An Improved Theory for Designing and Numerically Calibrating Circular Touch Mode Capacitive Pressure Sensors.

The design, especially the numerical calibration, of a circular touch mode capacitive pressure sensor is highly dependent on the accuracy of the analytical solution of the contact problem between the circular conductive membrane and the rigid plate of the sensor. In this paper, the plate/membrane contact problem is reformulated using a more accurate in-plane equilibrium equation, and a new and more accurate analytical solution is presented. On this basis, the design and numerical calibration theory for circular touch mode capacitive pressure sensors has been greatly improved and perfected. The analytical relationships of pressure and capacitance are numerically calculated using the new and previous analytical solutions, and the gradually increasing difference between the two numerical calculation results with the gradual increase in the applied pressure is graphically shown. How to use analytical solutions and analytical relationships to design and numerically calibrate a circular touch mode capacitive pressure sensor with a specified pressure detecting range is illustrated in detail. The effect of changing design parameters on capacitance-pressure analytical relationships is comprehensively investigated; thus, the direction of changing design parameters to meet the required or desired range of pressure or capacitance is clarified.

Insights into Advanced Neurological Dysfunction Mechanisms Following DBS Surgery in Parkinson's Patients: Neuroinflammation and Pyroptosis.

Parkinson's disease is a severe neurodegenerative disorder. Currently, deep brain electrical stimulation (DBS) is the first line of surgical treatment. However, serious neurological impairments such as speech disorders, disturbances of consciousness, and depression after surgery limit the efficacy of treatment. In this review, we summarize the recent experimental and clinical studies that have explored the possible causes of neurological deficits after DBS. Furthermore, we tried to identify clues from oxidative stress and pathological changes in patients that could lead to the activation of microglia and astrocytes in DBS surgical injury. Notably, reliable evidence supports the idea that neuroinflammation is caused by microglia and astrocytes, which may contribute to caspase-1 pathway-mediated neuronal pyroptosis. Finally, existing drugs and treatments may partially ameliorate the loss of neurological function in patients following DBS surgery by exerting neuroprotective effects.

A simple ATTR-CM score to identify transthyretin amyloid cardiomyopathy burden in HFpEF patients.

BACKGROUND: Transthyretin amyloid cardiomyopathy (ATTR-CM) is often found in patients with heart failure with preserved ejection fraction (HFpEF). However, the evidence regarding ATTR-CM and prognosis in HFpEF remains scarce. This study sought to determine whether the ATTR-CM burden was associated with clinical outcomes in HFpEF patients. METHODS: We evaluated the associations of baseline ATTR-CM score with adverse outcomes in HFpEF patients from the TOPCAT trial using the Cox proportional hazards model or the competing risk regression model. The discriminatory ability of the ATTR-CM score was assessed using the area under the time-dependent receiver operating characteristic curve (AUC). RESULTS: We included 870 HFpEF patients, 18.9% of which had an ATTR-CM score ≥6. Per 1 increment in the ATTR-CM score was significantly associated with an increased risk of the primary outcome (adjusted hazard ratio [HR] 1.19, 95% confidence interval [CI] 1.12-1.27) with an AUC of 0.652 (0.594-0.711), whereas patients with ATTR-CM score ≥6 presented higher risks of the primary outcome (adjusted HR 2.20, 95% CI 1.65-2.95). Similar results were observed toward the secondary outcomes. CONCLUSIONS: The simple ATTR-CM score identified an 18.9% ATTR-CM burden in HFpEF patients, and a higher ATTR-CM burden might predict adverse outcomes with moderate discriminatory abilities in HFpEF.

Emotion Classification from Multi-Band Electroencephalogram Data Using Dynamic Simplifying Graph Convolutional Network and Channel Style Recalibration Module.

