A narrative review of the relationship between head and neck cancer and obstructive sleep apnea: Clinical studies and statistical analysis.

Obstructive sleep apnea (OSA) is an underestimated and overlooked comorbidity in head and neck cancer (HNC) care. Refining HNC-OSA management requires an improved grasp of the HNC-OSA relationship. Thus, this paper reviews the current course of HNC therapy, causal and associative relationships before and after treatment, and statistical methods quantifying HNC-OSA interactions. This evaluation serves a dual purpose: to support oncologists and sleep physicians in improving the treatment outcomes of patients undergoing HNC treatment by considering OSA as a comorbidity and to assist researchers in selecting suitable analytical models for investigating the correlation between OSA and HNC. The investigation confirms a positive correlation between the apnea-hypopnea index (AHI) and primary tumor size, consistent with prior findings. Case studies also reported new evidence of lipoma and head-neck tumors triggering OSA, and sleep apnea surgery prompting tumor development. This paper provides an overview of existing statistical models and offers suggestions for model selection and a framework for designing experiments that delve into research questions surrounding the link between OSA and HNC across various stages of cancer treatment. Despite progress, understanding the HNC-OSA interplay remains incomplete due to limited histological, molecular, and clinical data. Future studies with longitudinal data are crucial for comprehensive insights.

Preparation and characterization of spiked gold nanobipyramids and its antibacterial effect on methicillin-resistant Staphylococcus aureus and methicillin-sensitive Staphylococcus aureus.

BACKGROUND: This paper reports the preparation of a new family of spiked gold nanoparticles, spiked gold nanobipyramids (SNBPs). This protocol includes the process to synthesize gold nanobipyramids (NBPs) using combined seed-mediated and microwave-assisted method and procedure to form spikes on whole surface of gold nanobipyramid. We also evaluated the antibacterial activity against both methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive Staphylococcus aureus (MSSA) in various concentrations of SNBPs and NBPs by well diffusion assay, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) determination. The effect of SNBPs on exposed bacteria was observed by scanning electron microscopy. RESULTS: The UV-Vis of purified NBPs exhibited two absorption bands located at 550 nm and 849 nm with yield of bipyramidal particles more than 90%. The average size of NBPs was 76.33 ± 10.11 nm in length and 26.57 ± 2.25 nm in diameter, respectively, while SNBPs were prolongated in length and achieved 182.37 ± 21.74 nm with multi-branches protruding whole surface areas. In antibacterial evaluations, SNBPs and NBPs showed antibacterial activity with MIC of 6.25 µl/ml and 12.5 µl/ml, respectively, for MSSA while 12.5 µl/ml and 25 µl/ml, respectively, for MRSA. Besides, MBC values of SNBPs and NBPs were found to be 12.5 µl/ml and 25 µl/ml, respectively, against MSSA while 25 µl/ml and 50 µl/ml, respectively, against MRSA. Furthermore, scanning electron microscopy observation showed the mechanism that SNBPs damaged the outer membrane, released cytoplasm, and altered the normal morphology of MRSA and MSSA, leading to bacterial death. CONCLUSIONS: This report suggests that these SNBPs are potential antibacterial agents that can be applied as antibacterial materials to inhibit the growth of human bacterial pathogen infections related to antibiotic-resistant bacteria.

Multifractality in Surface Potential for Cancer Diagnosis.

Recent advances in high-resolution biomedical imaging have improved cancer diagnosis, focusing on morphological, electrical, and biochemical properties of cells and tissues, scaling from cell clusters down to the molecular level. Multiscale imaging revealed high complexity that requires advanced data processing methods of multifractal analysis. We performed label-free multiscale imaging of surface potential variations in human ovarian cancer cells using Kelvin probe force microscopy (KPFM). An improvement in the differentiation between nonmalignant and cancerous cells by multifractal analysis using adaptive versus median threshold for image binarization was demonstrated. The results reveal the multifractality of cancer cells as a new biomarker for cancer diagnosis.

Exosomes Derived from Human Umbilical Cord Mesenchymal Stem Cells Enhance Angiogenesis Through Upregulation of the VWF and Flk1 Genes in Endothelial Cells.

