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To ensure reliable lane change behavior in-wheel motor-driven electric vehicles (IWM-EVs) under steer-by-wire (SBW) failure, this paper presents an integrated lateral–longitudinal lane change control strategy based on differential steering. The control framework and relevant models are first established. An upper-layer model predictive control (MPC) controller is then designed to simultaneously achieve lateral path tracking and longitudinal speed regulation, outputting the desired front-wheel steering angle and acceleration. Finally, a model-free adaptive control (MFAC)-based lower-layer lateral controller transforms the desired steering angle into differential driving torques for the front wheels, while a feedforward–feedback lower-layer longitudinal controller (incorporating drive/brake switching and PI control) computes the required driving torque or braking pressure. Co-simulation in Matlab/Simulink R2022b and CarSim R2020 reveals that the MPC controller designed in this study outperforms the LQR-PID controller, reducing the maximum absolute values of lateral error, heading error, front-wheel steering angle, yaw rate and sideslip angle by 42.9%, 50.0%, 7.8%, 2.8% and 10.3%. The proposed hierarchical control strategy outperforms the compared hierarchical controller, reducing the maximum absolute values of the lateral displacement error, heading error and yaw rate by 17.9%, 6.7%, and 33.3%. These results verify that the strategy can improve trajectory tracking accuracy and achieve basic differential steering functionality in specific scenarios.

Objectives: Brucella spondylitis (BS) and tuberculosis spondylitis (TS) are two causes of infection that share overlapping clinical and imaging features, complicating diagnoses. Early differentiation is critical, as treatment regimens differ significantly. This study aims to develop a deep learning framework using multimodal computed tomography (CT) and magnetic resonance imaging (MRI) data to accurately distinguish between these two conditions, improving diagnostic accuracy and patient outcomes. Methods: In this study, imaging data were acquired from two centers using different MRI and CT protocols. Sagittal T1-weighted (T1WI) and T2-weighted imaging (T2WI), fat-suppression sequences (T2WI FSE), and sagittal CT data were collected. Image preprocessing included region of interest (ROI) segmentation, and normalization and augmentation techniques were used. A deep learning model, based on pre-trained GoogleNet architectures, was trained and evaluated against human radiologists using metrics including accuracy, sensitivity, and AUC to assess diagnostic performance. Results: In this study, the GoogleNet deep learning model outperformed other architectures in classifying TS and BS, achieving AUCs of 95.97%, 91.24%, and 81.25% across training, test, and external validation datasets, respectively. In contrast, ResNet, DenseNet, and EfficientNet models showed lower AUC values. GoogleNet also demonstrated high accuracy (90.77% training, 83.04% test) and 90.91% sensitivity and 61.11% specificity in external validation. When compared to three radiologists, GoogleNet outperformed in diagnostic accuracy and speed, achieving an AUC of 88.01% and processing cases in 0.001 min. These findings highlight the potential of AI to enhance diagnostic performance and efficiency. Lastly, the explanation provided by the Grad-Cam model precisely localized major lesions. Conclusions: This multimodal-imaging-based deep learning model could well differentiate TS and BS. Deep learning does not need manual feature extraction, selection, or model development, and has great potential in daily clinical practice.

Phytophthora is a genus of oomycetes that includes many aggressive pathogens capable of devastating farmlands and forests worldwide. Among the oldest and most well‐known species, P. cactorum exhibits morphological and genetic similarities to other homothallic species within subclade 1a, which complicates the understanding of their evolutionary relationships. This study primarily compared seven P. cactorum strains from diverse origins with three closely related species in subclade 1a, utilizing mitogenome sequences for analysis. The circular mitogenomes of the four species were nearly identical in size and comprised 38 protein‐coding genes (PCGs), 25 transfer ribonucleic acid genes, and 2 ribosomal RNA genes. The mitochondrial genomes exhibited a higher percentage of A/T compared to G/C content. The majority of AT‐skew and GC‐skew values among the 38 PCGs were positive, with the AT‐skew demonstrating a more pronounced bias than the GC‐skew. The Ka/Ks ratios revealed that 35 PCGs underwent significant purifying selection. Although the AliGROOVE analysis indicated notable similarities among the subclade 1a species, four PCGs exhibited significantly higher pairing frequency compared to the complete mitogenome. The results from the phylogenetic analysis aligned with the pairwise genetic distances, indicating that P. cactorum is more closely related to P. pseudotsugae than to P. hedraiandra. Furthermore, we found that the nad9 gene is informative to differentiate closely related Phytophthora species within subclade 1a, akin to the cox1 gene. Mitogenomic analysis revealed the evolutionary relationships among Phytophthora 1a subclade species. Novel markers were identified to be sufficiently informative to distinguish between closely related species.

