The Role of Virtual Reality and Artificial Intelligence in Cognitive Pain Therapy: A Narrative Review.

PURPOSE OF REVIEW: This review investigates the roles of artificial intelligence (AI) and virtual reality (VR) in enhancing cognitive pain therapy for chronic pain management. The work assesses current research, outlines benefits and limitations and examines their potential integration into existing pain management methods. RECENT FINDINGS: Advances in VR have shown promise in chronic pain management through immersive cognitive therapy exercises, with evidence supporting VR's effectiveness in symptom reduction. AI's personalization of treatment plans and its support for mental health through AI-driven avatars are emerging trends. The integration of AI in hybrid programs indicates a future with real-time adaptive technology tailored to individual needs in chronic pain management. Incorporating AI and VR into chronic pain cognitive therapy represents a promising approach to enhance management by leveraging VR's immersive experiences and AI's personalized tactics, aiming to improve patient engagement and outcomes. Nonetheless, further empirical studies are needed to standardized methodologies, compare these technologies to traditional therapies and fully realize their clinical potential.

Solutions of the Lippmann-Schwinger equation for confocal parabolic billiards.

We present analytical and numerical solutions of the Lippmann-Schwinger equation for the scattered wave functions generated by confocal parabolic billiards and parabolic segments with various δ-type potential-strength functions. The analytical expressions are expressed as summations of products of parabolic cylinder functions D_{m}. We numerically investigate the resonances and tunneling in the confocal parabolic billiards by employing an accurate boundary wall method that provides a complete inside-outside picture. The criterion for discretizing the parabolic sides of the billiard is explained in detail. We discuss the phenomenon of transparency at certain eigenenergies.

Quantum states resembling classical periodic trajectories in mesoscopic elliptic billiards.

A quantum wave function with localization on classical periodic orbits in a mesoscopic elliptic billiard has been achieved by appropriately superposing nearly degenerate eigenstates expressed as products of Mathieu functions. We analyze and discuss the rotational and librational regimes of motion in the elliptic billiard. Simplified line equations corresponding to the classical trajectories can be extracted from the quantum state as an integral equation involving angular Mathieu functions. The phase factors appearing in the integrals are connected to the classical initial positions and velocity components. We analyze the probability current density, phase maps, and vortex distributions of the periodic orbit quantum states for both rotational and librational motions; furthermore, they may represent traveling and standing trajectories inside the elliptic billiard.

A Gamma-adapted subunit vaccine induces broadly neutralizing antibodies against SARS-CoV-2 variants and protects mice from infection.

In the context of continuous emergence of SARS-CoV-2 variants of concern (VOCs), one strategy to prevent the severe outcomes of COVID-19 is developing safe and effective broad-spectrum vaccines. Here, we present preclinical studies of a RBD vaccine derived from the Gamma SARS-CoV-2 variant adjuvanted with Alum. The Gamma-adapted RBD vaccine is more immunogenic than the Ancestral RBD vaccine in terms of inducing broader neutralizing antibodies. The Gamma RBD presents more immunogenic B-cell restricted epitopes and induces a higher proportion of specific-B cells and plasmablasts than the Ancestral RBD version. The Gamma-adapted vaccine induces antigen specific T cell immune responses and confers protection against Ancestral and Omicron BA.5 SARS-CoV-2 challenge in mice. Moreover, the Gamma RBD vaccine induces higher and broader neutralizing antibody activity than homologous booster vaccination in mice previously primed with different SARS-CoV-2 vaccine platforms. Our study indicates that the adjuvanted Gamma RBD vaccine is highly immunogenic and a broad-spectrum vaccine candidate.

Streamlines and topological transformation of modified vector Bessel-Gauss beams.

We characterize the streamline patterns of the transverse electric (TE) and transverse magnetic (TM) modes of the vector-modified Bessel-Gauss (BG) beam, which is the Fourier-transformed version of the ordinary BG beam. We derive analytical expressions to approximate the streamline patterns produced by the superposition of TM and TE modes. An analysis of the effect on the streamlines of the vector BG beams produced by some polarization devices, e.g., linear retarders and spiral polarizers, is presented. Additionally, we study the geometrical phase induced by linear retarders into the TM mode of the field. This work contributes to the description and understanding of the vector structure of the focal field of Bessel-Gauss beams.

Patient and Physician Perspectives on the Use of a Connected Ecosystem for Diabetes Management: International Cross-Sectional Observational Study.

