Local incomplete combustion emissions define the PM2.5 oxidative potential in Northern India.

The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

RGD targeted magnetic ferrite nanoparticles enhance antitumor immunotherapeutic efficacy by activating STING signaling pathway.

Manganese has been used in tumor imaging for their ability to provide T1-weighted MRI signal. Recent research find Mn2+ can induce activation of the stimulator of interferon gene (STING) pathway to create an active and favorable tumor immune microenvironment. However, the direct injection of Mn2+ often results in toxicity. In this study, we developed an RGD targeted magnetic ferrite nanoparticle (RGD-MnFe2O4) to facilitate tumor targeted imaging and improve tumor immunotherapy. Magnetic resonance imaging and fluorescence molecular imaging were performed to monitor its in vivo biodistribution. We found that RGD-MnFe2O4 showed active tumor targeting and longer accumulation at tumor sites. Moreover, RGD-MnFe2O4 can activate STING pathway with low toxicity to enhance the PD-L1 expression. Furthermore, combining RGD-MnFe2O4 and anti-PD-L1 antibody (aPD-L1) can treat several types of immunogenic tumors through promoting the accumulation of tumor-infiltrating cytotoxic T cells. In general, our study provides a promising new strategy for the targeted and multifunctional theranostic nanoparticle for the improvement of tumor immunotherapy.

Radiomic signatures associated with tumor immune heterogeneity predict survival in locally recurrent nasopharyngeal carcinoma.

BACKGROUND: The prognostic value of traditional clinical indicators for locally recurrent nasopharyngeal carcinoma (lrNPC) is limited due to their inability to reflect intratumor heterogeneity. We aimed to develop a radiomic signature to reveal tumor immune heterogeneity and predict survival in lrNPC. METHODS: This multicenter, retrospective study included 921 patients with lrNPC. A machine learning signature and nomogram based on pretreatment MRI features were developed for predicting overall survival (OS) in a training cohort and validated in two independent cohorts. A clinical nomogram and an integrated nomogram were constructed for comparison. Nomogram performance was evaluated by concordance index (C-index) and receiver operating characteristic curve analysis. Accordingly, patients were classified into risk groups. The biological characteristics and immune infiltration of the signature were explored by RNA sequencing (RNA-seq) analysis. RESULTS: The machine learning signature and nomogram demonstrated comparable prognostic ability to a clinical nomogram, achieving C-indexes of 0.729, 0.718, and 0.731 in the training, internal, and external validation cohorts, respectively. Integration of the signature and clinical variables significantly improved the predictive performance. The proposed signature effectively distinguished patients between risk groups with significantly distinct OS rates. Subgroup analysis indicated the recommendation of local salvage treatments for low-risk patients. Exploratory RNA-seq analysis revealed differences in interferon response and lymphocyte infiltration between risk groups. CONCLUSIONS: An MRI-based radiomic signature predicted OS more accurately. The proposed signature associated with tumor immune heterogeneity may serve as a valuable tool to facilitate prognostic stratification and guide individualized management for lrNPC patients.

[Components Characteristic and Source Apportionment of Fine Particulate Matter in Transition Period of Heating Season in Xi'an with High Time Resolution].

