Association between self-reported METs and other perioperative cardiorespiratory fitness assessment tools in abdominal surgery-a prospective cross-sectional correlation study.

Cardiovascular complications represent a significant proportion of adverse events during the perioperative period, necessitating accurate preoperative risk assessment. This study aimed to investigate the association between well-established risk assessment tools and self-reported preoperative physical performance, quantified by metabolic equivalent (MET) equivalents, in high-risk patients scheduled for elective abdominal surgery. A prospective cross-sectional correlation study was conducted, involving 184 patients admitted to a Gastrointestinal Surgery Department. Various risk assessment tools, including the Revised Cardiac Risk Index (RCRI), Surgical Mortality Probability Model (S-MPM), American University of Beirut (AUB)-HAS2 Cardiovascular Risk Index, and Surgical Risk Calculator (NSQIP-MICA), were utilized to evaluate perioperative risk. Patients self-reported their physical performance using the MET-REPAIR questionnaire. The findings demonstrated weak or negligible correlations between the risk assessment tools and self-reported MET equivalents (Spearman's ρ = - 0.1 to - 0.3). However, a statistically significant relationship was observed between the ability to ascend two flights of stairs and the risk assessment scores. Good correlations were identified among ASA-PS, S-MPM, NSQIP-MICA, and AUB-HAS2 scores (Spearman's ρ = 0.3-0.8). Although risk assessment tools exhibited limited correlation with self-reported MET equivalents, simple questions regarding physical fitness, such as the ability to climb stairs, showed better associations. A comprehensive preoperative risk assessment should incorporate both objective and subjective measures to enhance accuracy. Further research with larger cohorts is needed to validate these findings and develop a comprehensive screening tool for high-risk patients undergoing elective abdominal surgery.

[Effects of nasal valve on subjective nasal patency and nasal resistance: a correlation study on numerical simulation of nasal airflow].

Objective: To investigate the correlations between subjective nasal patency, nasal valve area size and aerodynamic parameters in normal nasal cavity by means of numerical simulation, and to explore the effect of nasal valve on nasal subjective sensation and nasal airflow regulation. Methods: A total of 52 healthy participants (31 males and 21 females) with the average age of 37.8 years, were recruited from the outpatient Department of Otorhinolaryngology Head and Neck Surgery, the Ninth People's Hospital Affiliated to the Medical College of Shanghai Jiao Tong University between January and August 2023. Visual Analog Scale (VAS) scores for unilateral nasal subjective sensation were obtained from all participants. Additionally, the aerodynamic characteristics of inspiratory airflow were simulated. A correlation matrix analysis was conducted to identify the correlation strength between these subjective and objective parameters. Results: VAS scores showed negative correlations with unilateral nasal valve cross-sectional area (r=-0.85, P<0.01) and unilateral intranasal airflow (r=-0.57, P<0.01), and was a positive correlation with unilateral nasal resistance (NR) at the front-end of inferior turbinate (r=0.61, P<0.01). The average cross-sectional area of unilateral nasal valve was (0.85±0.35) cm2. The cross-sectional area of unilateral nasal valve was negatively correlated with unilateral NR (r=-0.50, P<0.01), and positively correlated with unilateral nasal airflow (r=0.61, P<0.01). The NR at the nasal valve area accounted for (40.41±23.54)% of the total unilateral NR. Nearly half of the unilateral NR [(46.74±21.38)%] and air warming [(49.96±10.02)%] occurring before the front end of inferior turbinate were achieved. Conclusions: The nasal valve area plays a crucial role in influencing nasal NR, unilateral nasal airflow, and changes in nasal airflow temperature. Moreover, it is associated with subjective perception of nasal patency.

[Correlation study of NCF2 in chronic rhinosinusitis with nasal polyps].

