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Abstract Background Cost-effectiveness analyses rarely offer useful insights to policy decisions unless their results are compared against a benchmark threshold. The cost-effectiveness threshold (CET) represents the maximum acceptable monetary value for achieving a unit of health gain. This study aimed to identify CET values on a global scale, provide an overview of using multiple CETs, and propose a country-specific CET framework specifically tailored for Egypt. The proposed framework aims to consider the globally identified CETs, analyze global trends, and consider the local structure of Egypt’s healthcare system. Methods We conducted a literature review to identify CET values, with a particular focus on understanding the basis of differentiation when multiple thresholds are present. CETs of different countries were reviewed from secondary sources. Additionally, we assembled an expert panel to develop a national CET framework in Egypt and propose an initial design. This was followed by a multistakeholder workshop, bringing together representatives of different governmental bodies to vote on the threshold value and finalize the recommended framework. Results The average CET, expressed as a percentage of the gross domestic product (GDP) per capita across all countries, was 135%, with a range of 21 to 300%. Interestingly, while the absolute value of CET increased with a country’s income level, the average CET/GDP per capita showed an inverse relationship. Some countries applied multiple thresholds based on disease severity or rarity. In the case of Egypt, the consensus workshop recommended a threshold ranging from one to three times the GDP per capita, taking into account the incremental relative quality-adjusted life years (QALY) gain. For orphan medicines, a CET multiplier between 1.5 and 3.0, based on the disease rarity, was recommended. A two-times multiplier was proposed for the private reimbursement threshold compared to the public threshold. Conclusion The CET values in most countries appear to be closely related to the GDP per capita. Higher-income countries tend to use a lower threshold as a percentage of their GDP per capita, contrasted with lower-income countries. In Egypt, experts opted for a multiple CET framework to assess the value of health technologies in terms of reimbursement and pricing.

Recently, the attention to exploring and applying probiotics has been increased. Probiotics are living microscopic organisms that have valuable impacts on health when consumed in adequate amounts. One of the most popular widespread utilized probiotics for many years until now is the Lactobacillus species which exemplifies the hugest heterogeneous group among the lactic acid bacteria (LAB) that normally occupy many environments that contain high nutrient levels such as soil, humans, waters, plants, animals and even air without causing any illness. The purpose of this work is to review and demonstrate the wide diversity of lactobacilli isolation sources and related health benefits applications of the strains discovered in order to break the familiar sources of lactobacillus spp., thereby encouraging more research into unconventional sources and opening up opportunities for clinical applications of Lactobacillus spp. As a result, the isolation sources of lactobacillus spp. in this review have been split into two groups based on the environmental condition, including fermented and non-fermented habitats described as lactobacilli probiotic sources. The unique Lactobacilli isolated from various sources are regarded as potential therapies for a variety of illnesses and physiological abnormalities, including immunomodulation, suppression of carcinogenesis, and cholesterol reduction, in addition to their capacity to guard against infections. This will be highly significant for revealing updated information about Lactobacillus spp. that has attracted considerable attention due to its potential application in clinical practices.

Antibiotic resistance is a major risk to human health worldwide due to antibiotic- and multidrug-resistant bacteria, especially in the case of serious infections, which limits the availability of antimicrobial treatment options. Focusing on the bacterial resistance mechanisms against antibiotics and the conventional strategies used to combat antimicrobial resistance, this review highlights the history of antibiotics and their target mechanisms, mentions the strategy limitations, provides the most recent novel alternative therapies to combat resistance, and illustrates their mode of action and applications that may treat several infectious diseases caused by bacterial resistance. Finally, this paper mentions future prospects that we believe would make a considerable difference in the microbial resistance battle. Novel antibiotic alternative therapies, including nanomaterial therapy, antimicrobial photodynamic therapy, hybrid antimicrobial therapy, and phage therapy, are covered in this review.

High-resolution cervical auscultation (HRCA) is an emerging noninvasive and accessible option to assess swallowing by relying upon accelerometry and sound sensors. HRCA has shown tremendous promise and accuracy in identifying and predicting swallowing physiology and biomechanics with accuracies equivalent to trained human judges. These insights have historically been available only through instrumental swallowing evaluation methods, such as videofluoroscopy and endoscopy. HRCA uses supervised learning techniques to interpret swallowing physiology from the acquired signals, which are collected during radiographic assessment of swallowing using barium contrast. Conversely, bedside swallowing screening is typically conducted in non-radiographic settings using only water. This poses a challenge to translating and generalizing HRCA algorithms to bedside screening due to the rheological differences between barium and water. To address this gap, we proposed a cross-domain transformation framework that uses cycle generative adversarial networks to convert HRCA signals of water swallows into a domain compatible with the barium swallows-trained HRCA algorithms. The proposed framework achieved a cross-domain transformation accuracy that surpassed 90%. The authenticity of the generated signals was confirmed using a binary classifier to confirm the framework's capability to produce indistinguishable signals. This framework was also assessed for retaining swallow physiological and biomechanical properties in the signals by applying an existing model from the literature that identifies the opening and closure of the upper esophageal sphincter. The outcomes of this model showed nearly identical results between the generated and original signals. These findings suggest that the proposed transformation framework is a feasible avenue to advance HCRA towards clinical deployment for water-based swallowing screenings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Importance: Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality., Objective: To investigate the association between image-based built environment and the prevalence of cardiometabolic disease in urban cities., Design, Setting, and Participants: This cross-sectional study used features extracted from Google satellite images (GSI) to measure the built environment and link them with prevalence of cardiometabolic disease. Convolutional neural networks, light gradient-boosting machines, and activation maps were used to assess the association with health outcomes and identify feature associations with coronary heart disease (CHD), stroke, and chronic kidney disease (CKD). The study obtained aerial images from GSI covering census tracts in 7 cities (Cleveland, Ohio; Fremont, California; Kansas City, Missouri; Detroit, Michigan; Bellevue, Washington; Brownsville, Texas; and Denver, Colorado). The study used census tract-level data from the US Centers for Disease Control and Prevention's 500 Cities project. The data were originally collected from the Behavioral Risk Factor Surveillance System that surveyed people 18 years and older across the country. Analyses were conducted from February to December 2022., Exposures: GSI images of built environment and cardiometabolic disease prevalence., Main Outcomes and Measures: Census tract-level estimated prevalence of CHD, stroke, and CKD based on image-based built environment features., Results: The study obtained 31 786 aerial images from GSI covering 789 census tracts. Built environment features extracted from GSI using machine learning were associated with prevalence of CHD (R2 = 0.60), stroke (R2 = 0.65), and CKD (R2 = 0.64). The model performed better at distinguishing differences between cardiometabolic prevalence between cities than within cities (eg, highest within-city R2 = 0.39 vs between-city R2 = 0.64 for CKD). Addition of GSI features both outperformed and improved the model that only included age, sex, race, income, education, and composite indices for social determinants of health (R2 = 0.83 vs R2 = 0.76 for CHD; P <.001). Activation maps from the features revealed certain health-related built environment such as roads, highways, and railroads and recreational facilities such as amusement parks, arenas, and baseball parks., Conclusions and Relevance: In this cross-sectional study, a significant portion of cardiometabolic disease prevalence was associated with GSI-based built environment using convolutional neural networks.

