Miracle-dz/UniFAR-FTUs huggingface dataset:
Neurocognitive Outcome Following Recovery from Severe Acute Respiratory Syndrome – Coronavirus-1 (SARS-CoV-1)

Abstract Objective: Severe acute respiratory syndrome (SARS) is a highly contagious viral respiratory illness associated with hypoxia and dyspnea. Many of those who contracted and recovered from SARS during the 2002–2003 outbreak reported persistent physical, psychological, and cognitive difficulties. Here, we investigated the residual influences of SARS on cognition for a subset of healthcare professionals who recovered and were referred for neuropsychological evaluation through their workplace insurance. Method: Twenty-eight healthcare professionals were evaluated on neuropsychological and mood functioning approximately 1.5 years post-recovery from a severe respiratory illness. Test scores were compared with age-matched normative data, and correlations were examined between mood, self-report memory scales, subjective complaints (e.g., poor concentration, pain, fatigue), illness severity (i.e., length of hospitalization, oxygen use during hospital stay), and cognitive performance. Results: Participants performed within age expectations on the majority of cognitive measures including overall memory ability. Although processing speed was generally within normal limits, 43% showed significant speed–accuracy trade-offs favoring accuracy over maintaining speed. Deficits were observed on measures of complex attention, such as working memory and the ability to sustain attention under conditions of distraction. Participants endorsed poorer memory ability than same-age peers on a meta-memory measure and mild to moderate depression and anxiety symptoms. Objective test performance was largely uncorrelated with self-reports, mood, or illness severity, except for moderate correlations between complex attention and participants’ subjective ratings of Everyday Task-Oriented Memory. Conclusions: These findings demonstrate specific long-term cognitive deficits associated with SARS and provide further evidence of the cognitive effects of hypoxic illnesses.
IRF2 enhances RANKL-induced osteoclast differentiation via regulating NF-κB/NFATc1 signaling

Interferon regulatory factors (IRFs) play roles in various biological processes including cytokine signaling, cell growth regulation and hematopoietic development. Although it has been reported that several IRFs are involved in bone metabolism, the role of IRF2 in bone cells has not been elucidated. Here, we investigated the involvement of IRF2 in RANKL-induced osteoclast differentiation. IRF2 overexpression in osteoclast pre-cursor cells enhanced osteoclast differentiation by regulating the expression of NFATc1, a master regulator of osteoclasto-genesis. Conversely, IRF2 knockdown inhibited osteoclast differentiation and decreased the NFATc1 expression. Moreover, IRF2 increased the translocation of NF-κB subunit p65 to the nucleus in response to RANKL and subsequently induced the expression of NFATc1. IRF2 plays an important role in RANKL-induced osteoclast differentiation by regulating NF-κB/NFATc1 signaling pathway. Taken together, we demonstrated the molecular mechanism of IRF2 in osteoclast differentiation, and provide a molecular basis for potential therapeutic targets for the treatment of bone diseases characterized by excessive bone resorption.
Effects of metreleptin in patients with lipodystrophy with and without baseline concomitant medication use

