Pearson Correlation Coefficient Research Articles

A novel deep learning model for obstructive sleep apnea diagnosis: hybrid CNN-Transformer approach for radar-based detection of apnea-hypopnea events.

The demand for cost-effective and accessible alternatives to polysomnography (PSG), the conventional diagnostic method for obstructive sleep apnea (OSA), has surged. In this study, we have developed and validated a deep learning model for detecting apnea-hypopnea events using radar data. We conducted a single-center prospective cohort study, dividing participants with suspected sleep-disordered breathing into development and temporally independent test sets. Utilizing a hybrid CNN-Transformer architecture, we performed 5-fold cross-validation on the development set to develop and subsequently validate the model. Evaluation metrics included sensitivity for event detection, mean absolute error (MAE), intraclass correlation coefficient (ICC), and Pearson correlation coefficient (r) for apnea-hypopnea index (AHI) estimation. Linearly weighted kappa statistics (κ) assessed OSA severity. The development set comprised 54 participants (July 2021-May 2022), while the test set included 35 participants (June 2022-June 2023). In the test set, our model achieved an event detection sensitivity of 67.2% (95% CI: 65.8%, 68.5%) and demonstrated a MAE of 7.54 (95% CI: 5.36, 9.72), indicating good agreement (ICC = 0.889 [95% CI: 0.792, 0.942]) and a strong correlation (r = 0.892 [95% CI: 0.795, 0.945]) with the ground truth for AHI estimation. Furthermore, OSA severity estimation showed substantial agreement (κ = 0.780 [95% CI: 0.658, 0.903]). Our study highlights radar sensors and advanced AI models' potential to improve OSA diagnosis, paving the path for future radar-based diagnostic models in sleep medicine research.

Evaluation of tetrachloroethylene (PCE) and its degradation products in human exhaled breath and indoor air in a community setting.

Tetrachloroethylene (PCE) is a widely utilized volatile chemical in industrial applications, including dry cleaning and metal degreasing. Exposure to PCE potentially presents a significant health risk to workers as well as communities near contamination sites. Adverse health effects arise not only from PCE, but also from PCE degradation products, such as trichloroethylene (TCE) and vinyl chloride (VC). PCE, TCE, and VC can contaminate water, soil, and air, leading to exposure through multiple pathways, including inhalation, ingestion, and dermal contact. This study focused on a community setting in Martinsville, Indiana, a working-class Midwestern community in the United States, where extensive PCE contamination has occurred due to multiple contamination sites (referring to 'plumes'), including a Superfund site. Utilizing proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS), PCE, TCE, and VC concentrations were measured in the exhaled breath of 73 residents from both within and outside the plume areas. PCE was detected in 66 samples, TCE in 26 samples, and VC in 68 samples. Our results revealed a significant positive correlation between the concentrations of these compounds in exhaled breath and indoor air (Pearson correlation coefficients: PCE = 0.75, TCE = 0.71, and VC = 0.89). This study confirms the presence of PCE and its degradation products in exhaled breath in a community exposure investigation, demonstrating the potential of using exhaled breath analysis in monitoring exposure to environmental contaminants. This study showed the feasibility of utilizing PTR-TOF-MS in community investigations to assess exposure to PCE and its degradation products by measuring these compounds in exhaled breath and indoor air.

Optimizing preoperative bone health assessment for adult spinal deformity: a prospective correlation analysis of intraoperative pedicle screw insertion torque and imaging modalities in Japan.