Objective:After selecting NCF2 based on bioinformatics, clinical experiments were conducted to verify the expression of NCF2 in chronic rhinosinusitis with nasal polyps to study its correlation. Methods:The differentially expressed genes（DEGs） between CRSwNP and non-CRS patients were explored using the CRS-related dataset from the gene expression omnibus GEO database. The weighted gene co-expression network（WGCNA） was used for cluster analysis. The expression and cell distribution of NCF2 in the tissues were determined by single gene enrichment analysis（GSEA）, immune inflammatory infiltration analysis, and principal component（PCA） analysis. The expression degree of NCF2 in the tissues of the subjects was determined by immunohistochemistry, and the percentage of EOS in the peripheral blood of the subjects was detected and the correlation was analyzed. EOS in the tissues of the subjects were counted under a microscope and compared. Results:①The Venn diagram was obtained by crossing the module with the highest correlation between DEGs and WGCNA to determine the core gene NCF2. ②GSEA analysis showed that NCF2 was significantly related to the immunological processes such as allogeneic rejection and asthma. ③The area under the ROC curve was 1, indicating that NCF2 had diagnostic value for CRSwNP. ④NCF2 was highly expressed in nasal polyps, mainly distributed in monocytes and eosinophils. ⑤HE staining showed that the number of EOS in ECRSwNP tissues and the percentage of eosinophils in peripheral blood were higher than those in nonECRSwNP and control groups. ⑥The immunohistochemistry results showed that NCF2 was significantly expressed in the nasal polyps of ECRSwNP patients, which was higher than that in the nasal mucosa of nonECRSwNP group and control group. ⑦The expression of NCF2 in tissues was positively correlated with EOS count in ECRSwNP group and EOS expression in peripheral blood. Conclusion:The expression of NCF2 is increased in eosinophilic chronic rhinosinusitis with nasal polyps, and it is significantly correlated with the expression of eosinophils in peripheral blood and tissues, suggesting that NCF2 may be used as a basis for the intrinsic classification of ECRSwNP and a reference index for clinical diagnosis and treatment.

Heart Rate Variability and Pulse Rate Variability: Do Anatomical Location and Sampling Rate Matter?

Wearable technology and neuroimaging equipment using photoplethysmography (PPG) have become increasingly popularized in recent years. Several investigations deriving pulse rate variability (PRV) from PPG have demonstrated that a slight bias exists compared to concurrent heart rate variability (HRV) estimates. PPG devices commonly sample at ~20-100 Hz, where the minimum sampling frequency to derive valid PRV metrics is unknown. Further, due to different autonomic innervation, it is unknown if PRV metrics are harmonious between the cerebral and peripheral vasculature. Cardiac activity via electrocardiography (ECG) and PPG were obtained concurrently in 54 participants (29 females) in an upright orthostatic position. PPG data were collected at three anatomical locations: left third phalanx, middle cerebral artery, and posterior cerebral artery using a Finapres NOVA device and transcranial Doppler ultrasound. Data were sampled for five minutes at 1000 Hz and downsampled to frequencies ranging from 20 to 500 Hz. HRV (via ECG) and PRV (via PPG) were quantified and compared at 1000 Hz using Bland-Altman plots and coefficient of variation (CoV). A sampling frequency of ~100-200 Hz was required to produce PRV metrics with a bias of less than 2%, while a sampling rate of ~40-50 Hz elicited a bias smaller than 20%. At 1000 Hz, time- and frequency-domain PRV measures were slightly elevated compared to those derived from HRV (mean bias: ~1-8%). In conjunction with previous reports, PRV and HRV were not surrogate biomarkers due to the different nature of the collected waveforms. Nevertheless, PRV estimates displayed greater validity at a lower sampling rate compared to HRV estimates.

A simplified, 2-question grading system for evaluating abstracts in orthopedic scientific meetings: a serial randomization study.

BACKGROUND AND PURPOSE: Efficient abstract scoring for congress presentation is important. Given the emergence of new study methodologies, a scoring system that accommodates all study designs is warranted. We aimed to assess the equivalence of a simplified, 2-question abstract grading system with a more complex currently used system in assessing abstracts submitted for orthopedic scientific meetings in a serial randomized study. METHODS: Dutch Orthopedic Association Scientific Committee (DOASC) members were randomized to grade abstracts using either the current grading system, which includes up to 7 scoring categories, or the new grading system, which consists of only 2 questions. Pearson correlation coefficient and mean abstract score with 95% confidence intervals (CI) were calculated. RESULTS: Analysis included the scoring of 195 abstracts by 12-14 DOASC members. The average score for an abstract using the current system was 60 points (CI 58-62), compared with 63 points (CI 62-64) using the new system. By using the new system, abstracts were scored higher by 3.3 points (CI 1.7-5.0). Pearson correlation was poor with coefficient 0.38 (P < 0.001). CONCLUSION: The simplified abstract grading system exhibited a poor correlation with the current scoring system, while the new system offers a more inclusive evaluation of varying study designs and is preferred by almost all DOASC members.