Abstract Objective To evaluate the effects of metreleptin in distinct subgroups of patients with generalized lipodystrophy (GL) and partial lipodystrophy (PL), using multivariate linear regression modeling to account for the role of patients’ baseline usage of concomitant glucose and lipid-lowering medications and other covariates on their outcomes. Materials and methods A post-hoc statistical analysis of two published single-arm, interventional, phase 2 clinical trials at NIH was conducted. Concomitant medication use was assessed for the clinical trial population using prescription fill data, measured at baseline and the post-one year following metreleptin initiation. Pre-specified co-primary efficacy endpoints measured were change from baseline in HbA1c at month 12, and the percent change from baseline in fasting serum triglycerides (TG) at month 12. Descriptive and statistical analyses were conducted for the overall population, the separate populations with GL and PL, and additional PL subgroups defined by baseline metabolic markers of elevated HbA1c and elevated fasting TG. Results As previously reported, improvement in HbA1c and fasting TG from baseline to 12 months on metreleptin were observed in the overall population (mean change −1.57 percentage points and median change −37.9%, respectively) and subgroups. For both HbA1c and TG, baseline levels were significant predictors of changes after metreleptin. After considering baseline characteristics such as disease type, age, sex, and baseline HbA1c, baseline insulin use was not found to be a significant predictor of HbA1c improvement following metreleptin initiation. Similar results were seen for TG levels, with the use of any lipid-lowering medications at baseline not found to be a significant predictor of reductions in fasting TG levels. Conclusions Patients treated with metreleptin experienced statistically significant improvement in metabolic markers of glycemic and hypertriglyceridemic control—e.g. HbA1c and triglyceride levels—across various subgroups after controlling for baseline characteristics and concomitant medication usage.
Approximating a Zulu GF concrete syntax with a neural network for natural language understanding

Multilingual Grammatical Framework (GF) domain grammars have been used in a variety of different applications, including question answering, where concrete syntaxes for parsing questions and generating answers are typically required for each supported language. In low-resourced settings, grammar engineering skills, appropriate knowledge of the use of supported languages in a domain, and appropriate domain data are scarce. This presents a challenge for developing domain speciﬁc concrete syntaxes for a GF application grammar, on the one hand, while on the other hand, machine learning techniques for performing question-answering are hampered by a lack of sufﬁ-cient data. This paper presents a method for overcoming the two challenges of scarce or costly grammar engineering skills and lack of data for machine learning. A Zulu resource grammar is leveraged to create sufﬁcient data to train a neural network that approximates a Zulu concrete syntax for parsing questions in a proof-of-concept question-answering system.
Morphological determinants of bite force capacity in insects: a biomechanical analysis of polymorphous leaf-cutter ants

The extraordinary success of social insects is partially based on ‘division of labour’, i. e. individuals exclusively or preferentially perform specific tasks. Task-preference may correlate with morphological adaptations so implying task-specialisation, but the extent of such specialisation can be difficult to determine. Here, we demonstrate how the physical foundation of some tasks can be leveraged to quantitatively link morphology and performance. We study the allometry of bite force capacity in Atta vollenweideri leaf-cutter ants, polymorphic insects in which the mechanical processing of plant material is a key aspect of the behavioural portfolio. Through a morphometric analysis of tomographic scans, we show that the bite force capacity of the heaviest colony workers is twice as large as predicted by isometry. This disproportionate ‘boost’ is predominantly achieved through increased investment in muscle volume; geometrical parameters such as mechanical advantage, fibre length or pennation angle are likely constrained by the need to maintain a constant mandibular opening range. We analyse this preference for an increase in size-specific muscle volume and the adaptations in internal and external head anatomy required to accommodate it with simple geometric and physical models, so providing a quantitative understanding of the functional anatomy of the musculoskeletal bite apparatus in insects.
Increasing Awareness of Primigravidas About Fetal Movements During Pregnancy

Background: Fetal movements is a sign to the mother that her fetus is live and in contact with her, it is developed as a simple, inexpensive and easily accessible tool to support the mother in monitoring her fetal well-being and alarming behavior in time to intervene. Aim of the study: Increasing awareness of primigravidas about fetal movements during pregnancy. Setting: this study conducted at outpatient clinics of El–Dakhla general hospital and Family Health Center at El–Dakhla. Methods: A Convenient sample included 100 primigravida mother, a crosssectional research design was used Tools: A structured interview questionnaire to assess maternal perception and knowledge regarding fetal movements. Results: The study findings revealed that the majority of mothers shows positive perception and unsatisfactory knowledge regarding fetal movements and also found significant relationship between mother's knowledge and age, educational level and residence. Conclusion: The study concluded that most of primigravidas have positive perception toward fetal movements but have unsatisfactory knowledge with significant relationship between mother's knowledge & age, educational level and residence. Recommendations: Fetal movements counting should be a basic part of guidelines of antenatal care in all hospitals & all Maternity health centers for continuous education through antenatal classes is very important.
Priority-Based Skyline Query Processing for Incomplete Data

