Orphan drug policy analysis in China.

Rare diseases have various types, low incidence rates, complex conditions, and are often difficult to diagnose. Due to China's large population, there is a significant number of rare disease patients, but there is a shortage of orphan drugs. Consequently, these patients often find themselves in a situation where necessary medications are either unavailable or unaffordable. To address this urgent clinical need, China has implemented a series of orphan drug policies aimed at improving drug accessibility and affordability. In terms of drug accessibility, companies are encouraged to expedite drug development through the implementation of tax incentives, guidance for clinical research on rare diseases, and the provision of data protection periods of 6 years, along with market exclusivity periods limited to a maximum of 7 years. Moreover, exemptions for clinical trials, acceptance of overseas clinical trial data, and the creation of a list prioritizing clinically urgent new drugs from overseas have been introduced to expedite the drug registration application, review, inspection, and approval processes. In terms of drug affordability, the import value-added tax on rare disease drugs has been reduced by 3%, and various provinces and cities have established a representative rare disease protection model, which includes special funds, medical assistance programs, and serious disease insurance. The national medical insurance catalog has been adjusted to reduce the financial burden on rare disease patients, resulting in an increase in the number of orphan drugs covered by the catalog to 95 as of March 2024. By comparing orphan drug policies in the United States, the European Union, Japan, Australia, and other countries (or regions), we will provide relevant suggestions to further improve orphan drug policies in China, thus bringing more treatment options and hope to patients with rare diseases.

Bioelectrochemically altering microbial ecology in upflow anaerobic sludge blanket to enhance methanogenesis fed with high-sulfate methanolic wastewater.

A bioelectrochemical upflow anaerobic sludge blanket (BE-UASB) was constructed and compared with the traditional UASB to investigate the role of bioelectrocatalysis in modulating methanogenesis and sulfidogensis involved within anaerobic treatment of high-sulfate methanolic wastewater (COD/SO42- ratio ≤ 2). Methane production rate for BE-UASB was 1.4 times higher than that of the single UASB, while SO42- removal stabilized at 16.7%. Bioelectrocatalysis selectively enriched key functional anaerobes and stimulated the secretion of extracellular polymeric substances, especially humic acids favoring electron transfer, thereby accelerating the electroactive biofilms development of electrodes. Methanomethylovorans was the dominant genus (35%) to directly convert methanol to CH4. Methanobacterium as CO2 electroreduction methane-producing archaea appeared only on electrodes. Acetobacterium exhibited anode-dependence, which provided acetate for sulfate-reducing bacteria (norank Syntrophobacteraceae and Desulfomicrobium) through synergistic coexistence. This study confirmed that BE-UASB regulated the microbial ecology to achieve efficient removal and energy recovery of high-sulfate methanolic wastewater.

Time-Resolved X-ray Emission Spectroscopy and Resonant Inelastic X-ray Scattering Spectroscopy of Laser Irradiated Carbon.

The existence of liquid carbon as an intermediate phase preceding the formation of novel carbon materials has been a point of contention for several decades. Experimental observation of such a liquid state requires nonthermal melting of solid carbon materials at various laser fluences and pulse properties. Reflectivity experiments performed in the mid-1980s reached opposing conclusions regarding the metallic or insulating properties of the purported liquid state. Time-resolved X-ray absorption studies showed shortening of C-C bonds and increasing diffraction densities, thought to evidence a liquid or glassy carbon state, respectively. Nevertheless, none of these experiments provided information on the electronic structure of the proposed liquid state. Herein, we report the results of time-resolved resonant inelastic X-ray scattering (RIXS) and time-resolved X-ray emission spectroscopy (XES) studies on amorphous carbon (a-C) and ultrananocrystalline diamond (UNCD) as a function of delay time between the irradiating pulse and X-ray probe. For both a-C and UNCD, we attribute decreases in RIXS or XES signals to transition blocking, relaxation, and finally, ablation. Increased signal at 20 ps following the irradiation of the UNCD is attributed to the probable formation of nanoscale structures in the ablation plume. Differences in the amount of signal observed between a-C and UNCD are explained by the difference in sample thickness and, specifically, incomplete melting of the UNCD film. Comparisons to spectral simulations based on MD trajectories at extreme conditions indicate that the carbon state in our experiments is crystalline. Normal mode analysis confirmed that symmetrical bending or stretching of the C-C bonds in the diamond lattice results in XES spectra with small intensity differences. Overall, we observed no evidence of melting to a liquid state, as determined by the lack of changes in the spectral properties for up to 100 ps delays following the melting pulses.

