Consensus protocol for management of early and late twin-twin transfusion syndrome: Delphi study.

OBJECTIVE: Fetoscopic laser photocoagulation (FLP) is a well-established treatment for twin-twin transfusion syndrome (TTTS) between 16 and 26 weeks' gestation. High-quality evidence and guidelines regarding the optimal clinical management of very early (prior to 16 weeks), early (between 16 and 18 weeks) and late (after 26 weeks) TTTS are lacking. The aim of this study was to construct a structured expert-based clinical consensus for the management of early and late TTTS. METHODS: A Delphi procedure was conducted among an international panel of experts. Participants were chosen based on their clinical expertise, affiliation and relevant publications. A four-round Delphi survey was conducted using an online platform and responses were collected anonymously. In the first round, a core group of experts was asked to answer open-ended questions regarding the indications, timing and modes of treatment for early and late TTTS. In the second and third rounds, participants were asked to grade each statement on a Likert scale (1, completely disagree; 5, completely agree) and to add any suggestions or modifications. At the end of each round, the median score for each statement was calculated. Statements with a median grade of 5 without suggestions for change were accepted as the consensus. Statements with a median grade of 3 or less were excluded from the Delphi process. Statements with a median grade of 4 were modified according to suggestions and reconsidered in the next round. In the last round, participants were asked to agree or disagree with the statements, and those with more than 70% agreement without suggestions for change were considered the consensus. RESULTS: A total of 122 experts met the inclusion criteria and were invited to participate, of whom 53 (43.4%) agreed to take part in the study. Of those, 75.5% completed all four rounds. A consensus on the optimal management of early and late TTTS was obtained. FLP can be offered as early as 15 weeks' gestation for selected cases, and can be considered up to 28 weeks. Between 16 and 18 weeks, management should be tailored according to Doppler findings. CONCLUSIONS: A consensus-based treatment protocol for early and late TTTS was agreed upon by a panel of experts. This protocol should be modified at the discretion of the operator, according to their experience and the specific demands of each case. This should advance the quality of future studies, guide clinical practice and improve patient care. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Detecting Coronary Artery Disease Using Exhaled Breath Analysis.

INTRODUCTION: Coronary artery disease (CAD) is the leading cause of morbidity and mortality worldwide, and there is an unmet need for a simple, inexpensive, noninvasive tool aimed at CAD detection. The aim of this pilot study was to evaluate the possible use of breath analysis in detecting the presence of CAD. MATERIALS AND METHODS: In a prospective study, breath from patients with no history of CAD who presented with acute chest pain to the emergency room was sampled using a designated portable electronic nose (eNose) system. First, breath samples from 60 patients were analyzed and categorized as obstructive, nonobstructive, and no-CAD according to the actual presence and extent of CAD as was demonstrated on cardiac imaging (either computerized tomography angiography or coronary angiography). Classification models were built according to the results, and their diagnostic performance was then examined in a blinded manner on a new set of 25 patients. The data were compared with the actual results of coronary arteries evaluation. Sensitivity, specificity, and accuracy were calculated for each model. RESULTS: Obstructive CAD was correctly distinguished from nonobstructive and no-CAD with 89% sensitivity, 31% specificity, 83% negative predictive value (NPV), 42% positive predictive value (PPV), and 52% accuracy. In another model, any extent of CAD was successfully distinguished from no-CAD with 69% sensitivity, 67% specificity, 54% NPV, 79% PPV, and 68% accuracy. CONCLUSION: This proof-of-concept study shows that breath analysis has the potential to be used as a novel rapid, noninvasive diagnostic tool to help identify presence of CAD in patients with acute chest pain.

Sensing gastric cancer via point-of-care sensor breath analyzer.

BACKGROUND: Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening. METHODS: A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant analysis (LDA) was used as a classifying model of the sensing signals obatined from the examined groups. For the testing step, an additional device was added. The study group included 274 patients: 94 with gastric cancer, 67 who were in the high-risk group, and 113 controls. RESULTS: The results of the test set showed a clear discrimination between patients with gastric cancer and controls using the 2-device LDA model (area under the curve, 93.8%; sensitivity, 100%; specificity, 87.5%; overall accuracy, 91.1%), and acceptable results were also achieved for patients with high-risk lesions (the corresponding values for dysplasia were 84.9%, 45.2%, 87.5%, and 65.9%, respectively). The test-phase analysis showed lower accuracies, though still clinically useful. CONCLUSION: Our results demonstrate that a portable breath sensor device could be useful in point-of-care settings. It shows a promise for detection of gastric cancer as well as for other types of disease. LAY SUMMARY: A portable sensor-based breath analyzer for detection of gastric cancer can be used in point-of-care settings. The results are transferrable between devices via advanced IoT technology. Both the hardware and software of the reported breath analyzer could be easily modified to enable detection and monitirng of other disease states.

