Noninvasive Detection Research Articles

Deliberate inclusion of multiple co-correlated gene target sets during discovery for improved biomarker translation to a clinical assay in early-stage breast cancer.

e12560 Background: Co-correlation between gene targets provides a more robust, and often nonlinear, understanding of human biology, resulting in more accurate and reliable diagnostics. When translating from discovery to a clinical assay, detectability of promising targets often hinders diagnostic development. Translating a single set of co-correlated targets becomes more challenging, as the success of the program is dependent on the interrelationship between all targets and the ability of the entire set to translate clinically. Given target translation uncertainty, we hypothesized that the deliberate inclusion of multiple independent sets of co-correlated targets during discovery could bridge the gap between promising biology and a clinically viable assay. We set out to discover and clinically validate multiple sets of co-correlated targets required for noninvasive breast cancer detection. Methods: Nonlinear statistical methods were repeatedly applied to microarray gene expression profiles from peripheral blood (PBMCs) obtained from 140 patients with and without breast cancer. Four independent cohorts were used for subsequent studies to assess efficacy and reproducibility of discovered targets. In total, five independent sets of highly efficacious co-correlated targets, totaling 26 unique genes, were discovered and analytically validated across the five patient cohorts (n=357). A sixth independent cohort of 197 plasma samples (breast cancer n=116, controls n=81) was obtained and used to clinically translate and validate the 26 targets using real-time qPCR (qPCR). Results: qPCR revealed strong and reproducible clinical signal from 8/26 previously discovered targets (Table). To evaluate the efficacy of the targets, an 8-gene signature was trained on the PBMC discovery cohort, achieving >99% sensitivity, 83% specificity, indicating a promising classifier could be trained from the 8 qPCR targets. During CLIA validation of the assay, in normalized qPCR data from 87 patients, the 8-gene assay achieved a statistically significant >99% sensitivity, 89% specificity in stage I breast cancer. Conclusions: Given the performance observed from the 8-gene qPCR assay, we conclude that the deliberate inclusion of multiple sets of co-correlated targets, including those considered mathematically redundant during discovery, contributed to the success of a clinically viable assay for the detection of early-stage breast cancer in plasma. [Table: see text]

Noninvasive early detection and recurrence monitoring for non-muscle-invasive bladder cancer via urine tumor DNA.

Noninvasive early detection and recurrence monitoring for non-muscle-invasive bladder cancer via urine tumor DNA.

Assessment of plasma cell-free DNA fragmentation for multi-cancer early detection: An independent clinical validation study.

e15037 Background: Cell-free DNA (cfDNA) in the circulation has gained significant attention due to its potential applications for non-invasive early cancer detection. Fragmentomics of cfDNA is emerging as a promising field of biomarker research, exhibiting the capability to sensitively detect multiple cancer types. In previous retrospective research, we developed an approach called PatternWGS for comprehensive analysis of cfDNA fragmentation patterns and presented a multi-cancer detection model. In this study, we aim to evaluate the performance of PatternWGS in an independent validation cohort including lung, breast, colorectal, liver, and gastric cancers from a new clinical center. Methods: Participants with confirmed diagnosis of lung, breast, colorectal or liver cancer were enrolled in the cancer group. Non-cancer participants without known presence of malignancies were recruited from the same clinical center. Plasma samples from patients with lung (n=47), breast (n=19), colorectal (n=14), liver (n=8) and gastric (n=6) cancers, along with 101 non-cancer individuals were collected in this study. cfDNA was isolated from plasma and stored within a month prior to the whole genome sequencing. The characteristics of cfDNA fragmentation integrating fragment size profiles, motif patterns, genomic coverage distributions were utilized to evaluate the performance for cancer signal detection. In addition, the performance of estimated cfDNA tumor fraction, using copy number aberrations (ichorCNA), was compared with our approach. Results: 94 patients with one of five types of cancers and 101 non-cancer controls were prospectively enrolled between July 2023 and November 2023. Among the cancer group, 64% were at early stages (Stage I: 48%, Stage II: 16%). A significantly higher proportion of shorter fragments was observed in cancer group, and the degree increased with increasing cancer stage. Overall sensitivity across cancer types and stages was 72.3%, and the specificity for non-cancer controls was 80%. As expected, the sensitivity of cancer detection is higher in late-stage patients compared to those in the early-stages (61% in stage I, 80% in stage II, 84.6% in stage III, and 91.7% in stage IV). The sensitivity of detecting lung (72% had stage I cancer), breast, colorectal, liver, and gastric cancers reached 57.4%, 84.2%, 85.7%, 87.5% and 100% respectively. The detection performance using cfDNA tumor fraction by ichorCNA demonstrated a relatively low overall sensitivity of 28.7% (24.6% for stage I-II, 44% for stage III-IV). Conclusions: This independent clinical validation study, which focused on exploring plasma cfDNA fragmentation, demonstrated ideal performance in early-stage cancer detection. The cfDNA fragmentation-based approach exhibited a superior sensitivity in detecting early cancer signals compared with copy number aberrations-based approach.