Monitoring of ingestive activities is critically important for managing the health and wellness of individuals with various health conditions, including the elderly, diabetics, and individuals seeking better weight control. Monitoring swallowing events can be an ideal surrogate for developing streamlined methods for effective monitoring and quantification of eating or drinking events. Swallowing is an essential process for maintaining life. This seemingly simple process is the result of coordinated actions of several muscles and nerves in a complex fashion. In this study, we introduce automated methods for the detection and quantification of various eating and drinking activities. Wireless surface electromyography (sEMG) was used to detect chewing and swallowing from sEMG signals obtained from the sternocleidomastoid muscle, in addition to signals obtained from a wrist-mounted IMU sensor. A total of 4675 swallows were collected from 55 participants in the study. Multiple methods were employed to estimate bolus volumes in the case of fluid intake, including regression and classification models. Among the tested models, neural networks-based regression achieved an R 2 of 0.88 and a root mean squared error of 0.2 (minimum bolus volume was 10 ml). Convolutional neural networks-based classification (when considering each bolus volume as a separate class) achieved an accuracy of over 99% using random cross-validation and around 66% using cross-subject validation. Multiple classification methods were also used for solid bolus type detection, including SVM and decision trees (DT), which achieved an accuracy above 99% with random validation and above 94% in cross-subject validation. Finally, regression models with both random and cross-subject validation were used for estimating the solid bolus volume with an R 2 value that approached 1 and root mean squared error values as low as 0.00037 (minimum solid bolus weight was 3 gm). These reported results lay the foundation for a cost-effective and non-invasive method for monitoring swallowing activities which can be extremely beneficial in managing various chronic health conditions, such as diabetes and obesity., (© 2024. The Author(s).)

Background and Aims: Built environment plays an important role in the development of cardiovascular disease. Tools to evaluate the built environment using machine vision and informatic approaches have been limited. This study aimed to investigate the association between machine vision-based built environment and prevalence of cardiometabolic disease in US cities., Methods: This cross-sectional study used features extracted from Google Street View (GSV) images to measure the built environment and link them with prevalence of coronary heart disease (CHD). Convolutional neural networks, linear mixed-effects models, and activation maps were utilized to predict health outcomes and identify feature associations with CHD at the census tract level. The study obtained 0.53 million GSV images covering 789 census tracts in seven US cities (Cleveland, OH; Fremont, CA; Kansas City, MO; Detroit, MI; Bellevue, WA; Brownsville, TX; and Denver, CO)., Results: Built environment features extracted from GSV using deep learning predicted 63% of the census tract variation in CHD prevalence. The addition of GSV features improved a model that only included census tract-level age, sex, race, income, and education or composite indices of social determinant of health. Activation maps from the features revealed a set of neighbourhood features represented by buildings and roads associated with CHD prevalence., Conclusions: In this cross-sectional study, the prevalence of CHD was associated with built environment factors derived from GSV through deep learning analysis, independent of census tract demographics. Machine vision-enabled assessment of the built environment could potentially offer a more precise approach to identify at-risk neighbourhoods, thereby providing an efficient avenue to address and reduce cardiovascular health disparities in urban environments., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Developing K-ion conducting solid-state electrolytes (SSEs) plays a critical role in the safe implementation of potassium batteries. In this work, a chalcogenide-based potassium ion SSE is reported, K 3 SbSe 4 , which adopts a trigonal structure at room temperature. Single-crystal structural analysis reveals a trigonal-to-cubic phase transition at the low temperature of 50 °C, which is the lowest among similar compounds and thus provides easy access to the cubic phase. The substitution of barium for potassium in K 3 SbSe 4 leads to the creation of potassium vacancies, expansion of lattice parameters, and a transformation from a trigonal phase to a cubic phase. As a result, the maximum conductivity of K 3-2 x Ba x SbSe 4 reaches around 0.1 mS cm -1 at 40 °C for K 2.2 Ba 0.4 SbSe 4 , which is over two orders of magnitude higher than that of undoped K 3 SbSe 4 . This novel SSE is successfully employed in a K-O 2 battery operating at room temperature where a polymer-laminated K 2.2 Ba 0.4 SbSe 4 pellet serves as a separator between the oxygen cathode and the potassium metal anode. Effective protection of the K metal anode against corrosion caused by O 2 is demonstrated., (© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.)

