Unveiling breast cancer risk profiles: a survival clustering analysis empowered by an online web application.

Aim: To develop a shiny app for doctors to investigate breast cancer treatments through a new approach by incorporating unsupervised clustering and survival information. Materials & methods: Analysis is based on the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which contains 1726 subjects and 22 variables. Cox regression was used to identify survival risk factors for K-means clustering. Logrank tests and C-statistics were compared across different cluster numbers and Kaplan-Meier plots were presented. Results & conclusion: Our study fills an existing void by introducing a unique combination of unsupervised learning techniques and survival information on the clinician side, demonstrating the potential of survival clustering as a valuable tool in uncovering hidden structures based on distinct risk profiles.

Mathematical Modeling of Rhesus Cytomegalovirus Transplacental Transmission in Seronegative Rhesus Macaques.

Approximately 0.7% of infants are born with congenital cytomegalovirus (CMV), making it the most common congenital infection. About 1 in 5 congenitally infected babies will suffer long-term sequelae, including sensorineural deafness, intellectual disability, and epilepsy. CMV infection is highly species-dependent, and the rhesus CMV (RhCMV) infection of rhesus monkey fetuses is the only animal model that replicates essential features of congenital CMV (cCMV) infection in humans, including placental transmission, fetal disease, and fetal loss. Using experimental data from RhCMV seronegative rhesus macaques inoculated with RhCMV in the late first to early second trimesters of pregnancy, we built and calibrated a mathematical model for the placental transmission of CMV. The model was then used to study the effect of the timing of inoculation, maternal immune suppression, and hyper-immune globulin infusion on the risk of placental transmission in the context of primary and reactivated chronic maternal CMV infection.

A simple reaction-diffusion system as a possible model for the origin of chemotaxis.

Chemotaxis is a directed cell movement in response to external chemical stimuli. In this paper, we propose a simple model for the origin of chemotaxis - namely how a directed movement in response to an external chemical signal may occur based on purely reaction-diffusion equations reflecting inner working of the cells. The model is inspired by the well-studied role of the rho-GTPase Cdc42 regulator of cell polarity, in particular in yeast cells. We analyse several versions of the model to better understand its analytic properties and prove global regularity in one and two dimensions. Using computer simulations, we demonstrate that in the framework of this model, at least in certain parameter regimes, the speed of the directed movement appears to be proportional to the size of the gradient of signalling chemical. This coincides with the form of the chemical drift in the most studied mean field model of chemotaxis, the Keller-Segel equation.

Using a smartwatch and smartphone to assess early Parkinson's disease in the WATCH-PD study.

Digital health technologies can provide continuous monitoring and objective, real-world measures of Parkinson's disease (PD), but have primarily been evaluated in small, single-site studies. In this 12-month, multicenter observational study, we evaluated whether a smartwatch and smartphone application could measure features of early PD. 82 individuals with early, untreated PD and 50 age-matched controls wore research-grade sensors, a smartwatch, and a smartphone while performing standardized assessments in the clinic. At home, participants wore the smartwatch for seven days after each clinic visit and completed motor, speech and cognitive tasks on the smartphone every other week. Features derived from the devices, particularly arm swing, the proportion of time with tremor, and finger tapping, differed significantly between individuals with early PD and age-matched controls and had variable correlation with traditional assessments. Longitudinal assessments will inform the value of these digital measures for use in future clinical trials.

Random Search in Fluid Flow Aided by Chemotaxis.

In this paper, we consider the dynamics of a 2D target-searching agent performing Brownian motion under the influence of fluid shear flow and chemical attraction. The analysis is motivated by numerous situations in biology where these effects are present, such as broadcast spawning of marine animals and other reproduction processes or workings of the immune systems. We rigorously characterize the limit of the expected hit time in the large flow amplitude limit as corresponding to the effective one-dimensional problem. We also perform numerical computations to characterize the finer properties of the expected duration of the search. The numerical experiments show many interesting features of the process and in particular existence of the optimal value of the shear flow that minimizes the expected target hit time and outperforms the large flow limit.

Cobalt Doped in Zn-MOF-5 Nanoparticles to Regulate Tumor Microenvironment for Tumor Chemo/Chemodynamic Therapy.

Metal-organic frameworks are often used as a chemotherapeutic drug carrier due to their diverse metal sites and good acid degradation ability. Herein Co-doped Zn-MOF-5 nanoparticles with a high Co doping rate of 60% were synthesized for chemo-chemodynamic synergistic therapy of tumor. Co ions can mediate chemodynamic therapy through Fenton-like reaction and regulate the tumor microenvironment by consuming the reduced glutathione. The CoZn-MOF-5 shows high drug loading capacity with doxorubicin loading rate of 72.8%. The CoZn-MOF-5@PEG@DOX nanodrugs has a strong killing effect on 4T1 cancer cells, suggesting the chemo-chemodynamic synergistic effect on tumor therapy.

Iron-based materials for simultaneous removal of heavy metal(loid)s and emerging organic contaminants from the aquatic environment: Recent advances and perspectives.

The existence of heavy metals and emerging organic contaminants in wastewater produces serious toxic residues to the environment. Developing cheap and efficient materials to remove these persistent pollutants is crucial. Iron-based materials are cost-effective and environmentally friendly catalysts, and their applications in the environmental field deserve attention. This paper critically reviewed the removal mechanisms of heavy metals and emerging organic pollutants by different influencing factors. The removal of pollutants (heavy metals and emerging organic pollutants) in a multi-component system was analyzed in detail. The mechanisms of synergism, antagonism and non-interference were discussed. This paper had a certain reference value for the research of wastewater remediation technology which could simultaneously remove various pollutants by iron-based materials.

