Miracle-dz/UniFAR-FTUs huggingface dataset:
p300-Mediated Acetylation of Histone Demethylase JMJD1A Prevents Its Degradation by Ubiquitin Ligase STUB1 and Enhances Its Activity in Prostate Cancer

Identification of mechanisms regulating JMJD1A protein stability reveals new strategies to destabilize JMJD1A and concomitantly inhibit AR activities as potential prostate cancer therapy. The androgen receptor (AR) pathway plays a central role in the development of castration-resistant prostate cancer (CRPC). The histone demethylase JMJD1A has been shown to regulate activities of AR and c-Myc transcription factors and promote prostate cancer progression. Here, we report that JMJD1A protein stability is controlled by the ubiquitin ligase STUB1. High levels of JMJD1A were strongly correlated with low STUB1 levels in human CRPC specimens. STUB1 inhibited AR activity, AR-V7 levels, and prostate cancer cell growth partly through degradation of JMJD1A. Furthermore, the acetyltransferase p300 acetylated JMJD1A at lysine (K) 421, a modification that recruits the BET family member BRD4 to block JMJD1A degradation and promote JMJD1A recruitment to AR targets. Increased levels of both total and K421-acetylated JMJD1A were observed in prostate cancer cells as they developed resistance to the AR antagonist enzalutamide. Treatment of prostate cancer cells with either p300 or BET inhibitors destabilized JMJD1A, and enzalutamide-resistant prostate cancer cells were more sensitive than parental cells to these inhibitors. Together, our findings identify a critical role for acetylation of JMJD1A in regulating JMJD1A stability and AR activity in CRPC. These newly identified mechanisms controlling JMJD1A protein stability provide potential druggable targets to encourage the development of additional therapies for advanced prostate cancer. Significance: Identification of mechanisms regulating JMJD1A protein stability reveals new strategies to destabilize JMJD1A and concomitantly inhibit AR activities as potential prostate cancer therapy.
The Photosynthetic Function of Pigments other than Chlorophyll

Ever since men noticed yellowing autumnal leaves, or gathered brown, red, or blue algae, they must have speculated as to the meaning of these colors. Scientific interest became the more acute as physiologists realized the universal distribution of chlorophyll in photosynthetic systems, and its undoubted importance as the primary light absorber. But the other pigments are also widespread: one (f3-carotene) is almost always present, and there are usually several others found in every photosynthetic system. Their distribu­ tion is remarkably parallel to phylogenetic lines. What are these other pigments doing? Are they accidental and indifferent, merely happening to absorb light (like hemoglobin) without this absorption having much physiological function? Are they helpful or wasteful filters, by their absorption protecting other systems from injurious or useful radiation? Are they, perhaps, themselves injurious, inducing photodynamic or photo­ oxidative effects? Do they collaborate with chlorophyll, optically or chemical­ ly, thereby qualifying as truly "accessory"? Or are they completely inde­ pendent, supplementary light absorbers, with their own parallel complement of enzyme systems, able to carry out photosynthesis without the interven­ tion of chlorophyll? Indeed, do they sometimes take over the major absorb­ ing function, subordinating chlorophyll itself to an accessory or indifferent position? This chapter attempts to summarize current information on the role of the so-called "accessory pigments" in photosynthesis. There has been brief mention of these in various recent reviews (1 to 5), and Rabinowitch has given his usual excellent discussion of the problem [(6), chaps. IS, 17; (7), chaps. 21-24, 30]. Several comprehensive descriptions of the pigments, with­ out much emphasis on their function, have appeared lBoresch (8); Cook (9); Strain, (10, 11, 12)]. The present author has assembled some of the back­ ground, as well as new material, especially on the algae, in a forthcoming chapter [Blinks (13)]. No attempt is made here to include photosynthetic bacteria, which will be covered in Volume 8 of the Annual Review of Micro­ biology.
Electronic Nose-Based Fusarium Detection and Deoxynivalenol Aptamer Development