BACKGROUND: Collaboration between people with type 2 diabetes (T2DM) and their health care teams is important for optimal control of the disease and outcomes. Digital technologies could potentially tie together several health care-related devices and platforms into connected ecosystems (CES), but attitudes about CES are unknown. OBJECTIVE: We surveyed convenience samples of patients and physicians to better understand which patient characteristics are associated with higher likelihoods of (1) participating in a potential CES program, as self-reported by patients with T2DM and (2) clinical benefit from participation in a potential CES program, as reported by physicians. METHODS: Adults self-reporting a diagnosis of T2DM and current insulin use (n=197), and 33 physicians whose practices included ≥20% of such patients, were enrolled in the United States, France, and Germany. We surveyed both groups about the likelihood of patient participation in a CES. We then examined the associations between patients' clinical and sociodemographic characteristics and this likelihood. We also described characteristics of patients likely to clinically benefit from CES use, according to physicians. RESULTS: Compared with patients in Germany and France, US patients were younger (mean age 45.3 [SD 11.9] years vs 61.9 [SD 9.2] and 65.8 [SD 9.4] years, respectively), more often female, more highly educated, and more often working full-time. In all, 51 (44.7%) US patients, 16 (36.4%) German patients, and 18 (46.3%) French patients indicated strong interest in a CES program, and 115 (78.7%) reported currently using ≥1 connected device or app. However, physicians believed that only 11.3%-19.2% of their patients were using connected devices or apps to manage their disease. Physicians also reported infrequently recommending or prescribing connected devices to their patients, although ≥80% (n=28) of them thought that a CES could help support their patients in managing their disease. The factors most predictive of patient likelihood of participating in a CES program were cost, inclusion of medication reminders, and linking blood glucose levels to behaviors such as eating and exercise. In all countries, the most common patient expectations for a CES program were that it could help them eat more healthfully, increase their physical activity, increase their understanding of how blood glucose relates to behavior such as exercise and eating, and reduce stress. Physicians thought that newly diagnosed patients, sicker patients-those who had been hospitalized for diabetes, were currently using insulin, or who had any comorbid condition-and patients who were nonadherent to treatment were most likely to benefit from CES use. CONCLUSIONS: In this study, there was a high degree of interest in the future use of CES, although additional education is needed among both patients with T2DM and their physicians to achieve the full potential of such systems to improve self-management and clinical care for the disease.

Elliptic billiard with harmonic potential: Classical description.

The classical dynamics of the isotropic two-dimensional harmonic oscillator confined by an elliptic hard wall is discussed. The interplay between the harmonic potential with circular symmetry and the boundary with elliptical symmetry does not spoil the separability in elliptic coordinates; however, it generates nontrivial energy and momentum dependencies in the billiard. We analyze the equimomentum surfaces in the parameter space and classify the kinds of motion the particle can have in the billiard. The winding numbers and periods of the rotational and librational trajectories are analytically calculated and numerically verified. A remarkable finding is the possibility of having degenerate rotational trajectories with the same energy but different second constant of motion and different caustics and periods. The conditions to get these degenerate trajectories are analyzed. Similarly, we show that obtaining two different rotational trajectories with the same period and second constant of motion but different energy is possible.

Safety and immunogenicity of a SARS-CoV-2 Gamma variant RBD-based protein adjuvanted vaccine used as booster in healthy adults.

A Gamma Variant RBD-based aluminum hydroxide adjuvanted vaccine called ARVAC CG was selected for a first in human clinical trial. Healthy male and female participants (18-55 years old) with a complete COVID-19-primary vaccine scheme were assigned to receive two intramuscular doses of either a low-dose or a high-dose of ARVAC CG. The primary endpoint was safety. The secondary objective was humoral immunogenicity. Cellular immune responses were studied as an exploratory objective. The trial was prospectively registered in PRIISA.BA (Registration Code 6564) and ANMAT and retrospectively registered in ClinicalTrials.gov (NCT05656508). Samples from participants of a surveillance strategy implemented by the Ministry of Health of the Province of Buenos Aires that were boosted with BNT162b2 were also analyzed to compare with the booster effect of ARVAC CG. ARVAC CG exhibits a satisfactory safety profile, a robust and broad booster response of neutralizing antibodies against the Ancestral strain of SARS-CoV-2 and the Gamma, Delta, Omicron BA.1 and Omicron BA.5 variants of concern and a booster effect on T cell immunity in individuals previously immunized with different COVID-19 vaccine platforms.