The multi-strategy hybrid forecasting base on SSA-VMD-WST for complex system.

In view of the strong randomness and non-stationarity of complex system, this study suggests a hybrid multi-strategy prediction technique based on optimized hybrid denoising and deep learning. Firstly, the Sparrow search algorithm (SSA) is used to optimize Variational mode decomposition (VMD) which can decompose the original signal into several Intrinsic mode functions (IMF). Secondly, calculating the Pearson correlation coefficient (PCC) between each IMF component and the original signal, the subsequences with low correlation are eliminated, and the remaining subsequence are denoised by Wavelet soft threshold (WST) method to obtain effective signals. Thirdly, on the basis of the above data noise reduction and reconstruction, our proposal combines Convolutional neural network (CNN) and Bidirectional short-term memory (BiLSTM) model, which is used to analyze the evolution trend of real time sequence data. Finally, we applied the CNN-BiLSTM-SSA-VMD-WST to predict the real time sequence data together with the other methods in order to prove it's effectiveness. The results show that SNR and CC of the SSA-VMD-WST are the largest (the values are 20.2383 and 0.9342). The performance of the CNN-BiLSTM-SSA-VMD-WST are the best, MAE and RMSE are the smallest (which are 0.150 and 0.188), the goodness of fit R2 is the highest(its value is 0.9364). In contrast with other methods, CNN-BiLSTM-SSA-VMD-WST method is more suitable for denoising and prediction of real time series data than the traditional and singular deep learning methods. The proposed method may provide a reliable way for related prediction in various industries.

Feasibility of images acquired using smartphone camera for marginal and internal fit of fixed dental prosthesis: comparison and correlation study.

This study aimed to measure marginal and internal fit using images captured with both an optical microscope and a smartphone camera, comparing the fit measurement performance of these devices and analyzing their correlation. Working casts (with 10 posterior and 10 anterior teeth) created to fabricate fixed dental prostheses were used. These working casts were scanned using a desktop scanner (E1) to design an interim crown, and the designed interim crown was fabricated using a three-dimensional (3D) printer. Utilizing the silicone replica technique, the fabricated interim crown replicated the fit, which was then captured using both an optical microscope and a smartphone camera. The captured images were used to measure the marginal and internal fit according to the imaging device. Intraclass correlation coefficients (ICC) were used for reliability analysis according to the imaging device. Furthermore, the Wilcoxon signed-rank test was adopted for the comparative evaluation of the marginal and internal fit between the imaging devices (α = 0.05). The measurement results of the marginal and internal fit according to the optical microscope and smartphone camera did exhibit a significant difference (P < 0.05). The ICC between the two devices showed an "excellent" agreement of over 0.9 at all measurement points (P < 0.001). A smartphone camera could be used to obtain images for evaluating the marginal and internal fit.

Screening of sustainable supply chain performance evaluation indicators based on the ill-conditioned index cycle method.

The establishment of an evaluation indicator system that can accurately assess the sustainability of a supply chain while further enhancing its performance is vital and relevant. Based on the connotation of sustainable supply chains and triple bottom line theory, indicators are initially proposed from economic, environmental, and social dimensions. To increase the explanatory power of the indicator system and decrease information redundancy, the coefficient of variation is applied to identify the indicators with weak interpretation intensity, the ill-conditioned index cycle method is utilized to filter out indicators with redundant information, and data on 100 Chinese listed companies from 2019 to 2021 are used as samples. A performance evaluation indicator system of sustainable supply chains with 16 indicators is ultimately established. The information interpretation strength index and cumulative information contribution rate verify the rationality of the final indicator system. The outcome demonstrates that this screening method can strengthen the representativeness of the indicator system and rapidly reduce redundancy, leading to the better discrimination of the evaluation results. The findings of this study provide an indicator system and a methodological reference for both companies and policymakers and can aid in the transformation of supply chains toward sustainability.

Patient Characteristics and Telemedicine Use in the US, 2022.

