Protein-protein interactions and enzyme-catalyzed reactions are the fundamental processes in life, and the quantification and manipulation, kinetics determination, and ether activation or inhibition of these processes are critical for fully understanding physiological processes and discovering new medicine. Various methodologies and technologies have been developed to determine the parameters of these biological and medical processes. However, due to the extreme complexity of these processes, current methods and technologies can only determine one or a few parameters. The recent development of quantitative Forster resonance energy transfer (qFRET) methodology combined with technology aims to establish a high-throughput assay platform to determine protein interaction affinity, enzymatic kinetics, high-throughput screening, and pharmacological parameters using one assay platform. The FRET assay is widely used in biological and biomedical research in vitro and in vivo and provides high-sensitivity measurement in real time. Extensive efforts have been made to develop the FRET assay into a quantitative assay to determine protein-protein interaction affinity and enzymatic kinetics in the past. However, the progress has been challenging due to complicated FRET signal analysis and translational hurdles. The recent qFRET analysis utilizes cross-wavelength correlation coefficiency to dissect the sensitized FRET signal from the total fluorescence signal, which then is used for various biochemical and pharmacological parameter determination, such as KD, Kcat, KM, Ki, IC50, and product inhibition kinetics parameters. The qFRET-based biochemical and pharmacological parameter assays and qFRET-based screenings are conducted in 384-well plates in a high-throughput assay mode. Therefore, the qFRET assay platform can provide a universal high-throughput assay platform for future large-scale protein characterizations and therapeutics development.

Merging electronics with textiles has become an emerging trend since textiles hold magnificent wearing comfort and userfriendliness compared with conventional wearable bioelectronics. Smart textiles can be effectively integrated into our daily wearing to convert on-body biomechanical, biochemical, and body heat energy into electrical signals for long-term, real-time monitoring of physiological states, showing compelling medical and economic benefits. This review summarizes the current progress in self-powered biomonitoring textiles along three pathways: biomechanical, body heat, and biochemical energy conversion. Finally, it also presents promising directions and challenges in the field, as well as insights into future development. This review aims to highlight the frontiers of smart textiles for self-powered biomonitoring, which could contribute to revolutionizing our traditional healthcare into a personalized model.

The Severe Acute Respiratory Syndrome (SARS)-CoV-2-induced Coronavirus Disease 2019 (COVID-19) pandemic has caused an overwhelming influence on public health because of its high morbidity and mortality. Critical-illness cases often manifest as acute respiratory distress syndrome (ARDS). Previous evidence has suggested platelets and thrombotic events as key mediators of SARS-CoV-2-associated ARDS. However, how the balance of platelet regeneration from the hematopoietic system is changed in ARDS remains elusive. Here, we reported a more severe inflammation condition and hyperactivity of platelets in COVID-19 ARDS patients compared with those infected but without ARDS. Analysis of peripheral blood revealed an increased proportion of hematopoietic stem cells (HSCs), common myeloid progenitors (CMPs), megakaryocyteerythrocyte progenitors (MEPs), and megakaryocyte progenitors (MkPs) in ARDS patients, suggesting a megakaryocytic-differentiation tendency. Finally, we found altered gene expression pattern in HSCs in COVID-19 ARDS patients. Surprisingly, genes representing platelet-primed HSCs were downregulated, indicating these cells are being stimulated to differentiate. Taken together, our findings shed light on the response of the hematopoietic system to replenish platelets that were excessively consumed in COVID-19 ARDS, providing a mechanism for disease progression and further therapeutic development.

Optical imaging and spectroscopic modalities are of broad interest for in-vivo molecular imaging, fluorescence guided cancer surgery, minimally invasive diagnostic procedures, and wearable devices. However, considerable debate still exists as to how deeply visible and near-infrared (NIR) light could penetrate normal and diseased tissues under clinically relevant conditions. Here we report the use of surface-enhanced Raman scattering (SERS) nanotags embedded in ex-vivo animal tissues for direct and quantitative measurements of light attenuation and spectroscopic detection depth at both the NIR-I and NIR-II spectral windows. SERS nanotags are well suited for this purpose because of their sharp spectral features that can be accurately differentiated from fluorescence and background emission. For the first time, the spectroscopic detection depth is quantitatively defined and measured as the maximal thickness of tissues through which the embedded SERS nanotags are still detected at a signal-to-noise ratio (SNR) of three (99.7% confidence level). Based on data from six types of fresh ex-vivo tissues (brain, kidney, liver, muscle, fat, and skin), we find that the maximum detection depth values range from 1—3 mm in the NIR-I window, to 3—6 mm in the NIR-II window. The depth values are largely determined by two factors - the intrinsic optical properties of the tissue, and the overall SNRs of the system without the tissue (system SNR, a result of nanotag brightness, instrument efficiency, and data acquisition parameters). In particular, there is an approximately linearlogarithmic relationship between the system SNR and maximum detection depth. Thus, the detection of hidden or occult lesions can be improved by three strategies - reducing tissue attenuation, minimizing background noise, and maximizing the system’s performance as judged by SNR.

Three-dimensional cancer-on-a-chip tissue models aim to replicate the key hallmarks of the tumour microenvironment and allow for the study of dynamic interactions that occur during tumour progression. Recently, complex cancer-on-a-chip models incorporating multiple cell types and biomimetic extracellular matrices have been developed. These models have generated new research directions in engineering and medicine by allowing for the real-time observation of cancer-host cell interactions in a physiologically relevant microenvironment. However, these cancer-on-a-chip models have yet to overcome limitations including the complexity of device manufacturing, the selection of optimal materials for preclinical drug screening studies, long-term microfluidic cell culture as well as associated challenges, and the technical robustness or difficulty in the use of these microfluidic platforms. In this review, an overview of the tumour microenvironment, its unique characteristics, and the recent advances of cancer-on-a-chip models that recapitulate native features of the tumour microenvironment are presented. The current challenges that cancer-on-a-chip models face and the future directions of research that are expected to be seen are also discussed.