Prospective cohort study. This study aimed to identify the optimal preoperative bone health assessment for adult spinal deformity (ASD) surgery through correlation analysis between intraoperative pedicle screw (PS) insertion torque and various bone quality measures, including bone mineral density (BMD) assessed by dual-energy X-ray absorptiometry (DEXA), Hounsfield unit (HU) by computed tomography (CT), and vertebral bone quality (VBQ) score by magnetic resonance imaging. Existing data on optimal assessment tools for ASD surgery are limited. The study included patients with ASD aged >60 years who underwent spinal corrective fusion surgery from the lower thoracic spine to the pelvis. The intraoperative PS insertion torque was measured using a torque meter. Pearson correlation coefficients were calculated between the PS insertion torque and the BMD, HU, and VBQ score. Preoperative bone quality was compared between the proximal junctional failure (PJF) and non-PJF groups. Thirty-one patients with 177 PS at T10, T11, and T12 were analyzed. The PS insertion torque showed a moderate positive correlation with lumbar spine BMD (r=0.59-0.69, p<0.01), total hip BMD (0.58-0.62, p<0.01), and HU value (r=0.58-0.66, p<0.01). However, the VBQ score did not show significant correlation (r=-0.28 to -0.23, p >0.05). Notably, a strong correlation was found between the PS insertion torque and the HU value for screws of the same size (r=0.71 and 0.74, p<0.01). The HU value at T12 and the PS insertion torque at T10 were significantly lower in the PJF group than in the non-PJF group. This study demonstrates a positive correlation between the PS insertion torque and HU value in the lower thoracic spine and a moderate correlation with BMD but not the VBQ score. Preoperative assessment using DEXA and CT is crucial for optimizing bone health management in ASD surgery.

Image analysis for bright-field HER2 in situ hybridization: validation for clinical use.

The aim of the present study was to develop and validate a quantitative image analysis (IA) algorithm to aid pathologists in assessing bright-field HER2 in situ hybridization (ISH) tests in solid cancers. A cohort of 80 sequential cases (40 HER2-negative and 40 HER2-positive) were evaluated for HER2 gene amplification with bright-field ISH. We developed an IA algorithm using the ISH Module from HALO software to automatically quantify HER2 and CEP17 copy numbers per cell as well as the HER2/CEP17 ratio. We observed a high correlation of HER2/CEP17 ratio, an average of HER2 and CEP17 copy number per cell between visual and IA quantification (Pearson's correlation coefficient of 0.842, 0.916, and 0.765, respectively). IA was able to count from 124 cells to 47,044 cells (median of 5565 cells). The margin of error for the visual quantification of the HER2/CEP17 ratio and of the average of HER2 copy number per cell decreased from a median of 0.23 to 0.02 and from a median of 0.49 to 0.04, respectively, in IA. Curve estimation regression models showed that a minimum of 469 or 953 invasive cancer cells per case is needed to reach an average margin of error below 0.1 for the HER2/CEP17 ratio or for the average of HER2 copy number per cell, respectively. Lastly, on average, a case took 212.1s to execute the IA, which means that it evaluates about 130 cells/s and requires 6.7s/mm2. The concordance of the IA software with the visual scoring was 95%, with a sensitivity of 90% and a specificity of 100%. All four discordant cases were able to achieve concordant results after the region of interest adjustment. In conclusion, this validation study underscores the usefulness of IA in HER2 ISH testing, displaying excellent concordance with visual scoring and significantly reducing margins of error.

Clinical and pathological significance of Orai1 channel expression in human diabetic nephropathy.

Targeted therapies for diabetic nephropathy (DN) are lacking, partly due to their irreversible nature. The role of Orai1, a store-operated Ca2+ channel, in DN remains debated, with conflicting evidence on its effect on proteinuria in animal models. We aimed to elucidate the functional relevance of Orai1 expression for clinicopathological parameters in patients with DN. In this study, we included 93 patients diagnosed with DN between 2009 and 2019. Immunohistochemical staining for Orai1 was performed on paraffin-embedded kidney sections. The significance of Orai1 expression in human DN was assessed by examining its correlation with DN's pathological and clinical parameters using Pearson's correlation coefficient and univariate logistic regression. Orai1 was significantly overexpressed in DN patients compared to control. A strong correlation was observed between increased Orai1 expression and higher Renal Pathology Society DN classification, enhanced interstitial fibrosis and tubular atrophy scores. Positive correlations with serum creatinine levels and prognosis of chronic kidney disease (CKD) by glomerular filtration rate (GFR) and albuminuria category were noted but the estimated GFR was inversely related to Orai1 expression. Orai1's association with advanced CKD stages persisted even after adjusting for confounding variables in multivariate logistic regression analysis. Orai1 expression is closely associated with histological and clinical severities of DN, suggesting its potential as a predictive biomarker for disease progression and prognosis. These findings provide new perspectives on therapeutic interventions targeting Orai1 in DN.