Multicenter evaluation of the safety and efficacy of selective internal radiation therapy with yttrium-90 resin microspheres in Taiwan: data from the RESIN registry.

BACKGROUND AND AIM: The REgistry of Selective Internal radiation therapy in AsiaNs (RESIN) was a multicenter, single-arm, prospective, observational study of 90Y resin microspheres in patients with hepatocellular carcinoma (HCC) or metastatic colorectal cancer (mCRC) from Taiwan. RESIN is the first real-life clinical study of this therapy in an Asian cohort. Study objectives were to evaluate the safety and efficacy of 90Y resin microspheres. METHODS: Adults with HCC or mCRC scheduled to receive SIRT with 90Y resin microspheres were included. Primary endpoints were best overall response rate (ORR), adverse events, and changes from baseline in liver function. Secondary efficacy endpoints included overall survival (OS). RESULTS: Of 107 enrolled patients, 83 had HCC, and 24 had mCRC. ORR was 55.41% (HCC) and 33.33% (mCRC). Of 58 HCC patients with 6-month post-SIRT data, 13.79% (n = 8) had resection, transplantation, transarterial chemoembolization, or radiofrequency ablation as the result of down-staging or down-sizing of their lesions. One hundred and ten treatment emergent adverse events (TEAEs) were reported in 51 patients, and five serious adverse events (SAEs) were reported in five patients. The most frequent TEAEs were abdominal pain, nausea and decreased appetite (HCC), and abdominal pain, decreased appetite, fatigue, and vomiting (mCRC). Two deaths due to SAEs (probably related to SIRT) were reported, both in patients with extensive HCC, active hepatitis infection, and other comorbidities. Median OS was 24.07 (HCC) and 12.66 (mCRC) months. CONCLUSIONS: Safety and efficacy outcomes with the routine use of SIRT with 90Y resin microspheres in Taiwan are consistent with published data.

Development of a modified 3D region proposal network for lung nodule detection in computed tomography scans: a secondary analysis of lung nodule datasets.

BACKGROUND: Low-dose computed tomography (LDCT) has been shown useful in early lung cancer detection. This study aimed to develop a novel deep learning model for detecting pulmonary nodules on chest LDCT images. METHODS: In this secondary analysis, three lung nodule datasets, including Lung Nodule Analysis 2016 (LUNA16), Lung Nodule Received Operation (LNOP), and Lung Nodule in Health Examination (LNHE), were used to train and test deep learning models. The 3D region proposal network (RPN) was modified via a series of pruning experiments for better predictive performance. The performance of each modified deep leaning model was evaluated based on sensitivity and competition performance metric (CPM). Furthermore, the performance of the modified 3D RPN trained on three datasets was evaluated by 10-fold cross validation. Temporal validation was conducted to assess the reliability of the modified 3D RPN for detecting lung nodules. RESULTS: The results of pruning experiments indicated that the modified 3D RPN composed of the Cross Stage Partial Network (CSPNet) approach to Residual Network (ResNet) Xt (CSP-ResNeXt) module, feature pyramid network (FPN), nearest anchor method, and post-processing masking, had the optimal predictive performance with a CPM of 92.2%. The modified 3D RPN trained on the LUNA16 dataset had the highest CPM (90.1%), followed by the LNOP dataset (CPM: 74.1%) and the LNHE dataset (CPM: 70.2%). When the modified 3D RPN trained and tested on the same datasets, the sensitivities were 94.6%, 84.8%, and 79.7% for LUNA16, LNOP, and LNHE, respectively. The temporal validation analysis revealed that the modified 3D RPN tested on LNOP test set achieved a CPM of 71.6% and a sensitivity of 85.7%, and the modified 3D RPN tested on LNHE test set had a CPM of 71.7% and a sensitivity of 83.5%. CONCLUSION: A modified 3D RPN for detecting lung nodules on LDCT scans was designed and validated, which may serve as a computer-aided diagnosis system to facilitate lung nodule detection and lung cancer diagnosis.

A modified 3D RPN for detecting lung nodules on CT images that exhibited greater sensitivity and CPM than did several previously reported CAD detection models was established.

