[Identification and prenatal diagnosis for a novel NIPBL variant in a fetus with Cornelia de Lange syndrome].

OBJECTIVE: To explore the genetic basis for a fetus with nuchal cystic hygroma identified in the first trimester and cholecystomegaly identified in the middle trimester of pregnancy. METHODS: A 27-year-old pregnant woman who had presented at the Antenatal Diagnostic Center of Jinan Maternal and Child Health Care Hospital on October 25, 2018 was selected as the study subject. Chorionic villus sampling was carried out in the first trimester for chromosomal karyotyping and SNP-Array analysis. Amniocentesis was carried out in the second trimester, and peripheral blood of the couple was collected at the same time. Trio whole exome sequencing (WES) was carried out, and candidate variant was verified by Sanger sequencing and bioinformatic analysis. RESULTS: No abnormality was found by chromosomal karyotyping and SNP-Array, whilst high-throughput sequencing revealed that the fetus had harbored a heterozygous c.7732A>T (p.K2578X) nonsense variant of the NIPBL gene. Following elected abortion, the autopsy results were consistent with features of Cornelia de Lange syndrome (CdLS). The same variant was detected in neither parents and was unreported in the literature. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), it was classified as pathogenic (PVS1+PS2+PM2_Supporting+PP3). CONCLUSION: The novel nonsense variant of the NIPBL gene probably underlay the genetic etiology of CdLS in this fetus. Above finding has also enriched the mutational spectrum of the NIPBL gene.

Gloss Prior Guided Visual Feature Learning for Continuous Sign Language Recognition.

Continuous sign language recognition (CSLR) is to recognize the glosses in a sign language video. Enhancing the generalization ability of CSLR's visual feature extractor is a worthy area of investigation. In this paper, we model glosses as priors that help to learn more generalizable visual features. Specifically, the signer-invariant gloss feature is extracted by a pre-trained gloss BERT model. Then we design a gloss prior guidance network (GPGN). It contains a novel parallel densely-connected temporal feature extraction (PDC-TFE) module for multi-resolution visual feature extraction. The PDC-TFE captures the complex temporal patterns of the glosses. The pre-trained gloss feature guides the visual feature learning through a cross-modality matching loss. We propose to formulate the cross-modality feature matching into a regularized optimal transport problem, it can be efficiently solved by a variant of the Sinkhorn algorithm. The GPGN parameters are learned by optimizing a weighted sum of the cross-modality matching loss and CTC loss. The experiment results on German and Chinese sign language benchmarks demonstrate that the proposed GPGN achieves competitive performance. The ablation study verifies the effectiveness of several critical components of the GPGN. Furthermore, the proposed pre-trained gloss BERT model and cross-modality matching can be seamlessly integrated into other RGB-cue-based CSLR methods as plug-and-play formulations to enhance the generalization ability of the visual feature extractor.

Integrated approach for simultaneously measuring thermophysical parameters of semi-transparent materials.

To concurrently determine the thermophysical parameters of semi-transparent materials, a novel, to the best of our knowledge, integrated approach for concurrent measurement is proposed. In the measurement setup, a high-temperature radiation source and a beam reducer are employed to minimize the influence of background radiation. In order to differentiate between the transmitted and emitted radiation in the detection signal, the radiation signals from the radiation source are measured under four different conditions, enabling the calculation of transmissivity, emissivity, and reflectivity. The reliability and accuracy of the measurement method are validated by the thermophysical parameters of sapphire, and the results demonstrate a strong agreement between the measured data and previous findings. The combined uncertainties of transmissivity and emissivity for the sapphire at 753 K are estimated, highlighting the novel contribution of this method in investigating the thermophysical parameters of semi-transparent materials.

Study on heat transfer performance of cold plate with grid channel.