Objective: Dysphagia management relies on the evaluation of the temporospatial kinematic events of swallowing performed in videofluoroscopy (VF) by trained clinicians. The upper esophageal sphincter (UES) opening distension represents one of the important kinematic events that contribute to healthy swallowing. Insufficient distension of UES opening can lead to an accumulation of pharyngeal residue and subsequent aspiration which in turn can lead to adverse outcomes such as pneumonia. VF is usually used for the temporal and spatial evaluation of the UES opening; however, VF is not available in all clinical settings and may be inappropriate or undesirable for some patients. High resolution cervical auscultation (HRCA) is a noninvasive technology that uses neck-attached sensors and machine learning to characterize swallowing physiology by analyzing the swallow-induced vibrations/sounds in the anterior neck region. We investigated the ability of HRCA to noninvasively estimate the maximal distension of anterior-posterior (A-P) UES opening as accurately as the measurements performed by human judges from VF images., Methods and Procedures: Trained judges performed the kinematic measurement of UES opening duration and A-P UES opening maximal distension on 434 swallows collected from 133 patients. We used a hybrid convolutional recurrent neural network supported by attention mechanisms which takes HRCA raw signals as input and estimates the value of the A-P UES opening maximal distension as output., Results: The proposed network estimated the A-P UES opening maximal distension with an absolute percentage error of 30% or less for more than 64.14% of the swallows in the dataset., Conclusion: This study provides substantial evidence for the feasibility of using HRCA to estimate one of the key spatial kinematic measurements used for dysphagia characterization and management. Clinical and Translational Impact Statement: The findings in this study have a direct impact on dysphagia diagnosis and management through providing a non-invasive and cheap way to estimate one of the most important swallowing kinematics, the UES opening distension, that contributes to safe swallowing. This study, along with other studies that utilize HRCA for swallowing kinematic analysis, paves the way for developing a widely available and easy-to-use tool for dysphagia diagnosis and management.

Disparities in premature cardiovascular mortality (PCVM) have been associated with socioeconomic, behavioral, and environmental risk factors. Understanding the "phenotypes", or combinations of characteristics associated with the highest risk of PCVM, and the geographic distributions of these phenotypes is critical to targeting PCVM interventions. This study applied the classification and regression tree (CART) to identify county phenotypes of PCVM and geographic information systems to examine the distributions of identified phenotypes. Random forest analysis was applied to evaluate the relative importance of risk factors associated with PCVM. The CART analysis identified seven county phenotypes of PCVM, where high-risk phenotypes were characterized by having greater percentages of people with lower income, higher physical inactivity, and higher food insecurity. These high-risk phenotypes were mostly concentrated in the Black Belt of the American South and the Appalachian region. The random forest analysis identified additional important risk factors associated with PCVM, including broadband access, smoking, receipt of Supplemental Nutrition Assistance Program benefits, and educational attainment. Our study demonstrates the use of machine learning approaches in characterizing community-level phenotypes of PCVM. Interventions to reduce PCVM should be tailored according to these phenotypes in corresponding geographic areas., (© 2023. The Author(s).)

Dysphagia occurs secondary to a variety of underlying etiologies and can contribute to increased risk of adverse events such as aspiration pneumonia and premature mortality. Dysphagia is primarily diagnosed and characterized by instrumental swallowing exams such as videofluoroscopic swallowing studies. videofluoroscopic swallowing studies involve the inspection of a series of radiographic images for signs of swallowing dysfunction. Though effective, videofluoroscopic swallowing studies are only available in certain clinical settings and are not always desirable or feasible for certain patients. Because of the limitations of current instrumental swallow exams, research studies have explored the use of acceleration signals collected from neck sensors and demonstrated their potential in providing comparable radiation-free diagnostic value as videofluoroscopic swallowing studies. In this study, we used a hybrid deep convolutional recurrent neural network that can perform multi-level feature extraction (localized and across time) to annotate swallow segments automatically via multi-channel swallowing acceleration signals. In total, we used signals and videofluoroscopic swallowing study images of 3144 swallows from 248 patients with suspected dysphagia. Compared to other deep network variants, our network was superior at detecting swallow segments with an average area under the receiver operating characteristic curve value of 0.82 (95% confidence interval: 0.807-0.841), and was in agreement with up to 90% of the gold standard-labeled segments.

Background: Phelan-McDermid syndrome (PHMDS) is a rare genetic disorder mostly caused by haploinsufficincy of SHANK3 gene, and characterized by neonatal hypotonia, developmental delay, minor dysmorphic features, seizures and behavior problems. Literature of this syndrome is scanty and confusing, and represents a challenge for pediatricians, in terms of finding the correct diagnoses., Case Presentation: In a postnatal case with hypotonia and dysmorphic features a de novo ring chromosome r(22) leading to in parallel microdeletion and micro duplication in 22q13 was diagnosed by banding cytogenetics, and further characterized in detail by molecular cytogenetic and chromosomal microarray., Conclusion: Here a rare PHMDS case caused by a r(22) is presented. Less than 10 comparable cases are reported in the literature. The present case highlights the importance of conducting genetic counseling and appropriate genetic tests for newborns with mild dysmorphic features., (© 2022. The Author(s).)

Clinicians and researchers commonly judge the completeness of hyoid displacement from videofluoroscopic swallow study (VFSS) videos. Judgments made during the clinical exam are often subjective, and post-examination analysis reduces the measure's immediate value. This study aimed to determine the validity and feasibility of a visual, anatomically scaled benchmark for judging complete hyoid displacement during a VFSS. The third and fourth cervical vertebral bodies (C3 and C4) lie at roughly the same vertical position as the hyoid body and are strongly correlated with patient height. We hypothesized that anterior and superior displacement of the hyoid bone would approximate the height of one C3 or C4 body during safe swallows. Trained raters marked points of interest on C3, C4, and the hyoid body on 1414 swallows of adult patients with suspected dysphagia (n = 195) and 50 swallows of age-matched healthy participants (n = 17), and rated Penetration Aspiration Scale scores. Results indicated that the mean displacements of the hyoid bone were greater than one C3 unit in the superior direction for all swallows from patient and healthy participants, though significantly and clinically greater in healthy participant swallows (p < .001, d > .8). The mean anterior and superior displacements from patient and healthy participant swallows were greater than one C4 unit. Results show preliminary evidence that use of the C3 and/or C4 anatomic scalars can add interpretive value to the immediate judgment of hyoid displacement during the conduct of a clinical VFSS examination., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