INTRODUCTION: Exosomes derived from mesenchymal stem cells (MSCs) are crucial mediators of the paracrine effects as well as tissue repair and have promising clinical applications. They enhance tissue regeneration by reducing inflammatory responses, enhancing proliferation, inhibiting apoptosis, and stimulating angiogenesis. This study aimed to evaluate the mechanism of angiogenesis supported by exosomes derived from MSCs. METHODS: Exosomes were isolated via ultracentrifugation of a conditioned medium collected from human umbilical cord MSC (hUCMSC) cultures. These exosomes were characterized using transmission electron microscopy, and the expression of specific markers (CD9, CD81, and CD63) was evaluated. To understand the mechanism of angiogenesis, we evaluated the effects of exosomes in endothelial cells (HUVECs). The obtained exosomes were supplemented at a dose of 20 µg/mL into two kinds of culture media for HUVECs (M200 medium and endothelial cell growth medium), while phosphate-buffered saline was added to these media as a control. The effects of the exosomes were evaluated based on the formation of a tubular structure in the culture and the expression of angiogenic genes (MMP-2, Ephrin B2, Ephrin B4, Flk1, Flt1, VWF, VE-cadherin, CD31, ANG1, ANG2, and HGF) via RT-PCR. RESULTS: The exosomes were obtained from the hUCMSCs at a concentration of 0.7 ± 0.029 µg/mL. They accelerated the formation of new blood vessels by upregulating HGF, VWF, CD31, Flt1, and Flk1 (especially VWF and Flt1). CONCLUSION: Exosomes derived from hUCMSCs can promote angiogenesis through upregulation of VWF and Flt1 in endothelial cells.

A domain-knowledge modeling of hospital-acquired infection risk in Healthcare personnel from retrospective observational data: A case study for COVID-19.

INTRODUCTION: Hospital-acquired infections of communicable viral diseases (CVDs) have been posing a tremendous challenge to healthcare workers globally. Healthcare personnel (HCP) is facing a consistent risk of viral infections, and subsequently higher rates of morbidity and mortality. MATERIALS AND METHODS: We proposed a domain-knowledge-driven infection risk model to quantify the individual HCP and the population-level risks. For individual-level risk estimation, a time-variant infection risk model is proposed to capture the transmission dynamics of CVDs. At the population-level, the infection risk is estimated using a Bayesian network model constructed from three feature sets, including individual-level factors, engineering control factors, and administrative control factors. For model validation, we investigated the case study of the Coronavirus disease, in which the individual-level and population-level infection risk models were applied. The data were collected from various sources such as COVID-19 transmission databases, health surveys/questionaries from medical centers, U.S. Department of Labor databases, and cross-sectional studies. RESULTS: Regarding the individual-level risk model, the variance-based sensitivity analysis indicated that the uncertainty in the estimated risk was attributed to two variables: the number of close contacts and the viral transmission probability. Next, the disease transmission probability was computed using a multivariate logistic regression applied for a cross-sectional HCP data in the UK, with the 10-fold cross-validation accuracy of 78.23%. Combined with the previous result, we further validated the individual infection risk model by considering six occupations in the U.S. Department of Labor O*Net database. The occupation-specific risk evaluation suggested that the registered nurses, medical assistants, and respiratory therapists were the highest-risk occupations. For the population-level risk model validation, the infection risk in Texas and California was estimated, in which the infection risk in Texas was lower than that in California. This can be explained by California's higher patient load for each HCP per day and lower personal protective equipment (PPE) sufficiency level. CONCLUSION: The accurate estimation of infection risk at both individual level and population levels using our domain-knowledge-driven infection risk model will significantly enhance the PPE allocation, safety plans for HCP, and hospital staffing strategies.

The effects of the COVID-19 lockdown on patients with chronic cardiovascular disease in Vietnam.