Disease Detection with Molecular Biomarkers: From Chemistry of Body Fluids to Nature-Inspired Chemical Sensors.

This article aims to review nature-inspired chemical sensors for enabling fast, relatively inexpensive, and minimally (or non-) invasive diagnostics and follow-up of the health conditions. It can be achieved via monitoring of biomarkers and volatile biomarkers, that are excreted from one or combination of body fluids (breath, sweat, saliva, urine, seminal fluid, nipple aspirate fluid, tears, stool, blood, interstitial fluid, and cerebrospinal fluid). The first part of the review gives an updated compilation of the biomarkers linked with specific sickness and/or sampling origin. The other part of the review provides a didactic examination of the concepts and approaches related to the emerging chemistries, sensing materials, and transduction techniques used for biomarker-based medical evaluations. The strengths and pitfalls of each approach are discussed and criticized. Future perspective with relation to the information and communication era is presented and discussed.

Plankton reconstruction through robust statistical optical tomography.

Plankton interact with the environment according to their size and three-dimensional (3D) structure. To study them outdoors, these translucent specimens are imaged in situ. Light projects through a specimen in each image. The specimen has a random scale, drawn from the population's size distribution and random unknown pose. The specimen appears only once before drifting away. We achieve 3D tomography using such a random ensemble to statistically estimate an average volumetric distribution of the plankton type and specimen size. To counter errors due to non-rigid deformations, we weight the data, drawing from advanced models developed for cryo-electron microscopy. The weights convey the confidence in the quality of each datum. This confidence relies on a statistical error model. We demonstrate the approach on live plankton using an underwater field microscope.

Optical wide-field tomography of sediment resuspension.

We present a wide-field imaging approach to optically sense underwater sediment resuspension events. It uses wide-field multi-directional views and diffuse backlight. Our approach algorithmically quantifies the amount of material resuspended and its spatiotemporal distribution. The suspended particles affect the radiation that reaches the cameras, hence the captured images. By measuring the radiance during and prior to resuspension, we extract the optical depth on the line of sight per pixel. Using computed tomography (CT) principles, the optical depths yield estimation of the extinction coefficient of the suspension, per voxel. The suspended density is then derived from the reconstructed extinction coefficient.

Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation.

This article is an overview of the present and ongoing developments in the field of nanomaterial-based sensors for enabling fast, relatively inexpensive and minimally (or non-) invasive diagnostics of health conditions with follow-up by detecting volatile organic compounds (VOCs) excreted from one or combination of human body fluids and tissues (e.g., blood, urine, breath, skin). Part of the review provides a didactic examination of the concepts and approaches related to emerging sensing materials and transduction techniques linked with the VOC-based non-invasive medical evaluations. We also present and discuss diverse characteristics of these innovative sensors, such as their mode of operation, sensitivity, selectivity and response time, as well as the major approaches proposed for enhancing their ability as hybrid sensors to afford multidimensional sensing and information-based sensing. The other parts of the review give an updated compilation of the past and currently available VOC-based sensors for disease diagnostics. This compilation summarizes all VOCs identified in relation to sickness and sampling origin that links these data with advanced nanomaterial-based sensing technologies. Both strength and pitfalls are discussed and criticized, particularly from the perspective of the information and communication era. Further ideas regarding improvement of sensors, sensor arrays, sensing devices and the proposed workflow are also included.

Drops in Barometric Pressure Are Associated with Deep Intracerebral Hemorrhage.

BACKGROUND AND PURPOSE: The objective of this study is to assess the effects of changes in barometric pressure and outdoor temperature on the incidence of different subtypes of intracerebral hemorrhage (ICH). METHODS: Consecutive patients with primary supratentorial ICH were included. All patients resided in the same geographic area. We compared patients with subcortical ICH to those with cortical ICH. Meteorological data were continuously accrued. High-risk ICH days were defined as those on which 1 or more patients with ICH were admitted and compared to non-high-risk days. We analyzed the relationship between spontaneous ICH location and averaged daily atmospheric pressures and temperatures. RESULTS: We included 206 patients (147 with deep ICH and 59 with lobar ICH). Patients with deep ICH were younger (P < .001), more often had histories of diabetes, smoking and previous lacunar strokes, and were more often male (P < .01 for all). Drops in mean air pressure 2 days prior to the ictus were associated with deep but not lobar ICH (P = .006). Deep ICH clustered during February months in parallel with larger changes in barometric pressures (P < .001). CONCLUSIONS: Drops in daily atmospheric pressures were associated with deep but not cortical ICH, suggesting a link to hypertensive etiology. Changes in barometric pressures were also associated with higher monthly frequencies of ICH.

