Establishment and validation of a tumor-infiltrating γδT cell related prognostic gene signature in head and neck squamous cell carcinoma.

γδT cells are unconventional T cells only accounting for 1-5 % of circulating T lymphocytes. Their potent anti-tumor capability has been evidenced by accumulating studies. However, the prognostic value of γδT cells remains not well documented in head and neck squamous cell carcinoma (HNSCC). In this study, we utilized the TCGA HNSCC database to evaluate the infiltration of γδT cells and the association between γδT cells and clinicopathological factors by related gene signature, which were then validated by a total of 100 collected tumor samples from HNSCC patient cohort. Heterogeneity and functional characteristics of distinct infiltrating γδT cell profiles in HNSCC were then investigated based on the scRNA-seq data from the GEO database. We found higher γδT cell gene signature score was significantly associated with longer survival. Cox regression models showed that γδT cell gene signature could serve as an independent prognostic indicator for HNSCC patients. A high level of γδT cell-related gene signature was positively correlated with the infiltration of tumor-infiltrating lymphocytes and immune score. Through scRNA-seq analysis, we identified that γδ+ Trm cells and γδ+ CTL cells possessed anti-tumor and immunoregulatory properties. Notably, we found a significant association between the presence of these cells and improved survival outcomes. In our cell-cell communication analyses, we identified that γδT cells have the potential to eliminate tumor cells through the secretion of interferon-gamma and granzyme. Collectively, the infiltration of γδT cells may serve as a promising prognostic tool, prompting the consideration of treatment options for patients with HNSCC.

Fundamental and Practical Feasibility of Electrocardiogram Reconstruction from Photoplethysmogram.

Electrocardiogram (ECG) reconstruction from contact photoplethysmogram (PPG) would be transformative for cardiac monitoring. We investigated the fundamental and practical feasibility of such reconstruction by first replicating pioneering work in the field, with the aim of assessing the methods and evaluation metrics used. We then expanded existing research by investigating different cycle segmentation methods and different evaluation scenarios to robustly verify both fundamental feasibility, as well as practical potential. We found that reconstruction using the discrete cosine transform (DCT) and a linear ridge regression model shows good results when PPG and ECG cycles are semantically aligned-the ECG R peak and PPG systolic peak are aligned-before training the model. Such reconstruction can be useful from a morphological perspective, but loses important physiological information (precise R peak location) due to cycle alignment. We also found better performance when personalization was used in training, while a general model in a leave-one-subject-out evaluation performed poorly, showing that a general mapping between PPG and ECG is difficult to derive. While such reconstruction is valuable, as the ECG contains more fine-grained information about the cardiac activity as well as offers a different modality (electrical signal) compared to the PPG (optical signal), our findings show that the usefulness of such reconstruction depends on the application, with a trade-off between morphological quality of QRS complexes and precise temporal placement of the R peak. Finally, we highlight future directions that may resolve existing problems and allow for reliable and robust cross-modal physiological monitoring using just PPG.

