Headspace-programmed temperature vaporization-mass spectrometry for the rapid determination of possible volatile biomarkers of lung cancer in urine.

We propose a new method for the rapid determination of five volatile compounds described in the literature as possible biomarkers of lung cancer in urine samples. The method is based on the coupling of a headspace sampler, a programmed temperature vaporizer in solvent-vent injection mode, and a mass spectrometer (HS-PTV-MS). This configuration is known as an electronic nose based on mass spectrometry. Once the method was developed, it was used for the analysis of urine samples from lung cancer patients and healthy individuals. Multivariate calibration models were employed to quantify the biomarker concentrations in the samples. The detection limits ranged between 0.16 and 21 µg/L. For the assignment of the samples to the patient group or the healthy individuals, the Wilcoxon signed-rank test was used, comparing the concentrations obtained with the median of a reference set of healthy individuals. To date, this is the first time that multivariate calibration and non-parametric methods have been combined to classify biological samples from profile signals obtained with an electronic nose. When significant differences in the concentration of one or more biomarkers were found with respect to the reference set, the sample is considered as a positive one and a new analysis was performed using a chromatographic method (HS-PTV-GC/MS) to confirm the result. The main advantage of the proposed HS-PTV-MS methodology is that no prior chromatographic separation and no sample manipulation are required, which allows an increase of the number of samples analyzed per hour and restricts the use of time-consuming techniques to only when necessary. Graphical abstract Schematic diagram of the developed methodology.

Effects of realistic force feedback in a robotic assisted minimally invasive surgery system.

BACKGROUND: Robotic assisted minimally invasive surgery systems not only have the advantages of traditional laparoscopic procedures but also restore the surgeon's hand-eye coordination and improve the surgeon's precision by filtering hand tremors. Unfortunately, these benefits have come at the expense of the surgeon's ability to feel. Several research efforts have already attempted to restore this feature and study the effects of force feedback in robotic systems. The proposed methods and studies have some shortcomings. The main focus of this research is to overcome some of these limitations and to study the effects of force feedback in palpation in a more realistic fashion. MATERIAL AND METHODS: A parallel robot assisted minimally invasive surgery system (PRAMiSS) with force feedback capabilities was employed to study the effects of realistic force feedback in palpation of artificial tissue samples. PRAMiSS is capable of actually measuring the tip/tissue interaction forces directly from the surgery site. Four sets of experiments using only vision feedback, only force feedback, simultaneous force and vision feedback and direct manipulation were conducted to evaluate the role of sensory feedback from sideways tip/tissue interaction forces with a scale factor of 100% in characterising tissues of varying stiffness. Twenty human subjects were involved in the experiments for at least 1440 trials. Friedman and Wilcoxon signed-rank tests were employed to statistically analyse the experimental results. RESULTS: Providing realistic force feedback in robotic assisted surgery systems improves the quality of tissue characterization procedures. Force feedback capability also increases the certainty of characterizing soft tissues compared with direct palpation using the lateral sides of index fingers. CONCLUSION: The force feedback capability can improve the quality of palpation and characterization of soft tissues of varying stiffness by restoring sense of touch in robotic assisted minimally invasive surgery operations.

Statistical Analysis of Gastric Cancer Cells Response to Broadband Terahertz Radiation with and without Contrast Nanoparticles.

The paper describes the statistical analysis of the response of gastric cancer cells and normal cells to broadband terahertz radiation up to 4 THz, both with and without the use of nanostructured contrast agents. The THz spectroscopy analysis was comparatively performed under the ATR procedure and transmission measurement procedure. The statistical analysis was conducted towards multiple pairwise comparisons, including a support medium (without cells) versus a support medium with nanoparticles, normal cells versus normal cells with nanoparticles, and, respectively, tumor cells versus tumor cells with nanoparticles. When generally comparing the ATR procedure and transmission measurement procedure for a broader frequency domain, the differentiation between normal and tumor cells in the presence of contrast agents is superior when using the ATR procedure. THz contrast enhancement by using contrast agents derived from MRI-related contrast agents leads to only limited benefits and only for narrow THz frequency ranges, a disadvantage for THz medical imaging.

