A gold cluster fused manganese dioxide nanocube loaded with dihydroartemisinin for effective cancer treatment via amplified oxidative stress.

Chemodynamic therapy, leveraging metabolic processes for reactive oxygen species (ROS) generation, shows promise in cancer eradication. However, its efficacy is hampered by hypoxic conditions, substrate scarcity, and abundant ROS scavengers. In this study, we have devised a cubic manganese oxide nanozyme (BSA-AuNC-MnO2@DHA) to tackle these obstacles. This nanozyme integrates MnO2 with bovine serum albumin (BSA)-coated gold nanoclusters (AuNC), forming BSA-AuNC-MnO2, and further incorporates dihydroartemisinin (DHA) to confer both bioimaging and anticancer capabilities. The BSA-AuNC-MnO2 nanoparticles exhibit a uniform cubic morphology, with an average hydrated particle diameter of 76.4 ± 7.1 nm and a zeta potential of -32.6 mV, indicative of their excellent dispersion and stability. The encapsulation efficiency of DHA within the BSA-AuNC-MnO2@DHA system achieved a remarkable value of 72.45%, attesting to its substantial drug-loading capacity. MnO2 serves a dual function within the nanozyme: it augments oxidative stress while concurrently inhibiting antioxidant defenses. It depletes the antioxidant glutathione (GSH) to release Mn2+, which in turn catalyzes ROS production from intracellular substrates and DHA. The remarkable anticancer efficacy of this tailored approach is evidenced by the potent inhibition of tumor growth observed after a single-dose administration, which underscores the amplification of oxidative stress. Additionally, BSA-AuNC-MnO2@DHA exhibits negligible toxicity to major organs, highlighting its exceptional biocompatibility and safety profile.

Exploring approaches to tackle cross-domain challenges in brain medical image segmentation: a systematic review.

Introduction: Brain medical image segmentation is a critical task in medical image processing, playing a significant role in the prediction and diagnosis of diseases such as stroke, Alzheimer's disease, and brain tumors. However, substantial distribution discrepancies among datasets from different sources arise due to the large inter-site discrepancy among different scanners, imaging protocols, and populations. This leads to cross-domain problems in practical applications. In recent years, numerous studies have been conducted to address the cross-domain problem in brain image segmentation. Methods: This review adheres to the standards of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for data processing and analysis. We retrieved relevant papers from PubMed, Web of Science, and IEEE databases from January 2018 to December 2023, extracting information about the medical domain, imaging modalities, methods for addressing cross-domain issues, experimental designs, and datasets from the selected papers. Moreover, we compared the performance of methods in stroke lesion segmentation, white matter segmentation and brain tumor segmentation. Results: A total of 71 studies were included and analyzed in this review. The methods for tackling the cross-domain problem include Transfer Learning, Normalization, Unsupervised Learning, Transformer models, and Convolutional Neural Networks (CNNs). On the ATLAS dataset, domain-adaptive methods showed an overall improvement of ~3 percent in stroke lesion segmentation tasks compared to non-adaptive methods. However, given the diversity of datasets and experimental methodologies in current studies based on the methods for white matter segmentation tasks in MICCAI 2017 and those for brain tumor segmentation tasks in BraTS, it is challenging to intuitively compare the strengths and weaknesses of these methods. Conclusion: Although various techniques have been applied to address the cross-domain problem in brain image segmentation, there is currently a lack of unified dataset collections and experimental standards. For instance, many studies are still based on n-fold cross-validation, while methods directly based on cross-validation across sites or datasets are relatively scarce. Furthermore, due to the diverse types of medical images in the field of brain segmentation, it is not straightforward to make simple and intuitive comparisons of performance. These challenges need to be addressed in future research.

The Child Opportunity Index 2.0 and Disparities in Pediatric Cardiorespiratory Fitness.