There is growing enthusiasm to develop inexpensive, non-invasive, and portable methods that accurately assess swallowing and provide biofeedback during dysphagia treatment. High-resolution cervical auscultation (HRCA), which uses acoustic and vibratory signals from non-invasive sensors attached to the anterior laryngeal framework during swallowing, is a novel method for quantifying swallowing physiology via advanced signal processing and machine learning techniques. HRCA has demonstrated potential as a dysphagia screening method and diagnostic adjunct to VFSSs by determining swallowing safety, annotating swallow kinematic events, and classifying swallows between healthy participants and patients with a high degree of accuracy. However, its feasibility as a non-invasive biofeedback system has not been explored. This study investigated 1. Whether HRCA can accurately differentiate between non-effortful and effortful swallows; 2. Whether differences exist in Modified Barium Swallow Impairment Profile (MBSImP) scores (#9, #11, #14) between non-effortful and effortful swallows. We hypothesized that HRCA would accurately classify non-effortful and effortful swallows and that differences in MBSImP scores would exist between the types of swallows. We analyzed 247 thin liquid 3 mL command swallows (71 effortful) to minimize variation from 36 healthy adults who underwent standardized VFSSs with concurrent HRCA. Results revealed differences (p < 0.05) in 9 HRCA signal features between non-effortful and effortful swallows. Using HRCA signal features as input, decision trees classified swallows with 76% accuracy, 76% sensitivity, and 77% specificity. There were no differences in MBSImP component scores between non-effortful and effortful swallows. While preliminary in nature, this study demonstrates the feasibility/promise of HRCA as a biofeedback method for dysphagia treatment., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: Teleophthalmology has emerged as a convenient and cost-effective intervention to increase access to screening for diabetic retinopathy (DR), a disease that disproportionately affects socially disadvantaged communities. However, a few studies have directly compared the detection of eye disease by teleophthalmology between socially and geographically diverse communities. This study compared the rates and severity of diabetic eye disease, as detected by teleophthalmology, between safety net and non-Safety Net Hospitals (non-SNHs). Methods: Retrospective chart review of patients screened for DR at county Safety Net Hospitals (SNHs) and non-SNHs in 150 cities and 30 states. The rates of DR, macular edema, suspected cataract, suspected glaucoma, and suspected age-related macular degeneration were compared. Relative risk and severity of disease in the county SNH population were calculated. Images were graded by the same group of IRIS readers, who used at least one image per eye with a 45° field centered between the optic disc and the macula. Participants with ungradable screening images were excluded. Results: Ninety-four thousand three hundred twenty-nine participants were screened for eye disease from September 1, 2016 to August 31, 2017. Among the screened participants (54% female; mean [SD] age, 58.7 [12.9] years), overall disease detection was 31% in the county SNH population and 23.6% in the non-SNH population. Compared with the non-SNH population, the county SNH population was twice as likely to screen positive for three or more concurrent eye conditions (1.2% vs. 0.7%) and had increased prevalence of DR (20.2% vs. 16.2%), macular edema (4.9% vs. 3.4%), suspected glaucoma (9.1% vs. 4.3%), suspected cataract (9.6% vs. 4.8%), and proliferative DR (2.1% vs. 1.0%). Conclusions: Increased diabetic eye disease prevalence and severity among people seen at SNHs highlights the need for continued resources to screen, treat, and manage disease. Teleophthalmology continues to be an important tool in efforts to mitigate health inequities and address barriers faced by underserved communities.

Few research studies have investigated temporal kinematic swallow events in healthy adults to establish normative reference values. Determining cutoffs for normal and disordered swallowing is vital for differentially diagnosing presbyphagia, variants of normal swallowing, and dysphagia; and for ensuring that different swallowing research laboratories produce consistent results in common measurements from different samples within the same population. High-resolution cervical auscultation (HRCA), a sensor-based dysphagia screening method, has accurately annotated temporal kinematic swallow events in patients with dysphagia, but hasn't been used to annotate temporal kinematic swallow events in healthy adults to establish dysphagia screening cutoffs. This study aimed to determine: (1) Reference values for temporal kinematic swallow events, (2) Whether HRCA can annotate temporal kinematic swallow events in healthy adults. We hypothesized (1) Our reference values would align with a prior study; (2) HRCA would detect temporal kinematic swallow events as accurately as human judges. Trained judges completed temporal kinematic measurements on 659 swallows (N = 70 adults). Swallow reaction time and LVC duration weren't different (p > 0.05) from a previously published historical cohort (114 swallows, N = 38 adults), while other temporal kinematic measurements were different (p < 0.05), suggesting a need for further standardization to feasibly pool data analyses across laboratories. HRCA signal features were used as input to machine learning algorithms and annotated UES opening (69.96% accuracy), UES closure (64.52% accuracy), LVC (52.56% accuracy), and LV re-opening (69.97% accuracy); providing preliminary evidence that HRCA can noninvasively and accurately annotate temporal kinematic measurements in healthy adults to determine dysphagia screening cutoffs., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

We used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to evaluate a Stroke Prevention Team's readiness to prevent strokes in children with sickle cell anemia living in northern Nigeria. The NIH sponsored Stroke Prevention Trial in Nigeria included a goal of a sustainable stroke prevention program. The program's 1-year reach for transcranial Doppler screening was 14.7% (4710/32,000) of which 6.0% (281/4710) had abnormal velocities (≥200 cm/s). All participants with abnormal transcranial Doppler velocities were started on hydroxyurea (effectiveness). The leaders of all 5 hospitals agreed to adopt the program. After 1 year, program-implementation and maintenance rates were 100%, demonstrating the program's feasibility and short-term sustainability., Competing Interests: M.R.D.: had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. M.R.D.: designed the study. S.U.A. and M.A.T.: provided the TCD training. A.H.D., H.B.-M., H.I., A.T., A.A.S., B.W.J., S.G., Y.K., L.H., S.A., M.A.Z., and N.I.: administered the TCD screening. E.T. and L.J.: verified the neurological examinations. A.I.G., F.M.U., M.A.T., A.I.G., S.U.A., B.C.G., J.G., and D.L.G.: collected the data. D.L.G. and M.R.: performed the analyses. M.R.D., S.A., D.L.G., A.A.B., M.R.D.: interpreted the results. D.L.G., A.A.B., L.C.J., E.T., M.H.A., and M.R.D.: wrote the manuscript. Before submission, all authors reviewed the manuscript.The authors declare no conflict of interest., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc.)