An enhanced nonparametric quality control chart with application related to industrial process.

In various practical situations, the information about the process distribution is sometimes partially or completely unavailable. In these instances, practitioners prefer to use nonparametric charts as they don't restrict the assumption of normality or specific distribution. In this current article, a nonparametric double homogeneously weighted moving average control chart based on the Wilcoxon signed-rank statistic is developed for monitoring the location parameter of the process. The run-length profiles of the newly developed chart are obtained by using Monte Carlo simulations. Comparisons are made based on various performance metrics of run-length distribution among proposed and existing nonparametric counterparts charts. The extra quadratic loss is used to evaluate the overall performance of the proposed and existing charts. The newly developed scheme showed comparatively better results than its existing counterparts. For practical implementation of the suggested scheme, the real-world dataset related to the inside diameter of the automobile piston rings is also used.

Development of Computational Correlations among Known Drug Scaffolds and their Target-Specific Non-Coding RNA Scaffolds of Alzheimer's Disease.

BACKGROUND: Alzheimer's disease is the most common neurodegenerative disorder. Recent development in sciences has also identified the pivotal role of microRNAs (miRNAs) in AD pathogenesis. OBJECTIVES: We proposed a novel method to identify AD pathway-specific statistically significant miRNAs from the targets of known AD drugs. Moreover, microRNA scaffolds and corresponding drug scaffolds of different pathways were also discovered. MATERIAL AND METHODS: A Wilcoxon signed-rank test was performed to identify pathway-specific significant miRNAs. We generated feed-forward loop regulations of microRNA-TF-gene-based networks, studied the minimum free energy structures of pre-microRNA sequences, and clustered those microRNAs with their corresponding structural motifs of robust transcription factors. Conservation analyses of significant microRNAs were done, and the phylogenetic trees were constructed. We identified 3'UTR binding sites and chromosome locations of these significant microRNAs. RESULTS: In this study, hsa-miR-4261, hsa-miR-153-5p, hsa-miR-6766, and hsa-miR-4319 were identified as key miRNAs for the ACHE pathway and hsa-miR-326, hsa-miR-6133, hsa-miR-4251, hsa-miR-3148, hsa-miR-10527-5p, hsa-miR-527, and hsa-miR-518a were identified as regulatory miRNAs for the NMDA pathway. These miRNAs were regulated by several AD-specific TFs, namely RAD21, FOXA1, and ESR1. It has been observed that anisole and adamantane are important chemical scaffolds to regulate these significant miRNAs. CONCLUSION: This is the first study that developed a detailed correlation between known AD drug scaffolds and their AD target-specific miRNA scaffolds. This study identified chromosomal locations of microRNAs and corresponding structural scaffolds of transcription factors that may be responsible for miRNA co-regulation for Alzheimer's disease. Our study provides hope for therapeutic improvements in the existing microRNAs by regulating pathways and targets.

An improved hybrid whale optimization algorithm for global optimization and engineering design problems.

The whale optimization algorithm (WOA) is a widely used metaheuristic optimization approach with applications in various scientific and industrial domains. However, WOA has a limitation of relying solely on the best solution to guide the population in subsequent iterations, overlooking the valuable information embedded in other candidate solutions. To address this limitation, we propose a novel and improved variant called Pbest-guided differential WOA (PDWOA). PDWOA combines the strengths of WOA, particle swarm optimizer (PSO), and differential evolution (DE) algorithms to overcome these shortcomings. In this study, we conduct a comprehensive evaluation of the proposed PDWOA algorithm on both benchmark and real-world optimization problems. The benchmark tests comprise 30-dimensional functions from CEC 2014 Test Functions, while the real-world problems include pressure vessel optimal design, tension/compression spring optimal design, and welded beam optimal design. We present the simulation results, including the outcomes of non-parametric statistical tests including the Wilcoxon signed-rank test and the Friedman test, which validate the performance improvements achieved by PDWOA over other algorithms. The results of our evaluation demonstrate the superiority of PDWOA compared to recent methods, including the original WOA. These findings provide valuable insights into the effectiveness of the proposed hybrid WOA algorithm. Furthermore, we offer recommendations for future research to further enhance its performance and open new avenues for exploration in the field of optimization algorithms. The MATLAB Codes of FISA are publicly available at https://github.com/ebrahimakbary/PDWOA.