Comorbidity of Body Dysmorphic Disorder and Obsessive-Compulsive Disorder in Orthognathic Surgery Patients

Objective: Body dysmorphic disorder (BDD) is a mental health disorder in which a person believes that their actual physical features appear worse than they truly are. The aim of this study is to examine the presence of BDD and its comorbidity with anxiety, depression, and obsessive-compulsive disorder (OCD) in patients with planned orthognathic surgery for dentofacial deformities. Methods: In this study conducted on patients scheduled for orthognathic surgery, the presence of BDD, OCD, depression, anxiety, and stress was determined by administering the Florida Obsessive-Compulsive Inventory (FOCI), Depression, Anxiety, and Stress Scale-21 (DASS-21), and Body Image Disturbance Questionnaire (BIDQ) prior to the surgery. An independent samples t-test evaluated differences between group means, Pearson's correlation coefficient demonstrated the linear relationship between two variables, and the chi-square test assessed the relationship between two categorical variables. A p-value below 0.05 was deemed statistically significant. A total of 108 patients were included in the study, with 54 patients Class 2 and 54 patients Class 3. Results: BIDQ, FOCI, depression, anxiety, and stress, males showed statistically significant higher results compared to females (p &lt;0.05). There were no statistically significant differences in BIDQ, FOCI, depression, and stress between Class 2 and Class 3 patients (p&gt;0.05). Of the 108 patients included in the study, a total of 20.4% (n=22) were found to be BDD positive. Among the female patients, 10% (n=6) were BDD positive, while among the male patients, 33.3% (n=16) were BDD positive. When evaluated in terms of skeletal classification, 14.8% (n=8) of Class 2 patients were BDD positive, while 25.9% (n=14) of Class 3 patients were BDD positive. Conclusions: Surgeons performing orthognathic surgery should be familiar with common and often severe body image disturbances. When evaluating patients seeking orthognathic surgery, their psychological conditions should be carefully considered.

Remote levodopa challenge test in Parkinson's disease: Feasibility, reliability, validity and economic value.

The aim was to demonstrate the feasibility, reliability and validity of an in-home remote levodopa challenge test (LCT), as delivered through an online platform, for patients with Parkinson's disease (PwPD). Patients with Parkinson's disease eligible for deep brain stimulation surgery screening were enrolled. Participants sequentially received an in-home remote LCT and an in-hospital standard LCT (separated by 2.71 weeks). A modified Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III omitting rigidity and postural stability items was used in the remote LCT. The reliability of the remote LCT was evaluated using the intraclass correlation coefficient and the concurrent validity was evaluated using the Pearson's correlation coefficient r between the levodopa responsiveness of the remote and standard LCT. Out of 106 PwPD screened, 80 (75.5%) completed both the remote and standard LCT. There was a good reliability (intraclass correlation coefficient 0.81, 95% confidence interval 0.69-0.88) and a strong correlation (r = 0.84, 95% confidence interval 0.77-0.90) between the levodopa responsiveness of the remote and standard LCT. The mean cost for PwPD was estimated to be reduced by 91% by using the remote LCT. The remote LCT is feasible, reliable and valid and may reduce healthcare-related costs for PwPD and their caregivers.

Wearable-Based Kinematic Analysis of Upper-Limb Movements During Daily Activities Could Provide Insights into Stroke Survivors' Motor Ability.