Influenced by heating, the concentration of atmospheric fine particulate matter (PM2.5) rises in autumn and winter in northern cities. In this study, Q-ACSM, AE33, and Xact 625 were used to carry out online monitoring of PM2.5 chemical components with high time resolution in Xi'an from October 25 to November 17, 2019, to analyze the characteristics of PM2.5 pollution during the transition period of the heating season. Additionally, we analyzed the sources of PM2.5 in combination with the positive matrix factorization model. The results showed that the average PM2.5 concentration during the observation period was (78.3 ± 38.5) µg·m-3, and the main chemical components were organic matter (OA), secondary inorganic ions (SIA), and dust, which accounted for 38.7%, 31.6%, and 21.2%, respectively. The average concentrations of sulfate, nitrate, and ammonium were (4.0 ± 3.1), (14.9 ± 13.7), and (5.8 ± 4.8) µg·m-3, and the average concentrations of the major metals potassium, calcium, and iron were (1.0 ± 0.4), (1.5 ± 1.1), and (1.4 ± 0.9) µg·m-3. Black carbon, chloride ions, and trace elements contributed relatively little to PM2.5 (5.7%, 1.3%, and 1.5%, respectively). In the pollution development and maintenance stage, the concentration of OA and SIA increased by 137.7% to 537.0%, whereas in the pollution dissipation stage, only the concentration of dust gradually increased. The source apportionment results showed that secondary sources, biomass burning, dust, vehicle emission, industrial emission, and coal combustion were the main sources of PM2.5 during the observation period, contributing 29.1%, 21.1%, 15.3%, 12.9%, 11.4%, and 10.2%, respectively. The contribution rate of secondary sources and biomass burning was higher in the pollution development and maintenance stage, and dust was higher in the pollution dissipation stage.

Accurate Concentration Recovery for Quantitative Magnetic Particle Imaging Reconstruction via Nonconvex Regularization.

Magnetic particle imaging (MPI) uses nonlinear response signals to noninvasively detect magnetic nanoparticles in space, and its quantitative properties hold promise for future precise quantitative treatments. In reconstruction, the system matrix based method necessitates suitable regularization terms, such as Tikhonov or non-negative fused lasso (NFL) regularization, to stabilize the solution. While NFL regularization offers clearer edge information than Tikhonov regularization, it carries a biased estimate of the l1 penalty, leading to an underestimation of the reconstructed concentration and adversely affecting the quantitative properties. In this paper, a new nonconvex regularization method including min-max concave (MC) and total variation (TV) regularization is proposed. This method utilized MC penalty to provide nearly unbiased sparse constraints and adds the TV penalty to provide a uniform intensity distribution of images. By combining the alternating direction multiplication method (ADMM) and the two-step parameter selection method, a more accurate quantitative MPI reconstruction was realized. The performance of the proposed method was verified on the simulation data, the Open-MPI dataset, and measured data from a homemade MPI scanner. The results indicate that the proposed method achieves better image quality while maintaining the quantitative properties, thus overcoming the drawback of intensity underestimation by the NFL method while providing edge information. In particular, for the measured data, the proposed method reduced the relative error in the intensity of the reconstruction results from 28% to 8%.

Enhancing surgical outcomes: accurate identification and removal of prostate cancer with B7-H3-targeted NIR-II molecular imaging.

PURPOSE: One of the main reasons for prostate cancer (PCa) recurrence is the difficulty in identifying and removing cancerous lesions during surgery. Accurately localizing and excising cancerous tissue remains a significant challenge. The second near-infrared window (NIR-II, 1000-1700 nm) fluorescence offers enhanced resolution, a high signal-to-noise ratio, and the potential for deeper tissue penetration. However, this technology is not currently employed for intraoperative imaging of PCa. This study aims to construct a new NIR-II probe targeting B7-H3 (AbB7-H3-800CW) for accurate intraoperative identification and resection of PCa. METHODS: Based on the differential expression of B7-H3 in PCa, we designed a novel imaging probe to accurately identify and guide the resection of preclinical PCa models and ex vivo human PCa tissues using NIR-II fluorescence imaging technology. RESULTS: Analyzing tissue samples from 60 clinical cases of PCa, along with benign prostatic hyperplasia and normal prostate tissue from 22 cases, we observed a significant difference in B7-H3 protein expression levels (P < 0.001). Subcutaneous and orthotopic mouse models of PCa were imaged using NIR-II fluorescence after AbB7-H3-800CW injection, showing promising results with successful tumor targeting and high-contrast images achieved within 24-48 h post-injection. The imaging also enabled the detection of occult PCa lesions approximately 1 mm in diameter. In addition, imaging analysis of human PCa and adjacent tissues using AbB7-H3-800CW incubation revealed that cancer tissues exhibited a significantly higher fluorescence intensity than adjacent tissues (P < 0.05), which was conducive to the evaluation of tumor resection margin in vitro. CONCLUSION: The findings revealed that B7-H3 was a compelling imaging target for PCa. The AbB7-H3-800CW molecular imaging probe is capable of accurately identifying PCa lesions and guiding their removal. This approach can potentially reduce the rate of surgical margins under NIR-II fluorescence guidance.