[Research advance on quantitative assessment methods of ecosystem water conservation service functions]. / ç”Ÿæ€ç³»ç»Ÿæ°´æºæ¶µå »æœåŠ¡åŠŸèƒ½å®šé‡è¯„ä¼°æ–¹æ³•ç ”ç©¶è¿›å±•.

The water conservation service function, which is one of the most important ecological service function in the regional system, directly reflects the regulation role of a region in precipitation, the redistribution function of precipitation, and the ecohydrological value. With the development of the comprehensive evaluation method and the deepening of research on water conservation service function, relevant evaluation calculation process has changed significantly. Nowadays, in the assessment of the water conservation service function, it is necessary not only to calculate and evaluate relevant indicators, but also to localize specific parameters in the model and analyze the effectiveness of the overall model for specific study areas. However, the current literature review lacks systematic summaries of model evaluation methods. Meanwhile, the review is also insufficient on model validity verification and significance analysis methods, the result verification and applicability analysis methods such as parameter localization in water conservation studies. We reviewed the research advance on typical ecosystem water conservation ser-vice assessment methods with a specific focus on the model assessment methods that have developed rapidly in recent years. At the same time, we summarized methods commonly used for parameter localization, as well as validity testing and sensitivity analysis of simulation results, and discussed existing problems and future directions in this field.

Simultaneous removal of antibiotic resistance genes and improved dewatering ability of waste activated sludge by Fe(II)-activated persulfate oxidation.

Waste activated sludge properties vary widely with different regions due to the difference in living standards and geographical distribution, making a big challenge to developing a universally effective sludge dewatering technique. The Fe(II)-activated persulfate (S2O82-) oxidation process shows excellent ability to disrupt sludge cells and extracellular polymeric substances (EPS), and release bound water from sludge flocs. In this study, the discrepancies in the physicochemical characteristics of sludge samples from seven representative cities in China (e.g., dewaterability, EPS composition, surface charge, microbial community, relative abundance of antibiotic resistance genes (ARGs), etc.) were investigated, and the role of Fe(II)-S2O82- oxidation in enhancing removal of antibiotic resistance genes and dewatering ability were explored. The results showed significant differences between the EPS distribution and chemical composition of sludge samples due to different treatment processes, effluent sources, and regions. The Fe(II)-S2O82- oxidation pretreatment had a good enhancement of sludge dewatering capacity (up to 76 %). Microbial analysis showed that the microbial community in each sludge varied significantly depending on the types of wastewater, the wastewater treatment processes, and the regions, but Fe(II)-S2O82- oxidation was able to attack and rupture the sludge zoogloea indiscriminately. Genetic analysis further showed that a considerable number of ARGs were detected in all of these sludge samples and that Fe(II)-S2O82- oxidation was effective in removing ARGs by higher than 90 %. The highly active radicals (e.g., SO4-·, ·OH) produced in this process caused drastic damage to sludge microbial cells and DNA stability while liberating the EPS/cell-bound water. Co-occurrence network analysis highlighted a positive correlation between population distribution and ARGs abundance, while variations in microbial communities were linked to regional differences in living standards and level of economic development. Despite these variations, the Fe(II)-S2O82- oxidation consistently achieved excellent performance in both ARGs removal and sludge dewatering. The significant modularity of associations between different microbial communities also confirms its ability to reduce horizontal gene transfer (HGT) by scavenging microbes.

Therapeutic Decision Making in Prevascular Mediastinal Tumors Using CT Radiomics and Clinical Features: Upfront Surgery or Pretreatment Needle Biopsy?

The study aimed to develop machine learning (ML) classification models for differentiating patients who needed direct surgery from patients who needed core needle biopsy among patients with prevascular mediastinal tumor (PMT). Patients with PMT who received a contrast-enhanced computed tomography (CECT) scan and initial management for PMT between January 2010 and December 2020 were included in this retrospective study. Fourteen ML algorithms were used to construct candidate classification models via the voting ensemble approach, based on preoperative clinical data and radiomic features extracted from the CECT. The classification accuracy of clinical diagnosis was 86.1%. The first ensemble learning model was built by randomly choosing seven ML models from a set of fourteen ML models and had a classification accuracy of 88.0% (95% CI = 85.8 to 90.3%). The second ensemble learning model was the combination of five ML models, including NeuralNetFastAI, NeuralNetTorch, RandomForest with Entropy, RandomForest with Gini, and XGBoost, and had a classification accuracy of 90.4% (95% CI = 87.9 to 93.0%), which significantly outperformed clinical diagnosis (p < 0.05). Due to the superior performance, the voting ensemble learning clinical-radiomic classification model may be used as a clinical decision support system to facilitate the selection of the initial management of PMT.