OBJECTIVE: To evaluate the effect of neighborhood-level characteristics on cardiorespiratory fitness (CRF) via peak oxygen consumption (VO2peak) for healthy pediatric patients. STUDY DESIGN: The institutional cardiopulmonary exercise testing (CPET) database was analyzed retrospectively. All patients aged ≤ 18 years without a diagnosis of cardiac disease and with a maximal effort CPET were included. Patients were divided into three self-identified racial categories: White, Black, and Latinx. The Child Opportunity Index (COI) 2.0 was used to analyze social determinants of health. CRF was evaluated based on COI quintiles and race. Assessment of the effect of COI on racial disparities in CRF was performed using ANCOVA. RESULTS: A total of 1753 CPETs met inclusion criteria. The mean VO2peak was 42.1 ± 9.8 mL/kg/min. The VO2peak increased from 39.1 ± 9.6 mL/kg/min for patients in the very low opportunity cohort to 43.9 ± 9.4 mL/kg/min for patients in the very high opportunity cohort. White patients had higher percent predicted VO2peak compared with both Black and Latinx patients (P < .01 for both comparisons). The racial differences in CRF were no longer significant when adjusting for COI. CONCLUSION: In a large pediatric cohort, COI was associated with CRF. Racial disparities in CRF are reduced when accounting for modifiable risk factors.

Localised non-metastatic sarcomatoid renal cell carcinoma: a 31-year externally verified study.

OBJECTIVE: To evaluate post-nephrectomy outcomes and predictors of cancer-specific survival (CSS) between patients with localised sarcomatoid renal cell carcinoma (sRCC) and those with Grade 4 RCC (non-sRCC), as most sRCC research focuses on advanced or metastatic disease with limited studies analysing outcomes of patients with localised non-metastatic sRCC. PATIENTS AND METHODS: A total of 564 patients with localised RCC underwent partial or radical nephrectomy between June 1988 to March 2019 for sRCC (n = 204) or World Health Organization/International Society of Urological Pathology Grade 4 non-sRCC (n = 360). The CSS at every stage between groups was assessed. Phase III ASSURE clinical trial data were used to externally validate the CSS findings. The Mann-Whitney U-test and chi-squared test compared outcomes and the Kaplan-Meier method evaluated CSS, overall survival (OS) and recurrence-free survival. Clinicopathological features associated with RCC death were evaluated using Cox proportional hazards regression. RESULTS: The median follow-up was 31.5 months. The median OS and CSS between the sRCC and Grade 4 non-sRCC groups was 45 vs 102 months and 49 vs 152 months, respectively (P < 0.001). At every stage, sRCC had worse CSS compared to Grade 4 non-sRCC. Notably, pT1 sRCC had worse CSS than pT3 Grade 4 non-sRCC. Negative predictors of CSS were sarcomatoid features, non-clear cell histology, positive margins, higher stage (pT3/pT4), and use of minimally invasive surgery (MIS). ASSURE external verification showed worse CSS in patients with sRCC (hazard ratio [HR] 1.63, 95% confidence interval [CI] 1.12-2.36; P = 0.01), but not worse outcomes in MIS surgery (HR 1.39, 95% CI 0.75-2.56; P = 0.30). CONCLUSIONS: Localised sRCC had worse CSS compared to Grade 4 non-sRCC at every stage. Negative survival predictors included positive margins, higher pathological stage, use of MIS, and non-clear cell histology. sRCC is an aggressive variant even at low stages requiring vigilant surveillance and possible inclusion in adjuvant therapy trials.

Machine Learning for Medical Image Translation: A Systematic Review.