INTRODUCTION: We evaluated the impact of the lockdown policy during the COVID-19 pandemic on cardiovascular outpatients of a cardiology clinic in Vietnam from April to June 2020. We estimated the occurrence of different cardiovascular problems in general and the stability of blood pressure. METHODOLOGY: During the Covid-19 outbreak in Vietnam, we conducted a cross-sectional study to evaluate its impact on blood pressure stability of hypertensive patients treated as outpatients at the clinic of the University Medical Center (UMC), Ho Chi Minh City. RESULTS: The mean age of the recruited 493 patients was 62.2 ± 10.2 years. The stable blood pressure group consisted of 87% patients, while the unstable blood pressure group consisted of 13% patients. We found that 68% of the study population attended their follow-up appointments as scheduled: 87% with stable blood pressure versus only 13% with unstable blood pressure. Significant differences were noticed in body weight changes and cardiovascular problems between the two groups: body weight increase (22.6% vs. 10.2%), body weight decrease (3.2% vs. 6.7%), worsening of cardiovascular problems (35.5% vs. 17.9%) in the unstable and stable blood pressure groups, respectively. Multivariable regression analysis reflected the impact of the increase in body weight and occurrence of cardiovascular problems on the patients with unstable blood pressure. CONCLUSIONS: Our study provided concrete proof of the impact of the lockdown on chronic patients, which should warrant further surveys, and evaluation of the lockdown policy.

Temporal Associations Between Daytime Napping and Nocturnal Sleep: An Exploration of Random Slopes.

BACKGROUND: Restricting daytime naps is a common sleep hygiene recommendation to improve nocturnal sleep, but research on whether napping is related to sleep is mixed. The current literature is limited in that day level, bidirectional associations have not been tested in college students, and existing studies have not sufficiently examined the role of individual differences in these daily associations. PURPOSE: The current study addressed these limitations by assessing the temporal associations between self-reported daytime nap duration and objectively assessed nocturnal sleep, and whether these associations were moderated by chronotype or nap frequency, in college students. METHODS: Participants (N = 384) self-reported nap duration and wore an actiwatch to measure nocturnal sleep for 14 consecutive days and nights. Mixed linear models were used to test the daily associations between daytime nap duration and total sleep time (TST), sleep onset latency (SOL), sleep efficiency (SE), and wake after sleep onset (WASO). In addition, random slope modeling was used to test whether these associations significantly varied between participants. RESULTS: Longer nap duration was significantly associated with greater WASO, lower SE, and longer SOL. Shorter TST, shorter WASO, and greater SE were related to longer next-day nap duration. CONCLUSIONS: There were several significant associations between daytime napping and nocturnal sleep, and nap frequency significantly moderated the association between TST and next-day nap duration. Future research should test daily and contextual moderators of daytime napping and nocturnal sleep, which could refine sleep hygiene efforts by identifying individuals for whom recommendations would be most helpful.

Design and Analysis of Low-Power and High Speed Approximate Adders Using CNFETs.

Adders are constituted as the fundamental blocks of arithmetic circuits and are considered important for computation devices. Approximate computing has become a popular and developing area, promising to provide energy-efficient circuits with low power and high performance. In this paper, 10T approximate adder (AA) and 13T approximate adder (AA) designs using carbon nanotube field-effect transistor (CNFET) technology are presented. The simulation for the proposed 10T approximate adder and 13T approximate adder designs were carried out using the HSPICE tool with 32 nm CNFET technology. The metrics, such as average power, power-delay product (PDP), energy delay product (EDP) and propagation delay, were carried out through the HSPICE tool and compared to the existing circuit designs. The supply voltage Vdd provided for the proposed circuit designs was 0.9 V. The results indicated that among the existing full adders and approximate adders found in the review of adders, the proposed circuits consumed less PDP and minimum power with more accuracy.

Culture and Differentiation of Human Umbilical Cord-Derived Mesenchymal Stem Cells on Growth Factor-Rich Fibrin Scaffolds to Produce Engineered Cartilages.