KLF7 regulates super-enhancer-driven IGF2BP2 overexpression to promote the progression of head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous carcinoma (HNSCC) is known for its high aggressiveness and susceptibility to cervical lymph node metastasis, which greatly contributes to its poor prognosis. During tumorigenesis, many types of cancer cells acquire oncogenic super-enhancers (SEs) that drive the overexpression of oncogenes, thereby maintaining malignant progression. This study aimed to identify and validate the role of oncogenic SE-associated genes in the malignant progression of HNSCC. METHODS: We identified HNSCC cell-specific SE-associated genes through H3K27Ac ChIP-seq and overlapped them with HNSCC-associated genes obtained from The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) datasets using weighted gene coexpression network analysis (WGCNA) to identify hub genes. The expression of IGF2BP2 and KLF7 in HNSCC was detected using clinical samples. To determine the biological role of IGF2BP2, we performed CCK-8, colony formation assay, Transwell migration assay, invasion assay, and orthotopic xenograft model experiments. Furthermore, we utilized a CRISPR/Cas9 gene-editing system, small-molecule inhibitors, ChIP-qPCR, and dual-luciferase reporter assays to investigate the molecular mechanisms of IGF2BP2 and its upstream transcription factors. RESULTS: Our study identified IGF2BP2 as a hub SE-associated gene that exhibited aberrant expression in HNSCC tissues. Increased expression of IGF2BP2 was observed to be linked with malignant progression and unfavorable prognosis in HNSCC patients. Both in vitro and in vivo experiments confirmed that IGF2BP2 promotes the tumorigenicity and metastasis of HNSCC by promoting cell proliferation, migration, and invasion. Mechanistically, the IGF2BP2-SE region displayed enrichment for H3K27Ac, BRD4, and MED1, which led to the inhibition of IGF2BP2 transcription and expression through deactivation of the SE-associated transcriptional program. Additionally, KLF7 was found to induce the transcription of IGF2BP2 and directly bind to its promoter and SE regions. Moreover, the abundance of KLF7 exhibited a positive correlation with the abundance of IGF2BP2 in HNSCC. Patients with high expression of both KLF7 and IGF2BP2 showed poorer prognosis. Lastly, we demonstrated that the small molecule inhibitor JQ1, targeting BRD4, attenuated the proliferation and metastatic abilities of HNSCC cells. CONCLUSIONS: Our study reveals the critical role of IGF2BP2 overexpression mediated by SE and KLF7 in promoting HNSCC progression. Targeting SE-associated transcriptional programs may represent a potential therapeutic strategy in managing HNSCC.

Multi-site isomerization of synergistically regulated stimuli-responsive AIE materials toward multi-level decryption.

Stimuli-responsive aggregation-induced emission (AIE) materials are highly sensitive and rapidly responsive to external signals, making them ideal solid materials for anti-counterfeiting encryption. However, the limited conformational and packing variations resulting from regio-isomerization with a single substituent restricts the stimuli-responsive behavior of these materials. In this work, several AIE-active regio-structural isomers based on the salicylaldehyde Schiff base scaffold have been straightforwardly obtained through multiple substitutions with bromide and triphenylamine moieties. Solvent-effect experiments demonstrate their different orders of charge-transfer and excited-state intramolecular proton transfer upon photoexcitation, indicating the regulation of excited-state processes via multi-site isomerization. These isomers also demonstrate mechanochromism and acidichromism, allowing for adjustable stimuli-responsive effects. As a demonstration, p-Br-TPA with both mechanochromism and acidichromism can be synergistically utilized for multi-level decryption. This study successfully regulates the evolution of excited states through multi-site isomerization, offering a general approach for achieving tunable stimuli-responsive properties in AIE-active salicylaldehyde Schiff bases toward multi-level decryption.

Generalized Camera-Based Infant Sleep-Wake Monitoring in NICUs: A Multi-Center Clinical Trial.

The infant sleep-wake behavior is an essential indicator of physiological and neurological system maturity, the circadian transition of which is important for evaluating the recovery of preterm infants from inadequate physiological function and cognitive disorders. Recently, camera-based infant sleep-wake monitoring has been investigated, but the challenges of generalization caused by variance in infants and clinical environments are not addressed for this application. In this paper, we conducted a multi-center clinical trial at four hospitals to improve the generalization of camera-based infant sleep-wake monitoring. Using the face videos of 64 term and 39 preterm infants recorded in NICUs, we proposed a novel sleep-wake classification strategy, called consistent deep representation constraint (CDRC), that forces the convolutional neural network (CNN) to make consistent predictions for the samples from different conditions but with the same label, to address the variances caused by infants and environments. The clinical validation shows that by using CDRC, all CNN backbones obtain over 85% accuracy, sensitivity, and specificity in both the cross-age and cross-environment experiments, improving the ones without CDRC by almost 15% in all metrics. This demonstrates that by improving the consistency of the deep representation of samples with the same state, we can significantly improve the generalization of infant sleep-wake classification. Our code and model are available at https://github.com/contactless-healthcare/Camera-based-Infant-Sleep-Wake-Monitoring.

The effect of marathon running on the lower extremity kinematics and muscle activities during walking and running tasks.

