Miracle-dz/UniFAR-FTUs huggingface dataset:
PET of Aromatase in Gastric Parietal Cells

1Molecular Probe Dynamics Laboratory, RIKEN Center for Molecular Imaging Science, Minatojima minamimachi, Chuo-ku, Kobe, Hyogo, Japan; 2Molecular Imaging Labeling Chemistry Laboratory, RIKEN Center for Molecular Imaging Science, Minatojima minamimachi, Chuo-ku, Kobe, Hyogo, Japan; 3Graduate School of Biomedical Science, Tokyo Medical and Dental University, Kanda-Surugadai, Chiyoda-ku, Tokyo, Japan; and 4Cellular Function Imaging Laboratory, RIKEN Center for Molecular Imaging Science, Minatojima minamimachi, Chuo-ku, Kobe, Hyogo, Japan
Parents and Children Reading Together: Expanding Shared Book-Reading Across Genres

In this conceptual article we explore parents’ shared book reading (SBR) interactions with their preschoolers across different book genres in their natural home settings. We consider the unique and shared contributions of narrative, informational, wordless, and alphabet picturebooks, and how reading across genres can increase children’s involvement in the interaction, deepen their content knowledge, expand their vocabulary, and strengthen their visual literacy. Beyond the benefits for children, we discuss the advantages for parents of reading from different genres and highlight directions for future research.
Few-shot QA using DNN

Large pre-trained models were shown to yield strong results on QA tasks and often outperform human baseline [1]. However these systems don’t perform well in a few shot or zero shot settings [2]. In this project we propose a domain adaptation technique for BERT using meta learning based pre-training approach. We introduced a new special [QUESTION] token to learn relationships between question and context passages during training. The model is trained using a modified reptile [3] based meta learning algorithm. The inner loop of original reptile algorithm is modified to sample batches randomly from all tasks instead of sampling from a specific tasks in each step. This improves generalization across multiple domains. Our model achieved F1 and EM score of 52.397 and 39.005 in out of domain validation set and EM:40.023 and F1:57.800 in out of domain test set.
Machine Learning Theory (CS 6783)

We consider as a warmup example, the simplest statistical learning/prediction problem. That of learning coin flips ! Let us consider the case where we don't receive any input instance (or X = {}) and Y = {±1}. We receive ±1 valued samples y 1 ,. , y n ∈ {±1} drawn iid from Bernoullis distribution with parameter p (ie. Y is +1 with probability p and −1 with probability 1 − p). Our loss function is the zero-one loss function (y , y) = 1 1 {y =y}. Recall that our goal in statistical learning is to minimize L p (ˆ y) − inf f ∈{±1} L p (f). (Effectively our only choice of F for this problem is the set of constant mappings, F = {±1}).
E2AReceptors through Calmodulin Inhibition of Negative Feedback Regulation of Antigen

Signaling from the BCR is used to judge Ag-binding strengths of the Abs of B cells. BCR signaling enables the selection for successive improvements in the Ag afﬁnity over an extremely broad range of afﬁnities during somatic hypermutation. We show that the mouse BCR is subject to general negative feedback regulation of the receptor proteins, as well as many coreceptors and proteins in signal pathways from the receptor. Thus, the BCR can downregulate itself, which can enable sensitive detection of successive improvements in the Ag afﬁnity over a very large span of afﬁnities. Furthermore, the feedback inhibition of the BCR signalosome and most of its proteins, as well as most other regulations of genes by BCR stimulation, is to a large extent through inhibition of the transcription factor E2A by Ca 2+ /calmodulin. The Journal of Immunology , 2012, 188: 000–000. lymphocyte the cells have to pass several checkpoints verifying the functionality of their Ag receptors. The expression of a BCR with membrane-bound Ig is used for selection of cells for receptor editing, permission to leave the bone marrow, extrafollicular plasma cell differentiation, and somatic hypermutation (SH) in the germinal center (GC) reaction, as well as for selection against autoreactive cells (1–4). To optimize the initial wave of Ab defense against infections, the primary B cells with the highest Ag afﬁnity are selected to generate the extrafollicular plasmablast responses. B cells with somewhat weaker Ag binding are selected for the GC, where they undergo SH and selection for improved Ag afﬁnity (1– High-afﬁnity B cell clones the GC typically have 5–10 mutations in the variable regions of their Ig genes. They have increased their Ag-binding strength by many orders of magnitude (from ∼ 10 6 M 2 1 or less to ∼ 10 M 2 1 and higher) through several rounds of SH. Each round
Notebooks, 2, set. Transaction costs in biddings: analysis of the efficiency of the drug purchase process by public organizations