RUVBL1 ubiquitination by DTL promotes RUVBL1/2-ß-catenin-mediated transcriptional regulation of NHEJ pathway and enhances radiation resistance in breast cancer.

Radiotherapy effectiveness in breast cancer is limited by radioresistance. Nevertheless, the mechanisms behind radioresistance are not yet fully understood. RUVBL1 and RUVBL2, referred to as RUVBL1/2, are crucial AAA+ ATPases that act as co-chaperones and are connected to cancer. Our research revealed that RUVBL1, also known as pontin/TIP49, is excessively expressed in MMTV-PyMT mouse models undergoing radiotherapy, which is considered a murine spontaneous breast-tumor model. Our findings suggest that RUVBL1 enhances DNA damage repair and radioresistance in breast cancer cells both in vitro and in vivo. Mechanistically, we discovered that DTL, also known as CDT2 or DCAF2, which is a substrate adapter protein of CRL4, promotes the ubiquitination of RUVBL1 and facilitates its binding to RUVBL2 and transcription cofactor ß-catenin. This interaction, in turn, attenuates its binding to acetyltransferase Tat-interacting protein 60 (TIP60), a comodulator of nuclear receptors. Subsequently, ubiquitinated RUVBL1 promotes the transcriptional regulation of RUVBL1/2-ß-catenin on genes associated with the non-homologous end-joining (NHEJ) repair pathway. This process also attenuates TIP60-mediated H4K16 acetylation and the homologous recombination (HR) repair process. Expanding upon the prior study's discoveries, we exhibited that the ubiquitination of RUVBL1 by DTL advances the interosculation of RUVBL1/2-ß-catenin. And, it then regulates the transcription of NHEJ repair pathway protein. Resulting in an elevated resistance of breast cancer cells to radiation therapy. From the aforementioned, it is evident that targeting DTL-RUVBL1/2-ß-catenin provides a potential radiosensitization approach when treating breast cancer.

Cervical lymph node metastasis prediction from papillary thyroid carcinoma US videos: a prospective multicenter study.

BACKGROUND: Prediction of lymph node metastasis (LNM) is critical for individualized management of papillary thyroid carcinoma (PTC) patients to avoid unnecessary overtreatment as well as undesired under-treatment. Artificial intelligence (AI) trained by thyroid ultrasound (US) may improve prediction performance. METHODS: From September 2017 to December 2018, patients with suspicious PTC from the first medical center of the Chinese PLA general hospital were retrospectively enrolled to pre-train the multi-scale, multi-frame, and dual-direction deep learning (MMD-DL) model. From January 2019 to July 2021, PTC patients from four different centers were prospectively enrolled to fine-tune and independently validate MMD-DL. Its diagnostic performance and auxiliary effect on radiologists were analyzed in terms of receiver operating characteristic (ROC) curves, areas under the ROC curve (AUC), accuracy, sensitivity, and specificity. RESULTS: In total, 488 PTC patients were enrolled in the pre-training cohort, and 218 PTC patients were included for model fine-tuning (n = 109), internal test (n = 39), and external validation (n = 70). Diagnostic performances of MMD-DL achieved AUCs of 0.85 (95% CI: 0.73, 0.97) and 0.81 (95% CI: 0.73, 0.89) in the test and validation cohorts, respectively, and US radiologists significantly improved their average diagnostic accuracy (57% vs. 60%, P = 0.001) and sensitivity (62% vs. 65%, P < 0.001) by using the AI model for assistance. CONCLUSIONS: The AI model using US videos can provide accurate and reproducible prediction of cervical lymph node metastasis in papillary thyroid carcinoma patients preoperatively, and it can be used as an effective assisting tool to improve diagnostic performance of US radiologists. TRIAL REGISTRATION: We registered on the Chinese Clinical Trial Registry website with the number ChiCTR1900025592.