INTRODUCTION: After injuries, the cartilage healing capacity is limited owing to its nature as a particular connective tissue without blood vessels, lymphatics, or nerves. The creation of artificial cartilage tissue mimics the biological properties of native cartilage and can reduce the need for donated tissue. Fibrin is a type of biodegradable scaffold that has great potential in tissue engineering applications. It can become good material for cell adhesion and proliferation in vitro. Therefore, this study aimed to create a cartilage tissue in vitro using umbilical cord-derived mesenchymal stem cells (UCMSC) and growth factor-rich fibrin (GRF) scaffolds. METHODS: UCMSCs were isolated and expanded, and platelet-rich plasma (PRP) preparations were performed following previously published protocols. PRP was activated (aPRP) by a 0.45-µm syringe filter to release growth factors inside the platelets. Each 2.105 of the UCMSCs were suspended in 2 ml of aPRP to make the mixture of MSC and PRP (MSC-PRP). Then, Ca2+ solution was added to this mixture to produce the fibril scaffold with UCMSCs inside. UCMSCs' adhesion and proliferation inside the scaffold were evaluated by observation under inverted microscopy, H-E staining, MTT assays, and scanning electron microscopy (SEM). The fibril structure containing UCMSCs was cultured, and chondrogenesis was induced using commercial chondrogenesis media for 21 days (iMSC-GRF). The differentiation in efficacy toward cartilage was evaluated based on the accumulation of aggrecan (acan), glycosaminoglycans (GAGs), and collagen type II (Col II). RESULTS: The results showed that we successfully created a cartilage tissue with some characteristics that mimic the properties of natural cartilage. The engineered cartilage tissue was positive with some cartilage protein, such as acan, GAG, and Coll II. In vitro cartilage presented some natural chondrocyte-like cells. The artificial cartilage tissue was positive for CD14, CD34, CD90, CD105, and HLA-DR and negative for CD44, CD45, and CD73. CONCLUSION: These results showed that using UCMSCs and growth factor-rich fibril from platelet-rich plasma was feasible to produce engineered cartilage tissue for further experiments or clinical usage.

Treatment of Osteochondral Femoral Head Defect by Human Umbilical Cord Mesenchymal Stem Cell Sheet Transplantation: An Experimental Study in Rats.

INTRODUCTION: Articular cartilage is limited in self-repair following injuries due to avascular, lymphatic, and nerve absence. Recent treatments for cartilage injuries, such as physical therapy, anti-inflammatory medication, chondrocyte implantation, and joint replacement, still have limitations. This study aimed to evaluate the treatment efficacy of human umbilical cord-derived mesenchymal stem cell sheet (UCMSCS) transplantation in rat models of the osteochondral femoral head defect. METHODS: Models of osteochondral femoral head defect were produced in rats by drilling in order to reach the femoral bone tissue through the cartilage layer. Then, UCMSCS was implanted in the created cartilage lesion. The treatment efficacy was monitored by X-ray imaging. The cartilage regeneration was evaluated based on the hematoxylin and eosin staining, and proteoglycan accumulation was detected by staining Safranin O and Fast Green. The physiological, weight, or movement activity of rats were recorded during the treatment period. RESULTS: UCMSCS transplantation showed positive effects on the cartilage regeneration in osteochondral femoral head defect grade 4 (according to ICRS score/grade). Particularly, after 12 weeks of implantation of UCMSCS, the defect was filled with hyaline cartilage-like cells and accumulated a large density of proteoglycan. The osteochondral defect score significantly increased in the treated rats compared to the untreated rats (11.67 ± 0.6 and 9.67 ± 0.6, respectively) (p < 0.05). The histological score also increased in treated rats compared to untreated rats (21.33 ± 1.53 vs. 18.00 ± 1.00) (p < 0.0001). The accumulation of proteoglycan was higher in treated rats (20.50 ± 2.23) than untreated rats (5.38 ± 0.36) (p < 0.05). There was no change in the physiological activities between treated and untreated rats recorded during the study. CONCLUSION: MSCS transplantation could promote regeneration in advanced cartilage injury.

Probabilistic domain-knowledge modeling of disorder pathogenesis for dynamics forecasting of acute onset.

Disease pathogenesis, a type of domain knowledge about biological mechanisms leading to diseases, has not been adequately encoded in machine-learning-based medical diagnostic models because of the inter-patient variabilities and complex dependencies of the underlying pathogenetic mechanisms. We propose 1) a novel pathogenesis probabilistic graphical model (PPGM) to quantify the dynamics underpinning patient-specific data and pathogenetic domain knowledge, 2) a Bayesian-based inference paradigm to answer the medical queries and forecast acute onsets. The PPGM model consists of two components: a Bayesian network of patient attributes and a temporal model of pathogenetic mechanisms. The model structure was reconstructed from expert knowledge elicitation, and its parameters were estimated using Variational Expectation-Maximization algorithms. We benchmarked our model with two well-established hidden Markov models (HMMs) - Input-output HMM (IO-HMM) and Switching Auto-Regressive HMM (SAR-HMM) - to evaluate the computational costs, forecasting performance, and execution time. Two case studies on Obstructive Sleep Apnea (OSA) and Paroxysmal Atrial Fibrillation (PAF) were used to validate the model. While the performance of the parameter learning step was equivalent to those of IO-HMM and SAR-HMM models, our model forecasting ability was outperforming those two models. The merits of the PPGM model are its representation capability to capture the dynamics of pathogenesis and perform medical inferences and its interpretability for physicians. The model has been used to perform medical queries and forecast the acute onset of OSA and PAF. Additional applications of the model include prognostic healthcare and preventive personalized treatments.

