Choquet fuzzy integral-based classifier ensemble technique for COVID-19 detection

In vitro and in vivo accuracy of autonomous robotic vs. fully guided static computer-assisted implant surgery

OBJECTIVES

To assess the accuracy of autonomous robotic and fully guided static computer-assisted implant surgery (sCAIS) performed on models and patients.

MATERIALS AND METHODS

This study was divided into in vitro and in vivo sections. In vitro, 80 operators were assigned to two groups randomly. Forty operators performed forty autonomous robotic implant (ARI group) surgeries and the remaining forty operators carried out forty fully guided sCAIS (FGI group) surgeries on maxillary models, respectively. Each operator placed an implant in one maxillary model. In vivo, 60 patients with 113 implants from 2019 to 2023 (ARI group: 32 patients, 58 implants; FGI group: 28 patients, 55 implants) receiving implant surgeries were incorporated in this retrospective research. The preoperative and postoperative cone beam computer tomographs (CBCTs) were utilized to estimate the linear deviations and angular deviations in two-dimensional (2D) and three-dimensional (3D) space. The Pearson's chi-square test, Shapiro-Wilk test, Student's t test, Mann-Whitney U test and mixed models were applied, and p <0.05 was considered statistically significant.

RESULTS

In vitro, a total of 80 implants were enrolled and significant differences were found between the two groups (p < 0.001): The 3D deviation at the platform of ARI and FGI group was 0.58 ± 0.60 mm and 1.50 ± 1.46 mm, respectively, at the apex was 0.58 ± 0.60 mm and 1.78 ± 1.35 mm, respectively, and angle was 1.01 ± 0.87° and 2.93 ± 1.59°, respectively. Also, except for mesiodistal deviation at the implant platform, the rest linear and angular deviations in the ARI group were significantly lower than those in the FGI group in 2D space (p < 0.001). In vivo, a significantly lower mean of angular deviation (0.95 ± 0.50°, p < 0.001) and the linear deviation at both platform (0.45 ± 0.28 mm, p < 0.001) and apex (0.47 ± 0.28 mm, p < 0.001) were observed in ARI group when compared to the FGI group (4.31 ± 2.60°; 1.45 ± 1.27 mm; 1.77 ± 1.14 mm).

CONCLUSIONS

The use of autonomous robotic technology showed significantly higher accuracy than the fully guided sCAIS.

Investigating the mechanism of action of Yanghe Pingchuan Granule in the treatment of bronchial asthma based on bioinformatics and experimental validation

Background

Yanghe Pingchuan Granule (YPG) is a patented Chinese medicine developed independently by the Anhui Provincial Hospital of Traditional Chinese Medicine. For many years, it has been used for the treatment of asthma with remarkable clinical effects. However, the composition of YPG is complex, and its potential active ingredients and mechanism of action for the treatment of asthma are unknown.

Materials and methods

In this study, we investigated the potential mechanism of action of YPG in the treatment of asthma through a combination of bioinformatics and in vivo experimental validation. We searched for active compounds in YPG and asthma targets from multiple databases and obtained common targets. Subsequently, a protein-protein interaction (PPI) network for compound disease was constructed using the protein interaction database for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, hematoxylin and eosin (H&E) staining, Masson staining, enzyme-linked immunosorbent assay (ELISA) analysis, immunofluorescence (IF) experiments, and Western blot (WB) experiments were performed to verify the possible mechanism of action of YPG for asthma treatment.

Results

We obtained 72 active ingredients and 318 drug target genes that overlap with asthma. Serine/threonine-protein kinase (AKT1), tumor protein p53 (TP53), tumor necrosis factor (TNF), interleukin (IL)-6, IL-1β, vascular endothelial growth factor-A (VEGFA), prostaglandin-endoperoxide synthase 2 (PTGS2), caspase-3 (CASP3), mitogen-activated protein kinase 3 (MAPK3) and epidermal growth factor receptor (EGFR) were the most relevant genes in the PPI network. KEGG analysis showed a high number of genes enriched for the nuclear factor kappa-B (NF-κB) signaling pathway. Animal experiments confirmed that YPG reduced inflammatory cell infiltration and down-regulated the expression of ovalbumin-induced inflammatory factors. Furthermore, YPG treatment decreased the protein expression of NFĸB1, nuclear factor kappa B kinase subunit beta (IKBKB), vascular endothelial growth factor (VEGF), and vascular endothelial growth factor receptor 2 (VEGFR2) in lung tissue.