COVID-19-induced acute loss of consciousness in Marchiafava-Bignami disease: a case report.

Among the various manifestations of COVID-19, the neurological implications of SARS-CoV-2 infection are of significant concern. Marchiafava-Bignami disease (MBD), a neurodegenerative disorder, exhibits a clinical spectrum ranging from mild progressive dementia in its chronic form to states of acute coma and varied mortality rates. Acute MBD primarily occurs in chronic alcoholics and malnourished individuals and is characterized by sudden loss of consciousness, seizures, confusion, and psychosis. We herein report a case of MBD presenting as acute loss of consciousness after the development of COVID-19. The patient presented with a history of fever and upper respiratory infection and was diagnosed with SARS-CoV-2 infection. He developed a neurological syndrome characterized by altered consciousness and convulsions, and brain magnetic resonance imaging revealed abnormal signals in the corpus callosum and frontoparietal lobes. Considering his alcohol intake history and the absence of other differential diagnoses, we diagnosed him with acute MBD triggered by COVID-19. After high-dose vitamin B1 and corticosteroid therapy, his clinical symptoms improved. In this case, we observed a temporal sequence between the development of COVID-19 and acute exacerbation of MBD. This case adds to the mounting evidence suggesting the potential effect of SARS-CoV-2 on the neurological system.

Prediction of cross-border spread of the COVID-19 pandemic: A predictive model for imported cases outside China.

The COVID-19 pandemic has been present globally for more than three years, and cross-border transmission has played an important role in its spread. Currently, most predictions of COVID-19 spread are limited to a country (or a region), and models for cross-border transmission risk assessment remain lacking. Information on imported COVID-19 cases reported from March 2020 to June 2022 was collected from the National Health Commission of China, and COVID-19 epidemic data of the countries of origin of the imported cases were collected on data websites such as WHO and Our World in Data. It is proposed to establish a prediction model suitable for the prevention and control of overseas importation of COVID-19. Firstly, the SIR model was used to fit the epidemic infection status of the countries where the cases were exported, and most of the r2 values of the fitted curves obtained were above 0.75, which indicated that the SIR model could well fit different countries and the infection status of the region. After fitting the epidemic infection status data of overseas exporting countries, on this basis, a SIR-multiple linear regression overseas import risk prediction combination model was established, which can predict the risk of overseas case importation, and the established overseas import risk model overall P <0.05, the adjusted R2 = 0.7, indicating that the SIR-multivariate linear regression overseas import risk prediction combination model can obtain better prediction results. Our model effectively estimates the risk of imported cases of COVID-19 from abroad.

Oral arsenic plus imatinib versus imatinib solely for newly diagnosed chronic myeloid leukemia: a randomized phase 3 trial with 5-year outcomes.

PURPOSE: The synergistic effects of combining arsenic compounds with imatinib against chronic myeloid leukemia (CML) have been established using in vitro data. We conducted a clinical trial to compare the efficacy of the arsenic realgar-indigo naturalis formula (RIF) plus imatinib with that of imatinib monotherapy in patients with newly diagnosed chronic phase CML (CP-CML). METHODS: In this multicenter, randomized, double-blind, phase 3 trial, 191 outpatients with newly diagnosed CP-CML were randomly assigned to receive oral RIF plus imatinib (n = 96) or placebo plus imatinib (n = 95). The primary end point was the major molecular response (MMR) at 6 months. Secondary end points include molecular response 4 (MR4), molecular response 4.5 (MR4.5), progression-free survival (PFS), overall survival (OS), and adverse events. RESULTS: The median follow-up duration was 51 months. Due to the COVID-19 pandemic, the recruitment to this study had to be terminated early, on May 28, 2020. The rates of MMR had no significant statistical difference between combination and imatinib arms at 6 months and any other time during the trial. MR4 rates were similar in both arms. However, the 12-month cumulative rates of MR4.5 in the combination and imatinib arms were 20.8% and 10.5%, respectively (p = 0.043). In core treatment since the 2-year analysis, the frequency of MR4.5 was 55.6% in the combination arm and 38.6% in the imatinib arm (p = 0.063). PFS and OS were similar at five years. The safety profiles were similar and serious adverse events were uncommon in both groups. CONCLUSION: The results of imatinib plus RIF as a first-line treatment of CP-CML compared with imatinib might be more effective for achieving a deeper molecular response (Chinadrugtrials number, CTR20170221).