Dysphagia, commonly referred to as abnormal swallowing, affects millions of people annually. If not diagnosed expeditiously, dysphagia can lead to more severe complications, such as pneumonia, nutritional deficiency, and dehydration. Bedside screening is the first step of dysphagia characterization and is usually based on pass/fail tests in which a nurse observes the patient performing water swallows to look for dysphagia overt signs such as coughing. Though quick and convenient, bedside screening only provides low-level judgment of impairment, lacks standardization, and suffers from subjectivity. Recently, high resolution cervical auscultation (HRCA) has been investigated as a less expensive and non-invasive method to diagnose dysphagia. It has shown strong preliminary evidence of its effectiveness in penetration-aspiration detection as well as multiple swallow kinematics. HRCA signals have traditionally been collected and investigated in conjunction with videofluoroscopy exams which are performed using barium boluses including thin liquid. An HRCA-based bedside screening is highly desirable to expedite the initial dysphagia diagnosis and overcome all the drawbacks of the current pass/fail screening tests. However, all research conducted for using HRCA in dysphagia is based on thin liquid barium boluses and thus not guaranteed to provide valid results for water boluses used in bedside screening. If HRCA signals show no significant differences between water and thin liquid barium boluses, then the same algorithms developed on thin liquid barium boluses used in diagnostic imaging studies, it can be then directly used with water boluses. This study investigates the similarities and differences between HRCA signals from thin liquid barium swallows compared to those signals from water swallows. Multiple features from the time, frequency, time-frequency, and information-theoretic domain were extracted from each type of swallow and a group of linear mixed models was tested to determine the significance of differences. Machine learning classifiers were fit to the data as well to determine if the swallowed material (thin liquid barium or water) can be correctly predicted from an unlabeled set of HRCA signals. The results demonstrated that there is no systematic difference between the HRCA signals of thin liquid barium swallows and water swallows. While no systematic difference was discovered, the evidence of complete conformity between HRCA signals of both materials was inconclusive. These results must be validated further to confirm conformity between the HRCA signals of thin liquid barium swallows and water swallows.

Purpose The prevalence of dysphagia in patients with neurodegenerative diseases (ND) is alarmingly high and frequently results in morbidity and accelerated mortality due to subsequent adverse events (e.g., aspiration pneumonia). Swallowing in patients with ND should be continuously monitored due to the progressive disease nature. Access to instrumental swallow evaluations can be challenging, and limited studies have quantified changes in temporal/spatial swallow kinematic measures in patients with ND. High-resolution cervical auscultation (HRCA), a dysphagia screening method, has accurately differentiated between safe and unsafe swallows, identified swallow kinematic events (e.g., laryngeal vestibule closure [LVC]), and classified swallows between healthy adults and patients with ND. This study aimed to (a) compare temporal/spatial swallow kinematic measures between patients with ND and healthy adults and (b) investigate HRCA's ability to annotate swallow kinematic events in patients with ND. We hypothesized there would be significant differences in temporal/spatial swallow measurements between groups and that HRCA would accurately annotate swallow kinematic events in patients with ND. Method Participants underwent videofluoroscopic swallowing studies with concurrent HRCA. We used linear mixed models to compare temporal/spatial swallow measurements ( n = 170 ND patient swallows, n = 171 healthy adult swallows) and deep learning machine-learning algorithms to annotate specific temporal and spatial kinematic events in swallows from patients with ND. Results Differences ( p < .05) were found between groups for several temporal and spatial swallow kinematic measures. HRCA signal features were used as input to machine-learning algorithms and annotated upper esophageal sphincter (UES) opening, UES closure, LVC, laryngeal vestibule reopening, and hyoid bone displacement with 66.25%, 85%, 68.18%, 70.45%, and 44.6% accuracy, respectively, compared to human judges' measurements. Conclusion This study demonstrates HRCA's potential in characterizing swallow function in patients with ND and other patient populations.

Clinicians evaluate swallow kinematic events by analyzing videofluoroscopy (VF) images for dysphagia management. The duration of upper esophageal sphincter opening (DUESO) is one important temporal swallow event, because reduced DUESO can result in pharyngeal residue and penetration/aspiration. VF is frequently used for evaluating swallowing but exposes patients to radiation and is not always feasible/readily available. High resolution cervical auscultation (HRCA) is a non-invasive, sensor-based dysphagia screening method that uses signal processing and machine learning to characterize swallowing. We investigated HRCA's ability to annotate DUESO and predict Modified Barium Swallow Impairment Profile (MBSImP) scores (component #14). We hypothesized that HRCA and machine learning techniques would detect DUESO with similar accuracy as human judges. Trained judges completed temporal kinematic measurements of DUESO on 719 swallows (116 patients) and 50 swallows (15 age-matched healthy adults). An MBSImP certified clinician completed MBSImP ratings on 100 swallows. A multi-layer convolutional recurrent neural network (CRNN) using HRCA signal features for input was used to detect DUESO. Generalized estimating equations models were used to determine statistically significant HRCA signal features for predicting DUESO MBSImP scores. A support vector machine (SVM) classifier and a leave-one-out procedure was used to predict DUESO MBSImP scores. The CRNN detected UES opening within a 3-frame tolerance for 82.6% of patient and 86% of healthy swallows and UES closure for 72.3% of patient and 64% of healthy swallows. The SVM classifier predicted DUESO MBSImP scores with 85.7% accuracy. This study provides evidence of HRCA's feasibility in detecting DUESO without VF images., (© 2020. Springer Science+Business Media, LLC, part of Springer Nature.)

High-resolution cervical auscultation (HRCA) is an emerging method for non-invasively assessing swallowing by using acoustic signals from a contact microphone, vibratory signals from an accelerometer, and advanced signal processing and machine learning techniques. HRCA has differentiated between safe and unsafe swallows, predicted components of the Modified Barium Swallow Impairment Profile, and predicted kinematic events of swallowing such as hyoid bone displacement, laryngeal vestibular closure, and upper esophageal sphincter opening with a high degree of accuracy. However, HRCA has not been used to characterize swallow function in specific patient populations. This study investigated the ability of HRCA to differentiate between swallows from healthy people and people with neurodegenerative diseases. We hypothesized that HRCA would differentiate between swallows from healthy people and people with neurodegenerative diseases with a high degree of accuracy. We analyzed 170 swallows from 20 patients with neurodegenerative diseases and 170 swallows from 51 healthy age-matched adults who underwent concurrent video fluoroscopy with non-invasive neck sensors. We used a linear mixed model and several supervised machine learning classifiers that use HRCA signal features and a leave-one-out procedure to differentiate between swallows. Twenty-two HRCA signal features were statistically significant (p < 0.05) for predicting whether swallows were from healthy people or from patients with neurodegenerative diseases. Using the HRCA signal features alone, logistic regression and decision trees classified swallows between the two groups with 99% accuracy, 100% sensitivity, and 99% specificity. This provides preliminary research evidence that HRCA can differentiate swallow function between healthy and patient populations., (© 2020. Springer Science+Business Media, LLC, part of Springer Nature.)