Conclusion

YPG has a positive effect on asthma by interfering with multiple targets. Furthermore, YPG may significantly inhibit the follicle-induced inflammatory response through the NF-ĸB signaling pathway.

Relationship between EMG features and force in orbicularis oris muscle

BACKGROUND

Lip incompetence resulting from mouth breathing is a common clinical manifestation, while there are no definite indicators of amplitude and intensity of muscle functional training in clinical practice, which leads to unsatisfactory training results.

OBJECTIVE

The aim was to quantify the relationship between electromyography (EMG) and force in orbicularis oris muscle, so that the indicators of muscle functional training can be evaluated using EMG signals, so as to improve the training effects.

METHODS

The EMG and the force signals of orbicularis oris muscle from 0% to 100% MVC within 5 s in twelve healthy subjects (six males and six females; age, 25 ± 2 years; mass, 60 ± 15 kg) were recorded simultaneously for three trials. Four EMG features consisting of RMS, WAMP, SampEn and FuzzyEn were analyzed. The regression analyses were performed using first-order and third-order polynomial model.

RESULTS

There were high correlations between the four EMG features and muscle force with the two models. The third-order model yielded a higher coefficient of determination (R2) than the linear model (p< 0.001) and the result of FuzzyEn (R2: 0.884 ± 0.059) was the highest in the four features.

CONCLUSION

The third-order model with FuzzyEn of EMG signals may be used to guide the muscle functional training.

A two-tier feature selection method using Coalition game and Nystrom sampling for screening COVID-19 from chest X-Ray images

The world is still under the threat of different strains of the coronavirus and the pandemic situation is far from over. The method, that is widely used for the detection of COVID-19 is Reverse Transcription Polymerase chain reaction (RT-PCR), which is a time-consuming method and is prone to manual errors, and has poor precision. Although many nations across the globe have begun the mass immunization procedure, the COVID-19 vaccine will take a long time to reach everyone. The application of artificial intelligence (AI) and computer-aided diagnosis (CAD) has been used in the domain of medical imaging for a long period. It is quite evident that the use of CAD in the detection of COVID-19 is inevitable. The main objective of this paper is to use convolutional neural network (CNN) and a novel feature selection technique to analyze Chest X-Ray (CXR) images for the detection of COVID-19. We propose a novel two-tier feature selection method, which increases the accuracy of the overall classification model used for screening COVID-19 CXRs. Filter feature selection models are often more effective than wrapper methods as wrapper methods tend to be computationally more expensive and are not useful for large datasets dealing with a large number of features. However, most filter methods do not take into consideration how a group of features would work together, rather they just look at the features individually and decide on a score. We have used approximate Shapley value, a concept of Coalition game theory, to deal with this problem. Further, in the case of a large dataset, it is important to work with shorter embeddings of the features. We have used CUR decomposition and Nystrom sampling to further reduce the feature space. To check the efficacy of this two-tier feature selection method, we have applied it to the features extracted by three standard deep learning models, namely VGG16, Xception and InceptionV3, where the features have been extracted from the CXR images of COVID-19 datasets and we have found that the selection procedure works quite well for the features extracted by Xception and InceptionV3. The source code of this work is available at https://github.com/subhankar01/covidfs-aihc.

Stress-induced miRNAs isolated from wheat have a unique therapeutic potential in ultraviolet-stressed human keratinocyte cells

Increasing evidence supports the existence of cross-kingdom gene regulation. However, the therapeutic potential of stress-specific plant miRNAs and their role in UV-related pathologies in human tissue remain largely unexplored. The aim of this study was to investigate the therapeutic potential and mechanisms of action of stress-induced miRNA cocktails (SI-WmiRs) from Einkorn wheat (Triticum monococcum L.) on human keratinocyte (HaCaT) cells exposed to a high dose of UV-B radiation. We used a biofactory approach and irradiated wheatgrass with UV-C for 240 min to obtain the specific SI-WmiRs that wheat produces to recover from UV stress. We followed the plant with molecular and biochemical analyses and extracted our SI-WmiRs at the most appropriate time (0 h and 6 h after UV-C application). Then, we applied the SI-WmiR cocktail to HaCaT cells exposed to high-dose of UV-B radiation. Our results show that UV-B radiation induced lipid peroxidation and DNA damage, as demonstrated by increased malondialdehyde (MDA) levels and changes in the RAPD band profile, respectively. UV stress also impaired IL6/JAK2/STAT3 signalling and activated the inflammatory mediators IL6 and TNF-α in HaCaT cells, leading to significant induction of apoptotic cell death. We found that SI-WmiR transfection prevents lipid peroxidation and oxidative stress-related DNA damage by increasing antioxidant (CuZn-SOD, Mn-SOD) and DNA repair (EXO1, SMUG1 and XRCC3) gene expression. In addition, SI-WmiRs regulated IL6/JAK2/STAT3 signalling by reducing JAK2 and STAT3 gene expression and phosphorylated protein levels compared to the control treatments. Moreover, SI-WmiRs inhibited pro-apoptotic BAX, Caspase 3 and Caspase 8 gene expression and protein levels to prevent apoptosis of UV-stressed HaCaT cells. Our results demonstrate that stress-induced wheat miRNAs produced using a biofactory approach have strong potential as a novel and effective alternative therapy for UV stress-related skin damage.

