Miracle-dz/UniFAR-FTUs huggingface dataset:
Develop a Clinical Prediction Model for Postoperative Cognitive Dysfunction after Major Noncardiac Surgery in Elderly Patients: A Protocol for a Prospective Observational Study

Perioperative neurocognitive disorders (PNDs) refer to cognitive decline identified in the preoperative or postoperative period. It has been reported that the incidence of postoperative neurocognitive impairment after noncardiac surgery in patients older than 65 at 1 week was 25.8∼41.4%, and at 3 months 9.9∼12.7%. PNDs will last months or even develop to permanent dementia, leading to prolonged hospital stays, reduced quality of life, and increased mortality within 1 year. Despite the high incidence and poor prognosis of PNDs in the aged population, no effective clinical prediction model has been established to predict postoperative cognitive decline preoperatively. To develop a clinical prediction model for postoperative neurocognitive dysfunction, a prospective observational study (Clinical trial registration number: ChiCTR2000036304) will be performed in the Shanghai General Hospital during January 2021 to October 2022. A sample size of 675 patients aged >65 years old, male or female, and scheduled for elective major noncardiac surgery will be recruited. A battery of neuropsychological tests will be used to test the cognitive function of patients at 1 week, 1 month, and 3 months postoperatively. We will evaluate the associations of PNDs with a bunch of candidate predictors including general characteristics of patients, blood biomarkers, indices associated with anesthesia and surgery, retinal nerve-fiber layer thickness, and frailty index to develop the clinical prediction model by using multiple logistic regression analysis and least absolute shrinkage and the selection operator (LASSO) method. The k-fold cross-validation method will be utilized to validate the clinical prediction model. In conclusion, this study was aimed to develop a clinical prediction model for postoperative cognitive dysfunction of old patients. It is anticipated that the knowledge gained from this study will facilitate clinical decision-making for anesthetists and surgeons managing the aged patients undergoing noncardiac surgery.
Neural Changes Induced by a Speech Motor Treatment in Childhood Apraxia of Speech: A Case Series

We report a case series of children with childhood apraxia of speech, by describing behavioral and white matter microstructural changes following 2 different treatment approaches. Five children with childhood apraxia of speech were assigned to a motor speech treatment (PROMPT) and 5 to a language, nonspeech oral motor treatment. Speech assessment and brain MRI were performed pre- and post-treatment. The ventral (tongue/larynx) and dorsal (lips) corticobulbar tracts were reconstructed in each subject. Mean fractional anisotropy and mean diffusivity were extracted. The hand corticospinal tract was assessed as a control pathway. In both groups speech improvements paralleled changes in the left ventral corticobulbar tract fractional anisotropy. The PROMPT treated group also showed fractional anisotropy increase and mean diffusivity decrease in the left dorsal corticobulbar tract. No changes were detected in the hand tract. Our results may provide preliminary support to the possible neurobiologic effect of a multimodal speech motor treatment in childhood apraxia of speech.
Ecological Study on Anaerobic Sludge Bulking Caused by Filamentous Bacterial Growth in an Anaerobic Contact Process

The authors observed a biological sludge bulking phenomenon which was caused by filamentously growing anaerobic microorganisms in experimental anaerobic contact processes (ACP) treating wheat starch wastewater. There are many kinds of anaerobic microorganisms which grow filamentously, like in activated sludge. One species of anaerobic bacteria caused serious sludge bulking, and it had thin rod (around 0.2 µ m in width) and long chained morphology. When acidogenically fermented starch wastewater was fed to the ACP, the thin rod microorganism was eliminated and the biomass concentration of the methanogenic fermentor was recovered. The microorganism which caused bulking phenomenon was enriched in a liquid medium containing raw starch (wheat starch particle). The microorganism grew in long chained filamentous form, degraded raw starch, and fermented mainly volatile fatty acids (acetate, propionate, butyrate and ethanol). From these results, it is revealed that acidogenic fermentation of wastewater containing raw starch prior to treatment by an ACP is effective to prevent the anaerobic sludge bulking and to keep high organic laoding of ACPs.
Effects of Background Colors, Flashes, and Exposure Values on the Accuracy of a Smartphone-Based Pill Recognition System Using a Deep Convolutional Neural Network: Deep Learning and Experimental Approach