Because of its ability to objectively reflect people's emotional states, electroencephalogram (EEG) has been attracting increasing research attention for emotion classification. The classification method based on spatial-domain analysis is one of the research hotspots. However, most previous studies ignored the complementarity of information between different frequency bands, and the information in a single frequency band is not fully mined, which increases the computational time and the difficulty of improving classification accuracy. To address the above problems, this study proposes an emotion classification method based on dynamic simplifying graph convolutional (SGC) networks and a style recalibration module (SRM) for channels, termed SGC-SRM, with multi-band EEG data as input. Specifically, first, the graph structure is constructed using the differential entropy characteristics of each sub-band and the internal relationship between different channels is dynamically learned through SGC networks. Second, a convolution layer based on the SRM is introduced to recalibrate channel features to extract more emotion-related features. Third, the extracted sub-band features are fused at the feature level and classified. In addition, to reduce the redundant information between EEG channels and the computational time, (1) we adopt only 12 channels that are suitable for emotion classification to optimize the recognition algorithm, which can save approximately 90.5% of the time cost compared with using all channels; (2) we adopt information in the θ, α, ß, and γ bands, consequently saving 23.3% of the time consumed compared with that in the full bands while maintaining almost the same level of classification accuracy. Finally, a subject-independent experiment is conducted on the public SEED dataset using the leave-one-subject-out cross-validation strategy. According to experimental results, SGC-SRM improves classification accuracy by 5.51-15.43% compared with existing methods.

Hybrid Domain Consistency Constraints-Based Deep Neural Network for Facial Expression Recognition.

Facial expression recognition (FER) has received increasing attention. However, multiple factors (e.g., uneven illumination, facial deflection, occlusion, and subjectivity of annotations in image datasets) probably reduce the performance of traditional FER methods. Thus, we propose a novel Hybrid Domain Consistency Network (HDCNet) based on a feature constraint method that combines both spatial domain consistency and channel domain consistency. Specifically, first, the proposed HDCNet mines the potential attention consistency feature expression (different from manual features, e.g., HOG and SIFT) as effective supervision information by comparing the original sample image with the augmented facial expression image. Second, HDCNet extracts facial expression-related features in the spatial and channel domains, and then it constrains the consistent expression of features through the mixed domain consistency loss function. In addition, the loss function based on the attention-consistency constraints does not require additional labels. Third, the network weights are learned to optimize the classification network through the loss function of the mixed domain consistency constraints. Finally, experiments conducted on the public RAF-DB and AffectNet benchmark datasets verify that the proposed HDCNet improved classification accuracy by 0.3-3.84% compared to the existing methods.

Off-label underdosing of four individual NOACs in patients with nonvalvular atrial fibrillation: A systematic review and meta-analysis of observational studies.

BACKGROUND: Although several meta-analyses have examined the effects of off-label underdosing of nonvitamin K antagonist oral anticoagulants (NOACs) compared with their recommended doses in patients with atrial fibrillation (AF), they combined different kinds of NOACs in their primary analyses. Herein, we first conducted a meta-analysis to separately assess the effects of off-label underdosing versus on-label dosing of four individual NOACs on adverse outcomes in the AF population. METHODS: The PubMed and Embase database were systemically searched until November 2021 to identify the relevant studies. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were pooled by utilizing a random-effects model. RESULTS: A total of nine studies with 144,797 patients taking NOACs were included in the meta-analysis. In the pooled analysis, off-label underdosing of rivaroxaban was related to an increased risk of stroke or systemic embolism (HR = 1.31, 95% CI 1.05-1.63; p = .02), whereas off-label underdosing of apixaban was associated with a higher risk of all-cause death (HR = 1.21, 95% CI 1.05-1.40; p = .01). When comparing off-label underdosing versus on-label dosing of dabigatran or edoxaban, no differences were found in the primary and secondary clinical outcomes. CONCLUSION: Off-label underdosing of rivaroxaban may increase the risk of stroke or systematic embolism, whereas off-label underdosing of apixaban may heighten the incidence of all-cause death.

Fraxetin suppresses reactive oxygen species-dependent autophagy by the PI3K/Akt pathway to inhibit isoflurane-induced neurotoxicity in hippocampal neuronal cells.