Individualised screening of diabetic foot: creation of a prediction model based on penalised regression and assessment of theoretical efficacy

AIMS/HYPOTHESIS

A large proportion of people with diabetes do not receive proper foot screening due to insufficiencies in healthcare systems. Introducing an effective risk prediction model into the screening protocol would potentially reduce the required screening frequency for those considered at low risk for diabetic foot complications. The main aim of the study was to investigate the value of individualised risk assignment for foot complications for optimisation of screening.

METHODS

From 2015 to 2020, 11,878 routine follow-up foot investigations were performed in the tertiary diabetes clinic. From these, 4282 screening investigations with complete data containing all of 18 designated variables collected at regular clinical and foot screening visits were selected for the study sample. Penalised logistic regression models for the prediction of loss of protective sensation (LOPS) and loss of peripheral pulses (LPP) were developed and evaluated.

RESULTS

Using leave-one-out cross validation (LOOCV), the penalised regression model showed an AUC of 0.84 (95% CI 0.82, 0.85) for prediction of LOPS and 0.80 (95% CI 0.78, 0.83) for prediction of LPP. Calibration analysis (based on LOOCV) presented consistent recall of probabilities, with a Brier score of 0.08 (intercept 0.01 [95% CI -0.09, 0.12], slope 1.00 [95% CI 0.92, 1.09]) for LOPS and a Brier score of 0.05 (intercept 0.01 [95% CI -0.12, 0.14], slope 1.09 [95% CI 0.95, 1.22]) for LPP. In a hypothetical follow-up period of 2 years, the regular screening interval was increased from 1 year to 2 years for individuals at low risk. In individuals with an International Working Group on the Diabetic Foot (IWGDF) risk 0, we could show a 40.5% reduction in the absolute number of screening examinations (3614 instead of 6074 screenings) when a 10% risk cut-off was used and a 26.5% reduction (4463 instead of 6074 screenings) when the risk cut-off was set to 5%.

CONCLUSIONS/INTERPRETATION

Enhancement of the protocol for diabetic foot screening by inclusion of a prediction model allows differentiation of individuals with diabetes based on the likelihood of complications. This could potentially reduce the number of screenings needed in those considered at low risk of diabetic foot complications. The proposed model requires further refinement and external validation, but it shows the potential for improving compliance with screening guidelines.

Identification of potential edible mushroom as SARS-CoV-2 main protease inhibitor using rational drug designing approach

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is highly pathogenic to humans and has created health care threats worldwide. This urgent situation has focused the researchers worldwide towards the development of novel vaccine or small molecule therapeutics for SARS-CoV-2. Although several vaccines have already been discovered and are in use for the masses, no therapeutic medication has yet been approved by FDA for the treatment of COVID-19. Keeping this in view, in the present study, we have identified promising hits against the main protease (M^pro) of SARS-CoV-2 from edible mushrooms. Structure-based virtual screening (VS) of 2433 compounds derived from mushrooms was performed with M^pro protein (6LU7). Four promising hits, namely, Kynapcin-12 (M_78), Kynapcin-28 (M_82), Kynapcin-24 (M_83), and Neonambiterphenyls-A (M_366) were identified based on the result of docking, Lipinski's rule, 100 ns molecular dynamics (MD) simulation and MM/PBSA binding free energy calculations. Finally, the inhibitory properties of these hits were compared with three known inhibitors, baicalein (1), baicalin (2), and biflavonoid (3). Data indicated that M_78, M_82 and M_83 compounds present in edible mushroom Polyozellus multiplex were potent inhibitors of M^proprotein (6LU7). It could be concluded that edible mushroom Polyozellus multiplex has potential activity against SARS-CoV-2 infection and identified molecules could be further explored as therapeutic inhibitors against SARS-CoV-2.