BACKGROUND: CT scans are often the first and only form of brain imaging that is performed to inform treatment plans for neurological patients due to its time- and cost-effective nature. However, MR images give a more detailed picture of tissue structure and characteristics and are more likely to pick up abnormalities and lesions. The purpose of this paper is to review studies which use deep learning methods to generate synthetic medical images of modalities such as MRI and CT. METHODS: A literature search was performed in March 2023, and relevant articles were selected and analyzed. The year of publication, dataset size, input modality, synthesized modality, deep learning architecture, motivations, and evaluation methods were analyzed. RESULTS: A total of 103 studies were included in this review, all of which were published since 2017. Of these, 74% of studies investigated MRI to CT synthesis, and the remaining studies investigated CT to MRI, Cross MRI, PET to CT, and MRI to PET. Additionally, 58% of studies were motivated by synthesizing CT scans from MRI to perform MRI-only radiation therapy. Other motivations included synthesizing scans to aid diagnosis and completing datasets by synthesizing missing scans. CONCLUSIONS: Considerably more research has been carried out on MRI to CT synthesis, despite CT to MRI synthesis yielding specific benefits. A limitation on medical image synthesis is that medical datasets, especially paired datasets of different modalities, are lacking in size and availability; it is therefore recommended that a global consortium be developed to obtain and make available more datasets for use. Finally, it is recommended that work be carried out to establish all uses of the synthesis of medical scans in clinical practice and discover which evaluation methods are suitable for assessing the synthesized images for these needs.

Branch-first aortic arch replacement strategy decreases perioperative mortality.

OBJECTIVE: Sparce evidence suggests superiority of total arch replacement with the branch-first technique and antegrade cerebral perfusion over conventional techniques with respect to morbidity and mortality. Thus, we aimed to compare perioperative outcomes of patients undergoing traditional total arch replacement versus branch-first total arch replacement. METHODS: We retrospectively reviewed 144 patients undergoing total arch replacement from January 2017 to December 2021. Patients were dichotomized based on technique, either traditional total arch replacement or branch-first total arch replacement. Primary end points were 30-day mortality and adverse events. Branch-first total arch replacement and traditional total arch replacement cohorts were compared using Student t tests and chi-square tests. Univariable and multivariable logistic regressions were performed to identify risk factors associated with 30-day mortality. RESULTS: A total of 68 patients (47.2%) underwent traditional total arch replacement, and 76 patients (52.8%) underwent branch-first total arch replacement. The branch-first total arch replacement cohort had higher rates of chronic kidney disease, hypertension, atrial fibrillation, and previous myocardial infarction (P = .04, .002, .035, and .031 respectively). The majority of total arch replacements (78, 55%) were performed for aneurysmal disease. Median antegrade cerebral perfusion times were significantly shorter in the branch-first total arch replacement cohort (P = .001). There were no significant differences in rates of stroke, reintubation, postoperative lumbar drainage, renal failure, reoperation for bleeding, or prolonged ventilation between total arch replacement cohorts. The branch-first total arch replacement group had significantly lower 30-day mortality compared with the traditional total arch replacement group (4% vs 19%, P = .004). After adjustment for chronic kidney disease, nonelective status, antegrade cerebral perfusion time, rates of dissections arriving in extremis or with malperfusion, and primary surgeon, undergoing a branch-first total arch replacement was associated with a 93% reduced odds of 30-day mortality (odds ratio, 0.07, 95% CI, 0.009-0.48, P = .007). CONCLUSIONS: We provide evidence that branch-first total arch replacement significantly reduces 30-day mortality compared with traditional total arch replacement.

Detecting localised prostate cancer using radiomic features in PSMA PET and multiparametric MRI for biologically targeted radiation therapy.

BACKGROUND: Prostate-Specific Membrane Antigen (PSMA) PET/CT and multiparametric MRI (mpMRI) are well-established modalities for identifying intra-prostatic lesions (IPLs) in localised prostate cancer. This study aimed to investigate the use of PSMA PET/CT and mpMRI for biologically targeted radiation therapy treatment planning by: (1) analysing the relationship between imaging parameters at a voxel-wise level and (2) assessing the performance of radiomic-based machine learning models to predict tumour location and grade. METHODS: PSMA PET/CT and mpMRI data from 19 prostate cancer patients were co-registered with whole-mount histopathology using an established registration framework. Apparent Diffusion Coefficient (ADC) maps were computed from DWI and semi-quantitative and quantitative parameters from DCE MRI. Voxel-wise correlation analysis was conducted between mpMRI parameters and PET Standardised Uptake Value (SUV) for all tumour voxels. Classification models were built using radiomic and clinical features to predict IPLs at a voxel level and then classified further into high-grade or low-grade voxels. RESULTS: Perfusion parameters from DCE MRI were more highly correlated with PET SUV than ADC or T2w. IPLs were best detected with a Random Forest Classifier using radiomic features from PET and mpMRI rather than either modality alone (sensitivity, specificity and area under the curve of 0.842, 0.804 and 0.890, respectively). The tumour grading model had an overall accuracy ranging from 0.671 to 0.992. CONCLUSIONS: Machine learning classifiers using radiomic features from PSMA PET and mpMRI show promise for predicting IPLs and differentiating between high-grade and low-grade disease, which could be used to inform biologically targeted radiation therapy planning.