Clinical validation of Northstar Select, a novel liquid biopsy assay for comprehensive genomic profiling of solid tumors.

3072 Background: Comprehensive Genomic Profiling (CGP) liquid biopsy tests are vital tools for oncologists that enable the non-invasive detection of diverse somatic mutations, many of which correspond to targeted therapies, in circulating tumor DNA (ctDNA). However, these tests have less utility when ctDNA signal is low, which is common even in late-stage cancer patients. BillionToOne’s Northstar (NS) Select assay is a novel CGP test that seeks to leverage proprietary technology and novel calling algorithms to address this limitation by achieving higher sensitivity. Methods: Clinical samples for 182 unique patients with stage III or IV solid tumors were obtained via a prospective validation study assessing head-to-head concordance with widely adopted, commercially available ‘comparator’ liquid biopsy CGP assays. The study cohort was recruited from 1 large hospital center and 6 community clinics across the US and was diverse in patient demographics and clinical presentations. Over 15 different cancer types were represented in the cohort, with the majority of patients having either Lung, Breast, Colorectal, or Prostate cancer, all of which are commonly tested using liquid biopsies in the US. Pathogenic (including likely pathogenic) variants called by NS Select and/or the comparator assay were analyzed for concordance. For a subset of samples (N=28), white blood cell-derived genomic DNA was also processed to identify which variants were detected due to clonal hematopoiesis of indeterminate potential (CHIP). Results: In the head-to-head comparison, a large number of variants (N=380) were concordant between the two assays. In addition, NS Select detected 43% (N=147) more pathogenic variants than comparators when controlling for matched coverage regions. The majority of these variants were detected below the reported limit of detection of the comparator assays, but above the limit of detection of NS Select. The rate of CHIP mutations was not significantly different in the variants detected by NS Select (19.0% ± 7.6%) vs. comparators (17.2% ± 9.2%). Finally, the proportion of patients with no pathogenic variants detected was shown to be lower by 45% when using NS Select vs. the comparator assays (20/182 vs. 36/182). Conclusions: NS Select reported clinically useful information about the tumor for most patients. For patients in which ctDNA signal was high, NS Select had very high concordance with comparator tests. Furthermore, additional low-VAF pathogenic mutations identified by NS Select translated to a higher diagnostic yield compared to other CGP assays, and CHIP was ruled out as an explanation for these additional detections. This suggests that some patients with low levels of ctDNA would derive clinical benefit from testing with NS Select due to its high sensitivity.

Photonic Nanochains for Continuous Glucose Monitoring in Physiological Environment.

