We present a novel method to rapidly assess drug efficacy in targeted cancer therapy, where antineoplastic agents are conjugated to antibodies targeting surface markers on tumor cells. We have fabricated and characterized a device capable of rapidly assessing tumor cell sensitivity to drugs using multifrequency impedance spectroscopy in combination with supervised machine learning for enhanced classification accuracy. Currently commercially available devices for the automated analysis of cell viability are based on staining, which fundamentally limits the subsequent characterization of these cells as well as downstream molecular analysis. Our approach requires as little as 20 μL of volume and avoids staining allowing for further downstream molecular analysis. To the best of our knowledge, this manuscript presents the first comprehensive attempt to using high-dimensional data and supervised machine learning, particularly phase change spectra obtained from multi-frequency impedance cytometry as features for the support vector machine classifier, to assess viability of cells without staining or labelling.

Alzheimer's disease (AD) is the sixth-leading reason of fatality and is 70% present in all cases of dementia. The global burden of AD is expected to accelerate from 26.6 million cases in 2006 to 106.8 million by 2050. The total assumed worldwide costs of dementia were US$ 604 billion in 2010, equivalent to 1% of the world's Gross domestic product (GDP). This review is focused on the overview of pathophysiology and management of AD. The sources for the literature search were PubMed, ScienceDirect, Scopus and Google Scholar. AD is generally considered as disorders related to intensify loss of neurons and synapses proceeds in distinct anatomical loci, resulting in different phenotypes. The pathophysiology of Alzheimer's disease is credited to a number of factors such as the cholinergic dysfunction, amyloid/tau toxicity and oxidative stress/ mitochondrial dysfunction. Apart from various therapeutic targets, biomarkers and pharmaco-therapies available; Herbal drugs, secondary metabolites and to the some extent non-pharmacological therapies are impending and potential candidates for the management of AD. Further studies are required to elaborate the detailed mechanism of Herbal drugs, secondary metabolites and non-pharmacological therapies for the management of AD.

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We present a wearable microfluidic impedance cytometer implemented on a flexible circuit wristband with on-line smartphone readout for portable biomarker counting and analysis. The platform contains a standard polydimethylsiloxane (PDMS) microfluidic channel integrated on a wristband, and the circuitry on the wristband is composed  of a custom analog lock-in amplification system, a microcontroller with an 8-bit analog-to-digital converter (ADC), and a Bluetooth module wirelessly paired with a smartphone. The lock-in amplification (LIA) system is implemented with a novel architecture which consists of the lock-in amplifier followed by a high-pass filter stage with DC offset subtraction, and a post-subtraction high gain stage enabling detection of particles as small as 2.8  μm using the 8-bit ADC. The Android smartphone application was used to initiate the system and for offline data-plotting and peak counting, and supports online data readout, analysis, and file management. The data is exportable to researchers and medical professionals for in-depth analysis and remote health monitoring. The system, including the microfluidic sensor, microcontroller, and Bluetooth module all fit on the wristband with a footprint of less than 80 cm 2 . We demonstrate the ability of the system to obtain generalized blood cell counts; however the system can be applied to a wide variety of biomarkers by interchanging the standard microfluidic channel with microfluidic channels designed for biomarker isolation.

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