A one-two punch targeting reactive oxygen species and fibril for rescuing Alzheimer's disease.

Toxic amyloid-beta (Aß) plaque and harmful inflammation are two leading symptoms of Alzheimer's disease (AD). However, precise AD therapy is unrealizable due to the lack of dual-targeting therapy function, poor BBB penetration, and low imaging sensitivity. Here, we design a near-infrared-II aggregation-induced emission (AIE) nanotheranostic for precise AD therapy. The anti-quenching emission at 1350 nm accurately monitors the in vivo BBB penetration and specifically binding of nanotheranostic with plaques. Triggered by reactive oxygen species (ROS), two encapsulated therapeutic-type AIE molecules are controllably released to activate a self-enhanced therapy program. One specifically inhibits the Aß fibrils formation, degrades Aß fibrils, and prevents the reaggregation via multi-competitive interactions that are verified by computational analysis, which further alleviates the inflammation. Another effectively scavenges ROS and inflammation to remodel the cerebral redox balance and enhances the therapy effect, together reversing the neurotoxicity and achieving effective behavioral and cognitive improvements in the female AD mice model.

Prediction of surgical outcomes in severe encapsulating peritoneal sclerosis using a computed tomography scoring system.

BACKGROUND/PURPOSE: Encapsulating peritoneal sclerosis (EPS) is a rare and potential lethal complication of peritoneal dialysis characterized by bowel obstruction. Surgical enterolysis is the only curative therapy. Currently, there are no tools for predicting postsurgical prognosis. This study aimed to identify a computed tomography (CT) scoring system that could predict mortality after surgery in patients with severe EPS. METHODS: This retrospective study enrolled patients with severe EPS who underwent surgical enterolysis in a tertiary referral medical center. The association of CT score with surgical outcomes including mortality, blood loss, and bowel perforation was analyzed. RESULTS: Thirty-four patients who underwent 37 procedures were recruited and divided into a survivor and non-survivor group. The survivor group had higher body mass indices (BMIs, 18.1 vs. 16.7 kg/m2, p = 0.035) and lower CT scores (11 vs. 17, p < 0.001) than the non-survivor group. The receiver operating characteristic curve revealed that a CT score of ≥15 could be considered a cutoff point to predict surgical mortality, with an area under the curve of 0.93, sensitivity of 88.9%, and specificity of 82.1%. Compared with the group with CT scores of <15, the group with CT scores of ≥15 had a lower BMI (19.7 vs. 16.2 kg/m2, p = 0.004), higher mortality (4.2% vs. 61.5%, p < 0.001), greater blood loss (50 vs. 400 mL, p = 0.007), and higher incidence of bowel perforation (12.5% vs. 61.5%, p = 0.006). CONCLUSION: The CT scoring system could be useful in predicting surgical risk in patients with severe EPS receiving enterolysis.

Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT.

OBJECTIVES: The study aimed to develop a combined model that integrates deep learning (DL), radiomics, and clinical data to classify lung nodules into benign or malignant categories, and to further classify lung nodules into different pathological subtypes and Lung Imaging Reporting and Data System (Lung-RADS) scores. MATERIALS AND METHODS: The proposed model was trained, validated, and tested using three datasets: one public dataset, the Lung Nodule Analysis 2016 (LUNA16) Grand challenge dataset (n = 1004), and two private datasets, the Lung Nodule Received Operation (LNOP) dataset (n = 1027) and the Lung Nodule in Health Examination (LNHE) dataset (n = 1525). The proposed model used a stacked ensemble model by employing a machine learning (ML) approach with an AutoGluon-Tabular classifier. The input variables were modified 3D convolutional neural network (CNN) features, radiomics features, and clinical features. Three classification tasks were performed: Task 1: Classification of lung nodules into benign or malignant in the LUNA16 dataset; Task 2: Classification of lung nodules into different pathological subtypes; and Task 3: Classification of Lung-RADS score. Classification performance was determined based on accuracy, recall, precision, and F1-score. Ten-fold cross-validation was applied to each task. RESULTS: The proposed model achieved high accuracy in classifying lung nodules into benign or malignant categories in LUNA 16 with an accuracy of 92.8%, as well as in classifying lung nodules into different pathological subtypes with an F1-score of 75.5% and Lung-RADS scores with an F1-score of 80.4%. CONCLUSION: Our proposed model provides an accurate classification of lung nodules based on the benign/malignant, different pathological subtypes, and Lung-RADS system.