Ni based catalysts have been widely studied for H2 production due to the ability of Ni to break C-C and C-H bonds. In this work, we study inverse catalysts prepared by well-controlled sub-monolayer deposition of CeO2 nanocubes onto Ni thin films for ethanol steam reforming (ESR). Results show that controlling the coverage of CeO2 nanocubes on Ni enhances H2 production by more than an order of magnitude compared to pure Ni. Contrary to the idea that C deposits must be continuously oxidized for sustained H2 production, the surface of the most active catalysts show significant C deposition, yet no deactivation is observed. HAADF-STEM analysis reveals the formation of carbon filaments (CFILs), which propel Ni particles upward at the filament tips via a catalytic tip growth mechanism, resulting in a Ni@CFIL active phase for ESR. Near-ambient pressure XPS indicates that the Ni@CFIL active phase forms as a result of C gradients at the interface between regions of pure Ni metal and domains of closely packed CeO2 nanocubes. These results show that the mesoscale morphology of deposited CeO2 nanocubes is responsible for templating the formation of a Ni@CFIL catalyst, which resists deactivation leading to highly active and stable H2 production from ethanol.

Objective . Adequate upper esophageal sphincter (UES) opening is essential during swallowing to enable clearance of material into the digestive system, and videofluoroscopy (VF) is the most commonly deployed instrumental examination for assessment of UES opening. High-resolution cervical auscultation (HRCA) has been shown to be an effective, portable and cost-efficient screening tool for dysphagia with strong capabilities in non-invasively and accurately approximating manual measurements of VF images. In this study, we aimed to examine whether the HRCA signals are correlated to the manually measured anterior-posterior (AP) distension of maximal UES opening from VF recordings, under the hypothesis that they would be strongly associated. Approach . We developed a standardized method to spatially measure the AP distension of maximal UES opening in 203 swallows VF recording from 27 patients referred for VF due to suspected dysphagia. Statistical analysis was conducted to compare the manually measured AP distension of maximal UES opening from lateral plane VF images and features extracted from two sets of HRCA signal segments: whole swallow segments and segments excluding all events other than the duration of UES is opening. Main results . HRCA signal features were significantly associated with the normalized AP distension of the maximal UES opening in the longer whole swallowing segments and the association became much stronger when analysis was performed solely during the duration of UES opening. Significance . This preliminary feasibility study demonstrated the potential value of HRCA signals features in approximating the objective measurements of maximal UES AP distension and paves the way of developing HRCA to non-invasively and accurately predict human spatial measurement of VF kinematic events., (© 2021 Institute of Physics and Engineering in Medicine.)

Upper esophageal sphincter is an important anatomical landmark of the swallowing process commonly observed through the kinematic analysis of radiographic examinations that are vulnerable to subjectivity and clinical feasibility issues. Acting as the doorway of esophagus, upper esophageal sphincter allows the transition of ingested materials from pharyngeal into esophageal stages of swallowing and a reduced duration of opening can lead to penetration/aspiration and/or pharyngeal residue. Therefore, in this study we consider a non-invasive high resolution cervical auscultation-based screening tool to approximate the human ratings of upper esophageal sphincter opening and closure. Swallows were collected from 116 patients and a deep neural network was trained to produce a mask that demarcates the duration of upper esophageal sphincter opening. The proposed method achieved more than 90% accuracy and similar values of sensitivity and specificity when compared to human ratings even when tested over swallows from an independent clinical experiment. Moreover, the predicted opening and closure moments surprisingly fell within an inter-human comparable error of their human rated counterparts which demonstrates the clinical significance of high resolution cervical auscultation in replacing ionizing radiation-based evaluation of swallowing kinematics.

Laryngeal vestibule (LV) closure is a critical physiologic event during swallowing, since it is the first line of defense against food bolus entering the airway. Identifying the laryngeal vestibule status, including closure, reopening and closure duration, provides indispensable references for assessing the risk of dysphagia and neuromuscular function. However, commonly used radiographic examinations, known as videofluoroscopy swallowing studies, are highly constrained by their radiation exposure and cost. Here, we introduce a non-invasive sensor-based system, that acquires high-resolution cervical auscultation signals from neck and accommodates advanced deep learning techniques for the detection of LV behaviors. The deep learning algorithm, which combined convolutional and recurrent neural networks, was developed with a dataset of 588 swallows from 120 patients with suspected dysphagia and further clinically tested on 45 samples from 16 healthy participants. For classifying the LV closure and opening statuses, our method achieved 78.94% and 74.89% accuracies for these two datasets, suggesting the feasibility of implementing sensor signals for LV prediction without traditional videofluoroscopy screening methods. The sensor supported system offers a broadly applicable computational approach for clinical diagnosis and biofeedback purposes in patients with swallowing disorders without the use of radiographic examination., Competing Interests: Declaration of competing interest We declare we have no competing interests.

