Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of domains in Plasmodium falciparum proteins of unknown function using DALI search on Alphafold predictions

Plasmodium falciparum, the causative agent of malaria, poses a significant global health challenge, yet much of its biology remains elusive. A third of the genes in the P. falciparum genome lack annotations regarding their function, impeding our understanding of the parasite’s biology. In this study, we employed structure predictions and the DALI search algorithm to analyse proteins encoded by uncharacterized genes in the reference strain 3D7 of P. falciparum. By comparing Alphafold predictions to experimentally determined protein structures in the Protein Data Bank, we found similarities to known domains in 353 proteins of unknown function, shedding light on their potential functions. The lowest-scoring 5% of similarities were additionally validated using the size-independent TM-align algorithm, confirming the detected similarities in 88% of the cases. Notably, in over 70 P. falciparum proteins the presence of domains resembling heptatricopeptide repeats, which are typically involvement in RNA binding and processing, was detected. This suggests this family, which is important in transcription in mitochondria and apicoplasts, is much larger in Plasmodium parasites than previously thought. The results of this domain search provide a resource to the malaria research community that is expected to inform and enable experimental studies.
Dynamic Phytomeric Growth Contributes to Local Adaptation in Barley

Abstract Vascular plants have segmented body axes with iterative nodes and internodes. Appropriate node initiation and internode elongation are fundamental to plant fitness and crop yield; however, how these events are spatiotemporally coordinated remains elusive. We show that in barley (Hordeum vulgare L.), selections during domestication have extended the apical meristematic phase to promote node initiation, but constrained subsequent internode elongation. In both vegetative and reproductive phases, internode elongation displays a dynamic proximal—distal gradient, and among subpopulations of domesticated barleys worldwide, node initiation and proximal internode elongation are associated with latitudinal and longitudinal gradients, respectively. Genetic and functional analyses suggest that, in addition to their converging roles in node initiation, flowering-time genes have been repurposed to specify the timing and duration of internode elongation. Our study provides an integrated view of barley node initiation and internode elongation and suggests that plant architecture should be recognized as a collection of dynamic phytomeric units in the context of crop adaptive evolution.
Comments on the nature of HD 75767

HD 75767 is a nearby solar-type star. It has an unseen companion with which it is in an orbit that is very slightly off-circular and has a period of about 10 d. In addition, it has a faint visual companion. Wraight et al., in a recent paper, have built a considerable edifice on the idea that the orbital period has shown a perceptible change within the last 100 yr. We point out that the phase shift that constitutes their evidence for such a change arises only from their use of their own, relatively inaccurate, value for the period. Rotational-velocity measurements for HD 75767, published independently by each of the authors and by others, have all been smaller than would correspond to the equatorial velocity if the star’s rotation were synchronized to the orbital revolution. Each of the present authors has accordingly proposed (explicitly on the assumption of synchronism) an inclination corresponding to his favoured value of v sin i. There is, therefore, implicit surprise at the discovery by Wraight et al. that the system exhibits eclipses and therefore the orbital inclination must be close to 90◦. The logical conclusion must be that the star is rotating more slowly than would correspond to synchronism with the orbit.
Reduced differential transform method for partial differential equations within local fractional derivative operators

The non-differentiable solution of the linear and non-linear partial differential equations on Cantor sets is implemented in this article. The reduced differential transform method is considered in the local fractional operator sense. The four illustrative examples are given to show the efficiency and accuracy features of the presented technique to solve local fractional partial differential equations.
Real and effective thermal equilibrium in artificial square spin ices

Jason P. Morgan,1 Johanna Akerman,1,2 Aaron Stein,3 Charudatta Phatak,4 R. M. L. Evans,1 Sean Langridge,5 and Christopher H. Marrows1,* 1School of Physics and Astronomy, University of Leeds, Leeds LS2 9JT, United Kingdom 2Instituto de Sistemas Optoelectronicos y Microtecnologia (ISOM), Universidad Politecnica de Madrid, Avenida Complutense s/n, 28040 Madrid, Spain 3Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York 11973, USA 4Materials Science Division, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60439, USA 5ISIS, STFC Rutherford Appleton Laboratory, Chilton, Didcot OX11 0QX, United Kingdom (Received 17 August 2011; revised manuscript received 24 October 2012; published 9 January 2013)
Stability of equilibria for 2-D resonant Hamiltonian systems: a geometrical approach

The stability of an equilibrium point of a 2-D Hamiltonian system, in the presence of resonances, is decided by means of a geometrical criterium, when the corresponding quadratic part is not sign defined. It is proven that this method is the geometrical counterpart of a theorem of Cabral and Meyer which constitutes an extension of the Arnold’s theorem.
Detection Method for Non-circular Spinneret Hole