A chest CT-based nomogram for predicting survival in acute myeloid leukemia.

BACKGROUND: The identification of survival predictors is crucial for early intervention to improve outcome in acute myeloid leukemia (AML). This study aim to identify chest computed tomography (CT)-derived features to predict prognosis for acute myeloid leukemia (AML). METHODS: 952 patients with pathologically-confirmed AML were retrospectively enrolled between 2010 and 2020. CT-derived features (including body composition and subcutaneous fat features), were obtained from the initial chest CT images and were used to build models to predict the prognosis. A CT-derived MSF nomogram was constructed using multivariate Cox regression incorporating CT-based features. The performance of the prediction models was assessed with discrimination, calibration, decision curves and improvements. RESULTS: Three CT-derived features, including myosarcopenia, spleen_CTV, and SF_CTV (MSF) were identified as the independent predictors for prognosis in AML (P < 0.01). A CT-MSF nomogram showed a performance with AUCs of 0.717, 0.794, 0.796 and 0.792 for predicting the 1-, 2-, 3-, and 5-year overall survival (OS) probabilities in the validation cohort, which were significantly higher than the ELN risk model. Moreover, a new MSN stratification system (MSF nomogram plus ELN risk model) could stratify patients into new high, intermediate and low risk group. Patients with high MSN risk may benefit from intensive treatment (P = 0.0011). CONCLUSIONS: In summary, the chest CT-MSF nomogram, integrating myosarcopenia, spleen_CTV, and SF_CTV features, could be used to predict prognosis of AML.

On Difference Pattern Synthesis for Spherical Sensor Arrays.

An innovative method for synthesizing optimum difference patterns of the spherical sensor array is introduced, along with a sidelobe tapering technique. Firstly, we suggest employing the spherical harmonics of degree ±1 to synthesize the spherical array difference pattern; secondly, we study the mapping relationship between the difference pattern of the spherical sensor array and the difference pattern of the uniformly spaced linear array (ULA) with odd-numbered elements; finally, we enhance the Zolotarev difference pattern, which is a counterpart to the Dolph-Chebyshev sum pattern that traditionally allows synthesis only for ULA with even-numbered elements. Our modification extends its applicability to synthesize difference patterns for ULA with odd-numbered elements. Leveraging the optimal difference pattern, a generalized Bayliss difference pattern synthesis method designed for the ULA with odd-numbered elements is further proposed. To illustrate the effectiveness of our approach, we present several design examples through experimental simulation.

Peripheral immune cell traits and Parkinson's disease: A Mendelian randomization study.

BACKGROUND: The peripheral immune system is altered in Parkinson's disease (PD), but the causal relationship between the two remains controversial. In this study, we aimed to estimate the causal relationship between peripheral immune features and PD using a two-sample Mendelian randomization (MR) approach. METHODS: Genome-wide association study (GWAS) data of peripheral blood immune signatures from European populations were used for exposure and PD summary statistics were used as results. We conducted a two-sample MR study using the inverse-variance weighted (IVW), MR-Egger, and weighted median methods to evaluate the causal association between these factors. MR-Egger and MR-PRESSO were used for sensitivity analysis to test and correct horizontal pleiotropy. RESULTS: A total of 731 immune traits were analyzed for association with PD using three MR methods. After adjustment for FDR, we observed four peripheral immunological features associated with PD using the IVW method, including expression of CX3CR1 on monocytes [OR: 0.85, 95% CI: (0.81, 0.91), P = 6.56E-07] and CX3CR1 on CD14+CD16+ monocytes [OR: 0.87, 95% CI: (0.82, 0.93), P = 9.95E-06]. CONCLUSIONS: Our study further revealed the important role of monocytes in PD and indicated that CX3CR1 expression on monocytes is associated with a reduced risk of PD.