Patellofemoral pain syndrome (PFPS) is a common injury among runners, and it is thought that abnormal lower extremity biomechanics contribute to its development. However, the relationship between biomechanical changes after a marathon and PFPS injury remains limited. This study aims to investigate whether differences in knee and hip kinematics and lower extremity muscle activities exist in recreational runners before and after a marathon. Additionally, it aims to explore the relationship between these biomechanical changes and the development of PFPS injury. 12 recreational runners participated in the study. Kinematics and muscle activities of the lower extremity were recorded during walking (5 km/h) and running (10 km/h) tasks within 24 hours before and within 5 hours after a marathon. After the marathon, there was a significant decrease in peak knee flexion (walking: p = 0.006; running: p = 0.006) and an increase in peak hip internal rotation (walking: p = 0.026; running: p = 0.015) during the stance phase of both walking and running compared to before the marathon. The study demonstrates a decrease in knee flexion and an increase in hip internal rotation during the stance phase of gait tasks after completing a marathon, which may increase the risk of developing PFPS injury.

High preseason temperature variability drives convergence of xylem phenology in the Northern Hemisphere conifers.

Wood growth is key to understanding the feedback of forest ecosystems to the ongoing climate warming. An increase in spatial synchrony (i.e., coincident changes in distant populations) of spring phenology is one of the most prominent climate responses of forest trees. However, whether temperature variability contributes to an increase in the spatial synchrony of spring phenology and its underlying mechanisms remains largely unknown. Here, we analyzed an extensive dataset of xylem phenology observations of 20 conifer species from 75 sites over the Northern Hemisphere. Along the gradient of increase in temperature variability in the 75 sites, we observed a convergence in the onset of cell enlargement roughly toward the 5th of June, with a convergence in the onset of cell wall thickening toward the summer solstice. The increase in rainfall since the 5th of June is favorable for cell division and expansion, and as the most hours of sunlight are received around the summer solstice, it allows the optimization of carbon assimilation for cell wall thickening. Hence, the convergences can be considered as the result of matching xylem phenological activities to favorable conditions in regions with high temperature variability. Yet, forest trees relying on such consistent seasonal cues for xylem growth could constrain their ability to respond to climate warming, with consequences for the potential growing season length and, ultimately, forest productivity and survival in the future.

Single-cell transcriptomics reveals cell atlas and identifies cycling tumor cells responsible for recurrence in ameloblastoma.

Ameloblastoma is a benign tumor characterized by locally invasive phenotypes, leading to facial bone destruction and a high recurrence rate. However, the mechanisms governing tumor initiation and recurrence are poorly understood. Here, we uncovered cellular landscapes and mechanisms that underlie tumor recurrence in ameloblastoma at single-cell resolution. Our results revealed that ameloblastoma exhibits five tumor subpopulations varying with respect to immune response (IR), bone remodeling (BR), tooth development (TD), epithelial development (ED), and cell cycle (CC) signatures. Of note, we found that CC ameloblastoma cells were endowed with stemness and contributed to tumor recurrence, which was dominated by the EZH2-mediated program. Targeting EZH2 effectively eliminated CC ameloblastoma cells and inhibited tumor growth in ameloblastoma patient-derived organoids. These data described the tumor subpopulation and clarified the identity, function, and regulatory mechanism of CC ameloblastoma cells, providing a potential therapeutic target for ameloblastoma.

Camera-based Seismocardiogram for Heart Rate Variability Monitoring.

Heart rate variability (HRV) is a crucial metric that quantifies the variation between consecutive heartbeats, serving as a significant indicator of autonomic nervous system (ANS) activity. It has found widespread applications in clinical diagnosis, treatment, and prevention of cardiovascular diseases. In this study, we proposed an optical model for defocused speckle imaging, to simultaneously incorporate out-of-plane translation and rotation-induced motion for highly-sensitive non-contact seismocardiogram (SCG) measurement. Using electrocardiogram (ECG) signals as the gold standard, we evaluated the performance of photoplethysmogram (PPG) signals and speckle-based SCG signals in assessing HRV. The results indicated that the HRV parameters measured from SCG signals extracted from laser speckle videos showed higher consistency with the results obtained from the ECG signals compared to PPG signals. Additionally, we confirmed that even when clothing obstructed the measurement site, the efficacy of SCG signals extracted from the motion of laser speckle patterns persisted in assessing the HRV levels. This demonstrates the robustness of camera-based non-contact SCG in monitoring HRV, highlighting its potential as a reliable, non-contact alternative to traditional contact-PPG sensors.