With the application of CCD,the enlarged non-circular spinneret holes image was captured,followed by edge detection and preprocessing of thresholding and edge thinning.In the measurement of non-circular degree parameter,the basic circular and linear elements were first detected,then the method of least square was used to fit circular and linear for obtaining more accurate parameter.This method can achieve the judgment of block and detection of shaped degree for non-circular spinneret hole.Experimental results show that this method has the high precision and speed detection.Meanwhile,it is suitable for non-circular spinneret holes detection in synthetic fiber industry.
Improved Canonical Correlation Analysis and Its Applications in Image Recognition

The objective function of traditional canonical correlation analysis (CCA) is to maximize the correlations of the two observations of the same patterns, which can be regarded as a unsupervised learning method. Based on the traditional CCA, by introducing the class overall correlation matrix to improve the objective function, a new improved canonical correlation analysis (ICCA) method of multi-mode feature extraction is proposed, which is a supervised learning algorithm. The theory of ICCA can be explained as follows: If a pattern has a pair of observations (For any pattern space, there has two observation spaces), ICCA can find a relevant subspace of the two observation spaces, in which the mappings of the pair observations have maximum correlation, and in the relevant subspace, the mappings can have more discriminate semantic information for pattern recognition. The process of ICCA can be divided into three steps: extract two groups of feature vectors with the same pattern; establish the objective function of maximizing the class overall correlations of the all classes; extract their improved canonical correlation features to form effective discriminate vectors for recognition. Our proposed algorithm ICCA is validated by the experiments on Yale face database. Be compare with other methods, the recognition rate of our method is far higher than that of PCA algorithm only adopting single-mode features and the traditional CCA multi-mode feature fusion algorithm.
Modeling inter-individual differences in ambulatory-based multimodal signals via metric learning: a case study of personalized well-being estimation of healthcare workers

Introduction Intelligent ambulatory tracking can assist in the automatic detection of psychological and emotional states relevant to the mental health changes of professionals with high-stakes job responsibilities, such as healthcare workers. However, well-known differences in the variability of ambulatory data across individuals challenge many existing automated approaches seeking to learn a generalizable means of well-being estimation. This paper proposes a novel metric learning technique that improves the accuracy and generalizability of automated well-being estimation by reducing inter-individual variability while preserving the variability pertaining to the behavioral construct. Methods The metric learning technique implemented in this paper entails learning a transformed multimodal feature space from pairwise similarity information between (dis)similar samples per participant via a Siamese neural network. Improved accuracy via personalization is further achieved by considering the trait characteristics of each individual as additional input to the metric learning models, as well as individual trait base cluster criteria to group participants followed by training a metric learning model for each group. Results The outcomes of the proposed models demonstrate significant improvement over the other inter-individual variability reduction and deep neural baseline methods for stress, anxiety, positive affect, and negative affect. Discussion This study lays the foundation for accurate estimation of psychological and emotional states in realistic and ambulatory environments leading to early diagnosis of mental health changes and enabling just-in-time adaptive interventions.
Biofertilizer based on halotolerant microorganisms promotes the growth of rice plants and alleviates the effects of saline stress

Long-term soil salinization easily contributes to soil hardness, soil nutrient imbalance, and soil microbial diversity reduction, resulting in low rice yields in the salinized fields, and microbial remediation is one of the important measures to improve salinized soil. To verify the effect of biofertilizer based on halotolerant microorganisms on promoting rice growth and alleviating saline stress, this study discussed the effects of biofertilizer on soil microbial diversity and community structure and analyzed the correlation between the formation of microbial community structure and soil nutrient factors in the salinized field. The result, in comparison with applying inorganic fertilizer (referred to as CK), showed that notably increased soil available nitrogen, available phosphorus, available potassium, and rice paddy yield (p < 0.05) and significantly decreased soil electrical conductivity (p < 0.05) were achieved via biofertilizer (referred to as G2). Additionally, the application of biofertilizer contributes to the increase in soil microbial diversity and reorganization of microbial community structure, and through the analysis of linear discriminant analysis effect size, a notable difference in relative abundance was found in 13 genera, 6 families, and 3 orders between the control group and experimental groups (p < 0.05), and by linear discriminant analysis, Desulfomonas was further identified as the differentiated indicator. The redundancy analysis showed that available phosphorus and cation exchange capacity were the key environmental factors that affected microbial community structure and composition. Through bacterial functional prediction, increased rhizosphere soil bacterial metabolism, enzyme activity, membrane transport, and other potential functions were achieved by applying biofertilizer. Therefore, the application of biofertilizer could significantly alleviate rice growth stress and increase nutrient supply capacity in saline soil. These findings provide theoretical support for soil microbial improvement technology in the salinized field.
Health-related quality of life of children with Williams syndrome and caregivers in China

