Miracle-dz/UniFAR-FTUs huggingface dataset:
Adverse Childhood Experiences During the COVID-19 Pandemic and Associations with Poor Mental Health and Suicidal Behaviors Among High School Students — Adolescent Behaviors and Experiences Survey, United States, January–June 2021

Social and educational disruptions during the COVID-19 pandemic have exacerbated concerns about adolescents' mental health and suicidal behavior. Data from the 2021 Adolescent Behaviors and Experiences Survey (ABES) indicate that 37.1% of U.S. high school students reported poor mental health during the COVID-19 pandemic, with 19.9% considering and 9.0% attempting suicide in the preceding year (1). Adverse childhood experiences (ACEs)* are associated with poor mental health and suicidal behaviors (2,3), and high prevalence of some ACEs have been documented during the pandemic (4). ACEs are preventable, potentially traumatic events that occur in childhood (ages 0-17 years) such as neglect, experiencing or witnessing violence, or having a family member attempt or die by suicide. Also included are aspects of a child's environment that can undermine their sense of safety, stability, and bonding. Associations between ACEs occurring during the pandemic and mental health or suicidal behaviors among U.S. high school students were examined using ABES data. Experience of one to two ACEs was associated with poorer mental health and increased suicidal behaviors, and these deleterious outcomes increased with additional ACE exposure. After adjusting for demographic characteristics, adolescents who reported four or more ACEs during the pandemic had a prevalence of poor current mental health four times as high as, and a prevalence of past-year suicide attempts 25 times as high as, those without ACEs during the pandemic. Experience of specific ACE types (e.g., emotional abuse) was associated with higher prevalences of poor mental health and suicidal behaviors. Prevention and intervention strategies (5), including early identification and trauma-informed mental health service and support provision, for ACEs and their acute and long-term impacts could help address the U.S. child and adolescent mental health and suicide crisis. †.
The unexpected 2012 Draconid meteor storm

An unexpected intense outburst of the Draconid meteor shower was detected by the Canadian Meteor Orbit Radar on 2012 October 8. The peak flux occurred at ∼16:40 ut on October 8 with a maximum of 2.4 ± 0.3 h −1 km −2 (appropriate to meteoroid mass larger than 10 −7 kg), equivalent to a ZHR max ≈ 9000 ± 1000 using 5-min intervals, using a mass distribution index of s = 1.88 ± 0.01 as determined from the amplitude distribution of underdense Draconid echoes. This makes the outburst among the strongest Draconid returns since 1946 and the highest flux shower since the 1966 Leonid meteor storm, assuming that a constant power-law distribution holds from radar to visual meteoroid sizes. The weighted mean geocentric radiant in the time interval of 15–19 h ut, 2012 October 8, was α g = 262 $_{. }^{\circ}$4 ± 0 $_{. }^{\circ}$1, δ g = 55 $_{. }^{\circ}$7 ± 0 $_{. }^{\circ}$1 (epoch J2000.0). Visual observers also reported increased activity around the peak time, but with a much lower rate (ZHR ∼ 200), suggesting that the magnitude–cumulative number relationship is not a simple power law. Ablation modelling of the observed meteors as a population does not yield a unique solution for the grain size and distribution of Draconid meteoroids, but is consistent with a typical Draconid meteoroid of m total between 10 −6 and 10 −4 kg being composed of 10–100 grains. Dynamical simulations indicate that the outburst was caused by dust particles released during the 1966 perihelion passage of the parent comet, 21P/Giacobini-Zinner, although there are discrepancies between the modelled and observed timing of the encounter, presumably caused by approaches of the comet to Jupiter during 1966–1972. Based on the results of our dynamical simulation, we predict possible increased activity of the Draconid meteor shower in 2018, 2019, 2021 and 2025.
Phloroglucinol inhibits oxytocin-induced contraction in rat gastric circular muscle and uterine smooth muscle

