Miracle-dz/UniFAR-FTUs huggingface dataset:
High-level expression of leghemoglobin in Kluyveromyces marxianus by remodeling the heme metabolism pathway

Soy leghemoglobin, when bound to heme, imparts a meat-like color and flavor and can serve as a substitute for animal-derived proteins. Enhancing cellular heme synthesis improves the recombinant expression of leghemoglobin in yeast. To achieve high-level expression of leghemoglobin A (LBA) in Kluyveromyces marxianus, a food-safe yeast, large-scale heme synthesis modules were transferred into K. marxianus using yeast artificial chromosomes (KmYACs). These modules contained up to 8 native and heterologous genes to promote the supply of heme precursors and downstream synthesis. Next, eight genes inhibiting heme or LBA synthesis were individually or combinatorially deleted, with the lsc1Δssn3Δ mutant yielding the best results. Subsequently, heme synthesis modules were combined with the lsc1Δssn3Δ mutant. In the resulting strains, the module genes were all actively expressed. Among these module genes, heterologous S. cerevisiae genes in the downstream heme synthesis pathway significantly enhanced the expression of their counterparts in K. marxianus, resulting in high heme content and LBA yield. After optimizing the medium recipe by adjusting the concentrations of glucose, glycine, and FeSO4·7H2O, a heme content of 66.32 mg/L and an intracellular LBA titer of 7.27 g/L were achieved in the engineered strain in a 5 L fermentor. This represents the highest intracellular expression of leghemoglobin in microorganisms to date. The leghemoglobin produced by K. marxianus can be utilized as a safe ingredient for plant-based protein products.
Mechanism analysis of Buyang Huanwu decoction in treating atherosclerosis based on network pharmacology and in vitro experiments

Atherosclerosis (AS) is one of the main risk factors of ischemic cardiovascular and cerebrovascular diseases. Buyang Huanwu decoction (BYHWT) is a classic Chinese medicine prescription that is used for treating AS. However, the underlying pharmacological mechanism remains unclear. This study aims to clarify the molecular mechanism of BYHWT in treatment of AS through network pharmacology and in vitro experiments. Molecular structure information and targets of core components of BYHWT were obtained from PubChem and UniProtKB databases. Genes involved in AS were obtained from DisGeNet, GeneCards and OMIM databases. The core targets of BYHWT in AS treatment were identified by protein–protein interaction (PPI) network analysis with STRING platform, and analyzed by gene ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway enrichment analysis. Molecular docking was used to verify the binding affinity between the core targets and the bioactive ingredients. HUVEC viability, inflammatory response and mRNA expression levels of core target genes were evaluated by cell counting kit 8 assay, enzyme‐linked immunosorbent assay (ELISA) and qRT‐PCR. A total of 60 candidate compounds and 325 predicted target genes were screened. PPI network analysis suggested that TP53, SRC, STAT3, and AKT1 may be the core targets. BYHWT in AS treatment was associated with 46 signaling pathways. GA120, baicalein, and 3,9‐di‐o‐methylnissolin had good binding affinity with core target proteins. Baicalein treatment could significantly promoted the viability and repress the inflammatory response of HUVEC cells stimulated by ox‐LDL. In addition, Baicalein can regulate the expression of core targets including AKT1, MAPK1, PIK3CA, JUN, TP53, SRC, EGFR, and ESR1. In conclusion, BYHWT and its main bioactive component baicalein, inhibit inflammatory response and modulate multiple downstream genes of endothelial cells, and show good potential to block the progression of AS and cardiovascular/cerebrovascular diseases.
Impact of an upgraded model in the NCEP Global Ocean Data Assimilation System: The tropical Indian Ocean