Automated quantification of measurable residual disease in chronic lymphocytic leukemia using an artificial intelligence-assisted workflow.

Detection of measurable residual disease (MRD) in chronic lymphocytic leukemia (CLL) is an important prognostic marker. The most common CLL MRD method in current use is multiparameter flow cytometry, but availability is limited by the need for expert manual analysis. Automated analysis has the potential to expand access to CLL MRD testing. We evaluated the performance of an artificial intelligence (AI)-assisted multiparameter flow cytometry (MFC) workflow for CLL MRD. We randomly selected 113 CLL MRD FCS files and divided them into training and validation sets. The training set (n = 41) was gated by expert manual analysis and used to train the AI model. We then compared the validation set (n = 72) MRD results obtained by the AI-assisted analysis versus those by expert manual analysis using the Pearson correlation coefficient and Bland-Altman plot method. In the validation set, the AI-assisted analysis correctly categorized cases as MRD-negative versus MRD-positive in 96% of cases. When comparing the AI-assisted analysis versus the expert manual analysis, the Pearson r was 0.8650, mean bias was 0.2237 log10 units, and the 95% limit of agreement (LOA) was ±1.0282 log10 units. The AI-assisted analysis performed sub-optimally in atypical immunophenotype CLL and in cases lacking residual normal B cells. When excluding these outlier cases, the mean bias improved to 0.0680 log10 units and the 95% LOA to ±0.2926 log10 units. An automated AI-assisted workflow allows for the quantification of MRD in CLL with typical immunophenotype. Further work is required to improve performance in atypical immunophenotype CLL.

Quantification of tumorsphere migration with a physics-based machine learning method.

Current analysis techniques available for migration assays only provide quantitative measurements for overall migration. However, the potential of regional migration analyses can open further insight into migration patterns and more avenues of experimentation with the same assays. Previously, we developed an analysis pipeline utilizing the finite element (FE) method to show its potential in analyzing glioblastoma (GBM) tumorsphere migration, especially in characterizing regional changes in the migration pattern. This study aims to streamline and further automate the analysis system by integrating the machine-learning-based U-Net segmentation with the FE method. Our U-Net-based segmentation achieved a 98% accuracy in segmenting our tumorspheres. From the segmentations, FE models made up of 3D hexahedral elements were generated, and the migration patterns of the tumorspheres were analyzed under treatments B and C (under non-disclosure agreements). Our results show that our overall migration analysis correlated very strongly (R2 of 0.9611 and 0.9986 for treatments B and C, respectively) with ImageJ's method of migration area analysis, which is the most common method of tumorsphere migration analysis. Additionally, we were able to quantitatively represent the regional migration patterns in our FE models, which the methods purely based on segmentations could not do. Moreover, the new pipeline improved the efficiency and accessibility of the initial pipeline by implementing machine learning-based automated segmentation onto a mainly open-sourced FE analysis platform. In conclusion, our algorithm enables the development of a high-content and high-throughput in vitro screening platform to elucidate anti-migratory molecules that may reduce the invasiveness of these malignant tumors.

Gait biomechanics evaluation of the treatment effects for hallux valgus patients: A systematic review and meta-analysis.