Throughput Analysis of Buffer-Aided Decode-and-Forward Wireless Relaying with RF Energy Harvesting.

In this paper, we investigated a buffer-aided decode-and-forward (DF) wireless relaying system over fading channels, where the source and relay harvest radio-frequency (RF) energy from a power station for data transmissions. We derived exact expressions for end-to-end throughput considering half-duplex (HD) and full-duplex (FD) relaying schemes. The numerical results illustrate the throughput and energy efficiencies of the relaying schemes under different self-interference (SI) cancellation levels and relay deployment locations. It was demonstrated that throughput-optimal relaying is not necessarily energy efficiency-optimal. The results provide guidance on optimal relaying network deployment and operation under different performance criteria.

The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data.

The Center for Hydrometeorology and Remote Sensing (CHRS) has created the CHRS Data Portal to facilitate easy access to the three open data licensed satellite-based precipitation datasets generated by our Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) system: PERSIANN, PERSIANN-Cloud Classification System (CCS), and PERSIANN-Climate Data Record (CDR). These datasets have the potential for widespread use by various researchers, professionals including engineers, city planners, and so forth, as well as the community at large. Researchers at CHRS created the CHRS Data Portal with an emphasis on simplicity and the intention of fostering synergistic relationships with scientists and experts from around the world. The following paper presents an outline of the hosted datasets and features available on the CHRS Data Portal, an examination of the necessity of easily accessible public data, a comprehensive overview of the PERSIANN algorithms and datasets, and a walk-through of the procedure to access and obtain the data.

A Probability-Based Algorithm Using Image Sensors to Track the LED in a Vehicle Visible Light Communication System.

This paper proposes a probability-based algorithm to track the LED in vehicle visible light communication systems using a camera. In this system, the transmitters are the vehicles' front and rear LED lights. The receivers are high speed cameras that take a series of images of the LEDs. ThedataembeddedinthelightisextractedbyfirstdetectingthepositionoftheLEDsintheseimages. Traditionally, LEDs are detected according to pixel intensity. However, when the vehicle is moving, motion blur occurs in the LED images, making it difficult to detect the LEDs. Particularly at high speeds, some frames are blurred at a high degree, which makes it impossible to detect the LED as well as extract the information embedded in these frames. The proposed algorithm relies not only on the pixel intensity, but also on the optical flow of the LEDs and on statistical information obtained from previous frames. Based on this information, the conditional probability that a pixel belongs to a LED is calculated. Then, the position of LED is determined based on this probability. To verify the suitability of the proposed algorithm, simulations are conducted by considering the incidents that can happen in a real-world situation, including a change in the position of the LEDs at each frame, as well as motion blur due to the vehicle speed.

VLC-Based Positioning System for an Indoor Environment Using an Image Sensor and an Accelerometer Sensor.

Recently, it is believed that lighting and communication technologies are being replaced by high power LEDs, which are core parts of the visible light communication (VLC) system. In this paper, by taking advantages of VLC, we propose a novel design for an indoor positioning system using LEDs, an image sensor (IS) and an accelerometer sensor (AS) from mobile devices. The proposed algorithm, which provides a high precision indoor position, consists of four LEDs mounted on the ceiling transmitting their own three-dimensional (3D) world coordinates and an IS at an unknown position receiving and demodulating the signals. Based on the 3D world coordinates and the 2D image coordinate of LEDs, the position of the mobile device is determined. Compared to existing algorithms, the proposed algorithm only requires one IS. In addition, by using an AS, the mobile device is allowed to have arbitrary orientation. Last but not least, a mechanism for reducing the image sensor noise is proposed to further improve the accuracy of the positioning algorithm. A simulation is conducted to verify the performance of the proposed algorithm.