Fungal infestation on wheat is an increasingly grave nutritional problem in many countries worldwide. Fusarium species are especially harmful pathogens due to their toxic metabolites. Deoxynivalenol (DON) in particular, is a secondary metabolite that contaminates frequently cereal grain, cereal-based food or feed and is thus a serious health risk to humans. To comply with governmental regulations, new tools for fast and accurate DON and Fusaria estimation have to be developed. The discrimination properties of electronic noses have already been shown and are promising with respect to food control. Aptamers for ligand binding are already known and are suitable as recognition elements for biosensors. In this work the volatile compounds released by Fusarium cerealis, Fusarium graminearum, Fusarium culmorum and Fusarium redolens were studied. Using an electronic nose, it was possible to differentiate between infected and non-infected dry, whole wheat grain. The electronic nose was capable of distinguishing between four Fusaria species with an accuracy higher than 80%. Furthermore, DNA aptamers have been selected, reacting to DON with different affinities. The used SELEX is based on the formation of aptamer beacons upon DON binding. A single-stranded DNA library, covering 40 random positions, was bound to an affinity column. The library consisted of an estimated diversity of 6.6e14 molecules. Sequences which underwent a conformational change consequently to the addition of DON were collected and amplified. Eventually, 39 DNA structures of the amplifed pool were chosen for binding analysis among which 14 reacted to the application of DON.
Retrospective Inference as a Form of Bounded Rationality, and Its Beneficial Influence on Learning

Probabilistic models of cognition typically assume that agents make inferences about current states by combining new sensory information with fixed beliefs about the past, an approach known as Bayesian filtering. This is computationally parsimonious, but, in general, leads to suboptimal beliefs about past states, since it ignores the fact that new observations typically contain information about the past as well as the present. This is disadvantageous both because knowledge of past states may be intrinsically valuable, and because it impairs learning about fixed or slowly changing parameters of the environment. For these reasons, in offline data analysis it is usual to infer on every set of states using the entire time series of observations, an approach known as (fixed-interval) Bayesian smoothing. Unfortunately, however, this is impractical for real agents, since it requires the maintenance and updating of beliefs about an ever-growing set of states. We propose an intermediate approach, finite retrospective inference (FRI), in which agents perform update beliefs about a limited number of past states. (Formally, this represents online fixed-lag smoothing with a sliding window.) This can be seen as a form of bounded rationality in which agents seek to optimise the accuracy of their beliefs subject to computational and other resource costs. We show through simulation that this approach has the capacity to significantly increase the accuracy of both inference and learning, using a simple variational scheme applied to both randomly generated Hidden Markov models (HMMs), and a specific application of the HMM, in the form of the widely used probabilistic reversal task. Our proposal thus constitutes a theoretical contribution to normative accounts of bounded rationality, which makes testable empirical predictions that can be explored in future work.
ANISOTROPIC ETCHING OF SILICON IN (CH3)4NOH SOLUTIONS

