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Abstract Rosacea is a chronic inflammatory skin disorder, whose underlying cellular and molecular mechanisms remain obscure. Here, we generate a single-cell atlas of facial skin from female rosacea patients and healthy individuals. Among keratinocytes, a subpopulation characterized by IFNγ-mediated barrier function damage is found to be unique to rosacea lesions. Blocking IFNγ signaling alleviates rosacea-like phenotypes and skin barrier damage in mice. The papulopustular rosacea is featured by expansion of pro-inflammatory fibroblasts, Schwann, endothelial and macrophage/dendritic cells. The frequencies of type 1/17 and skin-resident memory T cells are increased, and vascular mural cells are characterized by activation of inflammatory pathways and impaired muscle contraction function in rosacea. Most importantly, fibroblasts are identified as the leading cell type producing pro-inflammatory and vasodilative signals in rosacea. Depletion of fibroblasts or knockdown of PTGDS, a gene specifically upregulated in fibroblasts, blocks rosacea development in mice. Our study provides a comprehensive understanding of the aberrant alterations of skin-resident cell populations and identifies fibroblasts as a key determinant in rosacea development.

Foodborne pathogen contamination of fermented food is an increasingly concerned problem in food industry. The types and sources of harmful microorganisms in food are discussed in this paper. The main techniques used to detect microorganisms are summarized. In addition, strategies for controlling these harmful microorganisms are discussed. By highlighting these important aspects, this paper aims to contribute to strengthening food quality assurance and promoting safer food practices.

IntroductionAlthough there is growing evidence supporting the effectiveness of Janus kinase (JAK) inhibitors in treating alopecia areata, the high rate of recurrence following drug discontinuation has led to prolonged treatment courses and raised concerns about long-term safety. In clinical practice, caution should be exercised while using JAK inhibitors for various indications, and a comprehensive pre-treatment screening.MethodsThis study presents an analysis of screening data collected from real-world settings before the initiation of Janus kinase inhibitors in patients with alopecia areata. Investigators collected retrospective medical data characterizing patients’ screening data. Data on demographic and clinical data, including age, sex, disease duration, severity of alopecia tool scale, history of prior treatment, and treatment regimen were recorded.ResultsIn this cohort (N = 218), JAK inhibitors were initiated for 163 of 218 (74.8%) alopecia areata patients. The numbers of patients positive for antinuclear antibodies, hepatitis B surface antigen, hepatitis C virus antibodies, human immunodeficiency virus antibody, treponema pallidum hemagglutination assay, and thyroid-stimulating hormone were 32 (32/176), 10(10/218), 0 (0/218), 0 (0/218), 3 (3/218) and 9 (9/176), respectively. The number of patients with T-cell spot positive or imaging of the chest indicating tuberculosis was 37 (37/218).DisccusionOur data provide additional information on the safety profile of JAK inhibitors in patients with alopecia areata. As such, it is necessary and crucial to screen for JAK inhibitors before it is used, particularly for individuals with a high risk of tuberculosis, hepatitis B, and other infections.

Alopecia areata (AA) is a common cause of hair loss in children. Despite numerous therapeutic options for paediatric AA, none have been found to be both effective and safe. Recent studies have demonstrated the efficacy and safety of the Janus kinase (JAK) inhibitor tofacitinib in adult patients with AA, whereas data on paediatric patients with AA in real-world practice are limited. This was a single-centre, retrospective study that included 11 pre-adolescent patients with AA treated with tofacitinib between December 2021 and September 2022. Clinical characteristics of patients, clinical response and adverse events were evaluated. Overall, 82% (9/11) of patients experienced hair regrowth and 64% (7/11) of patients experienced over 50% improvement in their Severity of Alopecia Tool (SALT) scores. Adverse events were mild. In the literature, tofacitinib has been used to treat AA in 31 children ≤12 years of age who failed to respond to prior treatments. Eighty-seven percent (27/31) of these patients showed significant responses based on changes in their SALT scores. This case series demonstrates that oral tofacitinib is an effective and safe treatment option for paediatric AA, particularly for children who have failed to respond to traditional treatments or are not suitable for such treatments.