Importance: Telemedicine use was common during the COVID-19 pandemic, expanding many patients' approaches to accessing health care. Of concern is whether telemedicine access was poorer among higher-needs and disadvantaged populations. Objective: To assess patient characteristics associated with telemedicine use and telemedicine mode and describe telemedicine visit experiences by telemedicine mode. Design, Setting, and Participants: This cross-sectional study included data from the 2022 Health Information National Trends Survey and included US adults with a health care visit. Data were analyzed from May to September 2023. Exposure: Patient characteristics. Main Outcomes and Measures: Any telemedicine visits vs in-person visits only; telemedicine mode (video vs audio-only). Multivariable logistic models assessed patient characteristics associated with telemedicine visits and mode. Bivariate analyses compared telemedicine experiences by mode. Results: The study included 5437 adult patients (mean [SE] age, 49.4 [0.23] years; 3136 females [53.4%]; 1928 males [46.6%]). In 2022, 2384 patients (43%) had a telemedicine visit; 1565 (70%) had a video visit while 819 (30%) had an audio-only visit. In multivariable models, older age (≥75 years: adjusted odds ratio [aOR], 0.63; 95% CI, 0.42-0.94), no internet use (aOR, 0.62; 95% CI, 0.48-0.81), and living in the Midwest (aOR, 0.50; 95% CI, 0.35-0.70) were negatively associated with having telemedicine visits. Female sex (aOR, 1.43; 95% CI, 1.12-1.83), having chronic conditions (aOR, 2.13; 95% CI, 1.66-2.73), and multiple health care visits (2-4 visits: aOR, 1.77; 95% CI, 1.23-2.54; ≥5 visits: aOR, 3.29; 95% CI, 2.20-4.92) were positively associated. Among individuals who used telemedicine, older age (65-74 years: aOR, 2.13; 95% CI, 1.09-4.14; ≥75 years: aOR, 3.58; 95% CI, 1.60-8.00), no health insurance (aOR, 2.84; 95% CI, 1.42-5.67), and no internet use (aOR, 2.11; 95% CI, 1.18-3.78) were positively associated with having audio-only visits. We observed no significant differences in telemedicine use or mode by education, race and ethnicity, or income. Patients' experiences using telemedicine were generally similar for video and audio-only except more individuals who used audio-only had privacy concerns (20% vs 12%, P = .02). Conclusions and Relevance: In this cross-sectional study of adults with health care visits, many patients, including those with the greatest care needs, chose telemedicine even after in-person visits were available. These findings support continuing this care delivery approach as an option valued by patients. Differences were not observed by most common measures of socioeconomic status. Continued monitoring of telemedicine use is needed to ensure equitable access to health care innovations.

Unraveling the Intraday Variations in the Tear Fluid Proteome.

Purpose: Tear fluid is a complex and dynamic biological fluid that plays essential roles in maintaining ocular homeostasis and protecting against the external environment. Owing to the small sample volume, studying the tear proteome is challenging. However, advances in high-resolution mass spectrometry have expanded tear proteome profiling, revealing >500 unique proteins. Tears are emerging as a noninvasive source of biomarkers for both ocular and systemic diseases; nevertheless, intraday variability of proteins in tear fluid remains questionable. This study investigates intraday variations in the tear fluid proteome to identify stable proteins that could act as candidate biomarkers. Methods: Tear samples from 15 individuals at four time points (10 am, 12 pm, 2 pm, and 4 pm) were analyzed using mass spectrometry to evaluate protein variation during these intervals. Technical variation was assessed by analyzing pooled samples and was subtracted from the total variation to isolate biological variability. Results: Owing to high technical variation, low-abundant proteins were filtered, and only 115 proteins met the criteria for further analysis. These criteria include being detected at all four time points in at least eight subjects, having a mean peptide-spectrum match count greater than 5, and having a technical variation less than 0.10. Lactotransferrin, lipocalin-1, and several immunoglobulins were among the 51 stable proteins (mean biological coefficient of variation < 0.10). Additionally, 43 proteins displayed significant slopes across the 4 time points, with 17 increasing and 26 decreasing over time. Conclusions: These findings contribute to the understanding of tear fluid dynamics and further expand our knowledge of the tear proteome.

Assessment of occupational stress among certified registered anesthetists in the Greater Accra region.

