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.

The COVID-19 pandemic affected the world through its ability to cause widespread infection. The Middle East including the Kingdom of Saudi Arabia (KSA) has also been hit by the COVID-19 pandemic like the rest of the world. This study aims to examine the relationships between meteorological factors and COVID-19 case counts in three cities of the KSA. The distribution of the COVID-19 case counts was observed for all three cities followed by cross-correlation analysis which was carried out to estimate the lag effects of meteorological factors on COVID-19 case counts. Moreover, the Poisson model and negative binomial (NB) model with their zero-inflated versions (i.e., ZIP and ZINB) were fitted to estimate city-specific impacts of weather variables on confirmed case counts, and the best model is evaluated by comparative analysis for each city. We found significant associations between meteorological factors and COVID-19 case counts in three cities of KSA. We also perceived that the ZINB model was the best fitted for COVID-19 case counts. In this case study, temperature, humidity, and wind speed were the factors that affected COVID-19 case counts. The results can be used to make policies to overcome this pandemic situation in the future such as deploying more resources through testing and tracking in such areas where we observe significantly higher wind speed or higher humidity. Moreover, the selected models can be used for predicting the probability of COVID-19 incidence across various regions.

Lake Urmia (LU) is the second largest hypersaline lake in the world. Lake Urmia\'s water level has dropped drastically from 1277.85 m to 1270.08 m a.s.l (equal to 7.77 m) during the last 20 years, equivalent to a loss of 70% of the lake area. The likelihood of lake-groundwater connection on the basin-scale is uncertain and understudied because of lack of basic data and precise information required for physically-based modeling. In this study, cross-correlation analysis is applied on a various time-frames of water level of the lake and groundwater levels (2001-2018) recorded in 797 observation wells across 17 adjacent aquifers. This provides insightful information on the lake-groundwater interaction. The cross-correlation coefficient between the monthly water level of lake and observations wells (rGW-L) and the difference of these two variables (Hf) was calculated for different time-frames. The values of rGW-L (ranged -0.69 to 0.97) and Hf (ranged -53 m to 293 m) indicated the significant role of time-frames of observed dataset on dynamic behavior of lake-groundwater interaction, and exchange fluxes in the study setting. Results suggested two opposing behaviors in lake-groundwater interaction of the study system mainly arise from anthropogenic activity (overexploitation of groundwater for irrigation) and aquifer type (unconfined/pressurized): three out of 17 adjacent aquifers are feeding by the LU and act as \"gaining aquifers\" (located in northern half of LU) and others discharging into the LU and act as \"losing aquifers\". This study aimed to provide easy-to-obtain insights into LGWI in the complex setting of LU Basin. It can be considered a preliminary step towards a deeper understanding of the interaction through physically-based analysis and modeling.