The National Centers for Environmental Prediction (NCEP) and the Indian National Centre for Ocean Information Services (INCOIS) produces global ocean analysis based on the Global Ocean Data Assimilation System (GODAS). This study shows how upgrades to the forward model simulations from MOM4p0d to MOM4p1 impact ocean analyses over the tropical Indian Ocean in GODAS. Three experiments were performed with same atmospheric forcing fields: (i) using MOM4p0d (GODAS_p0), (ii) using MOM4p1 (GODAS_p1), both using observed temperature and synthetic salinity, and (iii) using MOM4p1 (GODAS_p1S) assimilating both observed temperature and observed salinity. Validation with independent observations shows significant improvement of subsurface temperature and salinity in the new analysis using MOM4p1 versus MOM4p0d. There is also improvement in the upper ocean current of the equatorial Indian Ocean. The impact of observed salinity on the upper ocean surface current is marginal, but there is significant improvement in the subsurface current. The seasonal and inter-annual variability of the Wyrtki jet and the equatorial undercurrent is improved in GODAS_p1 versus GODAS_p0. All analyses reproduced the Indian Ocean dipole, with the GODAS_p1S simulated sea surface temperature (SST) the most accurate. The temperature inversion over the north Bay of Bengal (BoB) is reproduced only in GODAS_p1S. The mean sea level over BoB and equatorial Indian Ocean improved in GODAS_p1S as compared with AVISO observation. The combined model upgrade and assimilation of observed salinity led to reduced root-mean-square deviation and higher correlation coefficient values in the sea level anomaly (SLA) when compared with satellite observations.
Board Co-Option and Corporate Social Responsibility

: This paper investigates the impact of board co-optation on corporate social responsibility (CSR). It shows that board co-option carries a negative relationship with CSR based on a sample of 14,359 U.S. public companies. In line with the stakeholder theory, businesses with more co-opted directors are less inclined to protect the interests of their stakeholders, which results in firms engaging in less CSR. The paper also discovers reliable results using a propensity score matching approach and a high-dimensional fixed effect model.
Common lower extremity injuries in sports and their recovery and preventive measures

Lower extremity injuries and diseases are common problems during exercise. Understanding how these problems work and how to recover can help people better prevent and treat them so they stay healthy. Among different exercise, there are different kinds of injuries, for example, hamstring strains, groin pull, quadriceps strains, runner's knee, patellar tendinitis, ACL tear, lower leg stress fractures, muscle cramps, achilles tendonitis, ankle sprains, plantar fasciitis. Therefore, the main purpose of this article is to archive some lower extremity injuries and diseases that may occur during sports through literature research, and to provide readers with an understanding of lower extremity injuries from multiple perspectives, including the injury itself, rehabilitation and prevention. The basis of the mechanism. This article lists many typical lower extremity injuries and diseases, introduces their characteristics and rehabilitation methods. For example, knee pain is one of the common problems in sports and can be caused by a variety of reasons. Rehabilitation methods include physical therapy, surgery, and more. In addition to enumerating and introducing typical lower extremity injuries and diseases, this article also provides some common preventive methods to help readers pay attention to possible risks in daily life and take corresponding measures to reduce the risk of injury. For example, when exercising, you should gradually increase the intensity and time, and avoid sudden increases, so as not to cause injuries. In addition, correct posture and correct footwear are also important factors in preventing lower extremity injuries.
New insights in animal models of neurotoxicity-induced neurodegeneration

The high prevalence of neurodegenerative diseases is an unintended consequence of the high longevity of the population, together with the lack of effective preventive and therapeutic options. There is great pressure on preclinical research, and both old and new models of neurodegenerative diseases are required to increase the pipeline of new drugs for clinical testing. We review here the main models of neurotoxicity-based animal models leading to central neurodegeneration. Our main focus was on studying how changes in neurotransmission and neuroinflammation, mainly in rodent models, contribute to harmful processes linked to neurodegeneration. The majority of the models currently in use mimic Parkinson’s disease (PD) and Alzheimer’s disease (AD), which are the most common neurodegenerative conditions in older adults. AD is the most common age-related dementia, whereas PD is the most common movement disorder with also cases of dementia. Several natural toxins and xenobiotic agents induce dopaminergic neurodegeneration and can reproduce neuropathological traits of PD. The literature analysis of MPTP, 6-OH-dopamine, and rotenone models suggested the latter as a useful model when specific doses of rotenone were administrated systemically to C57BL/6 mice. Cholinergic neurodegeneration is mainly modelled with the toxin scopolamine, which is a useful rodent model for the screening of protective drugs against cognitive decline and AD. Several agents have been used to model neuroinflammation-based neurodegeneration and dementia in AD, including lipopolysaccharide (LPS), streptozotocin, and monomeric C-reactive protein. The bacterial agent LPS makes a useful rodent model for testing anti-inflammatory therapies to halt the development and severity of AD. However, neurotoxin models might be more useful than genetic models for drug discovery in PD but that is not the case in AD where they cannot beat the new developments in transgenic mouse models. Overall, we should work using all available models, either in vivo, in vitro, or in silico, considering the seriousness of the moment and urgency of developing effective drugs.
An Improved Empirical Wavelet Transform Filtering Method for Rail-Head Surface-Defect Magnetic-Flux Leakage Signal

