Cervical pre-cancer classification using entropic features and CNN: In vivo validation with a handheld fluorescence probe

Cervical cancer is one of the most prevalent forms of cancer, with a lengthy latent period and a gradual onset phase. Conventional techniques are found to be severely lacking in real time detection of disease progression which can greatly enhance the cure rate. Due to their high sensitivity and specificity, optical techniques are emerging as reliable tools, particularly in case of cancer. It has been seen that biochemical changes are better highlighted through intrinsic fluorescence devoid of interference from absorption and scattering. Its effectiveness in in-vivo conditions is affected by the fact that the intrinsic spectral signatures vary from patient to patient, as well as in different population groups. Here, we overcome this limitation by collectively enumerating the subtle changes in the spectral profiles and correlations through an information theory based entropic approach, which significantly amplifies the minute spectral variations. In conjunction with artificial intelligence (AI)/machine learning (ML) tools, it yields high specificity and sensitivity with a small dataset from patients in clinical conditions, without artificial augmentation. We have used an in-house developed handheld probe (i-HHP) for extracting intrinsic fluorescence spectra of human cervix from 110 different subjects drawn from diverse population groups. The average classification accuracy of the proposed methodology using 10-fold cross validation is 93.17%. A combination of polarised fluorescence spectra from i-HHP and the proposed classifier is proven to be minimally invasive with the ability to diagnose patients in real time. This paves the way for effective use of relatively smaller sized sensitive fluorescence data with advanced AI/ML tools for early cervical cancer detection in clinics.

A Neutral Flavin-Triphenylamine Probe for Mitochondrial Bioimaging under Different Microenvironments

A bioinspired design built around a neutral flavin-triphenylamine core has been investigated for selective mitochondrial bioimaging capabilities in different microenvironments. Significant advantages with respect to long-term tracking, faster internalization, penetrability within the spheroid structures, and strong emission signal under induced hypoxia conditions have been observed, which could offer an alternative to the existing mitotrackers for hypoxia-related biological events.

Formation of multiple complex light structures simultaneously in 3D volume using a single binary phase mask

Complex structure formation inside or through turbid media is a challenging task due to refractive index inhomogeneity, random light scattering, and speckle noise formation. In this article, we have coupled the data regression model in the R-squared metric and used its advantages as a fitness function in the genetic algorithm to advance the resolution and structural uniformity. As a compatible system with the binary genetic algorithm, we have presented a cost-effective iterative wavefront shaping system-design with binary phase modulation using an affordable ferroelectric liquid crystal (FLC) based binary-phase spatial light modulator (SLM). R-squared metric in the genetic algorithm is analyzed to optimize the binary phase mask, and the prototype system based on iterative binary phase modulation has been validated with a 120-grit ground glass diffuser and fresh chicken tissues of thickness 307 [Formula: see text] and 812 [Formula: see text]. The detailed results show that the proposed cost-effective wavefront shaping system with data regression model assisted R-squared fitness function can construct high-resolution multiple complex hetero-structures simultaneously in 3D volume using an optimized single phase-mask.

Co-electrolysis of seawater and carbon dioxide inside a microfluidic reactor to synthesize speciality organics

We report co-electrolysis of seawater and carbon dioxide (CO₂) gas in a solar cell-integrated membraneless microfluidic reactor for continuous synthesis of organic products. The microfluidic reactor was fabricated using polydimethylsiloxane substrate comprising of a central microchannel with a pair of inlets for injection of CO₂ gas and seawater and an outlet for removal of organic products. A pair of copper electrodes were inserted into microchannel to ensure its direct interaction with incoming CO₂ gas and seawater as they pass into the microchannel. The coupling of solar cell panels with electrodes generated a high-intensity electrical field across the electrodes at low voltage, which facilitated the co-electrolysis of CO₂ and seawater. The paired electrolysis of CO₂ gas and seawater produced a range of industrially important organics under influence of solar cell-mediated external electric field. The, as synthesized, organic compounds were collected downstream and identified using characterization techniques. Furthermore, the probable underlying electrochemical reaction mechanisms near the electrodes were proposed for synthesis of organic products. The inclusion of greenhouse CO₂ gas as reactant, seawater as electrolyte, and solar energy as an inexpensive electric source for co-electrolysis initiation makes the microreactor a low-cost and sustainable alternative for CO₂ sequestration and synthesis of organic compounds.

Recent Trends and Practices Toward Assessment and Rehabilitation of Neurodegenerative Disorders: Insights From Human Gait

The study of human movement and biomechanics forms an integral part of various clinical assessments and provides valuable information toward diagnosing neurodegenerative disorders where the motor symptoms predominate. Conventional gait and postural balance analysis techniques like force platforms, motion cameras, etc., are complex, expensive equipment requiring specialist operators, thereby posing a significant challenge toward translation to the clinics. The current manuscript presents an overview and relevant literature summarizing the umbrella of factors associated with neurodegenerative disorder management: from the pathogenesis and motor symptoms of commonly occurring disorders to current alternate practices toward its quantification and mitigation. This article reviews recent advances in technologies and methodologies for managing important neurodegenerative gait and balance disorders, emphasizing assessment and rehabilitation/assistance. The review predominantly focuses on the application of inertial sensors toward various facets of gait analysis, including event detection, spatiotemporal gait parameter measurement, estimation of joint kinematics, and postural balance analysis. In addition, the use of other sensing principles such as foot-force interaction measurement, electromyography techniques, electrogoniometers, force-myography, ultrasonic, piezoelectric, and microphone sensors has also been explored. The review also examined the commercially available wearable gait analysis systems. Additionally, a summary of recent progress in therapeutic approaches, viz., wearables, virtual reality (VR), and phytochemical compounds, has also been presented, explicitly targeting the neuro-motor and functional impairments associated with these disorders. Efforts toward therapeutic and functional rehabilitation through VR, wearables, and different phytochemical compounds are presented using recent examples of research across the commonly occurring neurodegenerative conditions [viz., Parkinson's disease (PD), Alzheimer's disease (AD), multiple sclerosis, Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS)]. Studies exploring the potential role of Phyto compounds in mitigating commonly associated neurodegenerative pathologies such as mitochondrial dysfunction, α-synuclein accumulation, imbalance of free radicals, etc., are also discussed in breadth. Parameters such as joint angles, plantar pressure, and muscle force can be measured using portable and wearable sensors like accelerometers, gyroscopes, footswitches, force sensors, etc. Kinetic foot insoles and inertial measurement tools are widely explored for studying kinematic and kinetic parameters associated with gait. With advanced correlation algorithms and extensive RCTs, such measurement techniques can be an effective clinical and home-based monitoring and rehabilitation tool for neuro-impaired gait. As evident from the present literature, although the vast majority of works reported are not clinically and extensively validated to derive a firm conclusion about the effectiveness of such techniques, wearable sensors present a promising impact toward dealing with neurodegenerative motor disorders.