The utilization of cold plate radiators as a prevalent method for indirect liquid cooling has been extensively investigated and implemented in server cooling systems. However, there is a lack of comprehensive study on the application of this technology at the chip size, indicating a need for more development and exploration in this area. A proposal was made for a grid-channel chip cold plate heat sink to facilitate the dissipation of heat from a chip. tests were conducted to investigate the impact of the flow rate of the cold plate and the layout of the inlet and outlet on various thermal parameters, including the average temperature, maximum temperature, thermal resistance, and uniformity coefficient of the cold plate. The tests were specifically conducted under a chip power of 150W, and the accuracy of the simulation was confirmed through the use of FLUENT. The findings indicate that the cold plate effectively regulates the temperature of the chip, ensuring it remains below 85 °C throughout all experimental groups. In contrast to the single in single out configuration, the single-in multiple-out layout exhibits a higher degree of temperature uniformity within the cold plate. Nevertheless, it is important to note that augmenting the quantity of exits does not guarantee an improvement in heat transfer efficiency. This outcome is contingent upon the presence of a longitudinal flow channel shared by the outlet and intake, as well as the dispersion characteristics of the outlet. Enhancing the dispersion of the exit can significantly enhance the thermal transfer efficiency of the cold plate. Furthermore, a strategy for adjusting the aperture of the orifice is proposed as a solution to address the challenges related to flow uniformity and the issue of high pressure drop in the cold plate.

Artificial intelligence-assisted system for the assessment of Forrest classification of peptic ulcer bleeding: a multicenter diagnostic study.

BACKGROUND: Inaccurate Forrest classification may significantly affect clinical outcomes, especially in high risk patients. Therefore, this study aimed to develop a real-time deep convolutional neural network (DCNN) system to assess the Forrest classification of peptic ulcer bleeding (PUB). METHODS: A training dataset (3868 endoscopic images) and an internal validation dataset (834 images) were retrospectively collected from the 900th Hospital, Fuzhou, China. In addition, 521 images collected from four other hospitals were used for external validation. Finally, 46 endoscopic videos were prospectively collected to assess the real-time diagnostic performance of the DCNN system, whose diagnostic performance was also prospectively compared with that of three senior and three junior endoscopists. RESULTS: The DCNN system had a satisfactory diagnostic performance in the assessment of Forrest classification, with an accuracy of 91.2% (95%CI 89.5%-92.6%) and a macro-average area under the receiver operating characteristic curve of 0.80 in the validation dataset. Moreover, the DCNN system could judge suspicious regions automatically using Forrest classification in real-time videos, with an accuracy of 92.0% (95%CI 80.8%-97.8%). The DCNN system showed more accurate and stable diagnostic performance than endoscopists in the prospective clinical comparison test. This system helped to slightly improve the diagnostic performance of senior endoscopists and considerably enhance that of junior endoscopists. CONCLUSION: The DCNN system for the assessment of the Forrest classification of PUB showed satisfactory diagnostic performance, which was slightly superior to that of senior endoscopists. It could therefore effectively assist junior endoscopists in making such diagnoses during gastroscopy.

Fast data processing method for multispectral radiation thermometry based on Euclidean distance optimization.

This study presents a fast and accurate data processing method for multispectral radiation thermometry that can accurately measure the true temperature of steel materials without requiring a priori emissivity model. The method generates a temperature matrix by inputting emissivity values at different wavelengths and selects a reference vector from the matrix. Then, it rearranges the temperature matrices at other wavelengths and calculates the Euclidean distance between each column element of the rearranged matrix and the reference vector. The method uses an unconstrained optimization technique to minimize the Euclidean distance and obtain the true temperature and emissivity of the object simultaneously. We evaluate the performance of the method by simulation and experiment in the response band of 1.4 ∼ 2.5 µm and temperature range of 873 ∼ 1173 K. The simulation results indicate that the relative error of the inverted temperature is within 0.229%, and the average computation time is less than 112.301 ms. The experimental results show that the maximum temperature error during the measurement process is 0.813%. Our method provides a feasible and efficient solution for real-time temperature measurement of steel materials.

