. Our experimental results show that NL-RoI can improve the performance of Faster/Mask R-CNN for object detection and instance segmentation.
Limited Gradient Descent: Learning With Noisy Labels

Label noise may affect the generalization of classifiers, and the effective learning of main patterns from samples with noisy labels is an important challenge. Recent studies have shown that deep neural networks tend to prioritize the learning of simple patterns over the memorization of noise patterns. This suggests a possible method to search for the best generalization that learns the main pattern until the noise begins to be memorized. Traditional approaches often employ a clean validation set to find the best stop timing of learning, i.e., early stopping. However, the generalization performance of such methods relies on the quality of validation sets. Further, in practice, a clean validation set is sometimes difficult to obtain. To solve this problem, we propose a method that can estimate the optimal stopping timing without a clean validation set, called limited gradient descent. We modified the labels of a few samples in a noisy dataset to obtain false labels and to create a reverse pattern. By monitoring the learning progress of the noisy and reverse samples, we can determine the stop timing of learning. In this paper, we also theoretically provide some necessary conditions on learning with noisy labels. Experimental results on CIFAR-10 and CIFAR-100 datasets demonstrate that our approach has a comparable generalization performance to methods relying on a clean validation set. Thus, on the noisy Clothing-1M dataset, our approach surpasses methods that rely on a clean validation set.
Testicular spermatozoon is superior to ejaculated spermatozoon for intracytoplasmic sperm injection to achieve pregnancy in infertile males with high sperm DNA damage

The purpose of this study was to compare the clinical outcome of testicular spermatozoon versus ejaculated spermatozoon in the treatment of infertile males with high sperm DNA damage, referred as sperm DNA fragmentation index (DFI), that attending intracytoplasmic sperm injection (ICSI) programme in terms of clinical pregnancy, births delivered as the primary and pregnancy loss and embryo fertilisation as the secondary outcome. A total of 102 males fulfilling the inclusion criteria were enrolled in the present study. Of the 102 males, 61 infertile males underwent testicular spermatozoon combined with ICSI while the remaining 41 males applied ejaculated spermatozoa in their first ICSI cycles, and the data of them were collected and analysed. In a 18‐month follow‐up, testicular spermatozoon achieved higher pregnancy rate and deliver rate than those in ejaculated sperm group (pregnancy rate, 36% vs. 14.6%, p = 0.017; deliver rate, 38.5% vs. 9.8%, p = 0.001). Nevertheless, there were no significant differences in the number of oocytes aspirated and number of embryos transferred between the two groups. Additionally, the fertilisation rate in the testicular sperm study cohort (70.4%) was also similar to that in the ejaculated sperm group (75.0%). Based on the current data, we conclude that testicular spermatozoon is the prior option in the treatment of infertile males with high sperm DFI in ICSI programme. More high‐quality studies with larger samples size are needed in the future due to the relative small size and the nonrandomized design of the present study.
Learned Video Compression

We present a new algorithm for video coding, learned end-to-end for the low-latency mode. In this setting, our approach outperforms all existing video codecs across nearly the entire bitrate range. To our knowledge, this is the first ML-based method to do so. We evaluate our approach on standard video compression test sets of varying resolutions, and benchmark against all mainstream commercial codecs in the low-latency mode. On standard-definition videos, HEVC/H.265, AVC/H.264 and VP9 typically produce codes up to 60% larger than our algorithm. On high-definition 1080p videos, H.265 and VP9 typically produce codes up to 20% larger, and H.264 up to 35% larger. Furthermore, our approach does not suffer from blocking artifacts and pixelation, and thus produces videos that are more visually pleasing. We propose two main contributions. The first is a novel architecture for video compression, which (1) generalizes motion estimation to perform any learned compensation beyond simple translations, (2) rather than strictly relying on previously transmitted reference frames, maintains a state of arbitrary information learned by the model, and (3) enables jointly compressing all transmitted signals (such as optical flow and residual). Secondly, we present a framework for ML-based spatial rate control --- a mechanism for assigning variable bitrates across space for each frame. This is a critical component for video coding, which to our knowledge had not been developed within a machine learning setting.
Toxic effects of subacute inhalation exposure to trichloroethylene on serum lipid profile, glucose and biochemical parameters in Sprague–Dawley rats