From the theory of transaction costs, it was observed that the effects of some transaction costs involved in public biddings produce advantageous results in terms of increasing competitiveness and obtaining better prices, in addition it was found that the bidding process in general is efficient, when compared to the prices practiced in the market, except for a portion of the acquisitions in which prices had significant distortions. Such distortions are verified in the procurement processes through the bidding waiver modality and in the bidding processes with low quantity of items. There were also situations in which the public administration is captured by a restricted market, whose competitive conditions can raise the average value of acquisitions. In spite of this, it is noteworthy that public organizations have the potential to reduce prices for the purchase of medicines through the bargaining power arising from large volumes of purchases.
Differences in community structure of gastrointestinal tract between Helicobacter pylori positive patients and negative patients with gastric cancer

Gastric cancer is one of the most severe cancers, while the relationship between Helicobacter pylori (H. pylori) and gastric cancer are still in dispute, and little work has been done to explore the microbial diversity between H. pylori positive patients and negative patients. In the present work, a total of 43 gastric cancer patients and 10 healthy 53 participants were enrolled to compare the microbial differences in community structure in gastrointestinal tract between H. pylori positive patients and negative patients with gastric cancer. Our results indicated that the abundance and diversity of gastrointestinal microbiota was slight lower in gastric cancer patients than that in healthy participants especially in intestine, while the abundance of some potential pathogens, e.g. Streptococcus, Lactobacillus, Akkermansia and Halomones were higher in H. pylori positive patients than H. pylori negative patients. Therefore, our work suggests the various microbial diversity between H. pylori positive patients and H. pylori negative patients with gastric cancer, which contribute to deepen the understanding of the role of H. pylori in gastric carcinogenesis and progression.
ONP-302 Nanoparticles Inhibit Tumor Growth By Altering Tumor-Associated Macrophages And Cancer-Associated Fibroblasts

In this study, we evaluated the ability of negatively charged bio-degradable nanoparticles, ONP- 302, to inhibit tumor growth. Therapeutic treatment with ONP-302 in vivo resulted in a marked delay in tumor growth in three different syngeneic tumor models in immunocompetent mice. ONP- 302 efficacy persisted with depletion of CD8+ T cells in immunocompetent mice and also was effective in immune deficient mice. Examination of ONP-302 effects on components of the tumor microenvironment (TME) were explored. ONP-302 treatment caused a gene expression shift in TAMs toward the pro-inflammatory M1 type and substantially inhibited the expression of genes associated with the pro-tumorigenic function of CAFs. ONP-302 also induced apoptosis in CAFs in the TME. Together, these data support further development of ONP-302 as a novel first-in- class anti-cancer therapeutic that can be used as a single-agent as well as in combination therapies for the treatment of solid tumors due to its ability to modulate the TME.
Which are the Effects of Body-Objectification and Instagram-Related Practices on Male Body Esteem? A Cross-Sectional Study

