Bronchiolar adenoma (BA) is a rare type of lung tumor characterized by bilayered epithelial cells having a continuous basal layer and a luminal layer. It resembles mucinous adenocarcinoma (MA) on frozen section, with difficulty in distinguishing the basal layer. Immunohistochemistry is the best choice for verifying the diagnosis. This study aimed to comprehensively characterize three cases of BA-combined carcinoma using clinical, histopathological, and genetic features. BA and carcinoma sections were subjected to next-generation sequencing, respectively. It was hypothesized that while different mutation forms matched different regions, BA and lung adenocarcinoma shared the same gene mutation when they co-occurred in the same location. BA with extensive carcinoma is extremely rare and presents diagnostic challenges due to its overlap with conditions such as MA. Because of its distinctive morphological characteristics, BA may be regarded as a low-grade malignancy, particularly during a confusing evaluation. A multifaceted examination of clinical, radiological, immunohistochemical, and genetic data is necessary for an accurate diagnosis.

To analyze the clinical and genetic features of oculopharyngodistal myopathy (OPDM) patients and compare the phenotypic differences among various causative genes.

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.

Mitochondria, the primary energy-producing organelles of the cell, also serve as signaling hubs and participate in diverse physiological and pathological processes, including apoptosis, inflammation, oxidative stress, neurodegeneration, and tumorigenesis. As semi-autonomous organelles, mitochondrial functionality relies on nuclear support, with mitochondrial biogenesis and homeostasis being stringently regulated by the nuclear genome. This interdependency forms a bidirectional signaling network that coordinates cellular energy metabolism, gene expression, and functional states. During mitochondrial damage or dysfunction, retrograde signals are transmitted to the nucleus, activating adaptive transcriptional programs that modulate nuclear transcription factors, reshape nuclear gene expression, and reprogram cellular metabolism. This mitochondrion-to-nucleus communication, termed “mitochondrial retrograde signaling”, fundamentally represents a mitochondrial “request” to the nucleus to maintain organellar health, rooted in the semi-autonomous nature of mitochondria. Despite possessing their own genome, the “fragmented” mitochondrial genome necessitates reliance on nuclear regulation. This genomic incompleteness enables mitochondria to sense and respond to cellular and environmental stressors, generating signals that modulate the functions of other organelles, including the nucleus. Evolutionary transfer of mitochondrial genes to the nuclear genome has established mitochondrial control over nuclear activities via retrograde communication. When mitochondrial dysfunction or environmental stress compromises cellular demands, mitochondria issue retrograde signals to solicit nuclear support. Studies demonstrate that mitochondrial retrograde signaling pathways operate in pathological contexts such as oxidative stress, electron transport chain (ETC) impairment, apoptosis, autophagy, vascular tension, and inflammatory responses. Mitochondria-related diseases exhibit marked heterogeneity but invariably result in energy deficits, preferentially affecting high-energy-demand tissues like muscles and the nervous system. Consequently, mitochondrial dysfunction underlies myopathies, neurodegenerative disorders, metabolic diseases, and malignancies. Dysregulated retrograde signaling triggers proliferative and metabolic reprogramming, driving pathological cascades. Mitochondrial retrograde signaling critically influences tumorigenesis and progression. Tumor cells with mitochondrial dysfunction exhibit compensatory upregulation of mitochondrial biogenesis, excessive superoxide production, and ETC overload, collectively promoting metastatic tumor development. Recent studies reveal that mitochondrial retrograde signaling—mediated by altered metabolite levels or stress signals—induces epigenetic modifications and is intricately linked to tumor initiation, malignant progression, and therapeutic resistance. For instance, mitochondrial dysfunction promotes oncogenesis through mechanisms such as epigenetic dysregulation, accumulation of mitochondrial metabolic intermediates, and mitochondrial DNA (mtDNA) release, which activates the cytosolic cGAS-STING signaling pathway. In normal cells, miR-663 mediates mitochondrion-to-nucleus retrograde signaling under reactive oxygen species (ROS) regulation. Mitochondria modulate miR-663 promoter methylation, which governs the expression and supercomplex stability of nuclear-encoded oxidative phosphorylation (OXPHOS) subunits and assembly factors. However, dysfunctional mitochondria induce oxidative stress, elevate methyltransferase activity, and cause miR-663 promoter hypermethylation, suppressing miR-663 expression. Mitochondrial dysfunction also triggers retrograde signaling in primary mitochondrial diseases and contributes to neurodegenerative disorders such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). Current therapeutic strategies targeting mitochondria in neurological diseases focus on 5 main approaches: alleviating oxidative stress, inhibiting mitochondrial fission, enhancing mitochondrial biogenesis, mitochondrial protection, and insulin sensitization. In AD patients, mitochondrial morphological abnormalities and enzymatic defects, such as reduced pyruvate dehydrogenase and α-ketoglutarate dehydrogenase activity, are observed. Platelets and brains of AD patients exhibit diminished cytochrome c oxidase (COX) activity, correlating with mitochondrial dysfunction. To model AD-associated mitochondrial pathology, researchers employ cybrid technology, transferring mtDNA from AD patients into enucleated cells. These cybrids recapitulate AD-related mitochondrial phenotypes, including reduced COX activity, elevated ROS production, oxidative stress markers, disrupted calcium homeostasis, activated stress signaling pathways, diminished mitochondrial membrane potential, apoptotic pathway activation, and increased Aβ42 levels. Furthermore, studies indicate that Aβ aggregates in AD and α‑synuclein aggregates in PD trigger mtDNA release from damaged microglial mitochondria, activating the cGAS-STING pathway. This induces a reactive microglial transcriptional state, exacerbating neurodegeneration and cognitive decline. Targeting the cGAS-STING pathway may yield novel therapeutics for neurodegenerative diseases like AD, though translation from bench to bedside remains challenging. Such research not only deepens our understanding of disease mechanisms but also informs future therapeutic strategies. Investigating the triggers, core molecular pathways, and regulatory networks of mitochondrial retrograde signaling advances our comprehension of intracellular communication and unveils novel pathogenic mechanisms underlying malignancies, neurodegenerative diseases, and type 2 diabetes mellitus. This review summarizes established mitochondrial-nuclear retrograde signaling axes, their roles in interorganellar crosstalk, and pathological consequences of dysregulated communication. Targeted modulation of key molecules and proteins within these signaling networks may provide innovative therapeutic avenues for these diseases.

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

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.

Gastric contrast-enhanced ultrasound is a non-invasive imaging method that uses oral gastrointestinal ultrasound contrast agents to fill the stomach cavity and display the structure and lesions of the stomach wall.In recent years,the development of contrast agents and the technological innovations of ultrasound equipment have boosted the unique advantages of this examination technique in the diagnosis of gastrointestinal diseases.Gastric contrast-enhanced ultrasound is becoming an important complementary examination means to gastroscopy and X-ray barium meal examination.In this paper,we summarize the clinical applications of gastric contrast-enhanced ultrasound at home and abroad in recent years and systematically analyze its clinical application value and limitations in six aspects:screening and staging of gastric cancer,differentiation and diagnosis of gastric tumors,diagnosis and follow-up of gastritis and gastric ulcers,assessment of gastric contents and gastric volume,evaluation of gastric emptying and gastric motility,and other special applications.
Humans ; Contrast Media ; Ultrasonography/methods* ; Stomach/diagnostic imaging* ; Stomach Neoplasms/diagnostic imaging*