A stable microtubule bundle formed through an orchestrated multistep process controls quiescence exit.

Cells fine-tune microtubule assembly in both space and time to give rise to distinct edifices with specific cellular functions. In proliferating cells, microtubules are highly dynamics, and proliferation cessation often leads to their stabilization. One of the most stable microtubule structures identified to date is the nuclear bundle assembled in quiescent yeast. In this article, we characterize the original multistep process driving the assembly of this structure. This Aurora B-dependent mechanism follows a precise temporality that relies on the sequential actions of kinesin-14, kinesin-5, and involves both microtubule-kinetochore and kinetochore-kinetochore interactions. Upon quiescence exit, the microtubule bundle is disassembled via a cooperative process involving kinesin-8 and its full disassembly is required prior to cells re-entry into proliferation. Overall, our study provides the first description, at the molecular scale, of the entire life cycle of a stable microtubule structure in vivo and sheds light on its physiological function.

Tubulin CFEOM mutations both inhibit or activate kinesin motor activity.

Kinesin-mediated transport along microtubules is critical for axon development and health. Mutations in the kinesin Kif21a, or the microtubule subunit ß-tubulin, inhibit axon growth and/or maintenance resulting in the eye-movement disorder congenital fibrosis of the extraocular muscles (CFEOM). While most examined CFEOM-causing ß-tubulin mutations inhibit kinesin-microtubule interactions, Kif21a mutations activate the motor protein. These contrasting observations have led to opposed models of inhibited or hyperactive Kif21a in CFEOM. We show that, contrary to other CFEOM-causing ß-tubulin mutations, R380C enhances kinesin activity. Expression of ß-tubulin-R380C increases kinesin-mediated peroxisome transport in S2 cells. The binding frequency, percent motile engagements, run length and plus-end dwell time of Kif21a are also elevated on ß-tubulin-R380C compared with wildtype microtubules in vitro. This conserved effect persists across tubulins from multiple species and kinesins from different families. The enhanced activity is independent of tail-mediated kinesin autoinhibition and thus utilizes a mechanism distinct from CFEOM-causing Kif21a mutations. Using molecular dynamics, we visualize how ß-tubulin-R380C allosterically alters critical structural elements within the kinesin motor domain, suggesting a basis for the enhanced motility. These findings resolve the disparate models and confirm that inhibited or increased kinesin activity can both contribute to CFEOM. They also demonstrate the microtubule's role in regulating kinesins and highlight the importance of balanced transport for cellular and organismal health.

Evaluation of Cytogenetic Alterations in Patients of Chronic Kidney Disease.

Introduction: In recent years, there has been a rise in chronic kidney disease (CKD), and it has been estimated that by 2040, CKD will be the fifth most common cause of death globally. In addition to diabetes, hypertension, obesity, hyperlipidemia, and nonalcoholic fatty liver disease commonly associated with CKD, exposure to various toxins as a result of pollution or industrial disasters is also discussed as a cause for multi-organ pathology including kidneys. Although few cytogenetic studies were undertaken to assess the genetic damage in survivors of the disaster, no studies are available on the cytogenetic damage of toxic-gas exposed population having CKD. Therefore, the present multi-group cross-sectional study was undertaken to assess the independent role of CKD as well as toxic gas exposure on cytogenetics. Methods: The cytogenetic alterations were evaluated through chromosomal aberration analysis and micronuclei assay. The study included 608 study participants divided into four groups on the basis of history of exposure to the leaked gas and presence or absence of CKD. Results: The results of the study showed no statistically significant difference in cytogenetic damage between gas-exposed and non-exposed patients of CKD, whereas significantly higher cytogenetic damage was observed among gas-exposed participants having CKD compared to gas-exposed participants free from CKD, suggesting that cytogenetic changes could be due to CKD itself. Conclusions: Thus, to conclude, the cytogenetic alterations observed in the study can be partly attributed to the disease itself.

Morphometry-based radiomics for predicting therapeutic response in patients with gliomas following radiotherapy.