Background Pill image recognition systems are difficult to develop due to differences in pill color, which are influenced by external factors such as the illumination from and the presence of a flash. Objective In this study, the differences in color between reference images and real-world images were measured to determine the accuracy of a pill recognition system under 12 real-world conditions (ie, different background colors, the presence and absence of a flash, and different exposure values [EVs]). Methods We analyzed 19 medications with different features (ie, different colors, shapes, and dosages). The average color difference was calculated based on the color distance between a reference image and a real-world image. Results For images with black backgrounds, as the EV decreased, the top-1 and top-5 accuracies increased independently of the presence of a flash. The top-5 accuracy for images with black backgrounds increased from 26.8% to 72.6% when the flash was on and increased from 29.5% to 76.8% when the flash was off as the EV decreased. However, the top-5 accuracy increased from 62.1% to 78.4% for images with white backgrounds when the flash was on. The best top-1 accuracy was 51.1% (white background; flash on; EV of +2.0). The best top-5 accuracy was 78.4% (white background; flash on; EV of 0). Conclusions The accuracy generally increased as the color difference decreased, except for images with black backgrounds and an EV of −2.0. This study revealed that background colors, the presence of a flash, and EVs in real-world conditions are important factors that affect the performance of a pill recognition model.
TH1902, a new docetaxel‐peptide conjugate for the treatment of sortilin‐positive triple‐negative breast cancer

Triple‐negative breast cancer (TNBC) is a heterogeneous subgroup of cancers which lacks the expression and/or amplification of targetable biomarkers (ie, estrogen receptor, progestrogen receptor, and human epidermal growth factor receptor 2), and is often associated with the worse disease‐specific outcomes than other breast cancer subtypes. Here, we report that high expression of the sortilin (SORT1) receptor correlates with the decreased survival in TNBC patients, and more importantly in those bearing lymph node metastases. By exploiting SORT1 function in ligand internalization, a new anticancer treatment strategy was designed to target SORT1‐positive TNBC‐derived cells both in vitro and in two in vivo tumor xenografts models. A peptide (TH19P01), which requires SORT1 for internalization and to which many anticancer drugs could be conjugated, was developed. In vitro, while the TH19P01 peptide itself did not exert any antiproliferative or apoptotic effects, the docetaxel‐TH19P01 conjugate (TH1902) exerted potent antiproliferative and antimigratory activities when tested on TNBC‐derived MDA‐MB‐231 cells. TH1902 triggered faster and more potent apoptotic cell death than did unconjugated docetaxel. The apoptotic and antimigratory effects of TH1902 were both reversed by two SORT1 ligands, neurotensin and progranulin, and on siRNA‐mediated silencing of SORT1. TH1902 also altered microtubule polymerization and triggered the downregulation of the anti‐apoptotic Bcl‐xL biomarker. In vivo, both i.p. and i.v. administrations of TH1902 led to greater tumor regression in two MDA‐MB‐231 and HCC‐70 murine xenograft models than did docetaxel, without inducing neutropenia. Altogether, the data demonstrates the high in vivo efficacy and safety of TH1902 against TNBC through a SORT1 receptor‐mediated mechanism. This property allows for selective treatment of SORT1‐positive TNBC and makes TH1902 a promising avenue for personalized therapy with the potential of improving the therapeutic window of cytotoxic anticancer drugs such as docetaxel.
Mating Systems in True Morels (Morchella)

True morels (Morchella spp., Morchellaceae, Ascomycota) are widely regarded as a highly prized delicacy and are of great economic and scientific value. Recently, the rapid development of cultivation technology and expansion of areas for artificial morel cultivation have propelled morel research into a hot topic. SUMMARY True morels (Morchella spp., Morchellaceae, Ascomycota) are widely regarded as a highly prized delicacy and are of great economic and scientific value. Recently, the rapid development of cultivation technology and expansion of areas for artificial morel cultivation have propelled morel research into a hot topic. Many studies have been conducted in various aspects of morel biology, but despite this, cultivation sites still frequently report failure to fruit or only low production of fruiting bodies. Key problems include the gap between cultivation practices and basic knowledge of morel biology. In this review, in an effort to highlight the mating systems, evolution, and life cycle of morels, we summarize the current state of knowledge of morel sexual reproduction, the structure and evolution of mating-type genes, the sexual process itself, and the influence of mating-type genes on the asexual stages and conidium production. Understanding of these processes is critical for improving technology for the cultivation of morels and for scaling up their commercial production. Morel species may well be good candidates as model species for improving sexual development research in ascomycetes in the future.
Comparison of development of step-kinematics of assisted 60 m sprints with different pulling forces between experienced male and female sprinters

The purpose of this study was to compare step-by-step kinematics of normal and assisted 60 m sprints with different loads in experienced sprinters. Step-by-step kinematics were measured using inertial measuring units (IMU) integrated with a 3-axis gyroscope and a laser gun in 24 national level male and female sprinters during a normal 60 m sprint and sprints with a 3, 4, and 5 kg pulling force. The main findings were that using increasing assisted loads resulted in faster 60 m times, as a result of higher step velocity mainly caused by longer step lengths in both genders and by shorter contact times in women. Men had longer step lengths, longer contact times, and shorter flight times than women. However, the assisted loads had a greater effect on women than on men, as shown by their larger decrease in sprint times. These time differences in gender were the result of more and longer duration increases in maximal step velocity with increasing assisted loads for women (70–80% of distance) than men (65–70% of distance). This was mainly caused by shorter contact times, and by more increased step lengths in women compared to men. In terms of practical application, it is notable that employing this approach, when using assisted loads can help athletes to reach higher step velocities and hold this for longer, which may be a training impulse to move the speed barrier upwards.
Electrohydrodynamic Micro-/Nanostructuring Processes Based on Prepatterned Polymer and Prepatterned Template