Detailed characteristics of tetramethyl ammoniumhydroxide (TMAH, (CH314NOH) as silicon anisotropic etching solutions with various concentrations from 5 to 40 wt. % have been studied. The etch rates of (100) and (111) crystal planes decreased with increasing concentration. The etched (100) planes were covered by pyramidal-shaped hillocks below 15 wt. %, but very smooth surfaces were obtained above 22 wt. %. The etch rate of 1.0 p/min at 90 'C was obtained using a 22 wt. % solution. The etch rate ratio of (100)/(111) varied from 10 to 35. The etch rate of thermally oxidized Si@ was almost four orders of magnitude lower than that for (100) plane. The etch rates for p-type and n-type (100) silicon became nearly zero by applying an electric potential. The dependences of open circuit potential and passivation potential on the resistivities from 0.01 to 10 n-cm were not observed. Anisotropic silicon etching is a key technology for the fabrication of various micromechanical devices. The important properties of anisotropic silicon etchants are anisotropy, selectivity, handling and process compatibility. The process compatibility becomes specially important, since sensors and actuators are required to be utilized with LS1 circuits on the same chip to realize a new transducer system with high performance[l,2]. Up to now, many etchants have been proposed, which include inorganic aqueous solutions of KOH[3], NaOH[41, CsOH[51 and NQOH[6], as well as organic aqueous solutions containing ethylenediamine[71, hydrazinei81 and choline[91. The most commonly used etchants are KOH, ethylenediamine-pyrocatechol-water (EDP), and hydrazine-water solutions. However, these solutions do not fulfill the requirements mentioned earlier. The goal of this research is to develop a new silicon. etchant with CMOS-compatibility, anisotropy, nontoxicity and selectivity which can be applied within ICfabrication lines. In order to meet these requirements, we noticed quaternary ammoniumhydroxide (QAH) solutions. QAH was proposed by M. Asano[9] in 1976 as an etching and cleaning solution of silicon and silicon dioxide surfaces. However, its detailed characteristics as a silicon anisotropic etchant have not been reported yet. We have already presented the basic characteristics of QAH by selecting tetraethyl ammoniumhydroxide (TEAH, (C2H514NOH) as representative etchants with various concentrations from 10 to 40 wt. %[lOl. In this paper, we focus on tetramethyl ammoniumhydroxide (TMAH, (CH3)aOH) solutions with various concentrations from 5 to 40 wt. %. The main feature of TMAH is the compatibility with the LSI-process, since TMAH has been utilized in the LSI process as the developing solution of positive photoresist. Therefore, semiconductor grade solutions can be easily obtained. The dependences of the etch rates of (100) and (111) crystal planes on temperature and concentration, selectivity to Si02 and Si3N4, and electrochemical etching characteristics were studied.
Marine algal flora of São Miguel Island, Azores

Abstract Background The macroalgal flora of the Island of São Miguel (eastern group of the Azores Archipelago) has attracted the interest of many researchers in the past, the first publications going back to the nineteenth century. Initial studies were mainly taxonomic, resulting in the publication of a checklist of the Azorean benthic marine algae. Later, the establishment of the University of the Azores on the Island permitted the logistic conditions to develop both temporal studies and long-term research and this resulted in a significant increase on research directed at the benthic marine algae and littoral communities of the Island and consequent publications. Prior to the present paper, the known macroalgal flora of São Miguel Island comprised around 260 species. Despite this richness, a significant amount of the research was never made public, notably Masters and PhD theses encompassing information regarding presence data recorded at littoral and sublittoral levels down to a depth of approximately 40 m around the Island and the many collections made, which resulted in vouchers deposited in the AZB Herbarium Ruy Telles Palhinha and the LSM- Molecular Systematics Laboratory at the Faculty of Sciences and Technology of the University of the Azores. The present publication lists the macroalgal taxonomic records, together with information on their ecology and occurrence around São Miguel Island, improving the knowledge of the Azorean macroalgal flora at local and regional scales. New information A total of 12,781 specimens (including some identified only to genus) belonging to 431 taxa of macroalgae are registered, comprising 284 Rhodophyta, 59 Chlorophyta and 88 Ochrophyta (Phaeophyceae). Of these, 323 were identified to species level (212 Rhodophyta, 48 Chlorophyta and 63 Ochrophyta), of which 61 are new records for the Island (42 Rhodophyta, 9 Chlorophyta and 10 Ochrophyta), one an Azorean endemic (Predaea feldmannii subsp. azorica Gabriel), five are Macaronesian endemisms (the red algae Botryocladia macaronesica Afonso-Carrillo, Sobrino, Tittley & Neto, Laurencia viridis Gil-Rodríguez & Haroun, Millerella tinerfensis (Seoane-Camba) S.M. Boo & J.M. Rico, Phyllophora gelidioides P.Crouan & H.Crouan ex Karsakoff and the green alga Codium elisabethiae O.C. Schmidt), 19 are introduced species (15 Rhodophyta, two Chlorophyta and two Ochrophyta) and 32 are of uncertain status (21 Rhodophyta, five Chlorophyta and six Ochrophyta).
"Alexa, what do you do for fun?" Characterizing playful requests with virtual assistants