Enhanced removal of Cr(VI) from aqueous solution by stabilized nanoscale zero valent iron and copper bimetal intercalated montmorillonite.

Batch experiments were conducted to study the Cr(VI) removal by nanoscale zero valent iron and copper intercalated montmorillonite (MMT-nFe0/Cu0) nanocomposite. MMT-nFe0/Cu0 was characterized using SEM, TEM, XRD, FTIR, N2 adsorption-desorption isotherms and XPS. The results demonstrated that highly dispersed nanoscale Fe0/Cu0 (nFe0/Cu0) were successfully introduced into the montmorillonite (MMT) layers. In the reaction process, the combination of Cu0 and Fe0 acted as a galvanic cell, and electrocorrosion not only speeded up the reaction rate, but also increased reduction activity of nFe0. MMT-nFe0/Cu0 as an excellent carrier had good functions in dispersing nFe0 and Cu0 particles, pH buffering and could keep nFe0 and Cu0 particles from being released. Besides, no iron ions and very low concentrations of copper ions released in the reaction system, which greatly avoided the influence of secondary environmental pollution.

Critical review of perovskite-based materials in advanced oxidation system for wastewater treatment: Design, applications and mechanisms.

Perovskite has been widely concerned in the field of modern environmental catalysis due to its low price, high stability, excellent catalytic activity, diverse structure and strong conversion adaptability. In recent years, people have been working on the coupling of perovskite catalysts and advanced oxidation processes (AOPs) on the removal of organic pollutants from wastewater. In this review, we classified perovskites of different designs and summarized the application and basic reaction mechanisms of each perovskite in different AOPs. This review helps scientists selecting and designing more effective perovskite catalysts for AOPs by summarizing the applications and reaction mechanisms of perovskite in AOPs. At the end of the review, the challenges and future directions of perovskite in removing organic pollutants from wastewater are discussed.

Cu-Fe embedded cross-linked 3D hydrogel for enhanced reductive removal of Cr(VI): Characterization, performance, and mechanisms.

Porous hydrogel, as a high-efficiency adsorbent for heavy metals, suffers the drawbacks of the use of expensive and toxic reagents during the process of preparation, further limiting its application ranges. Besides, the heavy metals couldn't be transformed into nontoxic species, which leads to the environmental pollution risk. Herein, a three-dimensionally (3D) structured Cu-Fe embedded cross-linked cellulose hydrogel (nFeCu-CH) was innovatively fabricated by a novel self-assembly and in-situ reduction method, which exhibited exceptionally enhanced adsorption-reduction property towards Cr(VI) wastewater. The results of degradation experiment exhibited that the removal reaction followed Langmuir-Hinshelwood first order kinetic model and the degradation rate constant decreased with solution pH and initial Cr(VI) concentration, while increased with nFeCu-CH dosage and temperature. Regeneration studies demonstrated that more than 88% of Cr(VI) was removed by nFeCu-CH even after five times of cycling. nFeCu-CH exhibited excellent reductive activity, which had a close connection with the superiority of 3D crosslinked architectures and bimetallic synergistic effect. And 97.1% of Cr(VI) could be removed when nFeCu-CH dosage was 9.5 g/L, pH was 5, initial concentration of Cr(VI) was 20 mg/L and temperature was 303 K. Combined with cellulose hydrogel not only could provide additional active sites, but also could restrain the crystallite growth and agglomeration of nano-metallic particles, leading to the promotion of Cr(VI) removal. In addition, coating with Cu facilitated the generation and transformation of electrons according to the continuous redox cycles of Fe(III)/Fe(II) and Cu(II)/Cu(I), leading to the further improvement of the reductivity of nFeCu-CH. Multiple interaction mechanisms including adsorption, reduction and co-precipitation between nFeCu-CH and Cr(VI) were realized. The current work suggested that nFeCu-CH with highly reactive sites, excellent stability and recyclability was considered as an potential material for remediation of Cr(VI) contaminated wastewater.

Improving Pesticide Uptake Modeling into Potatoes: Considering Tuber Growth Dynamics.

To explore pesticide uptake from soil into a growing potato, a moving-boundary dynamic model is proposed on the basis of the radical diffusion process of a chemical to a sphere. This model, which considers the logistic growth of the potato tuber, describes two hypothetical processes of chemical diffusion within a growing tuber. The model was tested in an illustrative case study for an application of chlorpyrifos. Results indicate that the distribution of chlorpyrifos concentrations along the potato radius is significantly affected by the tuber development. In comparison of our results to results from a classic model using a fixed boundary, the proposed dynamic model yields a quick and big jump for both the average concentration and bioconcentration factor (BCF) of chlorpyrifos in the potato as a result of the sigmoid expansion boundary. Overall, the dynamic model predicts that chlorpyrifos BCFs in the potato at harvest are higher than those using the classical model. In comparison of model results to measured uptake of chlorpyrifos into potato at harvest, the dynamic model shows better performance than the classical model. Our results provide a new perspective on pesticide uptake into potatoes and inform human health risk assessment for pesticides applied at different tuber growth stages.