Regional GABA levels modulate abnormal resting-state network functional connectivity and cognitive impairment in multiple sclerosis.

More evidence shows that changes in functional connectivity with regard to brain networks and neurometabolite levels correlated to cognitive impairment in multiple sclerosis. However, the neurological basis underlying the relationship among neurometabolite levels, functional connectivity, and cognitive impairment remains unclear. For this purpose, we used a combination of magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging to study gamma-aminobutyric acid and glutamate concentrations in the posterior cingulate cortex, medial prefrontal cortex and left hippocampus, and inter-network functional connectivity in 29 relapsing-remitting multiple sclerosis patients and 34 matched healthy controls. Neuropsychological tests were used to evaluate the cognitive function. We found that relapsing-remitting multiple sclerosis patients demonstrated significantly reduced gamma-aminobutyric acid and glutamate concentrations and aberrant functional connectivity involving cognitive-related networks compared to healthy controls, and both alterations were associated with specific cognition decline. Moreover, mediation analyses indicated that decremented hippocampus gamma-aminobutyric acid levels in relapsing-remitting multiple sclerosis patients mediated the association between inter-network functional connectivity in various components of default mode network and verbal memory deficits. In summary, our findings shed new lights on the essential function of GABAergic system abnormalities in regulating network dysconnectivity and functional connectivity in relapsing-remitting multiple sclerosis patients, suggesting potential novel approach to treatment.

Construction synergetic adsorption and activation surface via confined Cu/Cu2O and Ag nanoparticles on TiO2 for effective conversion of CO2 to CH4.

High-performance photocatalysts for catalytic reduction of CO2 are largely impeded by inefficient charge separation and surface activity. Reasonable design and efficient collaboration of multiple active sites are important for attaining high reactivity and product selectivity. Herein, Cu-Cu2O and Ag nanoparticles are confined as dual sites for assisting CO2 photoreduction to CH4 on TiO2. The introduction of Cu-Cu2O leads to an all-solid-state Z-scheme heterostructure on the TiO2 surface, which achieves efficient electron transfer to Cu2O and adsorption and activation of CO2. The confined nanometallic Ag further enhances the carrier's separation efficiency, promoting the conversion of activated CO2 molecules to •COOH and further conversion to CH4. Particularly, this strategy is highlighted on the TiO2 system for a photocatalytic reduction reaction of CO2 and H2O with a CH4 generation rate of 62.5 µmol∙g-1∙h-1 and an impressive selectivity of 97.49 %. This work provides new insights into developing robust catalysts through the artful design of synergistic catalytic sites for efficient photocatalytic CO2 conversion.

Artificial intelligence-aided diagnostic imaging: A state-of-the-art technique in precancerous screening.

BACKGROUND AND AIM: Chromoendoscopy with the use of indigo carmine (IC) dye is a crucial endoscopic technique to identify gastrointestinal neoplasms. However, its performance is limited by the endoscopist's skill, and no standards are available for lesion identification. Thus, we developed an artificial intelligence (AI) model to replace chromoendoscopy. METHODS: This pilot study assessed the feasibility of our novel AI model in the conversion of white-light images (WLI) into virtual IC-dyed images based on a generative adversarial network. The predictions of our AI model were evaluated against the assessments of five endoscopic experts who were blinded to the purpose of this study with a staining quality rating from 1 (unacceptable) to 4 (excellent). RESULTS: The AI model successfully transformed the WLI of polyps with different morphologies and different types of lesions in the gastrointestinal tract into virtual IC-dyed images. The quality ratings of the real IC-dyed and AI images did not significantly differ concerning surface structure (AI vs IC: 3.08 vs 3.00), lesion border (3.04 vs 2.98), and overall contrast (3.14 vs 3.02) from 10 sets of images (10 AI images and 10 real IC-dyed images). Although the score depended significantly on the evaluator, the staining methods (AI or real IC) and evaluators had no significant interaction (P > 0.05) with each other. CONCLUSION: Our results demonstrated the feasibility of employing AI model's virtual IC staining, increasing the possibility of being employed in daily practice. This novel technology may facilitate gastrointestinal lesion identification in the future.