BACKGROUND: Hallux valgus (HV) is a foot deformity characterized by lateral deviation of the big toe and medial deviation of the first metatarsal. RESEARCH QUESTION: This study aimed to shed light on the treatment effects of different interventions and surgical procedures for HV deformity to determine the effectiveness of gait biomechanics correction. METHODS: English-language searches of the electronic databases were conducted in the Cochrane Library, Web of Science, PubMed, Scopus, and Embase. Gait biomechanics evaluation before and after conservative or operative treatments was essential for inclusion in this review. Methodological quality was assessed by the Institute of Health Economics (IHE) quality appraisal tool. All pooled analysis was based on the random-effects model. RESULTS: Twenty-five articles (1003 participants) were identified in this review. Three studies chose conservative therapies for HV deformity, incorporating foot orthotics and minimalist running intervention, and surgeries were performed in twenty-two studies. For the pressure parameter alteration under the hallux, the effect size (ES) in the conservative treatment subgroup was - 0.95 with 95%CI [- 1.69, - 0.21]. It demonstrated a moderate ES of - 0.44% and 95%CI [- 0.81, - 0.07] in the surgery subgroup. The five operations' peak pressure alteration under the hallux demonstrated a moderate ES of - 0.45% and 95%CI [- 0.54, - 0.36]. SIGNIFICANCE: Both non-operative and operative treatments could achieve the forefoot pressure redistribution, decreasing loading beneath the hallux and first metatarsal regions，However, the treatment effects of surgeries were not very robust. The percutaneous DSTR-Akin technique is recommended as an adequate operative treatment, with a large ES and moderate heterogeneity. The negative gait return effect should be noticed while using Scarf osteotomy, despite positive clinical and radiographic outcomes.

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results.

Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder translating DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties could enable clinical review of the most uncertain regions, thereby building trust and paving the way toward clinical translation. Several uncertainty estimation methods have recently been introduced for DL medical image segmentation tasks. Developing scores to evaluate and compare the performance of uncertainty measures will assist the end-user in making more informed decisions. In this study, we explore and evaluate a score developed during the BraTS 2019 and BraTS 2020 task on uncertainty quantification (QU-BraTS) and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation. This score (1) rewards uncertainty estimates that produce high confidence in correct assertions and those that assign low confidence levels at incorrect assertions, and (2) penalizes uncertainty measures that lead to a higher percentage of under-confident correct assertions. We further benchmark the segmentation uncertainties generated by 14 independent participating teams of QU-BraTS 2020, all of which also participated in the main BraTS segmentation task. Overall, our findings confirm the importance and complementary value that uncertainty estimates provide to segmentation algorithms, highlighting the need for uncertainty quantification in medical image analyses. Finally, in favor of transparency and reproducibility, our evaluation code is made publicly available at https://github.com/RagMeh11/QU-BraTS.

The use of eculizumab in ventilator-dependent myasthenia gravis patients.

INTRODUCTION/AIMS: Eculizumab has been shown to be efficacious in acetylcholine receptor antibody-positive (AChR+ ) Myasthenia Gravis Foundation of America (MGFA) class II, III, and IV generalized myasthenia gravis (gMG) patients. However, it has not been studied in MGFA class V gMG patients. METHODS: We report three AChR+ , refractory, MGFA class V gMG patients treated with eculizumab. MGFA class, MG-Composite (MGC) score and MG Activities of Daily Living (MG-ADL) score were assessed before and after eculizumab. RESULTS: Two of three gMG patients, refractory to intravenous immunoglobulin, plasmapheresis, prednisone, and (in one case) rituximab, showed a robust response to eculizumab with marked improvement in MGFA, MG-ADL, and MGC measures. The third patient showed a partial response to eculizumab but remained on noninvasive ventilation and gastrostomy intubation. Patients 1 and 2 achieved minimal manifestation status at week 4 and week 6, respectively, and showed continued improvement on MG-ADL and MGC scores through weeks 55 and 43, respectively, with eculizumab. The third patient showed a partial response at week 10, followed by a slight decline in his MG-ADL score, but noted a slow but an incomplete improvement afterward on MG-ADL and MGC scores, possibly due to delayed eculizumab infusion. DISCUSSION: Eculizumab may play a role in the treatment of patients with MGFA class V, refractory gMG. Larger studies are required to provide further evidence.