Assessment, origin, and implementation of breath volatile cancer markers.

A new non-invasive and potentially inexpensive frontier in the diagnosis of cancer relies on the detection of volatile organic compounds (VOCs) in exhaled breath samples. Breath can be sampled and analyzed in real-time, leading to fascinating and cost-effective clinical diagnostic procedures. Nevertheless, breath analysis is a very young field of research and faces challenges, mainly because the biochemical mechanisms behind the cancer-related VOCs are largely unknown. In this review, we present a list of 115 validated cancer-related VOCs published in the literature during the past decade, and classify them with respect to their "fat-to-blood" and "blood-to-air" partition coefficients. These partition coefficients provide an estimation of the relative concentrations of VOCs in alveolar breath, in blood and in the fat compartments of the human body. Additionally, we try to clarify controversial issues concerning possible experimental malpractice in the field, and propose ways to translate the basic science results as well as the mechanistic understanding to tools (sensors) that could serve as point-of-care diagnostics of cancer. We end this review with a conclusion and a future perspective.

Meningitis and Meningoencephalitis among Israel Defense Force Soldiers: 20 Years Experience at the Hadassah Medical Centers.

BACKGROUND: Meningitis and meningoencephalitis pose major risks of morbidity and mortality. OBJECTIVES: To describe 20 years of experience treating infections of the central nervous system in Israel Defense Force (IDF) soldiers, including the common presentations, pathogens and sequelae, and to identify risk groups among soldiers. METHODS: All soldiers who were admitted to the Hadassah University Medical Center (both campuses: Ein Kerem and Mt. Scopus) due to meningitis and meningoencephalitis from January 1993 to January 2014 were included in this retrospective study. Clinical, laboratory and radiologic data were reviewed from their hospital and army medical corps files. Attention was given to patients' military job description, i.e., combat vs. non-combat soldier, soldiers in training, and medical personnel. RESULTS: We identified 97 cases of suspected meningitis or meningoencephalitis. Six were mistakenly filed and these patients were found to have other disorders. Four soldiers were diagnosed with epidural abscess and five with meningitis due to non-infectious in flammatory diseases. Eighty-two soldiers in active and reserve duty had infectious meningitis or meningoencephalitis. Of these, 46 (56.1%) were combat soldiers and 31 (37.8%) non-combat; 20 (29.2%) were soldiers in training, 10 (12.2%) were training staff and 8 (9.8%) were medical staff. The main pathogens were enteroviruses, Epstein-Barr virus an d Neisseria meningitidis. CONCLUSIONS: In our series, soldiers in training, combat soldiers and medical personnel had meningitis and meningoencephalitis more than other soldiers. Enteroviruses are highly infectious pathogens and can cause outbreaks. N. meningitidis among IDF soldiers is still a concern. Early and aggressive treatment with steroids should be considered especially in robust meningoencephalitis cases.

Hybrid volatolomics and disease detection.

This Review presents a concise, but not exhaustive, didactic overview of some of the main concepts and approaches related to "volatolomics"-an emerging frontier for fast, risk-free, and potentially inexpensive diagnostics. It attempts to review the source and characteristics of volatolomics through the so-called volatile organic compounds (VOCs) emanating from cells and their microenvironment. It also reviews the existence of VOCs in several bodily fluids, including the cellular environment, blood, breath, skin, feces, urine, and saliva. Finally, the usefulness of volatolomics for diagnosis from a single bodily fluid, as well as ways to improve these diagnostic aspects by "hybrid" approaches that combine VOC profiles collected from two or more bodily fluids, will be discussed. The perspectives of this approach in developing the field of diagnostics to a new level are highlighted.

Cutoff due to pointwise degradations in color images.

Many studies analyze resolution limits in single-channel, pan-chromatic systems. However, color imaging is popular. Thus, there is a need for its modeling in terms of resolving capacity under noise. This work analyzes the probability of resolving details as a function of spatial frequency in color imaging. The analysis introduces theoretical bounds for performance, using optimal linear filtering and fusion operations. The work focuses on resolution loss caused strictly by noise, without the presence of imaging blur. It applies to full-field color systems, which do not compromise resolution by spatial multiplexing. The framework allows us to assess and optimize the ability of an imaging system to distinguish an object of given size and color under image noise.

Non-contact immunological signaling for highly-efficient regulation of the transcriptional map of human monocytes.

