Miracle-dz/UniFAR-FTUs huggingface dataset:
FoxA1 and FoxA2 drive gastric differentiation and suppress squamous identity in NKX2-1-negative lung cancer

Changes in cancer cell identity can alter malignant potential and therapeutic response. Loss of the pulmonary lineage specifier NKX2-1 augments the growth of KRAS-driven lung adenocarcinoma and causes pulmonary to gastric transdifferentiation. Here, we show that the transcription factors FoxA1 and FoxA2 are required for initiation of mucinous NKX2-1-negative lung adenocarcinomas in the mouse and for activation of their gastric differentiation program. Foxa1/2 deletion severely impairs tumor initiation and causes a proximal shift in cellular identity, yielding tumors expressing markers of the squamocolumnar junction of the gastrointestinal tract. In contrast, we observe downregulation of FoxA1/2 expression in the squamous component of both murine and human lung adenosquamous carcinoma. Using sequential in vivo recombination, we find that FoxA1/2 loss in established KRAS-driven neoplasia originating from SPC-positive alveolar cells induces keratinizing squamous cell carcinomas. Thus, NKX2-1, FoxA1 and FoxA2 coordinately regulate the growth and identity of lung cancer in a context-specific manner.
Machine Learning and Imaging Informatics in Oncology

In the era of personalized and precision medicine, informatics technologies utilizing machine learning (ML) and quantitative imaging are witnessing a rapidly increasing role in medicine in general and in oncology in particular. This expanding role ranges from computer-aided diagnosis to decision support of treatments with the potential to transform the current landscape of cancer management. In this review, we aim to provide an overview of ML methodologies and imaging informatics techniques and their recent application in modern oncology. We will review example applications of ML in oncology from the literature, identify current challenges and highlight future potentials.
Recent Advances in Open Set Recognition: A Survey

In real-world recognition/classification tasks, limited by various objective factors, it is usually difficult to collect training samples to exhaust all classes when training a recognizer or classifier. A more realistic scenario is open set recognition (OSR), where incomplete knowledge of the world exists at training time, and unknown classes can be submitted to an algorithm during testing, requiring the classifiers to not only accurately classify the seen classes, but also effectively deal with unseen ones. This paper provides a comprehensive survey of existing open set recognition techniques covering various aspects ranging from related definitions, representations of models, datasets, evaluation criteria, and algorithm comparisons. Furthermore, we briefly analyze the relationships between OSR and its related tasks including zero-shot, one-shot (few-shot) recognition/learning techniques, classification with reject option, and so forth. Additionally, we also review the open world recognition which can be seen as a natural extension of OSR. Importantly, we highlight the limitations of existing approaches and point out some promising subsequent research directions in this field.
The effect of vitamin D administration on inflammatory markers in patients with inflammatory bowel disease

Background/Aims The exact relationship between vitamin D deficiency and inflammatory bowel disease (IBD) remains unclear. We evaluated the effect of vitamin D3 administration on inflammatory responses and disease severity in patients with IBD. Methods We investigated the serum 25-hydroxyvitamin D3 [25-(OH)D], C-reactive protein (CRP) levels and the partial Mayo score (PMS) in patients with IBD. Vitamin D3 was administered in patients with either vitamin D deficiency or insufficiency and CRP, serum vitamin D levels and PMS were re-examined at 6 months of administration. Results In 88 patients with Crohn’s disease (CD), a negative correlation was found between serum vitamin D and CRP. In 178 patients with ulcerative colitis (UC), serum vitamin D showed no association with CRP or PMS. Serum vitamin D increased from 11.08±3.63 to 22.69±6.11 ng/mL in 29 patients with CD and from 11.45±4.10 to 24.20±6.61 ng/mL in 41 patients with UC who received vitamin D3 treatment (P<0.001 and P<0.001, respectively). In patients with CD, median ΔCRP was –0.24 in the normalized vitamin D group and –0.11 in the non-normalized group (P=0.308). In patients with UC, median ΔCRP was −0.01 in the normalized vitamin D group and 0.06 in the non-normalized group (P=0.359). Conclusions Although a negative correlation was found between serum vitamin D and CRP levels in patients with CD, administration of vitamin D did not improve the CRP level in patients with CD. In patients with UC, serum vitamin D level was unrelated to CRP or PMS.
Sketch-R2CNN: An Attentive Network for Vector Sketch Recognition

