A biochemical feedback signal for hypothermia treatment for neonatal hypoxic-ischemic encephalopathy: focusing on central nervous system proteins in biofluids.

Hypothermia has been widely used to treat moderate to severe neonatal hypoxic-ischemic encephalopathy (HIE), yet evaluating the effects of hypothermia relies on clinical neurology, neuroimaging, amplitude-integrated electroencephalography, and follow-up data on patient outcomes. Biomarkers of brain injury have been considered for estimating the effects of hypothermia. Proteins specific to the central nervous system (CNS) are components of nervous tissue, and once the CNS is damaged, these proteins are released into biofluids (cerebrospinal fluid, blood, urine, tears, saliva), and they can be used as markers of brain damage. Clinical reports have shown that CNS-specific marker proteins (CNSPs) were early expressed in biofluids after brain damage and formed unique biochemical profiles. As a result, these markers may serve as an indicator for screening brain injury in infants, monitoring disease progression, identifying damage region of brain, and assessing the efficacy of neuroprotective measures. In clinical work, we have found that there are few reports on using CNSPs as biological signals in hypothermia for neonatal HIE. The aim of this article is to review the classification, origin, biochemical composition, and physiological function of CNSPs with changes in their expression levels after hypothermia for neonatal HIE. Hopefully, this review will improve the awareness of CNSPs among pediatricians, and encourage future studies exploring the mechanisms behind the effects of hypothermia on these CNSPs, in order to reduce the adverse outcome of neonatal HIE.

Study of Impacts of Two Types of Cellular Aging on the Yeast Bud Morphogenesis.

Understanding the mechanisms of cellular aging processes is crucial for attempting to extend organismal lifespan and for studying age-related degenerative diseases. Yeast cells divide through budding, providing a classical biological model for studying cellular aging. With their powerful genetics, relatively short lifespan and well-established signaling pathways also found in animals, yeast cells offer valuable insights into the aging process. Recent experiments suggested the existence of two aging modes in yeast characterized by nucleolar and mitochondrial declines, respectively. In this study, by analyzing experimental data it was shown that cells evolving into those two aging modes behave differently when they are young. While buds grow linearly in both modes, cells that consistently generate spherical buds throughout their lifespan demonstrate greater efficacy in controlling bud size and growth rate at young ages. A three-dimensional chemical-mechanical model was developed and used to suggest and test hypothesized mechanisms of bud morphogenesis during aging. Experimentally calibrated simulations showed that tubular bud shape in one aging mode could be generated by locally inserting new materials at the bud tip guided by the polarized Cdc42 signal during the early stage of budding. Furthermore, the aspect ratio of the tubular bud could be stabilized during the late stage, as observed in experiments, through a reduction on the new cell surface material insertion or an expansion of the polarization site. Thus model simulations suggest the maintenance of new cell surface material insertion or chemical signal polarization could be weakened due to cellular aging in yeast and other cell types.

Tissue interplay during morphogenesis.

The process by which biological systems such as cells, tissues and organisms acquire shape has been named as morphogenesis and it is central to a plethora of biological contexts including embryo development, wound healing, or even cancer. Morphogenesis relies in both self-organising properties of the system and in environmental inputs (biochemical and biophysical). The classical view of morphogenesis is based on the study of external biochemical molecules, such as morphogens. However, recent studies are establishing that the mechanical environment is also used by cells to communicate within tissues, suggesting that this mechanical crosstalk is essential to synchronise morphogenetic transitions and self-organisation. In this article we discuss how tissue interaction drive robust morphogenesis, starting from a classical biochemical view, to finalise with more recent advances on how the biophysical properties of a tissue feedback with their surroundings to allow form acquisition. We also comment on how in silico models aid to integrate and predict changes in cell and tissue behaviour. Finally, considering recent advances from the developmental biomechanics field showing that mechanical inputs work as cues that promote morphogenesis, we invite to revisit the concept of morphogen.

Combined High-Throughput Approaches Reveal the Signals Driven by Skin and Blood Environments and Define the Tumor Heterogeneity in Sézary Syndrome.

Sézary syndrome (SS) is an aggressive variant of cutaneous t-cell lymphoma characterized by the accumulation of neoplastic CD4+ lymphocytes-the SS cells-mainly in blood, lymph nodes, and skin. The tumor spread pattern of SS makes this lymphoma a unique model of disease that allows a concurrent blood and skin sampling for analysis. This review summarizes the recent studies highlighting the transcriptional programs triggered by the crosstalk between SS cells and blood-skin microenvironments. Emerging data proved that skin-derived SS cells show consistently higher activation/proliferation rates, mainly driven by T-cell receptor signaling with respect to matched blood SS cells that instead appear quiescent. Biochemical analyses also demonstrated an hyperactivation of PI3K/AKT/mTOR, a targetable pathway by multiple inhibitors currently in clinical trials, in skin SS cells compared with a paired blood counterpart. These results indicated that active and quiescent SS cells coexist in this lymphoma, and that they could be respectively treated with different therapeutics. Finally, this review underlines the more recent discoveries into the heterogeneity of circulating SS cells, highlighting a series of novel markers that could improve the diagnosis and that represent novel therapeutic targets (GPR15, PTPN13, KLRB1, and ITGB1) as well as new genetic markers (PD-1 and CD39) able to stratify SS patients for disease aggressiveness.