The rail is an important factor in railway traffic safety. Surface defects in the rail head comprise a common type of rail damage, and magnetic flux leakage (MFL) technology is applied for its detection. MFL detection is influenced by various factors, resulting in high noise and a low signal-to-noise ratio (SNR) in the collected MFL signal, which influence defect assessment. This article improves the empirical wavelet transform (EWT) to apply it to rail surface-defect MFL signal filtering. A boundary optimization method based on mutual information (MI) is proposed to reduce the boundary redundancy caused by adaptive spectrum division. A method for component selection based on MI and kurtosis is proposed to select the suitable components from the decomposed components for signal reconstruction. The experimental results show that the method can effectively filter out the interference in the MFL signal, and the effectiveness is superior to the traditional methods, such as complementary ensemble empirical mode decomposition (CEEMD) and wavelet transform (WT).
Behavioral development within one-year-old individuals of Sichuan snub-nosed monkeys Rhinopithecus roxellana in the Qinling Mountains

Between March 2003 and May 2004, we studied the behavioral development of five Sichuan snub-nosed monkeys Rhinopithecus roxellana at Yuhuangmiao, Zhouzhi National Nature Reserve in Shaanxi, China. We sampled the infants using focal animal sampling and collected data using the all-occurrences recording technique. Our results showed that infants first ventured away from their mother at 23 days of age and engaged in exploratory play at 68 days of age. At 5 months, they actively fed on solid foods and were capable of traveling with the troop by 6 months of age. Based on the first appearances of behaviors, we divided R.roxellana’s development into five stages: Stage 1 (0-1 month), complete dependence; Stage 2 (1-2 months), exploration; Stage 3 (3-7 months), socialization;Stage 4 (8-10 months), adaptation; and Stage 5 (11-12 months), gradual independence. During the first year, the infants could be found in physical contact with their mother or another caretaker. They also could be located either on tree branches or on the ground. Time spent in contact with the mother and other caretakers was negatively correlated with infants’ age. There was no significant correlation between infants’ age and time spent on branches. However, time spent on the ground was positively correlated with infants’ age
Machine Learning untuk Peramalan Kualitas Indeks Standar Pencemar Udara DKI Jakarta dengan Metode Hibrid ARIMAX-LSTM

Polusi udara merupakan tantangan lingkungan global yang signifikan, menyebabkan dampak serius terhadap kesehatan masyarakat tidak terkecuali di Jakarta. Dengan Indeks Standar Pencemaran Udara (ISPU) sebagai parameter utama untuk memantau kualitas udara. Meskipun ISPU memberikan informasi saat ini, informasi yang diberikan untuk kualitas udara di masa mendatang masih terbatas. Oleh karena itu, diperlukan pendekatan yang lebih canggih, dan salah satu metode yang menjanjikan adalah menggunakan teknik machine learning (ML). Metode ML telah terbukti efektif dalam pemantauan dan peramalan kualitas udara. Namun, untuk meningkatkan akurasi peramalan, pendekatan hibridisasi, seperti menggabungkan dua model telah diusulkan. Pendekatan ini dapat memberikan deteksi pola yang lebih komprehensif dan meningkatkan akurasi hasil peramalan. Penelitian ini bertujuan untuk memprediksi ISPU di DKI Jakarta menggunakan model hibrid ARIMAX-LSTM. Data polusi udara dari tahun 2012 hingga 2022 akan digunakan, bersama dengan variabel eksternal seperti volume kendaraan, temperatur, kelembapan, dan kecepatan angin. Model ini mampu menghasilkan model prediksi dengan RMSE 13.00; 20.51; dan 17.10 untuk masing-masing polutan PM10, PM2.5, dan O3. Sedangkan metriks MAPE yang dihasilkan dari model hibrid adalah 0.1916; 0.1917; dan 0.2869 untuk masing-masing polutan PM10, PM2.5, dan O3. Model hibrid mampu menghasilkan model prediksi yang lebih baik dari model ARIMAX itu sendiri.
Whole Flour of Purple Maize as a Functional Ingredient of Gluten-Free Bread: Effect of In Vitro Digestion on Starch and Bioaccessibility of Bioactive Compounds

