Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

OBJECTIVE To analyze the potential adverse drug interactions based on pharmacokinetics （PK-pADIs） of gefitinib， and establish its corresponding prescription review rules. METHODS Outpatient prescriptions of gefitinib combination therapy in our hospital from January 1， 2022 to November 30， 2024 were collected through rational drug software system. PK- pADIs present in the prescriptions were identified based on the Drugs.com® drug interactions database. The specific combination drugs and cases of PK-pADIs were statistically analyzed， and prescription review rules were established according to the severity classification of PK-pADIs. RESULTS & CONCLUSIONS A total of 217 prescriptions of gefitinib combination therapy were enrolled. Among them， 28 prescriptions （12.90%）， involving a total of 28 patients， had 29 cases of PK-pADIs， with respiratory medicine prescriptions （22 prescriptions） being the main type. The combination drugs included proton pump inhibitors （13 cases）， strong cytochrome P450 3A4 （CYP3A4） inhibitors （7 cases）， H2 receptor antagonists （4 cases）， CYP3A4 inducers （3 cases）， and CYP2D6 substrates （2 cases）. The severity classifications for these interactions were severe， moderate， severe， moderate and moderate， respectively. Based on the above severity classification of PK-pADIs， four prescription review rules had been established as follows： when gefitinib was combined with acid-suppressing drugs， it should be subject to “manual review”； when gefitinib was combined with dexamethasone， metoprolol， or strong CYP3A4 inhibitors， an “alert” should be triggered， and the physician should be informed via an alert box to strengthen the monitoring of relevant indicators. Clinical pharmacists need to conduct in-depth training on knowledge related to gefitinib drug interactions in key clinical departments such as respiratory medicine. They should strengthen the monitoring and guidance of rational drug use for patients who are on long-term gefitinib therapy， and promptly identify and intervene in PK-pADIs， thereby enhancing the rationality， safety， and effectiveness of clinical drug use.

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

Objective: This study aims to investigate the anatomical relationship among the nerve roots, intervertebral space, pedicles, and intradural rootlets of the cervical spine for improving operative outcomes and exploring neuroventral decompression approach in posterior endoscopic cervical discectomy (PECD). Methods: Cervical computed tomography myelography imaging data from January 2021 to May 2023 were collected, and the RadiAnt DICOM Viewer Software was employed to conduct multiplane reconstruction. The following parameters were recorded: width of nerve root (WN), nerve root-superior pedicle distance (NSPD), nerve root-inferior pedicle distance (NIPD), and the relationship between the intervertebral space and the nerve root (shoulder, anterior, and axillary). Additionally, the descending angles between the spinal cord and the ventral (VRA) and dorsal (DRA) rootlets were measured. Results: The WN showed a gradual increase from C4 to C7, with measurements notably larger in men compared to women. The NSPD decreased gradually from the C2–3 to the C5–6 levels. However, the NIPD showed an opposite level-related change, notably larger than the NSPD at the C4–5, C5–6, and C7–T1 levels. Furthermore, significant differences in NIPD were observed between different age groups and genders. The incidence of the anterior type exhibited a gradual decrease from the C2–3 to the C5–6 levels. Conversely, the axillary type exhibited an opposite level-related change. Additionally, the VRA and DRA decreased as the level descended, with measurements significantly larger in females. Conclusion A prediction of the positional relationship between the intervertebral space and the nerve root is essential for the direct neuroventral decompression in PECD to avoid damaging the neural structures. The axillary route of the nerve root offers a safer and more effective pathway for performing direct neuroventral decompression compared to the shoulder approach.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.