Purpose: Safe swallowing requires adequate protection of the airway to prevent swallowed materials from entering the trachea or lungs (i.e., aspiration). Laryngeal vestibule closure (LVC) is the first line of defense against swallowed materials entering the airway. Absent LVC or mistimed/ shortened closure duration can lead to aspiration, adverse medical consequences, and even death. LVC mechanisms can be judged commonly through the videofluoroscopic swallowing study; however, this type of instrumentation exposes patients to radiation and is not available or acceptable to all patients. There is growing interest in noninvasive methods to assess/monitor swallow physiology. In this study, we hypothesized that our noninvasive sensor- based system, which has been shown to accurately track hyoid displacement and upper esophageal sphincter opening duration during swallowing, could predict laryngeal vestibule status, including the onset of LVC and the onset of laryngeal vestibule reopening, in real time and estimate the closure duration with a comparable degree of accuracy as trained human raters., Method: The sensor-based system used in this study is high-resolution cervical auscultation (HRCA). Advanced machine learning techniques enable HRCA signal analysis through feature extraction and complex algorithms. A deep learning model was developed with a data set of 588 swallows from 120 patients with suspected dysphagia and further tested on 45 swallows from 16 healthy participants., Results: The new technique achieved an overall mean accuracy of 74.90% and 75.48% for the two data sets, respectively, in distinguishing LVC status. Closure duration ratios between automated and gold-standard human judgment of LVC duration were 1.13 for the patient data set and 0.93 for the healthy participant data set., Conclusions: This study found that HRCA signal analysis using advanced machine learning techniques can effectively predict laryngeal vestibule status (closure or opening) and further estimate LVC duration. HRCA is potentially a noninvasive tool to estimate LVC duration for diagnostic and biofeedback purposes without X-ray imaging.

High resolution cervical auscultation is a very promising noninvasive method for dysphagia screening and aspiration detection, as it does not involve the use of harmful ionizing radiation approaches. Automatic extraction of swallowing events in cervical auscultation is a key step for swallowing analysis to be clinically effective. Using time-varying spectral estimation of swallowing signals and deep feed forward neural networks, we propose an automatic segmentation algorithm for swallowing accelerometry and sounds that works directly on the raw swallowing signals in an online fashion. The algorithm was validated qualitatively and quantitatively using the swallowing data collected from 248 patients, yielding over 3000 swallows manually labeled by experienced speech language pathologists. With a detection accuracy that exceeded 95%, the algorithm has shown superior performance in comparison to the existing algorithms and demonstrated its generalizability when tested over 76 completely unseen swallows from a different population. The proposed method is not only of great importance to any subsequent swallowing signal analysis steps, but also provides an evidence that such signals can capture the physiological signature of the swallowing process.

Recent publications have suggested that high-resolution cervical auscultation (HRCA) signals may provide an alternative non-invasive option for swallowing assessment. However, the relationship between hyoid bone displacement, a key component to safe swallowing, and HRCA signals is not thoroughly understood. Therefore, in this work we investigated the hypothesis that a strong relationship exists between hyoid displacement and HRCA signals. Videofuoroscopy data was collected for 129 swallows, simultaneously with vibratory/acoustic signals. Horizontal, vertical and hypotenuse displacements of the hyoid bone were measured through manual expert analysis of videofluoroscopy images. Our results showed that the vertical displacement of both the anterior and posterior landmarks of the hyoid bone was strongly associated with the Lempel-Ziv complexity of superior-inferior and anterior-posterior vibrations from HRCA signals. Horizontal and hypotenuse displacements of the posterior aspect of the hyoid bone were strongly associated with the standard deviation of swallowing sounds. Medial-Lateral vibrations and patient characteristics such as age, sex, and history of stroke were not significantly associated with the hyoid bone displacement. The results imply that some vibratory/acoustic features extracted from HRCA recordings can provide information about the magnitude and direction of hyoid bone displacement. These results provide additional support for using HRCA as a non-invasive tool to assess physiological aspects of swallowing such as the hyoid bone displacement.

Hyoid bone movement is an important physiological event during swallowing that contributes to normal swallowing function. In order to determine the adequate hyoid bone movement, clinicians conduct an X-ray videofluoroscopic swallowing study, which even though it is the gold-standard technique, has limitations such as radiation exposure and cost. Here, we demonstrated the ability to track the hyoid bone movement using a non-invasive accelerometry sensor attached to the surface of the human neck. Specifically, deep neural networks were used to mathematically describe the relationship between hyoid bone movement and sensor signals. Training and validation of the system were conducted on a dataset of 400 swallows from 114 patients. Our experiments indicated the computer-aided hyoid bone movement prediction has a promising performance when compared with human experts' judgements, revealing that the universal pattern of the hyoid bone movement is acquirable by the highly nonlinear algorithm. Such a sensor-supported strategy offers an alternative and widely available method for online hyoid bone movement tracking without any radiation side-effects and provides a pronounced and flexible approach for identifying dysphagia and other swallowing disorders., Competing Interests: We declare we have no competing interests.

Purpose: Outcomes following total knee arthroplasty (TKA), whether clinical, radiological or survival analysis, have been well-studied. Still, there are some concerns about patient satisfaction with the outcome of the surgery and factors that might contribute to a suboptimal result. This study aims to determine if there is correlation between primary TKA malalignment and early patient-reported outcome measures (PROMs)., Materials and Methods: Sixty patients, who had primary TKA and a minimum of 2 years of follow up, were recruited for a detailed clinical and radiological examination. Knee alignment was measured in the coronal, sagittal and axial planes. Normal and the outlier measurements of the patients' knees were defined and the clinical results (PROMs) compared to see if there was a statistically significant difference., Results: Correlation between postoperative limb malalignment in the coronal and the sagittal planes and PROMs was not significant. Conversely, there was significant negative correlation between all types of malrotation and PROMs., Conclusions: Although malalignment has been linked to inferior outcome and implant survival, our results showed that coronal and sagittal limb malalignment has no significant effect on early PROMs. However, all types of component rotational malalignment significantly worsen early PROMs.

Molecular level information about thermodynamic variations (enthalpy, entropy, and free energy) of a gas molecule as it crosses a gas-liquid interface is strongly lacking from an experimental perspective under equilibrium conditions. Herein, we perform in situ measurements of water interacting with the ionic liquid (IL) 1-butyl-3-methylimidazolium acetate, [C 4 mim][Ace], using ambient pressure X-ray photoelectron spectroscopy in order to assess the interfacial uptake of water quantitatively as a function of temperature, pressure, and water mole fraction ( x w ). The surface spectroscopy results are compared to existing bulk water absorption experiments, showing that the amount of water in the interfacial region is consistently greater than that in the bulk. The enthalpy and entropy of water sorption vary significantly between the gas-liquid interface and the bulk as a function of x w , with a crossover that occurs near x w = 0.6 where the water-IL mixture converts from being homogeneous ( x w < 0.6) to nanostructured ( x w > 0.6). Free energy results reveal that water at the gas-IL interface is thermodynamically more favorable than that in the bulk, consistent with the enhanced water concentration in the interfacial region. The results herein show that the efficacy for an ionic liquid to absorb a gas phase molecule is not merely a function of bulk solvation parameters but also is significantly influenced by the thermodynamics occurring across the gas-IL interface during the mass transfer process.