The different immune system cells communicate and coordinate a response using a complex and evolved language of cytokines and chemokines. These cellular interactions carry out multiple functions in distinct cell types with numerous developmental outcomes. Despite the plethora of different cytokines and their cognate receptors, there is a restricted number of signal transducers and activators to control immune responses. Herein, we report on a new class of immunomodulatory signaling molecules based on volatile molecules (VMs, namely, volatile organic compounds [VOCs]), by which they can affect and/or control immune cell behavior and transcriptomic profile without any physical contact with other cells. The study demonstrates the role of VMs by analyzing non-contact cell communication between normal and cancerous lung cells and U937 monocytes, which are key players in the tumor microenvironment. Integrated transcriptome and proteome analyses showed the suggested regulatory role of VMs released from normal and cancer cells on neighboring monocytes in several molecular pathways, including PI3K/AKT, PPAR, and HIF-1. Presented data provide an initial platform for a new class of immunomodulatory molecules that can potentially mirror the genomic and proteomic profile of cells, thereby paving the way toward non-invasive immunomonitoring.

Real-time prognostic biomarkers for predicting in-hospital mortality and cardiac complications in COVID-19 patients.

Hospitalized patients with Coronavirus disease 2019 (COVID-19) are highly susceptible to in-hospital mortality and cardiac complications such as atrial arrhythmias (AA). However, the utilization of biomarkers such as potassium, B-type natriuretic peptide, albumin, and others for diagnosis or the prediction of in-hospital mortality and cardiac complications has not been well established. The study aims to investigate whether biomarkers can be utilized to predict mortality and cardiac complications among hospitalized COVID-19 patients. Data were collected from 6,927 hospitalized COVID-19 patients from March 1, 2020, to March 31, 2021 at one quaternary (Henry Ford Health) and five community hospital registries (Trinity Health Systems). A multivariable logistic regression prediction model was derived using a random sample of 70% for derivation and 30% for validation. Serum values, demographic variables, and comorbidities were used as input predictors. The primary outcome was in-hospital mortality, and the secondary outcome was onset of AA. The associations between predictor variables and outcomes are presented as odds ratio (OR) with 95% confidence intervals (CIs). Discrimination was assessed using area under ROC curve (AUC). Calibration was assessed using Brier score. The model predicted in-hospital mortality with an AUC of 90% [95% CI: 88%, 92%]. In addition, potassium showed promise as an independent prognostic biomarker that predicted both in-hospital mortality, with an AUC of 71.51% [95% Cl: 69.51%, 73.50%], and AA with AUC of 63.6% [95% Cl: 58.86%, 68.34%]. Within the test cohort, an increase of 1 mEq/L potassium was associated with an in-hospital mortality risk of 1.40 [95% CI: 1.14, 1.73] and a risk of new onset of AA of 1.55 [95% CI: 1.25, 1.93]. This cross-sectional study suggests that biomarkers can be used as prognostic variables for in-hospital mortality and onset of AA among hospitalized COVID-19 patients.

Biodegradable, Biocompatible, and Implantable Multifunctional Sensing Platform for Cardiac Monitoring.

Cardiac monitoring after heart surgeries is crucial for health maintenance and detecting postoperative complications early. However, current methods like rigid implants have limitations, as they require performing second complex surgeries for removal, increasing infection and inflammation risks, thus prompting research for improved sensing monitoring technologies. Herein, we introduce a nanosensor platform that is biodegradable, biocompatible, and integrated with multifunctions, suitable for use as implants for cardiac monitoring. The device has two electrochemical biosensors for sensing lactic acid and pH as well as a pressure sensor and a chemiresistor array for detecting volatile organic compounds. Its biocompatibility with myocytes has been tested in vitro, and its biodegradability and sensing function have been proven with ex vivo experiments using a three-dimensional (3D)-printed heart model and 3D-printed cardiac tissue patches. Moreover, an artificial intelligence-based predictive model was designed to fuse sensor data for more precise health assessment, making it a suitable candidate for clinical use. This sensing platform promises impactful applications in the realm of cardiac patient care, laying the foundation for advanced life-saving developments.

Multi sky-view 3D aerosol distribution recovery.

Aerosols affect climate, health and aviation. Currently, their retrieval assumes a plane-parallel atmosphere and solely vertical radiative transfer. We propose a principle to estimate the aerosol distribution as it really is: a three dimensional (3D) volume. The principle is a type of tomography. The process involves wide angle integral imaging of the sky on a very large scale. The imaging can use an array of cameras in visible light. We formulate an image formation model based on 3D radiative transfer. Model inversion is done using optimization methods, exploiting a closed-form gradient which we derive for the model-fit cost function. The tomography model is distinct, as the radiation source is unidirectional and uncontrolled, while off-axis scattering dominates the images.

