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Stimulated Raman scattering (SRS) is an efficient nonlinear frequency conversion method, enabling simultaneous generation of red, green, and blue (RGB) lasers. In order to synthesize a white light source for laser display by SRS, a 532 nm laser was used as pump source, and high purity gaseous carbon dioxide (CO2) was used as the Raman active medium. First, by optimizing experimental parameters, with an f = 1.5 m focal lens, in 0.8 atm CO2 pumped at 304 mJ, a first-order anti-Stokes (AS1) 495 nm blue laser was achieved, with an energy of 31.9 mJ, peak power of 10.9 MW and conversion efficiency (CE) of 10.5 %. Then, Then, the second-order Stokes light (S2) at 624 nm, residual pump laser (S0) at 532 nm, and AS1 laser were utilized as RGB primary colors. By the variation of pressure below 1 atmosphere (atm), the laser-driven white light (LDWL) with adjustable correlated color temperature (CCT) below 4700 K were simulated. Finally, LDWL up to 2.6 × 1018cd/m2 of a CCT of 3300 K could be synthesized at an RGB power ratio of PR: PG: PB = 0.447:0.094:0.459, resulting in a white light power CE of 44.4 % and luminous efficacy of 113.7 lm/W. In addition, use of the 574 nm yellow Raman light is expected to realize a four-primary (RGBY) laser display scheme with higher Luminance and broader color gamut. Moreover, the feasibility of using a 515 nm Yb: YAG laser as pump source to widen the range of CCT and improve the brightness of LDWL was discussed.

Multicentric reticulohistiocytosis (MRH) is a rare systemic disorder characterized by histiocytic hyperplasia that mainly involves the skin, mucous membranes, and joints. The typical clinical features include papules, nodules, and arthritis. MRH lesions are relatively extensive but small and scattered. Joint inflammation is characterized by diffuse symmetric polyarthritis as the first symptom, which can be severe and disabling due to destructive joint changes. MRH is easily misdiagnosed in clinical practice. Here, we report the case of an elderly male patient who presented with polyarticular pain in the hip and interphalangeal joints as the first manifestation, followed by the development of large, isolated, bulging skin nodules, which are atypical MRH lesions. This is rare in all MRH case reports, and we made the correct diagnosis by combining skin histopathology, immunohistochemistry, and other clinical examinations. We performed surgical treatment on the local skin lesions of this patient. This case suggests that clinicians should actively correlate the condition and accurately diagnose MRH when encountering atypical skin changes or other diseases as the first symptom and explore the mechanisms of MRH and other clinical manifestations.

In this work, 532 nm laser was used as the pump source and pressurized ethane was used as Raman active medium; 631.3 nm first Stokes (S1) and 776.0 nm second Stokes (S2) Raman lasers were generated. By the optimization of ethane pressure and focus lens, S2 and backwards first Stokes Raman conversion could be reduced, while the conversion of S1 could be improved. Under 2.0 MPa ethane and focal length of 1.5 m, the maximum S1 conversion efficiency of 84.5% was achieved. Up to 68.7 mJ S1 Raman laser was obtained, and the corresponding peak power is 17.2 MW. By the comparison of the threshold of methane Raman laser, Raman gain coefficients of ethane were estimated to be 0.50 × 10−12 m/W at 0.5 MPa and 0.76 × 10–12 m/W at 1.4 MPa ethane respectively.

Abstract Background Both stenosis rate and intraplaque hemorrhage (IPH) are important predictors of stroke risk. Simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) cardiovascular magnetic resonance (CMR) imaging can detect both stenosis rate and IPH. We aimed to evaluate consistency between SNAP and digital subtraction angiography (DSA) to assess symptomatic patients with stroke and explore the performance of SNAP to identify IPH and the clinical factors associated with IPH. Methods Eighty-one symptomatic patients with stroke, admitted to Wuhan Union Hospital who underwent CMR high-resolution vessel wall imaging (HR-VWI) and SNAP, were retrospectively identified. For patients who received interventional therapy, the imaging functions of SNAP and HR-VWI were compared with DSA. The diameters of the intracranial and carotid vessels were measured, and stenotic vessels were identified. The consistency of SNAP and HR-VWI in identifying IPH was also examined, and the correlations between IPH and clinical factors were analyzed. Results SNAP was more consistent with DSA than HR-VWI in measuring vascular stenosis (intraclass correlation coefficient [ICC]SNAP-DSA = 0.917, ICC HR-VWI-DSA = 0.878). Regarding the diameter measurements of each intracranial and carotid vessel segment, SNAP was superior or similar to HR-VWI, and both were consistent with DSA in the measurement of major intracranial vascular segments. HR-VWI and SNAP exhibited acceptable agreement in identifying IPH (Kappa = 0.839, 95% confidence interval [CI]: 0.704–0.974). Patients who underwent interventional therapy had a higher plaque burden (P