Frequent and objective monitoring of motor recovery progression holds significant importance in stroke rehabilitation. Despite extensive studies on wearable solutions in this context, the focus has been predominantly on evaluating limb activity. This study aims to address this limitation by delving into a novel measure of wrist kinematics more intricately related to patients' motor capacity. To explore a new wearable-based approach for objectively and reliably assessing upper-limb motor ability in stroke survivors using a single inertial sensor placed on the stroke-affected wrist. Seventeen stroke survivors performed a series of daily activities within a simulated home setting while wearing a six-axis inertial measurement unit on the wrist affected by stroke. Inertial data during point-to-point upper-limb movements were decomposed into movement segments, from which various kinematic variables were derived. A data-driven approach was then employed to identify a kinematic variable demonstrating robust internal reliability, construct validity, and convergent validity. We have identified a key kinematic variable, namely the 90th percentile of movement segment distance during point-to-point movements. This variable exhibited robust reliability (intra-class correlation coefficient of .93) and strong correlations with established clinical measures of motor capacity (Pearson's correlation coefficients of .81 with the Fugl-Meyer Assessment for Upper-Extremity; .77 with the Functional Ability component of the Wolf Motor Function Test; and -.68 with the Performance Time component of the Wolf Motor Function Test). The findings underscore the potential for continuous, objective, and convenient monitoring of stroke survivors' motor progression throughout rehabilitation.

Longitudinal variation of correlations between different components of assessment within a medical school

BackgroundAn assessment program should be inclusive and ensure that the various components of medical knowledge, clinical skills, and professionalism are assessed. The level and the variation over time in the strength of the correlation between these components of assessment is still a matter of study. Based on the meaningful learning theory and the integrated learning theory, we hypothesize that these components increase their connections during the medical school course.MethodsThis is a retrospective cohort study that analyzed data collected for a 10-year period in one medical school. We included students from the 3rd to 6th year of medical school from 2011 to 2021. Three assessment components were addressed: Knowledge, Clinical Skills, and Professionalism. For data analysis, Pearson correlation coefficients (R) and R2 were calculated to study the correlation between variables and a z-test on Fisher's r-to-z was used to determine the differences between correlation coefficients.Results949 medical students were included in the study. The correlation between Clinical Skills and Professionalism showed a medium to strong association (Pearson's R ranging from 0.485 to 0.734), while the correlation between Knowledge and Professionalism was weaker but exhibited a steady evolution with Pearson's R fluctuating between 0.075 and 0.218. The Knowledge and Clinical Skills correlation became statistically significant from 2013 onwards and peaking at Pearson's R of 0.440 for the cohort spanning 2016–2019. We also revealed a strengthening of correlations between Professionalism and Clinical Skills from the beginning to the end of clinical training, but not with the knowledge component.ConclusionsThis analysis contributes to our understanding of the dynamics of correlations of different assessment components within an institution and provides a framework for how they interact and influence each other.Trial registrationThis study was not a clinical trial, but a retrospective observational study, without health care interventions. Nevertheless, we provide herein the number of the study as submitted to the Ethics committee – CEICVS 146/2021.

A Pilot Study of Ultrasound Assessment of Umbilical Cord and Placental Vascular Flow for Cord Accident Stillbirth Prevention.

Our objective was to determine the feasibility and interobserver reliability of umbilical cord and placental arteriolar flow assessment in low-risk pregnancies near term. This was a prospective pilot study in low-risk pregnancies at 36 weeks with anterior placentas. We excluded any with an indication for antenatal testing or delivery before 39 weeks. Each participant underwent two ultrasounds by different examiners, which included arterial and venous velocimetry at three cord sites (fetal, free loop, and placental) in addition to maternal and fetal placental arterioles. The interobserver reliability was quantified using the Pearson correlation coefficient with that of standard clinical parameters serving as a benchmark for interpretation. Among 53 participants scanned at 356/7-371/7 weeks, the mean examination duration was 20.5 ± 4.2 minutes. Ascertainment success was high for measures at the free loop, placental cord insertion, and fetal placental arterioles (range 90.6%-99.1%) and was lower at the fetal cord insertion and maternal spiral arterioles (range 47.2%-87.7%). Interobserver reliability estimates for free-loop systolic/diastolic and pulsatility index ranged from 0.38 to 0.44. Interobserver reliability for experimental parameters varied by measurement site, and all were poor at the fetal insertion and in placental arterioles. Parameters had significant variation across cord sites (range 4.3%-21.7%). In our cohort, flow assessments of the free loop, placental insertion, and placental arterioles are feasible, but interrater reliability varies by measurement type and cord site. Future studies are needed to establish feasibility and reliability in nonanterior placentation and to assess clinical relevance.

