Experimental system and method of aerobic thermal environment simulation based on laser heating.

Considering the superior luminous intensity characteristics of lasers, a thermal simulation platform employing laser-induced heating in an aerobic environment was developed. Achieving a uniformly distributed flat-topped square laser beam output was facilitated through optical fibre bundling techniques, while precise control over laser power output was attained through current modulation. Utilising the aforementioned system, thermal shock simulation experiments were conducted in an aerobic environment, subjecting two types of high-temperature-resistant composites, namely C/C and C/SiC, to temperatures up to 1800 °C. These composites were lightweight, heat-resistant materials designed for hypersonic vehicle applications. The results show that the system and method can be used to simulate high temperatures, rapid temperature increases, and thermal shocks on C/C composite materials, with minimal variation in the coupling coefficient under aerobic conditions. The system and method can also provide key technology support for thermal-force-oxygen coupling testing of high temperature resistant materials.

LASSO-derived nomogram for early identification of pediatric monogenic lupus.

BACKGROUND: Monogenic lupus is defined as systemic lupus erythematosus (SLE)/SLE-like patients with either dominantly or recessively inherited pathogenic variants in a single gene with high penetrance. However, because the clinical phenotype of monogenic SLE is extensive and overlaps with that of classical SLE, it causes a delay in diagnosis and treatment. Currently, there is a lack of early identification models for clinical practitioners to provide early clues for recognition. Our goal was to create a clinical model for the early identification of pediatric monogenic lupus, thereby facilitating early and precise diagnosis and treatment for patients. METHODS: This retrospective cohort study consisted of 41 cases of monogenic lupus treated at the Department of Pediatrics at Peking Union Medical College Hospital from June 2012 to December 2022. The control group consisted of classical SLE patients recruited at a 1:2 ratio. Patients were randomly divided into a training group and a validation group at a 7:3 ratio. A logistic regression model was established based on the least absolute shrinkage and selection operator to generate the coefficient plot. The predictive ability of the model was evaluated using receiver operator characteristic curves and the area under the curve (AUC) index. RESULTS: A total of 41 cases of monogenic lupus patients and 82 cases of classical SLE patients were included. Among the monogenic lupus cases (with a male-to-female ratio of 1:1.05 and ages of onset ranging from birth to 15 years), a total of 18 gene mutations were identified. The variables included in the coefficient plot were age of onset, recurrent infections, intracranial calcifications, growth and developmental delay, abnormal muscle tone, lymphadenopathy/hepatosplenomegaly, and chilblain-like skin rash. Our model demonstrated satisfactory diagnostic performance through internal validation, with an AUC value of 0.97 (95% confidence interval = 0.92-0.97). CONCLUSIONS: We summarized and analyzed the clinical characteristics of pediatric monogenic lupus and developed a predictive model for early identification by clinicians. Clinicians should exercise high vigilance for monogenic lupus when the score exceeds - 9.032299.

Tocilizumab reduces the unmanageable inflammatory reaction of a patient with Aicardi-Goutières syndrome type 7 during treatment with ruxolitinib.

BACKGROUND: Aicardi-Goutières syndrome (AGS) is a rare hereditary early-onset encephalopathy characterized by upregulation of the type I interferon pathway, poorly responsive to conventional immunosuppression. CASE PRESENTATION: We describe a 7-year-old Chinese boy who developed symptoms at the age of 6 months. He presented with a chilblain-like rash, leukopenia, neutropenia, elevated liver enzymesgrowth retardation, microcephaly, elevated acute phase reactants, intracranial calcification and leukodystrophy. At the age of 3 years old, whole-exome sequencing confirmed a de novo heterozygous gain-of-function mutation, c.1016 C > A (p.Ala339Asp), in the IFIH1 gene, and he was diagnosed with AGS7. He was treated with ruxolitinib accompanied by steroids and thalidomide for about four years. The rash, hematological manifestations, and the liver function were all improved, but the erythrocyte sedimentation rate remained consistently elevated until the addition of tocilizumab, a monoclonal antibody against interleukin 6. CONCLUSIONS: Ruxolitinib was not successful in suppressing the inflammatory process, and tocilizumab produced highly encouraging results in reducing the inflammatory reaction of AGS. The study makes a significant contribution to the literature because we may found a potential alternative therapeutic option for AGS.

