Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Radiation-induced lung injury is a prevalent side effect of radiotherapy for chest cancer. The "three phases and three methods "is an innovative theory based on the evolution of the core pathogenesis of radiation-induced lung injury. Its formation also considers the understanding of radiation-induced lung injury by ancient and modern medical practitioners, pathological characteristics, clinical manifestations, and the development patterns of radiation-induced lung injury. The "three phases and three methods" refers to the three phases of the course and the three treatment methods. The core pathogenesis of radiation-induced lung injury from the beginning, middle and late stages is heat toxicity, yin deficiency, and blood stasis. Therefore, the course of radiation-induced lung injury is divided into three phases: blazing heat toxin, yin deficiency and heat accumulation, and static blood obstruction. The method of clearing the lung and resolving toxins, enriching yin and venting heat, invigorating blood and dissolving stasis are used respectively. Traditional Chinese medicines commonly used in each phase include Flos Lonicerae, Atrina Glass, heartleaf houttuynia herb, Radix Ophiopogonis, American Ginseng, Forsythiae Fructus, Radix Salviae Miltiorrhizae, Rhizoma Ligustici chuanxiong, Scorpio, etc. This article presents the theoretical origins of the "three phases and three methods" concept by reviewing of ancient literature, inheriting experience, and summarizing disease pathogenesis, as well as elaborating on the academic connotations of the "three phases and three methods". The scientific validity of the "three phases and three methods" is verified by literature, clinical, and basic research. The "three phases and three methods" interprets the core characteristics of each stage of radiation-induced lung injury, improves the traditional Chinese medicine prevention and treatment system for radiation-induced lung injury, and provides theoretical basis for achieving complete process management.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

This case report explores the therapeutic potential of theta burst stimulation (TBS) for cognitive enhancement in individuals with brain injuries. The study presents a 38-year-old male suffering from an organic mental disorder attributed to a traumatic brain injury (TBI), who demonstrated notable cognitive improvements following an intensive TBS protocol targeting the left dorsal lateral prefrontal cortex. The treatment led to significant enhancements in impulse control, irritability, and verbal comprehension without adverse effects. Neuropsychological assessments and brain imaging post-intervention revealed improvements in short-term memory, abstract reasoning, list-generating fluency, and increased cerebral blood flow in the prefrontal cortex. These findings suggest that TBS, by promoting neural plasticity and reconfiguring neural networks, offers a promising avenue for cognitive rehabilitation in TBI patients. Further research is warranted to optimize TBS protocols and understand the mechanisms underlying its cognitive benefits.

Objective To systematically evaluate the effects of total intravenous anesthesia and inhalational anesthesia on postoperative recovery in patients undergoing transsphenoidal pituitary tumor resection.Methods A comprehensive search was conducted in international biomedical databases including Ovid Medline,Embase,CINAHL(EBSCO),Cochrane Library,and Web of Science,from inception to July 4,2023.Additionally,ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform were searched for ongoing and completed trials.The randomized controlled trials(RCT)comparing total intravenous anesthesia and inhalational anesthesia in patients undergoing transsphenoidal surgery for pituitary tumors were included.The methodological quality of the included studies was evaluated by the Cochrane Collaboration tool.Relevant data were extracted and synthesized for analysis.Results A total of 327 records were identified,of which eight RCTs met the inclusion criteria.Four studies showed that the patients receiving desflurane or sevoflurane anesthesia experienced faster emergence from anesthesia than those receiving propofol.Two studies indicated that patients in the propofol group had lower levels of emergence agitation and a lower incidence of early postoperative nausea and vomiting.The results on postoperative cognitive function were inconsistent across studies.No differences were found between the groups in terms of postoperative complications or overall recovery quality during hospitalization.Conclusions Inhalational anesthesia appears to provide an advantage in promoting faster emergence following transsphenoidal pituitary surgery,whereas total intravenous anesthesia may contribute to smoother and more stable recovery.Further high-quality studies are needed to clarify the effects of different anesthetic techniques on both short- and long-term postoperative recovery.
Humans ; Anesthesia, Intravenous ; Pituitary Neoplasms/surgery* ; Anesthesia, Inhalation ; Randomized Controlled Trials as Topic ; Anesthesia Recovery Period ; Pituitary Gland/surgery* ; Postoperative Period

Phosgene is a highly reactive chemical substance and a prevalent chemical warfare agent,and it is vitally important for rapid and accurate detection of phosgene to counteract terrorist threats and industrial accidents.In this work,a phosgene probe,designated as SX-Pho,which incorporated benzimidazole and hydroxyl groups as recognition motifs,was prepared through Suzuki coupling and Debus-Radziszewski methodologies to incorporate an electron-donating carbazole moiety.This probe exhibited a large Stokes shift(Approximately 130 nm).Upon exposure to triphosgene/triethylamine conditions(in situ phosgene generation),the fluorescence emission of probe at 470 nm underwent significant quenching,with a 20-fold reduction in intensity,while the fluorescence lifetime decreased from 3.30 ns to 3.06 ns.Concentration titration experiments demonstrated that SX-Pho achieved a lower detection limit of 57.8 nmol/L with high specificity and interference resistance.Preton nuclear magnetic resonance spectroscopy(1H NMR),high-resolution mass spectrometry,and density functional theory(DFT)calculations confirmed the cyclization reaction between hydroxyl groups,imines,and phosgene.The extent of overlap between the highest occupied molecular orbital(HOMO)and the lowest unoccupied molecular orbital(LUMO)was notably decreased,leading to the suppression of radiative transitions.The energy gap underwent a reduction of 0.43 eV,while the non-radiative transition was augmented,resulting in fluorescence quenching and achieving rapid detection of phosgene.Based on this,probe-loaded test strips were prepared.The color change under 365 nm illumination allowed visual discrimination of phosgene at concentrations below 20 μL/L.Furthermore,using a smartphone's built-in RGB application to measure the intensity of the blue(B)channel after the test strips were exposed to phosgene enabled both qualitative and quantitative detection.The detection range was 1.82-50 μL/L,with a limit of detection(LOD)of 1.814 μL/L.