Accurate estimation of the normalized mutual information of multidimensional data.

While the linear Pearson correlation coefficient represents a well-established normalized measure to quantify the inter-relation of two stochastic variables X and Y, it fails for multidimensional variables, such as Cartesian coordinates. Avoiding any assumption about the underlying data, the mutual information I(X, Y) does account for multidimensional correlations. However, unlike the normalized Pearson correlation, it has no upper bound (I ∈ [0, ∞)), i.e., it is not clear if say, I = 0.4 corresponds to a low or a high correlation. Moreover, the mutual information (MI) involves the estimation of high-dimensional probability densities (e.g., six-dimensional for Cartesian coordinates), which requires a k nearest-neighbor algorithm, such as the estimator by Kraskov et al. [Phys. Rev. E 69, 066138 (2004)]. As existing methods to normalize the MI cannot be used in connection with this estimator, a new approach is presented, which uses an entropy estimation method that is invariant under variable transformations. The algorithm is numerically efficient and does not require more effort than the calculation of the (un-normalized) MI. After validating the method by applying it to various toy models, the normalized MI between the Cα-coordinates of T4 lysozyme is considered and compared to a correlation analysis of inter-residue contacts.

Noise in operating theatres, is it safe?

Noise-Induced Hearing Loss (NIHL) is a condition caused by repeated exposure to loud noise, with operating theatre personnel potentially at risk. The aims of this study were to establish the typical noise levels in orthopaedic theatres and to compare these to The Control of Noise at Work Regulations 2005. We measured the average noise levels in 40 trauma and orthopaedic surgeries in a single centre. We used the Decibel X app to take measurements, then performed corrections to ascertain noise levels at the surgeon's ear (Leq). The daily noise exposure level for theatre staff for each procedure (LEP, d) and the LEP, d over an average 8-hour working day when performing different groups of procedures were calculated. Data were analysed using descriptive statistics, ANOVA, t-test and the Pearson coefficient of correlation. The LEP, d lower action value (80 dBA) as set by the Health and Safety Executive (HSE) was met by performing a single revision total knee replacement or a right open ankle debridement. Assuming three procedures are conducted per list, lists consisting of joint replacements (82 dBA) or medium elective procedures (81 dBA) exceed this lower limit. Additionally, lists comprising large and medium bone fractures would be within 1 dB of the limit (79 dBA and 79 dBA, respectively). Soft tissue (74 dBA), arthroscopic (73 dBA), and small bone fracture (71 dBA) procedures had the lowest LEP, d. The greatest contributors to noise levels were surgical instruments. The number of people in the room made a significant difference to noise levels (p = 0.032). We have established the baseline noise levels in various orthopaedic procedures. Measures should be taken to meet UK regulations. Further research should determine suitable measures for protection from hearing damage for theatre staff and evaluate the risks high noise levels pose to patients.