Background: Work-related stress is a prevailing concern within the community of Certified Registered Anesthetists (CRAs), significantly impacting both the health and professional performance of these individuals. This study aimed to assess work-related stress and its influencing factors among CRAs practicing in the Greater Accra region was examined. Methods: Using convenience sampling techniques, data were gathered from 140 participants via a Google form questionnaire distributed through WhatsApp. Descriptive statistics were employed to analyze the collected data, focusing on frequencies and proportions for categorical variables. For continuous variables, bivariate analysis (Chi-square) and ordinal logistic regression were conducted using STATA 16. A p-value <0.05 was considered significant. Results: Among the 140 CRAs, 20 individuals (14.3%) reported experiencing mild stress levels according to the Weiman Occupational Stress Scale. Approximately 3 out of 4 CRAs (73.6%) reported having moderate stress levels, and 12.1% reported severe stress levels. This indicated that the majority of CRAs experienced moderate levels of stress, which was notably affected by the type of health facility and the use of inadequate or sub-standard equipment in the hospitals. Conclusion: Based on these findings, the study recommends educational programs and counseling for CRAs to heighten awareness of the demanding nature of their job. Additionally, it suggests the provision of proper resources and standard equipment for CRAs. Facility-level motivation for CRAs is also advised to alleviate their stress. Finally, the study proposes further investigations into the factors contributing to work-related stress among CRAs.

Translation and validation of the Chinese version of the menstrual distress questionnaire.

BACKGROUND: The Menstrual Distress Questionnaire (MDQ) is a commonly used questionnaire that assesses various symptoms and distress associated with the menstrual cycle in women. However, the questionnaire has not been completely translated into Chinese with rigorous reliability and validity testing. METHODS: This study translated the Menstrual Distress Questionnaire Form Cycle (MDQC) from English into Chinese: MDQCC in two stages. First, it was translated forward and backward using Jones' model; second, to test the validity and reliability, 210 Chinese-speaking women were recruited through online announcements and posters posted between June 2019 and May 2020. Expert validity, construct validity, convergent validity, and factorial validity were determined using content validity index (CVI), intraclass correlation coefficient (ICC), composite reliability (CR), and exploratory factor analysis, respectively. For concurrent criterion validity, MDQCC score was compared with three existing pain scales. Reliability was evaluated using internal consistency across items and two-week test-retest reliability over time. RESULTS: The CVI for content validity was .92. Item-CVI for expert validities among the 46 items ranged from .50 - 1; scale-CVI for the eight subscales, from .87 - 1; ICC, from .650 - .897; and CRs, from .303 - .881. Pearson correlation coefficients between MDQCC and short-form McGill pain questionnaire, present pain intensity, and visual analog scale scores were .640, .519, and .575, respectively. Cronbach's α for internal consistency was satisfactory (.932). ICC for test-retest reliability was .852 for the entire MDQCC. CONCLUSION: MDQCC was valid and reliable for Mandarin Chinese-speaking women. It can be used to evaluate female psychiatric symptoms related to the menstrual cycle in future work.

The Menstrual Distress Questionnaire has been used to evaluate menstrual distress, including dysmenorrhoea and premenstrual syndrome. This questionnaire has been translated into Persian, Korean, Japanese, and Cantonese, rendering it to be used more and more widely all over the world. The study translated all 46 items of the Menstrual Distress Questionnaire from English to Mandarin Chinese using a two-stage strategy. The Chinese version of this questionnaire developed by the present study was found to be a valid and reliable tool in Chinese Mandarin-speaking female populations. It could be used to evaluate women's physical and psychiatric symptoms related to the menstrual cycle in future works.

Ensemble Extreme Learning Machine Method for Hemoglobin Estimation Based on PhotoPlethysmoGraphic Signals.

Non-invasive detection of hemoglobin (Hb) concentration is of great clinical value for health screening and intraoperative blood transfusion. However, the accuracy and stability of non-invasive detection still need to be improved to meet clinical requirement. This paper proposes a non-invasive Hb detection method using ensemble extreme learning machine (EELM) regression based on eight-wavelength PhotoPlethysmoGraphic (PPG) signals. Firstly, a mathematical model for non-invasive Hb detection based on the Beer-Lambert law is established. Secondly, the captured eight-channel PPG signals are denoised and fifty-six feature values are extracted according to the derived mathematical model. Thirdly, a recursive feature elimination (RFE) algorithm is used to select the features that contribute most to the Hb prediction. Finally, a regression model is built by integrating several independent ELM models to improve prediction stability and accuracy. Experiments conducted on 249 clinical data points (199 cases as the training dataset and 50 cases as the test dataset) evaluate the proposed method, achieving a root mean square error (RMSE) of 1.72 g/dL and a Pearson correlation coefficient (PCC) of 0.76 (p < 0.01) between predicted and reference values. The results demonstrate that the proposed non-invasive Hb detection method exhibits a strong correlation with traditional invasive methods, suggesting its potential for non-invasive detection of Hb concentration.

