Optical fiber tips for biological applications: From light confinement, biosensing to bioparticles manipulation.

BACKGROUND: The tip of an optical fiber has been considered an attractive platform in Biology. The simple cleaved end of an optical fiber can be machined, patterned and/or functionalized, acquiring unique properties enabling the exploitation of novel optical phenomena. Prompted by the constant need to measure and manipulate nanoparticles, the invention of the Scanning Near-field Optical Microscopy (SNOM) triggered the optimization and development of novel fiber tip microfabrication methods. In fact, the fiber tip was soon considered a key element in SNOM by confining light to sufficiently small extensions, challenging the diffraction limit. As result and in consequence of the newly proposed "Lab On Tip" concept, several geometries of fiber tips were applied in three main fields: imaging (in Microscopy/Spectroscopy), biosensors and micromanipulation (Optical Fiber Tweezers, OFTs). These are able to exert forces on microparticles, trap and manipulate them for relevant applications, as biomolecules mechanical study or protein aggregates unfolding. SCOPE OF REVIEW: This review presents an overview of the main achievements, most impactful studies and limitations of fiber tip-based configurations within the above three fields, along the past 10 years. MAJOR CONCLUSIONS: OFTs could be in future a valuable tool for studying several cellular phenomena such as neurodegeneration caused by abnormal protein fibrils or manipulating organelles within cells. This could contribute to understand the mechanisms of some diseases or biophenomena, as the axonal growth in neurons. GENERAL SIGNIFICANCE: To the best of our knowledge, no other review article has so far provided such a broad view. Despite of the limitations, fiber tips have key roles in Biology/Medicine.

Fabrication of Multimode-Single Mode Polymer Fiber Tweezers for Single Cell Trapping and Identification with Improved Performance.

Optical fiber tweezers have been gaining prominence in several applications in Biology and Medicine. Due to their outstanding focusing abilities, they are able to trap and manipulate microparticles, including cells, needing any physical contact and with a low degree of invasiveness to the trapped cell. Recently, we proposed a fiber tweezer configuration based on a polymeric micro-lens on the top of a single mode fiber, obtained by a self-guided photopolymerization process. This configuration is able to both trap and identify the target through the analysis of short-term portions of the back-scattered signal. In this paper, we propose a variant of this fabrication method, capable of producing more robust fiber tips, which produce stronger trapping effects on targets by as much as two to ten fold. These novel lenses maintain the capability of distinguish the different classes of trapped particles based on the back-scattered signal. This novel fabrication method consists in the introduction of a multi mode fiber section on the tip of a single mode (SM) fiber. A detailed description of how relevant fabrication parameters such as the length of the multi mode section and the photopolymerization laser power can be tuned for different purposes (e.g., microparticles trapping only, simultaneous trapping and sensing) is also provided, based on both experimental and theoretical evidences.

Single Particle Differentiation through 2D Optical Fiber Trapping and Back-Scattered Signal Statistical Analysis: An Exploratory Approach.

Recent trends on microbiology point out the urge to develop optical micro-tools with multifunctionalities such as simultaneous manipulation and sensing. Considering that miniaturization has been recognized as one of the most important paradigms of emerging sensing biotechnologies, optical fiber tools, including Optical Fiber Tweezers (OFTs), are suitable candidates for developing multifunctional small sensors for Medicine and Biology. OFTs are flexible and versatile optotools based on fibers with one extremity patterned to form a micro-lens. These are able to focus laser beams and exert forces onto microparticles strong enough (piconewtons) to trap and manipulate them. In this paper, through an exploratory analysis of a 45 features set, including time and frequency-domain parameters of the back-scattered signal of particles trapped by a polymeric lens, we created a novel single feature able to differentiate synthetic particles (PMMA and Polystyrene) from living yeasts cells. This single statistical feature can be useful for the development of label-free hybrid optical fiber sensors with applications in infectious diseases detection or cells sorting. It can also contribute, by revealing the most significant information that can be extracted from the scattered signal, to the development of a simpler method for particles characterization (in terms of composition, heterogeneity degree) than existent technologies.

Neurophotonics: a comprehensive review, current challenges and future trends.

