Recent deep learning-based brain tumor segmentation models using multi-modality magnetic resonance imaging: a prospective survey.

Radiologists encounter significant challenges when segmenting and determining brain tumors in patients because this information assists in treatment planning. The utilization of artificial intelligence (AI), especially deep learning (DL), has emerged as a useful tool in healthcare, aiding radiologists in their diagnostic processes. This empowers radiologists to understand the biology of tumors better and provide personalized care to patients with brain tumors. The segmentation of brain tumors using multi-modal magnetic resonance imaging (MRI) images has received considerable attention. In this survey, we first discuss multi-modal and available magnetic resonance imaging modalities and their properties. Subsequently, we discuss the most recent DL-based models for brain tumor segmentation using multi-modal MRI. We divide this section into three parts based on the architecture: the first is for models that use the backbone of convolutional neural networks (CNN), the second is for vision transformer-based models, and the third is for hybrid models that use both convolutional neural networks and transformer in the architecture. In addition, in-depth statistical analysis is performed of the recent publication, frequently used datasets, and evaluation metrics for segmentation tasks. Finally, open research challenges are identified and suggested promising future directions for brain tumor segmentation to improve diagnostic accuracy and treatment outcomes for patients with brain tumors. This aligns with public health goals to use health technologies for better healthcare delivery and population health management.

The BMP2 prodomain promotes dimerization and cleavage of BMP6 homodimers and BMP2/6 heterodimers in vivo.

Bone morphogenetic protein 2 (BMP2) and BMP6 are key regulators of systemic iron homeostasis. All BMPs are generated as inactive precursor proteins that dimerize and are cleaved to generate the bioactive ligand and inactive prodomain fragments, but nothing is known about how BMP2 or BMP6 homodimeric or heterodimeric precursor proteins are proteolytically activated. Here, we conducted in vitro cleavage assays, which revealed that BMP2 is sequentially cleaved by furin at two sites, initially at a site upstream of the mature ligand, and then at a site adjacent to the ligand domain, while BMP6 is cleaved at a single furin motif. Cleavage of both sites of BMP2 is required to generate fully active BMP2 homodimers when expressed in Xenopus embryos or liver endothelial cells, and fully active BMP2/6 heterodimers in Xenopus . We analyzed BMP activity in Xenopus embryos expressing chimeric proteins consisting of the BMP2 prodomain and BMP6 ligand domain, or vice versa. We show that the prodomain of BMP2 is necessary and sufficient to generate active BMP6 homodimers and BMP2/6 heterodimers, whereas the BMP6 prodomain cannot generate active BMP2 homodimers or BMP2/6 heterodimers. We examined BMP2 and BMP6 homodimeric and heterodimeric ligands generated from native and chimeric precursor proteins expressed in Xenopus embryos. Whereas native BMP6 is not cleaved when expressed alone, it is cleaved to generate BMP2/6 heterodimers when co-expressed with BMP2. Furthermore, BMP2-6 chimeras are cleaved to generate BMP6 homodimers. Our findings reveal an important role for the BMP2 prodomain in dimerization and proteolytic activation of BMP6.

High energy density in artificial heterostructures through relaxation time modulation.

Electrostatic capacitors are foundational components of advanced electronics and high-power electrical systems owing to their ultrafast charging-discharging capability. Ferroelectric materials offer high maximum polarization, but high remnant polarization has hindered their effective deployment in energy storage applications. Previous methodologies have encountered problems because of the deteriorated crystallinity of the ferroelectric materials. We introduce an approach to control the relaxation time using two-dimensional (2D) materials while minimizing energy loss by using 2D/3D/2D heterostructures and preserving the crystallinity of ferroelectric 3D materials. Using this approach, we were able to achieve an energy density of 191.7 joules per cubic centimeter with an efficiency greater than 90%. This precise control over relaxation time holds promise for a wide array of applications and has the potential to accelerate the development of highly efficient energy storage systems.

A Gelatin/Alginate Double Network Hydrogel Nerve Guidance Conduit Fabricated by a Chemical-Free Gamma Radiation for Peripheral Nerve Regeneration.