AimsCognitive impairment is an increasingly urgent global public health challenge. Dietary Inflammatory Index (DII) is a literature-derived score that links diet to inflammation. The relationship between DII and cognitive impairment remains controversial. Therefore, our study aimed to analysis the role of DII on the risk of cognitive impairment by meta-analysis.MethodsPubMed, Cochrane Library, MEDLINE, Web of Science and EMBASE databases were searched up to July 2022. Newcastle–Ottawa scale (NOS) and Joanna Briggs Institute (JBI) Checklist were performed to estimate the quality of studies.ResultsNine observational studies with 19,379 subjects were included. Our study found that higher DII could elevate the risk of cognitive impairment (OR = 1.46, 95%CI = 1.26, 1.69). Meanwhile, the OR of cognitive impairment was 1.49 (95%CI = 1.21, 1.83) for cross-sectional studies and 1.42 (95%CI = 1.12, 1.79) for cohort studies, respectively.ConclusionOur meta-analysis indicated that higher DII (indicating a more pro-inflammatory diet) is related to increased risk of cognitive impairment.

The anaplastic lymphoma kinase (ALK) gene rearrangement is a driving mutation that underlies about 5-6% of non-small cell lung cancer (NSCLC) cases. Lung cancers that are ALK gene rearrangement-positive can be effectively treated with ALK inhibitors. However, the response of patients with rarer ALK gene rearrangements to ALK inhibitors remains unknown. Herein, we described a case of lung adenocarcinoma carrying ALK-HLA-DRB1 fusion in a 48-year-old nonsmoking woman. A similar case of ALK-HLA-DRB1 rearrangement in NSCLC has not been described previously neither in NSCLC nor in other disease. The patient achieved a progression-free survival of 18 months after sequential therapy consisting of crizotinib and then ceritinib during the follow-up. These findings provide basis for the application of ALK inhibitors in patients carrying the rare ALK-HLA-DRB1 fusion.

Although there have been remarkable advances in cartilage tissue engineering, construction of irregularly shaped cartilage, including auricular, nasal, tracheal, and meniscus cartilages, remains challenging because of the difficulty in reproducing its precise structure and specific function. Among the advanced fabrication methods, three-dimensional (3D) printing technology offers great potential for achieving shape imitation and bionic performance in cartilage tissue engineering. This review discusses requirements for 3D printing of various irregularly shaped cartilage tissues, as well as selection of appropriate printing materials and seed cells. Current advances in 3D printing of irregularly shaped cartilage are also highlighted. Finally, developments in various types of cartilage tissue are described. This review is intended to provide guidance for future research in tissue engineering of irregularly shaped cartilage.

Mastitis is one of the most serious diseases that causes losses in the dairy industry, seriously impairing milk production and milk quality, and even affecting human health. Menthol is a cyclic monoterpene compound obtained from the stem and leaves of peppermint, which has a variety of biological activities, including anti-inflammatory and antioxidant activity. The purpose of this study was to investigate the preventive effect of menthol on the lipopolysaccharide-induced inflammatory response in primary bovine mammary gland epithelial cells (BMECs) and its anti-inflammatory mechanism. First, BMECs were isolated and amplified from the udders of Holstein cows by enzymatic hydrolysis. BMECs were treated with menthol (10, 50, 100, 200 μM) for 1h, followed by lipopolysaccharide (5μg/ml) for 12 h. Lipopolysaccharide treatment upregulated the protein levels of cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (INOS) and the mRNA abundance of tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β), while menthol was able to inhibit this effect. The inhibitory effect of menthol on proinflammatory factors was significantly reduced when autophagy was blocked using 3-Methyladenine (5μg/ml), an inhibitor of autophagy. Furthermore, lipopolysaccharide treatment reduced the expression levels of milk lipids and milk proteins, which were inhibited by menthol. In addition, menthol (200 μM) treatment was able to significantly upregulate the expression level of autophagy-related protein LC3B, downregulate the expression level of P62, promote the expression abundance of autophagy-related gene mRNA, and enhance significantly enhance autophagic flux. Interestingly, treatment of BMECs with menthol (200 μM) promoted the phosphorylation of AMP-activated protein kinase (AMPK) and unc-51 like kinase 1 (ULK1) and increased the nuclear localization of nuclear factor-E2 associated factor 2 (Nrf-2). When the AMPK pathway was blocked using compound C (10μg/ml), an inhibitor of AMPK, autophagy was significantly inhibited. Autophagy levels were significantly decreased after blocking the Nrf-2 pathway using ML385 (5μg/ml), an inhibitor of Nrf-2. Overall, the data suggest that menthol activates the AMPK-ULK1 pathway to initiate the onset of autophagy and maintains the level of autophagy through the AMPK-Nrf-2 pathway. In conclusion, the findings suggest that menthol may alleviate the inflammatory response in BMECs via the AMPK/ULK1/Nrf-2/autophagy pathway.