Introduction: Gliomas are still considered as challenging in oncologic management despite the developments in treatment approaches. The complete elimination of a glioma might not be possible even after a treatment and assessment of therapeutic response is important to determine the future course of actions for patients with such cancers. In the recent years radiomics has emerged as a promising solution with potential applications including prediction of therapeutic response. Hence, this study was focused on investigating whether morphometry-based radiomics signature could be used to predict therapeutic response in patients with gliomas following radiotherapy. Methods: 105 magnetic resonance (MR) images including segmented and non-segmented images were used to extract morphometric features and develop a morphometry-based radiomics signature. After determining the appropriate machine learning algorithm, a prediction model was developed to predict the therapeutic response eliminating the highly correlated features as well as without eliminating the highly correlated features. Then the model performance was evaluated. Results: Tumor grade had the highest contribution to develop the morphometry-based signature. Random forest provided the highest accuracy to train the prediction model derived from the morphometry-based radiomics signature. An accuracy of 86% and area under the curve (AUC) value of 0.91 were achieved for the prediction model evaluated without eliminating the highly correlated features whereas accuracy and AUC value were 84% and 0.92 respectively for the prediction model evaluated after eliminating the highly correlated features. Discussion: Nonetheless, the developed morphometry-based radiomics signature could be utilized as a noninvasive biomarker for therapeutic response in patients with gliomas following radiotherapy.

Texture feature analysis of MRI-ADC images to differentiate glioma grades using machine learning techniques.

Apparent diffusion coefficient (ADC) of magnetic resonance imaging (MRI) is an indispensable imaging technique in clinical neuroimaging that quantitatively assesses the diffusivity of water molecules within tissues using diffusion-weighted imaging (DWI). This study focuses on developing a robust machine learning (ML) model to predict the aggressiveness of gliomas according to World Health Organization (WHO) grading by analyzing patients' demographics, higher-order moments, and grey level co-occurrence matrix (GLCM) texture features of ADC. A population of 722 labeled MRI-ADC brain image slices from 88 human subjects was selected, where gliomas are labeled as glioblastoma multiforme (WHO-IV), high-grade glioma (WHO-III), and low-grade glioma (WHO I-II). Images were acquired using 3T-MR systems and a region of interest (ROI) was delineated manually over tumor areas. Skewness, kurtosis, and statistical texture features of GLCM (mean, variance, energy, entropy, contrast, homogeneity, correlation, prominence, and shade) were calculated using ADC values within ROI. The ANOVA f-test was utilized to select the best features to train an ML model. The data set was split into training (70%) and testing (30%) sets. The train set was fed into several ML algorithms and selected most promising ML algorithm using K-fold cross-validation. The hyper-parameters of the selected algorithm were optimized using random grid search technique. Finally, the performance of the developed model was assessed by calculating accuracy, precision, recall, and F1 values reported for the test set. According to the ANOVA f-test, three attributes; patient gender (1.48), GLCM energy (9.48), and correlation (13.86) that performed minimum scores were excluded from the dataset. Among the tested algorithms, the random forest classifier(0.8772 ± 0.0237) performed the highest mean-cross-validation score and selected to build the ML model which was able to predict tumor categories with an accuracy of 88.14% over the test set. The study concludes that the developed ML model using the above features except for patient gender, GLCM energy, and correlation, has high prediction accuracy in glioma grading. Therefore, the outcomes of this study enable to development of advanced tumor classification applications that assist in the decision-making process in a real-time clinical environment.

Using Taxol-sensitized budding yeast to investigate the effect of microtubule stabilization on anaphase onset.

The microtubule (MT)-stabilizing drug Taxol (paclitaxel) is a commonly used tool to investigate MT dynamics and MT-dependent processes. Here, we present a protocol for using Taxol-sensitized budding yeast to investigate the effect of microtubule stabilization on anaphase onset. We describe steps for establishing a log phase culture, synchronizing cells in G1, arresting in metaphase, and releasing cells into Taxol. We then detail procedures for imaging and scoring anaphase onset. This protocol facilitates maintenance and reproducibility in testing drug-sensitized and Taxol-sensitized yeast strains. For complete details on the use and execution of this protocol, please refer to Proudfoot et al.1.

The importance of microtubule-dependent tension in accurate chromosome segregation.