As widely studied, the electrically induced micro-/nanostructuring process generally uses a prepatterned electrode to generate a spatially modulated electric field on an initially flat polymer surface to produce a nonuniform polymer deformation, leading to a structure with low aspect ratio, positive to the template pattern. However, a variant to this process that is proposed in this paper, which uses a flat electrode over an initially prepatterned polymer, can also generate the spatially modulated electric field. This paper presents a comparative study on the applicability of these two processes for microstructuring with high aspect ratio based on observations from our electrohydrodynamic simulation and experiment and shows that the proposed approach can provide a stronger electric modulation for the same experimental settings, therefore being more suitable for micro/nanostructuring with high aspect ratio.
Staphylococcal TSST-1 Association with Eczema Herpeticum in Humans

Atopic dermatitis (eczema, AD) with concurrent herpes simplex virus infection (eczema herpeticum, ADEH) is a severe form of AD. We show that ADEH patients are colonized with Staphylococcus aureus that primarily produces the superantigen toxic shock syndrome toxin-1 (TSST-1); however, significantly but to a lesser extent the superantigens staphylococcal enterotoxins A, B, and C are also represented in ADEH. ABSTRACT Atopic dermatitis (AD) is a condition affecting 30 million persons in the United States. AD patients are heavily infected with Staphylococcus aureus on the skin. A particularly severe form of AD is eczema herpeticum (ADEH), where the patients’ AD is complicated by S. aureus and herpes simplex virus (HSV) infection. This study examined the S. aureus strains from 15 ADEH patients, provided blinded, and showed a high association of ADEH with strains that produce toxic shock syndrome toxin-1 (TSST-1; 73%) compared to 10% production by typical AD isolates from patients without EH and those from another unrelated condition, cystic fibrosis. The ADEH isolates produced the superantigens associated with TSS (TSST-1 and staphylococcal enterotoxins A, B, and C). This association may in part explain the potential severity of ADEH. We also examined the effect of TSST-1 and HSV-1 on human epithelial cells and keratinocytes. TSST-1 used CD40 as its receptor on epithelial cells, and HSV-1 either directly or indirectly interacted with CD40. The consequence of these interactions was chemokine production, which is capable of causing harmful inflammation, with epidermal/keratinocyte barrier disruption. Human epithelial cells treated first with TSST-1 and then HSV-1 resulted in enhanced chemokine production. Finally, we showed that TSST-1 modestly increased HSV-1 replication but did not increase viral plaque size. Our data suggest that ADEH is associated with production of the major TSS-associated superantigens, together with HSV reactivation. The superantigens plus HSV may damage the skin barrier by causing harmful inflammation, thereby leading to increased symptoms. IMPORTANCE Atopic dermatitis (eczema, AD) with concurrent herpes simplex virus infection (eczema herpeticum, ADEH) is a severe form of AD. We show that ADEH patients are colonized with Staphylococcus aureus that primarily produces the superantigen toxic shock syndrome toxin-1 (TSST-1); however, significantly but to a lesser extent the superantigens staphylococcal enterotoxins A, B, and C are also represented in ADEH. Our studies showed that TSST-1 uses the immune costimulatory molecule CD40 as its epithelial cell receptor. Herpes simplex virus (HSV) also interacted directly or indirectly with CD40 on epithelial cells. Treatment of epithelial cells with TSST-1 and then HSV-1 resulted in enhanced chemokine production. We propose that this combination of exposures (TSST-1 and then HSV) leads to opening of epithelial and skin barriers to facilitate potentially serious ADEH.
Sensitivity of subcellular components of neuromuscular junctions to decreased neuromuscular activity

Muscle unloading imparts subtotal disuse on the neuromuscular system resulting in reduced performance capacity. This loss of function, at least in part, can be attributed to disruptions at the neuromuscular junction (NMJ). However, research has failed to document morphological remodeling of the NMJ with short term muscle unloading. Here, rather than quantifying cellular components of the NMJ, we examined subcellular active zone responses to 2 weeks of unloading in male Wistar rats. It was revealed that in the plantaris, but not the soleus muscles, unloading elicited significant (P ≤ 0.05) decrements in active zone staining as measured by Bassoon, and calcium channel expression. It was also discovered that unloading decreased the area of calcium channels staining relative to active zone areas of staining suggesting potential interference in the ability of calcium influx to trigger the release of vesicles docked at the active zone. Post‐synaptic adaptations of the motor endplate were not evident. This presynaptic subcellular size reduction was not associated with atrophy of the underlying plantaris muscle fibers, although atrophy of the weight‐bearing soleus fibers, where no subcellular remodeling was evident, was noted. These results suggest that the active zone is highly sensitive to alterations in neuromuscular activity, and that morphological adaptation of excitatory and contractile components of the NMJ can occur independently of each other.
Improving Language Model Performance on the United States Uniform Bar Exam