Efficacy and safety of thalidomide in children with monogenic autoinflammatory diseases: a single-center, real-world-evidence study.

BACKGROUND: Monogenic autoinflammatory diseases (AIDs) are rare inflammatory diseases caused by genetic variants. The pathogenesis is complex and treatment options are limited. This study aimed to describe the safety and efficacy of thalidomide in the treatment of monogenic AIDs. METHODS: This was a single-center, single-arm, real-world study. From September 2016 to August 2021, patients with monogenic AIDs who met the inclusion and exclusion criteria were given thalidomide for 12 months. There was a 3-month run-in period before dosing. The efficacy and adverse events were evaluated and recorded every 3 months. After 3 and 12 months of thalidomide treatment, clinical manifestations, disease activity score, inflammatory markers, and background medication adjustments were compared with baseline for efficacy analyses. RESULTS: A total of 16 patients entered this study, including 3 with Aicardi-Goutières syndrome (AGS), 4 Blau syndrome, 2 chronic infantile neurologic cutaneous articular syndrome (CINCA), 2 A20 haploinsufficiency (HA20), 1 adenosine deaminase 2 deficiency(DADA2), 1 familial Mediterranean fever (FMF),1 tumor necrosis factor (TNF) receptor-associated periodic syndrome (TRAPS), 1 PLCγ2-associated antibody deficiency and immune dysregulation (PLAID), and 1 stimulator of interferon genes-associated vasculopathy with onset in infancy(SAVI). The efficacy rate in the 16 patients after 3-month and 12-month thalidomide treatment in patients was 56.3%. Twelve patients completed the study, the fever improved in all of them, rash improved in 7 patients, and 5 patients stopped using glucocorticoids or other immunosuppressive agents. C-reactive protein was normal in 8 patients and erythrocyte sedimentation rate was normal in 11 patients. Anorexia and nausea occurred in 2 cases, with no other reported drug-related adverse reactions. CONCLUSION: The largest cohort of monogenic AIDs with the treatment of thalidomide demonstrated that thalidomide can help reduce disease activity and inflammation, reduce the dosage of glucocorticoids, and improve clinical outcomes. Thalidomide is relatively safe in monogenic AIDs.

Learning to detect 3D planes from a single plenoptic image.

In this paper, we propose a deep neural network to detect 3D planar surfaces from single plenoptic images captured by a Lytro Illum camera. Different from learning methods based on a single RGB image, we train a network to exploit the light distribution information both in spatial and angular dimensions from multi-sub-aperture images. The features from each sub-aperture image are extracted by using parameter-sharing convolutional layers and then fused to jointly infer the parameters of planes, depths, and segmentation masks. The experiments demonstrate that our approach outperforms the existing state-of-the-art methods with significant margins in the plane detection metrics.

Clinical phenotypes and prognosis of cytomegalovirus infection in the pediatric systemic lupus erythematosus: a longitudinal analysis.

BACKGROUND: Cytomegalovirus (CMV) plays an important role in the pathogenesis of systemic lupus erythematosus (SLE). However, it is not clear whether the anti-CMV treatment has an impact on the prognosis of SLE patients with CMV infection. We aimed to analyze the clinical characteristics and prognosis of CMV infection in pediatric SLE (pSLE) and to evaluate the effect of anti-CMV treatment on pSLE outcome. METHODS: A retrospective study including 146 pSLE from 2012 to 2021 was conducted. CMV-positive and CMV-negative groups were compared by univariate analysis and stepwise logistic multiple regression to analyze the clinical characteristics of CMV infection in pSLE. Generalized estimating equations (GEE) were used to model the longitudinal dynamics of pSLE disease activity with or without CMV infection and anti-CMV treatment. RESULTS: The CMV infection rate was 74.7% (109/146) in this pSLE cohort. CMV-positive pSLE patients were more likely to present positive anti-dsDNA antibody, hypocomplementemia, high SLEDAI-2K score and musculoskeletal involvement (P < 0.05). Survival analysis showed that CMV-positive pSLE patients were more prone to disease flare and poorer outcomes. GEE modeling indicated that CMV phosphoprotein 65 (pp65) titers were positively correlated with SLEDAI-2K, and anti-CMV treatment could better reduce pSLE activity than non-treatment (P < 0.05). CONCLUSIONS: CMV infection is highly prevalent among pSLE patients. Positive anti-dsDNA antibody, hypocomplementemia, high SLEDAI-2K score and musculoskeletal involvement were significant clinical clues indicating CMV infections in pSLE. CMV infection is correlated with higher disease activity and poorer outcome. Anti-CMV treatment can reduce disease activity and flares.