Accurate chromosome segregation is vital for cell and organismal viability. The mitotic spindle, a bipolar macromolecular machine composed largely of dynamic microtubules, is responsible for chromosome segregation during each cell replication cycle. Prior to anaphase, a bipolar metaphase spindle must be formed in which each pair of chromatids is attached to microtubules from opposite spindle poles. In this bipolar configuration pulling forces from the dynamic microtubules can generate tension across the sister kinetochores. The tension status acts as a signal that can destabilize aberrant kinetochore-microtubule attachments and reinforces correct, bipolar connections. Historically it has been challenging to isolate the specific role of tension in mitotic processes due to the interdependency of attachment and tension status at kinetochores. Recent technical and experimental advances have revealed new insights into how tension functions during mitosis. Here we summarize the evidence that tension serves as a biophysical signal that unifies multiple aspects of kinetochore and centromere function to ensure accurate chromosome segregation.

Fractal Dimension Analysis of Pixel Dynamic Contrast Enhanced-Magnetic Resonance Imaging Pharmacokinetic Parameters for Discrimination of Benign and Malignant Breast Lesions.

PURPOSE: Breast cancer is the most frequent cancer in women worldwide. However, its diagnosis mostly depends on visual examination of radiologic images, leading to an overdiagnosis with substantial costs. Therefore, a quantitative approach such as dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) through pharmacokinetic (PK) modeling is required for reliable analysis. As PK parameters lack information on parameter heterogeneity, texture-based analysis is required to quantify PK parameter heterogeneity. Therefore, this study focused on determining the usefulness of fractal dimension (FD) as a potential imaging biomarker of tumor heterogeneity for discriminating benign and malignant breast lesions. METHODS: Parametric maps for PK parameters, extravasation rate of contrast agent from blood plasma to extravascular extracellular space (Ktrans) and volume fraction of extravascular extracellular space (ve), were generated for the regions of interest (ROIs) under the standard model using 18 lesions. Then, tumor ROI and pixel DCE-MRI time-course data were analyzed to extract pixel values of Ktrans and ve. For each ROI, FD values of Ktrans and ve were computed using the blanket method. RESULTS: The FD values of Ktrans for benign and malignant lesions varied from 2.96 to 3.49 and from 2.37 to 3.16, respectively, whereas FD values of ve for benign and malignant lesions varied from 3.01 to 5.15 and 2.42 to 3.44, respectively. There were significant differences in FD values derived from Ktrans parametric maps (P = .0053) and ve parametric maps (P = .0271) between benign and malignant lesions according to the statistical analysis. CONCLUSION: Incorporating texture heterogeneity changes in breast lesions captured by FD with quantitative DCE-MRI parameters generated under the standard model is a potential marker for prediction of malignant lesions.

The relevance of arsenic speciation analysis in health & medicine.

Long term exposure to arsenic through consumption of contaminated groundwater has been a global issue since the last five decades; while from an alternate standpoint, arsenic compounds have emerged as unparallel chemotherapeutic drugs. This review highlights the contribution from arsenic speciation studies that have played a pivotal role in the progression of our understanding of the biological behaviour of arsenic in humans. We also discuss the limitations of the speciation studies and their association with the interpretation of arsenic metabolism. Chromatographic separation followed by spectroscopic detection as well as the utilization of biotinylated pull-down assays, protein microarray and radiolabelled arsenic have been instrumental in identifying hundreds of metabolic arsenic conjugates, while, computational modelling has predicted thousands of them. However, these species exhibit a variegated pattern, which supports more than one hypothesis for the metabolic pathway of arsenic. Thus, the arsenic species are yet to be integrated into a coherent mechanistic pathway depicting its chemicobiological fate. Novel biorelevant arsenic species have been identified due to significant evolution in experimental methodologies. However, these methods are specific for the identification of only a group of arsenicals sharing similar physiochemical properties; and may not be applicable to other constituents of the vast spectrum of arsenic species. Consequently, the identity of arsenic binding partners in vivo and the sequence of events in arsenic metabolism are still elusive. This resonates the need for additional focus on the extraction and characterization of both low and high molecular weight arsenicals in a combinative manner.

Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques.

