Search

Ductal carcinoma in situ (DCIS), a noninvasive breast cancer, rarely metastasises to distant locations. When the initial lesion is stable, bone marrow metastasis (BMM) and bone marrow necrosis (BMN) are even less common. Here, we report the case of a 47-year-old female patient who underwent localized surgery and radiotherapy for right-sided DCIS. The patient also had a mutation in the breast cancer susceptibility gene 1 (BRCA1 , OMIM: 113705) and tested positive for the progesterone and estrogen receptors. After 11 years of disease-free survival, the patient developed severe thrombocytopenia, anemia, fever, malaise, generalized multifocal pain, and irregular vaginal bleeding. A nodule was later found in the right axilla, and a postoperative biopsy revealed tumor cells from the breast. After three bone marrow biopsies, Positron Emission Tomography, 18F-fluorodeoxyglucose, positron emission tomography, computed tomography (18F-FDG PET/CT) scans, and other examinations, she was finally diagnosed with breast cancer BMM and BMN (stable primary lesion without bone metastasis). Despite symptomatic supportive treatment, the patient ultimately died rapidly as her condition deteriorated. In this case, we explored the possible mechanisms of BMM in this patient with DCIS by reviewing the literature related to this case and discussing the heterogeneous clinical presentation and pathologic phenotype. The diagnostic and therapeutic course of this case was extremely challenging. This suggests to clinicians that regular checkups and monitoring are necessary, even if the rate of distant metastasis from DCIS is low. [ABSTRACT FROM AUTHOR]

The main challenges faced when detecting targets captured by UAVs include small target image size, dense target distribution, and uneven category distribution.In addition, the hardware limitations of UAVs impose constraints on the size and complexity of the model, which may lead to poor detection accuracy of the model. In order to solve these problems, a small target detection method based on the improved YOLOv8 algorithm for UAV viewpoint is proposed. The following improvements are made to the YOLOv8n model. Firstly, a bi-directional feature pyramid network (BiFPN) is introduced to enhance the fusion capability of the features. This improvement leads to better detection of small targets. Secondly, in the head part of the model, the original C2f module is replaced with the C3Ghost module. This change maintains the model's performance while significantly reducing the computational load. Lastly, the detection head adds a channel attention mechanism. This mechanism helps in filtering out unimportant information and enhancing the recognition of key features. The MPDIoU (Minimum Point Distance based IoU) loss function is improved, and the idea of inner-IoU loss function is adopted as a way to improve the model's learning ability for difficult samples. Experimental results on the VisDrone dataset show that the YOLOv8n model with these improvements improves 17.2%, 10.5%, and 16.2% in mean accuracy (mAP), precision (P), and recall (R), respectively, and these improvements significantly improve the performance of small target detection from the UAV viewpoint. [ABSTRACT FROM AUTHOR]

Background: Epidemiological studies associate an increase in breast cancer risk, particularly triple-negative breast cancer (TNBC), with lack of breastfeeding. This is more prevalent in African American women, with significantly lower rate of breastfeeding compared to Caucasian women. Prolonged breastfeeding leads to gradual involution (GI), whereas short-term or lack of breastfeeding leads to abrupt involution (AI) of the breast. Our previous study utilizing a murine model demonstrated precancerous changes, specifically hyperplasia, a non-obligate precursor of breast cancer in the mammary glands of AI mice. Here we investigated mechanisms during early events of AI that prompts precancerous changes in mouse mammary glands. Methods: Uniparous FVB/N mice were randomized to AI and GI on postpartum day 7 when all pups were removed from AI dams. GI dams were allowed to nurse the pups till day 31. Cell death kinetics and gene expression were assessed by TUNEL assay and qPCR respectively. Immune cell changes were investigated by flow cytometry, cytokine array and multiplex immunofluorescence. 3D-organoid cultures were used for in vitro assay of luminal progenitor cells. Results: AI results in rapid cell death, DNA repair response, and immunosuppressive myeloid cells infiltration, leading to a chronically inflamed microenvironment. GI elicits a more controlled immune response and extended cell death. At the peak of cell death, AI glands harbored more immunosuppressive myeloid-derived suppressor cells (MDSCs) and CD206 + M2-like macrophages, known to promote oncogenic events, compared to GI glands. AI glands exhibit an enrichment of CCL9-producing MDSCs and CD206 + M2-like macrophages that promote expansion of ELF5 + /ERα- luminal cells, both in vitro and in vivo. Multiplex imaging of AI glands demonstrated an increase in ELF5 + /WNT5a + luminal cells alongside a reduction in the ELF5 + /ERα + population when involution appeared histologically complete. A significantly higher number of CD206 + cells in post involution AI gland attests to a chronically inflamed state induced by AI. Conclusions: Our findings reveal significant disparities between AI and GI gland dynamics at the early phase of involution. CCL9, secreted by immune cells at the peak of cell death promotes expansion of Elf5 + /ERα- luminal progenitor cells, the putative precursors of TNBC connecting early events of AI with increased breast cancer risk. [ABSTRACT FROM AUTHOR]

