Miracle-dz/UniFAR-FTUs huggingface dataset:
Neckio: Motivating Neck Exercises in Computer Workers

Neck pain is common among computer workers who may spend too much time in a static posture facing their display. Regular breaks and variety in one’s posture can help to prevent discomfort and pain. In order to understand how to support computer workers to do so regularly, we surveyed a convenience sample of computer workers (N = 130) regarding their work habits and their attitudes towards neck exercises at the workplace. The survey showed that they are highly motivated, but not able to comply with a neck exercise program. To address this challenge, we designed Neckio, a system that is aimed at encouraging posture variation and facilitating neck exercises at work. Neckio consists in an interactive application and a wireless angulation sensing appliance that can be mounted on the headset that office workers often use for reasons of privacy. Next to providing an interactive exercise program suitable for the workplace, its design places emphasis on an engaging user experience. We report a short-term user experience valuation of Neckio in an actual office environment (N = 10). Participants rated the overall user experience positively and reported to be intrinsically motivated to do the neck exercises. These results indicate the potential of the Neckio as a behavior change support technology to reduce the risk of developing neck pain in computer workers.
Molecular mechanisms controlling fructose‐specific memory and catabolite repression in lactose metabolism by Streptococcus mutans

Lactose is an abundant dietary carbohydrate metabolized by the dental pathogen Streptococcus mutans. Lactose metabolism presents both classic diauxic behaviors and long‐term memory, where the bacteria can pause for >11 h before initiating growth on lactose. Here, we explored mechanisms contributing to unusual aspects of regulation of the lac operon. The fructose‐phosphate metabolites, F‐1‐P and F‐6‐P, could modulate the DNA‐binding activities of the lactose repressor. Recombinant LacR proteins bound upstream of lacA and Gal‐6‐P induced the formation of different LacR‐DNA complexes. Deletion of lacR resulted in strain‐specific growth phenotypes on lactose, but also on a number of mono‐ and di‐saccharides that involve the glucose‐PTS or glucokinase in their catabolism. The phenotypes were consistent with the novel findings that loss of LacR altered glucose‐PTS activity and expression of the gene for glucokinase. CcpA was also shown to affect lactose metabolism in vivo and to bind to the lacA promoter region in vitro. Collectively, our study reveals complex molecular circuits controlling lactose metabolism in S. mutans, where LacR and CcpA integrate cellular and environmental cues to regulate metabolism of a variety of carbohydrates that are critical to persistence and pathogenicity of S. mutans.
Novel Low-Shot Deep Learning Approach for Retinal Image Classification With Few Examples.

Artificial intelligence (AI) stands to increasingly impact the practice of medicine as advances in deep learning for computer vision and natural language processing are translated to medical contexts. Applications of deep learning to retinal imaging have shown promise in recent years, beginning with a 2016 study by authors from Google demonstrating near-ophthalmologist accuracy in the classification of diabetic retinopathy from fundus photographs. 1 However, the challenges facing AI in retinal imaging parallel the challenges with applying AI to medicine in general. Many of these problems arise due to limitations in data. Large amounts of annotated data are traditionally required to “train” deep-learning models to perform well. Not only can high-volume data annotation be costly (the aforementioned diabetic retinopathy study required around 527 000 fundus-image evaluations by ophthalmologists), but sometimes sufficient data cannot be obtained, as may be the case for rare conditions. Additionally, an unbalanced distribution of characteristics, such as patient demographics, in the training data can result in poor performance in underrepresented populations. This new study in this issue of JAMA Ophthalmology by Burlina et al. 2 represents a key step toward combatting these challenges by applying cutting-edge, self-supervised, “low-shot” learning methods to improve performance in retina image classification under conditions of few training examples. The authors studied the influence of the amount of training data on AI model performance in the classification of diabetic retinopathy from fundus photographs. They trained several different types of models on subsets of training data from a publicly available fundus image database. The images were categorized into two classes: either having referable diabetic retinopathy or not. Independent models of each type were trained using subsets of the database increasing in size from 10 images per class to 5120 images per class. All models were evaluated on the primary metrics of accuracy and area under the receiver operating characteristic curve
PHND: Pashtu Handwritten Numerals Database and deep learning benchmark