Abstract Background Disease comorbidity is very common and has significant impact on disease treatment. Revealing the associations among diseases may help to understand the mechanisms of diseases, improve the prevention and treatment of diseases, and support the discovery of new drugs or new uses of existing drugs. Methods In this paper, we introduced a mathematical model to represent gene related diseases with a series of associated genes based on the overrepresentation of genes and diseases in PubMed literature. We also illustrated an efficient way to reveal the implicit connections between COPD and other diseases based on this model. Results We applied this approach to analyze the relationships between Chronic Obstructive Pulmonary Disease (COPD) and other diseases under the Lung diseases branch in the Medical subject heading index system and detected 4 novel diseases relevant to COPD. As judged by domain experts, the F score of our approach is up to 77.6%. Conclusions The results demonstrate the effectiveness of the gene fingerprint model for diseases on the basis of medical literature.

Background: Depression is a major psychiatric disorder and the leading cause of disability worldwide. Previous evidence suggested certain pattern of structural alterations were induced by major depression disorder (MDD) with heterogeneity due to patients' clinical characteristics and proposed that early impairment of fronto-limbic-striatal circuit was involved. Yet the hypothesis couldn't be replicated fully. Accordingly, this study aimed to validate this hypothesis in a new set of first-episode, drug naïve MDD patients and further explore the neuroimaging biomarker of illness severity using whole-brain voxel-based morphometry (VBM).Materials and Methods: A total of 93 participants, 30 patients with first-episode medication-naïve MDD, and 63 healthy controls were enrolled in the study. VBM was applied to analyze differences in the gray matter volume (GMV) between these two groups. The correlation between the GMV of the identified brain regions and the severity of clinical symptoms quantified by the Hamilton Depression Scale (HAMD) was further conducted in the post-hoc analysis to confirm the role of GMV structural alteration in clinical symptoms.Results: Our results revealed that the brain gray matter volume of the prefrontal lobe, limbic system, striatum, cerebellum, temporal lobe, and bilateral lingual gyri were significantly decreased in MDD patients compared with healthy controls. Besides, the HAMD scores were negatively correlated with GMV of the right insula and positively correlated with that of the right lingual gyrus.Conclusions: Our findings provide robust evidence that gray matter structural abnormalities within the prefronto-limbic-striatal circuit are implicated in the pathophysiology of MDD at an early stage without confounding influence of medication status. Besides, our data suggest that the cerebellum, lingual gyrus, and fusiform gyrus should also be integrated into the brain alterations in MDD. Future synthesis of individual neuroimaging studies and more advanced statistical analysis comparing subfields of the aforementioned regions are warranted to further shed light on the neurobiology of the disease and assist in the diagnosis of this burdensome disorder.

We demonstrated mid-infrared gaseous stimulated Raman scattering lasers in free space. Mixed gases of hydrogen and deuterium were used as Raman gain media in one Raman cell. Pumped by laser pulses at 1064 nm, the first Stokes Raman components at 1560 nm and 1907 nm were generated. A four-wave mixing process with the pump laser at 1064 nm and Raman lasers at 1560 nm and 1907 nm contributed to dramatically reducing the threshold of mid-IR laser generation at 4432 nm. The maximum output peak power of a mid-IR laser at 4432 nm reached 121 kW. Furthermore, by scattering on the rotational transition of deuterium, multispectral mid-IR Raman lasers at wavelengths of 2071 nm, 2266 nm, 2604 nm, 2920 nm, 3322 nm, 3743 nm, 4432 nm, and 5431 nm were also generated. Our results show that this is a convenient method to reduce the threshold and achieve a high power output with mid-IR Raman lasers.