Freehand sketching is a dynamic process where points are sequentially sampled and grouped as strokes for sketch acquisition on electronic devices. To recognize a sketched object, most existing methods discard such important temporal ordering and grouping information from human and simply rasterize sketches into binary images for classification. In this paper, we propose a novel single-branch attentive network architecture RNN-Rasterization-CNN (Sketch-R2CNN for short) to fully leverage the dynamics in sketches for recognition. Sketch-R2CNN takes as input only a vector sketch with grouped sequences of points, and uses an RNN for stroke attention estimation in the vector space and a CNN for 2D feature extraction in the pixel space respectively. To bridge the gap between these two spaces in neural networks, we propose a neural line rasterization module to convert the vector sketch along with the attention estimated by RNN into a bitmap image, which is subsequently consumed by CNN. The neural line rasterization module is designed in a differentiable way to yield a unified pipeline for end-to-end learning. We perform experiments on existing large-scale sketch recognition benchmarks and show that by exploiting the sketch dynamics with the attention mechanism, our method is more robust and achieves better performance than the state-of-the-art methods.
Cell Interactions and Receptor Antibodies in Immune Responses.

This book contains the proceedings of a meeting on the same topic held in Helsinki in June 1970. For investigators interested in the cellular basis of the immune response it was a significant occasion, representing the formal christening of the T (thymus) and B (bone marrow) cells. The book comprises 40 papers, some of which are followed by verbatim recordings of discussion or by postscripts inserted after the meeting. Some of the papers were mere summaries of data already published in extenso. Some had preliminary data better left unpublished, but most papers were of high quality and revealed the thinking of some prominent immunologists at a particular moment in time. To understand the significance of this volume it is necessary for the nonimmunologist to gain some insight into the status of cellular immunology in early 1970. That two separable populations of lymphocytes interact in mammals to induce a humoral
Comparison of statistical analysis methods for object case best–worst scaling

Abstract Aims: Different methods have been used to analyze “object case” best–worst scaling (BWS). This study aims to compare the most common statistical analysis methods for object case BWS (i.e. the count analysis, multinomial logit, mixed logit, latent class analysis, and hierarchical Bayes estimation) and to analyze their potential advantages and limitations based on an applied example. Methods: Data were analyzed using the five analysis methods. Ranking results were compared among the methods, and methods that take respondent heterogeneity into account were presented specifically. A BWS object case survey with 22 factors was used as a case study, tested among 136 policy-makers and HTA experts from the Netherlands, Germany, France, and the UK to assess the most important barriers to HTA usage. Results: Overall, the five statistical methods yielded similar rankings, particularly in the extreme ends. Latent class analysis identified five clusters and the mixed logit model revealed significant preference heterogeneity for all, with the exception of three factors. Limitations: The variety of software used to analyze BWS data may affect the results. Moreover, this study focuses solely on the comparison of different analysis methods for the BWS object case. Conclusions: The most common statistical methods provide similar rankings of the factors. Therefore, for main preference elicitation, count analysis may be considered as a valid and simple first-choice approach. However, the latent class and mixed logit models reveal additional information: identifying latent segments and/or recognizing respondent heterogeneity.
Through the magnifying glass: ALMA acute viewing of the intricate nebular architecture of OH231.8+4.2.