Objective According to the objectification framework, media pressure toward body models promotes the internalization of beauty ideals that negatively influence individuals’ body image and self-esteem. Historically, women have been the main target of sociocultural pressures. However, research has recently suggested that self-objectification is a male phenomenon as well, which can be inscribed in men’s body experiences. Nevertheless, fewer studies have specifically focused on the male experience and general consequences of body-objectification are yet to be extensively analyzed regarding males’ body image features. The current cross-sectional study explores the consequences of body-objectification on male body esteem, specifically testing the predictive role of exercising/dietary habits, body-objectification features, and SNS-related practices on male body esteem. Method A total of 238 male participants (mean age = 24.28 years, SD = 4.32) have been involved in an online survey. Three hierarchical analyses were performed to test the influence of objectified body consciousness and social networking-related experiences (i.e. Instagram intensity use, photo manipulation, selfie feedback investment) on young men’s body esteem with specific reference to the weight, appearance, and attribution features of the Body Esteem Scale. Results Findings highlighted that body shame played an interesting key role, influencing negatively all the body esteem dimensions, thus highlighting that attention needs to be deserved on this feature of OBC regarding males’ experience. On the contrary, appearance control-related dimensions positively influenced body esteem. Overall, findings confirmed that objectification theory can adequately mark a pathway by which media imagery is internalized also by men and may negatively affect their body esteem. Conclusions Despite some limitations, this study may contribute to enlarging our knowledge on male body image and self-objectification experience and support literature shattering the stereotype that body dissatisfaction is a “female-exclusive” issue. Likewise, beyond some questioning positions, these findings also encourage further exploration of a healthier “control dimension”, including body appearance-related activities and beliefs.
West Nile and Usutu virus seroprevalence in Hungary: A nationwide serosurvey among blood donors in 2019

In Hungary, West Nile virus (WNV) has been responsible for 459 laboratory confirmed human cases between 2004 and 2019, while the first human Usutu virus (USUV) infection was confirmed only in 2018. A comprehensive serosurvey was conducted among blood donors to assess the WNV and USUV seroprevalence in 2019, one year after the largest European WNV epidemic. Altogether, 3005 plasma samples were collected and screened for WNV and USUV specific Immunoglobulin G (IgG) antibodies by Enzyme–Linked Immunosorbent Assay (ELISA). All reactive samples were further tested for tick-borne encephalitis virus IgG antibodies by ELISA. Indirect immunofluorescence test and microneutralization assay were used as confirmatory methods. Overall, the WNV seroprevalence was 4.32%, and in five blood donors USUV seropositivity was confirmed. The highest seroprevalence was measured in Central, Eastern and Southern Hungary, while the Western part of the country proved to be less affected. There was a statistically strong association between the WNV seroprevalence of 2019 and the cumulative incidence in the period of 2004 and 2019 calculated for every NUTS 3 region. The last WNV serological screening was performed in 2016 and the prevalence of anti-WNV IgG proved to be 2.19%. One year after the 2018 WNV outbreak, a significant increase in seroprevalence was observed in the Hungarian population and evidence for USUV seropositivity was also obtained. The spatial pattern of seroprevalence can support the identification of high-risk areas raising awareness of the need for increased surveillance, such as screening vector, equine, and avian populations. The communication with general practitioners and other professionals in primary health care services can support the early identification of acute human cases. Education and awareness-raising on the importance of protection against mosquito vectors amongst residents are also important parts of preventive measures.
Thermo-visco-elastic modelling of photovoltaic laminates: Advanced shear-lag theory and model order reduction techniques

During lamination, residual thermo-mechanical stresses are induced in the encapsulated solar cells composing photovoltaic (PV) modules. Depending on the material and geometrical configuration of the layers of the laminate, this residual stress field can be beneficial since it may lead to a compressive stress state in Silicon and therefore crack closure effects in the presence of cracks, with a recovery of electrical conductivity in cracked solar cells. It is therefore important to investigate the distribution of thermo-mechanical stresses within the PV laminate with a view to optimizing the coupling between the electrical response and elastic deformation in the operation of PV modules. A promising approach proposed in the present thesis regards the prediction of residual stresses in composite laminates by using a shear-lag theory to model the epoxy-vinil-acetate polymeric layers, accounting for their thermo-visco-elastic response. Moreover, it will be shown that thermomechanical formulations for stress analysis of a PV laminate lead to a system of higher order ordinary differential equations or partial differential equations in which the exact solutions may be impossible to be determined in closed form and hence numerical schemes become desirable. However, the computational cost associated with the implementation of the numerical scheme may be significantly expensive. Therefore, a method to reduce the computational complexity is expected to be very important. To this aim, Model Order Reduction (MOR) techniques are applied hierarchically, first to the thermal system of a PV module in service, and then extended to coupled thermo-mechanical problems. A combination of proper orthogonal decomposition (POD) and discrete empirical interpolation method (DEIM) with a modified formulation is proposed for the first-order thermal equations of photovoltaic system during service and a new coupled second-order Krylov based formulation is developed for model order reduction of the coupled thermo-mechanical model of the photovoltaic module. The results of these reduction schemes show a huge computational gain in the reduced system solutions and a high accuracy of the reduced system outputs
Subject-specific lower extremity modeling: personalization of musculoskeletal models using medical imaging and functional measurements