Over the years, several skyline query techniques have been introduced to handle incompleteness of data, the most recent of which has proposed to sort the points of a dataset into several distinct lists based on each dimension. The points would be accessed based on these lists in round robin fashion, and the points that haven’t been dominated by the end would compose the final skyline. The work is based on the assumption that relatively dominant points, if sorted, would be processed first, and even if the point wouldn’t be a skyline point, it would prune huge amount of data. However, that approach doesn’t take into consideration that the dominance of a point depends not only on the highest value of a given dimension, but also on the number of complete dimensions a point has. Hence, we propose a Priority-First Sort-Based Incomplete Data Skyline (PFSIDS) that utilizes a different indexing technique that allows optimization of access based on both number of complete dimensions a point has as well as sorting of the data.
Morphological Evolution of the Hosts of Far-infrared/Submillimeter Galaxies

We present a host morphological study of 1266 far-infrared galaxies (FIRGs) and submillimeter galaxies (SMGs) in the Cosmic Evolution Survey field using the F160W and F814W images obtained by the Hubble Space Telescope. The FIRGs and SMGs are selected from the Herschel Multi-tiered Extragalactic Survey and the SCUBA-2 Cosmology Legacy Survey, respectively. Their precise locations are based on the interferometry data from the Atacama Large Millimeter/submillimeter Array and the Very Large Array. These objects are mostly at 0.1 ≲ z ≲ 3. The SMGs can be regarded as the population at the high-redshift tail of the FIRGs. Most of our FIRGs/SMGs have a total infrared luminosity (L IR) in the regimes of luminous and ultraluminous infrared galaxies (LIRGs, L IR = 1011−12 L ⊙; ULIRGs, L IR > 1012 L ⊙). The hosts of the SMG ULIRGs, FIRG ULIRGs, and FIRG LIRGs are of sufficient numbers to allow for detailed analysis, and they are only modestly different in their stellar masses. Their morphological types are predominantly disk galaxies (type D) and irregular/interacting systems (type Irr/Int). There is a morphological transition at z ≈ 1.25 for the FIRG ULIRG hosts, above which the Irr/Int galaxies dominate and below which the D and Irr/Int galaxies have nearly the same contributions. The SMG ULIRG hosts seem to experience a similar transition. This suggests a shift in the relative importance of galaxy mergers/interactions versus secular gas accretions in “normal” disk galaxies as the possible triggering mechanisms of ULIRGs. The FIRG LIRG hosts are predominantly D galaxies over z = 0.25–1.25, where they are of sufficient statistics.
The Second Generalization of the Hausdorff Dimension Theorem for Random Fractals

In this paper, we present a second partial solution for the problem of cardinality calculation of the set of fractals for its subcategory of the random virtual ones. Consistent with the deterministic case, we show that for the given quantities of the Hausdorff dimension and the Lebesgue measure, there are aleph-two virtual random fractals with, almost surely, a Hausdorff dimension of a bivariate function of them and the expected Lebesgue measure equal to the latter one. The associated results for three other fractal dimensions are similar to the case given for the Hausdorff dimension. The problem remains unsolved in the case of non-Euclidean abstract fractal spaces.
Deep learning for bioimage analysis in developmental biology

ABSTRACT Deep learning has transformed the way large and complex image datasets can be processed, reshaping what is possible in bioimage analysis. As the complexity and size of bioimage data continues to grow, this new analysis paradigm is becoming increasingly ubiquitous. In this Review, we begin by introducing the concepts needed for beginners to understand deep learning. We then review how deep learning has impacted bioimage analysis and explore the open-source resources available to integrate it into a research project. Finally, we discuss the future of deep learning applied to cell and developmental biology. We analyze how state-of-the-art methodologies have the potential to transform our understanding of biological systems through new image-based analysis and modelling that integrate multimodal inputs in space and time.
How to interpret absorption and fluorescence spectra of charge transfer states in an organic solar cell