The growing demand for gluten-free products requires the study of alternatives to produce nutritionally and technologically favorable foods. The aim was to evaluate the content and antioxidant capacity of gluten-free bread enriched with whole flour of purple maize (PM) and how starch and bioaccessibility of antioxidant compounds were modified during in vitro digestion. Gluten-free bread was prepared with the addition of 34%, 50%, and 70% PM, and white maize bread served as control. The content of total polyphenols, anthocyanins, and antioxidant capacity through FRAP and TEAC was measured. Specific volume, crumb texture, and starch digestibility were determined in the breads. Simultaneously, in vitro digestion and dialysis by membrane were performed to evaluate the bioaccessible and potentially bioavailable fraction. Bread with 34% PM had a similar specific volume and crumb texture to the control, but higher content of polyphenols (52.91 mg AG/100 g), anthocyanins (23.13 mg c3-GE/100 g), and antioxidant capacity (3.55 and 5.12 µmol tr/g for FRAP and TEAC, respectively). The PM breads had a higher antioxidant content and capacity and higher slowly digestible and resistant starch than the control. These parameters increased as the PM proportion rose. After digestion, anthocyanins were degraded, polyphenols and antioxidant capacity decreased, but they remained potentially bioavailable, although to a lesser extent. Bread with 34% shows acceptable technological parameters, lower starch digestibility, and contribution of bioactive compounds with antioxidant capacity. This indicates that purple maize flour represents a potential ingredient to produce gluten-free bread with an improved nutritional profile.
Hypocalcemia in Patients With Osteoporosis and Normal Renal Function, Treated With Denosumab, a Retrospective Analysis

Objective: The reported hypocalcemia in postmenopausal women with osteoporosis who received Denosumab was low (0.05%-1.7% to 7.4%). The major prediction factors were vitamin D and calcium levels and renal function. The objective is to evaluate the incidence of hypocalcemia in patients with osteoporosis, normal renal function, and vitamin D who received Denosumab. Method: A retrospective analysis was conducted using the medical records (2022-2023). We looked for hypocalcemia (albumin-adjusted calcium lower than 2.2 mmol/L). Results: Two hundred one postmenopausal women diagnosed with osteoporosis and received denosumab treatment were included. All patients received vitamin D3 capsules and calcium supplementation. The mean age of the patient was 75.7 ± 7.0 years (56-91 years). Hypocalcemia was observed in 46 (23%) patients following a subcutaneous dose of Denosumab 60 mg. Median calcium was 2.25 mmol/L (minimum: 0.890 mmol/L, maximum: 2.6 mmol/L). Fourteen (30.4%) patients had severe hypocalcemia (<1.8 mmol/L) and required parenteral correction. A comparison between hypocalcemia and patients with normal calcium indicated that the significant predictor of hypocalcemia was pretreatment parathyroid hormone levels (9.9 ± 11.8vs 7.6 ± 2.56 pmol/L, respectively; P < .005). The prognostic role of parathyroid hormone for the denosumab-associated hypocalcemia was assessed using ROC curve analysis. For the cut-off value of Parathyroid hormone = 6.8 pmol/L, giving serum parathyroid measurement an AUC of 0.668 (0.599-0.737) - P = . 0007; sensitivity 85%; specificity 52%. Conclusion: Hypocalcemia induced by the denosumab treatment is more prevalent than previously shown in patients with osteoporosis receiving adequate calcium and vitamin D supplements. An elevated parathyroid hormone predicts hypocalcemia related to denosumab therapy in patients with normal calcium and vitamin D levels.
Association between household income levels and nutritional intake of allergic children under 6 years of age in Korea: 2019 Korea National Health and Nutrition Examination Survey and application of machine learning