Application of cardiovascular risk scales to identify carotid atherosclerosis in patients with rheumatoid arthritis

Aim. To evaluate the cardiovascular risk (CVR) and analyze its relationship with detection of early carotid artery atherosclerotic lesion in patients with rheumatoid arthritis (RA). Materials and methods. One hundred and nine RA patients aged 45 to 60 without established cardiovascular diseases (CVD) were included in the study. The median age was 52 [48; 54] years, duration of RA was 120 [36; 204] months, DAS28 was 4.7 [3.5; 5.6] points. CVD risk was calculated with mSCORE, Reynolds Risk Score (RRS), ASSIGN, QRISK3, ERS-RA scales and Carotid Artery Doppler Ultrasound Exam was performed for all patients. Results. High risk was found in 5, 5, 14, 6, and 38% of patients according to mSCORE, RRS, ASSIGN, QRISK3, ERS-RA scales, respectively. Atherosclerotic plaques of carotid arteries were found in 30% of patients. It was found that carotid intima-media thickness is correlated to all CVR calculators, age, systolic and diastolic blood pressure, cholesterol, erythrocyte sedimentation rate, interleukin-6 levels. The sensitivity and specificity of the CVR algorithms in prognostication of atherosclerotic carotid artery lesions were 73 and 67% for mSCORE, 64 and 63% for RRS, 64 and 56% for ASSIGN, 73 and 49% for QRISK3, respectively, p0.05 in all cases, 67 and 50% for ERS-RA, p=0.06. Conclusion. RRS, mSCORE, ASSIGN, QRISK3 calculators equally predict atherosclerotic carotid artery damage in RA patients. The optimal ratio of specificity and sensitivity is shown for the mSCORE scale. Stratification of CVR in RA patients should include assessment of the carotid intima-media thickness. To identify CVR in RA patients, the most informative methods are mSCORE calculation and carotid intima-media thickness determination.

Research on a bifurcation location algorithm of a drainage tube based on 3D medical images

Based on patient computerized tomography data, we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model. To improve the efficiency and accuracy of identifying puncture points, a point-cloud search arithmetic method for modified adaptive weighted particle swarm optimization is proposed and used for optimal external axis extraction. According to the characteristics of the multitube drainage tube and the clinical needs of puncture for intracranial hematoma removal, the proposed algorithm can provide an optimal route for a drainage tube for the hematoma, the precise position of the puncture point, and preoperative planning information, which have considerable instructional significance for clinicians.

Pattern Reorganization of Corticomuscular Connection with the Tactile Stimulation

Sensitivity to tactile stimuli is an indispensable feedback in human motion control. However, previous studies on tactile stimulation mainly focused on the effects of superficial tactile stimulation on the motor cortex, but the role of deep tactile feedback stimulation in motor tasks is not clear. Corticomuscular coherence (CMC) is an effective method for studying dynamic motion tasks. Recent evidence suggests that CMC is enhanced by tactile stimulation in the beta-band. But, the mechanism of tactile stimulation in dynamic motor tasks is still undetermined. In order to explore the role of tactile stimulation in dynamic motion tasks, we examined the correlation between EEG/EMG in a motor task with tactile stimulus input, including the corticomuscular coherence and the causal connections (convergent cross mapping, CCM). In this study, seventeen subjects were recruited to complete stimuli and non-stimuli motor tasks. After the experiment, the time-frequency analysis of CMC showed that the somatosensory association cortex was clearly involved in the dynamic motor tasks. During the contraction of hand muscles, the activity of CMC was concentrated in gamma band, while in the maintenance process, it was concentrated in beta-band. After eliminating the distractors of attention, we did not find a similar result as previous studies had found-tactile stimuli lead to increased CMC activity in gamma band. On the contrary, CCM causality analysis showed that tactile stimulation could significantly enhance the connection between the cerebral cortex and a muscle. We speculate that tactile stimulation can enhance the corticomuscular causal relationship, and that the effect of tactile stimulation on corticomuscular coherence may have more complex mechanisms. This study provides new insights into neural mechanism of tactile feedback and provides more information about the causality of brain networks in tactile feedback task.