In this paper we introduce a real Pashtu handwritten numerals dataset (PHND) having 50,000 scanned images and make publicly available for research and scientific use. Although more than fifty million people in the world use this language for written and oral communication, no significant efforts are devoted to the Pashtu Optical Character Recognition (POCR). We present a new approach for Pahstu handwritten numerals recognition (PHNR) based on deep neural networks. We train Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) on high-frequency numerals for feature extraction and classification. We evaluated the performance of the proposed algorithm on the newly introduced Pashtu handwritten numerals database PHND and Bangla language number database CMATERDB 3.1. 1. We obtained best recognition rate of 98.00% and 98.64% on PHND and CMATERDB 3.1. 1. respectively.
Loneliness in Later Life and Reaching Longevity: Findings From the Longitudinal Aging Study Amsterdam

Abstract Objectives There is an increasing research interest in factors that characterize those who reach exceptionally old ages. Although loneliness is often associated with an increased risk for premature mortality, its relationship with reaching longevity is still unclear. We aimed to quantify the association between (social/emotional) loneliness and the likelihood of reaching the age of 90 years in men and women separately. Methods For these analyses, data from the Longitudinal Aging Study Amsterdam (LASA) were used. Loneliness, social loneliness, and emotional loneliness were assessed at baseline using the 11-item De Jong-Gierveld scale in 1992–1993 (at age 64–85 years). Follow-up for vital status information until the age of 90 years was 99.5% completed. Multivariable-adjusted Cox regression analyses with a fixed follow-up time were based on 1,032 men and 1,078 women to calculate risk ratios (RR) of reaching 90 years. Results No significant associations were observed between loneliness and reaching 90 years in both men (RR, 0.90; 95% confidence interval [CI], 0.70–1.14) and women (RR, 0.98; 95% CI, 0.83–1.14). Social loneliness was significantly associated with a reduced chance of reaching 90 years in women (RR, 0.82; 95% CI, 0.67–0.99). Discussion The current analyses did not show support for the existence of a meaningful effect of loneliness on reaching longevity in both sexes. When investigating specific dimensions of loneliness, we observed that reporting social loneliness was associated with reaching 90 years in women. This indicates that, for women, a large and diverse personal network at an older age could increase the probability of reaching longevity. However, replication of our findings in other cohorts is needed.
Arterio-Hepatic Venous Fistula Following Liver Biopsy: A Rare Case Report and Literature Review

Arterio-hepatic venous fistula (AHVF) is an exceedingly rare phenomenon compared to arterio-portal venous fistula with only 8 cases reported in world literature. Many listed causes can be attributed to the development of there are no reported cases of AHVF following a core-needle biopsy. We report a case of 38 year-old-female with EHPVO, who underwent splenectomy with a proximal splenorenal shunt. She had an injury to left hepatic artery, consequent to a blind intra-operative core needle biopsy from the liver, which led to the development of a fistulous connection between left hepatic artery and middle hepatic vein causing high output cardiac failure. She was successfully managed with trans-arterial embolization. The present review emphasizes the possibility of AHVF following a liver biopsy and the role of digital subtraction angiography in the diagnosis, therapeutic intravascular interventions, and follow-up.
The Perspectives of Professional Caregivers on Implementing Audio-Based Technology in Residential Dementia Care

Music and familiar everyday sounds can be meaningful for people with dementia by providing benefits such as evoking memories and emotions or prompting social interactions with caregivers or relatives. Motivated by this potential, researchers and designers are investigating how to leverage these beneficial effects of sound in care environments through audio-based technology. However, there is a gap in the knowledge of how audio-based technology can be successfully implemented within everyday care practice. In this paper, we present the outcome of three participatory workshops with 18 professional caregivers to explore how audio-based technology can add value to existing care processes and activities in residential dementia care. During the participatory workshops, professional caregivers (1) mapped existing care activities; (2) linked findings in research with practice, and (3) designed scenarios for the Vita sound cushion. Care professionals indicate how audio-based technology can support existing care practice by influencing the mood of residents and by supporting social interaction during moments of care, daytime activities, or situational sessions. This study bridges research findings with insights from practice, contributing to a shared understanding of opportunities for embedding audio-based technology in dementia care. These opportunities motivate future research to implement and evaluate audio-based technology in residential dementia care.
Clustering in a newly forming social network by subjective perceptions of loneliness

Abstract Objectives: To determine whether first-year college students cluster in networks based on subjective perceptions of loneliness. Participants: 492 first-year Notre Dame students completed surveys across two semesters and provided communication data used to reconstruct their social networks. Methods: Subjective perceptions of loneliness are measured using the Social and Emotional Loneliness Scale for Adults (SELSA). Correlations between an individual’s loneliness and the average loneliness of their alters are compared to associations in random networks created using a rewiring algorithm to determine statistical significance. Results: During their first semester, students are more likely than chance to form ties with other students with similar levels of family and romantic loneliness. In their second semester, students cluster on romantic loneliness but not on family or social loneliness. Conclusions: Students are more likely than chance to form ties with people with similar self-perceived levels of loneliness, but only for certain types of loneliness and during certain periods.
Bichromatic Photoassociation Spectroscopy for the Determination of Rotational Constants of Cs2 0u+ Long-Range State below the 6S1/2 + 6P1/2 Asymptote