Multispectral Depolarization based Living-skin Detection: A New Measurement Principle.

Camera-based photoplethysmographic imaging enabled the segmentation of living-skin tissues in a video, but it has inherent limitations to be used in real-life applications such as video health monitoring and face anti-spoofing. Inspired by the use of polarization for improving vital signs monitoring (i.e. specular reflection removal), we observed that skin tissues have an attractive property of wavelength-dependent depolarization due to its multi-layer structure containing different absorbing chromophores, i.e. polarized light photons with longer wavelengths (R) have deeper skin penetrability and thus experience thorougher depolarization than those with shorter wavelengths (G and B). Thus we proposed a novel dual-polarization setup and an elegant algorithm (named "MSD") that exploits the nature of multispectral depolarization of skin tissues to detect living-skin pixels, which only requires two images sampled at the parallel and cross polarizations to estimate the characteristic chromaticity changes (R/G) caused by tissue depolarization. Our proposal was verified in both the laboratory and hospital settings (ICU and NICU) focused on anti-spoofing and patient skin segmentation. The clinical experiments in ICU also indicate the potential of MSD for skin perfusion analysis, which may lead to a new diagnostic imaging approach in the future. The proposed MSD algorithm is extremely simple to implement (only 5 lines of Matlab code) and its performance is highly reproducible: https://github.com/contactless-healthcare/Multispectral-Depolarization-based-Living-skin-Detection.

Notch RGB-camera based SpO2 estimation: a clinical trial in a neonatal intensive care unit.

Regular and narrow-band RGB cameras are recently explored for contactless SpO2 monitoring. Regular RGB cameras with cross-band overlap provide a high signal-to-noise-ratio (SNR) in measuring the photoplethysmographic signals but possess high dependency on the spectra of incident light, whereas narrow-band RGB cameras have better spectral independence but lower SNR especially in dim lighting conditions, such as in the neonatal intensive care unit (NICU). This paper proposes a notch RGB camera based SpO2 measurement approach that uses an optical notch filter to attenuate the wavelengths of 580-605 nm of a regular RGB camera to improve the spectral independence while maintaining high SNR in signal measurement. The proposed setup was validated in the lab condition (e.g. dark chamber) against the existing solutions for visible-light based camera-SpO2 measurement and further verified in the NICU on preterm infants. The clinical trial conducted in the NICU with 22 preterm infants shows that the notch RGB camera can achieve a mean absolute error (MAE) less than 4% for SpO2 measurement. This is the first showcase of continuous monitoring of absolute camera-SpO2 values in the NICU.

CYTOR Facilitates Formation of FOSL1 Phase Separation and Super Enhancers to Drive Metastasis of Tumor Budding Cells in Head and Neck Squamous Cell Carcinoma.

Tumor budding (TB) is a small tumor cell cluster with highly aggressive behavior located ahead of the invasive tumor front. However, the molecular and biological characteristics of TB and the regulatory mechanisms governing TB phenotypes remain unclear. This study reveals that TB exhibits a particular dynamic gene signature with stemness and partial epithelial-mesenchymal transition (p-EMT). Importantly, nuclear expression of CYTOR is identified to be the key regulator governing stemness and the p-EMT phenotype of TB cells, and targeting CYTOR significantly inhibits TB formation, tumor growth and lymph node metastasis in head and neck squamous cell carcinoma (HNSCC). Mechanistically, CYTOR promotes tumorigenicity and metastasis of TB cells by facilitating the formation of FOSL1 phase-separated condensates to establish FOSL1-dependent super enhancers (SEs). Depletion of CYTOR leads to the disruption of FOSL1-dependent SEs, which results in the inactivation of cancer stemness and pro-metastatic genes. In turn, activation of FOSL1 promotes the transcription of CYTOR. These findings indicate that CYTOR is a super-lncRNA that controls the stemness and metastasis of TB cells through facilitating the formation of FOSL1 phase separation and SEs, which may be an attractive target for therapeutic interventions in HNSCC.