The aim of the present work is to identify the appropriate framework for analyzing photoluminescence and photocurrent (EQE) spectra of charge transfer (CT) states in donor–acceptor blends used as active materials for organic solar cells. It was stimulated by the work of Vandewal et al. (J. Am. Chem. Soc., 2017, 139(4), 1699–1704) who analyzed EQE spectra of CT states of a series of blend systems in terms of Marcus theory assuming that, first, the spectral shape reflects the reorganization energy of the donor upon ionization and, second, that disorder effects are unimportant. To test this assumption we applied gated photoluminescence (PL) spectroscopy within a temperature range from 5 to 295 K combined with EQE as well as electroluminescence (EL) experiments on 1 : 1 Me-LPPP : PCBM blends by weight. We find that the PL spectra are virtually temperature independent and the temporal decay of the emission features a power law with an exponent close to −3/2 as Hong and Noolandi predicted for distributed geminately bound electron-holes pairs. The EL spectrum reveals a red-shift by 100 meV relative to the PL spectrum. The results are inconsistent with both Marcus’ electron transfer theory and the original Marcus–Levich–Jortner (MLJ) theory, and they prove that disorder effects are crucial. Both PL and EQE spectra can be rationalized in terms of the classic Franck–Condon picture of electronic transitions that couple to intra-molecular vibrations as well as low frequency modes of the donor–acceptor pair that forms the CT state.
Investigating the Acceptability and Perceived Effectiveness of a Chatbot in Helping Students Assess their Well-being

Students are vulnerable to health problems due to numerous stressors and overwhelming pressure at home and in school. With the rapid development in AI technologies, there are many opportunities to develop tools that can assist students affected by these problems. Chatbots can serve as a platform for individuals to share their emotions, gain motivation to maintain a healthy lifestyle, and consider professional help. In this paper, we describe the design of our chatbot, named Abot, to encourage students to improve their lifestyle habits and well-being, which are important components to maintaining an optimal mental health. Validation with 25 senior high school students who used Abot for a one-week period showed a positive improvement in their physical well-being, positive change in their social well-being, and positive change in their academic well-being. Students’ evaluation of Abot on a 4-point Likert scale showed an average score of 3.35 on performance, 3.36 on humanity, and 3.68 on affect, which points to perceived user acceptability of the chatbot as a potential tool to help them manage their health and well-being.
Silencing of PFKFB3 protects podocytes against high glucose-induced injury by inducing autophagy

Diabetic nephropathy (DN) is a diabetic complication that threatens the health of patients with diabetes. In addition, podocyte injury can lead to the occurrence of DN. The protein 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) may be associated with diabetes; however, the effects of PFKFB3 knockdown by small interfering (si)RNA on the growth of podocytes remains unknown. To investigate the mechanism by which PFKFB3 mediates podocyte injury, MPC5 mouse podocyte cells were treated with high-glucose (HG), and cell viability and apoptosis were examined by Cell Counting Kit-8 assay and flow cytometry, respectively. In addition, the expression of autophagy-related proteins were measured using western blot analysis and immunofluorescence staining. Cell migration was investigated using a Transwell assay and phalloidin staining was performed to observe the cytoskeleton. The results revealed that silencing of PFKFB3 significantly promoted MPC5 cell viability and inhibited apoptosis. In addition, the migration of the MPC5 cells was notably downregulated by siPFKFB3. Moreover, PFKFB3 silencing notably reversed the HG-induced decrease in oxygen consumption rate, and the HG-induced increase in extracellular acidification rate was rescued by PFKFB3 siRNA. Furthermore, silencing of PFKFB3 induced autophagy in HG-treated podocytes through inactivating phosphorylated (p-)mTOR, p-AMPKα, LC3 and sirtuin 1, and activating p62. In conclusion, silencing of PFKFB3 may protect podocytes from HG-induced injury by inducing autophagy. Therefore, PFKFB3 may serve as a potential target for treatment of DN.
Fewer non‐COVID‐19 respiratory tract infections and gastrointestinal infections during the COVID‐19 pandemic