Cyto-nuclear shuttling of β-catenin is at the epicenter of the canonical Wnt pathway and mutations in genes that result in excessive nuclear accumulation of β-catenin are the driving force behind the initiation of many cancers. Recently, Naked Cuticle homolog 1 (Nkd1) has been identified as a Wnt-induced intracellular negative regulator of canonical Wnt signaling. The current model suggests that Nkd1 acts between Disheveled (Dvl) and β-catenin. Here, we employ the zebrafish embryo to characterize the cellular and biochemical role of Nkd1 in vivo. We demonstrate that Nkd1 binds to β-catenin and prevents its nuclear accumulation. We also show that this interaction is conserved in mammalian cultured cells. Further, we demonstrate that Nkd1 function is dependent on its interaction with the cell membrane. Given the conserved nature of Nkd1, our results shed light on the negative feedback regulation of Wnt signaling through the Nkd1-mediated negative control of nuclear accumulation of β-catenin.

[Purpose/Significance] In the era of digital intelligence, robots technology is playing an increasingly important role in the field of education. The applying of AI chatbots in library scenarios is an important lever for the future construction of learning ecosystems in universities. This study aims to explain the influencing factors of users' willingness to continue using library AI chatbots, and provide a new perspective beyond the IT perspective to understand the impact of the basic characteristics of AI chatbots on human behavioral intentions, in order to better understand the sustainability thinking of interpreters and provide some inspiration for the further development of library AI chatbots in the future learning ecosystem. [Method/Process] Based on U&G theory and the SOR framework, we developed a conceptual model of library AI chatbot users's willingness to continue using the chatbot. Data were collected using a questionnaire survey method, with teachers and students as the main respondents. The variables of the AI chatbot user's continuous usage intention model were set to 8, each consisting of 3-6 options, and then measured using a 7-point Likert scale. Finally, the variables and hypotheses in the model were validated using a mixed research method of PLS-SEM and fsQCA. [Results/Conclusions] The research results indicate that three types of satisfaction, hedonic (entertainment and avoidance), social (social presence), and utilitarian (convenience and information consultation), have a significant positive impact on emotional experience (awe experience and emotional participation), with avoidance having the greatest impact on awe experience and social presence having the greatest impact on emotional participation. Emotional experience has a significant positive impact on the intention to continue using, with awe experience having the greatest impact on the intention to continue using. Emotional experience, as a mechanism of action, affects user satisfaction and willingness to use. Based on the data analysis, four suggestions are proposed from the perspective of future learning ecology design and user psychology. When designing library AI chatbots, the usage scenarios should be enriched, and the healing function, immersive experiences and immersive experiences should be emphasized. The limitation of this study is that the use of first-hand cross-sectional data cannot prove whether the influencing mechanism changes over time. In the future, a combination of first-hand and second-hand data can be used to improve the explanatory power. In addition, although this study ensures the validity and reliability of cross-sectional data, there may be geographic and cultural differences in users' behavioral intentions. In the future, a comparative study of the intention to continue using library AI chatbots in different regions and levels can be considered.

Type 1 diabetes is characterized by autoimmune destruction of β cells located in pancreatic islets. However, tractable in vivo models of human pancreatic β cells have been limited. Here, we generated xenogeneic human pancreatic β-like cells in the mouse pancreas by orthotopic transplantation of stem cell-derived β (SC-β) cells into the pancreas of neonatal mice. The engrafted β-like cells expressed β cell transcription factors and markers associated with functional maturity. Engrafted human cells recruited mouse endothelial cells, suggesting functional integration. Human insulin was detected in the blood circulation of transplanted mice for months after transplantation and increased upon glucose stimulation. In addition to β-like cells, human cells expressing markers for other endocrine pancreas cell types, acinar cells, and pancreatic ductal cells were identified in the pancreata of transplanted mice, indicating that this approach allows studying other human pancreatic cell types in the mouse pancreas. Our results demonstrate that orthotopic transplantation of human SC-β cells into neonatal mice is an experimental platform that allows the generation of mice with human pancreatic β-like cells in the endogenous niche.