The human brain, with its vast network of billions of neurons and trillions of synapses (connections) between diverse cell types, remains one of the greatest mysteries in science and medicine. Despite extensive research, an understanding of the underlying mechanisms that drive normal behaviors and response to disease states is still limited. Advancement in the Neuroscience field and development of therapeutics for related pathologies requires innovative technologies that can provide a dynamic and systematic understanding of the interactions between neurons and neural circuits. In this work, we provide an up-to-date overview of the evolution of neurophotonic approaches in the last 10 years through a multi-source, literature analysis. From an initial corpus of 243 papers retrieved from Scopus, PubMed and WoS databases, we have followed the PRISMA approach to select 56 papers in the area. Following a full-text evaluation of these 56 scientific articles, six main areas of applied research were identified and discussed: (1) Advanced optogenetics, (2) Multimodal neural interfaces, (3) Innovative therapeutics, (4) Imaging devices and probes, (5) Remote operations, and (6) Microfluidic platforms. For each area, the main technologies selected are discussed according to the photonic principles applied, the neuroscience application evaluated and the more indicative results of efficiency and scientific potential. This detailed analysis is followed by an outlook of the main challenges tackled over the last 10 years in the Neurophotonics field, as well as the main technological advances regarding specificity, light delivery, multimodality, imaging, materials and system designs. We conclude with a discussion of considerable challenges for future innovation and translation in Neurophotonics, from light delivery within the brain to physical constraints and data management strategies.

The SWORD tele-rehabilitation system.

In spite of the growing interest verified in the field of technology-based interventions for Stroke rehabilitation, there is still no global solution that is both successful and suitable for a widespread use [1,2]. In this article, we present a novel tele-rehabilitation tool designed to be used for ambulatory patients, and developed towards the motor recovery of the patient's upper-limb. The SWORD system combines a movement quantification system that analyzes the quality of the motor task performed with a biofeedback console. The proposed structure defines the SWORD system as a complete tele-rehabilitation framework that enables a direct connection between clinical and ambulatory settings. Currently a randomized clinical trial is being designed in order to assess the effectiveness of the SWORD tele-rehabilitation system.

Involvement of the Anterior Nucleus of the Thalamus during Focal Automatisms in Epileptic Seizures: A First Evidence Study.

The Anterior Nucleus of Thalamus (ANT) Deep Brain Stimulation (DBS) has long been touted as the most effective DBS-target for interrupting seizures in focal refractory epilepsy patients. The ANT is primarily involved in cognitive tasks but has extensive reciprocal connections with motor-related regions, suggesting that it is also involved in motor-cognitive tasks. In this work, we aimed to assess the involvement of the ANT during voluntary upper limbs movements. For this purpose, we analyzed Local Field Potentials (LFPs) signals recorded during a movement protocol from one of the first epilepsy patients implanted with a Percept™ PC system, who performed a 5-day period of simultaneous video electroencephalography (vEEG) and Percept PC-LFPs recordings. We estimated time-frequency maps and performed event-related desynchronization (ERD) or synchronization (ERS) analysis and we found that synchronizations found in left hemisphere 7-17 Hz map corresponded to maximum hand rotations. Positive peaks on the ERD/ERS curve occurred at a similar frequency of the hand movements ([Formula: see text] against [Formula: see text]). These results suggested that the ANT may be involved in the execution of automatisms. Moreover, we found that ERD/ERS appeared approximately 2 seconds before the movement onset, as it was found on the EEG of healthy subjects performing the same protocol.

Autonomic correlates of attachment insecurity in a sample of women with eating disorders.

This study examined associations between attachment insecurity and autonomic response during the Adult Attachment Interview (AAI) in a sample of 47 women with eating disorders using a new system for the synchronous acquisition of behavioral and physiological data: the Bio Dual-channel and Representation of Attachment Multimedia System (BioDReAMS; Soares, Cunha, Zhan Jian Li, Pinho, & Neves, 1998). Consistent with the emerging literature on the psychophysiology of adult attachment, insecurity was positively correlated with electrodermal reactivity during the AAI. Furthermore, relatively secure patients showed some evidence of parasympathetic withdrawal, which can be conceptualized as evidence of more effective emotion regulation. Results suggest that, even among women with diagnosed psychopathology, security is associated with moreproductive patterns of psychophysiological response to attachment-related challenges.