Serum uric acid predicts the development of atherosclerosis in women but not in men: A ten-year cohort study in China.

BACKGROUND AND AIM: Atherosclerosis is becoming a significant health burden. Serum uric acid (SUA) is the final enzymatic product of purine metabolism and can contribute to the development of atherosclerosis. The aim of this study was to explore the possible predictive value of SUA in the development of atherosclerosis in a healthy Chinese population. METHODS AND RESULTS: In this study, a total of 11,222 healthy subjects with no carotid plaque at baseline were enrolled and divided into sex-specific groups, and then the occurrence of carotid plaque during the follow-up time was documented. The association between carotid plaque and SUA levels was examined using Cox proportional-hazards regression models. The mean SUA level was 5.35 ± 1.41 mg/dL. A total of 2,911 individuals (25.94%) developed carotid plaque during the follow-up time, including 1,071 females and 1,840 males. After adjusting for potential confounding factors, the hazard ratio (HR) and 95% confidence interval (95% CI) in women for the occurrence of carotid plaque associated with SUA levels were 1.163 (1.017-1.330), but no significant correlation was found in men, as the HR was 1.050 (0.965-1.143). CONCLUSION: Our results indicate that SUA levels predict the development of carotid plaque independent of traditional risk factors only in women.

Comparison of coccidioidal complement fixation and quantitative immunodiffusion serology at a reference laboratory.

The incidence of coccidioidomycosis continues to increase. The diagnosis frequently relies on non-invasive diagnostic testing with immunodiffusion and complement fixation (CF) testing the current gold standard. A direct comparison of quantitative immunodiffusion and CF for IgG antibodies has not been previously reported. In a comparison of 368 samples, there was close concordance observed (360/368 = 97.8%) (P-value < .001). These tests can be considerably interchangeable in the reference laboratory setting.

There are several diagnostic methodologies available in coccidioidomycosis. Direct comparisons of these methods are limited. Prior studies have not compared quantitative immunodiffusion to complement fixation testing. Our results show these tests are highly concordant.

Learning Self-Corrective Network via Adaptive Self-Labeling and Dynamic NMS for High-Performance Long-Term Tracking.

This article presents a self-corrective network-based long-term tracker (SCLT) including a self-modulated tracking reliability evaluator (STRE) and a self-adjusting proposal postprocessor (SPPP). The targets in the long-term sequences often suffer from severe appearance variations. Existing long-term trackers often online update their models to adapt the variations, but the inaccurate tracking results introduce cumulative error into the updated model that may cause severe drift issue. To this end, a robust long-term tracker should have the self-corrective capability that can judge whether the tracking result is reliable or not, and then it is able to recapture the target when severe drift happens caused by serious challenges (e.g., full occlusion and out-of-view). To address the first issue, the STRE designs an effective tracking reliability classifier that is built on a modulation subnetwork. The classifier is trained using the samples with pseudo labels generated by an adaptive self-labeling strategy. The adaptive self-labeling can automatically label the hard negative samples that are often neglected in existing trackers according to the statistical characteristics of target state, and the network modulation mechanism can guide the backbone network to learn more discriminative features without extra training data. To address the second issue, after the STRE has been triggered, the SPPP follows it with a dynamic NMS to recapture the target in time and accurately. In addition, the STRE and the SPPP demonstrate good transportability ability, and their performance is improved when combined with multiple baselines. Compared to the commonly used greedy NMS, the proposed dynamic NMS leverages an adaptive strategy to effectively handle the different conditions of in view and out of view, thereby being able to select the most probable object box that is essential to accurately online update the basic tracker. Extensive evaluations on four large-scale and challenging benchmark datasets including VOT2021LT, OxUvALT, TLP, and LaSOT demonstrate superiority of the proposed SCLT to a variety of state-of-the-art long-term trackers in terms of all measures. Source codes and demos can be found at https://github.com/TJUT-CV/SCLT.