A Real-Time Mobile Intervention to Reduce Sedentary Behavior Before and After Cancer Surgery: Pilot Randomized Controlled Trial.

BACKGROUND: Sedentary behavior (SB) is prevalent after abdominal cancer surgery, and interventions targeting perioperative SB could improve postoperative recovery and outcomes. We conducted a pilot study to evaluate the feasibility and preliminary effects of a real-time mobile intervention that detects and disrupts prolonged SB before and after cancer surgery, relative to a monitoring-only control condition. OBJECTIVE: Our aim was to evaluate the feasibility and preliminary effects of a perioperative SB intervention on objective activity behavior, patient-reported quality of life and symptoms, and 30-day readmissions. METHODS: Patients scheduled for surgery for metastatic gastrointestinal cancer (n=26) were enrolled and randomized to receive either the SB intervention or activity monitoring only. Both groups used a Fitbit smartwatch and companion smartphone app to rate daily symptoms and collect continuous objective activity behavior data starting from at least 10 days before surgery through 30 days post discharge. Participants in the intervention group also received prompts to walk after any SB bout that exceeded a prespecified threshold, with less frequent prompts on days that patients reported more severe symptoms. Participants completed end-of-study ratings of acceptability, and we also examined adherence to assessments and to walking prompts. In addition, we examined effects of the intervention on objective SB and step counts, patient-reported quality of life and depressive and physical symptoms, as well as readmissions. RESULTS: Accrual (74%), retention (88%), and acceptability ratings (mean overall satisfaction 88.5/100, SD 9.1) were relatively high. However, adherence to assessments and engagement with the SB intervention decreased significantly after surgery and did not recover to preoperative levels after postoperative discharge. All participants exhibited significant increases in SB and symptoms and decreases in steps and quality of life after surgery, and participants randomized to the SB intervention unexpectedly had longer maximum SB bouts relative to the control group. No significant benefits of the intervention with regard to activity, quality of life, symptoms, or readmission were observed. CONCLUSIONS: Perioperative patients with metastatic gastrointestinal cancer were interested in a real-time SB intervention and rated the intervention as highly acceptable, but engagement with the intervention and with daily symptom and activity monitoring decreased significantly after surgery. There were no significant effects of the intervention on step counts, patient-reported quality of life or symptoms, and postoperative readmissions, and there was an apparent adverse effect on maximum SB. Results highlight the need for additional work to modify the intervention to make reducing SB and engaging with mobile health technology after abdominal cancer surgery more feasible and beneficial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03211806; https://tinyurl.com/3napwkkt.

A Wearable Vibratory Device (The Emma Watch) to Address Action Tremor in Parkinson Disease: Pilot Feasibility Study.

BACKGROUND: Parkinson disease (PD) is a neurodegenerative disease that has a wide range of motor symptoms, such as tremor. Tremors are involuntary movements that occur in rhythmic oscillations and are typically categorized into rest tremor or action tremor. Action tremor occurs during voluntary movements and is a debilitating symptom of PD. As noninvasive interventions are limited, there is an ever-increasing need for an effective intervention for individuals experiencing action tremors. The Microsoft Emma Watch, a wristband with 5 vibrating motors, is a noninvasive, nonpharmaceutical intervention for tremor attenuation. OBJECTIVE: This pilot study investigated the use of the Emma Watch device to attenuate action tremor in people with PD. METHODS: The sample included 9 people with PD who were assessed on handwriting and hand function tasks performed on a digitized tablet. Tasks included drawing horizontal or vertical lines, tracing a star, spiral, writing "elelelel" in cursive, and printing a standardized sentence. Each task was completed 3 times with the Emma Watch programmed at different vibration intensities, which were counterbalanced: high intensity, low intensity (sham), and no vibration. Digital analysis from the tablet captured kinematic, dynamic, and spatial attributes of drawing and writing samples to calculate mathematical indices that quantify upper limb motor function. APDM Opal sensors (APDM Wearable Technologies) placed on both wrists were used to calculate metrics of acceleration and jerk. A questionnaire was provided to each participant after using the Emma Watch to gain a better understanding of their perspectives of using the device. In addition, drawings were compared to determine whether there were any visual differences between intensities. RESULTS: In total, 9 people with PD were tested: 4 males and 5 females with a mean age of 67 (SD 9.4) years. There were no differences between conditions in the outcomes of interest measured with the tablet (duration, mean velocity, number of peaks, pause time, and number of pauses). Visual differences were observed within a small subset of participants, some of whom reported perceived improvement. The majority of participants (8/9) reported the Emma Watch was comfortable, and no problems with the device were reported. CONCLUSIONS: There were visually depicted and subjectively reported improvements in handwriting for a small subset of individuals. This pilot study was limited by a small sample size, and this should be taken into consideration with the interpretation of the quantitative results. Combining vibratory devices, such as the Emma Watch, with task specific training, or personalizing the frequency to one's individual tremor may be important steps to consider when evaluating the effect of vibratory devices on hand function or writing ability in future studies. While the Emma Watch may help attenuate action tremor, its efficacy in improving fine motor or handwriting skills as a stand-alone tool remains to be demonstrated.

Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials.

Background: The proliferation and increasing maturity of biometric monitoring technologies allow clinical investigators to measure the health status of trial participants in a more holistic manner, especially outside of traditional clinical settings. This includes capturing meaningful aspects of health in daily living and a more granular and objective manner compared to traditional tools in clinical settings. Summary: Within multidisciplinary teams, statisticians and data scientists are increasingly involved in clinical trials that incorporate digital clinical measures. They are called upon to provide input into trial planning, generation of evidence on the clinical validity of novel clinical measures, and evaluation of the adequacy of existing evidence. Analysis objectives related to demonstrating clinical validity of novel clinical measures differ from typical objectives related to demonstrating safety and efficacy of therapeutic interventions using established measures which statisticians are most familiar with. Key Messages: This paper discusses key considerations for generating evidence for clinical validity through the lens of the type and intended use of a clinical measure. This paper also briefly discusses the regulatory pathways through which clinical validity evidence may be reviewed and highlights challenges that investigators may encounter while dealing with data from biometric monitoring technologies.

The impact of the COVID-19 pandemic on the oncology services demand in a middle-income setting with universal health insurance.

Aim: We analyze the impact of the COVID-19 pandemic on oncology service demand in a middle-income country with universal health coverage. Methods: We collected data from January 1st-2017 to December 31th-2021 at a reference center in Bogotá-Colombia regarding first-time consultations of cross-cutting services (clinical oncology, hematology, palliative care, radiation oncology); specialized multidisciplinary units (breast, prostate, lung, stomach); inpatient and outpatient systemic therapy; radiotherapy; oncology surgery; and bone marrow transplant. A descriptive time series analysis was performed, estimating monthly percent change and endemic channels. Results: Starting the confinement (April 2020), a general decrease in service demand was observed (R: -14.9% to -90.0%), with an additional but lower decrease in August 2020 coinciding with the first pandemic wave (R: -11.3% to -70.0%). Follow-up visits and ambulatory treatment showed no consistent reductions. New patients' consultations for cross-cutting services had a speedy recovery (1 month), but clinical oncology, specialized units, and in-hospital treatment resumed more slowly. Only breast and stomach cancer showed a sustained reduction in early-stage disease. Women and older patients had a more significant reductionin service demand. Conclusion: Despite no changes in service supply, the confinement induced a significant reduction in service demand. Variations by cancer type, service type, and population demographics deserve careful consideration for a suitable response to the emergency. The speedy recovery and the absence of a significant decrease during subsequent waves of the pandemic suggest patient resiliency and a lower impact than expected in middle-income settings in the presence of universal health insurance.