Abstract Phloroglucinol is commonly used to alleviate dysmenorrhoea and stomach cramps. However, there is little evidence of phloroglucinol in the mechanism of primary dysmenorrhoea (PD) development. In this study, a PD rat model was established. The effects of phloroglucinol on the contraction of rat gastric circular muscle and uterine smooth muscle induced by oxytocin (OT) were investigated. The writhing response, and levels of oestradiol (E2), prostaglandin e2 (PGE2), and prostaglandin f2α (PGF2α) were determined. The protein and mRNA levels of OT receptor (OTR) were detected. OT showed a significant promoting effect on gastric circular muscle and uterine smooth muscle contraction. However, phloroglucinol strongly inhibited the contraction induced by 10−6 mol/L of OT. We also found that phloroglucinol reduced writhing response and attenuated uterine damage. Compared to the blank group, E2 and PGF2α were significantly increased, but PGE2 was significantly decreased in the PD model group. Phloroglucinol was found to reverse the changes of E2, PGF2α and PGE2. Moreover, phloroglucinol reduced the protein and mRNA levels of OTR. In conclusion, phloroglucinol could attenuate PD and inhibit the contraction of rat gastric circular muscle and uterine smooth muscle induced by OT. The mechanism might be related with the regulation of OTR expression. IMPACT STATEMENT What is already known on this subject? Phloroglucinol is commonly used to alleviate dysmenorrhoea and stomach cramps. However, there is little evidence of phloroglucinol in the mechanism of primary dysmenorrhoea (PD) development. What do the results of this study add? Phloroglucinol could attenuate PD and inhibit the contraction of rat gastric circular muscle and uterine smooth muscle induced by OT. The underlying mechanisms of phloroglucinol for PD treatment may be associated with OTR. What are the implications of these findings for clinical practice and/or further research? These findings provide novel ideas for the role of phloroglucinol in PD development.
Adherence to COVID-19 preventive measures and associated factors in Ethiopia: A systematic review and meta-analysis

Background Reluctance to the COVID-19 preventive measures have been repeatedly reported in Ethiopia although compliance with these actions is the key step to minimize the pandemic’s burden. Hence, this systematic review and meta-analysis aims to address the gap in the literature by determining the pooled magnitude of adherence to COVID-19 preventive measures and identifying its associated factors in Ethiopia. Materials and methods The electronic databases used to search articles were PubMed/MEDLINE, CINAHL, Web of Science, ScienceDirect, Research4Life and other sources of grey literature including Google Scholar and World Health Organization (WHO) database portals for low- and middle-income countries. Full English-language articles published between 2019 and 2022 were eligible for the review and meta-analysis. Relevant data extracted and descriptive summaries of the studies presented in tabular form. The methodological quality of articles assessed using the Joanna Briggs Institute (JBI) quality assessment tool. The pooled magnitude of adherence determined by applying a random-effects model at a 95% CI. Results Of 1029 records identified, 15 articles were included in the systematic review and 11 were selected for meta-analysis. The pooled estimate of adherence to COVID-19 preventive measures in Ethiopia was 41.15% (95% CI:32.16–50.14%). Furthermore, perceived COVID-19 disease severity (AOR:1.77, 95% CI: (1.40–2.25)), attitude (AOR:1.85, 95% CI: (1.36–2.53)) and knowledge (AOR:2.51, 95% CI: (1.67–3.78)) to COVID-19 preventive measures showed significant association with adherence to COVID-19 preventive measures. Conclusion The magnitude of adherence to COVID-19 preventive measures in Ethiopia appeared to be low. Therefore, the government of Ethiopia and other stakeholders should mobilize resources to improve the adherence level of the community to the COVID-19 preventive measures and decrease public fatigue.
Within- and across-frequency temporal processing and speech perception in cochlear implant users