BACKGROUND: Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI) technique that is being routinely used in brain examinations in modern clinical radiology practices. This study focuses on extracting demographic and texture features from MRI Apparent Diffusion Coefficient (ADC) images of human brain tumors, identifying the distribution patterns of each feature and applying Machine Learning (ML) techniques to differentiate malignant from benign brain tumors. METHODS: This prospective study was carried out using 1599 labeled MRI brain ADC image slices, 995 malignant, 604 benign from 195 patients who were radiologically diagnosed and histopathologically confirmed as brain tumor patients. The demographics, mean pixel values, skewness, kurtosis, features of Grey Level Co-occurrence Matrix (GLCM), mean, variance, energy, entropy, contrast, homogeneity, correlation, prominence and shade, were extracted from MRI ADC images of each patient. At the feature selection phase, the validity of the extracted features were measured using ANOVA f-test. Then, these features were used as input to several Machine Learning classification algorithms and the respective models were assessed. RESULTS: According to the results of ANOVA f-test feature selection process, two attributes: skewness (3.34) and GLCM homogeneity (3.45) scored the lowest ANOVA f-test scores. Therefore, both features were excluded in continuation of the experiment. From the different tested ML algorithms, the Random Forest classifier was chosen to build the final ML model, since it presented the highest accuracy. The final model was able to predict malignant and benign neoplasms with an 90.41% accuracy after the hyper parameter tuning process. CONCLUSIONS: This study concludes that the above mentioned features (except skewness and GLCM homogeneity) are informative to identify and differentiate malignant from benign brain tumors. Moreover, they enable the development of a high-performance ML model that has the ability to assist in the decision-making steps of brain tumor diagnosis process, prior to attempting invasive diagnostic procedures, such as brain biopsies.

Lateral transition-metal dichalcogenide heterostructures for high efficiency thermoelectric devices.

Monolayer transition-metal dichalcogenides (TMDC) have emerged as promising candidates for thermoelectric applications due to their large effective mass and low thermal conductivity. In this article, we study the thermoelectric performance of lateral TMDC heterostructures within a multiscale quantum transport framework. Both n-type and p-type lateral heterostructures are considered for all possible combinations of semiconducting TMDCs: MoS2, MoSe2, WS2, and WSe2. The band alignment between these materials is found to play a crucial role in enhancing the thermoelectric figure-of-merit (ZT) and power factor far beyond those of pristine TMDCs. In particular, we show that the room-temperature ZT value of n-type WS2 with WSe2 triangular inclusions is five times larger than that of the pristine WS2 monolayer. We also show that p-type MoSe2 with WSe2 inclusions has a room-temperature ZT value which is two times larger than that of the pristine MoSe2 monolayer. The peak power factor values, calculated here, are the highest reported amongst gapped monolayers at room temperature. Hence, monolayer lateral TMDC heterostructures open new avenues to develop ultra-efficient, planar thermoelectric devices.

Microtubules in Microorganisms: How Tubulin Isotypes Contribute to Diverse Cytoskeletal Functions.

The cellular functions of the microtubule (MT) cytoskeleton range from relatively simple to amazingly complex. Assembled from tubulin, a heterodimeric protein with α- and ß-tubulin subunits, microtubules are long, hollow cylindrical filaments with inherent polarity. They are intrinsically dynamic polymers that utilize GTP binding by tubulin, and subsequent hydrolysis, to drive spontaneous assembly and disassembly. Early studies indicated that cellular MTs are composed of multiple variants, or isotypes, of α- and ß-tubulins, and that these multi-isotype polymers are further diversified by a range of posttranslational modifications (PTMs) to tubulin. These findings support the multi-tubulin hypothesis whereby individual, or combinations of tubulin isotypes possess unique properties needed to support diverse MT structures and/or cellular processes. Beginning 40 years ago researchers have sought to address this hypothesis, and the role of tubulin isotypes, by exploiting experimentally accessible, genetically tractable and functionally conserved model systems. Among these systems, important insights have been gained from eukaryotic microbial models. In this review, we illustrate how using microorganisms yielded among the earliest evidence that tubulin isotypes harbor distinct properties, as well as recent insights as to how they facilitate specific cellular processes. Ongoing and future research in microorganisms will likely continue to reveal basic mechanisms for how tubulin isotypes facilitate MT functions, along with valuable perspectives on how they mediate the range of conserved and diverse processes observed across eukaryotic microbes.

Computational simulation-based study of novel ZnO Buckyball structures.