Integration services to enable regional shared electronic health records.

eHealth is expected to integrate a comprehensive set of patient data sources into a coherent continuum, but implementations vary and Portugal is still lacking on electronic patient data sharing. In this work, we present a clinical information hub to aggregate multi-institution patient data and bridge the information silos. This integration platform enables a coherent object model, services-oriented applications development and a trust framework. It has been instantiated in the Rede Telemática de Saúde (www.RTSaude.org) to support a regional Electronic Health Record approach, fed dynamically from production systems at eight partner institutions, providing access to more than 11,000,000 care episodes, relating to over 350,000 citizens. The network has obtained the necessary clearance from the Portuguese data protection agency.

Author Correction: iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification.

With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due to alterations in fundamental cellular processes such as glycosylation. Glycans are involved in tumor cell biology and they have been considered to be suitable cancer biomarkers. Thus, more selective cancer screening assays can be developed through the detection of specific altered glycans on the surface of circulating cancer cells. Currently, this is only possible through time-consuming assays. In this work, we propose the "intelligent" Lab on Fiber (iLoF) device, that has a high-resolution, and which is a fast and portable method for tumor single-cell type identification and isolation. We apply an Artificial Intelligence approach to the back-scattered signal arising from a trapped cell by a micro-lensed optical fiber. As a proof of concept, we show that iLoF is able to discriminate two human cancer cell models sharing the same genetic background but displaying a different surface glycosylation profile with an accuracy above 90% and a speed rate of 2.3 seconds. We envision the incorporation of the iLoF in an easy-to-operate microchip for cancer identification, which would allow further biological characterization of the captured circulating live cells.

Optical fiber-based sensing method for nanoparticle detection through supervised back-scattering analysis: a potential contributor for biomedicine.

BACKGROUND: In view of the growing importance of nanotechnologies, the detection/identification of nanoparticles type has been considered of utmost importance. Although the characterization of synthetic/organic nanoparticles is currently considered a priority (eg, drug delivery devices, nanotextiles, theranostic nanoparticles), there are many examples of "naturally" generated nanostructures - for example, extracellular vesicles (EVs), lipoproteins, and virus - that provide useful information about human physiology or clinical conditions. For example, the detection of tumor-related exosomes, a specific type of EVs, in circulating fluids has been contributing to the diagnosis of cancer in an early stage. However, scientists have struggled to find a simple, fast, and low-cost method to accurately detect/identify these nanoparticles, since the majority of them have diameters between 100 and 150 nm, thus being far below the diffraction limit. METHODS: This study investigated if, by projecting the information provided from short-term portions of the back-scattered laser light signal collected by a polymeric lensed optical fiber tip dipped into a solution of synthetic nanoparticles into a lower features dimensional space, a discriminant function is able to correctly detect the presence of 100 nm synthetic nanoparticles in distilled water, in different concentration values. RESULTS AND DISCUSSION: This technique ensured an optimal performance (100% accuracy) in detecting nanoparticles for a concentration above or equal to 3.89 µg/mL (8.74E+10 particles/mL), and a performance of 90% for concentrations below this value and higher than 1.22E-03 µg/mL (2.74E+07 particles/mL), values that are compatible with human plasmatic levels of tumor-derived and other types of EVs, as well as lipoproteins currently used as potential biomarkers of cardiovascular diseases. CONCLUSION: The proposed technique is able to detect synthetic nanoparticles whose dimensions are similar to EVs and other "clinically" relevant nanostructures, and in concentrations equivalent to the majority of cell-derived, platelet-derived EVs and lipoproteins physiological levels. This study can, therefore, provide valuable insights towards the future development of a device for EVs and other biological nanoparticles detection with innovative characteristics.

Psychophysiological Stress Assessment Among On-Duty Firefighters.