Musculoskeletal models have represented for decades one of the most important research tools to understand how the human body works, and to have a better comprehension of the dysfunctions of the locomotor system. In the last years, progress in musculoskeletal mechanics, medical imaging and computational power have tremendously increased the detail and complexity of musculoskeletal models. Today, the use of musculoskeletal simulations holds significant promise for applications in the biomedical industry, in order to improve the diagnosis and treatment for patients, and in the near future model predictions are expected to gain a central role in personalized healthcare. Work presented in this thesis aimed to develop accurate and efficient methods to create subject-specific musculoskeletal models of the lower extremity. A new comprehensive and complete dataset, called Twente Lower Extremity Model 2.0, based on CT and MRI scans and dissection measurements, was purposely built to be easily combined with innovative image-based scaling techniques. TLEM 2.0 represented the starting point of a streamlined modeling workflow to create subject-specific models, using medical images and functional measurements, in a semi-automatic way with limited manual intervention. This modeling workflow was applied to ten healthy subjects in order to build a unique set of ten subject-specific musculoskeletal models, then effects of personalization and improvements in model predictions were assessed using the novel FDG-PET technique. This thesis shows that it is possible today to build a subject-specific model of the lower extremity in an efficient way, and the improvements in the model predictions make the personalization process worth the effort. Future research on developing more accurate validation techniques are needed to gain the reliability necessary for critical scenarios, such as surgical planning and clinical decision-making process, in order to reach the ambitious goal of application of subject-specific musculoskeletal models to clinical practice on a large scale.
Prenatal Opioid Exposure Impairs Endocannabinoid and Glutamate Transmission in the Dorsal Striatum

Abstract The opioid crisis has contributed to a growing population of children exposed to opioids during fetal development; however, many of the long-term effects of opioid exposure on development are unknown. We previously demonstrated that opioids have deleterious effects on endocannabinoid plasticity at glutamate synapses in the dorsal striatum of adolescent rodents, but it is unclear whether prenatal opioid exposure produces similar neuroadaptations. Using a mouse model of prenatal methadone exposure (PME), we performed proteomics, phosphoproteomics, and patch-clamp electrophysiology in the dorsolateral striatum (DLS) and dorsomedial striatum (DMS) to examine synaptic functioning in adolescent PME offspring. PME impacted the proteome and phosphoproteome in a region- and sex-dependent manner. Many proteins and phosphorylated proteins associated with glutamate transmission were differentially abundant in PME offspring, which was associated with reduced glutamate release in the DLS and altered the rise time of excitatory events in the DMS. Similarly, the intrinsic excitability properties of DMS neurons were significantly affected by PME. Last, pathway analyses revealed an enrichment in retrograde endocannabinoid signaling in the DLS, but not in the DMS, of males. Electrophysiology studies confirmed that endocannabinoid-mediated synaptic depression was impaired in the DLS, but not DMS, of PME-males. These results indicate that PME induces persistent neuroadaptations in the dorsal striatum and could contribute to the aberrant behavioral development described in offspring with prenatal opioid exposure.
Spatial metabolomics identifies distinct tumor-specific subtypes in gastric cancer patients.

