Citations

Abstract Background Accurate synthesis of computed tomography (CT) images from magnetic resonance imaging (MRI) is clinically valuable for cranial applications such as attenuation correction, radiotherapy planning, and image‐guided interventions. However, the heterogeneity of MRI data across magnetic field strengths and pulse sequences limits the generalizability of existing methods, posing a barrier to clinical translation. Purpose This study aims to reformulate cranial CT synthesis as a modular, structurally coupled problem using a deep learning approach, enhancing adaptability across heterogeneous MRI conditions, including different field strengths and sequence protocols. Methods We implemented a cascaded multitask pipeline that jointly models skull segmentation and Hounsfield Unit (HU) regression in anatomically targeted regions. A 3D patch‐based training paradigm shifts the modeling focus from global image translation to localized bone feature extraction. The backbone leverages a residual Mamba‐based state space model within a 3D U‐Net structure to improve spatial representation, while a Transformer U‐Net serves as a widely recognized reference baseline comparison. The model was trained and evaluated in terms of multi‐modal (T1‐weighted and T2‐FLAIR) and cross‐domain transferability from a public 1.5 Tesla brain dataset ( n = 37) to an independent 7 Tesla clinical brain dataset ( n = 44). Performance was assessed using Dice and Jaccard indices for segmentation accuracy and mean absolute error (MAE) for HU regression. Results Quantitative analysis showed that our multitask pipeline, incorporating both morphological and HU map prediction stages, significantly outperformed conventional direct MRI‐to‐CT mapping across all metrics on the public 1.5T dataset (p < 0.05). Consistent performance on an external 7T clinical dataset (p < 0.001) further demonstrated the method's robustness and adaptability across field strengths. Conclusion These findings support that task‐structured training for modality transformation markedly improves both accuracy and generalizability of cranial CT synthesis across heterogeneous MRI conditions. The observed consistency across field strengths validates the robustness of the proposed methodology.

Multiplexed single-cell analysis of proteins in their native cellular contexts holds great promise to reveal the composition, interaction and function of the distinct cell types in complex biological systems. However, the existing multiplexed protein imaging technologies are limited by their detection sensitivity or technical demands. To address these issues, here, we develop an ultrasensitive and multiplexed in situ protein profiling approach by reiterative staining with off-the-shelf antibodies and cleavable fluorescent tyramide (CFT). In each cycle of this approach, the protein targets are recognized by antibodies labeled with horseradish peroxidase, which catalyze the covalent deposition of CFT on or close to the protein targets. After imaging, the fluorophores are chemically cleaved, and the antibodies are stripped. Through continuous cycles of staining, imaging, fluorophore cleavage and antibody stripping, a large number of proteins can be quantified in individual cells in situ. Applying this method, we analyzed 20 different proteins in each of ~67,000 cells in a human formalin-fixed paraffin-embedded (FFPE) tonsil tissue. Based on their unique protein expression profiles and microenvironment, these individual cells are partitioned into different cell clusters. We also explored the cell–cell interactions in the tissue by examining which specific cell clusters are selectively associating or avoiding each other.

Intra-acinar trypsinogen activation occurs in the earliest stages of pancreatitis and is believed to play important roles in pancreatitis pathogenesis. However, the exact role of intra-acinar trypsin activity in pancreatitis remains elusive. Here, we aimed to examine the specific effects of intra-acinar trypsin activity on the development of pancreatitis using a transgenic mouse model. This transgenic mouse model allowed for the conditional expression of a mutant trypsinogen that can be activated specifically inside pancreatic acinar cells. We found that expression of this active mutated trypsin had no significant effect on triggering spontaneous pancreatitis. Instead, several protective compensatory mechanisms, including SPINK1 and heat shock proteins, were upregulated. Notably, these transgenic mice developed much more severe acute pancreatitis, compared with control mice, when challenged with caerulein. Elevated tissue edema, serum amylase, inflammatory cell infiltration and acinar cell apoptosis were dramatically associated with increased trypsin activity. Furthermore, chronic pathological changes were observed in the pancreas of all transgenic mice, including inflammatory cell infiltration, parenchymal atrophy and cell loss, fibrosis, and fatty replacement. These changes were not observed in control mice treated with caerulein. The alterations in pancreata from transgenic mice mimicked the histological changes common to human chronic pancreatitis. Taken together, we provided in vivo evidence that increased intra-acinar activation of trypsinogen plays an important role in the initiation and progression of both acute and chronic pancreatitis. NEW & NOTEWORTHY Trypsinogen is activated early in pancreatitis. However, the roles of trypsin in the development of pancreatitis have not been fully addressed. Using a genetic approach, we showed trypsin activity is critical for the severity of both acute and chronic pancreatitis.