The epithelial-to-mesenchymal transition (EMT) transcriptional program is characterized by repression of E-cadherin (CDH1) and induction of N-cadherin (CDH2), and mesenchymal genes like vimentin (VIM). Placenta-specific 8 (PLAC8) has been implicated in colon cancer; however, how PLAC8 contributes to disease is unknown, and endogenous PLAC8 protein has not been studied. We analyzed zebrafish and human tissues and found that endogenous PLAC8 localizes to the apical domain of differentiated intestinal epithelium. Colon cancer cells with elevated PLAC8 levels exhibited EMT features, including increased expression of VIM and zinc finger E-box binding homeobox 1 (ZEB1), aberrant cell motility, and increased invasiveness. In contrast to classical EMT, PLAC8 overexpression reduced cell surface CDH1 and upregulated P-cadherin (CDH3) without affecting CDH2 expression. PLAC8-induced EMT was linked to increased phosphorylated ERK2 (p-ERK2), and ERK2 knockdown restored cell surface CDH1 and suppressed CDH3, VIM, and ZEB1 upregulation. In vitro, PLAC8 directly bound and inactivated the ERK2 phosphatase DUSP6, thereby increasing p-ERK2. In a murine xenograft model, knockdown of endogenous PLAC8 in colon cancer cells resulted in smaller tumors, reduced local invasion, and decreased p-ERK2. Using MultiOmyx, a multiplex immunofluorescence-based methodology, we observed coexpression of cytosolic PLAC8, CDH3, and VIM at the leading edge of a human colorectal tumor, supporting a role for PLAC8 in cancer invasion in vivo.

We previously reported that single cells from a human colorectal cancer (CRC) cell line (HCA-7) formed either hollow single-layered polarized cysts or solid spiky masses when plated in 3D in type-I collagen. To begin in-depth analyses into whether clonal cysts and spiky masses possessed divergent properties, individual colonies of each morphology were isolated and expanded. The lines thus derived faithfully retained their parental cystic and spiky morphologies and were termed CC (cystic) and SC (spiky), respectively. Although both CC and SC expressed EGF receptor (EGFR), the EGFR-neutralizing monoclonal antibody, cetuximab, strongly inhibited growth of CC, whereas SC was resistant to growth inhibition, and this was coupled to increased tyrosine phosphorylation of MET and RON. Addition of the dual MET/RON tyrosine kinase inhibitor, crizotinib, restored cetuximab sensitivity in SC. To further characterize these two lines, we performed comprehensive genomic and transcriptomic analysis of CC and SC in 3D. One of the most upregulated genes in CC was the tumor suppressor 15-PGDH/HPGD, and the most up-regulated gene in SC was versican (VCAN) in 3D and xenografts. Analysis of a CRC tissue microarray showed that epithelial, but not stromal, VCAN staining strongly correlated with reduced survival, and combined epithelial VCAN and absent HPGD staining portended a poorer prognosis. Thus, with this 3D system, we have identified a mode of cetuximab resistance and a potential prognostic marker in CRC. As such, this represents a potentially powerful system to identify additional therapeutic strategies and disease-relevant genes in CRC and possibly other solid tumors.

[目的/意义]探究用户持续使用图书馆AI聊天机器人意愿的影响因素，更好地理解用户的持续性思维，并为未来学习生态下图书馆AI聊天机器人的进一步发展带来启示。[方法/过程]基于使用与满足理论和“刺激-机体-反应”框架，建立图书馆AI聊天机器人用户持续使用意愿概念模型。采用问卷调查法收集数据，再结合PLS-SEM和fsQCA混合研究方法对模型中所含变量与假设进行验证。[结果/结论]研究结果表明，享乐性（娱乐和逃避）、社会性（社交存在）和功利性（便利性和信息咨询）3种类型的满足对情感体验（敬畏体验和情感参与）有显著正向影响，其中逃避对敬畏体验影响最大，社交存在对情感参与影响最大；情感体验对持续使用意愿有显著正向影响，其中敬畏体验对持续使用意愿影响最大；情感体验作为作用机制影响了用户满足感和使用意愿。