Mechanical Analysis of Collagen and DNA

It is known that mechanics plays a central role in many biological events. Tissue can remodel and turnover to adapt to new mechanical environment, such as hypertension and exercising. During the remodeling, hydrolysis of collagen is a key step. It is found that extension will change the cleavage rate of both collagen monomers and fibrils. The specificity of the collagen cleavage site is explained as the unique local mechanical environment of the cleavage site. DNA is another important filament molecule, and its behavior is also regulated by mechanics. The sequence-dependence of mechanical property has been observed, and is related to the specific interaction between proteins and DNA. On the pursuit of understanding the role of mechanics in those biological events as well as connecting atomistic to mesoscale properties of biopolymers, we used molecular dynamics (MD) simulation to study collagen and DNA. In collagen study, from the local bending stiffness calculated around cleavage site, we found it is transitioned from stiff to flexible across the cleavage site, which agrees with the classic model and can be seen as the structural feature recognizable by MMPs. We showed that the α-chain registry can determine the local conformation of collagen, and hence the cleavability of collagen. The resistance of homotrimer form to hydrolysis is interpreted as the stabilization role of arginines downstream to the cleavage site. Homotrimer form is found mainly in fetal tissue and carcinomas, and related to osteogenesis imperfecta. This resistance mechanism can help people to better understand its role in these processes. We further resolved controversial findings in experiments regarding the relationship between extension and collagen cleavage rate published the same year on the same journal. By mimicking the pulling conditions in the experiments, we found it is their different ways of pulling that induces different conformations, and therefore, different relationship of cleavage rate vs extension. This indicates the importance of mechanical environment on collagen. In our DNA investigation, we further developed our triad method to make it being capable for local isotropic mechanics study. We demonstrated the mechanical property is mainly determined at the dinucleotide-level sequence. The sequence-dependent flexibility can be applied to mechanical property prediction of any DNA sequence, as well as DNA nanostructures construction. We found the overwhelmingly used helicoidal parameters are not suitable for dynamic study, due to their degeneracy in describing conformational changes. Based on our data, we built a coarse-grained model that can capture the mechanical properties measured in experiments. This model bridges the atomistic dynamics and mesoscale property of DNA. By using the obtained stiffness and equilibrium data, we calculated energy of crystal structures of dsDNA-protein complexes without non-standard bases and paring. The results provided quantitative insight into the DNA-protein interaction dynamics. We further analyzed DNA methylation, a fundamental epigenetic modification that generates profound impact on gene regulation. We showed methylation generally will cause the immediate neighbor steps to be stiffer, whereas the methylated step itself less affected in mechanics. This is mainly because the steric interaction between methyl groups of methylated cytosine with other groups. We also demonstrated the hydration distribution change upon methylation could play a role in the stiffness variation, as well as affect the binding affinity to different proteins, since hydration force is key in molecular interactions. The findings in this study display influence of methylation in high resolution, and are potentially helpful to elucidate the mechanism of methylation in gene regulation. Currently we are investigating interaction between kinesin-1 motor head and tubulin. Its dimer or tetramer form can walk unidirectionally on microtubules (MTs), in an out-of phase manner. The motion can be attributed to different binding affinity when pulled in different directions and various nucleotide binding modes. We will simulate those different conditions to understand the atomistic mechanism

Semicryptic Diversity around Chaetoceros elegans (Bacillariophyta, Mediophyceae), and the Description of Two New Species

The globally distributed Chaetoceros elegans belongs to the Chaetoceros lorenzianus (C. lorenzianus) complex and is characterized by having tear-shaped setae poroids. Several strains of C. elegans were established from Chinese coastal waters. The vegetative cells and the resting spores were observed using light and electron microscopy. Phylogenetic analyses of two nuclear ribosomal RNA genes (SSU and the D1–D3 region of LSU) and the internal transcribed spacer (ITS) revealed that the C. elegans strains clustered into three clades, corresponding to different morphotypes. Based on the type material, the delineation of C. elegans was amended, and two new taxa, (Chaetoceros macroelegans) C. macroelegans sp. nov. and (Chaetoceros densoelegans) C.densoelegans sp. nov., were described. The two new taxa are featured by the presence of two types of setae poroids, tear-shaped and round-oval setae poroids, whereas only tear-shaped setae poroids are seen in C. elegans. The setae base is distinct in C. elegans, but absent or short in the two new taxa. In C. macroelegans, the tear-shaped poroids on the intercalary setae are larger and less densely spaced than in the other two species. The round-oval setae poroids are more densely spaced in C.densoelegans than in C. macroelegans, although they have more or less the same size. Resting spores characterize the two new taxa, but are unknown in the amended C. elegans. When comparing the ITS2 secondary structure, two and four compensatory base changes (CBCs) distinguish C. elegans from C. macroelegans and C.densoelegans, respectively. Between the two new taxa, no CBC but five hemi-CBCs (HCBCs) are present. The shape, size and density of the setae poroids, as well as the morphology of the resting spores, are important characteristics for species identification among the presently nine known species within the C. lorenzianus complex. View Full-Tex