Early drainage reduces the length of hospital stay in patients with lung abscess.

Background: Although percutaneous transthoracic catheter drainage (PCD) has been proven effective in lung abscesses, the optimal timing of PCD is still unclear. The study aimed to evaluate the safety and efficacy of early versus delayed drainage in patients with lung abscesses. Methods: This retrospective study included 103 consecutive patients with liquefied lung abscesses more than 3 cm confirmed by a CT scan received CT-guided PCD over 16 years, from July 2005 to September 2021, in a single institution were reviewed. Early drainage was defined as PCD within one week after a lung abscess was diagnosed. The primary outcome was 90-day mortality. The secondary outcomes included perioperative complications and patients' length of hospital stay (LoS). Factors associated with 90-day mortality and LoS were also analyzed. The key statistical methods were Chi-square test, Fisher's exact test, Student t-test, and Pearson correlation. Results: Amount the 103 patients, there were 64 patients who received early PCD, and 39 patients received delayed PCD. Between the two groups, there were no significant differences in clinical characteristics, 90-day mortality, or perioperative complications. The LoS was significantly shortened in early PCD group (28.6 ± 25.5 vs. 39.3 ± 26.8 (days), p = 0.045). Higher Charlson comorbidity index, secondary lung abscess, and liver cirrhosis were associated with higher mortality (all p < 0.05). Positive sputum culture significantly increased the LoS (coefficient 19.35 (10.19, 28.50), p < 0.001). Conclusion: The 90-day mortality and complications were similar for early PCD and delayed PCD patients, but LoS was significantly shortened in early PCD patient.

Dual-Site Förster Resonance Energy Transfer Route of Upconversion Nanoparticles-Based Brain-Targeted Nanotheranostic Boosts the Near-Infrared Phototherapy of Glioma.

Glioblastoma multiforme (GBM) is the most common malignant brain tumor with low survival, primarily due to the blood-brain barrier (BBB) and high infiltration. Upconversion nanoparticles (UCNPs)-based near-infrared (NIR) phototherapy with deep penetration is a promising therapy method against glioma but faces low photoenergy utilization that is induced by spectral mismatch and single-site Förster resonance energy transfer (FRET). Herein, we designed a brain-targeting NIR theranostic system with a dual-site FRET route and superior spectral matching to maximize energy utilization for synergistic photodynamic and photothermal therapy of glioma. The system was fabricated by Tm-doped UCNPs, zinc tetraphenylporphyrin (ZnTPP), and copper sulfide (CuS) nanoparticles under multioptimized modulation. First, the Tm-doping ratio was precisely adjusted to improve the relative emission intensity at 475 nm of UCNPs (11.5-fold). Moreover, the J-aggregate of ZnTPP increased the absorption at 475 nm (163.5-fold) of monomer; both together optimize the FRET matching between UCNPs and porphyrin for effective NIR photodynamic therapy. Simultaneously, the emission at 800 nm was utilized to magnify the photothermal effect of CuS nanoparticles for photothermal therapy via the second FRET route. After being modified by a brain-targeted peptide, the system efficiently triggers the synergistic phototherapy ablation of glioma cells and significantly prolongs the survival of orthotopic glioma-bearing mice after traversing the BBB and targeting glioma. This success of advanced spectral modulation and dual-site FRET strategy may inspire more strategies to maximize the photoenergy utilization of UCNPs for brain diseases.

Multidisciplinary Taiwan consensus for the use of conventional TACE in hepatocellular carcinoma treatment.