Diabetes is a common disease that seriously endangers human health. Continuous glucose monitoring (CGM) is important for the prevention and treatment of diabetes. Glucose-sensing photonic nanochains (PNCs) have the advantages of naked-eye colorimetric readouts, short response time and noninvasive detection of diabetes, showing immense potential in CGM systems. However, the developed PNCs cannot disperse in physiological environment at the pH of 7.4 because of their poor hydrophilicity. In this study, we report a new kind of PNCs that can continuously and reversibly detect the concentration of glucose (Cg) in physiological environment at the pH of 7.4. Polyacrylic acid (PAA) added to the preparation of PNCs forms hydrogen bonds with polyvinylpyrrolidone (PVP) in Fe3O4@PVP colloidal nanoparticles and the hydrophilic monomer N-2-hydroxyethyl acrylamide (HEAAm), which increases the content of PHEAAm in the polymer shell of prepared PNCs. Moreover, 4-(2-acrylamidoethylcarbamoyl)-3-fluorophenylboronic acid (AFPBA), with a relatively low pKa value, is used as the glucose-sensing monomer to further improve the hydrophilicity and glucose-sensing performances of PNCs. The obtained Fe3O4@(PVP-PAA)@poly(AFPBA-co-HEAAm) PNCs disperse in artificial serum and change color from yellow-green to red when Cg increases from 3.9 mM to 11.4 mM, showing application potential for straightforward CGM.

Engineering the luminescence and photothermal properties of metal complex Ruphen functionalized with silver nanoparticles for infrared human detection

A luminescence quenching enhanced infrared (IR) detector has been developed to achieve highly sensitive recognition of human body by adding metallic luminescence quenchers. Spherical Ag NPs were mixed with Ru(phen)32+ complex to obtain temperature-sensitive Ag/Ruphen/PVDF films. The relationships among luminescence output, temperature rise and silver addition were investigated and a satisfactory combination of enhanced luminescence factor and temperature change was found with an addition of 5 mol% of 71 nm Ag NPs. It is found that the metal-enhanced luminescence output is insignificant compared to its thermal ingredient since silver provides additional possible electron transfer channels, promoting non-radiative transitions and weakening luminescence. Besides, the Ag NPs induced additional temperature rise bringing further reduction of luminescence. The photothermal effect of Ag NPs can attain a higher temperature change under a certain IR radiation without an observed degradation of luminescence output. A coupled optical-thermal model was established to explain the schematic of the constructed infrared thermal detector. The non-invasive detections of moving and stationary human by the detector were successfully demonstrated. The work tends to provide an engineered optical-thermal model in luminophores and construct highly sensitive luminescence-based infrared thermal detectors.

Comparison of an Affibody-based Molecular Probe and 18F-FDG for Detecting HER2-Positive Breast Cancer at PET/CT.

Background Human epidermal growth factor receptor 2 (HER2) affibody-based tracers could be an alternative to nonspecific radiotracers for noninvasive detection of HER2 expression in breast cancer lesions at PET/CT. Purpose To compare an affibody-based tracer, Al18F-NOTA-HER2-BCH, and fluorine 18 (18F) fluorodeoxyglucose (FDG) for detecting HER2-positive breast cancer lesions on PET/CT images. Materials and Methods In this prospective study conducted from June 2020 to July 2023, participants with HER2-positive breast cancer underwent both Al18F-NOTA-HER2-BCH and 18F-FDG PET/CT. HER2 positivity was confirmed with pathologic assessment (immunohistochemistry test results of 3+, or 2+ followed by fluorescence in situ hybridization, indicated HER2 amplification). Two independent readers visually assessed the uptake of tracers on images. Lesion uptake was quantified using the maximum standardized uptake value (SUVmax) and target to background ratio (TBR) and compared using a general linear mixed model. Results A total of 42 participants (mean age, 56.3 years ± 10.1 [SD]; 41 female) with HER2-positive breast cancer were included; 42 (100%) had tumors that were detected with Al18F-NOTA-HER2-BCH PET/CT and 40 (95.2%) had tumors detected with 18F-FDG PET/CT. Primary tumors in two of 21 participants, lymph node metastases in four of 21 participants, bone metastases in four of 15 participants, and liver metastases in three of nine participants were visualized only with Al18F-NOTA-HER2-BCH. Lung metastasis in one of nine participants was visualized only with 18F-FDG. Al18F-NOTA-HER2-BCH enabled depiction of more suspected HER2-positive primary tumors (26 vs 21) and lymph node (170 vs 130), bone (92 vs 66), and liver (55 vs 27) metastases than 18F-FDG. The SUVmax and TBR values of primary tumors and lymph node, bone, and liver metastases were all higher on Al18F-NOTA-HER2-BCH images than on 18F-FDG images (median SUVmax range, 10.4-13.5 vs 3.4-6.2; P value range, <.001 to .02; median TBR range, 2.7-17.6 vs 1.2-7.8; P value range, <.001 to .001). No evidence of differences in the SUVmax and TBR for chest wall or lung metastases was observed between Al18F-NOTA-HER2-BCH and 18F-FDG (P value range, .06 to .53). Conclusion PET/CT with the affibody-based tracer Al18F-NOTA-HER2-BCH enabled detection of more primary lesions and lymph node, bone, and liver metastases than PET/CT using 18F-FDG. ClinicalTrials.gov Identifier: NCT04547309 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ulaner in this issue.