Starting an undergraduate degree amid the COVID-19 pandemic: A mixed-method egocentric network study on student loneliness.

Students who began their undergraduate university studies in the midst of the COVID-19 pandemic (the 'COVID cohort'), may have been particularly at risk for experiencing increased loneliness. This study employed an exploratory egocentric network and mixed-methods approach to investigate the links between social networks and loneliness in the COVID cohort. Of sixty-one respondents meeting inclusion criteria for the study, fifty-eight first-year undergraduate students from the September 2020 intake at a large Scottish University provided egocentric network data via an online survey, as well as responses to three open-ended questions which were aimed at generating qualitative data about participants' experiences of starting university in the context of the COVID-19 pandemic. Bivariate analyses suggest that having a larger social network, and higher satisfaction with that network, was associated with reduced loneliness. We additionally explored these associations in subsamples of students living on-campus and living off-campus. Our qualitative data adds valuable insight into the impact that pandemic-related social-distancing restrictions had on limiting students' opportunities for meeting their peers and forging meaningful social connections at university. Limitations of this study include a small sample size and an exploratory approach requiring further investigation and replication. However, in the context of universities continuing to use hybrid teaching models, this study provides useful initial insights, highlighting potential avenues for institutions to support students in developing social connections in the transition to higher education.

Measuring e-Professional Behavior of Doctors of Medicine and Dental Medicine on Social Networking Sites: Indexes Construction With Formative Indicators.

BACKGROUND: Previous studies have predominantly measured e-professionalism through perceptions or attitudes, yet there exists no validated measure specifically targeting the actual behaviors of health care professionals (HCPs) in this realm. This study addresses this gap by constructing a normative framework, drawing from 3 primary sources to define e-professional behavior across 6 domains. Four domains pertain to the dangers of social networking sites (SNSs), encompassing confidentiality, privacy, patient interaction, and equitable resource allocation. Meanwhile, 2 domains focus on the opportunities of SNSs, namely, the proactive dissemination of public health information and maintaining scientific integrity. OBJECTIVE: This study aims to develop and validate 2 new measures assessing the e-professional behavior of doctors of medicine (MDs) and doctors of dental medicine (DMDs), focusing on both the dangers and opportunities associated with SNSs. METHODS: The study used a purposive sample of MDs and DMDs in Croatia who were users of at least one SNS. Data collection took place in 2021 through an online survey. Validation of both indexes used a formative approach, which involved a 5-step methodology: content specification, indicators definition with instructions for item coding and index construction, indicators collinearity check using the variance inflation factor (VIF), external validity test using multiple indicators multiple causes (MIMIC) model, and external validity test by checking the relationships of the indexes with the scale of attitude toward SNSs using Pearson correlation coefficients. RESULTS: A total of 753 responses were included in the analysis. The first e-professionalism index, assessing the dangers associated with SNSs, comprises 14 items. During the indicators collinearity check, all indicators displayed acceptable VIF values below 2.5. The MIMIC model showed good fit (χ213=9.4, P=.742; χ2/df=0.723; root-mean-square error of approximation<.001; goodness-of-fit index=0.998; comparative fit index=1.000). The external validity of the index is supported by a statistically significant negative correlation with the scale measuring attitudes toward SNSs (r=-0.225, P<.001). Following the removal of 1 item, the second e-professionalism index, focusing on the opportunities associated with SNSs, comprises 5 items. During the indicators collinearity check, all indicators exhibited acceptable VIF values below 2.5. Additionally, the MIMIC model demonstrated a good fit (χ24=2.5, P=.718; χ2/df=0.637; root-mean-square error of approximation<0.001; goodness-of-fit index=0.999; comparative fit index=1.000). The external validity of the index is supported by a statistically significant positive correlation with the scale of attitude toward SNSs (r=0.338; P<.001). CONCLUSIONS: Following the validation process, the instrument designed for gauging the e-professional behavior of MDs and DMDs consists of 19 items, which contribute to the formation of 2 distinct indexes: the e-professionalism index, focusing on the dangers associated with SNSs, comprising 14 items, and the e-professionalism index, highlighting the opportunities offered by SNSs, consisting of 5 items. These indexes serve as valid measures of the e-professional behavior of MDs and DMDs, with the potential for further refinement to encompass emerging forms of unprofessional behavior that may arise over time.