Introduction This study investigated the prevalence of allergic diseases in Korean children aged 6 and below, focusing on the interplay between nutritional status, household income levels, and allergic disease occurrence. Methods This study used data from the 2019 Korea National Health and Nutrition Examination Survey, a nationwide comprehensive survey, and included a representative sample of 30,382 children under the age of 6 to investigate in detail the relationship between allergic diseases, nutritional intake, and socioeconomic factors. Logistic regression analysis was performed to identify factors associated with allergic diseases, including gender, BMI, eating habits, dietary supplement intake, and nutrient consumption. To predict childhood asthma, 14 machine learning models were compared using the ‘pycaret’ package in Python. Results We discerned that 24.7% were diagnosed with allergic conditions like atopic dermatitis, asthma, and allergic rhinitis. Notably, household income exhibited a significant influence, with the lowest income quartile exhibiting higher prevalence rates of asthma, allergic rhinitis, and multiple allergic diseases. In contrast, the highest income quartile displayed lower rates of allergic rhinitis. Children diagnosed with allergic diseases demonstrated compromised intake of essential nutrients such as energy, dietary fiber, vitamin B1, sodium, potassium, and iron. Particularly noteworthy were the deficits in dietary fiber, vitamin A, niacin, and potassium intake among children aged 3–5 with allergies. Logistic regression analysis further elucidated that within low-income families, female children with higher BMIs, frequent dining out, dietary supplement usage, and altered consumption of vitamin B1 and iron faced an elevated risk of allergic disease diagnosis. Additionally, machine learning analysis pinpointed influential predictors for childhood asthma, encompassing BMI, household income, subjective health perception, height, and dietary habits. Discussion Our findings underscore the pronounced impact of income levels on the intricate nexus between allergic diseases and nutritional status. Furthermore, our machine learning insights illuminate the multifaceted determinants of childhood asthma, where physiological traits, socioeconomic circumstances, environmental factors, and dietary choices intertwine to shape disease prevalence. This study emphasizes the urgency of tailored nutritional interventions, particularly in socioeconomically disadvantaged populations, while also underscoring the necessity for comprehensive longitudinal investigations to unravel the intricate relationship between allergic diseases, nutritional factors, and socioeconomic strata.
Force/position-based velocity control strategy for the lower limb rehabilitation robot during active training: design and validation

Aiming at the shortcomings of most existing control strategies for lower limb rehabilitation robots that are difficult to guarantee trajectory tracking effect and active participation of the patient, this paper proposes a force/position-based velocity control (FPVC) strategy for the hybrid end-effector lower limb rehabilitation robot (HE-LRR) during active training. The configuration of HE-LRR is described and the inverse Jacobian analysis is carried out. Then, the FPVC strategy design is introduced in detail, including normal velocity planning and tangential velocity planning. The experimental platform for the HE-LRR system is presented. A series of experiments are conducted to validate the FPVC strategy’s performance, including trajectory measurement experiments, force and velocity measurement experiments, and active participation experiments. Experimental studies show that the end effector possesses good following performance with the reference trajectory and the desired velocity, and the active participation of subjects can be adjusted by the control strategy parameters. The experiments have verified the rationality of the FPVC strategy, which can meet the requirements of trajectory tracking effect and active participation, indicating its good application prospects in the patient’s robot-assisted active training.
Committing to change: a persuasive systems design analysis of user commitments for a behaviour change support system

ABSTRACT Persuasive systems in different domains have been used to support people in changing their behaviours. These systems motivate desirable behaviour in users by providing relevant information, tracking user progress, and giving them feedback. This study investigates the persuasive features of a web-based information system that supports the enforcement of user commitments. A structural equation modelling approach and analysis of open text responses are used to identify the factors that affect the intention to continue to use the system, to gather users’ perspectives on how the system helps them to stick to their goals and the improvements that could be made. Data (N = 227) collected from the system's users is tested against the proposed research model. The results show that 30% of users’ continuance intention is explained by the implemented persuasive software feature categories (computer-human dialogue support, primary task support, perceived credibility, and social support) and perceived competence. Of these categories, primary task support has the strongest effect on perceived competence and continuance intention. The results also reveal how the system helps users to be consistent in their goals and the lack of specialised social support features. The study concludes with a discussion and recommendations for future research.