Long-Term Efficacy and Safety Among Patients With Severe Eosinophilic Asthma Treated With Mepolizumab and Its Effect on Small Airways.

BACKGROUND: The major problem at the Cleveland Allergy and Asthma Center was the need for additional therapy for severe eosinophilic asthma patients who were steroid-dependent or required frequent bursts of prednisone. OBJECTIVES: The objectives of this study were to determine the efficacy of monthly mepolizumab (MP) injections up to 6½ years using Asthma Control Quesitonnaire-7 (ACQ-7), forced expiratory volume in 1 second (FEV1), forced expiratory flow at 25% to 75% (FEF25%-75%) overall and among super-responders, and to understand whether FEF25%-75% is an effective parameter to evaluate MP efficacy. METHODS: We reviewed the charts of 67 patients with severe eosinophilic asthma and compared the results between 47 super-responders and the rest of the cohort regarding ACQ-6, ACQ-7, eosinophils, FEV1, and FEF25%-75%. The groups of super-responders and all other patients were described with respect to initial and current values of the study end points using medians and 25th and 75th percentiles. Changes from the initial to the current values in the study end points were measured using percent changes. The Wilcoxon signed rank test was used within each group to test the null hypothesis of 0 median percent change. RESULTS: After 6½ years, there were no significant changes in FEV1. The FEF25%-75%, had a significant median percent increase of 40% among the super-responders (P < .001), which was substantially higher (P = .026) than the median percent increase of 13.8% observed among all other patients. CONCLUSIONS: The use of MP up to 6½ years was safe and effective, with significant changes to ACQ-7 and FEF25%-75% associated with MP treatment, but not the FEV1. A higher magnitude of changes was observed among super-responders than the rest of the cohort. Changes in FEF25%-75% were more meaningful than changes in FEV1 in evaluating pulmonary function responsiveness of severe eosinophilic asthma to MP.

Normal variation of infant hip development : patterns revealed by 3D ultrasound.

AIMS: Studies of infant hip development to date have been limited by considering only the changes in appearance of a single ultrasound slice (Graf's standard plane). We used 3D ultrasound (3DUS) to establish maturation curves of normal infant hip development, quantifying variation by age, sex, side, and anteroposterior location in the hip. METHODS: We analyzed 3DUS scans of 519 infants (mean age 64 days (6 to 111 days)) presenting at a tertiary children's hospital for suspicion of developmental dysplasia of the hip (DDH). Hips that did not require ultrasound follow-up or treatment were classified as 'typically developing'. We calculated traditional DDH indices like α angle (αSP), femoral head coverage (FHCSP), and several novel indices from 3DUS like the acetabular contact angle (ACA) and osculating circle radius (OCR) using custom software. RESULTS: α angle, FHC, and ACA indices increased and OCR decreased significantly by age in the first four months, mean αSP rose from 62.2° (SD 5.7°) to 67.3° (SD 5.2°) (p < 0.001) in one- to eight- and nine- to 16-week-old infants, respectively. Mean αSP and mean FHCSP were significantly, but only slightly, lower in females than in males. There was no statistically significant difference in DDH indices observed between left and right hip. All 3DUS indices varied significantly between anterior and posterior section of the hip. Mean 3D indices of α angle and FHC were significantly lower anteriorly than posteriorly: αAnt = 58.2° (SD 6.1°), αPost = 63.8° (SD 6.3°) (p < 0.001), FHCAnt = 43.0 (SD 7.4), and FHCPost = 55.4° (SD 11.2°) (p < 0.001). Acetabular rounding measured byOCR indices was significantly greater in the anterior section of the hip (p < 0.001). CONCLUSION: We used 3DUS to show that hip shape and normal growth pattern vary significantly between anterior and posterior regions, by magnitudes similar to age-related changes. This highlights the need for careful selection of the Graf plane during 2D ultrasound examination. Whole-joint evaluation by obtaining either 3DUS or manual 'sweep' video images provides more comprehensive DDH assessment.Cite this article: Bone Jt Open 2022;3(11):913-923.