ARID1A regulates R-loop associated DNA replication stress.

ARID1A is a core DNA-binding subunit of the BAF chromatin remodeling complex, and is lost in up to 7% of all cancers. The frequency of ARID1A loss increases in certain cancer types, such as clear cell ovarian carcinoma where ARID1A protein is lost in about 50% of cases. While the impact of ARID1A loss on the function of the BAF chromatin remodeling complexes is likely to drive oncogenic gene expression programs in specific contexts, ARID1A also binds genome stability regulators such as ATR and TOP2. Here we show that ARID1A loss leads to DNA replication stress associated with R-loops and transcription-replication conflicts in human cells. These effects correlate with altered transcription and replication dynamics in ARID1A knockout cells and to reduced TOP2A binding at R-loop sites. Together this work extends mechanisms of replication stress in ARID1A deficient cells with implications for targeting ARID1A deficient cancers.

Circulating Tumor Cells Exhibit Metastatic Tropism and Reveal Brain Metastasis Drivers.

Hematogenous metastasis is initiated by a subset of circulating tumor cells (CTC) shed from primary or metastatic tumors into the blood circulation. Thus, CTCs provide a unique patient biopsy resource to decipher the cellular subpopulations that initiate metastasis and their molecular properties. However, one crucial question is whether CTCs derived and expanded ex vivo from patients recapitulate human metastatic disease in an animal model. Here, we show that CTC lines established from patients with breast cancer are capable of generating metastases in mice with a pattern recapitulating most major organs from corresponding patients. Genome-wide sequencing analyses of metastatic variants identified semaphorin 4D as a regulator of tumor cell transmigration through the blood-brain barrier and MYC as a crucial regulator for the adaptation of disseminated tumor cells to the activated brain microenvironment. These data provide the direct experimental evidence of the promising role of CTCs as a prognostic factor for site-specific metastasis. SIGNIFICANCE: Interests abound in gaining new knowledge of the physiopathology of brain metastasis. In a direct metastatic tropism analysis, we demonstrated that ex vivo-cultured CTCs from 4 patients with breast cancer showed organotropism, revealing molecular features that allow a subset of CTCs to enter and grow in the brain.This article is highlighted in the In This Issue feature, p. 1.

The predictive role of preoperative and postoperative neutrophil-lymphocyte ratio in sarcomatoid renal cell carcinoma.

OBJECTIVE: Preoperative inflammatory parameters are associated with outcome in renal cell carcinoma; however, their predictive value in tumors with sarcomatoid dedifferentiation (sRCC) is uncertain. We aimed to evaluate the association between preoperative and postoperative inflammatory parameters and the outcome of patients with locoregional and metastatic sRCC who underwent nephrectomy. METHODS AND MATERIALS: After obtaining IRB approval, we identified 230 patients with sRCC treated between 1994 and 2018 with a complete blood count drawn ≤1 month before nephrectomy. Preoperative neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio, and platelet-lymphocyte ratio were evaluated as continuous variables. Postoperative NLR, 1 to 8 weeks after surgery, and percentage change in NLR were calculated. Cox regression models were used to identify predictors of outcome. RESULTS: The study cohort included 105 metastatic patients and 112 patients with locoregional disease. Patients with metastatic disease had significantly higher preoperative NLR (4.31 vs. 3.29) and PLR (248 vs. 194), and lower preoperative LMR (2.6 vs. 3.23). Median follow-up for patients with locoregional and metastatic disease was 36 months and 20 months, respectively, and estimated 5-year cancer-specific survival (CSS) rates were 56% and 15%, respectively. Preoperative NLR was a significant predictor of CSS for both metastatic (HR = 1.23, 95% CI 1.1-1.37, P < 0.001) and locoregional (HR = 1.09, 95% CI 1-1.2, P = 0.049) patients. For metastatic patients, postoperative NLR was significantly associated with CSS on univariate analysis; however, change in NLR was not associated with outcome. CONCLUSIONS: Preoperative NLR is associated with CSS in locoregional and metastatic sRCC. NLR should be considered when establishing future predictive models for sRCC.