Background and Purpose: Many imaging studies have reported structure alterations in patients with type 1 diabetes mellitus (T1DM) by using voxel-based morphometry (VBM). Nevertheless, the results reported were inconsistent and had not been reviewed quantitatively. Accordingly, the quantitative meta-analysis which including VBM studies of patients with T1DM was conducted.Materials and Methods: The gray matter volume alterations in patients with T1DM was estimated by using the software seed-based d mapping. Meantime, the meta-regression was applied to detect the effects of some demographics and clinical characteristics.Results: Six studies were finally included, which with 6 datasets comprising 414 T1DM patients and 216 healthy controls. The pooled meta-analyses detected that patients with T1DM showed robustly increased gray matter volume in the left dorsolateral superior frontal gyrus and middle frontal gyrus and a decreased gray matter volume in the right lingual gyrus, cerebellum, precuneus, the left inferior temporal gyrus, and middle temporal gyrus. The meta-regression showed that the mean age, the female patient's ratio, duration of illness and HbAlc% for T1DM patients were not linearly related with gray matter alterations.Conclusion: This meta-analysis demonstrates that gray matter volume decreases in T1DM patients were mainly locates in the cortical regions and cerebellum.

Abstract Background Suicide has been one of the leading causes of deaths in the United States. One major cause of suicide is psychiatric stressors. The detection of psychiatric stressors in an at risk population will facilitate the early prevention of suicidal behaviors and suicide. In recent years, the widespread popularity and real-time information sharing flow of social media allow potential early intervention in a large-scale population. However, few automated approaches have been proposed to extract psychiatric stressors from Twitter. The goal of this study was to investigate techniques for recognizing suicide related psychiatric stressors from Twitter using deep learning based methods and transfer learning strategy which leverages an existing annotation dataset from clinical text. Methods First, a dataset of suicide-related tweets was collected from Twitter streaming data with a multiple-step pipeline including keyword-based retrieving, filtering and further refining using an automated binary classifier. Specifically, a convolutional neural networks (CNN) based algorithm was used to build the binary classifier. Next, psychiatric stressors were annotated in the suicide-related tweets. The stressor recognition problem is conceptualized as a typical named entity recognition (NER) task and tackled using recurrent neural networks (RNN) based methods. Moreover, to reduce the annotation cost and improve the performance, transfer learning strategy was adopted by leveraging existing annotation from clinical text. Results & conclusions To our best knowledge, this is the first effort to extract psychiatric stressors from Twitter data using deep learning based approaches. Comparison to traditional machine learning algorithms shows the superiority of deep learning based approaches. CNN is leading the performance at identifying suicide-related tweets with a precision of 78% and an F-1 measure of 83%, outperforming Support Vector Machine (SVM), Extra Trees (ET), etc. RNN based psychiatric stressors recognition obtains the best F-1 measure of 53.25% by exact match and 67.94% by inexact match, outperforming Conditional Random Fields (CRF). Moreover, transfer learning from clinical notes for the Twitter corpus outperforms the training with Twitter corpus only with an F-1 measure of 54.9% by exact match. The results indicate the advantages of deep learning based methods for the automated stressors recognition from social media.