Meaningful values of the EQ-5D-3L in patients undergoing primary knee arthroplasty.

AIMS: The aim of this study was to report the meaningful values of the EuroQol five-dimension three-level questionnaire (EQ-5D-3L) and EuroQol visual analogue scale (EQ-VAS) in patients undergoing primary knee arthroplasty (KA). METHODS: This is a retrospective study of patients undergoing primary KA for osteoarthritis in a university teaching hospital (Royal Infirmary of Edinburgh) (1 January 2013 to 31 December 2019). Pre- and postoperative (one-year) data were prospectively collected for 3,181 patients (median age 69.9 years (interquartile range (IQR) 64.2 to 76.1); females, n = 1,745 (54.9%); median BMI 30.1 kg/m2 (IQR 26.6 to 34.2)). The reliability of the EQ-5D-3L was measured using Cronbach's alpha. Responsiveness was determined by calculating the anchor-based minimal clinically important difference (MCID), the minimal important change (MIC) (cohort and individual), the patient-acceptable symptom state (PASS) predictive of satisfaction, and the minimal detectable change at 90% confidence intervals (MDC-90). RESULTS: The EQ-5D-3L demonstrated good internal consistency with an overall Cronbach alpha of 0.75 (preoperative) and 0.88 (postoperative), respectively. The MCID for the Index score was 0.085 (95% confidence interval (CI) 0.042 to 0.127) and EQ-VAS was 6.41 (95% CI 3.497 to 9.323). The MICCOHORT was 0.289 for the EQ-5D and 5.27 for the EQ-VAS. However, the MICINDIVIDUAL for both the EQ-5D-3L Index (0.105) and EQ-VAS (-1) demonstrated poor-to-acceptable reliability. The MDC-90 was 0.023 for the EQ-5D-3L Index and 1.0 for the EQ-VAS. The PASS for the postoperative EQ-5D-3L Index and EQ-VAS scores predictive of patient satisfaction were 0.708 and 77.0, respectively. CONCLUSION: The meaningful values of the EQ-5D-3L Index and EQ-VAS scores can be used to measure clinically relevant changes in health-related quality of life in patients undergoing primary KA.Cite this article: Bone Joint Res 2022;11(9):619-628.

A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test.

Phase synchronization has been an effective measurement of functional connectivity, detecting similar dynamics over time among distinct brain regions. However, traditional phase synchronization-based functional connectivity indices have been proved to have some drawbacks. For example, the phase locking value (PLV) index is sensitive to volume conduction, while the phase lag index (PLI) and the weighted phase lag index (wPLI) are easily affected by noise perturbations. In addition, thresholds need to be applied to these indices to obtain the binary adjacency matrix that determines the connections. However, the selection of the thresholds is generally arbitrary. To address these issues, in this paper we propose a novel index of functional connectivity, named the phase lag based on the Wilcoxon signed-rank test (PLWT). Specifically, it characterizes the functional connectivity based on the phase lag with a weighting procedure to reduce the influence of volume conduction and noise. Besides, it automatically identifies the important connections without relying on thresholds, by taking advantage of the framework of the Wilcoxon signed-rank test. The performance of the proposed PLWT index is evaluated on simulated electroencephalograph (EEG) datasets, as well as on two resting-state EEG datasets. The experimental results on the simulated EEG data show that the PLWT index is robust to volume conduction and noise. Furthermore, the brain functional networks derived by PLWT on the real EEG data exhibit a reasonable scale-free characteristic and high test-retest (TRT) reliability of graph measures. We believe that the proposed PLWT index provides a useful and reliable tool to identify the underlying neural interactions, while effectively diminishing the influence of volume conduction and noise.

Investigation of sorption and diffusion of hydrocarbons into polydimethylsiloxane in the headspace-solid phase microextraction sampling process via inverse gas chromatography.

