Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To investigate the role of pulmonary neuroendocrine cells(PNEC)and γ-aminobutyric acid(GABA)in patients with pulmonary neuroendocrine tumors(PNET).Methods The pathological specimens of 29 cases of PNET treated in the eighth Medical Center of Chinese PLA General Hospital from October 2018 to January 2022 were collected.The morphological characteristics were observed by HE staining,and the expression levels of synaptophysin(Syn),chromogranin A(CgA),CD56,Ki-67,CD86 and CD163 were observed by immunohistochemical staining.Calcitonin gene-related peptide(CGRP)and glutamic acid decarboxylase(GAD)65/67 in different types of PNETs were detected by double antibody immunofluorescence co-staining,and the correlation between GAD65/67 positive PNEC and macrophage polarization was analyzed.Results The results of HE staining showed that all four types of PNET tissues had neuroendocrine(NE)characteristics:rosette structure and organ nesting or palisade pattern,but they were different,and the proportion of mitotic cells from low to high was typical carcinoid(TC),atypical carcinoid(AC),large cell neuroendocrine carcinoma(LCNEC)and small cell lung cancer(SCLC).The results of immunohistochemical staining showed that the positive expression rate of Syn and CgA and the positive degree of Syn,CgA and CD56 in carcinoid(TC and AC)were significantly higher than those in LCNEC and SCLC(P＜0.05).The Ki-67 indices of the four types of PNET are:TC＜5%,AC 5%-20%,LCNEC and SCLC＞75%respectively.The number of PNEC in carcinoid was significantly higher than that in LCNEC,SCLC and paratumoral tissues(P＜0.05),but there was no significant difference in the number of PNEC between LCNEC and SCLC and para-tumor tissues(P＞0.05).The results of immunofluorescence staining showed that the number of GAD65/67 positive cells co-expressing GAD65/67 in 95%PNEC was significantly higher than that in LCNEC,SCLC and para-tumor tissues(P＜0.05),but there was no significant difference between LCNEC and SCLC GAD65/67 positive cells and para-tumor tissues(P＞0.05).The results of immunohistochemical staining also showed that the number of CD86 positive M1 macrophages was significantly higher than that of CD163 positive M2 macrophages in para-tumor tissues(P＜0.05),while M2 macrophages were significantly more than M1 macrophages in AC,LCNEC and SCLC(P＜0.01).Correlation analysis showed that the number of GAD65/67 positive PNEC cells in PNET was negatively correlated with the number of CD163 positive M2 macrophages in tumor stroma(r=-0.6336,P=0.0174).Conclusions PNEC is the main source of GABA in lung tissue and plays an immunomodulatory role in the lung,which may be involved in the progression of PNET.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

Objective:To explore the effects of RNF113A on the proliferation,migration,in-vasion,apoptosis,and autophagy of hepatocellular carcinoma cells.Methods:Hep3B cells were divided into control group and RNF113A overexpression group(RNF113A-OE),HepG2 was divided into control group and RNF113A knockdown group(si-RNF113A),CCK-8 assay was used to detect changes in cell viability,clone formation assay was used to detect changes in cell proliferation abili-ty,Transwell assay was used to detect changes in cell invasion ability,wound healing assay was used to detect changes in cell migration ability,and flow cytometry was used to detect changes in cell apoptosis ability,Western blot experiments were used to detect changes in protein expression of autophagy related genes and AMPK signaling pathway related genes.Results:Compared with the control group,the proliferation,cloning,invasion,and migration abilities of Hep3B cells in the RNF113A-OE group were improved,while apoptosis and autophagy abilities were decreased,and the AMPK signaling pathway was inhibited;In the si-RNF113A group,the proliferation,cloning,in-vasion,and migration abilities of HepG2 cells were significantly reduced,while apoptosis and au-tophagy abilities were increased,and the activation of the AMPK signaling pathway was promoted.Conclusion:RNF113A promotes the proliferation,cloning,invasion,and migration of hepatocel-lular carcinoma cells,and inhibited apoptosis and autophagy by inhibiting the AMPK signaling path-way.