Systematic reviews of scores and predictors to trigger activation of massive transfusion protocols.

BACKGROUND: The use of massive transfusion protocols (MTPs) in the resuscitation of hemorrhaging trauma patients ensures rapid delivery of blood products to improve outcomes, where the decision to trigger MTPs early is important. Scores and tools to predict the need for MTP activation have been developed for use to aid with clinical judgment. We performed a systematic review to assess (1) the scores and tools available to predict MTP in trauma patients, (2) their clinical value and diagnostic accuracies, and (3) additional predictors of MTP. METHODS: MEDLINE, EMBASE, and CENTRAL were searched from inception to June 2017. All studies that utilized scores or predictors of MTP activation in adult (age, ≥18 years) trauma patients were included. Data collection for scores and tools included reported sensitivities and specificities and accuracy as defined by the area under the curve of the receiver operating characteristic. RESULTS: Forty-five articles were eligible for analysis, with 11 validated and four unvalidated scores and tools assessed. Of four scores using clinical assessment, laboratory values, and ultrasound assessment the modified Traumatic Bleeding Severity Score had the best performance. Of those scores, the Trauma Associated Severe Hemorrhage score is most well validated and has higher area under the curve of the receiver operating characteristic than the Assessment of Blood Consumption and Prince of Wales scores. Without laboratory results, the Assessment of Blood Consumption score balances accuracy with ease of use. Without ultrasound use, the Vandromme and Schreiber scores have the highest accuracy and sensitivity respectively. The Shock Index uses clinical assessment only with fair performance. Other clinical variables, laboratory values, and use of point-of-care testing results were identified predictors of MTP activation. CONCLUSION: The use of scores or tools to predict MTP need to be individualized to hospital resources and skill set to aid clinical judgment. Future studies for triggering nontrauma MTP activations are needed. LEVEL OF EVIDENCE: Systematic review, level III.

Pancreatic Cancer Gene Therapy Delivered by Nanoparticles.

Pancreatic cancer is one of the most lethal forms of cancer and has proven to be difficult to treat through conventional methods, including surgery and chemotherapy. Gene therapy serves as a potential novel treatment to interfere with genes that make this cancer so aggressive, but free nucleic acids have low cell uptake due to their negative charge and are unstable in circulation. Nanoparticles can serve as an effective carrier for a wide variety of gene therapies for pancreatic cancer as they can improve the circulation time, decrease the recognition by the immune system, and be functionalized to target specific surface proteins. In this review, we focus on therapeutic strategies using nanoparticles as carriers of small interfering RNA (siRNA), microRNA (miRNA), and gene augmentation (DNA) therapies in the context of pancreatic cancer. Lastly, we discuss the future outlook of nanoparticle-based therapies, including challenges in the clinical setting.

Safety and efficacy of balloon kyphoplasty at 4 or more levels in a single anesthetic session.

OBJECTIVE In this case series, the authors evaluated the safety of balloon kyphoplasty at 4 or more vertebral levels in a single anesthetic session. The current standard is that no more than 3 levels should be cemented at one time because of a perceived risk of increased complications. METHODS A retrospective chart review was performed for 19 consecutive patients who underwent ≥ 4-level balloon kyphoplasty between July 1, 2011, and December 31, 2015. Outcomes documented included kyphoplasty-associated complications and incidences of subsequent vertebral fracture. RESULTS Nineteen patients aged 22 to 95 years (mean 66.1 years, median 66 years; 53% male, 47% female) had 4 or more vertebrae cemented during the same procedure (mean 4.6 levels [62 thoracic, 29 lumbar]). No postoperative anesthetic complication, infection, extensive blood loss, symptomatic cement leakage, pneumothorax, or new-onset anemia was observed. Five patients experienced new compression fracture within a mean of 278 days postoperatively. One patient with metastatic cancer suffered bilateral pulmonary embolism 19 days after surgery, but no evidence of cement in the pulmonary vasculature was found. CONCLUSIONS In this case series, kyphoplasty performed on 4 or more vertebral levels was not found to increase risk to patient safety, and it might decrease unnecessary risks associated with multiple operations. Also, morbidity associated with leaving some fractures untreated because of an unfounded fear of increased risk of complications might be decreased by treating 4 or more levels in the same anesthetic session.