Objetivo: Analizar el impacto de la pandemia de COVID-19 sobre la demanda de servicios oncológicos. Metodos: Se recolectaron datos de enero 1/2017 hasta diciembre 31/2021 de consulta de primera vez en servicios transversales (oncología clinica, hematología, cuidados paliativos, oncología radioterápica) y servicios especializados multidisciplinarios (mama, próstata, pulmón, estómago), así como de suministro de tratamiento (terapia sistémica ambulatoria y hospitalaria, radioterapia, cirugía oncológica, trasplante de médula ósea), en un centro de referencia en Bogotá-Colombia. Se realizó un análisis descriptivo de series de tiempo estimando el cambio porcentual mensual y los canales endémicos. Resultados: Al inicio del confinamiento obligatorio (abril/2020) hubo una disminución general en la demanda de servicios transversales (R: -14.9% a -90.0%), con nuevo descenso de menor grado en agosto/2020 durante la primera ola de infecciones (R: -11.3% a -70.0%). Las consultas de seguimiento y tratamientos ambulatorios no mostraron reducciones consistentes. Exceptuando oncología clínica, las consultas de primera vez para servicios transversales tuvieron rápida recuperación hasta cifras basales (1 mes), pero las unidades especializadas y los tratamientos intrahospitalarios tuvieron recuperación mas lenta. Únicamente los cánceres de mama y estómago mostraron una reduccion sostenida de estadios tempranos de la enfermedad. La reducción de la demanda fue mas marcada en mujeres y adultos mayores. Conclusión: A pesar de no tener cambios en la oferta, el confinamiento indujo una reducción significativa en la demanda de servicios oncológicos con variación diferencial por tipo de cáncer, servicio y características demográficas de la población. Esto merece consideración especial para generar respuestas adecuadas a las emergencias sanitarias. La rápida recuperación de la demanda y la ausencia de caídas en olas de infección subsiguientes sugieren resiliencia de los pacientes e impacto menor del esperado en países con cobertura de salud universal.

Continuous-Time Modeling of the Bidirectional Relationship Between Incidental Affect and Physical Activity.

BACKGROUND: Previous research suggests that there is a bidirectional relationship between incidental affect (i.e., how people feel in day-to-day life) and physical activity behavior. However, many inconsistencies exist in the body of work due to the lag interval between affect and physical activity measurements. PURPOSE: Using a novel continuous-time analysis paradigm, we examined the temporal specificity underlying the dynamic relationship between positive and negative incidental affective states and moderate-to-vigorous physical activity (MVPA). METHODS: A community sample of adults (n = 126, Mage = 27.71, 51.6% Male) completed a 14-day ambulatory assessment protocol measuring momentary positive and negative incidental affect six times a day while wearing a physical activity monitor (Fitbit). Hierarchical Bayesian continuous-time structural equation modeling was used to elucidate the underlying dynamics of the relationship between incidental affective states and MVPA. RESULTS: Based on the continuous-time cross-effects, positive and negative incidental affect predicted subsequent MVPA. Furthermore, engaging in MVPA predicted subsequent positive and negative incidental affect. Incidental affective states had a greater relative influence on predicting subsequent MVPA compared to the reciprocal relationship. Analysis of the discrete-time coefficients suggests that cross-lagged effects increase as the time interval between measurements increase, peaking at about 8 h between measurement occasions before beginning to dissipate. CONCLUSIONS: The results provide support for a recursive relationship between incidental affective states and MVPA, which is particularly strong at 7-9 hr time intervals. Future research designs should consider these medium-term dynamics, for both theory development and intervention.

The impact of the COVID-19 pandemic on the oncology services demand in a middle-income setting with universal health insurance / Impacto de la pandemia de COVID-19 sobre la demanda de servicios oncológicos en un país de medianos ingresos con cobertura de salud universal

Abstract Aim: We analyze the impact of the COVID-19 pandemic on oncology service demand in a middle-income country with universal health coverage. Methods: We collected data from January 1st-2017 to December 31th-2021 at a reference center in Bogotá-Colombia regarding first-time consultations of cross-cutting services (clinical oncology, hematology, palliative care, radiation oncology); specialized multidisciplinary units (breast, prostate, lung, stomach); inpatient and outpatient systemic therapy; radiotherapy; oncology surgery; and bone marrow transplant. A descriptive time series analysis was performed, estimating monthly percent change and endemic channels. Results: Starting the confinement (April 2020), a general decrease in service demand was observed (R: -14.9% to -90.0%), with an additional but lower decrease in August 2020 coinciding with the first pandemic wave (R: -11.3% to -70.0%). Follow-up visits and ambulatory treatment showed no consistent reductions. New patients' consultations for cross-cutting services had a speedy recovery (1 month), but clinical oncology, specialized units, and in-hospital treatment resumed more slowly. Only breast and stomach cancer showed a sustained reduction in early-stage disease. Women and older patients had a more significant reductionin service demand. Conclusion: Despite no changes in service supply, the confinement induced a significant reduction in service demand. Variations by cancer type, service type, and population demographics deserve careful consideration for a suitable response to the emergency. The speedy recovery and the absence of a significant decrease during subsequent waves of the pandemic suggest patient resiliency and a lower impact than expected in middle-income settings in the presence of universal health insurance.