Predicting significant wave height in the South China Sea using the SAC-ConvLSTM model

IntroductionThe precise forecasting of Significant wave height(SWH) is vital to ensure the safety and efficiency of aquatic activities such as ocean engineering, shipping, and fishing.MethodsThis paper proposes a deep learning model named SAC-ConvLSTM to perform 24-hour prediction with the SWH in the South China Sea. The long-term prediction capability of the model is enhanced by using the attention mechanism and context vectors. The prediction ability of the model is evaluated by mean absolute error (MAE), root mean square error (RMSE), mean square error (MSE), and Pearson correlation coefficient (PCC).ResultsThe experimental results show that the optimal input sequence length for the model is 12. Starting from 12 hours, the SAC-ConvLSTM model consistently outperforms other models in predictive performance. For the 24-hour prediction, this model achieves RMSE, MAE, and PCC values of 0.2117 m, 0.1083 m, and 0.9630, respectively. In addition, the introduction of wind can improve the accuracy of wave prediction. The SAC-ConvLSTM model also has good prediction performance compared to the ConvLSTM model during extreme weather, especially in coastal areas.DiscussionThis paper presents a 24-hour prediction of SWH in the South China Sea. Through comparative validation, the SAC-ConvLSTM model outperforms other models. The inclusion of wind data enhances the model's predictive capability. This model also performs well under extreme weather conditions. In physical oceanography, variables related to SWH include not only wind but also other factors such as mean wave period and sea surface air pressure. In the future, additional variables can be incorporated to further improve the model's predictive performance.

Comparison of acromio-axillo-suprasternal notch index with thyromental height test to predict difficult visualization of larynx

Background: Securing and maintaining a patent airway for the conduct of general anesthesia are a major concern for an anesthesiologist. Unanticipated difficult intubation in anesthetized patients is the main cause of morbidity or mortality. Several predictors are proposed to anticipate difficult tracheal intubation, but no predictor is found to be 100% accurate. Acromio-axillo-suprasternal notch index (AASI) is a recent addition to the list of predictors. Aims and Objectives: The current study compared the usefulness of AASI and thyromental height test (TMHT) as predictors of difficult visualization of larynx (DVL). Materials and Methods: Following approval by the Institutional Ethics Committee and CTRI registration, written informed consent was taken. The study was conducted on 300 patients aged 18–65 years belonging to American Society of Anesthesiologists’ physical status I and II, with modified Mallampati (MMP) Scores of 1 and 2, over a period of 6 months. Preoperatively all patient’s airway was evaluated using AASI and TMHT. The DVL during direct laryngoscopy was noted as assessed by Cormack and Lehane grading. We compared the sensitivity and specificity for DVL with regard to AASI and TMHT. Results: The incidence of unanticipated DVL was 14%. The sensitivity, specificity, positive predictive value, and negative predictive value of AASI were 86.4%, 38.1%, 89.6%, and 31.4%, respectively, and for TMHT, they were 94.6%, 4.8%, 85.9%, and 12.5%, respectively. Pearson correlation coefficient was r = −0.068 (P=0.243) when AASI was compared with TMHT. Conclusion: AASI was found to be less sensitive when compared to TMHT and there was statistically no significant correlation between the two parameters to predict the DVL.

A Novel Approach for Forecasting and Scheduling Building Load through Real-Time Occupant Count Data

AbstractThe smart buildings’ load forecasting is necessary for efficient energy management, and it is easily possible because of the data availability based on widespread use of Internet of Things (IoT) devices and automation systems. The information of buildings’ occupancy is directly associated with energy consumption. Therefore, we present a hybrid model consisting of a Long Short-Term Memory (LSTM) network, Extreme Gradient Boosting (XgBoost), Random Forest (RF) and Linear Regression (LR) for commercial and academic buildings’ load forecasting. The correlation between occupants’ count and total load of the building is calculated using Pearson Correlation Coefficient (PCC). The comparative analysis of the proposed approach with LSTM, XgBoost, RF and Gated Recurrent Unit (GRU) is also performed. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Square Error (MSE) and Normalized Root Mean Square Error (NRMSE) are used as performance indicators for evaluating performance. Findings indicate that the proposed hybrid approach outperforms other models. The RMSE and MAE of 2.99 and 2.18, respectively, are recorded by the proposed model for commercial building dataset while for academic building the RMSE and MAE are 4.48 and 2.85, respectively. Occupancy and load consumption have a positive correlation as evident from PCC analysis. Therefore, we have scheduled the forecasted load based on occupancy patterns for two different cases. Cost is reduced by 17.42% and 33.40% in case 1 and case 2, respectively. Moreover, the performance of the proposed hybrid approach is compared with different techniques presented in literature for buildings load forecasting.

