MGPPI: multiscale graph neural networks for explainable protein-protein interaction prediction.

Protein-Protein Interactions (PPIs) involves in various biological processes, which are of significant importance in cancer diagnosis and drug development. Computational based PPI prediction methods are more preferred due to their low cost and high accuracy. However, existing protein structure based methods are insufficient in the extraction of protein structural information. Furthermore, most methods are less interpretable, which hinder their practical application in the biomedical field. In this paper, we propose MGPPI, which is a Multiscale graph convolutional neural network model for PPI prediction. By incorporating multiscale module into the Graph Neural Network (GNN) and constructing multi convolutional layers, MGPPI can effectively capture both local and global protein structure information. For model interpretability, we introduce a novel visual explanation method named Gradient Weighted interaction Activation Mapping (Grad-WAM), which can highlight key binding residue sites. We evaluate the performance of MGPPI by comparing with state-of-the-arts methods on various datasets. Results shows that MGPPI outperforms other methods significantly and exhibits strong generalization capabilities on the multi-species dataset. As a practical case study, we predicted the binding affinity between the spike (S) protein of SARS-COV-2 and the human ACE2 receptor protein, and successfully identified key binding sites with known binding functions. Key binding sites mutation in PPIs can affect cancer patient survival statues. Therefore, we further verified Grad-WAM highlighted residue sites in separating patients survival groups in several different cancer type datasets. According to our results, some of the highlighted residues can be used as biomarkers in predicting patients survival probability. All these results together demonstrate the high accuracy and practical application value of MGPPI. Our method not only addresses the limitations of existing approaches but also can assists researchers in identifying crucial drug targets and help guide personalized cancer treatment.

Clinical Evaluation of Effectiveness and Safety of Combined Use of Dietary Supplements Amberen® and Smart B® in Women with Climacteric Syndrome in Perimenopause.

INTRODUCTION: Perimenopause is a time of transition in a woman's life that links her reproductive years to the cessation of ovulation, or menopause. For many women, this time is characterized by a variety of physiological and lifestyle changes, including increasing irregularity in menstrual bleeding, frequency and severity of vasomotor symptoms, etc. Therapies evaluated specifically for the perimenopausal women are very limited. This study aimed to evaluate the effectiveness and safety of Amberen® (a succinate-based non-hormonal supplement) combined with a Smart B® (vitamin B) complex in women with typical (without complications) mild to moderate climacteric syndrome during perimenopause. METHODS: Women up to 50 years of age, in perimenopause, with vasomotor and psychosomatic symptoms of the climacteric syndrome were enrolled for the study. The trial was randomized, double-blinded, placebo-controlled, comparative, and prospective. RESULTS: A total of 106 participants were enrolled in the trial and, per protocol, 105 completed the trial. We observed statistically significant improvements in most of the Greene Climacteric Scale symptoms, State-Trait Anxiety Inventory (STAI), Hospital Anxiety and Depression Scale (HADS), and Well-being, Activity, and Mood (WAM) scores. The intervention was well tolerated with few adverse effects reported to be mild and transient. CONCLUSION: The use of this dietary supplement is safe and eliminates or improves vasomotor and psychosomatic symptoms of climacteric symptoms in perimenopausal women: it improves sleep and cognitive abilities, lowers depression and anxiety, improves mood and well-being, and positively affects quality of life. GOV IDENTIFIER: NCT03897738.

Predicting the effect of hydro-climatic and land-use dynamic variables on watershed health status.

This study aimed to predict the impact of changing hydro-climatic variables and land use changes on the future health status of the Safaroud Watershed, northern Iran. It also sought to explore the significance of hydro-climatic and land use variables in prioritizing sub-watersheds based on the watershed health index. The study involved extracting key characteristics related to anthropogenetic, climatic, and hydrological factors for pressure, state, and response indicators. The current watershed health index was calculated, followed by predictions of watershed health based on dynamic hydro-climatic and land-use variables for the next 10 and 20 years. The Safaroud Watershed health assessment and zoning showed that the average value and standard deviation of the current pressure index were equal to 0.573 and 0.185, respectively. The lowest value of this index was around 0.290 and related to sub-watershed 5, and the highest value was around 0.840 and related to sub-watershed 11. The initial evaluation of the classification indicated the prevalence of moderate and high-pressure conditions with a range of about 79%. Finally, the physical factors of sub-watersheds (time of concentration with 15.72%) had the lowest role. In general, among the criteria used to calculate the pressure index in the current period, anthropogenetic and climatic factors showed the highest percentage of participation in determining the pressure index. The quantification of the current watershed health status and the 10- and 20-year-forecast periods showed that the values of the watershed health index were similar. However, the changes in the health index in the sub-watersheds at the beginning of the study period ranged from relatively unhealthy favorable conditions to moderately positive and moderately negative conditions.

WAM to SeeSaw model for cancer therapy - overcoming LQM difficulties.