Resumen Objetivo: Analizar el impacto de la pandemia de COVID-19 sobre la demanda de servicios oncológicos. Metodos: Se recolectaron datos de enero 1/2017 hasta diciembre 31/2021 de consulta de primera vez en servicios transversales (oncología clinica, hematología, cuidados paliativos, oncología radioterápica) y servicios especializados multidisciplinarios (mama, próstata, pulmón, estómago), así como de suministro de tratamiento (terapia sistémica ambulatoria y hospitalaria, radioterapia, cirugía oncológica, trasplante de médula ósea), en un centro de referencia en Bogotá-Colombia. Se realizó un análisis descriptivo de series de tiempo estimando el cambio porcentual mensual y los canales endémicos. Resultados: Al inicio del confinamiento obligatorio (abril/2020) hubo una disminución general en la demanda de servicios transversales (R: -14.9% a -90.0%), con nuevo descenso de menor grado en agosto/2020 durante la primera ola de infecciones (R: -11.3% a -70.0%). Las consultas de seguimiento y tratamientos ambulatorios no mostraron reducciones consistentes. Exceptuando oncología clínica, las consultas de primera vez para servicios transversales tuvieron rápida recuperación hasta cifras basales (1 mes), pero las unidades especializadas y los tratamientos intrahospitalarios tuvieron recuperación mas lenta. Únicamente los cánceres de mama y estómago mostraron una reduccion sostenida de estadios tempranos de la enfermedad. La reducción de la demanda fue mas marcada en mujeres y adultos mayores. Conclusión: A pesar de no tener cambios en la oferta, el confinamiento indujo una reducción significativa en la demanda de servicios oncológicos con variación diferencial por tipo de cáncer, servicio y características demográficas de la población. Esto merece consideración especial para generar respuestas adecuadas a las emergencias sanitarias. La rápida recuperación de la demanda y la ausencia de caídas en olas de infección subsiguientes sugieren resiliencia de los pacientes e impacto menor del esperado en países con cobertura de salud universal.

Higher Adherence to ERAS Society® Recommendations is Associated with Shorter Hospital Stay Without an Increase in Postoperative Complications or Readmissions in Bariatric Surgery: the Association Between Use of Enhanced Recovery After Surgery Protocols and Postoperative Complications after Bariatric Surgery (POWER 3) Multicenter Observational Study.

PURPOSE: The effectiveness of enhanced recovery after surgery (ERAS) pathways in patients undergoing bariatric surgery remains unclear. Our objective was to determine the effect of the ERAS elements on patient outcomes following elective bariatric surgery. MATERIALS AND METHODS: Prospective cohort study in adult patients undergoing elective bariatric surgery. Each participating center selected a single 3-month data collection period between October 2019 and September 2020. We assessed the 24 individual components of the ERAS pathways in all patients. We used a multivariable and multilevel logistic regression model to adjust for baseline risk factors, ERAS elements, and center differences RESULTS: We included 1419 patients. One hundred and fourteen patients (8%) developed postoperative complications. There were no differences in the incidence of overall postoperative complications between the self-designated ERAS and non-ERAS groups (54 (8.7%) vs. 60 (7.6%); OR, 1.14; 95% CI, 0.73-1.79; P = .56), neither for moderate-to-severe complications, readmissions, re-interventions, mortality, or hospital stay (2 [IQR 2-3] vs. 3 [IQR 2-4] days, 0.85; 95% CI, 0.62-1.17; P = .33) Adherence to the ERAS elements in the highest adherence quartile (Q1) was greater than 72.2%, while in the lowest adherence quartile (Q4) it was less than 55%. Patients with the highest adherence rates had shorter hospital stay (2 [IQR 2-3] vs. 3 [IQR 2-4] days, 1.54; 95% CI, 1.09-2.17; P = .015), while there were no differences in the other outcomes CONCLUSIONS: Higher adherence to ERAS Society® recommendations was associated with a shorter hospital stay without an increase in postoperative complications or readmissions. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03864861.

Detecting Mental Health Behaviors Using Mobile Interactions: Exploratory Study Focusing on Binge Eating.