Introduction Williams syndrome (WS) is a rare genetic disorder that impacts multiple systems and may cause developmental delays. These medical and developmental issues impose a heavy burden on affected children and their families. However, there was no study on children’s health-related quality of life (HRQoL) with WS and only two studies about family quality of life globally. Therefore, the primary purpose of this study was to assess the HRQoL of children with WS and their caregivers in China, and the secondary purpose was to identify the potential determinants of children’s and caregivers’ HRQoL. Methods In total, 101 children and caregivers were included. We applied the proxy-reported PedsQL 4.0 Generic Core Module (PedsQL GCM) and PedsQL 3.0 Family Impact Module (FIM) to measure the HRQoL of children and caregivers. Additionally, we collected information on a comprehensive set of social demographic and clinical characteristics. Differences in HRQoL scores across subgroups were assessed by two-independent-samples t-tests, one-way ANOVA, and post hoc tests. We also calculated effect sizes to indicate clinical relevance. Multivariate linear regression models were applied to assess the potential determinants of HRQoL. Results We found that the HRQoL of children with WS and their caregivers was dramatically worse than the norm average scores of the healthy controls of children published in previous studies. Paternal educational level, household income, and the perceived financial burden significantly influenced the HRQoL of both children and families (p-values < 0.05). Multivariate linear regression analysis showed that the perceived financial burden was independently associated with family quality of life (p-values < 0.05). , and the presence of sleeping problem was independently associated with children’s HRQoL (p-value = 0.01). Conclusion We call for attention from policymakers and other stakeholders on the health status and well-being of children with WS and their families. Supports are needed to relieve psychosocial distress and financial burden.
Indocyanine green angiography for lower incidence of anastomotic leakage after transanal total mesorectal excision: a propensity score-matched cohort study

Background Anastomotic leakage (AL) is the most serious complication that can arise during colorectal surgery. Indocyanine green (ICG) angiography offers an intraoperative assessment of colonic vascular perfusion in real time. We aimed to assess ICG’s effects on the AL rate in patients who have undergone transanal total mesorectal excision (TaTME) for rectal cancer. Methods This retrospective cohort study was conducted at our center from October 2018 to March 2022 to analyze the clinical data of patients with rectal cancer who have undergone TaTME after propensity score matching (PSM). The primary outcome was the proximal colonic transection line modification and clinical AL rate. Results A total of 143 patients in the non-ICG group and 143 patients in the ICG group were included after PSM. The proximal colonic transection line of seven patients in the non-ICG group was modified, while 18 were in the ICG group (4.9% vs. 12.5%, p = 0.023). Twenty-three patients (16.1%) in the non-ICG group and five patients (3.5%) in the ICG group were diagnosed with AL (p < 0.001). The ICG group had a less hospital readmission rate than the non-ICG group (0.7% vs. 7.7%, p = 0.003). The between-group differences in basic line and other outcomes were not significant. Conclusions ICG angiography is a safe and feasible method to help surgeons identify potentially poor colonic vascular perfusion and modify the proximal colonic transection line, resulting in a significant reduction in AL and hospital readmission rates.
Identifying factors influencing COVID-19 vaccine uptake in Finland – a qualitative study using social media data

Introduction Vaccine demand creation requires understanding what is driving the uptake of the vaccine. 24 Qualitative research methods are paramount to gaining a localized understanding of behavioral 25 drivers and barriers to vaccine uptake, but they are often underutilized. Methods This is a qualitative study that 26 used public comments on the Facebook and Twitter posts of the Finnish Institute for Health and 27 Welfare (THL) as data sources to identify behavioral drivers for COVID-19 vaccine uptake in 28 Finland. The participatory data analysis utilized thematic analysis and the Theoretical Domains 29 Framework (TDF). NVIVO was used to assist in the coding process. Results The greatest number of FB and 30 Twitter comments were linked with six TDF domains: knowledge, environmental context and 31 resources, beliefs in consequences, beliefs in capabilities, social and professional role, and social 32 influences. The domains included 15 themes that were interlinked. The knowledge domain 33 overlapped with all other domains. Discussion By using public discourse on Facebook and Twitter, and rapid 34 qualitative data analysis methods within a behavioral insight framework, this study adds to the 35 emerging knowledge about behavioral drivers of COVID-19 vaccines that can be used by public 36 health experts to enhance the uptake of vaccines during future pandemics and epidemics.
Optogenetic manipulation of inhibitory interneurons can be used to validate a model of spatiotemporal sequence learning