Home Triad: A New Exploration of Home for People Living With Dementia Based on Lefebvre's Spatial Triad.

OBJECTIVES: This article examines a novel theoretical framework, which we term Home Triad, for research and practice involving people living with dementia (PLWD). BACKGROUND: Most of the existing home-related research on PLWD focuses on interior modifications, home care interventions and models, place attachment, and/or institutional homelike environments. However, limited studies have examined the meaning of home from PLWD's perspective, and even fewer have simultaneously considered the individual experience of PLWD, the external power (e.g., the role of design), and their interaction dynamics in the meaning-making process. METHODS: We developed home triad based on Lefebvre's spatial triad. Inspired by Chaudhury's home story structure, we conducted a life story analysis of a person living with dementia, "Kai," under four contexts-childhood home, neighborhood and city, daily routine, and attachment-within home triad. RESULTS: Home triad abstracts "home" with a dialectically interconnected relationship of the conceived, perceived, and lived home. Through PLWD's everyday life, the essence of home is primarily shaped by the interaction between their lived and perceived homes. However, a person's experiences of and participation in home living activities are also planned and/or regulated by different groups of people (caregivers, designers, and policymakers), who play important roles in the conceived home. Critically examining how PLWD's lived and perceived home is constrained or enabled through the conceived home deserves greater future research efforts. CONCLUSION: A systematic examination of the essence of home for PLWD using home triad can facilitate subsequent research and practice that promote PLWD's health, well-being, and quality of life.

Natural Acceptor of Coumarin-Isomerized Red-Emissive BioAIEgen for Monitoring Cu2+ Concentration in Live Cells via FLIM.

Artificial aggregation-induced emission luminogens (AIEgens) have flourished in bio-applications with the development of synthetic chemistry, which however are plagued by issues like singularity in structures and non-renewability. The unique structures and renewability of biomass moieties can compensate for these drawbacks, but their properties are hard to design and regulate due to their confined structures. Therefore, it appears to be a reasonable approach to derive AIEgens from abundant biomass (BioAIEgens), integrating the bilateral advantages of both synthetic and natural AIEgens. In this work, the blue-violet emissive coumarin with its lactone structure serving as a rare natural acceptor, is utilized to construct donor-π-acceptor typed BioAIE isomers incorporating the propeller-like and electron-donating triphenylamine (TPA) unit. The results show that Cm-p-TPA undergoes charge transfer with its keto form, emitting red light at 600 nm, which can be applied to monitor Cu2+ concentration during mitophagy using fluorescence lifetime imaging microscopy because of the excellent biocompatibility, photostability, and specific recognition to Cu2+ . This work not only demonstrates the feasibility of utilizing positional isomerization to modulate excited-state evolutions and resultant optical properties, but also provides evidence for the rationality of constructing biologically-active BioAIEgens via a biomass-derivatization concept.

A Large-Scale Clinical Benchmark of ResNet-based Deep Models for Newborn Face Recognition.

Newborn face recognition is a meaningful application for obstetrics in the hospital, as it enhances security measures against infant swapping and abduction through authentication protocols. Due to limited newborn face datasets, this topic was not thoroughly studied. We conducted a clinical trial to create a dataset that collects face images from 200 newborns within an hour after birth, namely NEWBORN200. To our best knowledge, this is the largest newborn face dataset collected in the hospital for this application. The dataset was used to evaluate the four latest ResNet-based deep models for newborn face recognition, including ArcFace, CurricularFace, MagFace, and AdaFace. The experimental results show that AdaFace has the best performance, obtaining 55.24% verification accuracy at 0.1% false accept rate in the open set while achieving 78.76% rank-1 identification accuracy in a closed set. It demonstrates the feasibility of using deep learning for newborn face recognition, also indicating the direction of improvement could be the robustness to varying postures.

Feasibility of Exploiting Physiological and Motion Features for Camera-based Sleep Staging: A Clinical Study.