Non-invasive detection of urothelial carcinoma through ensembled methylation profiles and fragmentomic patterns in urinary cell-free DNA.

Non-invasive detection of urothelial carcinoma through ensembled methylation profiles and fragmentomic patterns in urinary cell-free DNA.

IDENTIFICATION OF SIGNIFICANT TEMPORAL FEATURES FROM PHOTO PULSE PLETHYSMOGRAM FOR PREDICTION OF HYPERGLYCEMIA

The increase in diabetic class population is witnessed every year and hence frequent need of checking blood glucose levels is highly required in both diabetic and healthy subjects. This requirement has led many researchers to develop efficient, accurate and easy estimation of blood glucose level without painful blood pricking or extraction. In line with this objective, this study is an effort for waveform analysis of autonomic response of photo pulse plethysmogram (PPG) and to evaluate PPG features that may provide better non-invasive detection of the disease. A total of 300 (150 diabetic and 150 control) subjects aged more than 18 years are considered for this study. Relevant patient details were obtained, and finger PPG recording in digital form was performed for 5 min with the digitization sampling rate of 200 sample points per second. After signal baseline correction, features are calculated from averaged normalized PPG and its first and second derivatives. A total of 41 features were derived from normalized PPG pulse and its derivatives for the assessment of hyperglycemia. But in practice, computation of many features is time-consuming and truly a tedious job for any model design. Further, model performance and accuracy are affected significantly. Applying six different statistical and machine learning methods for the identification of important features, 20 features were identified out of 41 features whose values are highly significantly different for control and study (diabetic) groups. This work was focused on feature extraction stage for a PPG-based diagnostic system. Though our study is aimed to identify significant features that can discriminate between diabetic and control groups non-invasively, these features have the potential for much clinical assessment and other pathological disorders without any doubt.

Dynamic processes of positive/negative immune-vascular crosstalk loop via functional MRI-guided monitor

Immunotherapy holds significant promise to completely eliminate tumor, yet lack of timely evaluation of immune responses, which challenged by inherent lagging and pseudoprogression during immunotherapy. Immune-vascular crosstalk (IVC), an enhancement ring for the mutual regulation linking tumor vascular normalization with immune remodeling forms, emerging as a systematic indicator for immunotherapy outcomes, necessitates timely, non-invasive, and early detection of its status to enhance clinical benefits. Herein, positive and negative loop models of tumor IVC were established using different degree of photothermal therapy (PTT) based on NaBiF4:Gd@PDA@PEG nanoprobes. Multi-functional magnetic resonance imaging, including fast spoiled gradient-recalled (FSPGR), time-resolved imaging of contrast kinetics (TRICKs) and dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI), was applied to dynamically reflect normalized/ablated tumor vasculature, well-matched increased/decreased immune response corresponding to different status of IVC, confirmed by pathology results. This study proposes a novel biological method to noninvasively detect the positive/negative IVC loop, paving the visualized way for immunotherapy assessed benefits, which is expected to be extended to clinical translation.

Non-invasive early detection on esophageal squamous cell carcinoma and precancerous lesions by microbial biomarkers combining epidemiological factors in China.