Distribution of Heavy Metals in the Surrounding Mining Region of Kizhnica in Kosovo

This study investigated the distribution of heavy metals in agricultural soils in the vicinity of three large mining landfills of the Kizhnica mine in the Republic of Kosovo. The mining sector is one of the most important sectors of Kosovo’s economic development, and the Kizhnica mine is one of the most important ore producers in Kosovo. Besides the positive aspects, the development of production also has some negative side effects, such as the generation of industrial waste and the possible contamination of surrounding areas, including agricultural land. Therefore, ten sampling sites were selected in the vicinity of the Kizhnica mine. These sites were characterized and assessed as the most important due to the anthropogenic impact of mineral processing and open-tailing waste deposits in Kizhnica. The concentration of Pb, Zn, Cu, As, Cd, Ni, Mn and Sb in the selected samples was determined using inductively coupled plasma–optical emission spectrometry. The data obtained were used to create geochemical maps and calculate the contamination factor, pollution load index and geoaccumulation index. Cluster analysis, Pearson correlation coefficient and air spatial distribution patterns using the air dispersion model were used to evaluate within the area. The results showed that heavy metal levels are influenced by the anthropogenic nature of pollution, confirming a current ecological threat from mining activities in the region. In order to improve waste management, reduce the hazardous impacts of mining and contribute to the sustainable development of the region, the potential reuse of the deposited waste material in the construction industry is proposed.

Intraoperative OCT to check the correct postimplant position of PreserfloTM.

This study was designed to examine the capacity of intraoperative optical coherence tomography (OCT) to predict the postimplant position of the glaucoma drainage device PreserfloTM. 13 eyes (mean age 65.42 (14.89) years) underwent PreserfloTM (Santen, Osaka, Japan) placement. Before surgery, participants were subjected to a comprehensive ophthalmic examination (intraocular pressure (IOP), cup to disk ratio (C/D), visual field, OCT, endothelial cell count). Anterior segment OCT scans were obtained intraoperatively using a Rescan 700 OCT system (Carl Zeiss Meditec, Inc., Oberkochen, Germany). One day postsurgery, anterior segment OCT using the Spectralis OCT (Heidelberg Engineering GmbH) was performed in a sitting position to capture the same chamber cross-section as before. The main outcome variables were tube-endothelium distance (T-E) and tube length (TL) in the anterior chamber measured using both OCT systems. Correlation between intraoperative and office measurements was examined through Pearson correlation (r) and intraclass correlation coefficients (ICC). Mean intraoperative and in-office T-E were 625.26 (SD 366.60) versus 561.16 (SD 364.62) µm respectively (p = 0.540). Intraoperative and in-office anterior chamber TL were 1386 (SD 701.82) and 1433.91 (SD 713.55) µm, respectively (p = 0.029). Excellent correlation was observed between both sets of T-E (r = 0.992; p = 0.008) and TL (r = 0.984; p = 0.016) values. Both OCT systems showed good agreement yielding ICCs of 0.992 (p < 0.001) for T-E and 0.995 (p = 0.001) for TL. Excellent correlation was observed between our intraoperative and postoperative OCT measurements. These results support the usefulness of intraoperative OCT to confirm the correct position of an implanted PreserfloTM microshunt.

Modification of an AIE Fluorescent Probe for Monitoring the Polarity of Lipid Droplets Based on a series of Synthesized Aryl Naphthalizes.