Isoflurane, a common volatile anesthetic, has been widely used to provide general anesthesia in operations. However, exposure to isoflurane may cause widespread neurotoxicity in the developing animal brain. Fraxetin, a natural coumarin derivative extracted from the bark of Fraxinus rhynchophylla, possesses versatile pharmacological properties including anti-oxidative, anti-inflammatory, and neuroprotective effects. However, the effect and action mechanism of fraxetin on neurotoxicity induced by isoflurane are unknown. Reactive oxygen species (ROS) generation, cell viability, lactate dehydrogenase (LDH) release, and apoptosis were estimated by 2',7'-dichlorofluorescin-diacetate (DCFH-DA) staining, MTT, LDH release, and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick end-labeling (TUNEL) staining assays, respectively. The protein levels of light chain 3 (LC3)-I, LC3-II, p62, protein kinase B (Akt), and phosphorylated Akt (p-Akt) were detected by western blot analysis. Isoflurane induced ROS, LDH release, apoptosis, and autophagy, but inhibited the viability in HT22 cells, which were overturned by fraxetin or ROS scavenger N-acetyl-L-cysteine. Fraxetin suppressed isoflurane-induced PI3K/Akt inactivation in HT22 cells. PI3K/Akt inactivation by LY294002 resisted the effects of fraxetin on isoflurane-induced autophagy and autophagy-modulated neurotoxicity in HT22 cells. In conclusion, fraxetin suppressed ROS-dependent autophagy by activating the PI3K/Akt pathway to inhibit isoflurane-induced neurotoxicity in hippocampal neuronal cells.

Impact of the COVID-19 pandemic on career intention amongst undergraduate medical students: a single-centre cross-sectional study conducted in Hubei Province.

BACKGROUND: Undergraduate medical (UM) students faced the difficulties inherent in medical careers due to the coronavirus (COVID-19) outbreak. Thus, imperative containment measures might affect UM students' career intentions. Information on the factors that may be associated with these students' career change intentions is limited. METHODS: We conducted a cross-sectional survey in August 2020 to investigate the impact of the COVID-19 pandemic on career intention and the associated factors in UM students. Univariate analyses and logistic regression analysis were performed to identify said factors. RESULTS: A total of 2040 medical students from the Hubei University of Medicine were surveyed. Univariate analyses showed that grade, attitude towards healthcare, and the degree of the COVID-19 pandemic's impact on the students' lives were associated with changes in career choice (P<0.05). Logistic regression analysis showed that Grade 2, Grade 5, attitude towards a medical career, and having relatives with a medical background were associated with changes in career choice. The degree of the COVID-19 pandemic's impact was a common and significant factor associated with career preference, career perspective, and ideal workplace. CONCLUSIONS: Changes in career intentions were particularly influenced by grade, attitude towards being a health worker, and the degree of COVID-19's impact on the participants' lives. Treating large-scale public health emergencies rationally, setting up correct views of occupation choice, and building reasonable career planning may reduce the loss of medical talent.

A Further Theoretical Study of Capacitive Pressure Sensors Based on Thin Film Elastic Deflection and Parallel Plate Capacitor: Refined Closed-Form Solution and Numerical Calibration.

The capacitive pressure sensor based on thin film elastic deflection and a parallel plate capacitor uses a non-conductive elastic annular thin film centrally connected to a conductive, rigid, flat, concentric-circular thin plate as a pressure sensing unit. On application of pressure, the non-conductive thin film deflects elastically, which in turn moves the conductive thin plate (as a movable upper electrode plate of the parallel plate capacitor) towards the lower electrode plate, resulting in a change in the capacitance of the capacitor. Therefore, the applied pressure can be determined by measuring the capacitance change, based on the closed-form solution for the elastic behavior of the annular thin film under pressure. Such capacitive pressure sensors are more suitable for large-sized sensors such as those used for building-facade wind pressure measurements, etc. In this paper, a further theoretical study of such capacitive pressure sensors is presented. The newly presented, more refined closed-form solution can greatly reduce the output pressure error under the same input capacitance, in comparison with the previously presented closed-form solution. A numerical example of how to use the resulting closed-form solution to numerically calibrate input-output characteristics is given for the first time. The variation trend of pressure operation ranges and input-output characteristics with important parametric variations, which can be used for guiding the design of such capacitive pressure sensors, is investigated.

EEG Emotion Classification Network Based on Attention Fusion of Multi-Channel Band Features.