Surface-Enhanced Infrared Absorption: Pushing the Frontier for On-Chip Gas Sensing.

Surface-enhanced infrared absorption (SEIRA) is capable of identifying molecular fingerprints by resonant detection of infrared vibrational modes through the coupling with plasmonic modes of metallic nanostructures. However, SEIRA for on-chip gas sensing is still not very successful due to the intrinsically weak light-matter interaction between photons and gas molecules and the technical challenges in accumulating sufficient gas species in the vicinity of the spatially localized enhanced electric field, namely, the "hot-spots", generated through plasmonics. In this paper, we present a suspended silicon nitride (Si3N4) nanomembrane device by integrating plasmonic nanopatch gold antennas with metal-organic framework (MOF), which can largely adsorb carbon dioxide (CO2) through its nanoporous structure. Unlike conventional SEIRA sensing relying on highly localized hot-spots of plasmonic nanoantennas or nanoparticles, the device reported in this paper engineered the coupled surface plasmon polaritons in the metal-Si3N4 and metal-MOF interfaces to achieve strong optical field enhancement across the entire MOF film. We successfully demonstrated on-chip gas sensing of CO2 with more than 1800× enhancement factors by combining the concentration effect from the 2.7 µm MOF thin film and the optical field enhancement of the plasmonic nanopatch antennas.

Management of Sigmoid Sinus Associated Pulsatile Tinnitus: A Systematic Review of the Literature.

OBJECTIVES: Although studies demonstrate 4 to 20% of patients with pulsatile tinnitus (PT) have associated sigmoid sinus anomalies, no consensus exists regarding optimal management. Our objective was to perform a systematic review exploring surgical and endovascular intervention of PT caused by sigmoid sinus anomalies. DATA SOURCES/EXTRACTION: A systematic review was performed using the Preferred Reporting Systems for Systematic Reviews and Meta-Analysis guidelines for reporting of results, with a target population encompassing patients with PT and either sigmoid sinus diverticulum or sigmoid wall dehiscence. From an initial search yielding 74 articles, 21 manuscripts met inclusion criteria. DATA SYNTHESIS: Of 139 patients, 90.4% were female. Mean age was 39.0 years. Diagnosis was sigmoid sinus diverticulum/aneurysm in 47.5% of patients, sigmoid sinus dehiscence in 35.3% of patients, and both in 17.3%. Sigmoid sinus wall reconstruction/resurfacing (SSW R/R) was used in 91.4% and endovascular procedures in 7.9% of patients. Postoperative recurrence was 3.5% (mean follow-up 21.1 m). Although there was no association between resolution rate and age or sex, right-sided PT resolved at a higher rate. For every increase in body mass index by 1 kg/m, the odds of PT resolution increased 9.2%. CONCLUSION: PT as a result of sigmoid sinus diverticula, aneurysms, and dehiscence is a rare, but largely treatable condition. Available interventions include SSW R/R, endovascular intervention, and cardiac U-clip techniques. In SSW R/R, bone pate, unspecified soft-tissue graft, and bone cement had the highest rates of PT resolution. While temporalis fascia and autologous bone chips were the materials most commonly used, they had significantly lower rates of PT resolution compared with the other materials, with the exception of auricular cartilage and bone cement. Most episodes of recurrence are resolved with medical management or a revision procedure. This study serves to summarize the current state of knowledge on the treatment of pulsatile tinnitus across disciplines.