PURPOSE: The assessment of biological effects caused by radiation exposure has been currently carried out with the linear-quadratic (LQ) model as an extension of the linear non-threshold (LNT) model. In this study, we suggest a new mathematical model named as SeaSaw (SS) model, which describes proliferation and cell death effects by taking account of Bergonie-Tribondeau's law in terms of a differential equation in time. We show how this model overcomes the long-standing difficulties of the LQ model. MATERIALS AND METHODS: We construct the SS model as an extended Wack-A-Mole (WAM) model by using a differential equation with respect to time in order to express the dynamics of the proliferation effect. A large number of accumulated data of such parameters as α and ß in the LQ based models provide us with valuable pieces of information on the corresponding parameter b1 and the maximum volume Vm of the SS model. The dose rate b1 and the notion of active cell can explain the present data without introduction of ß, which is obtained by comparing the SS model with not only the cancer therapy data but also with in vitro experimental data. Numerical calculations are presented to grasp the global features of the SS model. RESULTS: The SS model predicts the time dependence of the number of active- and inactive-cells. The SS model clarifies how the effect of radiation depends on the cancer stage at the starting time in the treatment. Further, the time dependence of the tumor volume is calculated by changing individual dose strength, which results in the change of the irradiation duration for the same effect. We can consider continuous irradiation in the SS model with interesting outcome on the time dependence of the tumor volume for various dose rates. Especially by choosing the value of the dose rate to be balanced with the total growth rate, the tumor volume is kept constant. CONCLUSIONS: The SS model gives a simple equation to study the situation of clinical radiation therapy and risk estimation of radiation. The radiation parameter extracted from the cancer therapy is close to the value obtained from animal experiment in vitro and in vivo. We expect the SS model leads us to a unified description of radiation therapy and protection and provides a great development in cancer-therapy clinical-planning.

Comparison between two autorefractor performances in large scale vision screening in Chinese school age children.

AIM: To evaluate the effectiveness of Grand Seiko Ref/Keratometer WAM-5500 compared to Topcon KR800 autorefractor in detecting refractive error in large scale vision screening for Chinese school age children with the WHO criteria. METHODS: A total of 886 participants were enrolled with mean age of 9.49±1.88y from Tianjin, China. Spherical equivalent (SE) was obtained from un-cycloplegic autorefraction and cycloplegic autorefraction. Topcon KR 800 (Topcon) and Grand Seiko WAM-5500 (WAM) autorefractors were used. Bland-Altman Plot and regression were generated to compare their performance. The overall effectiveness of detecting early stage refractive error was analyzed with receiver operating characteristic (ROC) curves. RESULTS: The mean SE was -0.98±1.81 diopter (D) and the prevalence of myopia was 48.9% defined by WHO criteria according to the result of cycloplegic autorefraction. The mean SE of un-cycloplegic autorefraction with Topcon and WAM were -1.21±1.65 and -1.20±1.68 D respectively. There was a strong linear agreement between result obtained from WAM and cycloplegic autorefraction with an R2 of 0.8318. Bland-Altman plot indicated a moderate agreement of cylinder values between the two methods. The sensitivity and specificity for detecting hyperopia were 90.52% and 83.51%; for detecting myopia were 95.60% and 90.24%; for detecting astigmatism were 79.40% and 90.21%; for detecting high myopia were 98.16% and 98.91% respectively. CONCLUSION: These findings suggest that both Grand Seiko and Topcon autorefractor can be used in large-scale vision screening for detecting refractive error in Chinese population. Grand Seiko gives relatively better performance in detecting myopia, hyperopia, and high myopia for school age children.

Study of mutation from DNA to biological evolution.

Purpose: This is a paper based on a talk given in the BER2018 conference by M. Bando. We first emphasize the importance of collaborations among scientists in various fields for the low dose/dose-rate effects on biological body. We make comparisons of quantitative estimations of mutation caused by the radiation exposure on various animals and plants using one mathematical model. We derive the importance of the spontaneous mutation at the DNA level, which provides the key to understand the biological evolution. We try to make a guide map to solve this problem and find that the mutation is an important stage of the pathway from the DNA damage to the macroscopic biological evolution. Materials and methods: We construct a mathematical model for the mutation, named as 'WAM' model, which takes into account the recovery effect. The model setting is regarded as an extension of the survival and the hazard functions. The WAM model is used to reproduce accumulated data of mutation frequency of animals and plants. Especially the model analysis shows that the dose-rate dependence is important to understand various mutation data. Results and conclusions: The WAM model is successful in reproducing various mutation data of animals and plants. We find that the inclusion of the dose rate is important to understand all the mutation data. Hence, we are able to develop the 'scaling law' to make the cross-species comparison of mutation frequency data. With this finding, we can extract the dominant effect on the mutation to be caused by the spontaneous mutation, and quantify this amount. We are able to write then the artificial radiation frequency by subtracting the spontaneous mutation. With this success, we estimate the origin of the spontaneous mutation as due to ROS, the order of which agrees to the spontaneous mutation.