We present continuum and molecular line emission ALMA observations of OH 231.8+4.2, a well studied bipolar nebula around an asymptotic giant branch (AGB) star. The high angular resolution ( ∼ 0 · ″ 2 - 0 · ″ 3 ) and sensitivity of our ALMA maps provide the most detailed and accurate description of the overall nebular structure and kinematics of this object to date. We have identified a number of outflow components previously unknown. Species studied in this work include 12CO, 13CO, CS, SO, SO2, QCS, SiO, SiS, H3O+, Na37Cl, and CH3OH. The molecules Na37Cl and CH3OH are first detections in OH 231.8+4.2, with CH3OH being also a first detection in an AGB star. Our ALMA maps bring to light the totally unexpected position of the mass-losing AGB star (QX Pup) relative to the large-scale outflow. QX Pup is enshrouded within a compact (≲60 AU) parcel of dust and gas (clump S) in expansion (V exp~5-7 km s-1) that is displaced by ∼ 0 · ″ 6 to the south of the dense equatorial region (or waist) where the bipolar lobes join. Our SiO maps disclose a compact bipolar outflow that emerges from QX Pup's vicinity. This outflow is oriented similarly to the large-scale nebula but the expansion velocities are about ten times lower (V exp≲35km s-1). We deduce short kinematical ages for the SiO outflow, ranging from ~50-80 yr, in regions within ~150 AU, to ~400-500 yr at the lobe tips (~3500 AU). Adjacent to the SiO outflow, we identify a small-scale hourglass-shaped structure (mini-hourglass) that is probably made of compressed ambient material formed as the SiO outflow penetrates the dense, central regions of the nebula. The lobes and the equatorial waist of the mini-hourglass are both radially expanding with a constant velocity gradient (V exp ∝ r). The mini-waist is characterized by extremely low velocities, down to ~1 km s-1 at ~150 AU, which tentatively suggest the presence of a stable structure. The spatio-kinematics of the large-scale, high-velocity lobes (HV lobes) and the dense equatorial waist (large waist) known from previous works are now precisely determined, indicating that both were shaped nearly simultaneously about ~800-900 yr ago. We report the discovery of two large (~8″×6″), faint bubble-like structures (fish bowls) surrounding the central parts of the nebula. These are relatively old structures although probably slightly (~100-200 yr) younger than the large waist and the HV lobes. We discuss the series of events that may have resulted in the complex array of nebular components found in OH 231.8+4.2 as well as the properties and locus of the central binary system. The presence of ≲80 yr bipolar ejections indicate that the collimated fast wind engine is still active at the core of this outstanding object.
Clozapine-related Sudden Pericarditis in a Patient Taking Long Acting Aripiprazole and Valproate: A Case Report

Clozapine may be associated with cardiovascular adverse effects including QTc prolongation and, more rarely, with myocarditis and pericarditis. Although rare, these latter cardiovascular adverse effects may be life-threatening and must be immediately recognized and treated. Several cases of clozapine related-pericarditis have been described and often it has a subtle and insidious onset with symptoms that may be often misdiagnosed with psychiatric manifestations (e.g. anxiety, panic or somatization) leading to a delayed correct diagnosis with potential fatal consequences. In the present report we describe the case of a 27-year-old girl with schizoaffective disorder taking long acting aripiprazole and valproate who developed a sudden onset clozapine-related pericarditis during titration phase that resolved with immediate clozapine discontinuation and indomethacin administration. We underline the importance of an early diagnosis of clozapine-related pericarditis and the need to have monitoring protocols to prevent this potentially fatal adverse effect especially when polypharmacy is administered to patients taking clozapine.
Increased risk of central nervous system tumours with carbamate insecticide use in the prospective cohort AGRICAN.

Background Pesticide exposures are suspected to be implicated in the excess of central nervous system (CNS) tumours observed in farmers, but evidence concerning individual pesticides remains limited. Carbamate insecticides, used on a wide range of crops, have shown evidence of carcinogenicity in some experimental studies. In the cohort AGRICAN (AGRIculture & CANcer), we assessed the associations between potential exposures to carbamate insecticides and the incidence of CNS tumours, overall and by histological subtype. Methods AGRICAN enrolled 181 842 participants involved in agriculture. Incident CNS tumours were identified by linkage with cancer registries from enrolment (2005-07) until 2013. Carbamate exposure was assessed by combining information on lifetime periods of pesticide use on crop or livestock and the French crop-exposure matrix PESTIMAT, individually for each of the 19 carbamate insecticides registered in France since 1950. Associations were estimated using proportional hazards models with age as the underlying time scale, adjusting for gender, educational level and smoking. Results During a 6.9-year average follow-up, 381 incident cases of CNS tumours occurred, including 164 gliomas and 134 meningiomas. Analyses showed increased risks of CNS tumours with overall exposure to carbamate insecticides and linear trends with duration of use of each carbamate. Considering tumour subtypes, hazard ratios for gliomas ranged from 1.18 for thiofanox to 4.60 for formetanate, and for meningiomas from 1.51 for carbaryl to 3.67 for thiofanox. Conclusions Findings reinforce carcinogenicity evidence for already suspected active ingredients and draw attention to additional active ingredients, notably used on fruit trees, vineyards, potatoes and beets.
Demand-Based Computation Offloading Framework for Mobile Devices

