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With the rapid development of the autonomous driving industry, there is increasing research on related perception tasks. However, research on road surface traffic sign detection tasks is still limited. There are two main challenges to this task. First, when the target object’s pixel ratio is small, the detection accuracy often decreases. Second, the existing publicly available road surface traffic sign datasets have limited image data. To address these issues, this paper proposes a new instance segmentation network, RTS R-CNN, for road surface traffic sign detection tasks based on Mask R-CNN. The network can accurately perceive road surface traffic signs and provide important information for the autonomous driving decision-making system. Specifically, CSPDarkNet53_ECA is proposed in the feature extraction stage to enhance the performance of deep convolutional networks by increasing inter-channel interactions. Second, to improve the network’s detection accuracy for small target objects, GR-PAFPN is proposed in the feature fusion part, which uses a residual feature enhancement module (RFA) and atrous spatial pyramid pooling (ASPP) to optimize PAFPN and introduces a balanced feature pyramid module (BFP) to handle the imbalanced feature information at different resolutions. Finally, data augmentation is used to generate more data and prevent overfitting in specific scenarios. The proposed method has been tested on the open-source dataset Ceymo, achieving a Macro F1-score of 87.56%, which is 2.3% higher than the baseline method, while the inference speed reaches 23.5 FPS.

Vaginal microbiota transplantation (VMT) is a cutting-edge treatment modality that has the potential to revolutionize the management of vaginal disorders. The human vagina is a complex and dynamic ecosystem home to a diverse community of microorganisms. These microorganisms play a crucial role in maintaining the health and well-being of the female reproductive system. However, when the balance of this ecosystem is disrupted, it can lead to the development of various vaginal disorders. Conventional treatments, such as antibiotics and antifungal medications, can temporarily relieve the symptoms of vaginal disorders. However, they often fail to address the underlying cause of the problem, which is the disruption of the vaginal microbiota. In recent years, VMT has emerged as a promising therapeutic approach that aims to restore the balance of the vaginal ecosystem. Several studies have demonstrated the safety and efficacy of VMT in treating bacterial vaginosis, recurrent yeast infections, and other vaginal conditions. The procedure has also shown promising results in reducing the risk of sexually transmitted infections and preterm birth in pregnant women. However, more research is needed to establish optimal donor selection, preparation, and screening protocols, as well as long-term safety and efficacy. VMT offers a safe, effective, and minimally invasive treatment option for women with persistent vaginal problems. It could improve the quality of life for millions of women worldwide and become a standard treatment option shortly. With further research and development, it could potentially treat a wide range of other health problems beyond the scope of vaginal disorders.

To the Editor: The amide proton transfer (APT) magnetic resonance imaging (MRI) is an emerging molecular imaging method for detecting mobile proteins/peptides and the potential of hydrogen (pH) with enhanced detection sensitivity compared to direct measurement without external magnetic resonance contrast agents [Figure 1]. [...]the utilization of APT can assist medical professionals in devising treatment regimens tailored to the individual needs of cancer patients, resulting in improved therapeutic outcomes. In addition to established imaging techniques such as O-(2-[18F]fluoroethyl)-L-tyrosine (FET)-positron emission tomography (PET) and dynamic susceptibility contrast (DSC) perfusion imaging, the utilization of amide proton transfer-weighted (APTw) imaging has emerged as a promising and innovative magnetic resonance (MR) technique. [...]research is necessary to enhance our understanding of various biological imaging techniques’ benefit. [...]precise preoperative assessment of the histologic grade using imaging modalities is imperative.

Autoimmune diseases can damage specific or multiple organs and tissues, influence the quality of life, and even cause disability and death. A ‘disease in a dish’ can be developed based on patients-derived induced pluripotent stem cells (iPSCs) and iPSCs-derived disease-relevant cell types to provide a platform for pathogenesis research, phenotypical assays, cell therapy, and drug discovery. With rapid progress in molecular biology research methods including genome-sequencing technology, epigenetic analysis, ‘-omics’ analysis and organoid technology, large amount of data represents an opportunity to help in gaining an in-depth understanding of pathological mechanisms and developing novel therapeutic strategies for these diseases. This paper aimed to review the iPSCs-based research on phenotype confirmation, mechanism exploration, drug discovery, and cell therapy for autoimmune diseases, especially multiple sclerosis, inflammatory bowel disease, and type 1 diabetes using iPSCs and iPSCs-derived cells.

Landslide displacement system is generally characterized by non-stationary and nonlinear characteristics. Traditionally, many artificial neural network (ANN) models have been proposed to forecast landslide displacement. However, the underlying non-stationary characteristics in the landslide displacement are not captured, and the input–output variables of the ANN models are not selected nonlinearly. To overcome these drawbacks, this paper proposes the chaos theory-based discrete wavelet transform (DWT)–extreme learning machine (ELM) model to predict landslide displacement. The DWT method is adopted to decompose the landslide displacement into several low- and high-frequency components to address the non-stationary characteristics. And chaos theory is used to determine the input–output variables of the ELM model. The cumulative displacement time series of the Baishuihe and Baijiabao landslides in the Three Gorges Reservoir Area, China, are used as data sets. The results show that the chaotic DWT-ELM model accurately predicts landslide displacement. The chaotic DWT–support vector machine (SVM), chaotic DWT–back-propagation neural network (BPNN) and single chaotic ELM models are used for comparisons. The comparison results show that the chaotic DWT-ELM model achieves higher prediction accuracy than do the chaotic DWT-SVM, chaotic DWT-BPNN and the single chaotic ELM models.