New Insights Into the Response of Metabolome of Escherichia coli O157:H7 to Ohmic Heating

The objective of this study was to investigate the effects of ohmic heating and water bath heating (WB) on the metabolome of Escherichia coli O157:H7 cells at the same inactivation levels. Compared to low voltage long time ohmic heating (5 V/cm, 8.50 min, LVLT) and WB (5.50 min), the high voltage short time ohmic heating (10 V/cm, 1.75 min, HVST) had much shorter heating time. Compared to the samples of control (CT), there were a total of 213 differential metabolites identified, among them, 73, 78, and 62 were presented in HVST, LVLT, and WB samples, revealing a stronger metabolomic response of E. coli cells to HVST and LVLT than WB. KEGG enrichment analysis indicated that the significantly enriched pathways were biosynthesis and metabolism of amino acids (alanine, arginine, aspartate, and glutamate, etc.), followed by aminoacyl-tRNA biosynthesis among the three treatments. This is the first metabolomic study of E. coli cells in response to ohmic heating and presents an important step toward understanding the mechanism of ohmic heating on microbial inactivation, and can serve as a theoretical basis for better application of ohmic heating in food products

Online COVID-19 diagnosis prediction using complete blood count: an innovative tool for public health

Abstract Background COVID-19, caused by SARS-CoV-2, presents distinct diagnostic challenges due to its wide range of clinical manifestations and the overlapping symptoms with other common respiratory diseases. This study focuses on addressing these difficulties by employing machine learning (ML) methodologies, particularly the XGBoost algorithm, to utilize Complete Blood Count (CBC) parameters for predictive analysis. Methods We performed a retrospective study involving 2114 COVID-19 patients treated between December 2022 and January 2023 at our healthcare facility. These patients were classified into fever (1057 patients) and pneumonia groups (1057 patients), based on their clinical symptoms. The CBC data were utilized to create predictive models, with model performance evaluated through metrics like Area Under the Receiver Operating Characteristics Curve (AUC), accuracy, sensitivity, specificity, and precision. We selected the top 10 predictive variables based on their significance in disease prediction. The data were then split into a training set (70% of patients) and a validation set (30% of patients) for model validation. Results We identified 31 indicators with significant disparities. The XGBoost model outperformed others, with an AUC of 0.920 and high precision, sensitivity, specificity, and accuracy. The top 10 features (Age, Monocyte%, Mean Platelet Volume, Lymphocyte%, SIRI, Eosinophil count, Platelet count, Hemoglobin, Platelet Distribution Width, and Neutrophil count.) were crucial in constructing a more precise predictive model. The model demonstrated strong performance on both training (AUC = 0.977) and validation (AUC = 0.912) datasets, validated by decision curve analysis and calibration curve. Conclusion ML models that incorporate CBC parameters offer an innovative and effective tool for data analysis in COVID-19. They potentially enhance diagnostic accuracy and the efficacy of therapeutic interventions, ultimately contributing to a reduction in the mortality rate of this infectious disease

Chain Registry and Load-Dependent Conformational Dynamics of Collagen

Degradation of fibrillar collagen is critical for tissue maintenance. Yet, understanding collagen catabolism has been challenging partly due to a lack of atomistic picture for its load-dependent conformational dynamics, as both mechanical load and local unfolding of collagen affect its cleavage by matrix metalloproteinase (MMP). We use molecular dynamics simulation to find the most cleavage-prone arrangement of α chains in a collagen triple helix and find amino acids that modulate stability of the MMP cleavage domain depending on the chain registry within the molecule. The native-like state is mechanically inhomogeneous, where the cleavage site interfaces a stiff region and a locally unfolded and flexible region along the molecule. In contrast, a triple helix made of the stable glycine-proline-hydroxyproline motif is uniformly flexible and is dynamically stabilized by short-lived, low-occupancy hydrogen bonds. These results provide an atomistic basis for the mechanics, conformation, and stability of collagen that affect catabolism