In subjects with chronic low back pain, does neuropathia exclusively correlated to neuronal compression? A correlation study of PainDETECT questionnaire and corresponding MRI and X-ray findings.

INTRODUCTION: Understanding the complex nature of low back pain (LBP) is crucial for effective management. The PainDETECT questionnaire is a tool that distinguishes between neuropathic (NeP), nociceptive (NoP), and ambiguous pain. This study aimed to investigate the relationship between pain classification and lumbar intervertebral degenerative parameters obtained from imaging. METHODS: A cohort study was conducted involving 279 patients, aged 18 years and above, who completed PainDETECT questionnaires and underwent lumbar MRI and/or X-ray scans. RESULTS: The study included 102 patients with NoP, 78 with ambiguous pain, and 99 with NeP. The NeP group had lower mean age (58.21 vs. 53.63, p < 0.05) and higher mean numerical rating scale score (7.9 vs. 5.9, p < 0.001) compared to the NoP group. A negative correlation was found between PainDETECT scores and pelvic incidence (τ = - 0.177, p = 0.043). The NeP group exhibited significantly higher severity of foraminal stenosis (U = 18.962, p = 0.002), spinal stenosis (U = 14.481, p = 0.005), and Pfirrmann grade (U = 14.221, p = 0.028) compared to the NoP group. A higher proportion of NeP patients had intervertebral disk bulge (96% vs. 78% vs. 78%, p = 0.002) and high-intensity zones (51% vs. 41% vs. 19%, p < 0.001) compared to those with NoP and ambiguous pain. CONCLUSION: NeP, as determined by the PainDETECT questionnaire, is associated with more severe neural compression, increased presence of discogenic disease and inflammatory disk severity, and decreased pelvic incidence. This pioneering study establishes a connection between pathological findings and pain categorization, providing clinicians with valuable guidance for formulating tailored management plans and reducing the need for unnecessary pharmacotherapy, imaging, and non-targeted surgical interventions.

Correlation study on microbial communities and volatile flavor compounds in cigar tobacco leaves of diverse origins.

To elucidate the significant influence of microorganisms on geographically dependent flavor formation by analyzing microbial communities and volatile flavor compounds (VFCs) in cigar tobacco leaves (CTLs) obtained from China, Dominica, and Indonesia. Microbiome analysis revealed that the predominant bacteria in CTLs were Staphylococcus, Aerococcus, Pseudomonas, and Lactobacillus, while the predominant fungi were Aspergillus, Wallemia, and Sampaiozyma. The microbial communities of CTLs from different origins differed to some extent, and the diversity and abundance of bacteria were greater than fungi. Metabolomic analysis revealed that 64 VFCs were identified, mainly ketones, of which 23 VFCs could be utilized to identify the geographical origins of CTLs. Sixteen VFCs with OAV greater than 1, including cedrol, phenylacetaldehyde, damascone, beta-damascone, and beta-ionone, play important roles in shaping the flavor profile of CTLs from different origins. Combined with the correlation analysis, bacterial microorganisms were more closely related to key VFCs and favored a positive correlation. Bacillus, Vibrio, and Sphingomonas were the main flavor-related bacteria. The study demonstrated that the predominant microorganisms were essential for the formation of key flavor qualities in CTLs, which provided a theoretical reference for flavor control of CTLs by microbial technology. KEY POINTS: • It is the high OAV VFCs that determine the flavor profile of CTLs. • The methylerythritol phosphate (MEP) pathway and the carotenoid synthesis pathway are key metabolic pathways for the formation of VFCs in CTLs. • Microbial interactions influence tobacco flavor, with bacterial microorganisms contributing more to the flavor formation of CTLs.

Exploration of collective tactical variables in elite netball: An analysis of team and sub-group positioning behaviours.