A nanomaterial-based breath test for short-term follow-up after lung tumor resection.

In this case study, we demonstrate the feasibility of nanomaterial-based sensors for identifying the breath-print of early-stage lung cancer (LC) and for short-term follow-up after LC-resection. Breath samples were collected from a small patient cohort prior to and after lung resection. Gas-chromatography/mass-spectrometry showed that five volatile organic compounds were significantly reduced after LC surgery. A nanomaterial-based sensor-array distinguished between pre-surgery and post-surgery LC states, as well as between pre-surgery LC and benign states. In contrast, the same sensor-array could neither distinguish between pre-surgery and post-surgery benign states, nor between LC and benign states after surgery. This indicates that the observed pattern is associated with the presence of malignant lung tumors. The proof-of-concept presented here has initiated a large-scale clinical study for post-surgery follow-up of LC patients. FROM THE CLINICAL EDITOR: Monitoring for tumor recurrence remains very challenging due to post-surgical and radiation therapy induced changes in target organs, which often renders standard radiological identification of recurrent malignancies inaccurate. In this paper a novel nanotechnology-based sensor array is used for identification of volatile organic compounds in exhaled air that enable identification of benign vs. malignant states.

Volatile fingerprints of cancer specific genetic mutations.

We report on a new concept for profiling genetic mutations of (lung) cancer cells, based on the detection of patterns of volatile organic compounds (VOCs) emitted from cell membranes, using an array of nanomaterial-based sensors. In this in-vitro pilot study we have derived a volatile fingerprint assay for representative genetic mutations in cancer cells that are known to be associated with targeted cancer therapy. Five VOCs were associated with the studied oncogenes, using complementary chemical analysis, and were discussed in terms of possible metabolic pathways. The reported approach could lead to the development of novel methods for guiding treatments, so that patients could benefit from safer, more timely and effective interventions that improve survival and quality of life while avoiding unnecessary invasive procedures. Studying clinical samples (tissue/blood/breath) will be required as next step in order to determine whether this cell-line study can be translated into a clinically useful tool. FROM THE CLINICAL EDITOR: In this novel study, a new concept for profiling genetic mutations of (lung) cancer cells is described, based on the detection of patterns of volatile organic compounds emitted from cell membranes, using an array of nano-gold based sensors.

Using Zodiacal Light For Spaceborne Calibration Of Polarimetric Imagers.

We propose that spaceborne polarimetric imagers can be calibrated, or self-calibrated using zodiacal light (ZL). ZL is created by a cloud of interplanetary dust particles. It has a significant degree of polarization in a wide field of view. From space, ZL is unaffected by terrestrial disturbances. ZL is insensitive to the camera location, so it is suited for simultaneous cross-calibration of satellite constellations. ZL changes on a scale of months, thus being a quasi-constant target in realistic calibration sessions. We derive a forward model for polarimetric image formation. Based on it, we formulate an inverse problem for polarimetric calibration and self-calibration, as well as an algorithm for the solution. The methods here are demonstrated in simulations. Towards these simulations, we render polarized images of the sky, including ZL from space, polarimetric disturbances, and imaging noise.

Continuous Monitoring of Psychosocial Stress by Non-Invasive Volatilomics.

Stress is becoming increasingly commonplace in modern times, making it important to have accurate and effective detection methods. Currently, detection methods such as self-evaluation and clinical questionnaires are subjective and unsuitable for long-term monitoring. There have been significant studies into biomarkers such as HRV, cortisol, electrocardiography, and blood biomarkers, but the use of multiple electrodes for electrocardiography or blood tests is impractical for real-time stress monitoring. To this end, there is a need for non-invasive sensors to monitor stress in real time. This study looks at the possibility of using breath and skin VOC fingerprinting as stress biomarkers. The Trier social stress test (TSST) was used to induce acute stress and HRV, cortisol, and anxiety levels were measured before, during, and after the test. GC-MS and sensor array were used to collect and measure VOCs. A prediction model found eight different stress-related VOCs with an accuracy of up to 78%, and a molecularly capped gold nanoparticle-based sensor revealed a significant difference in breath VOC fingerprints between the two groups. These stress-related VOCs either changed or returned to baseline after the stress induction, suggesting different metabolic pathways at different times. A correlation analysis revealed an association between VOCs and cortisol levels and a weak correlation with either HRV or anxiety levels, suggesting that VOCs may include complementary information in stress detection. This study shows the potential of VOCs as stress biomarkers, paving the way into developing a real-time, objective, non-invasive stress detection tool for well-being and early detection of stress-related diseases.