Understanding learners' emotions can help optimize instruction sand further conduct effective learning interventions. Most existing studies on student emotion recognition are based on multiple manifestations of external behavior, which do not fully use physiological signals. In this context, on the one hand, a learning emotion EEG dataset (LE-EEG) is constructed, which captures physiological signals reflecting the emotions of boredom, neutrality, and engagement during learning; on the other hand, an EEG emotion classification network based on attention fusion (ECN-AF) is proposed. To be specific, on the basis of key frequency bands and channels selection, multi-channel band features are first extracted (using a multi-channel backbone network) and then fused (using attention units). In order to verify the performance, the proposed model is tested on an open-access dataset SEED (N = 15) and the self-collected dataset LE-EEG (N = 45), respectively. The experimental results using five-fold cross validation show the following: (i) on the SEED dataset, the highest accuracy of 96.45% is achieved by the proposed model, demonstrating a slight increase of 1.37% compared to the baseline models; and (ii) on the LE-EEG dataset, the highest accuracy of 95.87% is achieved, demonstrating a 21.49% increase compared to the baseline models.

PINK1 mediated mitophagy attenuates early apoptosis of gingival epithelial cells induced by high glucose.

BACKGROUND: Oxidative stress mediated by hyperglycemia damages cell-reparative processes such as mitophagy. Down-regulation of mitophagy is considered to be a susceptible factor for diabetes mellitus (DM) and its complications. However, the role of mitophagy in DM-associated periodontitis has not been fully elucidated. Apoptosis of human gingival epithelial cells (hGECs) is one of the representative events of DM-associated periodontitis. Thus, this study aimed to investigate PTEN-induced putative kinase 1 (PINK1)-mediated mitophagy activated in the process of high glucose (HG)-induced hGECs apoptosis. METHODS: For dose-response studies, hGECs were incubated in different concentrations of glucose (5.5, 15, 25, and 50 mmol/L) for 48 h. Then, hGECs were challenged with 25 mmol/L glucose for 12 h and 48 h, respectively. Apoptosis was detected by TdT-mediated dUTP nick end labeling (TUNEL), caspase 9 and mitochondrial membrane potential (MMP). Subsequently, autophagy was evaluated by estimating P62, LC3 II mRNA levels, LC3 fluorescent puncta and LC3-II/I ratio. Meanwhile, the involvement of PINK1-mediated mitophagy was assessed by qRT-PCR, western blotting and immunofluorescence. Finally, hGECs were transfected with shPINK1 and analyzed by MMP, caspase 9 and annexin V-FITC apoptosis. RESULTS: The number of TUNEL-positive cells and caspase 9 protein were significantly increased in cells challenged with HG (25 mmol/L) for 48 h (HG 48 h). MMP was impaired both at HG 12 h and HG 48 h, but the degree of depolarization was more serious at HG 48 h. The autophagy improved as the amount of LC3 II increased and p62 decreased in HG 12 h. During this process, HG 12 h treatment induced PINK1-mediated mitophagy. PINK1 silencing with HG 12 h resulted in MMP depolarization and cell apoptosis. CONCLUSIONS: These results suggested that loss of the PINK1 gene may cause mitochondrial dysfunction and increase sensitivity to HG-induced apoptosis of hGECs at the early stage. PINK1 mediated mitophagy attenuates early apoptosis of gingival epithelial cells induced by high glucose.

An Improved Tiered Head Pose Estimation Network with Self-Adjust Loss Function.

As an important task in computer vision, head pose estimation has been widely applied in both academia and industry. However, there remains two challenges in the field of head pose estimation: (1) even given the same task (e.g., tiredness detection), the existing algorithms usually consider the estimation of the three angles (i.e., roll, yaw, and pitch) as separate facets, which disregard their interplay as well as differences and thus share the same parameters for all layers; and (2) the discontinuity in angle estimation definitely reduces the accuracy. To solve these two problems, a THESL-Net (tiered head pose estimation with self-adjust loss network) model is proposed in this study. Specifically, first, an idea of stepped estimation using distinct network layers is proposed, gaining a greater freedom during angle estimation. Furthermore, the reasons for the discontinuity in angle estimation are revealed, including not only labeling the dataset with quaternions or Euler angles, but also the loss function that simply adds the classification and regression losses. Subsequently, a self-adjustment constraint on the loss function is applied, making the angle estimation more consistent. Finally, to examine the influence of different angle ranges on the proposed model, experiments are conducted on three popular public benchmark datasets, BIWI, AFLW2000, and UPNA, demonstrating that the proposed model outperforms the state-of-the-art approaches.

