Preparation of the Branch Bark Ethanol Extract in Mulberry Morus alba

The biological activities of the branch bark ethanol extract (BBEE) in the mulberry Morus alba L. were investigated. The determination of active component showed that the flavonoids, phenols, and saccharides are the major components of the ethanol extract. The BBEE had a good scavenging activity of the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical with around 100 μg/mL of IC50 value. In vitro assay revealed that the BBEE strongly inhibited both α-glucosidase and sucrase activities whose IC50 values were 8.0 and 0.24 μg/mL, respectively. The kinetic analysis showed that the BBEE as a kind of α-glucosidase inhibitor characterized a competitive inhibition activity. Furthermore, the carbohydrate tolerance of the normal mice was obviously enhanced at 0.5 h (P<0.05) and 1.0 h (P<0.05) after the BBEE intragastric administration as compared to negative control. At 0.5, 1.0, 1.5, and 2.0 h after the intragastric administration with starch, the postprandial hyperglycemia of the type 2 diabetic mice can be significantly decreased (P<0.01) by supplying various concentrations of the BBEE (10–40 mg/kg body weight). Therefore, the BBEE could effectively inhibit the postprandial hyperglycemia as a novel α-glucosidase activity inhibitor for the diabetic therapy

A NOVEL ALGORITHM ENUMERATING BENT FUNCTIONS

By the relationship between the Walsh spectra at partial points and the Walsh spectra of its sub-functions, by the action of general linear group on the set of Boolean functions, and by the Reed-Muller transform, a novel method is developed, which can theoretically construct all bent functions. With this method, we enumerate all bent functions in 6 variables; in 8-variable case, our method is more efficient than the method presented by Clark though we still can not enumerate all bent functions; enumeration of all homogeneous bent functions of degree 3 in eight variables can be done in one minute by a P4 1.7G HZ computer; construction of homogenous bent function of degree 3 in 10 variables is efficient too; the nonexistence of homogeneous bent functions in 10 variables of degree 4 is prove

Analysis of Affinely Equivalent Boolean Functions

By walsh transform, autocorrelation function, decomposition, derivation and modification of truth table, some new invariants are obtained. Based on invariant theory, we get two results: first a general algorithm which can be used to judge if two boolean functions are affinely equivalent and to obtain the affine equivalence relationship if they are equivalent. For example, all 8-variable homogenous bent functions of degree 3 are classified into 2 classes; second, the classification of the Reed-Muller code $R(4,6)/R(1,6),R(3,7)/R(1,7),$ which can be used to almost enumeration of 8-variable bent functions

A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the pharmaceutical industry, including drug screening, design, and repurposing. However, traditional machine learning methods for calculating DTA often lack accuracy, posing a significant challenge in accurately predicting DTA. Fortunately, deep learning has emerged as a promising approach in computational biology, leading to the development of various deep learning-based methods for DTA prediction. To support researchers in developing novel and highly precision methods, we have provided a comprehensive review of recent advances in predicting DTA using deep learning. We firstly conducted a statistical analysis of commonly used public datasets, providing essential information and introducing the used fields of these datasets. We further explored the common representations of sequences and structures of drugs and targets. These analyses served as the foundation for constructing DTA prediction methods based on deep learning. Next, we focused on explaining how deep learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer, and Graph Neural Networks (GNNs), were effectively employed in specific DTA prediction methods. We highlighted the unique advantages and applications of these models in the context of DTA prediction. Finally, we conducted a performance analysis of multiple state-of-the-art methods for predicting DTA based on deep learning. The comprehensive review aimed to help researchers understand the shortcomings and advantages of existing methods, and further develop high-precision DTA prediction tool to promote the development of drug discovery

Correlation between Drug Compliance and Quality of Life in AIDS Patients under Effects of Nursing Intervention