Virtual assistants such as Amazon's Alexa, Apple's Siri, Google Home, and Microsoft's Cortana, are becoming ubiquitous in our daily lives and successfully help users in various daily tasks, such as making phone calls or playing music. Yet, they still struggle with playful utterances, which are not meant to be interpreted literally. Examples include jokes or absurd requests or questions such as,"Are you afraid of the dark? ","Who let the dogs out? ", or"Order a zillion gummy bears". Today, virtual assistants often return irrelevant answers to such utterances, except for hard-coded ones addressed by canned replies. To address the challenge of automatically detecting playful utterances, we first characterize the different types of playful human-virtual assistant interaction. We introduce a taxonomy of playful requests rooted in theories of humor and refined by analyzing real-world traffic from Alexa. We then focus on one node, personification, where users refer to the virtual assistant as a person ("What do you do for fun? "). Our conjecture is that understanding such utterances will improve user experience with virtual assistants. We conducted a Wizard-of-Oz user study and showed that endowing virtual assistant s with the ability to identify humorous opportunities indeed has the potential to increase user satisfaction. We hope this work will contribute to the understanding of the landscape of the problem and inspire novel ideas and techniques towards the vision of giving virtual assistants a sense of humor.
Nursing staff ratio and skill mix in Swedish emergency departments: A national cross-sectional benchmark study.

AIM To describe ratio and skill mix for nursing staff in Swedish emergency departments over a specific 24-hour period. BACKGROUND The link between number of patients per nursing staff and missed nursing care is well described within the in-hospital setting, showing association with negative outcomes such as increased mortality. Potential association within the emergency department setting is still unexplored. METHOD A national descriptive cross-sectional benchmark study. RESULTS The majority (n=54; 89%) of Swedish emergency departments participated. The patients-per-registered nurse ratio varied between the shifts, from 0.3 patients to 8.8 patients (mean 3.2). The variation of patients per licensed practical nurse varied, from 1.5 to 23.5 patients (mean 5.0). The average skill mix was constant at around 60% registered nurses and 40% licensed practical nurses. CONCLUSION The varying ratios for patient per registered nurse and licensed practical nurse in Swedish emergency departments is noteworthy. Furthermore, the patient flow and nursing staff numbers did not match one another, resulting in higher nursing staff ratios during the evening shift. IMPLICATIONS FOR NURSING MANAGEMENT Findings can be used to improve rosters in relation to crowding, to manage the challenging recruitment and retention situation for nursing staff and to improve patient safety.
Action Recognition Using Multi-Scale Temporal Shift Module and Temporal Feature Difference Extraction Based on 2D CNN

Convolutional neural networks, which have achieved outstanding performance in image recognition, have been extensively applied to action recognition. The mainstream approaches to video understanding can be categorized into two-dimensional and three-dimensional convolutional neural networks. Although three-dimensional convolutional filters can learn the temporal correlation between different frames by extracting the features of multiple frames simultaneously, it results in an explosive number of parameters and calculation cost. Methods based on two-dimensional convolutional neural networks use fewer parameters; they often incorporate optical flow to compensate for their inability to learn temporal relationships. However, calculating the corresponding optical flow results in additional calculation cost; further, it necessitates the use of another model to learn the features of optical flow. We proposed an action recognition framework based on the two-dimensional convolutional neural network; therefore, it was necessary to resolve the lack of temporal relationships. To expand the temporal receptive field, we proposed a multi-scale temporal shift module, which was then combined with a temporal feature difference extraction module to extract the difference between the features of different frames. Finally, the model was compressed to make it more compact. We evaluated our method on two major action recognition benchmarks: the HMDB51 and UCF-101 datasets. Before compression, the proposed method achieved an accuracy of 72.83% on the HMDB51 dataset and 96.25% on the UCF-101 dataset. Following compression, the accuracy was still impressive, at 95.57% and 72.19% on each dataset. The final model was more compact than most related works.
Verifying Serializability Protocols With Version Order Recovery