This article demonstrates new observation of the high-resolution ro-vibrational bichromatic photoassociation spectra (BPAS) of Cs2 in the 0u+ long-range state below the asymptotes 6S1/2 + 6P1/2. By combining with a modulation spectroscopic technique, precise references of the frequency differences have been engineered through the BPAS, with which the rotational constants of low-lying vibrational levels of the Cs2 0u+ long-range state have been accurately determined by fitting the frequency differences to the non-rigid-rotor model. The rotational constants for the newly observed seven ro-vibrational levels are summarized and disagreement for the level ῦ = 498 is clarified. The rotational constants of different vibrational levels demonstrate strong perturbations of the related energy structures. A simple analysis is performed and shows good agreement with experimental results.
The Effect of Positive Emotion and Interpersonal Relationships to Adaptation of School Life on High School Athletic Class Students

Background: Adaption for school life is important for all students. As for athletic students, since they need to cope with schoolwork and extensive training, adaption for school life could be very challenging. Taking this into consideration, the purpose of this study was to explore the factors which may help high school athletic students’ adaption of school life. Owing to this, the study explored previous researches and proposed four hypotheses: the first two hypotheses proposed that athletes’ positive emotion will have positive impacts on both their interpersonal relationships and adaption of school life; the third hypothesis suggests that athletes’ interpersonal relationships will have positive impacts on their adaption of school life and the fourth hypothesis suggested that interpersonal relationships play a mediating role among the positive emotion’s effect on adaption of school life. Methods: A total of 800 structured questionnaires were distributed to eleven high schools with athletic class students for data collection with a valid return rate of 90.6%. Structural equation modelling was used to test the relationship among them. Results: The result showed that positive emotion (β = 0.72, p < 0.05) and interpersonal relationships (β = 0.34, p < 0.05) had positive impacts on students’ adaption of school life with a predictive power of 68%. In addition, positive emotion also affected students’ school life adaption through interpersonal relationships. Conclusion: The study confirmed the positive emotion can have significant influences on student athletes’ interpersonal relationships and school life adaption. Implications: According to our findings, we suggest to encourage and promote athletes’ positive emotions so to help them have better interpersonal relationships and school life adaption.
Structural basis for the interaction of Shiga toxin 2a with a C-terminal peptide of ribosomal P stalk proteins

The principal virulence factor of human pathogenic enterohemorrhagic Escherichia coli is Shiga toxin (Stx). Shiga toxin 2a (Stx2a) is the subtype most commonly associated with severe disease outcomes such as hemorrhagic colitis and hemolytic uremic syndrome. The catalytic A1 subunit (Stx2A1) binds to the conserved elongation factor binding C-terminal domain (CTD) of ribosomal P stalk proteins to inhibit translation. Stx2a holotoxin also binds to the CTD of P stalk proteins because the ribosome-binding site is exposed. We show here that Stx2a binds to an 11-mer peptide (P11) mimicking the CTD of P stalk proteins with low micromolar affinity. We cocrystallized Stx2a with P11 and defined their interactions by X-ray crystallography. We found that the last six residues of P11 inserted into a shallow pocket on Stx2A1 and interacted with Arg-172, Arg-176, and Arg-179, which were previously shown to be critical for binding of Stx2A1 to the ribosome. Stx2a formed a distinct P11-binding mode within a different surface pocket relative to ricin toxin A subunit and trichosanthin, suggesting different ribosome recognition mechanisms for each ribosome inactivating protein (RIP). The binding mode of Stx2a to P11 is also conserved among the different Stx subtypes. Furthermore, the P stalk protein CTD is flexible and adopts distinct orientations and interaction modes depending on the structural differences between the RIPs. Structural characterization of the Stx2a-ribosome complex is important for understanding the role of the stalk in toxin recruitment to the sarcin/ricin loop and may provide a new target for inhibitor discovery.
Adaptive harmony search algorithm for mechanical performance optimization of properties of particleboard from cotton stalk