Abstract Background As a highly heterogeneous tumor, non-small cell lung cancer (NSCLC) is famous for its high incidence and mortality worldwide. Smoking can cause genetic changes, which leading to the occurrence and progress of NSCLC. Nevertheless, the function of smoking-related genes in NSCLC needs more research. Methods We downloaded transcriptome data and clinicopathological parameters from Gene Expression Omnibus (GEO) databases, and screened smoking-related genes. Lasso regression were applied to establish the 7-gene signature. The associations between the 7-gene signature and immune microenvironment analysis, survival analysis, drug sensitivity analysis and enriched molecular pathways were studied. Ultimately, cell function experiments were conducted to research the function of FCGBP in NSCLC. Results Through 7-gene signature, NSCLC samples were classified into high-risk group (HRG) and low-risk group (LRG). Significant difference in overall survival (OS) between HRG and LRG was found. Nomograms and ROC curves indicated that the 7-gene signature has a stable ability in predicting prognosis. Through the analysis of immune microenvironment, we found that LRG patients had better tumor immune activation. FCGBP showed the highest mutation frequency among the seven prognostic smoking related genes (LRRC31, HPGD, FCGBP, SPINK5, CYP24A1, S100P and FGG), and was notable down-regulated in NSCLC smokers compared with non-smoking NSCLC patients. The cell experiments confirmed that FCGBP knockdown promoting proliferation, migration, and invasion in NSCLC cells. Conclusion This smoking-related prognostic signature represents a promising tool for assessing prognosis and tumor microenvironment in smokers with NSCLC. The role of FCGBP in NSCLC was found by cell experiments, which can be served as diagnostic biomarker and immunotherapy target for NSCLC.

Abstract Although previous studies have made some clear leap in learning latent dynamics from high‐dimensional representations, the performances in terms of accuracy and inference time of long‐term model prediction still need to be improved. In this study, a deep convolutional network based on the Koopman operator (CKNet) is proposed to model non‐linear systems with pixel‐level measurements for long‐term prediction. CKNet adopts an autoencoder network architecture, consisting of an encoder to generate latent states and a linear dynamical model (i.e., the Koopman operator) which evolves in the latent state space spanned by the encoder. The decoder is used to recover images from latent states. According to a multi‐step ahead prediction loss function, the system matrices for approximating the Koopman operator are trained synchronously with the autoencoder in a mini‐batch manner. In this manner, gradients can be synchronously transmitted to both the system matrices and the autoencoder to help the encoder self‐adaptively tune the latent state space in the training process, and the resulting model is time‐invariant in the latent space. Therefore, the proposed CKNet has the advantages of less inference time and high accuracy for long‐term prediction. Experiments are performed on OpenAI Gym and Mujoco environments, including two and four non‐linear forced dynamical systems with continuous action spaces. The experimental results show that CKNet has strong long‐term prediction capabilities with sufficient precision.

Abstract This research aims to explore the influencing mechanism of a caring ethical climate on knowledge-hiding behavior in large construction firms according to the reciprocity principle of social exchange theory. This is an empirical study based on the analysis of survey data collected from 413 employees working in large construction firms in China. Hierarchical regression is applied to test the research model. This research finds: (1) Caring ethical climate has a negative influence on knowledge-hiding behavior; (2) Caring ethical climate has a positive influence on psychological contract; (3) Psychological contract has a negative influence on knowledge-hiding behavior; (4) Psychological contract mediates the relationship between caring ethical climate and knowledge-hiding behavior; (5) Task interdependence positively moderates the relationship between psychological contract and knowledge-hiding behavior. Based on the social exchange theory, this study provides significant contributions to the theory and practice of knowledge management in large construction firms by highlighting the influence of a caring ethical climate on knowledge hiding among employees. This paper provides suggestions for reducing knowledge hiding and enhancing knowledge sharing among employees in large construction firms, so as to improve the knowledge management ability of large construction firms and enhance their competitive advantages.

Indocyanine green (ICG) is an important kind of near infrared (NIR) photosensitive molecules for PTT/PDT therapy as well as imaging. When exposed to NIR light, ICG can produce reactive oxygen species (ROS), which can kill cancer cells and pathogenic bacteria. Moreover, the absorbed light can also be converted into heat by ICG molecules to eliminate cancer cells. In addition, it performs exceptionally well in optical imaging-guided tumor therapy and antimicrobial therapy due to its deeper tissue penetration and low photobleaching properties in the near-infrared region compared to other dyes. In order to solve the problems of water and optical stability and multi-function problem of ICG molecules, composite nanomaterials based on ICG have been designed and widely used, especially in the fields of tumors and sterilization. So far, ICG molecules and their composite materials have become one of the most famous infrared sensitive materials. However, there have been no corresponding review articles focused on ICG molecules. In this review, the molecular structure and properties of ICG, composite material design, and near-infrared light- triggered anti-tumor, and antibacterial, and clinical applications are reviewed in detail, which of great significance for related research.