NPAS4 suppresses propofol-induced neurotoxicity by inhibiting autophagy in hippocampal neuronal cells.

Propofol, a general intravenous anesthetic, has been demonstrated to cause a profound neuroapoptosis in the developing brain followed by long-term neurocognitive impairment. Our study aimed to examine the neuroprotective effect of neuronal PAS domain protein 4 (NPAS4), an activity-dependent neuron-specific transcription factor, on propofol-induced neurotoxicity in hippocampal neuronal HT22 cells. The differentially expressed genes in HT22 cells after treatment with propofol were screened from Gene Expression Omnibus dataset GSE106799. NPAS4 expression in HT22 cells treated with different doses of propofol was investigated by qRT-PCR and Western blot analysis. Cell viability, lactate dehydrogenase (LDH) release, caspase-3 activity, and apoptosis were evaluated by MTT, a LDH-Cytotoxicity Assay Kit, a Caspase-3 Colorimetric Assay Kit, and TUNEL assay, respectively. The protein levels of LC3-I, LC3-II, Beclin 1, p62 and NPAS4 were detected using Western blot analysis. Propofol treatment concentration-dependently decreased NPAS4 expression in HT22 cells. Propofol treatment inhibited cell viability, increased LDH release and caspase-3 activity, and induced apoptosis and autophagy in HT22 cells. NPAS4 overexpression suppressed propofol-induced cell injury and autophagy in HT22 cells. Mechanistically, autophagy agonist rapamycin attenuated the neuroprotective effect of NPAS4 in propofol-treated HT22 cells. In conclusion, NAPS4 overexpression protected hippocampal neuronal HT22 cells against propofol-induced neurotoxicity by reducing autophagy.

Adipose-derived mesenchymal stem cells ameliorate the inflammatory reaction in CLP-induced septic acute lung injury rats via sTNFR1.

We hypothesized that the adipose-derived mesenchymal stem cells (ADMSCs), which secrete high amounts of soluble molecules, such as soluble tumor necrosis factor receptor 1 (sTNFR1), may ameliorate sepsis-induced acute lung injury (ALI). A total of 120 male adult Sprague-Dawley rats were separated into four groups: the sham control (SC), sepsis induced by cecal ligation and puncture (CLP), CLP-ADMSCs, and CLP-sTNFR1 small interfering RNA (siRNA) groups; CLP groups underwent CLP and then received 1 × 106 ADMSCs with or without knockdown of sTNFR1 intravenously at 1 hr after surgery. Rats were killed at 3, 6, 24, and 48 hr after the SC or CLP procedures. 5-Ethynyl-2'-deoxyuridine-labeled ADMSCs extensively colonized the lungs at 6, 24, and 72 hr after injection. The lung wet/dry (W/D) weight ratios in the CLP group were higher than those in SC group; however, ADMSCs ameliorated the W/D weight ratios following CLP, and this effect was abolished by sTNFR1 siRNA treatment. The levels of serum sTNFR1 and interleukin-10 (IL-10) were higher in the CLP-ADMSCs group and lower in the SC group than in other groups; interestingly, these levels were higher in CLP and CLP-sTNFR1 siRNA groups than in SC group. Tumor necrosis factor-α and IL-6 levels increased significantly after CLP, and ADMSCs could alleviate these changes, but the effect was weakened by sTNFR1 siRNA treatment. The lung cell apoptosis and edema levels were consistent with IL-6 levels among all groups. Therapeutically administered ADMSCs secrete sTNFR1, which most likely protects against ALI in septic rats by ameliorating inflammation and lung edema.

Inhibition of potassium currents is involved in antiarrhythmic effect of moderate ethanol on atrial fibrillation.

