Optical absorbance-based rapid test for the detection of sickle cell trait and sickle cell disease at the point-of-care.

People afflicted with sickle cell disease (SCD) experience severe deterioration in quality of life. The disease is characterized by debilitating pain, anemia, and increased susceptibility to life threatening infections. This genetic disorder is endemic to many parts of the world. Extensive and accurate screening of individuals with sickle cell trait (SCT) in the population, coupled with genetic counselling can inhibit the propagation of the disease. The gold-standard techniques for the detection of sickle hemoglobin, such as capillary electrophoresis, HPLC, and genetic testing, are prohibitively expensive and time-consuming. Mass screening is usually conducted with a low-cost test called the solubility test, which does not offer high specificity. This study proposes a game-changing single-step low-cost method for rapidly yet accurately screening and diagnosing SCD and SCT. This method relies on the hitherto unexplored differences in the optical absorbance between diseased, trait, and normal blood samples, under deoxygenated conditions. The proposed method was tested in two phases of clinical validation: a pilot study and a blind study. A total of 438 patient samples were tested using the proposed method across the two phases. The proposed method offers an average accuracy, sensitivity, and specificity of 97.6%, 96.9%, and 98.6%, respectively. The proposed test has the potential to obliviate the conventional two-step process of screening and diagnostic tests as it can be used at the point-of-care with minimal training and yet yield results reliable enough to assess disability benefit claims.

Recent technical advances in whole slide imaging instrumentation.

Microscopic observation of biological specimen smears is the mainstay of diagnostic pathology, as defined by the Digital Pathology Association. Though automated systems for this are commercially available, their bulky size and high cost renders them unusable for remote areas. The research community is investing much effort towards building equivalent but portable, low-cost systems. An overview of such research is presented here, including a comparative analysis of recent reports. This paper also reviews recently reported systems for automated staining and smear formation, including microfluidic devices; and optical and computational automated microscopy systems including smartphone-based devices. Image pre-processing and analysis methods for automated diagnosis are also briefly discussed. It concludes with a set of foreseeable research directions that could lead to affordable, integrated and accurate whole slide imaging systems.

Diagnosis of some diseases such as cervical cancer is done using a microscope, and this process still relies heavily on human experts. Since the need for such diagnosis is increasing at a rapid pace, it makes a lot of sense to automate the whole process. This requires automatic microscopes, which should be able to take images of a 'slide' - a glass slab with colorized human cells at its surface. These images should get analyzed by a software, resulting in a fully automated diagnosis. This article reviews recent research into this field, especially the technical advances on the hardware for automated microscopes (also known as slide imagers). It compares research reports and highlights how there's still more effort needed to build low-cost, yet clinically useful systems. It also highlights some of the emerging technologies that can be integrated into slide imagers to enable new kinds of diagnostics.

Emerging graphene-based sensors for the detection of food adulterants and toxicants - A review.

The detection of food adulterants and toxicants can prevent a large variety of adverse health conditions for the global population. Through the process of rapid sensing enabled by deploying novel and robust sensors, the food industry can assist in the detection of adulterants and toxicants at trace levels. Sensor platforms which exploit graphene-based nanomaterials satisfy this requirement due to outstanding electrical, optical and thermal properties. The materials' facile conjugation with linkers and biomolecules along with the option for further enhancement using nanoparticles results in highly sensitive and selective sensing characteristics. This review highlights novel applications of graphene derivatives for detection covering three important approaches; optical, electrical (field-effect) and electrochemical sensing. Suitable graphene-based sensors for portable devices as point-of-need platforms are also presented. The future scope of these sensors is discussed to showcase how these emerging techniques will disrupt the food detection sector for years to come.

Guided filter based image enhancement for focal error compensation in low cost automated histopathology microscopic system.

Low-cost automated histopathology microscopy systems usually suffer from optical imperfections, producing images that are slightly Out of Focus (OoF). In this work, a guided filter (GF) based image preprocessing is proposed for compensating focal errors and its efficacy is demonstrated on images of healthy and malaria infected red blood cells (h-RBCs and i-RBCs), and PAP smears. Since contrast enhancement has been widely used as an image preprocessing step for the analysis of histopathology images, a systematic comparison is made with six such prominently used methods, namely Contrast Limited Adaptive Histogram Equalization (CLAHE), RIQMC-based optimal histogram matching (ROHIM), modified L0, Morphological Varying(MV)-Bitonic filter, unsharp mask filter and joint bilateral filter. The images enhanced using GF approach lead to better segmentation accuracy (upto 50% improvement over native images) and visual quality compared to other approaches, without any change in the color tones. Thus, the proposed GF approach is a viable solution for rectifying the OoF microscopy images without the loss of the valuable diagnostic information presented by the color tone.