For preventing the spread of the coronavirus disease 2019 (COVID‐19) pandemic, measures like wearing masks, social distancing, and hand hygiene played crucial roles. These measures may also have affected the expansion of other infectious diseases like respiratory tract infections (RTI) and gastro‐intestinal infections (GII). Therefore, we aimed to investigate non‐COVID‐19 related RTI and GII during the COVID‐19 pandemic. Patients with a diagnosis of an acute RTI (different locations) or acute GII documented anonymously in 994 general practitioner (GP) or 192 pediatrician practices in Germany were included. We compared the prevalence of acute RTI and GII between April 2019–March 2020 and April 2020–March 2021. In GP practices, 715,440 patients were diagnosed with RTI or GII in the nonpandemic period versus 468,753 in the pandemic period; the same trend was observed by pediatricians (275,033 vs. 165,127). By GPs, the strongest decrease was observed for the diagnosis of influenza (−71%, p < 0.001), followed by acute laryngitis (−64%, p < 0.001), acute lower respiratory infections (bronchitis) (−62%, p < 0.001), and intestinal infections (−40%, p < 0.001). In contrast, the relatively rare viral pneumonia strongly increased by 229% (p < 0.001). In pediatrician practices, there was a strong decrease in infection diagnoses, especially influenza (−90%, p < 0.001), pneumonia (−73%, p < 0.001 viral; −76%, p < 0.001 other pneumonias), and acute sinusitis (−66%, p < 0.001). No increase was observed for viral pneumonia in children. The considerable limitations concerning social life implemented during the COVID‐19 pandemic to combat the spread of SARS‐CoV‐2 also resulted in an inadvertent but welcome reduction in other non‐Covid‐19 respiratory tract and gastro‐intestinal infections.
Mechanism and kinetics of cellobiose decomposition in hot-compressed water

Conversion of biomass or biomass-derived liquids in HCW is considered to be a promising technology for the sustainable production of renewable fuels and green chemicals which are currently synthesised from petroleum. However, the yields of target products are low due to the lack of knowledge on fundamental reaction chemistry. Cellulose, as a major model compound of biomass, primarily decomposes in HCW into glucose and its oligomers at various degree of polymerisation. These primary products subsequently experience decomposition reactions into other products. However, apart from glucose, the decomposition of glucose oligomers is still largely unknown. Therefore, the present study aims to understand the fundamental mechanism of glucose oligomers under various conditions, using cellobiose as a model compound. Firstly, cellobiose decomposition in hot-compressed water (HCW) was investigated at a temperature range of 225−275 °C using a continuous reactor system. The liquid products were characterised by high-performance anion exchange chromatography with pulsed amperometric detection and mass spectrometry (HPAEC-PAD/MS). The importance of isomerisation reactions to form two cellobiose isomers (i.e., cellobiulose and glucosyl-mannose) as the primary reaction products is clearly demonstrated under the reaction conditions. The results also confirm another two primary reactions take place during cellobiose decomposition in HCW: retro-aldol condensation reaction to produce glucosyl-erythrose (GE) and glycolaldehyde, and hydrolysis reaction to produce glucose. Isomerisation reactions dominate the primary reactions of cellobiose decomposition, contributing to 71−87% of cellobiose decomposition depending on reaction conditions. In contrast, cellobiose hydrolysis makes only limited contributions (10−20% depending on reaction conditions) to the primary decomposition of cellobiose. The contribution of retro-aldol condensation reaction is very small (<5%) at 225-275 °C. This indicates that hydroxyl ions have a more significant effect in