Excessive consumption of alcohol is a well-established risk factor of atrial fibrillation (AF). However, the effects of moderate alcohol drinking remain to be elucidated. This study was designed to determine the effects of moderate ethanol ingestion on atrial fibrillation and the electrophysiological mechanisms. In acetylcholine-induced canine and mouse AF models, the moderate ethanol prevented the generation and persistence of AF through prolonging the latent period of AF and shortening the duration of AF. The action potential duration (APD) was remarkably prolonged under the concentration range of 12.5-50.0mM ethanol in guinea pig atrial myocytes. Ultra-rapid delayed rectified potassium currents (IKv1.5) were markedly inhibited by 12.5-50.0mM ethanol in a concentration-dependent manner. Ethanol with 50.0mM could inhibit rapid delayed rectifier potassium currents (IhERG). Ethanol under 6.25-50.0mM did not affect on inward rectifier potassium currents (IKir2.1). Collectively, the present study provided an evidence that moderate ethanol intake can prolong the APD of atrial myocytes by inhibition of IKv1.5 and IhERG, which contributed to preventing the development and duration of AF.

High-power 1018 nm ytterbium-doped fiber laser with output of 805 W.

This Letter presents a high-power 1018 nm ytterbium-doped fiber laser (YDFL) with optimized parameters. A record output power reaching 805 W was achieved, along with a light-to-light efficiency of 64.9% and a beam quality factor of M2=1.80. Further, a higher efficiency of 82.8% of 1018 nm YDFL pumped by wavelength-stabilized laser diodes for the first time, to the best of our knowledge, was shown. At last some attempts were made in bidirectional pumping structure. In this Letter, all the measured spectra showed strong amplified spontaneous emission suppression, and the power curves indicated the potential for further power scaling.

Kilowatt-level cladding light stripper for high-power fiber laser.

We designed and fabricated a high-power cladding light stripper (CLS) by combining a fiber-etched CLS with a cascaded polymer-recoated CLS. The etched fiber reorganizes the numerical aperture (NA) distribution of the cladding light, leading to an increase in the leakage power and a flatter distribution of the leakage proportion in the cascaded polymer-recoated fiber. The index distribution of the cascaded polymer-recoated fiber is carefully designed to ensure an even leakage of cladding light. More stages near the index of 1.451 are included to disperse the heat. The CLS is capable of working consistently under 1187 W of cladding light with an attenuation of 26.59 dB, and the highest local temperature is less than 35°C.

933 W Yb-doped fiber ASE amplifier with 50.4 nm bandwidth.

In this paper, a 933 W amplified spontaneous emission (ASE) source with a full width at half maximum (FWHM) of 50.4 nm is presented. The broadband source is generated by a 1271 W ASE amplifier together with 140m ordinary passive fiber for nonlinear transformation. With multi-wavelength rate equations and a nonlinear Schrödinger equation (NLSE), spectral evolution of the ASE source is analyzed theoretically.

24 Y-chromosomal STR haplotypic polymorphisms for Chinese Uygur ethnic group and its phylogenic analysis with other Chinese groups.

The Uygur ethnic minority is the largest ethnic group in the Xinjiang Uygur Autonomous Region of China, and is a precious resource for the study of ethnogeny and forensic biology. Previous studies have focused on the genetic background of the Uygur group, however, the patrilineal descent of the group is still unclear. In this study, we investigated the genetic diversity of 24 Y-STR loci in the Uygur group and analyzed the population differentiations as well as the genetic relationships between the Uygur group and other previously reported populations using 17 Y-filer loci. According to haplotypic analysis of the 24 Y-STR loci in 109 Uygur individuals, 104 different haplotypes were obtained, 99 of which were unique. The haplotypic diversity and discrimination capacity of these 24 Y-STR loci in Uygur group were 0.9992 and 0.9541, respectively. An additional 7 loci (DYS388, DYS444, DYS447, DYS449, DYS522, and DYS527a,b) showed high genetic diversity and improved the overall discrimination capacity of the 24 Y-STR system. Pairwise Fst and neighbor-joining analysis showed that the Uygur group was genetically close to the Han populations from different regions.