BACKGROUND: Binge eating is a subjective loss of control while eating, which leads to the consumption of large amounts of food. It can cause significant emotional distress and is often accompanied by purging behaviors (eg, meal skipping, overexercising, or vomiting). OBJECTIVE: The aim of this study was to explore the potential of mobile sensing to detect indicators of binge-eating episodes, with a view toward informing the design of future context-aware mobile interventions. METHODS: This study was conducted in 2 stages. The first involved the development of the DeMMI (Detecting Mental health behaviors using Mobile Interactions) app. As part of this, we conducted a consultation session to explore whether the types of sensor data we were proposing to capture were useful and appropriate, as well as to gather feedback on some specific app features relating to self-reporting. The second stage involved conducting a 6-week period of data collection with 10 participants experiencing binge eating (logging both their mood and episodes of binge eating) and 10 comparison participants (logging only mood). An optional interview was conducted after the study, which discussed their experience using the app, and 8 participants (n=3, 38% binge eating and n=5, 63% comparisons) consented. RESULTS: The findings showed unique differences in the types of sensor data that were triangulated with the individuals' episodes (with nearby Bluetooth devices, screen and app use features, mobility features, and mood scores showing relevance). Participants had a largely positive opinion about the app, its unobtrusive role, and its ease of use. Interacting with the app increased participants' awareness of and reflection on their mood and phone usage patterns. Moreover, they expressed no privacy concerns as these were alleviated by the study information sheet. CONCLUSIONS: This study contributes a series of recommendations for future studies wishing to scale our approach and for the design of bespoke mobile interventions to support this population.

Reproducible Analysis Pipeline for Data Streams: Open-Source Software to Process Data Collected With Mobile Devices.

Smartphone and wearable devices are widely used in behavioral and clinical research to collect longitudinal data that, along with ground truth data, are used to create models of human behavior. Mobile sensing researchers often program data processing and analysis code from scratch even though many research teams collect data from similar mobile sensors, platforms, and devices. This leads to significant inefficiency in not being able to replicate and build on others' work, inconsistency in quality of code and results, and lack of transparency when code is not shared alongside publications. We provide an overview of Reproducible Analysis Pipeline for Data Streams (RAPIDS), a reproducible pipeline to standardize the preprocessing, feature extraction, analysis, visualization, and reporting of data streams coming from mobile sensors. RAPIDS is formed by a group of R and Python scripts that are executed on top of reproducible virtual environments, orchestrated by a workflow management system, and organized following a consistent file structure for data science projects. We share open source, documented, extensible and tested code to preprocess, extract, and visualize behavioral features from data collected with any Android or iOS smartphone sensing app as well as Fitbit and Empatica wearable devices. RAPIDS allows researchers to process mobile sensor data in a rigorous and reproducible way. This saves time and effort during the data analysis phase of a project and facilitates sharing analysis workflows alongside publications.

Iota-carrageenan and xylitol inhibit SARS-CoV-2 in Vero cell culture.

Last year observed a global pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome-coronavirus 2) infection affecting millions of individuals worldwide. There is an urgent unmet need to provide an easily producible and affordable medicine to prevent transmission and provide early treatment for this disease. Since the nasal cavity and the rhinopharynx are the sites of initial replication of SARS-CoV-2, a nasal spray may be an effective option to target SARS-CoV-2 infection. In this study, we tested the antiviral action of three candidate nasal spray formulations against SARS-CoV-2 in vitro. We determined that iota-carrageenan in concentrations as low as 6 µg/mL inhibits SARS-CoV-2 in vitro. The concentrations of iota-carrageenan with activity against SARS-CoV-2 in vitro may be easily achieved through the application of nasal sprays as commonly used in several countries. Recently a double-blind, placebo-controlled study showed that iota-carrageenan in isotonic sodium chloride reduces ca. five times the risk of infection by SARS-CoV-2 in health care personnel. Further, xylitol at a concentration of 50 mg/mL (ca. 329 mM) was found to exert some antiviral action, though this preliminary finding needs further confirmation.

Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study.