A core feature of many database systems is the ability to group operations into transactions. An isolation level defines the extent to which operations within a transaction interact with operations from other concurrent transactions. The serializable isolation level provides correctness guarantees that many programmers implicitly assume, since it provides the illusion of transactions running sequentially. However, implementing serializable transactions, particularly in a distributed setting, has proven to be a challenging task, with many systems failing to live up to their guarantees. One method of providing assurance of the correctness of concurrency control protocols purporting to offer serializability is by verifying that the execution histories they produce are serializable. However, existing verifiers either have no guarantees on their worst-case execution time or require constraints on the type of operations they support, for example no verifier currently supports verifying histories containing predicate operations except in very special cases. We introduce the concept of version order recovery, which recovers the version order from database systems while imposing fewer constraints than existing verifiers, that provides the means for efficient verification of serializable concurrency control protocols. We implement version order recovery for both PostgreSQL and TiDB, and show that it has minimal overhead on execution performance. We also implement a serializability verifier Emme and show that its performance is competitive with or better than existing verifiers. Additionally, when object visibility information can be recovered on a per-operation basis, we show that Emme supports the verification of moderate size histories containing predicate operations. Due to the significant improvements in efficiency, broader testing applicability, and moderate implementation effort, we expect version order recovery to be widely adopted in practice.
Rapid PCR-based method for herbivore dietary evaluation using plant-specific primers

Polyphagous pests cause significant economic loss worldwide through feeding damage on various cash crops. However, their diets in agricultural landscapes remain largely unexplored. Pest dietary evaluation in agricultural fields is a challenging task currently approached through visual observation of plant feeding and microscopic identification of semi-digested plant material in pest’s guts. While molecular gut content analysis using metabarcoding approaches using universal primers (e.g., rbcl and trnL) have been successful in evaluating polyphagous pest diet, this method is relatively costly and time-consuming. Hence, there is a need for a rapid, specific, sensitive, and cost-effective method to screen for crops in the gut of pests. This is the first study to develop plant-specific primers that target various regions of their genomes, designed using a whole plant genome sequence. We selected Verticillium wilt disease resistance protein (VE-1) and pathogenesis related protein-coding genes 1–5 (PR-1-5) as our targets and designed species-specific primers for 14 important crops in the agroecosystems. Using amplicon sizes ranging from 115 to 407 bp, we developed two multiplex primer mixes that can separate nine and five plant species per PCR reaction, respectively. These two designed primer mixes provide a rapid, sensitive and specific route for polyphagous pest dietary evaluation in agroecosystems. This work will enable future research to rapidly expand our knowledge on the diet preference and range of crops that pests consume in various agroecosystems, which will help in the redesign and development of new crop rotation regimes to minimize polyphagous pest pressure and damage on crops.
It Has Potential: Gradient-Driven Denoisers for Convergent Solutions to Inverse Problems

In recent years there has been increasing interest in leveraging denoisers for solving general inverse problems. Two leading frameworks are regularization-by-denoising (RED) and plug-and-play priors (PnP) which incorporate explicit likelihood functions with priors induced by denoising algorithms. RED and PnP have shown state-of-the-art performance in diverse imaging tasks when powerful denoisers are used, such as convolutional neural networks (CNNs). However, the study of their convergence remains an active line of research. Recent works derive the convergence of RED and PnP methods by treating CNN denoisers as approximations for maximum a posteriori (MAP) or minimum mean square error (MMSE) estimators. Yet, state-of-the-art denoisers cannot be interpreted as either MAP or MMSE estimators, since they typically do not exhibit symmetric Jacobians. Furthermore, obtaining stable inverse algorithms often requires controlling the Lipschitz constant of CNN denoisers during training. Precisely enforcing this constraint is impractical, hence, convergence cannot be completely guaranteed. In this work, we introduce image denoisers derived as the gradients of smooth scalar-valued deep neural networks, acting as potentials. This ensures two things: (1) the proposed denoisers display symmetric Jacobians, allowing for MAP and MMSE estimators interpretation; (2) the denoisers may be integrated into RED and PnP schemes with backtracking step size, removing the need for enforcing their Lipschitz constant. To show the latter, we develop a simple inversion method that utilizes the proposed denoisers. We theoretically establish its convergence to stationary points of an underlying objective function consisting of the learned potentials. We numerically validate our method through various imaging experiments, showing improved results compared to standard RED