A novel Zinc Oxide Buckyball (ZnO-b) system has been optimized using the first principle density functional theory (DFT). The study of the structural, electronic, and optical properties of both the pristine and Al, Ga, and Ag-doped ZnO-b and ZnO-h (ZnO hexagonal) systems have been reported here. A comparative study of the variations which occurred due to changes in the crystal structure, dopant element as well as doping site was done for both systems. The study includes the structural analysis followed by the electronic analysis with the study of Density of States (DOS), Partial Density of States (PDOS), and at last the Optical analysis of the systems. The bandgap engineering due to structural variations in ZnO is observed here as metal-doped ZnO-h structures showed a vast shift towards a smaller bandgap value, showing enhancement in the metallic behaviour, while for ZnO-b it varied between 1.52 eV-2.94 eV with similar doping. It was observed that mostly the value of the cell volume and the bandgap decreases with an increase in the atomic radii of the dopant atoms due to quantum confinement effects. Ag-doped sample has shown a better optical conductivity with lower absorbance as compared to other dopants in the ZnO-b structure, which makes it a suitable material for optoelectronic applications. Overall, in the buckyball structures properties of dopants are predominating whereas, in hexagonal structures, properties of ZnO are predominating. This makes the ZnO-b structure a useful material for biomedical applications along with optoelectronic devices. This work also opens a wide area of study for applications of these novel structures from biomedicines to optoelectronic devices by precisely controlling their physical properties.

Thalamocortical Projections Are Significantly Impaired in the R6/2 Mouse Model of Huntington's Disease.

As Huntington's disease (HD) progresses, there is a significant loss of neurons in the striatum in addition to a distinct thinning of the cerebral cortex. Despite an early presence of sensorimotor deficits in patients with HD, electrophysiological studies designed to assess the integrity of thalamocortical circuits are sparse. Using the R6/2 mouse model of HD, we provide evidence of reduced connectivity between thalamic cells and their targeted cortical regions. Whole-cell patch clamp recordings from ventral anterolateral nucleus (VAL; motor) and ventral posteromedial nucleus (VPM; somatosensory) thalamic neurons in ex vivo brain slices of R6/2 and wild-type (WT) mice revealed that cells in both thalamic nuclei of R6/2 mice exhibited significant differences in passive and active cell membrane properties (smaller cell membrane capacitances, faster decay time constants and increased input resistances) compared with WT cells. Although only cells in the VPM of symptomatic R6/2 mice had more depolarized resting membrane potentials compared with WTs, cells in both nuclei displayed increased excitability in symptomatic, but not presymptomatic, R6/2 mice. Optical activation of VAL and VPM terminals elicited smaller magnitude current responses in cortical pyramidal neurons (CPNs) in both motor cortex (M1CTX) and somatosensory barrel cortex (BCTX) of symptomatic R6/2 mice compared with CPNs in WT mice. Furthermore, we observed a decrease in the frequency of thalamocortical excitatory quantal events in R6/2 BCTX CPNs, with no genotype-dependent differences in AMPA:NMDA response amplitude ratios. These data suggest there is a decrease in the transmission of thalamocortical information that is likely because of impaired neurotransmitter release.

Tubulin isotypes - functional insights from model organisms.

The microtubule cytoskeleton is assembled from the α- and ß-tubulin subunits of the canonical tubulin heterodimer, which polymerizes into microtubules, and a small number of other family members, such as γ-tubulin, with specialized functions. Overall, microtubule function involves the collective action of multiple α- and ß-tubulin isotypes. However, despite 40 years of awareness that most eukaryotes harbor multiple tubulin isotypes, their role in the microtubule cytoskeleton has remained relatively unclear. Various model organisms offer specific advantages for gaining insight into the role of tubulin isotypes. Whereas simple unicellular organisms such as yeast provide experimental tractability that can facilitate deeper access to mechanistic details, more complex organisms, such as the fruit fly, nematode and mouse, can be used to discern potential specialized functions of tissue- and structure-specific isotypes. Here, we review the role of α- and ß-tubulin isotypes in microtubule function and in associated tubulinopathies with an emphasis on the advances gained using model organisms. Overall, we argue that studying tubulin isotypes in a range of organisms can reveal the fundamental mechanisms by which they mediate microtubule function. It will also provide valuable perspectives on how these mechanisms underlie the functional and biological diversity of the cytoskeleton.