Developed in early 1980s, transarterial chemoembolization (TACE) with Lipiodol was adopted globally after large-scale randomized control trials and meta-analyses proving its effectiveness were completed. Also known as "conventional TACE" (cTACE), TACE is currently the first-line treatment for patients with unresectable intermediate stage hepatocellular carcinoma (HCC) and delivers both ischemic and cytotoxic effects to targeted tumors. Although new technology and clinical studies have contributed to a more comprehensive understanding of when and how to apply this widely-adopted therapeutic modality, some of these new findings and techniques have yet to be incorporated into a guideline appropriate for Taiwan. In addition, differences in the underlying liver pathologies and treatment practices for transcatheter embolization between Taiwan and other Asian or Western populations have not been adequately addressed, with significant variations in the cTACE protocols adopted in different parts of the world. These mainly revolve around the amount and type of chemotherapeutic agents used, the type of embolic materials, reliance on Lipiodol, and the degree of selectiveness in catheter positioning. Subsequently, interpreting and comparing results obtained from different centers in a systematic fashion remain difficult, even for experienced practitioners. To address these concerns, we convened a panel of experts specializing in different aspects of HCC treatment to devise modernized recommendations that reflect recent clinical experiences, as well as cTACE protocols which are tailored for use in Taiwan. The conclusions of this expert panel are described herein.

Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

[This corrects the article DOI: 10.3389/fonc.2023.1105100.].

Kinetic Control via Binding Sites within the Confined Space of Metal Metalloporphyrin-Frameworks for Enhanced Shape-Selectivity Catalysis.

One striking feature of enzyme is its controllable ability to trap substrates via synergistic or cooperative binding in the enzymatic pocket, which renders the shape-selectivity of product by the confined spatial environment. The success of shape-selective catalysis relies on the ability of enzyme to tune the thermodynamics and kinetics for chemical reactions. In emulation of enzyme's ability, we showcase herein a targeting strategy with the substrate being anchored on the internal pore wall of metal-organic frameworks (MOFs), taking full advantage of the sterically kinetic control to achieve shape-selectivity for the reactions. For this purpose, a series of binding site-accessible metal metalloporphyrin-frameworks (MMPFs) have been investigated to shed light on the nature of enzyme-mimic catalysis. They exhibit a different density of binding sites that are well arranged into the nanospace with corresponding distances of opposite binding sites. Such a structural specificity results in a facile switch in selectivity from an exclusive formation of the thermodynamically stable product to the kinetic product. Thus, the proposed targeting strategy, based on the combination of porous materials and binding events, paves a new way to develop highly efficient heterogeneous catalysts for shifting selectivity.

Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

Purpose: To compare the diagnostic performance of radiomic analysis with machine learning (ML) model with a convolutional neural network (CNN) in differentiating thymic epithelial tumors (TETs) from other prevascular mediastinal tumors (PMTs). Methods: A retrospective study was performed in patients with PMTs and undergoing surgical resection or biopsy in National Cheng Kung University Hospital, Tainan, Taiwan, E-Da Hospital, Kaohsiung, Taiwan, and Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan between January 2010 and December 2019. Clinical data including age, sex, myasthenia gravis (MG) symptoms and pathologic diagnosis were collected. The datasets were divided into UECT (unenhanced computed tomography) and CECT (enhanced computed tomography) for analysis and modelling. Radiomics model and 3D CNN model were used to differentiate TETs from non-TET PMTs (including cyst, malignant germ cell tumor, lymphoma and teratoma). The macro F1-score and receiver operating characteristic (ROC) analysis were performed to evaluate the prediction models. Result: In the UECT dataset, there were 297 patients with TETs and 79 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 83.95%, ROC-AUC = 0.9117) had better performance than the 3D CNN model (macro F1-score = 75.54%, ROC-AUC = 0.9015). In the CECT dataset, there were 296 patients with TETs and 77 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 85.65%, ROC-AUC = 0.9464) had better performance than the 3D CNN model (macro F1-score = 81.01%, ROC-AUC = 0.9275). Conclusion: Our study revealed that the individualized prediction model integrating clinical information and radiomic features using machine learning demonstrated better predictive performance in the differentiation of TETs from other PMTs at chest CT scan than 3D CNN model.

A Brain-Targeting NIR-II Ferroptosis System: Effective Visualization and Oncotherapy for Orthotopic Glioblastoma.