Collective tactical behaviours are aspects of player interactions that are particularly important in netball, due to its unique restrictions on player movement (players unable to move when in possession of the ball and positional spatial restrictions). The aim of this study was to explore variables representing collective tactical behaviours in netball. A local positioning system provided player positions of one team throughout seven elite-level netball matches. The positions were analysed to provide mean, variability (standard deviation) and irregularity (normalised approximate entropy) for each attack and defence possession (470 and 423, respectively) for the team and positional subgroups (forwards, midcourts and defenders) for 10 position-related variables. Correlational analyses showed collective tactical variables could be grouped as lateral and longitudinal dispersion variables. The variables were each analysed after log transformation with a linear mixed model to compare attack and defence and to estimate standardised effects on attack and defence of possession outcome, possession duration, score difference, match time, opposition strength and season time. During attack, the team and all sub-groups adopted greater lateral dispersion between players, while on defence there was generally greater longitudinal dispersion. The team also showed increased longitudinal dispersion when home and opposition possessions ended in a score. Additionally, greater irregularity was observed in active sub-groups (forwards on attack, defenders on defence). Score difference and opposition strength had trivial-small but generally unclear effects. In conclusion, these effects show that analysis of player positions on attack and defence is a promising avenue for coaches and analysts to modify collective tactical behaviours in netball.

Spectacle-wearing compliance and its associated determinants among infants with bilateral corrective refractive errors: An observational study.

This study aimed to evaluate spectacle-wearing compliance and identify the determinants associated with it in infants with bilateral corrective refractive errors. Infants aged < 3 years with bilateral corrective refractive errors who were supplied with spectacles for > 1 month were enrolled at the pediatric comprehensive clinic of Zhongshan Ophthalmic Center. Spectacle-wearing compliance was evaluated by calculating the percentage of spectacle-wearing time in the awake time (STIT), and its potential determinants were identified based on interviews with the infants' caregivers using univariate and multivariate logistic regression analysis. Pearson correlation analysis was performed to further determine the degree of correlation between spectacle-wearing compliance and weight of spectacles. A total of 366 infants (age: 20.85 ±â€…9.06 months, male: 54.92%) were included. The mean percentage of STIT was 64.00%±41.69%. The communication between caregivers of different infants regarding spectacle-wearing experience (P = .004, OR = 2.290, 95% confidence interval [CI] for OR = 1.301-4.029), perceptions of spectacle-wearing importance (P = .000, OR = 6.337, 95% CI for OR = 3.664-10.961), and weight of spectacles (P = .000, OR = 7.271, 95% CI for OR = 4.141-12.769) were significantly associated with spectacle-wearing compliance. Besides, spectacle-wearing compliance was positively correlated with the weight of spectacles (P < .01), exhibiting a decreasing trend with the weight of spectacles. Overall, spectacle-wearing compliance requires improvement. Moreover, efficient strategies aimed at improving spectacle-wearing compliance, such as enhancing communication between caregivers of different infants regarding spectacle-wearing experience, raising awareness about the importance of wearing spectacles, and reducing the weight of spectacles, are urgently needed.

Progress in Predicting Ames Test Outcomes from Chemical Structures: An In-Depth Re-Evaluation of Models from the 1st and 2nd Ames/QSAR International Challenge Projects.

The Ames/quantitative structure-activity relationship (QSAR) International Challenge Projects, held during 2014-2017 and 2020-2022, evaluated the performance of various predictive models. Despite the significant insights gained, the rules allowing participants to select prediction targets introduced ambiguity in model performance evaluation. This reanalysis identified the highest-performing prediction model, assuming a 100% coverage rate (COV) for all prediction target compounds and an estimated performance variation due to changes in COV. All models from both projects were evaluated using balance accuracy (BA), the Matthews correlation coefficient (MCC), the F1 score (F1), and the first principal component (PC1). After normalizing the COV, a correlation analysis with these indicators was conducted, and the evaluation index for all prediction models in terms of the COV was estimated. In total, using 109 models, the model with the highest estimated BA (76.9) at 100% COV was MMI-VOTE1, as reported by Meiji Pharmaceutical University (MPU). The best models for MCC, F1, and PC1 were all MMI-STK1, also reported by MPU. All the models reported by MPU ranked in the top four. MMI-STK1 was estimated to have F1 scores of 59.2, 61.5, and 63.1 at COV levels of 90%, 60%, and 30%, respectively. These findings highlight the current state and potential of the Ames prediction technology.