Abstract Bacterial outer membrane vesicles (OMVs) are diminutive vesicles naturally released by Gram-negative bacteria. These vesicles possess distinctive characteristics that attract attention for their potential use in drug administration and immunotherapy in cancer treatment. Therapeutic medicines may be delivered via OMVs directly to the tumor sites, thereby minimizing exposure to healthy cells and lowering the risk of systemic toxicity. Furthermore, the activation of the immune system by OMVs has been demonstrated to facilitate the recognition and elimination of cancer cells, which makes them a desirable tool for immunotherapy. They can also be genetically modified to carry specific antigens, immunomodulatory compounds, and small interfering RNAs, enhancing the immune response to cancerous cells and silencing genes associated with disease progression. Combining OMVs with other cancer treatments like chemotherapy and radiation has shown promising synergistic effects. This review highlights the crucial role of bacterial OMVs in cancer, emphasizing their potential as vectors for novel cancer targeted therapies. As researchers delve deeper into the complexities of these vesicles and their interactions with tumors, there is a growing sense of optimism that this avenue of study will bring positive outcomes and renewed hope to cancer patients in the foreseeable future.

Mps one binder 2 (MOB2) regulates the NDR kinase family, however, whether and how it is implicated in cancer remain unknown. Here we show that MOB2 functions as a tumor suppressor in glioblastoma (GBM). Analysis of MOB2 expression in glioma patient specimens and bioinformatic analyses of public datasets revealed that MOB2 was downregulated at both mRNA and protein levels in GBM. Ectopic MOB2 expression suppressed, while depletion of MOB2 enhanced, the malignant phenotypes of GBM cells, such as clonogenic growth, anoikis resistance, and formation of focal adhesions, migration, and invasion. Moreover, depletion of MOB2 increased, while overexpression of MOB2 decreased, GBM cell metastasis in a chick chorioallantoic membrane model. Overexpression of MOB2-mediated antitumor effects were further confirmed in mouse xenograft models. Mechanistically, MOB2 negatively regulated the FAK/Akt pathway involving integrin. Notably, MOB2 interacted with and promoted PKA signaling in a cAMP-dependent manner. Furthermore, the cAMP activator Forskolin increased, while the PKA inhibitor H89 decreased, MOB2 expression in GBM cells. Functionally, MOB2 contributed to the cAMP/PKA signaling-regulated inactivation of FAK/Akt pathway and inhibition of GBM cell migration and invasion. Collectively, these findings suggest a role of MOB2 as a tumor suppressor in GBM via regulation of FAK/Akt signaling. Additionally, we uncover MOB2 as a novel regulator in cAMP/PKA signaling. Given that small compounds targeting FAK and cAMP pathway have been tested in clinical trials, we suggest that interference with MOB2 expression and function may support a theoretical and therapeutic basis for applications of these compounds.

[1,2] Researchers found that anthracycline-in-duced cardiotoxicity (AIC) develops during or after treatment; however, the exact mechanism is unclear. [...]the optimal use of non-invasive cardiac examinations is necessary to control the drug side effects. Medical imaging technology has been reckoned to be the most effective method for the non-invasive detection of AIC. [...]to minimize the cardiac risk, a brief overview of the latest advances in medical imaging technology has been provided in this article. [...]it can be used for the monitoring of patients who are away from chemotherapy or longitudinal detection of anthracycline-induced changes during treatment. [...]the potential association between this uptake index and anthracycline cardiotoxicity has only been described in one case report, and its clinical potential remains uncertain. [...]Bauckneht et al[7] conducted a transformation study based on this report to verify whether evaluation of doxorubicin uptake based on cardiac FDG can predict advanced cardiotoxicity.

Activating transcription factor 6 (ATF6) is a key regulator of the unfolded protein response (UPR) and is important for ER function and protein homeostasis in metazoan cells. Patients carrying loss-of-function ATF6 disease alleles develop the cone dysfunction disorder achromatopsia. The effect of loss of ATF6 function on other cell types, organs, and diseases in people remains unclear. Here, we report that progressive sensorineural hearing loss was a notable complaint in some patients carrying ATF6 disease alleles and that Atf6-/- mice also showed progressive auditory deficits affecting both sexes. In mice with hearing deficits, we found disorganized stereocilia on hair cells and focal loss of outer hair cells. Transcriptomics analysis of Atf6-/- cochleae revealed a marked induction of the UPR, especially through the protein kinase RNA-like endoplasmic reticulum kinase (PERK) arm. These findings identify ATF6 as an essential regulator of cochlear health and function. Furthermore, they support the idea that ATF6 inactivation in people causes progressive sensorineural hearing loss as part of a blindness-deafness genetic syndrome targeting hair cells and cone photoreceptors. Last, our genetic findings indicate that ER stress is an important pathomechanism underlying cochlear damage and hearing loss, with clinical implications for patient lifestyle modifications that minimize environmental and physiological sources of ER stress to the ear.

Malignant gliomas occur more often in adults and may affect any part of the central nervous system (CNS). Although their results could be better, surgical excision, postoperative radiation and chemotherapy, and electric field therapy are today’s mainstays of glioma care. However, bacteria can also exert anti-tumor effects via mechanisms such as immune regulation and bacterial toxins to promote apoptosis, inhibit angiogenesis, and rely on their natural characteristics to target the tumor microenvironment of hypoxia, low pH, high permeability, and immunosuppression. Tumor-targeted bacteria expressing anticancer medications will go to the cancer site, colonize the tumor, and then produce the therapeutic chemicals that kill the cancer cells. Targeting bacteria in cancer treatment has promising prospects. Rapid advances have been made in the study of bacterial treatment of tumors, including using bacterial outer membrane vesicles to load chemotherapy drugs or combine with nanomaterials to fight tumors, as well as the emergence of bacteria combined with chemotherapy, radiotherapy, and photothermal/photodynamic therapy. In this study, we look back at the previous years of research on bacteria-mediated glioma treatment and move forward to where we think it is headed.