Objective Cochlear implant (CI) recipient’s speech perception performance is highly variable and is influenced by temporal processing abilities. Temporal processing is commonly assessed using a behavioral task that requires the participant to detect a silent gap with the pre- and post-gap stimuli of the same frequency (within-frequency gap detection) or of different frequencies (across-frequency gap detection). The purpose of the study was to evaluate behavioral and electrophysiological measures of within- and across-frequency temporal processing and their correlations with speech perception performance in CI users. Design Participants included 11 post-lingually deafened adult CI users (n = 15 ears; Mean Age = 50.2 yrs) and 11 age- and gender-matched normal hearing (NH) individuals (n = 15 ears; Mean Age = 49.0 yrs). Speech perception was assessed with Consonant-Nucleus-Consonant Word Recognition (CNC), Arizona Biomedical Sentence Recognition (AzBio), and Bamford-Kowal-Bench Speech-in-Noise Test (BKB-SIN) tests. Within- and across-frequency behavioral gap detection thresholds (referred to as the GDTwithin and GDTacross) were measured using an adaptive, two-alternative, forced-choice procedure. Cortical auditory evoked potentials (CAEPs) were elicited using within- and across-frequency gap stimuli under four gap duration conditions (no gap, GDT, sub-threshold GDT, and supra-threshold GDT). Correlations among speech perception, GDTs, and CAEPs were examined. Results CI users had poorer speech perception scores compared to NH listeners (p < 0.05), but the GDTs were not different between groups (p > 0.05). Compared to NH peers, CI users showed increased N1 latency in the CAEPs evoked by the across-frequency gap stimuli (p < 0.05). No group difference was observed for the CAEPs evoked by the within-frequency gap (p > 0.05). Three CI ears showing the longest GDTwithin also showed the poorest performance in speech in noise. The within-frequency CAEP increased in amplitude with the increase of gap duration; while the across-frequency CAEP displayed a similar amplitude for all gap durations. There was a significant correlation between speech scores and within-frequency CAEP measures for the supra-threshold GDT condition, with CI users with poorer speech performance having a smaller N1-P2 amplitude and longer N1 latency. No correlations were found among GDTacross, speech perception, and across-frequency CAEP measures. Conclusions Within- and across-frequency gap detection may involve different neural mechanisms. The within-frequency gap detection task can help identify CI users with poor speech performance for rehabilitation. The within-frequency CAEP is a better predictor for speech perception performance than the across-frequency CAEP.
Correlations between serum hepatitis B core-related antigen and hepatitis B surface antigen in patients with hepatitis B cirrhosis and a hepatitis B virus-DNA-negative status: a retrospective study

Objective This study aimed to examine the correlations between serum hepatitis B core-related antigen (HBcrAg) and hepatitis B surface antigen (HBsAg) titers in patients with hepatitis B cirrhosis and a hepatitis B virus (HBV)-DNA-negative status. Methods We retrospectively analyzed the data and blood samples of patients who were diagnosed with HBV liver cirrhosis and an HBV-DNA negative status. These patients were hospitalized between October 2018 and October 2019 at one hospital. Results A total of 180 patients were included. The median (interquartile range) HBsAg and HBcrAg concentrations were 2.77 log10 IU/mL (1.60–3.15) and 3.96 log10 U/mL (2.70–4.97), respectively. A non-linear significant relationship was found between HBsAg and HBcrAg concentrations. The inflection point was 0.58. The effect size and confidence interval on the left and right sides of the inflection point were 0.10 (−0.23–0.42) and 0.62 (0.46–0.78), respectively. When HBsAg concentrations were ≥0.58 log10 IU/mL, HBsAg concentrations were positively correlated with HBcrAg concentrations. When HBsAg concentrations increased by 1 log10 IU/mL, HBcrAg concentrations increased by 0.62 log10 U/mL (95% confidence interval: 0.46, 0.78). Conclusions There might be a non-linear relationship between HBcrAg and HBsAg concentrations in patients with hepatitis B cirrhosis and an HBV-DNA-negative status.
Metabolomics analysis of antiquitin deficiency in cultured human cells and plasma: Relevance to pyridoxine‐dependent epilepsy

