Brain tumor segmentation by combining MultiEncoder UNet with wavelet fusion.

BACKGROUND AND OBJECTIVE: Accurate segmentation of brain tumors from multimodal magnetic resonance imaging (MRI) holds significant importance in clinical diagnosis and surgical intervention, while current deep learning methods cope with situations of multimodal MRI by an early fusion strategy that implicitly assumes that the modal relationships are linear, which tends to ignore the complementary information between modalities, negatively impacting the model's performance. Meanwhile, long-range relationships between voxels cannot be captured due to the localized character of the convolution procedure. METHOD: Aiming at this problem, we propose a multimodal segmentation network based on a late fusion strategy that employs multiple encoders and a decoder for the segmentation of brain tumors. Each encoder is specialized for processing distinct modalities. Notably, our framework includes a feature fusion module based on a 3D discrete wavelet transform aimed at extracting complementary features among the encoders. Additionally, a 3D global context-aware module was introduced to capture the long-range dependencies of tumor voxels at a high level of features. The decoder combines fused and global features to enhance the network's segmentation performance. RESULT: Our proposed model is experimented on the publicly available BraTS2018 and BraTS2021 datasets. The experimental results show competitiveness with state-of-the-art methods. CONCLUSION: The results demonstrate that our approach applies a novel concept for multimodal fusion within deep neural networks and delivers more accurate and promising brain tumor segmentation, with the potential to assist physicians in diagnosis.

tRF-Gly-GCC in Atretic Follicles Promotes Ferroptosis in Granulosa Cells by Down-Regulating MAPK1.

Follicle development refers to the process in which the follicles in the ovary gradually develop from the primary stage to a mature state, and most primary follicles fail to develop normally, without forming a dense granular cell layer and cell wall, which is identified as atretic follicles. Granulosa cells assist follicle development by producing hormones and providing support, and interference in the interaction between granulosa cells and oocytes may lead to the formation of atretic follicles. Ferroptosis, as a non-apoptotic form of death, is caused by cells accumulating lethal levels of iron-dependent phospholipid peroxides. Healthy follicles ranging from 4 to 5 mm were randomly divided into two groups: a control group (DMSO) and treatment group (10 uM of ferroptosis inducer erastin). Each group was sequenced after three repeated cultures for 24 h. We found that ferroptosis was associated with atretic follicles and that the in vitro treatment of healthy follicles with the ferroptosis inducer erastin produced a phenotype similar to that of atretic follicles. Overall, our study elucidates that tRF-1:30-Gly-GCC-2 is involved in the apoptosis and ferroptosis of GCs. Mechanistically, tRF-1:30-Gly-GCC-2 inhibits granulosa cell proliferation and promotes ferroptosis by inhibiting Mitogen-activated protein kinase 1 (MAPK1). tRF-1:30-Gly-GCC-2 may be a novel molecular target for improving the development of atretic follicles in ovarian dysfunction. In conclusion, our study provides a new perspective on the pathogenesis of granulosa cell dysfunction and follicular atresia.

Copper mediated follicular atresia: Implications for granulosa cell death.

3-nitropropanoic acid is a potent oxidative stress inducer that is conventionally regarded as a regulator of follicular atresia by regulating granulosa cells (GCs) death through the apoptosis pathway. There has been no research investigating the impact of copper metal overload induced Cuproptosis in ovarian GCs as a factor contributing to hindered follicular development.To elucidate whether 3-NP-induced oxidative stress plays a contributory role in promoting Cuproptosis, and discuss the role of Cuproptosis in the development of ovarian follicles.We conducted an analysis of cuproptosis occurrence in murine GCs and C57BL/6 J mice under the influence of 3-NP and 3-NP with added exogenous copper.The results revealed that 3-NP serving as a robust facilitator of exogenous copper uptake by upregulating the expression of copper transporter 1 (CTR1). In turn, culminated in the accumulation of intracellular copper within mouse granulosa cells (mGCs). Furthermore, 3-NP promoted mitochondrial permeability transition pore opening and concurrently reduced the stability of lipoic acid proteins. These actions collectively induced the oligomerization of Dihydrolipoamide S-Acetyltransferase (DLAT), ultimately leading to cuproptosis in GCs and consequent follicular atresia. Heavy metal copper and fungal decomposition product 3-NP, induce ovarian atresia via cuproptosis, modulating the reproductive performance of female animals.

n-3 PUFA Promotes Ferroptosis in PCOS GCs by Inhibiting YAP1 through Activation of the Hippo Pathway.

Polycystic ovary syndrome (PCOS) is an endocrine disorder characterized by hyperandrogenemia with multiple suspended sinus follicles, thickened cortical tissue, and excessive proliferation of ovarian granulosa cells that severely affects the fertility and quality of life of women. The addition of n-3 PUFA to the diet may slightly reduce body weight and greatly alleviate disturbed blood hormone levels in PCOS mice. We treated KGN as a cell model for n-3 PUFA addition and showed that n-3 PUFA inhibited the proliferation of GCs and promoted ferroptosis in ovarian granulosa cells. We used CCK-8, fluorescence quantitative transmission electron microscopy experiments and ferroptosis marker gene detection and other methods. Furthermore, n-3 PUFA was found to promote YAP1 exocytosis by activating Hippo and weakening the cross-talk between YAP1 and Nrf2 by activating the Hippo signaling pathway. In this study, we found that n-3 PUFA inhibited the over proliferation of granulosa cells in ovarian follicles by activating Hippo, promoting YAP1 exocytosis, weakening the cross-talk between YAP1 and Nrf2, and ultimately activating the ferroptosis sensitivity of ovarian granulosa cells. We demonstrate that n-3 PUFA can alleviate the hormonal and estrous cycle disorder with PCOS by inhibiting the YAP1-Nrf2 crosstalk that suppresses over proliferating ovarian granulosa cells and promotes iron death in GCs. These findings reveal the molecular mechanisms by which n-3 PUFA attenuates PCOS and identify YAP1-Nrf2 as a potential therapeutic target for regulation granulosa cells in PCOS.

Note: Response time characterization of fiber Bragg grating temperature sensor in water medium.

Response times of fiber Bragg grating (FBG) temperature sensors are investigated. The response model is established and three types of sensors, including bare, gold-coated, and ceramics packaged FBG, are employed to measure their response time under a step simulation. The matched FBG method is used to obtain the response times. Each FBG sensor is measured 5 times and the average values of the sensors are 8.9 ms, 12.3 ms, and 336 ms, respectively. The results are useful for temperature measurement caring about time characteristic.

An optical fiber Fabry-Perot flow measurement technology based on partial bend structure.

An optical fiber Fabry-Perot (F-P) flow measurement technology is presented, which is based on partial bend structure. A 90° partial bend structure is designed to achieve the non-probe flow measurement with a pressure difference. The fluid simulation results of partial bend structure show that the error of the pressure difference is below 0.05 kPa during steady flow. The optical fiber F-P sensor mounted on the elbow with pressure test accuracy of 1% full scale is used to measure the fluid flow. Flow test results show that when the flow varies from 1 m(3)/h to 6.5 m(3)/h at ambient temperature of 25 °C, the response time is 1 s and the flow test accuracy is 4.5% of the F-P flow test system, proving that the F-P flow test method based on partial bend structure can be used in fluid flow measurement.