Lipid droplets (LDs) are subcellular organelles that are dynamic and play a central role in energy homeostasis and lipid metabolism. They also contribute to the transport and maturation of cellular proteins and are closely associated with several diseases. The important role of the cellular microenvironment in maintaining cellular homeostasis. Changes in cell polarity, particularly in organelles, have been found to be strongly linked to inflammation, Alzheimer's disease, cancer, and other illnesses. It is essential to check the polarity of the LDs. A series of arylated naphthalimide derivatives were synthesized using the Suzuki reaction. Modification of synthesized aryl naphthalimides using oligomeric PEG based on intramolecular charge transfer (ICT) mechanism. A series of fluorescent probes were designed to target LDs and detect their polarity. Nap-TPA-PEG3 probe exhibited high sensitivity to polarity. The addition of oligomeric polyethylene glycol (PEG) to the probe not only significantly improved its solubility in water, but also effectively reduced its cytotoxicity. In addition, the probe exhibited excellent aggregation-induced luminescence (AIE) properties and solvent discolouration effects. Nap-TPA-PEG3 probe exhibited high Pearson correlation coefficient (0.957163) in lipid droplet co-localization in cells. Nap-TPA-PEG3 could be used as an effective hand tool to monitor cell polarity.

Utilizing Entropy of Cadence to Optimize Cycling Rehabilitation in Individuals With Parkinson's Disease.

Previous studies have established that increased Sample Entropy (SampEn) of cadence, a measure of non-linear variability, during dynamic cycling leads to greater improvements in motor function for individuals with Parkinson's disease (PD). However, there is significant variability in responses among individuals with PD due to symptoms and disease progression. The aim of this study was to develop and test a paradigm for adapting a cycling exercise intervention using SampEn of cadence and rider effort to improve motor function. Twenty-two participants were randomized into either patient-specific adaptive dynamic cycling (PSADC) or non-adaptive (NA) group. SampEn of cadence was calculated after each of the 12 sessions, and motor function was evaluated using the Kinesia test. Pearson's correlation coefficient was used to analyze the relationship between SampEn of cadence and motor function improvement. Multiple linear regression (MLR) was used to identify the strongest predictors of motor function improvement. Pearson's correlation coefficient revealed a significant correlation between SampEn of cadence and motor function improvements (R2 = -.545, P = .009), suggesting that higher SampEn of cadence led to greater motor function improvement. MLR demonstrated that SampEn of cadence was the strongest predictor of motor function improvement (β = -8.923, t = -2.632, P = .018) over the BMI, Levodopa equivalent daily dose, and effort. The findings show that PSADC paradigm promoted a greater improvement in motor function than NA dynamic cycling. These data will be used to develop a predictive model to optimize motor function improvement after cycling in individuals with PD.

Machine-Learning-Assisted Design of Novel TiZrNbVAl Refractory High-Entropy Alloys with Enhanced Ductility

Refractory high-entropy alloys (RHEAs) typically exhibit excellent high-temperature strength but limited ductility. In this study, a comprehensive machine learning strategy with integrated material knowledge is proposed to predict the elongation of TiZrNbVAl RHEAs. By referring to the ductility theories, a set of cost-effective material features is developed with various mathematical forms of thermodynamic parameters. These features are proven to effectively incorporate material knowledge into ML modeling. They also offer potential alternatives to those obtained from costly first-principles calculations. Based on Pearson correlation coefficients, the linear relationships between pairwise features were compared, and the seven key features with the greatest impact on the model were selected for ML modeling. Regression tasks were performed to predict the ductility of TiZrNbVAl, and the CatBoost gradient boosting algorithm exhibiting the best performance was eventually selected. The established optimized model achieves high predictive accuracies exceeding 0.8. These key features were further analyzed using interpretable ML methods to elucidate their influences on various ductility mechanisms. According to the ML results, different compositions of TiZrNbVAl with excellent tensile properties were prepared. The experimental results indicate that Ti44Zr24Nb17V5Al10 and Ti44Zr26Nb8V13Al9 both exhibited ultimate tensile strengths of approximately 1180 MPa and elongations higher than 21%. They verified that the ML strategy proposed in this study is an effective approach for predicting the properties of RHEAs. It is a potential method that can replace costly first-principles calculations. Thermodynamic parameters have been shown to effectively predict alloy ductility to a certain extent.