The top 100 most-cited studies on monkeypox: a brief bibliometric analysis.

Background: A plethora of monkeypox papers have been published; however, pinpointing key and pivotal studies can be challenging amongst the ever-expanding literature. Bibliometric analyses are helpful in identifying the most influential articles and their impact pertinent to this field, which has helped mould the recognition and management of monkeypox. Methods: The Web of Science Core Collection (WoSCC) was searched on 27 October 2022. The top 100 most-cited articles on monkeypox were identified and evaluated by author, country, institution, type of articles, theme, journal of publication, keywords, and citations. Results: The top 100 most-cited studies were published between 1997 and 2022, and the 5-year period with the largest number of articles was 2007-2011. The median number of citations among the top 100 most-cited articles was 78.23. Of the top 100 most-cited studies, 91 were original articles, and nine were reviews, the median of annual citations was significantly higher in the review group than the original group, 7.86 (4.20-13.80) versus 4.50 (3.07-7.59; P=0.023). The 100 articles were classified into different research theme, with the top three being Immunology (31%), Infectious Diseases (30%), and Virology (26%), respectively. The keywords with the highest co-occurrence frequency were "monkeypox", "smallpox," and "smallpox virus." The largest number of articles in the top 100 were published in Emerging Infectious Diseases (n=13), followed by Journal of Virology (n=11), Journal of Infectious Diseases (n=5), and PLoS One (n=5). The authors identified 711 different authors from 195 institutions and 28 countries in the top 100 most-cited articles, with the majority based in the USA. Conclusion: The top 100 most-cited studies provide an important insight into the historical developments of monkeypox. The authors should strengthen the recognition and management of monkeypox worldwide and strengthen research cooperation among scholars in order to better respond to the ongoing or future outbreak.

Data processing for simultaneous inversion of emissivity and temperature using improved CABCSMA and target-to-best DE algorithms in multispectral radiation thermometry (MRT).

In this paper, what we believe to be, a new combined algorithm of artificial bee colony and slime mould algorithm (CABCSMA) and a differential evolution (DE) algorithm using target-to-best variation strategy are proposed to process the data based on Planck's radiation law and the mathematical model of reference temperature. The material model with 6 different emissivity trends is simulated. Simulation results show that the average relative error of CABCSMA algorithm is less than 0.68%, and the average calculation time is 0.44s. The average relative error of DE algorithm is less than 0.43%, and the average calculation time is only 0.06s. The two algorithms were applied to the temperature test of silicon carbide sample, tungsten material and rocket engine nozzle. The experimental results show that the relative error of silicon carbide experimental temperature is less than 0.41% and 0.28%, and the relative error of tungsten material experimental temperature is less than 0.31% and 0.3%. The relative errors of rocket engine nozzle temperature experiments are within 0.68% and 0.52%, respectively. The results show that these two algorithms are expected to be applied in practical measurement scenarios.

Approach to multispectral thermometry with Planck formula and hybrid metaheuristic optimization algorithm.

Accurate temperature measurement has significant implications for product quality, industrial process control, and scientific research. As a non-contact temperature measurement method with broad application prospects, multispectral thermometry still poses significant challenges in data processing. Currently, most multispectral thermometry methods use the Wien approximation equation to construct the objective function. However, the use of the Wien approximation equation is conditional and generally applicable only to low temperatures or short wavelengths. In this paper, what we believe is a new data processing model of multispectral thermometry is established based on the Planck formula; Additionally, a feasible region constraint method is proposed to constrain the emissivity range; By utilizing a hybrid metaheuristic optimization algorithm based on differential evolution (DE) and multi-population genetic (MPG) algorithms, the simulation results of six different models and experimental results of silicon carbide demonstrate that the proposed algorithm achieves an average relative error in temperature measurement within 0.42% and a random relative error within 0.79%. The average computation time for each temperature inversion is approximately 0.26 seconds. The accuracy and efficiency of the algorithm ensure that it can be applied to real-time temperature measurement in industrial field.