Microbiota may be associated with esophageal squamous cell carcinoma (ESCC) development. However, it is not known the predictive value of microbial biomarkers combining epidemiological factors for the early detection of ESCC and precancerous lesions. A total of 449 specimens (esophageal swabs and saliva) were collected from 349 participants with different esophageal statuses in China to explore and validate ESCC-associated microbial biomarkers from genes level to species level by 16S rRNA sequencing, metagenomic sequencing and real-time quantitative polymerase chain reaction. A bacterial biomarker panel including Actinomyces graevenitzii (A.g_1, A.g_2, A.g_3, A.g_4), Fusobacteria nucleatum (F.n_1, F.n_2, F.n_3), Haemophilus haemolyticus (H.h_1), Porphyromonas gingivalis (P.g_1, P.g_2, P.g_3) and Streptococcus australis (S.a_1) was explored by metagenomic sequencing to early detect the participants in Need group (low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia and ESCC) vs participants without these lesions as the Noneed group. Significant quantitative differences existed for each microbial target in which the detection efficiency rate was higher in saliva than esophageal swab. In saliva, the area under the curve (AUC) based on the microbial biomarkers (A.g_4 ∩ P.g_3 ∩ H.h_1 ∩ S.a_1 ∩ F.n_2) was 0.722 (95% CI 0.621-0.823) in the exploration cohort. Combining epidemiological factors (age, smoking, drinking, intake of high-temperature food and toothache), the AUC improved to 0.869 (95% CI 0.802-0.937) in the exploration cohort, which was validated with AUC of 0.757 (95% CI 0.663-0.852) in the validation cohort. It is feasible to combine microbial biomarkers in saliva and epidemiological factors to early detect ESCC and precancerous lesions in China.

PIK3CA Hotspot Mutations in Saliva as a Diagnostic Marker in Oral Squamous Cell Carcinoma Patients.

This study aimed at the analogous detection of PIK3CA mutations, common in oral squamous cell carcinoma (OSCC), in matched tumor and saliva samples. Tissue and saliva samples were obtained from 29 patients diagnosed with primary OSCC. Saliva samples were obtained preoperatively; tissue specimens were acquired during tumor resection. Tumor DNA was extracted from both tissue and saliva samples. All samples were controlled for DNA quantity and quality and genetic matching of sample pairs was confirmed using the iPlex Pro Exome QC Panel. Variant detection was performed using the MassARRAY® System, a mass-spectrometry based detection system. Mutational analysis in tissue tumor DNA was made using the multiplexed ClearSEEK™ PIK3CA v1.0 Panel covering 20 hotspot mutations in PIK3CA. In saliva samples, variants were analyzed using both the ClearSEEK™ and the UltraSEEK® Lung v1.1 Panel, with a higher limit of detection but covering less PIK3CA variants. Overall, a PIK3CA variant was found in seven of the 29 tumor tissue samples (24%) by ClearSEEK™; UltraSEEK® additionally confirmed the variant in four of these seven positive samples. Of the three variants not detected by UltraSEEK®, two were not included in the panel and one was included but not detected. Of the seven variants found in tissue, five could also be detected in the matching saliva samples (71%), either by utilizing ClearSEEK™ or UltraSEEK® Conclusion: The detection of PIK3CA hotspot mutations in OSCC and their simultaneous occurrence in saliva underline the potential benefit of liquid biopsies for non-invasive cancer detection and follow-up care of OSCC patients.

A novel method for chronic obstructive pulmonary disease detection using comprehensive respiratory impedance and electrocardiogram-derived respiration

Currently, pulmonary function test is the only standard method for diagnosing COPD, but it often involves high testing costs, poor compliance, and a high dependence on patient cooperation. Other new detection methods, such as CT and FOT, also have disadvantages such as radiation exposure and high usage costs. Existing non-invasive COPD detection methods consider the impact of COPD on the lungs or heart, thus they can only roughly detect COPD in individuals, without the ability to grade COPD. Therefore, this study proposed a method for COPD detection using comprehensive respiratory impedance (CRI) and electrocardio-derived respiration (EDR) signals. The method measured both respiratory impedance and ECG synchronously, and the CRI and EDR signals were obtained through an algorithm. The effects of COPD on respiratory pattern were studied by taking CRI and EDR signal morphology as objects, from which characteristic parameters were extracted and input into the supervised classifier to fuse the information of COPD on the changes of respiratory signal morphology pattern in the heart and lungs. The final result is accurate detection of normal, mild COPD and moderate COPD. The experimental results of 46 subjects showed that the accuracy, sensitivity and specificity of CRI and EDR signal characteristics for COPD detection by different classifiers were up to 93.5 %, 90.5 % and 96.5 %, and the AUC values of different classifiers were all > 0.88. Therefore, the method can not only effectively distinguish COPD patients from healthy people, but also provide differentiated detection capabilities for different COPD clinical grades, providing strong support for the early diagnosis and treatment of COPD, and can be applied to the development of portable medical devices for the detection of COPD.