First magnetic particle imaging to assess pulmonary vascular leakage in vivo in the acutely injured and fibrotic lung.

Increased pulmonary vascular permeability is a characteristic feature of lung injury. However, there are no established methods that allow the three-dimensional visualization and quantification of pulmonary vascular permeability in vivo. Evans blue extravasation test and total protein test of bronchoalveolar lavage fluid (BALF) are permeability assays commonly used in research settings. However, they lack the ability to identify the spatial and temporal heterogeneity of endothelial barrier disruption, which is typical in lung injuries. Magnetic resonance (MR) and near-infrared (NIR) imaging have been proposed to image pulmonary permeability, but suffer from limited sensitivity and penetration depth, respectively. In this study, we report the first use of magnetic particle imaging (MPI) to assess pulmonary vascular leakage noninvasively in vivo in mice. A dextran-coated superparamagnetic iron oxide (SPIO), synomag®, was employed as the imaging tracer, and pulmonary SPIO extravasation was imaged and quantified to evaluate the vascular leakage. Animal models of acute lung injury and pulmonary fibrosis (PF) were used to validate the proposed method. MPI sensitively detected the SPIO extravasation in both acutely injured and fibrotic lungs in vivo, which was confirmed by ex vivo imaging and Prussian blue staining. Moreover, 3D MPI illustrated the spatial heterogeneity of vascular leakage, which correlated well with CT findings. Based on the in vivo 3D MPI images, we defined the SPIO extravasation index (SEI) to quantify the vascular leakage. A significant increase in SEI was observed in the injured lungs, in consistent with the results obtained via ex vivo permeability assays. Overall, our results demonstrate that 3D quantitative MPI serves as a useful tool to examine pulmonary vascular integrity in vivo, which shows promise for future clinical translation.

Macrophage membrane-modified targeted phase-change nanoparticles for multimodal imaging of experimental autoimmune myocarditis.

Myocarditis is an important public health issue due to the high prevalence of sudden death in adolescents and young adults. Nevertheless, the early identification of myocarditis remains a serious problem for clinicians. There is no single non-invasive method to diagnose myocarditis in the currently available clinical guidelines and consensus. Molecular imaging is an effective approach for accurate diagnosis. Poly(lactic acid-glycolic acid) (PLGA) is considered to be the preferred carrier for molecular imaging because of its biosafety and modifiability. Macrophage membrane-modified biomimetic nanoprobes (MM-NPs) possess low immunogenicity and inflammation-directed chemotaxis capabilities and are repeatedly chosen as materials for targeted diagnosis and treatment of inflammatory diseases. In this study, experimental autoimmune myocarditis (EAM) was used as an animal model of inflammation. Previous studies have confirmed that this model is similar to pathological injury caused by acute myocarditis in humans. In multimodal imaging (US/PA/MRI), a phase-change material (PFH) and superparamagnetic iron oxide (SPIO) are used as imaging substances. Early identification of myocardial inflammatory sites was achieved by the tail vein injection of MM/NPs loaded with PFH and SPIO. This probe is expected to be a powerful tool for clinicians to diagnose myocarditis.

Thoracoscopic Intercostal Nerve Block with Cocktail Analgesics for Pain Control After Video-Assisted Thoracoscopic Surgery: A Prospective Cohort Study.