PURPOSE Current systems of gastric cancer (GC) molecular classification include genomic, molecular, and morphological features. GC classification based on tissue metabolomics remains lacking. This study aimed to define metabolically distinct GC subtypes and identify their clinicopathological and molecular characteristics. EXPERIMENTAL DESIGN Spatial metabolomics by high mass resolution imaging mass spectrometry was performed in 362 GC patients. K-means clustering was used to define tumor and stroma-related subtypes based on tissue metabolites. The identified subtypes were linked with clinicopathological characteristics, molecular features, and metabolic signatures. Responses to trastuzumab treatment were investigated across the subtypes by introducing an independent patient cohort with HER2-positive GC from a multicenter observational study. RESULTS Three tumor- and three stroma-specific subtypes with distinct tissue metabolite patterns were identified. Tumor-specific subtype T1(HER2+MIB+CD3+) positively correlated with HER2, MIB1, DEFA-1, CD3, CD8, FOXP3, but negatively correlated with MMR. Tumor-specific subtype T2(HER2-MIB-CD3-) negatively correlated with HER2, MIB1, CD3, FOXP3, but positively correlated with MMR. Tumor-specific subtype T3(pEGFR+) positively correlated with pEGFR. Patients with tumor subtype T1(HER2+MIB+CD3+) had elevated nucleotide levels, enhanced DNA metabolism, and a better prognosis than T2(HER2-MIB-CD3-) and T3(pEGFR+). An independent validation cohort confirmed that the T1 subtype benefited from trastuzumab therapy. Stroma-specific subtypes had no association with clinicopathological characteristics, however linked to distinct metabolic pathways and molecular features. CONCLUSIONS Patient subtypes derived by tissue-based spatial metabolomics are a valuable addition to existing GC molecular classification systems. Metabolic differences between the subtypes and their associations with molecular features could provide a valuable tool to aid in selecting specific treatment approaches.
Comparison of Three Different In-Wheel SMPM Motor Configurations Based on the Urban NEDC

Design optimization of traction motors for light electric vehicles over an operating point is an adequate way of achieving higher overall efficiency under a standard driving scheme of the vehicle. However, this work proves that a direct comparison of similar candidates regarding efficiency values under a predetermined operating point does not yield sufficient information on the economy achieved on a specific driving pattern per candidate. This paper presents a comparative study on three similar surface mounted permanent magnet in-wheel motor configurations. On a first step, these configurations are compared in terms of efficiency and performance over one operating point. On a second step, efficiency maps of the designs under study are utilized to provide a wider picture of their efficiency attributes. On the final step, the three configurations are simulated driving a prototype light electric vehicle in the Urban part of the New European Driving Cycle and the results are discussed.
Decoding continuous kinetic information of grasp from stereo-electroencephalographic (SEEG) recordings

Objective. Brain–computer interfaces (BCIs) have the potential to bypass damaged neural pathways and restore functionality lost due to injury or disease. Approaches to decoding kinematic information are well documented; however, the decoding of kinetic information has received less attention. Additionally, the possibility of using stereo-electroencephalography (SEEG) for kinetic decoding during hand grasping tasks is still largely unknown. Thus, the objective of this paper is to demonstrate kinetic parameter decoding using SEEG in patients performing a grasping task with two different force levels under two different ascending rates. Approach. Temporal-spectral representations were studied to investigate frequency modulation under different force tasks. Then, force amplitude was decoded from SEEG recordings using multiple decoders, including a linear model, a partial least squares model, an unscented Kalman filter, and three deep learning models (shallow convolutional neural network, deep convolutional neural network and the proposed CNN+RNN neural network). Main results. The current study showed that: (a) for some channel, both low-frequency modulation (event-related desynchronization (ERD)) and high-frequency modulation (event-related synchronization) were sustained during prolonged force holding periods; (b) continuously changing grasp force can be decoded from the SEEG signals; (c) the novel CNN+RNN deep learning model achieved the best decoding performance, with the predicted force magnitude closely aligned to the ground truth under different force amplitudes and changing rates. Significance. This work verified the possibility of decoding continuously changing grasp force using SEEG recordings. The result presented in this study demonstrated the potential of SEEG recordings for future BCI application.