Recent Advancement of Nanotheranostics in Cancer Applications.

The field of nanomedicine shows promising implications in the concurrent delivery of therapeutic and diagnostic (theranostics) compounds in a single platform. Nanotheranostics is incredibly promising since it offers simultaneous non-invasive disease detection and treatment together with the exciting ability to track drug release and distribution in real-time, thereby forecasting and evaluating the efficacy of the therapy. The cancer theranostic approach improves the cancer prognosis safely and effectively. Common classes of nanoscale biomaterials, including magnetic nanoparticles, quantum dots, upconversion nanoparticles, mesoporous silica nanoparticles, carbon- based nanoparticles, and organic dye-based nanoparticles, have demonstrated enormous potential for theranostic activity. The need for improved disease detection and enhanced chemotherapeutic treatments, together with realistic considerations for clinically translatable nanomaterials will be key driving factors for theranostic agent research shortly. The developments of precision theranostic nanomaterials are employed in imaging systems like, MRI, PET, and SPECT with multifunctional ability. In this review, different nanoparticles/nanomaterials that are used/developed for theranostic activity are discussed.

Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease.

With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-β (Aβ) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific training data and BioFINDER-2, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aβ-PET/CSF testing as the standard of truth. Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aβ-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aβ positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required from confirmatory testing. This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aβ-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.

Non-invasive detection of cardiac arrhythmias using photoplethysmography signals

Abstract Cardiac arrhythmias (CAs) are associated with critical heart-related complications such as stroke or heart failure. Because of the intermittent and asymptomatic presentation of some CAs in their early stages, the screening remains limited using traditional methods based on ECG. Recent advances in photoplethysmography (PPG) have revealed substantial potential for wearable devices to detect CAs within large populations. Although PPG has demonstrated efficiency in discriminating atrial fibrillation (AF) from normal sinus rhythm, it remains unclear whether AF detection methods remains effective in the presence of CAs other than AF. In this study, we applied a recurrent neural network on a dataset containing eight different types of CAs (Table 1). The classifier processes sequences of interbeat intervals (IBIs) as input and discriminates between normal and abnormal rhythms. The algorithm was evaluated on 64 patients (45 males and 19 females , with a mean age of 55.9 ± 16.0) undergoing a diagnostic or therapeutic electrophysiological procedure. This dataset includes simultaneous recordings of PPG signals from a wrist-bracelet and 12-lead ECG, with the latter used as the gold-standard for annotating cardiac rhythms. The classifier achieved 84% accuracy, 77% sensitivity and 88% specificity in detecting abnormal rhythms. Table 1 shows that AF (99.6%), atrial tachycardia (100%) and AVRT (96.4%) were well classified as abnormal rhythm, whereas the reliability of the detection decreased for atrial flutter (65.4%), atrial or ventricular bigeminy (72.4%) and ventricular tachycardia (80.2%). Undetected abnormal rhythms were often characterized by a rather regular rhythm (illustrated by VT in Figure 1) and CAs for which PPG heartbeat detection was initially not optimal (Bigeminy in Figure 1). In conclusion, this study shows the capability of PPG-based technology to detect various CAs extending beyond AF. It highlights the merits and limitations of IBI-based detection of abnormal rhythms, highlighting the need for a better comprehension of the peripheral hemodynamic signature of CAs.

Design and evaluation of an AR-based thermal imaging system for planning reconstructive surgeries.