Fetotoxicity of Nanoparticles: Causes and Mechanisms

The application of nanoparticles in consumer products and nanomedicines has increased dramatically in the last decade. Concerns for the nano-safety of susceptible populations are growing. Due to the small size, nanoparticles have the potential to cross the placental barrier and cause toxicity in the fetus. This review aims to identify factors associated with nanoparticle-induced fetotoxicity and the mechanisms involved, providing a better understanding of nanotoxicity at the maternal–fetal interface. The contribution of the physicochemical properties of nanoparticles (NPs), maternal physiological, and pathological conditions to the fetotoxicity is highlighted. The underlying molecular mechanisms, including oxidative stress, DNA damage, apoptosis, and autophagy are summarized. Finally, perspectives and challenges related to nanoparticle-induced fetotoxicity are also discussed

Health Assessment of High-Speed Train Running Gear System under Complex Working Conditions Based on Data-Driven Model

It is very important for the normal operation of high-speed trains to assess the health status of the running gear system. In actual working conditions, many unknown interferences and random noises occur during the monitoring process, which cause difficulties in providing an accurate health status assessment of the running gear system. In this paper, a new data-driven model based on a slow feature analysis-support tensor machine (SFA-STM) is proposed to solve the problem of unknown interference and random noise by removing the slow feature with the fastest instantaneous change. First, the relationship between various statuses of the running gear system is analyzed carefully. To remove the random noise and unknown interferences in the running gear systems under complex working conditions and to extract more accurate data features, the SFA method is used to extract the slowest feature to reflect the general trend of system changes in data monitoring of running gear systems of high-speed trains. Second, slowness data were constructed in a tensor form to achieve an accurate health status assessment using the STM. Finally, actual monitoring data from a running gear system from a high-speed train was used as an example to verify the effectiveness and accuracy of the model, and it was compared with traditional models. The maximum sum of squared resist (SSR) value was reduced by 16 points, indicating that the SFA-STM method has the higher assessment accuracy

Synthesis and biological evaluation of 3-arylcoumarins as potential anti-Alzheimer's disease agents

Alzheimer's disease, a neurodegenerative illness, has the extremely complex pathogenesis. Accumulating evidence indicates there is a close relationship between several enzymes and Alzheimer's disease. Various substituted 3-arylcoumarin derivatives were synthesised, and their in vitro activity, including cholinesterase inhibitory activity, monoamine oxidase inhibitory activity, and antioxidant activity were investigated. Most of the compounds exhibited high activity; therefore 3-arylcoumarin compounds have the potential as drug candidates for the treatment of Alzheimer's disease

Molecular Detection of Tick-Borne Bacterial and Protozoan Pathogens in <i>Haemaphysalis longicornis</i> (Acari: Ixodidae) Ticks from Free-Ranging Domestic Sheep in Hebei Province, China

Ticks and tick-borne pathogens significantly threaten human and animal health worldwide. Haemaphysalis longicornis is one of the dominant tick species in East Asia, including China. In the present study, 646 Ha. longicornis ticks were collected from free-ranging domestic sheep in the southern region of Hebei Province, China. Tick-borne pathogens of zoonotic and veterinary importance (i.e., Rickettsia, Anaplasma, Ehrlichia, Borrelia, Theileria, and Hepatozoon spp.) were detected in the ticks using PCR assays and sequence analysis. The prevalence rates of these pathogens were 5.1% (33/646), 15.9% (103/646), 1.2% (8/646), 17.0% (110/646), 0.15% (1/646), and 0.15% (1/646), respectively. For Rickettsia spp., R. japonica (n = 13), R. raoultii (n = 6), and Candidatus R. jingxinensis (n = 14) were detected for the first time in the province, while several Anaplasma spp. were also detected in the ticks, including A. bovis (n = 52), A. ovis (n = 31), A. phagocytophilum (n = 10), and A. capra (n = 10). A putative novel Ehrlichia spp. was also found with a prevalence of 1.2% in the area. The present study provides important data for effectively controlling ticks and tick-borne diseases in the Hebei Province region of China