Hereditary (variant) transthyretin amyloidosis (ATTRv amyloidosis), which is caused by variants in the transthyretin (TTR) gene, leads to TTR amyloid deposits in multiple organs and various symptoms such as limb ataxia, muscle weakness, and cardiac failure. Interaction between amyloid proteins and extracellular vesicles (EVs), which are secreted by various cells, is known to promote the clearance of the proteins, but it is unclear whether EVs are involved in the formation and deposition of TTR amyloid in ATTRv amyloidosis. To clarify the relationship between ATTRv amyloidosis and EVs, serum-derived EVs were analyzed. In this study, we showed that cell-derived EVs are involved in the formation of TTR amyloid deposits on the membrane of small EVs, as well as the deposition of TTR amyloid in cells. Human serum-derived small EVs also altered the degree of aggregation and deposition of TTR. Furthermore, the amount of TTR aggregates in serum-derived small EVs in patients with ATTRv amyloidosis was lower than that in healthy controls. These results indicate that EVs contribute to the metabolism of TTR amyloid, and suggest that TTR in serum-derived small EVs is a potential target for future ATTRv amyloidosis diagnosis and therapy.

Space manipulators have attracted much attention due to their implications in on-orbit servicing in recent years. Air bearing based support equipment is widely used for ground test to offset the effect of gravity. However, an air bearing support introduces a new problem caused by additional inertial and mass properties. Additional mass and inertial load will influence the dynamics behavior, especially stiffness information and vibration response of the whole ground test system. In this paper, a set of procedures are presented to remove the influence of air bearings and identify the true equivalent joint stiffness and damping from the test data of a motor-braked space manipulator with an air bearing support. First, inertia parameters are identified. Then, the equivalent joint stiffness and damping are determined by using a genetic algorithm (GA) method. Finally, true vibration characteristics of the manipulator are estimated by removing the additional inertia caused by the air bearings. Moreover, simulations and experiments are carried out to validate the presented procedures.

Fraud detection is one of the core issues of loan risk control, which aims to detect fraudulent loan applications and safeguard the property of both individuals and organizations. Because of its close relevance to the security of financial operations, fraud detection has received widespread attention from industry. In recent years, with the rapid development of artificial intelligence technology, an automatic feature engineering method that can help to generate features has been applied to fraud detection with good results. However, in car loan fraud detection, the existing methods do not satisfy the requirements because of overreliance on behavioral features. To tackle this issue, this paper proposed an optimized deep feature synthesis (DFS) method in the automatic feature engineering scheme to improve the car loan fraud detection. Problems like feature dimension explosion, low interpretability, long training time, and low detection accuracy are solved by compressing abstract and uninterpretable features to limit the depth of DFS algorithm. Experiments are developed based on actual car loan credit database to evaluate the performance of the proposed scheme. Compared with traditional automatic feature engineering methods, the number of features and training time are reduced by 92.5% and 54.3%, respectively, whereas accuracy is improved by 23%. The experiment demonstrates that our scheme effectively improved the existing automatic feature engineering car loan fraud detection methods.

Space manipulators which have a similar symmetrical structure with seven revolute joints, such as the space station remote manipulator system (SSRMS), can be called SSRMS-type space manipulators. The analytical inverse kinematics of an SSRMS-type manipulator can be solved by locking a single joint; the locked joint (joint 1, 2, 6, or 7) can be determined by configuration analysis. Although widely used in establishing the kinematics of SSRMS-type manipulators, the Denavit-Hartenberg (DH) method has a singular problem when two adjacent joint axes are nearly parallel. To avoid this problem, this paper proposes a novel analytical inverse kinematics method for SSRMS-type manipulators based on the product of exponentials (POE) formula and the Paden-Kahan subproblem. Because of the symmetrical structure, an SSRMS-type manipulator degrades to two kinds of 6-degree-of-freedom (DOF) manipulators when locking a single joint (joint 1, 2, 6, or 7). The analytical inverse kinematics of these two kinds of 6-DOF manipulators is solved by combining the Paden-Kahan subproblems and geometric and algebraic methods, respectively. The proposed approach is not only singularity free compared with the traditional DH-based methods but also more accurate than the POE-based numerical solution. The simulation results verify the efficiency of the proposed approach.

The Waters scheme was transformed into the content extraction signature scheme at the bridge of the thought from the batch signature scheme.The proposed scheme is improved by the RSAProd scheme,presented by Steinfeld,Bull,Zheng (ICISC 2001).The operation time is saved in every stage at the slight sacrifice of the length of extraction signatures.The security was proved that the proposed scheme is existentially unforgeable under chosen message attacks while the privacy is maintained.