Evidence for Uranium(VI/V) Redox Supported by 2,2'-Bipyridyl-6,6'-dicarboxylate.

The 2,2'-bipyridyl-6,6'-dicarboxylate ligand (bdc) has been shown in prior work to effectively capture the uranyl(VI) ion, UO22+, from aqueous solutions. However, the redox properties of the uranyl complex of this ligand have not been addressed despite the relevance of uranium-centered reduction to the nuclear fuel cycle and the presence of a bipyridyl core in bdc, a motif long recognized for its ability to support redox chemistry. Here, the bdc complex of UO22+ (1-UO2) has been synthetically prepared and isolated under nonaqueous conditions for the study of its reductive chemical and electrochemical behavior. Spectrochemical titration data collected using decamethylcobaltocene (Cp*2Co) as the reductant demonstrate that 1e- reduction of 1-UO2 is accessible, and companion near-infrared and infrared spectroscopic data, along with theoretical findings from density functional theory, provide evidence that supports the accessibility of the U(V) oxidation state. Data obtained for control ruthenium complexes of bdc and related polypyridyl dicarboxylate ligands provide a counterpoint to these findings; ligand-centered reduction of bdc in these control compounds occurs at potentials more negative than those measured for reduction of 1-UO2, further supporting the generation of uranium(V) in 1-UO2. Taken together, these results underscore the usefulness of bdc as a ligand for actinyl ions and suggest that it could be useful for further studies of the reductive activation of these unique species.

D-dimer-albumin ratio (DAR) as a new biomarker for predicting preoperative deep vein thrombosis after geriatric hip fracture patients.

PURPOSE: Hip fractures in the elderly are complicated by preoperative deep vein thrombosis (DVT). The objective of this study is to determine the usefulness of blood-based biomarkers, particularly the D-dimer-albumin ratio (DAR), in predicting preoperative DVT. METHODS: A retrospective observational study was carried out on 1149 patients from a single hospital, and subsequently validated on an additional 626 patients from a separate hospital. The aim was to evaluate the prognostic and predictive value of 10 biomarkers, with a specific emphasis on DAR, in both cohorts. The primary measure of interest was the occurrence of preoperative DVT. RESULTS: The ratio of D-dimer to albumin demonstrated superior predictive capability for preoperative DVT in older patients with hip fractures compared to other biomarkers (AUC = 0.677). Using the optimal cutoff point of 0.24, high DAR was significantly associated with preoperative DVT (OR 3.45, 95% CI 2.00-5.95). Notably, all the DAR definitions detailed above were successfully validated in an external, independent cohort. CONCLUSIONS: DAR may be a valuable biomarker for predicting preoperative DVT in elderly patients with hip fractures.

TRIM38 suppresses migration, invasion, metastasis, and proliferation in non-small cell lung cancer (NSCLC) via regulating the AMPK/NF-κB/NLRP3 pathway.