BACKGROUND: Depression is a prevalent mental health challenge. Current depression assessment methods using self-reported and clinician-administered questionnaires have limitations. Instrumenting smartphones to passively and continuously collect moment-by-moment data sets to quantify human behaviors has the potential to augment current depression assessment methods for early diagnosis, scalable, and longitudinal monitoring of depression. OBJECTIVE: The objective of this study was to investigate the feasibility of predicting depression with human behaviors quantified from smartphone data sets, and to identify behaviors that can influence depression. METHODS: Smartphone data sets and self-reported 8-item Patient Health Questionnaire (PHQ-8) depression assessments were collected from 629 participants in an exploratory longitudinal study over an average of 22.1 days (SD 17.90; range 8-86). We quantified 22 regularity, entropy, and SD behavioral markers from the smartphone data. We explored the relationship between the behavioral features and depression using correlation and bivariate linear mixed models (LMMs). We leveraged 5 supervised machine learning (ML) algorithms with hyperparameter optimization, nested cross-validation, and imbalanced data handling to predict depression. Finally, with the permutation importance method, we identified influential behavioral markers in predicting depression. RESULTS: Of the 629 participants from at least 56 countries, 69 (10.97%) were females, 546 (86.8%) were males, and 14 (2.2%) were nonbinary. Participants' age distribution is as follows: 73/629 (11.6%) were aged between 18 and 24, 204/629 (32.4%) were aged between 25 and 34, 156/629 (24.8%) were aged between 35 and 44, 166/629 (26.4%) were aged between 45 and 64, and 30/629 (4.8%) were aged 65 years and over. Of the 1374 PHQ-8 assessments, 1143 (83.19%) responses were nondepressed scores (PHQ-8 score <10), while 231 (16.81%) were depressed scores (PHQ-8 score ≥10), as identified based on PHQ-8 cut-off. A significant positive Pearson correlation was found between screen status-normalized entropy and depression (r=0.14, P<.001). LMM demonstrates an intraclass correlation of 0.7584 and a significant positive association between screen status-normalized entropy and depression (ß=.48, P=.03). The best ML algorithms achieved the following metrics: precision, 85.55%-92.51%; recall, 92.19%-95.56%; F1, 88.73%-94.00%; area under the curve receiver operating characteristic, 94.69%-99.06%; Cohen κ, 86.61%-92.90%; and accuracy, 96.44%-98.14%. Including age group and gender as predictors improved the ML performances. Screen and internet connectivity features were the most influential in predicting depression. CONCLUSIONS: Our findings demonstrate that behavioral markers indicative of depression can be unobtrusively identified from smartphone sensors' data. Traditional assessment of depression can be augmented with behavioral markers from smartphones for depression diagnosis and monitoring.

Digital Biomarkers of Symptom Burden Self-Reported by Perioperative Patients Undergoing Pancreatic Surgery: Prospective Longitudinal Study.

BACKGROUND: Cancer treatments can cause a variety of symptoms that impair quality of life and functioning but are frequently missed by clinicians. Smartphone and wearable sensors may capture behavioral and physiological changes indicative of symptom burden, enabling passive and remote real-time monitoring of fluctuating symptoms. OBJECTIVE: The aim of this study was to examine whether smartphone and Fitbit data could be used to estimate daily symptom burden before and after pancreatic surgery. METHODS: A total of 44 patients scheduled for pancreatic surgery participated in this prospective longitudinal study and provided sufficient sensor and self-reported symptom data for analyses. Participants collected smartphone sensor and Fitbit data and completed daily symptom ratings starting at least two weeks before surgery, throughout their inpatient recovery, and for up to 60 days after postoperative discharge. Day-level behavioral features reflecting mobility and activity patterns, sleep, screen time, heart rate, and communication were extracted from raw smartphone and Fitbit data and used to classify the next day as high or low symptom burden, adjusted for each individual's typical level of reported symptoms. In addition to the overall symptom burden, we examined pain, fatigue, and diarrhea specifically. RESULTS: Models using light gradient boosting machine (LightGBM) were able to correctly predict whether the next day would be a high symptom day with 73.5% accuracy, surpassing baseline models. The most important sensor features for discriminating high symptom days were related to physical activity bouts, sleep, heart rate, and location. LightGBM models predicting next-day diarrhea (79.0% accuracy), fatigue (75.8% accuracy), and pain (79.6% accuracy) performed similarly. CONCLUSIONS: Results suggest that digital biomarkers may be useful in predicting patient-reported symptom burden before and after cancer surgery. Although model performance in this small sample may not be adequate for clinical implementation, findings support the feasibility of collecting mobile sensor data from older patients who are acutely ill as well as the potential clinical value of mobile sensing for passive monitoring of patients with cancer and suggest that data from devices that many patients already own and use may be useful in detecting worsening perioperative symptoms and triggering just-in-time symptom management interventions.