Unique mutation spectrum of progressive pseudorheumatoid dysplasia in the Chinese population: a retrospective genotype-phenotype analysis of 105 patients.

BACKGROUND: Progressive pseudorheumatoid dysplasia (PPRD) is a rare genetic disease with autosomal recessive inheritance. There was a lack of genotype-phenotype correlation data from the Chinese population. This study aimed to identify the genotype and phenotype characteristics of Chinese PPRD patients and to conduct a genotype-phenotype analysis of Chinese PPRD patients. METHODS: Genetic analysis was performed for suspected PPRD patients from Peking Union Medical College Hospital. Medical records were collected from the electronic medical record system and patient-held portable health records. Published Chinese PPRD cases were gathered from both international and Chinese local databases. We collected demographic information, genetic variants, clinical manifestations, and imaging characteristics for further analysis. RESULTS: We included 105 Chinese PPRD patients in the current study. Thirty-three variants, including nine novels and five hotspot variants, were identified, with 26/33 (79%) variants exclusively seen in the Chinese population. Chinese PPRD patients share a phenotype similar to that in international reports. Joint involvement may progress with age (R2 = 0.2541). Long bone shortening and severe deformities occur in three patients with biallelic null variants, of which at least one variant is located in exon 2. Among hotspot variants, c.624dupA (p.C209Mfs*21) were associated with later onset and more involved joints. Elbow joints were more likely to be affected in patients carrying c.624dupA (p.C209Mfs*21) and c.866dupA (p.S209Efs*13). Shoulder joints are more likely to be involved in patients with biallelic null variants (P = 0.027). CONCLUSIONS: Chinese PPRD patients share a unique mutation spectrum. Among the five hotspot variants, c.624dupA is associated with later onset of disease, more extensive joint involvement, and a tendency to affect elbow joints. Biallelic null variants with at least one variant in exon 2 could be a likely cause of long bone shortening and severe deformities.

DJ-1 Protein Inhibits Apoptosis in Cerebral Ischemia by Regulating the Notch1 and Nuclear Factor Erythroid2-Related Factor 2 Signaling Pathways.

DJ-1 plays a neuroprotective role in cerebral ischemia- reperfusion (I/R) injury and participates in the apoptosis of brain nerve cells, but the underlying mechanism is unclear. We explored the molecular pathways underlying this role using in vivo and in vitro approaches. Middle cerebral artery occlusion- reperfusion (MCAO/R) rat models and oxygen- glucose deprivation- reoxygenation (OGD/R) HAPI cell cultures were used to simulate cerebral ischemia-reperfusion injury. The interaction between DJ-1 and Notch1 was enhanced after MCAO/R in rats. After treatment of rats with DJ-1 siRNA, the expression of Notch1 and Nrf2 was down-regulated, and apoptosis was promoted. In contrast, the DJ-1 based peptide ND-13 upregulated the expression of Notch1 and Nrf2, and prevented apoptosis. In vitro, the Notch1 signaling pathway inhibitor DAPT reversed the neuroprotective effect of ND-13 and promoted apoptosis, weakened the interaction between DJ-1 and Notch1, and decreased the expression of proteins in the Notch1 and Nrf2 pathways. Thus, we found that DJ-1 inhibits apoptosis by regulating the Notch1 signaling pathway and Nrf2 expression in cerebral I/R injury. These results imply that DJ-1 is a potential therapeutic target for cerebral I/R injury.

Learning feature fusion for target detection based on polarimetric imaging.

We propose a polarimetric imaging processing method based on feature fusion and apply it to the task of target detection. Four images with distinct polarization orientations were used as one parallel input, and they were fused into a single feature map with richer feature information. We designed a learning feature fusion method using convolutional neural networks (CNNs). The fusion strategy was derived from training. Meanwhile, we generated a dataset involving one original image, four polarization orientation images, ground truth masks, and bounding boxes. The effectiveness of our method was compared to that of conventional deep learning methods. Experimental results revealed that our method gets a 0.80 mean average precision (mAP) and a 0.09 miss rate (MR), which are both better than the conventional deep learning method.