Objective: Good drug compliance is the significant premise of the therapeutic efficacy and the physically healthy level could be reflected by the quality of life. It will be of great importance in enhancing the drug compliance and the quality of life for patients to firm their confidence in fighting with the disease, cooperate with treatment and prolong the lifetime through researching the nursing intervention model for AIDS patients. Based on the analysis of the effects of nursing intervention on AIDS patients’ drug compliance and quality of life, this report studies the correlation between drug compliance and quality of life in AIDS patients under effects of nursing intervention, so as to provide theoretical basis for offering reasonable scheme of nursing intervention more comprehensively, assess the effect of treatment and improve the entirely healthy level of AIDS patients. Methods: A total of 240 AIDS patients were selected as subjects randomly, who were randomized into control group and intervention group, with 120 patients in each group. Both control group and intervention group were given routine nursing measures, while intervention group was given reasonable nursing intervention measures according to nursing requirements on the basis of routine nursing. Baseline data of patients, data after 3 months of observation and data after 10 months of observation were collected using self-made Antiviral Drug Compliance Questionnaire and World Health Organization Quality of Life with 100 Questions (WHOQOL-100), followed by rank correlation analysis and regression analysis. Results: After 3 months and 10 months of nursing intervention, there was obvious rank correlation between patients’ drug compliance and quality of life in the intervention group. After 10 months of nursing intervention, the effects of drug compliance showed obvious gradual enhancement. As for domains of quality of life, after 3 months of nursing intervention, the rank correlation between drug compliance and physiology domain, independence domain and social relation domain became significant; after 10 months of nursing intervention, the rank correlation became more significant, and the rank correlation between drug compliance and psychology domain and environment domain also became significant. Conclusion: Drug compliance has direct influence on the therapeutic effects of patients, and the quality of life can improve the therapeutic effects of patients through influencing patients’ drug compliance. With the continuation of intervention measures, the effects of intervention show gradual enhancement. Keywords: AIDS; correlation; nursing intervention; treatment compliance; quality of lif

Effects of vitamin C on inhalation anesthetic isoflurane-induced developmental, neuronal apoptosis in neonatal rats

Developmental abnormalities, neuronal apoptosis and associated cognitive impairment following isoflurane exposure in neonatal rodents have been reported. The study was undertaken to investigate the effect of vitamin C supplementation against isoflurane-induced neurotoxicity. Seven day old rats were exposed to 1.1% isoflurane, or air for 6 hours. Treatment groups were administered with vitamin C (30 mg/kg, orally) from postnatal day 1 (P1) to P10 and were exposed to isoflurane on P7. Isoflurane exposure induced apoptosis was determined by Fluoro-Jade C and terminal deoxynucleotidyl-transferase-mediated 2-deoxyuridine 5-triphosphate nick-end labeling assay. Vitamin C considerably improved memory and learning impairments, modulated neuroapoptosis and improved expressions of brain-derived neurotrophic factor, nerve growth factor, Bcl-xL and decreased activated caspase-3 expressions. Thus, vitamin C effectively offered protection against isoflurane-induced neuronal apoptosis, learning and memory disturbances

A Preclinical Systematic Review of Ginsenoside-Rg1 in Experimental Parkinson’s Disease

To date, no drug has been proven to be neuroprotective or disease-modifying for Parkinson’s disease (PD) in clinical trials. Here, we aimed to assess preclinical evidence of Ginsenosides-Rg1 (G-Rg1), a potential neuroprotectant, for experimental PD and its possible mechanisms. Eligible studies were identified by searching six electronic databases from their inception to August 2016. Twenty-five eligible studies involving 516 animals were identified. The quality score of these studies ranged from 3 to 7. Compared with the control group, two out of the 12 studies of MPTP-induced PD showed significant effects of G-Rg1 for improving the rotarod test (P<0.01), two studies for improving the swim-score values (P<0.01), six studies for improving the level of TH protein expression (P<0.01), and two studies for increasing the expression of TH mRNA in the substantia nigra of mice (P<0.01). The studies reported that G-Rg1 exerted potential neuroprotective effects on PD model through different mechanisms as antineuroinflammatory activities (n=10), antioxidant stress (n=3), and antiapoptosis (n=11). In conclusion, G-Rg1 exerted potential neuroprotective functions against PD largely by antineuroinflammatory, antioxidative, and antiapoptotic effects. G-Rg1 as a promising neuroprotectant for PD needs further confirmation by clinical trials