Abstract The current study evaluated the inhalation toxicity of trichloroethylene (TCE) at 0, 10, 100, 250 and 400 ppm in Sprague–Dawley rats for 10 day period, because the subacute inhalation toxicity of TCE on serum lipid profile, glucose and some biochemical parameters has not been previously reported. TCE vapors were generated using the dynamic generation system based on evaporation method in the exposure chamber. On the basis of the results, mean serum low-density lipoprotein (LDL) and albumin (ALB) decreased significantly in all the groups exposed to TCE compared with the control group (p < .005), but there was a significant increase for parameters: fasting blood glucose (FBG) and alkaline phosphatase (ALP) (p < .005). Rats exposed to 400 ppm TCE showed a significant decrease in serum cholesterol (CHOL) and protein (Pr) compared with the control group (p < .005). A negative relationship was found between triglycerides (TG), very low density lipoprotein (VLDL), CHOL, LDL, Pr, ALB and urea levels and the subacute exposure to concentrations of TCE (R2 = –0.26, p < .05), but there was a direct correlation for parameters FBG, ALP and alanine aminotransferase (ALT) (R2 = 0.42, p < .05). In conclusion, studies with Sprague–Dawley rats demonstrated that subacute inhalation exposure to TCE (≥ 100 PPM) is associated with biochemical and lipotoxicity in the form of decreased serum ALB and LDL and raised ALP and glucose levels. The present study also provides additional evidence relating to decreased serum CHOL and Pr after subacute inhalation exposure to 400 ppm TCE.
Phenology of the sugar beet weevil, Bothynoderes punctiventris Germar (Coleoptera: Curculionidae), in Croatia

Abstract The sugar beet weevil (SBW), Bothynoderes punctiventris Germar, 1824, is a significant pest in most of Eastern Europe. Here, the SBW is described and its seasonal activity characterized, in terms of its different developmental stages in relation to Julian days (JDs), degree-day accumulations (DDAs), and precipitation, as a key to improving monitoring and forecasting of the pest. The phenology and population characteristics of SBW were investigated in sugar beet fields in eastern Croatia over a 4-year period (2012–2015). By using the degree-day model (lower development threshold of 5°C, no upper development threshold, biofix 1 January), the first emergence of overwintering adults was determined as becoming established when the DDA reached 20. The adult emergence was completed when the DDA reached 428. SBW males emerged first, following which the females dominated the adult population. Overwintering adults were present in the field until early July. In August, adults of the offspring generation began to appear. The eggs laid by the overwintering generation required, on average, 10–15 days to develop into larvae; however, eggs were found in soil samples over a period of 102 days (between JDs 112 and 214). Larvae were present in the soil samples over a period of a maximum of 143 days (the first larvae were established on JD 122 and the last one on JD 265), and pupae were established in the soil over a period of 102 days (between JDs 143 and 245). This study provides important data for understanding SBW population dynamics and developing potential population dynamic models for pest forecasting on a regional scale.
Valuation of Life Among Old and Very Old Adults: Comparison Between Germany and Japan

Abstract Background and Objectives Valuation of life (VOL) represents a construct capturing individuals’ active attachment to their life. The majority of studies on VOL were conducted in North America and Europe where personal autonomy and independence are highly valued, leaving open the question about the relevance of this construct in interdependence-oriented cultures. Using a framework of cross-cultural and life-span theories, the present study compared levels and predictors of VOL between the young-old and old-old individuals from Germany and Japan. Research Design and Methods Two hundred fifty-seven Germans and 248 Japanese, matched by age, gender, education, and IADL, answered a 5-item VOL scale and shared information on sociodemographic, social, and health resources. Results Germans’ VOL levels were higher than in Japanese participants. Both culture- and age-moderated predictions of VOL: education was significant only in the young-old Japanese, and close social partners mattered in the old-old, not in the young-old. Health determined VOL irrespective of culture and age. Discussion and Implications The findings suggest that cultural values and aging processes should be considered to better understand how individuals value their life and to help older adults to feel that his/her life is meaningful and worth living.
Performance Analysis of the Robust Diffusion Normalized Least Mean  ${p}$ -Power Algorithm

The diffusion least-mean <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula>-power algorithm is presented for distributed estimation in impulsive noise environments, which aims to minimize the <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula>-norm of the error. However, it suffers from slow convergence rate. In this brief, we propose a diffusion normalized least-mean <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula>-power algorithm (DNLMP), motivated by the normalized-based algorithms. To further improve the performance of the DNLMP algorithm, a robust DNLMP (RDNLMP) algorithm is developed for distributed estimation. The RDNLMP algorithm considers the error signal in normalization factor, and therefore can diminish the significance of outliers under impulsive noise environments. Moreover, the steady-state analysis of the RDNLMP algorithm is provided. Both performance analysis and numerical simulations are given to verify the proposed algorithms.
A Deep Tree-Structured Fusion Model for Single Image Deraining

We propose a simple yet effective deep tree-structured fusion model based on feature aggregation for the deraining problem. We argue that by effectively aggregating features, a relatively simple network can still handle tough image deraining problems well. First, to capture the spatial structure of rain we use dilated convolutions as our basic network block. We then design a tree-structured fusion architecture which is deployed within each block (spatial information) and across all blocks (content information). Our method is based on the assumption that adjacent features contain redundant information. This redundancy obstructs generation of new representations and can be reduced by hierarchically fusing adjacent features. Thus, the proposed model is more compact and can effectively use spatial and content information. Experiments on synthetic and real-world datasets show that our network achieves better deraining results with fewer parameters.