The brain uses temporal information to link discrete events into memory structures supporting recognition, prediction, and a wide variety of complex behaviors. It is still an open question how experience-dependent synaptic plasticity creates memories including temporal and ordinal information. Various models have been proposed to explain how this could work, but these are often difficult to validate in a living brain. A recent model developed to explain sequence learning in the visual cortex encodes intervals in recurrent excitatory synapses and uses a learned offset between excitation and inhibition to generate precisely timed “messenger” cells that signal the end of an instance of time. This mechanism suggests that the recall of stored temporal intervals should be particularly sensitive to the activity of inhibitory interneurons that can be easily targeted in vivo with standard optogenetic tools. In this work we examined how simulated optogenetic manipulations of inhibitory cells modifies temporal learning and recall based on these mechanisms. We show that disinhibition and excess inhibition during learning or testing cause characteristic errors in recalled timing that could be used to validate the model in vivo using either physiological or behavioral measurements.
Nearly one out of every five adult TB patients suffered from food insecurity in Grawa District, Eastern Ethiopia: a multicenter facility-based cross-sectional study

Background Despite a dramatic decline in tuberculosis mortality over the past 10 years, tuberculosis is still the leading cause of death globally. In the last 2 years, tuberculosis has affected an estimated 10 million individuals, and 1.4 million people have died worldwide. In Ethiopia, the weight of the problem is less known in the study area. As a result, the purpose of this study was to assess food insecurity and associated factors among adult patients with tuberculosis attending public health facilities in Grawa district, Eastern Ethiopia. Methods A multicenter facility-based cross-sectional study was conducted from 01 March to 31 March 2022, among 488 randomly selected adult tuberculosis patients on treatment follow-up at public health facilities in Grawa district, Eastern Ethiopia. Data were collected using a pretested structured questionnaire through a face-to-face interview and document review, entered into EpiData version 3.1, and analyzed using SPSS version 25. The prevalence was reported using a 95% confidence interval (CI) and summary measures. Predictors were assessed using a multivariable logistic regression analysis model and reported using an adjusted odds ratio (AOR) with 95% CI. Statistical significance was declared at a p-value of <0.05. Results Overall, the prevalence of food insecurity among the study participants was 19.5%, with a 95% CI (15.8%, 23.2%). Factors such as being male [AOR = 0.58, 95% CI: (0.34, 0.97)], being married [AOR = 2.93, 95% CI: (1.33, 6.47)], being merchant [AOR = 0.22, 95% CI: (0.04, 0.67)], having low wealth quintiles [AOR = 2.10,95%CI:(1.04–4.23)], receiving anti-TB treatment for two or fewer months [AOR = 0.48, 95% CI: (0.26–0.91)], using khat [AOR = 2.18, 95% CI: (1.29, 3.70)], and owning livestock (AOR = 0.56, 95% CI: 0.29–0.94) were significantly associated with food insecurity. Conclusions According to this study, nearly one out of every five adults TB patients is food insecure. Factors such as being male, being married, being merchant, having low wealth quintiles, receiving anti-TB treatment for two or less months, those who chew mKhat and having a livestock were significantly associated with food insecurity. As a result, all stakeholders and concerned entities should prioritize improving the livelihood of TB patients through social security system programs, which are critical to the success of TB control and prevention efforts.
Gender dimensions of health-related challenges among urban poor during COVID-19 pandemic in low-and middle-income countries: a systematic review and gap analysis

The COVID-19 pandemic has varying effects on men, women, and the transgender population. However, there is a paucity of systematic evidence on how gender and other social determinants of health during COVID-19 are affected in resource constraint urban settings. This review describes the gender dimensions of health-related challenges among the urban poor during COVID-19 in LMICs. We searched 11 scholarly online repositories including PubMed, Embase, Web of Science, CINAHL using the domain “slums,” “COVID-19”, “LMICs” and “gender identities. ” We used thematic framework analysis to synthesize qualitative data, and meta-analysis to determine the pooled prevalence. We registered in PROSPERO (CRD42020203783). We identified 6490 records, and 37 articles included. The studies reported stress among 74% women and 78% men, depression among 59% women and 62% men, and anxiety among 79% women and 63% men. Men had more stress than women during COVID-19; men are primarily responsible for household sustenance. Women had more anxiety than men, possibly because they are often the primary caregivers for children and the older population. While the severity varies according to gender identity, their vulnerability mostly related to their literacy and economy, highlighting the significance of including all social determinants in future primary studies. Systematic review registration https://www.crd. york.ac. uk/prospero/#recordDetails.