The breakthrough progress of implantable brain-computer interfaces (iBCIs) technology in the field of clinical trials has attracted widespread attention from both academia and industry. The development and advancement of this technology have provided new solutions for the rehabilitation of patients with movement disorders. However, challenges from many aspects make it difficult for iBCIs to further implement and transform technologies. This paper illustrates the key challenges restricting the large-scale development of iBCIs from the perspective of system implementation, then discusses the latest clinical application progress in depth, aiming to provide new ideas for researchers. For the system implementation part, we have elaborated the front-end signal collector, signal processing and decoder, then the effector. The most important part of the front-end module is the neural electrode, which can be divided into two types: piercing and attached. These two types of electrodes are newly classified and described. In the signal processing and decoder section, we have discussed the experimental paradigm together with signal processing and decoder for the first time and believed that the experimental paradigm acts as a learning benchmark for decoders that play a pivotal role in iBCIs systems. In addition, the characteristics and roles of the effectors commonly used in iBCIs systems, including cursors and robotic arms, are analyzed in detail. In the clinical progress section, we have divided the latest clinical progress into two categories: functional rehabilitation and functional replacement from the perspective of the application scenarios of iBCIs. Functional rehabilitation and functional replacement are two different types of application, though the boundary between the two is not absolute. To this end, we have first introduced the corresponding clinical trial progress from the three levels: application field, research team, and clinical timeline, and then conducted an in-depth discussion and analysis of their functional boundaries, in order to provide guidance for future research. Finally, this paper mentions that the key technical challenges in the development of iBCIs technology come from multiple aspects. First of all, from the signal acquisition level, high-throughput and highly bio-compatible neural interface designing is essential to ensure long-term stable signal acquisition. The electrode surface modification method and electrode packaging were discussed. Secondly, in terms of decoding performance, real-time, accurate, and robust algorithms have a decisive impact on improving the reliability of iBCIs systems. The third key technology is from the perspective of practicality, we believe that the signal transmission mode of wireless communication is the trend of the future, but it still needs to overcome challenges such as data transmission rate and battery life. Finally, we believe that issues such as ethics, privacy, and security need to be addressed through legal, policy, and technological innovation. In summary, the development of iBCIs technology requires not only the unremitting efforts of scientific researchers, but also the participation and support of policymakers, medical professionals, technology developers, and all sectors of society. Through interdisciplinary collaboration and innovation, iBCIs technology will achieve wider clinical applications in the future and make important contributions to improving the quality of life of patients.

italic>Artemisia argyi is a traditional Chinese medicine in China, which is used as medicine with its leaves. The leaves of A. argyi mainly contain flavonoids, phenolic acids, volatile oils and other compounds, and have a variety of pharmacological activities. AP2/ERF transcription factors are abundant in plants and are mainly involved in plant growth and development, abiotic stress response and secondary metabolite biosynthesis regulation. However, there are few reports on the AP2/ERF gene family and its functions in A. argyi. In this study, we systematically identified the AP2/ERF gene family in A. argyi genome, and analyzed its phylogenetic tree, protein physicochemical properties, subcellular localization, conserved motifs, promoter elements, and expression patterns. The results showed that a total of 204 AP2/ERF transcription factors were identified in A. argyi genome, encoding proteins consisting of 88-483 amino acids with a relative molecular mass of 10-52.94 kDa and a theoretical isoelectric point of 4.62-9.88. Subcellular prediction showed that the majority of AP2/ERFs were located in the nucleus, cytoplasm, and the minority of them is located in the membrane and chloroplasts. According to the Arabidopsis AP2/ERF family classification, A. argyi AP2/ERF proteins were divided into four subfamilies: Soloist, AP2, ERF (B3, B4, B5, B6), and DREB (A1, A2, A4, A5, A6), among which DREB family accounted for the largest proportion, and the same subfamily had similar conserved motifs. cis-Acting element analysis showed that AP2/ERF promoters have a large number of elements responding to light and abiotic stress. Expression pattern analysis showed that most of the genes of the AP2/ERF family were dominantly expressed mainly in roots and stems, of which 19 were dominantly expressed in leaves, 77 would be induced to be expressed by methyl jasmonate, of which 16 genes were both dominantly expressed in leaves and induced to be expressed by methyl jasmonate, and these AP2/ERF genes may be the key regulatory genes for the synthesis of active ingredients in A. argyi leaves.This study lays the foundation for the functional study of AP2/ERF family genes and their regulating roles in the active components biosynthesis in A. argyi leaves.