Mobile cloud computing is an emerging commercial infrastructure paradigm to enhance the power of smart mobile devices. However, there are significant problems pertaining to efficient provisioning and delivery of mobile applications using cloud IT resources. These barriers concern various levels such as enabling individual mobile user's to dynamically adjust their computing demands and managing these infrequent demands under intermittent network connectivity along with maintaining quality of service (QoS), whereas cloud resources are available for long-time quanta granularity and incur significant setup times. This paper proposes a demand-based computation offloading framework (DBCOF) to balance these competing goals. It provides a mechanism to solve the key problem of application partitioning according to user's demand. In addition, it also reduces the monetary costs per request for the service providers and minimizes service-level agreement (SLA) violations for maintaining QoS. Previous approaches to these problems have focused only on maximizing energy savings in all contexts, irrespective of user's computing requirements. We have implemented the DBCOF prototype for Android and explored its design space by extending CloudSim, the state-of-the-art cloud simulator. Analyses of the results show the effectiveness of DBCOF system in terms of managing computation offloading demands. It also reduces the cost of providing cloud resources to mobile devices to 44.79% and minimizes SLA violations to nearly 1.34% for maintaining the QoS.
L‐theanine ameliorate depressive‐like behavior in a chronic unpredictable mild stress rat model via modulating the monoamine levels in limbic–cortical–striatal–pallidal–thalamic‐circuit related brain regions

L‐theanine, originally found in green tea, elicits various physiological effects, such as promoting relaxation, improving concentration and learning ability, and providing antianxiety‐like and antidepressant‐like properties. This study aims to investigate the effects of L‐theanine (2 mg/kg) on monoamine levels in an animal model of depression. The effect of l‐theanine on the symptoms of depression was examined through the open‐field test, sucrose preference test, and forced swim test. The monoamine neurotransmitters that involve serotonin (5‐HT), norepinephrine (NE), and dopamine (DA) were measured in the limbic–cortical–striatal–pallidal–thalamic (LCSPT)‐circuit related brain regions, including the prefrontal cortex (PFC), nucleus accumbens (NAC), striatum (ST), amygdala, and hippocampus (HIP). L‐theanine ameliorated the depressive‐like behaviors in the chronic unpredictable mild stress (CUMS) rat model. In the PFC, NAC, and HIP, L‐theanine administration significantly increased the levels of 5‐HT, NE, and DA. In the ST, the levels of 5‐HT and DA were increased after the administration of L‐theanine. However, in the HIP, only the level of DA significantly changed after the treatment of L‐theanine. Taken together, these results indicated that L‐theanine has possibly antidepressant‐like effects in the CUMS rat model, which could be mediated by the monoamine neurotransmitters in the LCSPT‐circuit related brain regions.
Generative Interpretation of Medical Images

This thesis describes, proposes and evaluates methods for automated analysis and quantification of medical images. A common theme is the usage of generative methods, which draw inference from unknown images by synthesising new images having shape, pose and appearance similar to the analysed images. The theoretical framework for fulfilling these goals is based on the class of Active Appearance Models, which has been explored and extended in case studies involving cardiac and brain magnetic resonance images (MRI), and chest radiographs. Topics treated include model truncation, compression using wavelets, handling of non-Gaussian variation by means of cluster analysis, correction of respiratory noise in cardiac MRI, and the extensions to multi-slice two-dimensional time-series and bi-temporal three-dimensional models. The medical applications include automated estimation of: left ventricular ejection fraction from 4D cardiac cine MRI, myocardial perfusion in bolus passage cardiac perfusion MRI, corpus callosum shape and area in mid-sagittal brain MRI, and finally, lung, heart, clavicle location and cardiothoracic ratio in anterior-posterior chest radiographs.
X-Band Power and Linearity Performance of Compositionally Graded AlGaN Channel Transistors