Optical flexible biosensors: From detection principles to biomedical applications.

Optical flexible biosensors are novel sensors fabricated on flexible or ductile materials that are used for the detection of analytes. Compared to traditional sensors, these biosensors offer greater flexibility, which allows them to adapt to different working environments, to meet the deformation requirements of humans. Flexible devices can not only detect alterations in analytes in vitro, but can also realize real-time and non-invasive monitoring of the variation of physical conditions or metabolites in vivo. Flexible devices are earning increasing attention from researchers and clinicians. In the present review, we summarize and introduce the detection principles, key analytes, and applications of optical flexible biosensors in the diagnosis/treatment of diseases as well as health detection. Moreover, the remaining challenges of flexible devices and their perspectives have also been addressed. We hope that this review will pave ways for the development of more feasible and multifunctional flexible devices.

A microfluidic generator of dynamic shear stress and biochemical signals based on autonomously oscillatory flow.

Biological cells in vivo typically reside in a dynamic flowing microenvironment with extensive biomechanical and biochemical cues varying in time and space. These dynamic biomechanical and biochemical signals together act to regulate cellular behaviors and functions. Microfluidic technology is an important experimental platform for mimicking extracellular flowing microenvironment in vitro. However, most existing microfluidic chips for generating dynamic shear stress and biochemical signals require expensive, large peripheral pumps and external control systems, unsuitable for being placed inside cell incubators to conduct cell biology experiments. This study has developed a microfluidic generator of dynamic shear stress and biochemical signals based on autonomously oscillatory flow. Further, based on the lumped-parameter and distributed-parameter models of multiscale fluid dynamics, the oscillatory flow field and the concentration field of biochemical factors has been simulated at the cell culture region within the designed microfluidic chip. Using the constructed experimental system, the feasibility of the designed microfluidic chip has been validated by simulating biochemical factors with red dye. The simulation results demonstrate that dynamic shear stress and biochemical signals with adjustable period and amplitude can be generated at the cell culture chamber within the microfluidic chip. The amplitudes of dynamic shear stress and biochemical signals is proportional to the pressure difference and inversely proportional to the flow resistance, while their periods are correlated positively with the flow capacity and the flow resistance. The experimental results reveal the feasibility of the designed microfluidic chip. Conclusively, the proposed microfluidic generator based on autonomously oscillatory flow can generate dynamic shear stress and biochemical signals without peripheral pumps and external control systems. In addition to reducing the experimental cost, due to the tiny volume, it is beneficial to be integrated into cell incubators for cell biology experiments. Thus, the proposed microfluidic chip provides a novel experimental platform for cell biology investigations.

Precise generation of dynamic biochemical signals by controlling the programmable pump in a Y-shaped microfluidic chip with a "christmas tree" inlet.

The generation of dynamic biochemical signals in a microfluidic control system is of importance for the study of the interaction between biological cells and their niches. However, most of microfluidic control systems are not able to provide dynamic biochemical signals with high precision and stability due to inherent mechanical vibrations caused by the actuators of the programmable pumps. In this paper, we propose a novel microfluidic feedback control system integrating an external feedback control system with a Y-shaped microfluidic chip with a "Christmas tree" inlet. The Proportional Integral Derivative (PID) controller is implemented to reduce the influence of vibrations. In order to regulate the control parameters efficiently, a mathematical model is built to describe the actuator of the programmable pump, in which a fractional-order model is utilized. Both simulation and experimental studies are carried out, confirming that the microfluidic feedback control system can precisely and stably generate desired dynamic biochemical signals.

A review of computational models of bone fracture healing.

In the process of fracture healing, there are many cellular and molecular events that are regulated by mechanical stimuli and biochemical signals. To explore the unknown mechanisms underlying bone fracture healing, optimal fixation configurations, and the design of new treatment strategies, computational healing models provide a good solution. With the simulation of mechanoregulatory healing models, bioregulatory healing models and coupled mechanobioregulatory healing models, healing outcomes can be predicted. In this review, first, we provide an overview of current computational healing models. Their clinical applications are also presented. Then, the limitations of current models and their corresponding solutions are discussed in this review. Finally, future potentials are presented in this review. Multiscale modeling from the intracellular level to the tissue level is essential, and more clinical applications of computational healing models are required in future research.

A review of bioregulatory and coupled mechanobioregulatory mathematical models for secondary fracture healing.

Fracture healing is a complex biological process involving many cellular and molecular events. During fracture healing, biochemical signals play a regulatory role in promoting the healing process. Although many experiments have been conducted to study fracture healing, not all of the mechanisms are clearly understood. Over the past years, a lot of mathematical models and computational simulations have been established to investigate the fracture healing process. These models offer a powerful tool to study the interplay between cell behaviour, mechanical stimuli and biochemical signals and help design new treatment strategies. However, most of the mathematical models focus on the effect of mechanical stimuli and few models consider the important role of biochemical signals during fracture healing. In this review, we first emphasize the importance of biochemical signals during fracture healing. Then, existing bioregulatory and coupled mechanobioregulatory models are presented. Finally, some limitations and possible solutions are discussed.