Near-infrared-II (NIR-II) ferroptosis activators offer promising potentials in in vivo theranostics of deep tumors, such as glioma. However, most cases are nonvisual iron-based systems that are blind for in vivo precise theranostic study. Additionally, the iron species and their associated nonspecific activations might trigger undesired detrimental effects on normal cells. Considering gold (Au) is an essential cofactor for life and it can specifically bind to tumor cells, Au(I)-based NIR-II ferroptosis nanoparticles (TBTP-Au NPs) for brain-targeted orthotopic glioblastoma theranostics are innovatively constructed. It achieves the real-time visual monitoring of both the BBB penetration and the glioblastoma targeting processes. Moreover, it is first validated that the released TBTP-Au specifically activates the effective heme oxygenase-1-regulated ferroptosis of glioma cells to greatly extend the survival time of glioma-bearing mice. This new ferroptosis mechanism based on Au(I) may open a new way for the fabrication of advanced and high-specificity visual anticancer drugs for clinical trials.

Short-Term Effects of Genicular Artery Embolization on Symptoms and Bone Marrow Abnormalities in Patients with Refractory Knee Osteoarthritis.

PURPOSE: To evaluate the short-term outcomes of genicular artery embolization (GAE) for knee osteoarthritis (OA) with and without bone marrow lesion (BML) and/or subchondral insufficiency fracture of the knee (SIFK). MATERIALS AND METHODS: This single-institution prospective observational pilot study analyzed 24 knees in 22 patients with mild to moderate knee OA, including 8 knees without BML, 13 knees with BML, and 3 knees with both BML and SIFK. The area and volume of BMLs on magnetic resonance images were measured before and after GAE. Baseline and postoperative pain and physical function were assessed using the visual analog scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). RESULTS: GAE significantly reduced the BML area and volume 3 months after embolization in the knees with BML (both P < .0005). GAE significantly decreased the VAS scores at 3 and 6 months after embolization in patients without BML (both P = .04) and those with BML (both P = .01). GAE also lowered the WOMAC scores 3 months after embolization in patients without and with BML (P = .02 and P = .0002, respectively). However, GAE did not significantly alter the BML area and volume (both P = .25), VAS scores (P = 1.00), and WOMAC scores (P = .08) in patients with BML and SIFK at 3 months after GAE. CONCLUSIONS: This observational pilot study suggested that GAE effectively reduces the BML area and volume and improves pain and physical function in patients with knee OA accompanied by BML but is inefficacious in those with both BML and SIFK.

Improving puncture accuracy in percutaneous CT-guided needle insertion with wireless inertial measurement unit: a phantom study.

OBJECTIVES: A novel method applying inertial measurement units (IMUs) was developed to assist CT-guided puncture, which enables real-time displays of planned and actual needle trajectories. The method was compared with freehand and laser protractor-assisted methods. METHODS: The phantom study was performed by three operators with 8, 2, and 0 years of experience in CT-guided procedure conducted five consecutive needle placements for three target groups using three methods (freehand, laser protractor-assisted, or IMU-assisted method). The endpoints included mediolateral angle error and caudocranial angle error of the first pass, the procedure time, the total number of needle passes, and the radiation dose. RESULTS: There was a significant difference in the number of needle passes (IMU 1.2 ± 0.42, laser protractor 2.9 ± 1.6, freehand 3.6 ± 2.0 time, p < 0.001), the procedure time (IMU 3.0 ± 1.2, laser protractor 6.4 ± 2.9, freehand 6.2 ± 3.1 min, p < 0.001), the mediolateral angle error of the first pass (IMU 1.4 ± 1.2, laser protractor 1.6 ± 1.3, freehand 3.7 ± 2.5 degree, p < 0.001), the caudocranial angle error of the first pass (IMU 1.2 ± 1.2, laser protractor 5.3 ± 4.7, freehand 3.9 ± 3.1 degree, p < 0.001), and the radiation dose (IMU 250.5 ± 74.1, laser protractor 484.6 ± 260.2, freehand 561.4 ± 339.8 mGy-cm, p < 0.001) among three CT-guided needle insertion methods. CONCLUSION: The wireless IMU improves the angle accuracy and speed of CT-guided needle punctures as compared with laser protractor guidance and freehand techniques. KEY POINTS: • The IMU-assisted method showed a significant decrease in the number of needle passes (IMU 1.2 ± 0.42, laser protractor 2.9 ± 1.6, freehand 3.6 ± 2.0 time, p < 0.001). • The IMU-assisted method showed a significant decrease in the procedure time (IMU 3.0 ± 1.2, laser protractor 6.4 ± 2.9, freehand 6.2 ± 3.1 min, p < 0.001). • The IMU-assisted method showed a significant decrease in the mediolateral angle error of the first pass and the caudocranial angle error of the first pass.