Nerve guidance conduits (NGCs) are widely developed using various materials for the functional repair of injured or diseased peripheral nerves. Especially, hydrogels are considered highly suitable for the fabrication of NGCs due to their beneficial tissue-mimicking characteristics (e.g., high water content, softness, and porosity). However, the practical applications of hydrogel-based NGCs are hindered due to their poor mechanical properties and complicated fabrication processes. To bridge this gap, a novel double-network (DN) hydrogel using alginate and gelatin by a two-step crosslinking process involving chemical-free gamma irradiation and ionic crosslinking, is developed. DN hydrogels (1% alginate and 15% gelatin), crosslinked with 30 kGy gamma irradiation and barium ions, exhibit substantially improved mechanical properties, including tensile strength, elastic modulus, and fracture stain, compared to single network (SN) gelatin hydrogels. Additionally, the DN hydrogel NGC exhibits excellent kink resistance, mechanical stability to successive compression, suture retention, and enzymatic degradability. In vivo studies with a sciatic defect rat model indicate substantially improved nerve function recovery with the DN hydrogel NGC compared to SN gelatin and commercial silicone NGCs, as confirm footprint analysis, electromyography, and muscle weight measurement. Histological examination reveals that, in the DN NGC group, the expression of Schwann cell and neuronal markers, myelin sheath, and exon diameter are superior to the other controls. Furthermore, the DN NGC group demonstrates increased muscle fiber formation and reduced fibrotic scarring. These findings suggest that the mechanically robust, degradable, and biocompatible DN hydrogel NGC can serve as a novel platform for peripheral nerve regeneration and other biomedical applications, such as implantable tissue constructs.

Laminin-Augmented Decellularized Extracellular Matrix Ameliorating Neural Differentiation and Neuroinflammation in Human Mini-Brains.

Non-neural extracellular matrix (ECM) has limited application in humanized physiological neural modeling due to insufficient brain-specificity and safety concerns. Although brain-derived ECM contains enriched neural components, certain essential components are partially lost during the decellularization process, necessitating augmentation. Here, it is demonstrated that the laminin-augmented porcine brain-decellularized ECM (P-BdECM) is xenogeneic factor-depleted as well as favorable for the regulation of human neurons, astrocytes, and microglia. P-BdECM composition is comparable to human BdECM regarding brain-specificity through the matrisome and gene ontology-biological process analysis. As augmenting strategy, laminin 111 supplement promotes neural function by synergic effect with laminin 521 in P-BdECM. Annexin A1(ANXA1) and Peroxiredoxin(PRDX) in P-BdECM stabilized microglial and astrocytic behavior under normal while promoting active neuroinflammation in response to neuropathological factors. Further, supplementation of the brain-specific molecule to non-neural matrix also ameliorated glial cell inflammation as in P-BdECM. In conclusion, P-BdECM-augmentation strategy can be used to recapitulate humanized pathophysiological cerebral environments for neurological study.

Dislocation after Revision Total Hip Arthroplasty: A Comparison between Dual Mobility and Conventional Total Hip Arthroplasty.

Purpose: The objective of this study was to analyze the results from a cohort of patients who underwent a revision total hip arthroplasty (THA) using a dual mobility cup (DMC) implant. Materials and Methods: A retrospective review of revised THAs was conducted using the database from a single tertiary referral hospital. A total of 91 revision THAs from 91 patients were included in the study. There were 46 male hips and 45 female hips. The mean age was 56.3±14.6 years, and the mean follow-up period was 6.4±5.9 years. In performance of revision THAs, the DMC implants were used in 18 hips (19.8%), and the conventional implants were used in 73 hips (80.2%). Results: During the follow-up period, three dislocations were identified, and the overall dislocation rate was 3.3%. Early dislocation (at one month postoperatively) occurred in one patient, while late dislocation (at a mean of 7.5 years) occurred in two patients. There was no occurrence of dislocation in the DMC group (0%), and three dislocations were detected in the conventional group (4.1%). However, no significant difference in the rate of dislocation was observed between the two groups (P=0.891). Conclusion: Although the rate of dislocation was higher in the conventional group, there were no statistically significant differences between the two groups due to the small number of patients. Nevertheless, we believe that the dual mobility design is advantageous in terms of reducing dislocation rate and can be recommended as an option for a revision THA.