Deficiency of antiquitin (α‐aminoadipic semialdehyde dehydrogenase), an enzyme involved in lysine degradation and encoded by ALDH7A1, is the major cause of vitamin B6‐dependent epilepsy (PDE‐ALDH7A1). Despite seizure control with high dose pyridoxine (PN), developmental delay still occurs in approximately 70% of patients. We aimed to investigate metabolic perturbations due to possible previously unidentified roles of antiquitin, which may contribute to developmental delay, as well as metabolic effects of high dose pyridoxine supplementation reflecting the high doses used for seizure control in patients with PDE‐ALDH7A1. Untargeted metabolomics by high resolution mass spectrometry (HRMS) was used to analyze plasma of patients with PDE‐ALDH7A1 and two independently generated lines of cultured ReNcell CX human neuronal progenitor cells (NPCs) with CRISPR/Cas mediated antiquitin deficiency. Accumulation of lysine pathway metabolites in antiquitin‐deficient NPCs and western‐blot analysis confirmed knockdown of ALDH7A1. Metabolomics analysis of antiquitin‐deficient NPCs in conditions of lysine restriction and PN supplementation identified changes in metabolites related to the transmethylation and transsulfuration pathways and osmolytes, indicating a possible unrecognized role of antiquitin outside the lysine degradation pathway. Analysis of plasma samples of PN treated patients with PDE‐ALDH7A1 and antiquitin‐deficient NPCs cultured in conditions comparable to the patient plasma samples demonstrated perturbation of metabolites of the gamma‐glutamyl cycle, suggesting potential oxidative stress‐related effects in PN‐treated patients with PDE‐ALDH7A1. We postulate that a model of human NPCs with CRISPR/Cas mediated antiquitin deficiency is well suited to characterize previously unreported roles of antiquitin, relevant to this most prevalent form of pyridoxine‐dependent epilepsy.
Exact results for the bipartite entanglement entropy of the AKLT spin-1 chain

We study the bipartite entanglement between a subsystem of size l and the rest of the system of total size L as it occurs in a spin-1 Affleck–Kennedy–Lieb–Tasaki (AKLT) chain subject to open boundary conditions. In this case, the ground-state manifold is four-fold degenerate and there is strong dependence on the parity of the number of spins, L. We present exact analytical results for the von Neumann entanglement entropy, as a function of both the size of the subsystem, l, and the total system size, L, for all four degenerate ground states for both odd and even L. In the large l, L limits the entanglement entropy approaches ln (2) for the SzT = ±1 while it approaches twice that value, 2ln (2), for the SzT = 0 states. In all cases, it is found that this constant is approached exponentially fast defining a length scale ξ = 1/ln (3) equal to the known bulk correlation length.
Clinical evaluation of AI-assisted screening for diabetic retinopathy in rural areas of midwest China

Background Although numerous studies have described the application of artificial intelligence (AI) in diabetic retinopathy (DR) screening among diabetic populations, studies among populations in rural areas are rare. The purpose of this study was to evaluate the application value of an AI-based diagnostic system for DR screening in rural areas of midwest China. Methods In this diagnostic accuracy study, diabetes mellitus (DM) patients in the National Basic Public Health Information Systems of Licheng County and Lucheng County of Changzhi city from July to December 2020 were selected as the target population. A total of 7824 eyes of 3933 DM patients were enrolled in this screening; the patients included 1395 males and 2401 females, with an average age of 19–87 years (63±8.735 years). All fundus photographs were collected by a professional ophthalmologist under natural pupil conditions in a darkroom using the Zhiyuan Huitu fundus image AI analysis software EyeWisdom. The AI-based diagnostic system and ophthalmologists were tasked with diagnosing the photos independently, and the consistency rate, sensitivity and specificity of the two methods in diagnosing DR were calculated and compared. Results The prevalence rates of DR according to the ophthalmologist and AI diagnoses were 22.7% and 22.5%, respectively; the consistency rate was 81.6%. The sensitivity and specificity of the AI system relative to the ophthalmologists’ grades were 81.2% (95% confidence interval [CI]: 80.3% 82.1%) and 94.3% (95% CI: 93.7% 94.8%), respectively. There was no significant difference in diagnostic outcomes between the methods (χ2 = 0.329, P = 0.566, P>0.05), and the AI-based diagnostic system had high consistency with the ophthalmologists’ diagnostic results (κ = 0.752). Conclusion Our research demonstrated that DR patients in rural area hospitals can be screened feasibly. Compared with that of the ophthalmologists, however, the accuracy of the AI system must be improved. The results of this study might lend support to the large-scale application of AI in DR screening among different populations.
Molecular dynamics simulation study on the structures of fascin mutants