Effects of non-essential protein on D-glucose to control diabetes: DFT approach.

Diabetes is a disease found in every 1 out of 4 people in the world. The glucose molecule is one of the sources of energy in the body and the lack of the digestion of glucose causes diabetes type 1 and type 2. Arginine and cysteine are nonessential amino acids that contain sulfur and help maintain the metabolisms of humans. We explored the glucose-arginine (Glc-arg) and glucose-cysteine (Glc-cys) molecules by finding their structural properties, electronic properties, chemical reactivity, mechanical strength, and transport properties because these non-essential amino acid molecules inhibit glucose-stimulated insulin secretion. Density functional theory (DFT) has been implemented to study all the properties of Glc-arg and Glc-cys using SIESTA software. Glucose-arginine (Glc-arg) inhibits a large percentage of glucose secretion and shows high chemical reactivity.

Tubulin isotypes optimize distinct spindle positioning mechanisms during yeast mitosis.

Microtubules are dynamic cytoskeleton filaments that are essential for a wide range of cellular processes. They are polymerized from tubulin, a heterodimer of α- and ß-subunits. Most eukaryotic organisms express multiple isotypes of α- and ß-tubulin, yet their functional relevance in any organism remains largely obscure. The two α-tubulin isotypes in budding yeast, Tub1 and Tub3, are proposed to be functionally interchangeable, yet their individual functions have not been rigorously interrogated. Here, we develop otherwise isogenic yeast strains expressing single tubulin isotypes at levels comparable to total tubulin in WT cells. Using genome-wide screening, we uncover unique interactions between the isotypes and the two major mitotic spindle positioning mechanisms. We further exploit these cells to demonstrate that Tub1 and Tub3 optimize spindle positioning by differentially recruiting key components of the Dyn1- and Kar9-dependent mechanisms, respectively. Our results provide novel mechanistic insights into how tubulin isotypes allow highly conserved microtubules to function in diverse cellular processes.

Fabrication of TiO2 microspikes for highly efficient intracellular delivery by pulse laser-assisted photoporation.

The introduction of foreign cargo into living cells with high delivery efficiency and cell viability is a challenge in cell biology and biomedical research. Here, we demonstrate a nanosecond pulse laser-activated photoporation for highly efficient intracellular delivery using titanium dioxide (TiO2) microspikes as a substratum. The TiO2 microspikes were formed on titanium (Ti) substrate using an electrochemical anodization process. Cells were cultured on top of the TiO2 microspikes as a monolayer, and the biomolecule was added. Due to pulse laser exposure of the TiO2 microspike-cell membrane interface, the microspikes heat up and induce cavitation bubbles, which rapidly grow, coalesce and collapse to induce explosion, resulting in very strong fluid flow at the cell membrane surface. Thus, the cell plasma membrane disrupts and creates transient nanopores, allowing delivery of biomolecules into cells by a simple diffusion process. By this technique, we successfully delivered propidium iodide (PI) dye in HeLa cells with high delivery efficiency (93%) and high cell viability (98%) using 7 mJ pulse energy at 650 nm wavelength. Thus, our TiO2 microspike-based platform is compact, easy to use, and potentially applicable for therapeutic and diagnostic purposes.

Electrochemical fabrication of TiO2 micro-flowers for an efficient intracellular delivery using nanosecond light pulse.

Introduction of foreign cargo into the targeted living cell with high transfection efficiency and high cell viability is an important mean for many biological and biomedical research purpose. Here, we have demonstrated a newly developed Titanium oxide micro-flower structure (TMS) for intracellular delivery. The TMS were formed on titanium (Ti) substrate using an electrochemical anodization process. The TMS consists of branches of titanium dioxide (TiO2) nanotubes, which play an important role in efficient cargo delivery. Due to nanosecond pulse laser exposure, Ti substrate heat-up, generating cavitation bubbles. These bubbles can rapidly grow, coalesce, and collapse to induce explosion resulting in very strong fluid flow through the TiO2 nanotubes and disrupt the cell plasma membrane promoting the delivery of biomolecules into cells. Using this platform, we successfully deliver dyes with 93% efficiency and nearly 98% cell viability into HCT cells, and this technique is potentially applicable for cellular therapy and diagnostics.