Blockchain technology has gained considerable attention, with an escalating interest in a plethora of numerous applications, ranging from data management, financial services, cyber security, IoT, and food science to healthcare industry and brain research. There has been a remarkable interest witnessed in utilizing applications of blockchain for the delivery of safe and secure healthcare data management. Also, blockchain is reforming the traditional healthcare practices to a more reliable means, in terms of effective diagnosis and treatment through safe and secure data sharing. In the future, blockchain could be a technology that may potentially help in personalized, authentic, and secure healthcare by merging the entire real-time clinical data of a patient’s health and presenting it in an up-to-date secure healthcare setup. In this paper, we review both the existing and latest developments in the field of healthcare by implementing blockchain as a model. We also discuss the applications of blockchain, along with the challenges faced and future perspectives.

Single-cell proteomics can reveal cellular phenotypic heterogeneity and cell-specific functional networks underlying biological processes. Here, we present a streamlined workflow combining microfluidic chips for all-in-one proteomic sample preparation and data-independent acquisition (DIA) mass spectrometry (MS) for proteomic analysis down to the single-cell level. The proteomics chips enable multiplexed and automated cell isolation/counting/imaging and sample processing in a single device. Combining chip-based sample handling with DIA-MS using project-specific mass spectral libraries, we profile on average ~1,500 protein groups across 20 single mammalian cells. Applying the chip-DIA workflow to profile the proteomes of adherent and non-adherent malignant cells, we cover a dynamic range of 5 orders of magnitude with good reproducibility and <16% missing values between runs. Taken together, the chip-DIA workflow offers all-in-one cell characterization, analytical sensitivity and robustness, and the option to add additional functionalities in the future, thus providing a basis for advanced single-cell proteomics applications.

Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.

Over the last couple of decades the healthcare monitoring system has drawn considerable attentions of the researchers. The growing trends in information and communication technology (ICT) applications have given birth to potential technologies (such as, Telemedicine, Telemonitoring and Tele-health etc.) which have replaced the traditional healthcare with more advanced digital healthcare system. Although these technologies have reshaped the healthcare scenarios at a good extent but none of them has fully succeeded in providing a complete, up-to-date and reliable telemonitoring frame-work in terms of cost, time and better real-time diagnosis. Consequently, most of the available technologies being practiced are used in parts which are equally expensive as well as time-consuming. This paper focuses on the development of a novel, rapid and cost-effective tele-monitoring architecture based on an Arduino device hardware system. The prime goal was to design a prototype that could serve as a reliable patient monitoring system, so that healthcare professionals can monitor their patients in real-time, who are either hospitalized in critical conditions or unable to perform their normal daily life activities. In this work we have presented an Arduino based cost effective Tele-monitoring system that can provide real-time information about physiological conditions of a patient. Our proposed system is designed to measure, monitor and transmit important physiological parameters of patients in the form of vital signs in order to accurately describe the status of their health and fitness. This prototype framework would be helpful to perform real-time tele-monitoring which will ultimately lead to better diagnosis and treatment of remote patient community.