Carbon nanotube-based field-effect transistors (NTFETs) are ideal sensor devices as they provide rich information regarding carbon nanotube interactions with target analytes and have potential for miniaturization in diverse applications in medical, safety, environmental, and energy sectors. Herein, we investigate chemical detection with cross-sensitive NTFETs sensor arrays comprised of metal nanoparticle-decorated single-walled carbon nanotubes (SWCNTs). By combining analysis of NTFET device characteristics with supervised machine-learning algorithms, we have successfully discriminated among five selected purine compounds, adenine, guanine, xanthine, uric acid, and caffeine. Interactions of purine compounds with metal nanoparticle-decorated SWCNTs were corroborated by density functional theory calculations. Furthermore, by testing a variety of prepared as well as commercial solutions with and without caffeine, our approach accurately discerns the presence of caffeine in 95% of the samples with 48 features using a linear discriminant analysis and in 93.4% of the samples with only 11 features when using a support vector machine analysis. We also performed recursive feature elimination and identified three NTFET parameters, transconductance, threshold voltage, and minimum conductance, as the most crucial features to analyte prediction accuracy.

Millions of people across the globe suffer from swallowing difficulties, known as dysphagia, which can lead to malnutrition, pneumonia, and even death. Swallowing cervical auscultation, which has been suggested as a noninvasive screening method for dysphagia, has not been associated yet with any physical events. In this paper, we have compared the hyoid bone displacement extracted from the videofluoroscopy images of 31 swallows to the signal features extracted from the cervical auscultation recordings captured with a tri-axial accelerometer and a microphone. First, the vertical displacement of the anterior part of the hyoid bone is related to the entropy rate of the superior-inferior swallowing vibrations and to the kurtosis of the swallowing sounds. Second, the vertical displacement of the posterior part of the hyoid bone is related to the bandwidth of the medial-lateral swallowing vibrations. Third, the horizontal displacements of the posterior and anterior parts of the hyoid bone are related to the spectral centroid of the superior-inferior swallowing vibrations and to the peak frequency of the medial-lateral swallowing vibrations, respectively. At last, the airway protection scores and the command characteristics were associated with the vertical and horizontal displacements, respectively, of the posterior part of the hyoid bone. Additional associations between the patients' characteristics and auscultations' signals were also observed. The hyoid bone maximal displacement is a cause of swallowing vibrations and sounds. High-resolution cervical auscultation may offer a noninvasive alternative for dysphagia screening and additional diagnostic information.

Introduction: Studies have shown that structured cataract surgery training curricula are beneficial for resident surgeons-in-training, yet nearly one-third of US training programs do not have one, and public dissemination of said curricula are lacking., Methods: We created a microsurgical simulation center and accompanying structured training curriculum. Weekly lectures focused on the steps of cataract surgery, variations on technique, and complications. Each didactic was followed by a 1.5- to 2-hour time block with faculty supervision in the wet lab. Finally, to demonstrate proficiency, residents submitted a recorded video illustrating their competency within 1 week of the lecture. We reviewed videos and provided written feedback via a standardized form. Curriculum effectiveness was evaluated through formative feedback on the course itself and complication rates for resident-performed cataract surgery before and after implementation of the curriculum., Results: The course was implemented in 4 consecutive academic years, allowing time for nine junior residents to participate in the course at least once before operating as a senior. The incidence of posterior capsule tears for senior residents decreased from 3.07% in the 4 years preceding curriculum implementation to 1.13% for the senior residents who completed the course at least once as juniors ( p = .0571). Supervised wet lab sessions and submitted videos allowed faculty to identify surgically struggling residents early., Discussion: Implementation of a cataract surgery training curriculum for junior ophthalmology residents provides a safe and effective environment to practice surgical techniques. Such a curriculum may decrease the complication rates of beginner surgeons., Competing Interests: None to report.

Introduction: Acetabular cup version is crucial for successful total hip arthroplasty (THA). Many methods have been described for measurement of cup version angle. The aim of this study is to assess the accuracy of five commonly used methods for measurement of acetabular cup version in plain antero-posterior views of the pelvis and hip., Material and Methods: Sixty primary THA cases were subjected postoperatively to plain A-P of the pelvis (AP-P), A-P view of the hip (AP-H), and computed tomography (CT) imaging. The acetabular cup version was measured in AP-P and AP-H by five methods (Lewinnek, Widmer, Hassan et al., Ackland et al., and Liaw et al.). These measurements were compared to the CT measurement., Results: All plain X-ray methods showed no significant differences from the CT, except those of Hassan et al. in AP-H, and Widmer and Ackland et al. in AP-P., Conclusions and Recommendations: For measurement of acetabular cup version angle, we recommend the use of Lewinnek and Liaw et al. methods both in AP-P and in AP-H, while Hassan et al.'s method is recommended in AP-P only, and Widmer and Ackland et al.'s methods in AP-H only.

The ionic liquid-gas interface of 1-hexyl-3-methyl-imidazolium chloride, [HMIM][Cl], was examined in the presence of water vapor using lab-based ambient pressure x-ray photoelectron spectroscopy (APXPS) at room temperature. The interfacial water uptake was measured quantitatively in the pressure range of high vacuum up to a maximum of 5 Torr (27% RH) and back to high vacuum in a systematic manner. Water mole fractions in the interface determined from APXPS were compared to previously published tandem differential mobility analysis results on [HMIM][Cl] nanodroplets. Our findings show that water constitutes a significantly larger mole fraction at the interface when compared to the bulk. Additionally, the reverse isotherms showed that the uptake of water at the interface of [HMIM][Cl] is a reversible process.