Thermal imaging can be used for the non-invasive detection of blood vessels of the skin. However, mapping the results to the patient currently lacks user-friendliness. Augmented reality may provide a useful tool to superimpose thermal information on the patient. A system to support planning in reconstructive surgery using a thermal camera was designed. The obtained information was superimposed on the physical object using a Microsoft HoloLens. An RGB, depth, and thermal camera were combined to capture a scene of different modalities and reconstruct a virtual scene in real time. To register the different cameras and the AR device, an active calibration target was developed and evaluated. A Vuforia marker was used to register the hologram in the virtual space. The accuracy of the projected hologram was evaluated in a laboratory setting with participants by measuring the error between the physical object and the hologram. The AR-based system was evaluated by 21 participants in a laboratory setting. The mean projection error is 10.3 ± 9.4mm. The system is able to stream a three-dimensional scene with augmented thermal information in real time at 5 frames per second. The active calibration target can be used independently of the environment. The calibration target provides an easy-to-use method for the registration of cameras capturing the visible to long-infrared spectral range. The inside-out tracking of the HoloLens in combination with a Vuforia marker is not accurate enough for the intended clinical use.

Sensitive detection and imaging of H2O density through Rydberg resonant femtosecond laser induced photofragmentation fluorescence.

A femtosecond laser induced photofragmentation fluorescence (fs-LIPF) scheme for the sensitive detection and imaging of water vapor is presented. Two photons of 244.3nm excite water to the D̃ state and produce hydroxyl radicals in the fluorescing à state. Two more photons promote electrons from the D̃ state to a neutral Rydberg state of the (1b2)-1 ionic core through a 2 + 2 doubly resonant process. The resulting high-lying Rydberg state undergoes neutral dissociation, and the energetic hydrogen fragments are detected from their Balmer series fluorescence. These channels (in the low-pressure limit) have detection sensitivities around 1012 molecules per cubic centimeters, orders of magnitude more sensitive than laser-induced fluorescence based approaches, allowing for sensitive non-invasive detection and imaging of water density for many important processes.

Exosome-mediated PROTAC delivery for treatment of RNA viral infections and zoonosis

The increase in diseases caused by RNA viruses, such as influenza, severe acute respiratory syndrome-coronavirus (SARS-CoV), Middle East respiratory syndrome (MERS), and Ebola, presents a growing global health challenge as well as the threat of zoonosis. Traditional antiviral treatments are often undermined by fast-mutating viruses, drug resistance, and newly emerging pathogens. Here, we explore proteolysis-targeting chimeras (PROTACs), a novel protein degradation machinery that has the potential to reshape the way in which RNA viral infections can be managed. PROTACs excel at specifically degrading pathogenic proteins, offering a targeted and efficient antiviral strategy. We also investigate the potential of exosome-based diagnostic technologies, which harness cell-derived nanovesicles for non-invasive sampling and early viral infection detection. Addressing the challenge of PROTAC delivery, we introduce a groundbreaking strategy utilizing exosomes to deliver PROTACs with improved precision and as a targeted delivery vehicle. Integrating these innovative strategies provides a novel approach to combat RNA zoonotic viral diseases, paving the way for a new era in antiviral therapy.

A Portable Device for in Situ Noninvasive Monitoring of Cell Secretions and Communications with Fluorescence and Nanochannel Electrochemistry.

In situ monitoring of cell secretions and communications plays a fundamental role in screening of disease diagnostic biomarkers and drugs. Quantitative detection of cell secretions and monitoring of intercellular communication have been separately reported, which often rely on target labeling or complex pretreatment steps, inevitably causing damage to the target. Simultaneous in situ noninvasive detection of cell secretions and monitoring of intercellular communication are challenging and have never been reported. Herein, we smartly developed a portable device for in situ label-free monitoring of cell secretions and communications with fluorescence and ion-transport-based nanochannel electrochemistry. Based on the dual signal mode, a series of nonelectroactive secretions were sensitively and accurately quantified. The detection limits for VEGF, MUC1, and ATP were 3.84 pg/mL, 32.7 pg/mL, and 47.4 fM (3σ/S), which were 1/3.9, 1/1.1, and 1/41 of those of commercial ELISA kits, respectively. More interestingly, under the released secretions, the gradual opening of the nanochannel connected the two cells in the left and right chambers of the device; thus, the secretion mediated intercellular communication can be monitored. The proposed platform may provide a promising tool for understanding the mechanism of intercellular communication and discovering new therapeutic targets.