Fascin is a filamentous actin (F‐actin) bundling protein, which cross‐links F‐actin into bundles and becomes an important component of filopodia on the cell surface. Fascin is overexpressed in many types of cancers. The mutation of fascin affects its ability to bind to F‐actin and the progress of cancer. In this paper, we have studied the effects of residues of K22, K41, K43, K241, K358, K399, and K471 using molecular dynamics (MD) simulation. For the strong‐effect residues, that is, K22, K41, K43, K358, and K471, our results show that the mutation of K to A leads to large values of root mean square fluctuation (RMSF) around the mutated residues, indicating those residues are important for the flexibility and thermal stability. On the other hand, based on residue cross‐correlation analysis, alanine mutations of these residues reinforce the correlation between residues. Together with the RMSF data, the local flexibility is extended to the entire protein by the strong correlations to influence the dynamics and function of fascin. By contrast, for the mutants of K241A and K399A those do not affect the function of fascin, the RMSF data do not show significant differences compared with wild‐type fascin. These findings are in a good agreement with experimental studies.
Not your Mother’s MAPKs: Apicomplexan MAPK function in daughter cell budding

Reversible phosphorylation by protein kinases is one of the core mechanisms by which biological signals are propagated and processed. Mitogen-activated protein kinases, or MAPKs, are conserved throughout eukaryotes where they regulate cell cycle, development, and stress response. Here, we review advances in our understanding of the function and biochemistry of MAPK signaling in apicomplexan parasites. As expected for well-conserved signaling modules, MAPKs have been found to have multiple essential roles regulating both Toxoplasma tachyzoite replication and sexual differentiation in Plasmodium. However, apicomplexan MAPK signaling is notable for the lack of the canonical kinase cascade that normally regulates the networks, and therefore must be regulated by a distinct mechanism. We highlight what few regulatory relationships have been established to date, and discuss the challenges to the field in elucidating the complete MAPK signaling networks in these parasites.
UltraButton: A Minimalist Touchless Multimodal Haptic Button

We present UltraButton a minimalist touchless button including haptic, audio and visual feedback costing only $200. While current mid-air haptic devices can be too bulky and expensive (around $2 k) to be integrated into simple mid-air interfaces such as point and select, we show how a clever arrangement of 83 ultrasound transducers and a new modulation algorithm can produce compelling mid-air haptic feedback and parametric audio at a minimal cost. To validate our prototype, we compared its haptic output to a commercially-available mid-air haptic device through force balance measurements and user perceived strength ratings and found no significant differences. With the addition of 20 RGB LEDs, a proximity sensor and other off-the-shelf electronics, we then propose a complete solution for a simple multimodal touchless button interface. We tested this interface in a second experiment that investigated user gestures and their dependence on system parameters such as the haptic and visual activation times and heights above the device. Finally, we discuss new interactions and applications scenarios for UltraButtons.
Noise-Robust Sleep Staging via Adversarial Training With an Auxiliary Model

Deep learning (DL)-based automatic sleep staging approaches have attracted much attention recently due in part to their outstanding accuracy. At the testing stage, however, the performance of these approaches is likely to be degraded, when applied in different testing environments, because of the problem of domain shift. This is because while a pre-trained model is typically trained on noise-free electroencephalogram (EEG) signals acquired from accurate medical equipment, deployment is carried out on consumer-level devices with undesirable noise. To alleviate this challenge, in this work, we propose an efficient training approach that is robust against unseen arbitrary noise. In particular, we propose to generate the worst-case input perturbations by means of adversarial transformation in an auxiliary model, to learn a wide range of input perturbations and thereby to improve reliability. Our approach is based on two separate training models: (i) an auxiliary model to generate adversarial noise and (ii) a target network to incorporate the noise signal to enhance robustness. Furthermore, we exploit novel class-wise robustness during the training of the target network to represent different robustness patterns of each sleep stage. Our experimental results demonstrated that our approach improved sleep staging performance on healthy controls, in the presence of moderate to severe noise levels, compared with competing methods. Our approach was able to effectively train and deploy a DL model to handle different types of noise, including adversarial, Gaussian, and shot noise.
Equations of motion in metric-affine gravity: A covariant unified framework

We derive the equations of motion of extended deformable bodies in metric-affine gravity. The conservation laws which follow from the invariance of the action under the general coordinate transformations are used as a starting point for the discussion of the dynamics of extended deformable test bodies. By means of a covariant approach, based on Synge's world function, we obtain the master equation of motion for an arbitrary system of coupled conserved currents. This unified framework is then applied to metric-affine gravity. We confirm and extend earlier findings; in particular, we once again demonstrate that it is only possible to detect the post-Riemannian spacetime geometry by ordinary (nonmicrostructured) test bodies if gravity is nonminimally coupled to matter.