Objective: To evaluate whether using a cocktail of intercostal nerve blocks (TINB) during thoracoscopic surgery results in better clinical outcomes than patient-controlled analgesia (PCIA). Methods: Patients in two medical groups undergoing video-assisted thoracoscopic surgery (VATS) for pulmonary nodules in West China Hospital of Sichuan University were collected consecutively between March 2022 and December 2022. The groups were divided into two subgroups based on their analgesic program, which were TINB group and PCIA group. The primary outcome was the visual analogue scale (VAS) of the two groups at different stage after surgery and after discharge. Any analgesic related adverse events (ARAEs) were also recorded. Results: A total of 230 patients who underwent VATS were enrolled, in which 113 patients (49.1%) received a cocktail TINB after surgery, and 117 patients (50.9%) received a PCIA. After PSM, 62 patients in each group were selected. The difference of resting VAS (RVAS) and active VAS (AVAS) at different stage during hospitalization was only related to the change of period (p < 0.05, p < 0.05), and the two groups showed no significant differences in RVAS or AVAS during hospitalization (p = 0.271, p = 0.915). However, the rates of dizziness (4.84% vs 25.81%, p = 0.002), nausea and vomiting (0 vs 22.58%, p < 0.05), fatigue (14.52% vs 34.87%, p = 0.012), and insomnia (0 vs 58.06%, p < 0.05) in TINB group were lower than that in PCIA group. Besides, AVAS and RVAS at 7, 14, and 30 days after discharge in TINB group were both significantly lower than that in PCIA group (p < 0.05, p < 0.05). Conclusion: Cocktail TINB provided better analgesia after discharge and reduced the incidence of ARAEs in patients undergoing VATS.

A Novel Local Magnetic Fluid Hyperthermia Based on High Gradient Field Guided by Magnetic Particle Imaging.

Magnetic Particle Imaging (MPI)-guided Magnetic Fluid Hyperthermia (MFH) has the potential for widespread utilization, as it allows for the prediction of magnetothermal dosage, real-time visualization of the thermal therapy process, and precise localization of the lesion area. However, the existing MPI-guided MFH (MPI-MFH) method is insensitive to concentration gradients of magnetic nanoparticles (MNPs) and is susceptible to causing damage to normal tissues with high MNP concentrations during MFH treatment, while inadequately heating tumor tissues with lower MNP concentrations. In this work, we established a relationship between MNP concentration and heating efficiency through simulations and phantom measurements, enabling the optimal selection of MFH parameters guided by MPI. Based on these findings, we developed a high-gradient field MPI-MFH method using a fieldfree point (FFP) approach to achieve precise local heating. Phantom experiments and in vivo glioma model experiments were conducted to validate this proposed method. The results demonstrated that the proposed method of MPIMFH can improve the MNP concentration gradient sensitivity to ±1 mg/ml, thereby enabling more effective lesion-site heating without damaging normal tissues. This method not only reduced glioma size effectively but also holds promise for application in various other types of cancers.

Intraoperative Resection Guidance and Rapid Pathological Diagnosis of Osteosarcoma using B7H3 Targeted Probe under NIR-II Fluorescence Imaging.

Complete removal of all tumor tissue with a wide surgical margin is essential for the treatment of osteosarcoma (OS). However, it's difficult, sometimes impossible, to achieve due to the invisible small satellite lesions and blurry tumor boundaries. Besides, intraoperative frozen-section analysis of resection margins of OS is often restricted by the hard tissues around OS, which makes it impossible to know whether a negative margin is achieved. Any unresected small tumor residuals will lead to local recurrence and worse prognosis. Herein, based on the high expression of B7H3 in OS, a targeted probe B7H3-IRDye800CW is synthesized by conjugating anti-B7H3 antibody and IRDye800CW. B7H3-IRDye800CW can accurately label OS areas after intravenous administration, thereby helping surgeons identify and resect residual OS lesions (<2 mm) and lung metastatic lesions. The tumor-background ratio reaches 4.42 ± 1.77 at day 3. After incubating fresh human OS specimen with B7H3-IRDye800CW, it can specifically label the OS area and even the microinvasion area (confirmed by hematoxylin-eosin [HE] staining). The probe labeled area is consistent with the tumor area shown by magnetic resonance imaging and complete HE staining of the specimen. In summary, B7H3-IRDye800CW has translational potential in intraoperative resection guidance and rapid pathological diagnosis of OS.