Algorithms for Monitoring Heart Rate and Respiratory Rate From the Video of a User's Face.

Smartphone cameras can measure heart rate (HR) by detecting pulsatile photoplethysmographic (iPPG) signals from post-processing the video of a subject's face. The iPPG signal is often derived from variations in the intensity of the green channel as shown by Poh et. al. and Verkruysse et. al.. In this pilot study, we have introduced a novel iPPG method where by measuring variations in color of reflected light, i.e., Hue, and can therefore measure both HR and respiratory rate (RR) from the video of a subject's face. This paper was performed on 25 healthy individuals (Ages 20-30, 15 males and 10 females, and skin color was Fitzpatrick scale 1-6). For each subject we took two 20 second video of the subject's face with minimal movement, one with flash ON and one with flash OFF. While recording the videos we simultaneously measuring HR using a Biosync B-50DL Finger Heart Rate Monitor, and RR using self-reporting. This paper shows that our proposed approach of measuring iPPG using Hue (range 0-0.1) gives more accurate readings than the Green channel. HR/Hue (range 0-0.1) ([Formula: see text], [Formula: see text]-value = 4.1617, and RMSE = 0.8887) is more accurate compared with HR/Green ([Formula: see text], [Formula: see text]-value = 11.60172, and RMSE = 0.9068). RR/Hue (range 0-0.1) ([Formula: see text], [Formula: see text]-value = 0.2885, and RMSE = 3.8884) is more accurate compared with RR/Green ([Formula: see text], [Formula: see text]-value = 0.5608, and RMSE = 5.6885). We hope that this hardware agnostic approach for detection of vital signals will have a huge potential impact in telemedicine, and can be used to tackle challenges, such as continuous non-contact monitoring of neo-natal and elderly patients. An implementation of the algorithm can be found at https://pulser.thinkbiosolution.com.

How flexible is a protein: simple estimates using FRET microscopy.

Flexible proteins are frequently used to link subunits of larger complexes in various contexts, for instance, in the construction of unimolecular sensors used in FRET microscopy, and fusion proteins. How flexible such linkers are can be an important question in the overall design of the complex, and yet sometimes suprisingly difficult to establish. Such difficulties can arise because the actual flexibility of a protein depends significantly on its interactions with the solvent, and when the local environment is a subcellular compartment, even the conditions of the solvent, may not be known. In this communication we propose a simple numerical procedure through which the flexibility of such proteins can be extracted from FRET based microscopy data.

TongueSim: Development of an Automated Method for Rapid Assessment of Fungiform Papillae Density for Taste Research.

Taste buds are found on the tongue in 3 types of structures: the fungiform papillae, the foliate papillae, and the circumvallate papillae. Of these, the fungiform papillae (FP) are present in the greatest numbers on the tongue, and are thought to be correlated to the overall number of taste buds. For this reason, FP density on the tongue is often used to infer taste function, although this has been controversial. Historically, videomicroscopy techniques were used to assess FP. More recently, advances in digital still photography and in software have allowed the development of rapid methods for obtaining high quality images in situ. However, these can be subject to inter-researcher variation in FP identification, and are somewhat limited in the parameters that can be measured. Here, we describe the development of a novel, automated method to count the FP, using the TongueSim suite of software. Advantages include the reduction in time required for image analysis, elimination of researcher bias, and the added potential to measure characteristics such as the degree of roundness of each papilla. We envisage that such software has a wide variety of novel research applications.

In Silico Designing of an Industrially Sustainable Carbonic Anhydrase Using Molecular Dynamics Simulation.

Carbonic anhydrase (CA) is a family of metalloenzymes that has the potential to sequestrate carbon dioxide (CO2) from the environment and reduce pollution. The goal of this study is to apply protein engineering to develop a modified CA enzyme that has both higher stability and activity and hence could be used for industrial purposes. In the current study, we have developed an in silico method to understand the molecular basis behind the stability of CA. We have performed comparative molecular dynamics simulation of two homologous α-CA, one of thermophilic origin (Sulfurihydrogenibium sp.) and its mesophilic counterpart (Neisseria gonorrhoeae), for 100 ns each at 300, 350, 400, and 500 K. Comparing the trajectories of two proteins using different stability-determining factors, we have designed a highly thermostable version of mesophilic α-CA by introducing three mutations (S44R, S139E, and K168R). The designed mutant α-CA maintains conformational stability at high temperatures. This study shows the potential to develop industrially stable variants of enzymes while maintaining high activity.