Striatin-interacting protein 1 (Strip1) is a core component of the striatin interacting phosphatase and kinase (STRIPAK) complex, which is involved in embryogenesis and development, circadian rhythms, type 2 diabetes, and cancer progression. However, the expression and role of Strip1 in the mammalian cochlea remains unclear. Here we studied the expression and function of Strip1 in the mouse cochlea by using Strip1 knockout mice. We first found that the mRNA and protein expression of Strip1 increases as mice age starting from postnatal day (P) 3 and reaches its highest expression level at P30 and that the expression of Strip1 can be detected by immunofluorescent staining starting from P14 only in cochlear HCs, and not in supporting cells (SCs). Next, we crossed Strip1 heterozygous knockout (Strip +/−) mice to obtain Strip1 homozygous knockout (Strip1 −/−) mice for studying the role of Strip1 in cochlear HCs. However, no Strip1 −/− mice were obtained and the ratio of Strip +/− to Strip1 +/+ mice per litter was about 2:1, which suggested that homozygous Strip1 knockout is embryonic lethal. We measured hearing function and counted the HC number in P30 and P60 Strip +/− mice and found that they had normal hearing ability and HC numbers compared to Strip1 +/+ mice. Our study suggested that Strip1 probably play important roles in HC development and maturation, which needs further study in the future. [ABSTRACT FROM AUTHOR]

This study constructs a Stackelberg game model between low‐carbon manufacturers and capital‐constrained retailers. Considering the manufacturer's financing model, the manufacturer's investment model, and the internal blended financing model, it studies the optimal wholesale price of manufacturers. This paper investigates the impact of consumers' low‐carbon preference, the financing interest rate of manufacturers, investment ratio, investment return on carbon emission reduction investment, and supply chain pricing. The conditions for low‐carbon supply chain participants to choose the best financing mode and the impact of different financing models on the performance of low‐carbon supply chains were obtained. [ABSTRACT FROM AUTHOR]

Since the actual operation of the bearing inevitably exists in both noise and variable working conditions, most of the traditional networks can only deal with them alone, and the fault identification result will be significantly reduced under such complex conditions. Therefore, Parallel Multichannel Deep Convolution Neural Network (PMDCNN) and Long Short-Term Memory (LSTM) are proposed as PMDCNN-LSTM model to enable better performance. And a local sparse structure is used to greatly reduce the number of model parameters, the Exponential Linear Unit (ELU) activation function is used to further improve accuracy and stability. The results show that the proposed method is strongly resistant to noise and variable working conditions, as verified by the Case Western Reserve University (CWRU) bearing dataset and bearing fault simulation experimental platform dataset. The comparison with other model shows that the proposed model has good applicability, strong stability and high accuracy of bearing fault identification. [ABSTRACT FROM AUTHOR]

The correction notice in the journal "Frontiers in Genetics" addresses an error in Figure 5B of the article "Characterization of Strip1 expression in mouse cochlear hair cells." The image of the cochlear middle turn in P60 Strip1+/− mice was mistakenly used instead of the cochlear apex turn. The authors have acknowledged and corrected this mistake, emphasizing that it does not impact the scientific conclusions of the study. The original article has been updated to reflect the accurate information. [Extracted from the article]