Accumulating data have revealed the pivotal function of tripartite motif protein 38 (TRIM38) in tumors. In view of this, this investigation aims to explore the function and potential mechanism of TRIM38 in non-small cell lung cancer (NSCLC). A xenotypic tumor model was established in vivo by subcutaneously injecting NSCLC cells (2 × 106 cells) in tail vein of each mouse. Relative expression of TRIM38 mRNA was detected via quantitative real-time polymerase chain reaction (qRT-PCR). For exploring the role of TRIM38 in vivo and in vitro, mice or NSCLC cells were divided into two groups: the vector group and the TRIM38 overexpression group. Also, protein expression levels of TRIM38, Vimentin, E-cadherin, and N-cadherin were determined using western blotting and immunohistochemistry staining. Tumor nodules of mouse lung tissues were assessed via performing H&E staining. Moreover, proliferation of NSCLC cells was evaluated through colony formation and CCK-8 assays. Further, migration and invasion of NSCLC cells were assessed through wound healing and transwell assays. Protein levels of pathway-related proteins including p-p65, p65, IκB, p-IκB, p-AMPK, AMPK, and NLRP3 were examined through western blotting analysis. Tumor lung tissues of mice and NSCLC cells showed low protein and mRNA expression of TRIM38. Functionally, up-regulation of TRIM38 reduced the number of tumor nodules and suppressed epithelial-to-mesenchymal transition (EMT) in lung tissues of mice. Furthermore, up-regulation of TRIM38 in NSCLC cells inhibited migration, invasion, EMT, and proliferation. With respect to the mechanism, in vivo experiments, the inhibitory effects of TRIM38 overexpression on tumor nodules, and EMT were reversed by AMPK inhibitor. In vitro experiments, TRIM38 overexpression caused down-regulation of p-IκB and p-p65 as well as up-regulation of p-AMPK. The inhibitory effects of TRIM38 overexpression on migration, proliferation, invasion, and EMT of NSCLC cells were reversed by overexpression of NLRP3. Concurrently, AMPK inhibitor enhanced the TRIM38-overexpressed NSCLC cell's abilities in migration, clone formation, invasion, and proliferation. TRIM38 regulated the AMPK/NF-κB/NLRP3 pathway to suppress the NSCLC's progression and development.

Efficacy of low-intensity pulsed ultrasound in the treatment of COVID-19 pneumonia.

PURPOSE: As a public health emergency of international concern, coronavirus disease 2019 (COVID-19) still lacks specific antiviral drugs, and symptomatic treatment is currently the mainstay. The overactivated inflammatory response in COVID-19 patients is associated with a high risk of critical illness or even death. Low-intensity pulsed ultrasound (LIPUS) can mitigate inflammation and inhibit edema formation. We aimed to investigate the efficacy of LIPUS therapy for COVID-19 pneumonia. MATERIALS AND METHODS: 62 patients were randomly assigned to a treatment group (LIPUS treatment area - Group 1; self-control area - Group 2) and an external control group (Group 3). The primary outcomes were the volume absorption rate (VAR) and the area absorption rate (AAR) of lung inflammation in CT images. RESULTS: After an average duration of treatment 7.2 days, there were significant differences in AAR and VAR between Group 1 and Group 2 (AAR 0.25 vs 0.12, p=0.013; VAR 0.35 vs 0.11, p=0.005), and between Group 1 and Group 3 (AAR 0.25 vs 0.11, p=0.047; VAR 0.35 vs 0.19, p=0.042). Neither AAR nor VAR was statistically different between Group 2 and Group 3. After treatment, C-reactive protein, interleukin-6, leukocyte, and fingertip arterial oxygen saturation (SaO2) improved in Group 1, while in Group 3 only fingertip SaO2 increased. CONCLUSION: LIPUS therapy reduced lung inflammation and serum inflammatory factor levels in hospitalized COVID-19 patients, which might be a major advancement in COVID-19 pneumonia therapy.

An Improved Method for Accurate Radiation Measurement Based on Dark Output Noise Drift Compensation.

This paper verified through experiments that change in ambient temperature are the main cause of dark output noise drift. Additionally, the impact of dark output noise drift in fiber optic spectrometers on emissivity measurements has been investigated in this work. Based on an improved fiber optic spectrometer, two methods were proposed for characterizing and correcting the dark output noise offset in fiber optic spectrometers: the mean correction scheme and the linear fitting correction scheme. Compared to the mean correction scheme, the linear fitting correction scheme is more effective in solving the problem of dark output noise drift. When the wavelength is greater than 1600 nm, the calibration relative error of silicon carbide (SIC) emissivity is less than 0.8% by the mean correction scheme, while the calibration relative error of silicon carbide emissivity is less than 0.62% by the linear fitting correction scheme. This work solves the problem of dark output noise drift in prolonged measurement based on fiber optic spectrometers, improving the accuracy and reliability of emissivity and quantitative radiation measurement.