Firefighting is a hazardous profession commonly exposed to high stress that can interfere with firefighter's health and performance. Nevertheless, on-duty stress levels quantitative evaluations are very rare in the literature. In order to investigate firefighters' occupational health in terms of stress perceptions, symptoms, and quantified physiological reactions under real-world conditions, an ambulatory assessment protocol was developed. Therefore, cardiac signal from firefighters ($N =6$) was continuously monitored during two shifts within a working week with a medical clinically certified equipment (VitalJacket®), allowing continuous electrocardiogram (ECG) and actigraphy measurement. Psychological data were collected with an android application, collecting potential stressful events, stress symptoms, and stress appraisal. A total of 130 hours of medical-quality ECG were collected, from which heart rate variability (HRV) metrics were extracted and analyzed. Statistical significant differences were found in some HRV metrics - AVNN, RMSSD, pNN50 and LF/HF - between events and non-events, showing higher levels of physiological stress during events (p<0.05). Stress symptoms increase from the beginning to the end of the shift (from 1.54 ± 0.52 to 2.01 ± 0.73), however the mean stress self-perception of events was very low (3.22 ± 2.38 in a scale ranging from 0 to 10). Negative and strong correlations were also found between stress symptoms and some time-domain ECG measures (AVNN, SDNN and pNN50). It can be concluded that stress may not always be detected when using merely self-reports. These results enhance the importance of combining both self-report and ambulatory high-quality physiological stress measures in occupational health settings. Future studies should investigate not only what causes stress but also its impact on health and well-being of these professionals, in order to contribute to the design of efficient stress-management interventions.

Beat-ID: Towards a computationally low-cost single heartbeat biometric identity check system based on electrocardiogram wave morphology.

In recent years, safer and more reliable biometric methods have been developed. Apart from the need for enhanced security, the media and entertainment sectors have also been applying biometrics in the emerging market of user-adaptable objects/systems to make these systems more user-friendly. However, the complexity of some state-of-the-art biometric systems (e.g., iris recognition) or their high false rejection rate (e.g., fingerprint recognition) is neither compatible with the simple hardware architecture required by reduced-size devices nor the new trend of implementing smart objects within the dynamic market of the Internet of Things (IoT). It was recently shown that an individual can be recognized by extracting features from their electrocardiogram (ECG). However, most current ECG-based biometric algorithms are computationally demanding and/or rely on relatively large (several seconds) ECG samples, which are incompatible with the aforementioned application fields. Here, we present a computationally low-cost method (patent pending), including simple mathematical operations, for identifying a person using only three ECG morphology-based characteristics from a single heartbeat. The algorithm was trained/tested using ECG signals of different duration from the Physionet database on more than 60 different training/test datasets. The proposed method achieved maximal averaged accuracy of 97.450% in distinguishing each subject from a ten-subject set and false acceptance and rejection rates (FAR and FRR) of 5.710±1.900% and 3.440±1.980%, respectively, placing Beat-ID in a very competitive position in terms of the FRR/FAR among state-of-the-art methods. Furthermore, the proposed method can identify a person using an average of 1.020 heartbeats. It therefore has FRR/FAR behavior similar to obtaining a fingerprint, yet it is simpler and requires less expensive hardware. This method targets low-computational/energy-cost scenarios, such as tiny wearable devices (e.g., a smart object that automatically adapts its configuration to the user). A hardware proof-of-concept implementation is presented as an annex to this paper.

Heart rate variability metrics for fine-grained stress level assessment.

BACKGROUND AND OBJECTIVES: In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window. METHODS: The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital JacketTM while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way. RESULTS: A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis. CONCLUSIONS: The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.

Towards a movement quantification system capable of automatic evaluation of upper limb motor function after neurological injury.

The paper proposes an integrated system to automatically assess motor function after neurological injury. A portable motion capture system was developed in order to obtain all the relevant three dimensional kinematics of the upper limb movement. These kinematics were analyzed by means of a decision tree classifier which features where inferred from the Functional Ability Score (FAS) of the Wolf Motor Function Test (WMFT). In addition, the system is able to correctly quantify the performance time of each selected task of the WMFT. In terms of the FAS the system and the clinician show coherent results for 3 out of 5 patients in the first task tested and 4 out of 5 for the second task tested. Regarding performance time, the mean error between the system and the clinician was of 0.216 s for the 25 trials performed (5 patients, 5 tasks each). These results represent an important proof of concept towards a system capable of precisely evaluate upper limb motor function after neurological injury.