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To address the performance degradation of cross-domain object detection under various illumination conditions and adverse weather scenarios, this paper introduces a novel method a called Step-wise Domain Adaptation DEtection TRansformer (SDA-DETR). Our approach decomposes the adaptation process into three sequential steps, progressively transferring knowledge from a labeled dataset to an unlabeled one using the DETR (DEtection TRansformer) architecture. Each step precisely reduces domain discrepancy, thereby facilitating effective transfer learning. In the initial step, a target-like domain is constructed as an auxiliary to the source domain to reduce the domain gap at the image level. Then, we adaptively align the source domain and target domain features at both global and local levels. To further mitigate model bias towards the source domain, we develop a token-masked autoencoder (t-MAE) to enhance target domain features at the semantic level. Comprehensive experiments demonstrate that the SDA-DETR outperforms several popular cross-domain object detection methods on three challenging public driving datasets. [ABSTRACT FROM AUTHOR]

New Findings: What is the central question of this study?Do autoantibodies to the M2 muscarinic receptor (M2R‐AAbs) have the potential to facilitate specific sustained tachyarrhythmias in the presence of thyroxine (T4) in rabbits?What is the main finding and its importance?The M2R‐AAb and T4 jointly destabilized the electrophysiological properties, thus promoting the occurrence of atrial and sinus tachyarrhythmias in rabbits. These findings provide a practical basis for understanding the pathophysiological role of M2R‐AAb alone and with T4 in arrhythmia induction and might provide an innovative option for treatment of Graves' disease with rhythm disturbance. Activating autoantibodies toward the β1/2‐adrenergic receptors (β1/2AR‐AAbs) and M2 muscarinic receptor (M2R‐AAbs) are present in a high proportion of patients with Graves' disease. We previously demonstrated that β1/2AR‐AAbs with or without the presence of M2R‐AAbs in combination with excessive thyroxine (T4) increased the induction of sustained tachyarrhythmias in an autoimmune rabbit model. However, the separate role of M2R‐AAbs and their interaction with T4 are not clear. The aim of this study was to investigate the impact of M2R‐AAbs and T4 on the induction of cardiac arrhythmias in a similar rabbit model. Ten New Zealand White rabbits were randomly divided into two groups. In group A (n = 6), the rabbits were immunized with the second extracellular loop peptide of M2R and subjected to 2 weeks of T4 treatment. In group B (n = 4), the rabbits were treated only with T4 for 2 weeks. After induction of general anaesthesia, rabbits were subjected to an electrophysiological study at 0 (pre‐immune), 6 (post‐immune) and 8 weeks (post‐immune+T4 treatment) in group A and at 0 (baseline) and 8 weeks (T4 treatment) in group B. Each rabbit served as its own control. In group A, high levels and activity of M2R‐AAbs were detected in all immunized animals. Thyroxine in combination with immunization significantly increased induction of sustained sinus tachycardia and atrial fibrillation in comparison to the pre‐immune state. In group B, T4 predominantly induced sustained sinus tachycardia. This study demonstrated that M2R‐AAbs and T4 jointly increased the susceptibility to both sinus and atrial tachyarrhythmias. The data supported the pathophysiological role of M2R‐AAbs in hyperthyroidism‐associated supraventricular tachyarrhythmias. [ABSTRACT FROM AUTHOR]

Polycystic ovary syndrome (PCOS), a metabolic and reproductive disease, is frequently associated with type 2 diabetes. We have demonstrated activating autoantibodies (AAb) directed toward the second extracellular loop (ECL2) of the gonadotropin‐releasing hormone receptor (GnRHR) are present in a significant subgroup of PCOS patients. It is unclear whether GnRHR‐AAb can induce peripheral tissue insulin resistance (IR) in animal models. Sixteen rats were divided equally into a GnRHR ECL2 peptide‐immunized group (IMM group) and a control group (CON group). Sera GnRHR‐AAb titer, luteinizing hormone (LH), and testosterone (T) were higher in IMM rats compared with CON rats. No significant difference in fasting blood glucose was observed between the two groups. However, the plasma glucose level at other time points of the IMM group was higher than that of the CON group during an intraperitoneal glucose tolerance test (IPGTT) and an insulin tolerance test (ITT) (p < 0.01). These data support the likelihood of the GnRHR‐AAb induction of glucose intolerance and IR. Compared with the CON group, the IMM group showed a significant increase in insulin‐stimulated phosphorylation of IRS‐1 (p‐IRS‐1 S636/639) and a decrease in insulin‐stimulated phosphorylation of Akt (p‐AKT S473). Expression of the glucose transport genes including GLUT‐2 in liver and GLUT‐4 in white adipose tissue and skeletal muscle was significantly decreased in IMM rats compared with the CON rats. Serum levels of proinflammatory cytokines (TNF‐α, IL‐1α, and IL‐18) were increased, while anti‐inflammatory cytokines (IL‐4 and IL‐10) were decreased in the IMM group. Taken together, elevated GnRHR‐AAb enhanced LH, hyperandrogenism, and inflammation. These changes are likely related to the observed peripheral tissue IR through the downregulation of the insulin‐stimulated IRS/PI3K/Akt/Glut signaling pathway. [ABSTRACT FROM AUTHOR]

As a dual-modal imaging technology that has emerged in recent years, cone-beam X-ray luminescence computed tomography (CB-XLCT) has exhibited promise as a tool for the early three-dimensional detection of tumors in small animals. However, due to the challenges imposed by the low absorption and high scattering of light in tissues, the CB-XLCT reconstruction problem is a severely ill-conditioned inverse problem, rendering it difficult to obtain satisfactory reconstruction results. In this study, a strategy that utilizes dictionary learning and group structure (DLGS) is proposed to achieve satisfactory CB-XLCT reconstruction performance. The group structure is employed to account for the clustering of nanophosphors in specific regions within the organism, which can enhance the interrelation of elements in the same group. Furthermore, the dictionary learning strategy is implemented to effectively capture sparse features. The performance of the proposed method was evaluated through numerical simulations and in vivo experiments. The experimental results demonstrate that the proposed method achieves superior reconstruction performance in terms of location accuracy, target shape, robustness, dual-source resolution, and in vivo practicability.