Inverse gas chromatography was employed to investigate the sorption and diffusion of hydrocarbons into polydimethylsiloxane (PDMS) in the headspace-solid phase microextraction (HS-SPME) sampling process. Six hydrocarbons as molecular probes and two types of non-cross-linked PDMS with different average molecular weights as stationary phases were used in this study. Experimental measurements with columns containing a PDMS stationary phase were carried out to obtain specific retention volumes, molar enthalpies of sorption, interaction parameters, diffusion coefficients, and activation energies of diffusion of hydrocarbon probes over temperatures ranging from 60 to 90°C. The primary driving force of the hydrocarbon sorption into the PDMS SPME fibers was found to be the molar enthalpy of sorption, which depended on the molecular size of the hydrocarbons. As the molecular size of the hydrocarbon increased, the molar enthalpies of sorption became more exothermic. Interaction parameters and diffusion coefficients indicated that both n-heptane and n-octane were diffused into the PDMS matrix and localized to form clusters or aggregates, which were responsible for more negative molar entropies of sorption. However, the diffusivities of n-nonane and aromatic probes were limited due to their large molecular size and lack in the structural flexibility, respectively. The molar enthalpies of hydrocarbon sorption were independent of the average molecular weight of PDMS. However, specific retention volumes, interaction parameters, diffusion coefficients, and activation energies of diffusion of the hydrocarbons depended on the molecular weight of PDMS as well as the molecular weights and structures of hydrocarbons, as shown by the results of the Wilcoxon signed-rank test.

Measurements of relative distribution constants of vaporized hydrocarbons between air and polydimethylsiloxane via capillary columns for the calculation of headspace hydrocarbon compositions.

This study focused on the measurements and validity of relative distribution constants of vaporized hydrocarbons between air and polydimethylsiloxane (PDMS) using commercially available capillary columns. Capillary column gas chromatography (CCGC) measurements, using two columns containing a PDMS stationary phase with different film thicknesses, were conducted to determine the relative distribution constants of n-heptane, toluene, n-octane, p-xylene, n-nonane, and 1,2,4-trimethylbenzene between air and PDMS at 90 and 120 °C. To validate the accuracy of the relative distribution constants via CCGC, the compositions of three headspace samples containing different amounts of hydrocarbons were calculated using the relative distribution constants via CCGC and extracted amounts via PDMS solid phase microextraction (SPME) at 90 and 120 °C. It was found that calculated hydrocarbon compositions of headspace samples were comparable to true headspace hydrocarbon compositions via direct vapor analysis, with an average absolute relative error of 3.2%. Our results indicate that CCGC is an alternative method that can provide a reliable and convenient method to determine the relative distribution constants of various hydrocarbons between air and PDMS for quantitative chemical analysis of headspace.

Classification of osteoporosis by artificial neural network based on monarch butterfly optimisation algorithm.

Osteoporosis is a life threatening disease which commonly affects women mostly after their menopause. It primarily causes mild bone fractures, which on advanced stage leads to the death of an individual. The diagnosis of osteoporosis is done based on bone mineral density (BMD) values obtained through various clinical methods experimented from various skeletal regions. The main objective of the authors' work is to develop a hybrid classifier model that discriminates the osteoporotic patient from healthy person, based on BMD values. In this Letter, the authors propose the monarch butterfly optimisation-based artificial neural network classifier which helps in earlier diagnosis and prevention of osteoporosis. The experiments were conducted using 10-fold cross-validation method for two datasets lumbar spine and femoral neck. The results were compared with other similar hybrid approaches. The proposed method resulted with the accuracy, specificity and sensitivity of 97.9% ± 0.14, 98.33% ± 0.03 and 95.24% ± 0.08, respectively, for lumbar spine dataset and 99.3% ± 0.16%, 99.2% ± 0.13 and 100, respectively, for femoral neck dataset. Further, its performance is compared using receiver operating characteristics analysis and Wilcoxon signed-rank test. The results proved that the proposed classifier is efficient and it outperformed the other approaches in all the cases.