In this study, the optimum conditions for manufacturing particleboard-based waste cotton stalks were evaluated to achieve a good performance of mechanical properties. The response surface methodology (RSM) is used to calibrate the experiment results based on input variables consisting of the weight ratio of melamine formaldehyde to urea-formaldehyde (MU) resins, shelling ratio (SR), and the proportion of cotton particles to poplar particle (CP) in the core layer. An adaptive harmony search (AHS) algorithm is offered to search the optimum constructing conditions of mechanical properties for the composite particleboard using two optimization models. The optimum conditions are evaluated using maximum performance of mechanical properties. Besides, the optimum conditions are searched based on the material cost of the mechanical properties of composite particleboard that are utilized in its constraints. The results showed that the RSM can provide a perfect prediction for the mechanical properties of particleboard. The AHS is successfully applied to optimize the composite conditions. In the first optimization application, the optimal point is obtained for input variables in composite as 21.91% MU, 37.10% SR, and 13.54% CP. However, in the second condition, the optimum conditions are obtained for a good level as 18.32% MU, 51.71% SR, and 8.37% CP in the core layer.
Multiomics dissection of molecular regulatory mechanisms underlying autoimmune-associated noncoding SNPs

More than 90% of autoimmune-associated variants are located in noncoding regions, leading to challenges in deciphering the underlying causal roles of functional variants and genes and biological mechanisms. Therefore, to reduce the gap between traditional genetic findings and mechanistic understanding of disease etiologies and clinical drug development, it is important to translate systematically the regulatory mechanisms underlying noncoding variants. Here, we prioritized functional noncoding SNPs with regulatory gene targets associated with 19 autoimmune diseases by incorporating hundreds of immune cell–specific multiomics data. The prioritized SNPs are associated with transcription factor (TF) binding, histone modification, or chromatin accessibility, indicating their allele-specific regulatory roles. Their target genes are significantly enriched in immunologically related pathways and other known immunologically related functions. We found that 90.1% of target genes are regulated by distal SNPs involving several TFs (e.g., the DNA-binding protein CCCTC-binding factor [CTCF]), suggesting the importance of long-range chromatin interaction in autoimmune diseases. Moreover, we predicted potential drug targets for autoimmune diseases, including 2 genes (NFKB1 and SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. Taken together, these findings may provide useful information for future experimental follow-up and drug applications on autoimmune diseases.
Conserved UBE3A subcellular distribution between human and mice is facilitated by non-homologous isoforms

Abstract The human UBE3A gene, which is essential for normal neurodevelopment, encodes three Ubiquitin E3 ligase A (UBE3A) protein isoforms. However, the subcellular localization and relative abundance of these human UBE3A isoforms are unknown. We found, as previously reported in mice, that UBE3A is predominantly nuclear in human neurons. However, this conserved subcellular distribution is achieved by strikingly distinct cis-acting mechanisms. A single amino-acid deletion in the N-terminus of human hUBE3A-Iso3, which is homologous to cytosolic mouse mUBE3A-Iso2, results in its translocation to the nucleus. This singe amino-acid deletion is shared with apes and Old World monkeys and was preceded by the appearance of the cytosolic hUBE3A-Iso2 isoform. This hUBE3A-Iso2 isoform arose after the lineage of New World monkeys and Old World monkeys separated from the Tarsiers (Tarsiidae). Due to the loss of a single nucleotide in a non-coding exon, this exon became in frame with the remainder of the UBE3A protein. RNA-seq analysis of human brain samples showed that the human UBE3A isoforms arise by alternative splicing. Consistent with the predominant nuclear enrichment of UBE3A in human neurons, the two nuclear-localized isoforms, hUBE3A-Iso1 and -Iso3, are the most abundantly expressed isoforms of UBE3A, while hUBE3A-Iso2 maintains a small pool of cytosolic UBE3A. Our findings provide new insight into UBE3A localization and evolution and may have important implications for gene therapy approaches in Angelman syndrome.
Graphene Quantum Dots’ Surface Chemistry Modulates the Sensitivity of Glioblastoma Cells to Chemotherapeutics

Recent evidence has shown that graphene quantum dots (GQDs) are capable of crossing the blood–brain barrier, the barrier that reduces cancer therapy efficacy. Here, we tested three alternative GQDs’ surface chemistries on two neural lineages (glioblastoma cells and mouse cortical neurons). We showed that surface chemistry modulates GQDs’ biocompatibility. When used in combination with the chemotherapeutic drug doxorubicin, GDQs exerted a synergistic effect on tumor cells, but not on neurons. This appears to be mediated by the modification of membrane permeability induced by the surface of GQDs. Our findings highlight that GQDs can be adopted as a suitable delivery and therapeutic strategy for the treatment of glioblastoma, by both directly destabilizing the cell membrane and indirectly increasing the efficacy of chemotherapeutic drugs.