We report on the power and linearity performance of metal organic chemical vapor deposition grown AlGaN channel polarization-graded field-effect transistor (PolFET). The fabricated transistors with 3-D electron channels showed nearly flat transconductance profiles. Maximum <inline-formula> <tex-math notation="LaTeX">${f}_{T}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${f}_{\text {max}}$ </tex-math></inline-formula> of 23 and 65 GHz were measured for 0.7-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> gate-length transistors, corresponding to an <inline-formula> <tex-math notation="LaTeX">${f}_{T}$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${L}_{G}$ </tex-math></inline-formula> product of 16.2 GHz<inline-formula> <tex-math notation="LaTeX">$\cdot \mu \text{m}$ </tex-math></inline-formula>. Load-pull measurement at 10 GHz revealed a maximum output power of 2 W/mm with a maximum small signal gain of 16 dB. Two-tone measurement at 10 GHz showed an OIP3 of 33 dBm for 150-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> device width and a corresponding linearity figure-of-merit OIP3/<inline-formula> <tex-math notation="LaTeX">$\text{P}_{\text {DC}}$ </tex-math></inline-formula> of 3.4 dB. These results suggest that PolFETs could be useful for high-frequency applications requiring high linearity.
Synaptic Plasticity Dynamics for Deep Continuous Local Learning (DECOLLE)

A growing body of work underlines striking similarities between biological neural networks and recurrent, binary neural networks. A relatively smaller body of work, however, addresses the similarities between learning dynamics employed in deep artificial neural networks and synaptic plasticity in spiking neural networks. The challenge preventing this is largely caused by the discrepancy between the dynamical properties of synaptic plasticity and the requirements for gradient backpropagation. Learning algorithms that approximate gradient backpropagation using local error functions can overcome this challenge. Here, we introduce Deep Continuous Local Learning (DECOLLE), a spiking neural network equipped with local error functions for online learning with no memory overhead for computing gradients. DECOLLE is capable of learning deep spatio temporal representations from spikes relying solely on local information, making it compatible with neurobiology and neuromorphic hardware. Synaptic plasticity rules are derived systematically from user-defined cost functions and neural dynamics by leveraging existing autodifferentiation methods of machine learning frameworks. We benchmark our approach on the event-based neuromorphic dataset N-MNIST and DvsGesture, on which DECOLLE performs comparably to the state-of-the-art. DECOLLE networks provide continuously learning machines that are relevant to biology and supportive of event-based, low-power computer vision architectures matching the accuracies of conventional computers on tasks where temporal precision and speed are essential.
High Efficiency Targeting of Non-coding Sequences Using CRISPR/Cas9 System in Tilapia

The CRISPR/Cas9 has been successfully applied for disruption of protein coding sequences in a variety of organisms. The majority of the animal genome is actually non-coding sequences, which are key regulators associated with various biological processes. In this study, to understand the biological significance of these sequences, we used one or dual gRNA guided Cas9 nuclease to achieve specific deletion of non-coding sequences including microRNA and 3′ untranslated region (UTR) in tilapia, which is an important fish for studying sex determination and evolution. Co-injection of fertilized eggs with single gRNA targeting seed region of miRNA and Cas9 mRNA resulted in indel mutations. Further, co-injection of fertilized eggs with dual gRNAs and Cas9 mRNA led to the removal of the fragment between the two target loci, yielding maximum efficiency of 11%. This highest genomic deletion efficiency was further improved up to 19% using short ssDNA as a donor. The deletions can be transmitted through the germline to the next generation at average efficiency of 8.7%. Cas9-vasa 3′-UTR was used to increase the efficiency of germline transmission of non-coding sequence deletion up to 14.9%. In addition, the 3′-UTR of the vasa gene was successfully deleted by dual gRNAs. Deletion of vasa 3′-UTR resulted in low expression level of vasa mRNA in the gonad when compared with the control. To summarize, the improved CRISPR/Cas9 system provided a powerful platform that can assist to easily generate desirable non-coding sequences mutants in non-model fish tilapia to discovery their functions.