Abstract A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

Background The safety of vaccines is a critical factor in maintaining public trust in national vaccination programs. This study aimed to evaluate the safety profiles of human papillomavirus (HPV) vaccines with regard to the distribution of adverse events (AE) across gender and age, and the correlations across various AEs using the Food and Drug Administration/Centers for Disease Control and Prevention Vaccine Adverse Event Reporting System (VAERS). Methods For analyses, 27,348 patients aged between 9 and 25 years old with at least one AE reported in VAERS between the year of 2006 and 2017 were included. AEs were summarized into two levels: the lower level preferred term (PT) and higher level system organ classes (SOCs) based on the structure of Medical Dictionary for Regulatory Activities (MedDRA). A series of statistical analyses were applied on both levels of AEs. Zero-truncated Poisson regression and multivariate logistic regression models were first developed to assess the rate and risk of SOCs across age groups and genders. Pairwise Pearson correlation analyses and hierarchical clustering analyses were then conducted to explore the interrelationships and clustering pattern among AEs. Results We identified 27,337 unique HPV vaccine reports between 2006 and 2017. Disproportional reporting of AEs was observed across age and gender in 21 SOCs (p < 0.05). The correlation analyses found most SOCs demonstrate weak positive correlations except for five pairs which were negatively correlated: skin and subcutaneous tissue disorders + injury poisoning and procedural complications; skin and subcutaneous tissue disorders + nervous system disorders; Skin and subcutaneous tissue disorders + pregnancy, puerperium and perinatal conditions; nervous system disorders + pregnancy, puerperium and perinatal conditions; pregnancy, puerperium and perinatal conditions + general disorders and administration site conditions. Nervous system disorders had the most AEs which contributed to 12,448 (46%) cases. In the further analyses of correlations between PT in nervous system disorders, the three most strongly correlated AEs were psychiatric disorders (r = 0.35), gastrointestinal disorders (r = 0.215), and musculoskeletal and connective tissue disorders (r = 0.261). We observed an inter-SOCs correlation of the PTs among AE pairs by nervous system disorders/psychiatric disorders/gastrointestinal disorders/musculoskeletal and connective tissue disorders. Conclusions The analyses revealed a different distribution pattern of AEs across gender and age subgroups in 21 SOC level AEs. Correlation analyses and hierarchical clustering analyses further revealed several correlated patterns across various AEs. However, findings from this study should be interpreted with caution. Further clinical studies are needed to understand the heterogeneity of AEs reporting across subgroups and the biological pathways among the statistically correlated AEs.

Background There are many problems with fitness trackers, such as device usability, which limit their large-scale application, and relevant studies are limited in terms of their sample size and evaluation methods. The purpose of the study was to evaluate the perceived usability of various mainstream fitness trackers on the market, and to learn about user feedback on feature preferences for each device. Methods Trial use of seven mainstream fitness trackers (two smart watches and five smart wristbands) followed by a survey study were applied. The questionnaire was specifically developed for this study, which included two parts (user preferences and device usability in five dimensions). We recruited users to test the devices for at least 30 days and asked experienced users to provide feedback in order to evaluate each device, including the rating and user preference of each device. Results We received 388 valid questionnaires, in which users rated their responses on a five-point Likert scale. (1) User preference: the average user satisfaction was 3.50–3.86 (points), and the rating for willingness to buy averaged between 3.36 and 3.59. More users were willing to wear (58.3–81.3%) and purchase (56.8–83.0%) the devices than were not. The top three general feature preferences were daily activity tracking, heart health monitoring, and professional fitness tracking. The top three health-related feature preferences were heart rate monitoring, daily pedometer, and professional fitness tracking. (2) Usability evaluation: product design was rated from 3.57 to 4.00; durability, 3.63–4.26; ease of use, 3.70–3.90; added features, 3.30–3.83; and user-rated accuracy, 3.44–3.78. A significant difference was observed in the rating of product design and durability among the different devices (p < 0.05) score. Conclusions Users generally had positive subjective intent regarding fitness trackers but were less satisfied with their cost effectiveness. The users preferred health related features such as heart health monitoring, and professional fitness tracking. The rating of most of the current mainstream fitness trackers was fair with some significant differences among the devices. Thus, further improvement is needed.

Elastomeric bearings consist of alternating rubber and metal spacer layers bonded via vulcanization technique. As important structural components in aerospace and bridge construction as well as other industries, the reliability of elastomeric bearings has a significant impact on the safety of the whole system. In this work, the finite element method is used to study the stress and displacement distributions of spherical laminated elastomeric bearings during helicopter flight, and then the theory of cumulative fatigue damage is used to analyze the fatigue lifetime of the bearing. By means of the comparative analysis of six single-load cases and a multiple-load case of the bearing categorized from the viewpoint of helicopter flight characteristics, the main influencing factors and how they affect the stress and displacement distributions are revealed. Finally, a durability test is conducted and the experimental results are well consistent with the calculated results, which indicates the prediction accuracy of the model. The work would be beneficial to the optimal design and reliable service of elastomeric bearings. [ABSTRACT FROM AUTHOR]