This work explores methods for improving language model performance on the United States Uniform Bar Exam. Achieving strong machine performance on this task has implications for our ability to provide basic legal services at scale through AI systems because it signals that language models have the capacity to interpret and reason about the law at a comparable level to a human legal professional. We experimented with various pre-training and ﬁne-tuning processes on BERT based Transformer models and found that unsupervised legal domain-speciﬁc pre-training, combined with ﬁne-tuning on an adjacent legal task and further ﬁne-tuning on the target task, resulted in the highest performing model, which achieved classiﬁcation accuracy of 0.390.
Learning Multi-Agent Navigation from Human Crowd Data

The task of safely steering agents amidst static and dynamic obstacles has many applications in robotics, graphics, and traffic engineering. While decentralized solutions are essential for scalability and robustness, achieving globally efficient motions for the entire system of agents is equally important. In a traditional decentralized setting, each agent relies on an underlying local planning algorithm that takes as input a preferred velocity and the current state of the agent’s neighborhood and then computes a new velocity for the next time-step that is collision-free and as close as possible to the preferred one. Typically, each agent promotes a goal-oriented preferred velocity, which can result in myopic behaviors as actions that are locally optimal for one agent is not necessarily optimal for the global system of agents. In this thesis, we explore a human-inspired approach for efficient multi-agent navigation that allows each agent to intelligently adapt its preferred velocity based on feedback from the environment. Using supervised learning, we investigate different egocentric representations of the local conditions that the agents face and train various deep neural network architectures on extensive collections of human trajectory datasets to learn corresponding life-like velocities. During simulation, we use the learned velocities as high-level, preferred velocities signals passed as input to the underlying local planning algorithm of the agents. We evaluate our proposed framework using two state-of-the-art local methods, the ORCA method, and the PowerLaw method.
Deep Learning Applications for Computer-Aided Design of Directed Evolution Libraries

In the past decades, the advancement in industrial enzymes, biological therapeutics, and biologic-based "green" technologies have been driven by advances in protein engineering. Speciﬁcally, the development of directed evolution techniques have enabled scientists to generate genetic diversity to iteratively test randomized libraries of variants to generate optimized enzymes for speciﬁc functions. However, throughput of directed evolution is limited due to the potential number number of variants in a randomized library. Training neural network models that utilize the growing number of datasets from deep mutational scanning experiments that characterize entire mutational landscapes and new computational representations of protein properties provides a unique opportunity to signiﬁcantly improve the efﬁciency and throughput of directed evolution , alleviating a major bottleneck and cost in many research and development projects.
Why a Construction—That is the Question! *

While idioms and idiomatic patterns constitute a large part of our linguistic knowledge, they nevertheless present special difficulties because their meanings are not predictable merely from the combination of their constituents. Recently, as studies of construction grammar (CG hereafter) has suggested, the syntactic, semantic and pragmatic unpredictability of the so-called constructional idioms should be resorted to Construction itself. Based on the CG assumption, this paper aims to suggest that the existence of Constructions such as the Chinese X-lai (come)-X/Y-qu (go) (XLXQ or XLYQ), bu (not)-X-bu (not)-Y (BXBY), and bu (not)-X-er (yet)-Y (BXEY) stands for a certain format of mental representation, i.e., the conceptual structure. The difference in terms of their degree of productivity hints at their different stage in the grammaticalization process. The comparison of the linguistic features and constructional meanings of these three combinations will show that one does not interpret the idiomatic expression solely on the lexicon. Levels beyond syntax, semantics and even pragmatics should be incorporated in linguistic analysis so that a speaker may grasp meaning of ”non-lexically filled elements” that are not in the lexicon. For this reason, a constructional idiom is taken as ”a match of syntactic and conceptual structure” which cannot be derived compositionally.
Automatic Music Transcription

Automatic Music Transcription (AMT) provides instrumental performers with convenience of performing any compositions they like. It is an interesting but challenging task as it solves the problem of forming a mapping from an audio sequence input to a symbolic representation output. In this paper, we explored several models for AMT problem, including baseline neural network model, Convolutional Recurrent Neural Network and Transformer Model. We experimented with different model architectures and hyperparameters, and the results are analyzed using different metrics.