Camera-based sleep monitoring is an emergent research topic in sleep medicine. The feasibility of using both the physiological features and motion features measured by a video camera for sleep staging was not thoroughly investigated. In this paper, we built a camera-based non-contact sleep monitoring setup in the Institute of Respiratory Diseases, Shenzhen People's Hospital, and created a clinical sleep dataset (nocturnal video data of 11 adults) including the expert-corrected PSG references synchronized with the video. The camera-based measurements have shown high correlations with the PSG. It obtains an overall Mean Absolute Error (MAE) of 1.5 bpm for heart-rate (HR), 0.7 bpm for breathing-rate (BR), 13.9 ms for heart-rate variability (HRV), and an accuracy of 93.5% for leg motion detection. The statistical analysis indicates that the averaged HR and variations of BR are distinct features for annotating four sleep stages (awake, REM, light sleep, and deep sleep). HRV parameter (SDNN) can clearly differentiate rapid-eye-movement (REM) and non-REM, while the leg movement is a distinctive feature for separating awake and sleep. The clinical trial demonstrated the feasibility of using physiological and motion features measured by a camera for joint sleep staging, and provides insights for sleep-related feature selection.

Occlusion-robust Sleep Posture Detection using Body Rolling Motion in a Video.

It has been reported that the monitoring of sleep postures is useful for the treatment and prevention of sleep diseases such as obstructive sleep apnea and heart failure. Camera-based sleep posture detection is attractive for the nature of comfort and convenience of use. However, the main challenge is to detect postures from images of the body that are occluded by bed sheets or covers. To address this issue, we propose a novel occlusion-robust sleep posture detection method exploiting the body rolling motion in a video. It uses the head orientation to indicate the posture direction (supine, left or right lateral), triggered by the full-body rolling motion (as a sign of posture change). The experimental results show that our proposed method, as compared with the state-of-the-art approaches such as skeleton-based (MediaPipe) and full-image ResNet based methods, obtained clear improvements on sleep posture detection with heavy body occlusions, with an averaged precision, recall and F1-score of 0.974, 0.993 and 0.983, respectively. The next step is to integrate the sleep posture detection algorithm into a camera-based sleep monitoring system for clinical validations.

Impact of Different Skin Penetration Depths of Red and Green Wavelengths on Camera-based SpO2 Measurement.

Remote camera-based estimation of blood oxygen saturation (SpO2) using visible lights has been studied recently, typically for red (660 nm) and green (550 nm) wavelengths. This paper investigates the impact of different skin penetration depths of red and green wavelengths on the SpO2 estimation based on mathematical modeling and experiments, where the SpO2-calibritability between two illumination setups, narrow-band red/green and narrow-band red/infrared, are statistically compared using the "ratio-of-ratios" method. The results show that the performance of the setup using red/green is less consistent among 17 volunteers than the setup using red/infrared, and larger SpO2 disparity between different skin regions (by SpO2 imaging) have been found for individuals in the red/green wavelengths setup. The use of visible light (red and green) may impose a risk of SpO2 calibration due to the different skin penetration depths of these two wavelengths.

A Pilot Study of Deep Learning Models for Camera based Hand Hygiene Monitoring in ICU.

Hand hygiene is key to preventing cross-infections in the Intensive Care Unit (ICU). Monitoring of hand washing activities can effectively increase the compliance of clinicians to hand hygiene. In this paper, we explored the feasibility of recognizing clinicians' hand-washing activities using a clinical dataset recorded in ICU using CCTV cameras. We benchmarked three types of hand hygiene detection methods on the dataset with the aim of identifying the 7-step hand washing procedure defined by WHO. Experimental results show that our approach achieves 97% average accuracy for personalized and 67% for generalized modeling. Preliminary results indicate that hand hygiene recognition is subject-dependent, and thus cross-subject modeling or subject-adaptive learning should be used to enhance generalization. The feasibility and challenges of CCTV-camera-based hand hygiene recognition are discussed. The results may contribute to design a hand hygiene scoring and alert system as part of the IoT system in hospitals. The hospital data and code are available at https://github.com/SunnySideUp11/ICU-MH-20.