Controlling 1D Nanostructures and Handedness by Polar Residue Chirality of Amphiphilic Peptides.

Peptide assemblies are promising nanomaterials, with their properties and technological applications being highly hinged on their supramolecular architectures. Here, how changing the chirality of the terminal charged residues of an amphiphilic hexapeptide sequence Ac-I4 K2 -NH2 gives rise to distinct nanostructures and supramolecular handedness is reported. Microscopic imaging and neutron scattering measurements show thin nanofibrils, thick nanofibrils, and wide nanotubes self-assembled from four stereoisomers. Spectroscopic and solid-state nuclear magnetic resonance (NMR) analyses reveal that these isomeric peptides adopt similar anti-parallel ß-sheet secondary structures. Further theoretical calculations demonstrate that the chiral alterations of the two C-terminal lysine residues cause the formation of diverse single ß-strand conformations, and the final self-assembled nanostructures and handedness are determined by the twisting direction and degree of single ß-strands. This work not only lays a useful foundation for the fabrication of diverse peptide nanostructures by manipulating the chirality of specific residues but also provides a framework for predicting the supramolecular structures and handedness of peptide assemblies from single molecule conformations.

SNAT2-mediated regulation of estrogen and progesterone in the proliferation of goat mammary epithelial cells.

The development of the goat mammary gland is mainly under the control of ovarian hormones particularly estrogen and progesterone (P4). Amino acids play an essential role in mammary gland development and milk production, and sodium-coupled neutral amino acid transporter 2 (SNAT2) was reported to be expressed in the mammary gland of rats and bovine mammary epithelial cells, which may affect the synthesis of milk proteins or mammary cell proliferation by mediating prolactin, 17ß-estradiol (E2) or methionine function. However, whether SNAT2 mediates the regulatory effects of E2 and P4 on the development of the ruminant mammary gland is still unclear. In this study, we show that E2 and P4 could increase the proliferation of goat mammary epithelial cells (GMECs) and regulate SNAT2 mRNA and protein expression in a dose-dependent manner. Further investigation revealed that SNAT2 is abundantly expressed in the mammary gland during late pregnancy and early lactation, while knockdown and overexpression of SNAT2 in GMECs could inhibit or enhance E2- and P4-induced cell proliferation as well as mammalian target of rapamycin (mTOR) signaling. We also found that the accelerated proliferation induced by SNAT2 overexpression in GMECs was suppressed by the mTOR signaling pathway inhibitor rapamycin. This indicates that the regulation of GMECs proliferation mediated by SNAT2 in response to E2 and P4 is dependent on the mTOR signaling pathway. Finally, we found that the total content of the amino acids in GMECs changed after knocking-down and overexpressing SNAT2. In summary, the results demonstrate that the regulatory effects of E2 and P4 on GMECs proliferation may be mediated by the SNAT2-transported amino acid pathway. These results may offer a novel nutritional target for improving the development of the ruminant mammary gland and milk production.

Building knowledge using a novel web-based intervention to promote HPV vaccination in a diverse, low-income population.

OBJECTIVES: HPV vaccination rates remain suboptimal despite proven efficacy. Data suggest misconceptions or lack of knowledge are leading barriers. Our study aimed to develop and pilot a novel interactive education resource designed to educate parents and patients about HPV vaccines. METHODS: This is a prospective pilot study conducted in an urban teaching hospital pediatric clinic. The Patient Activated Learning System (PALS) intervention included 3 web-based videos with HPV vaccine-related educational content. Participants were parents of adolescent patients, aged 11-17 years, and young adult patients, aged 18-26 years. Enrolled participants completed an HPV vaccine knowledge survey before and after watching PALS; paired scores were evaluated. Acceptability and participant-reported impact of PALS modules were measured via Likert-scale surveys. RESULTS: 132 individuals were approached; 101 (76%) enrolled and completed the study. Participants self-identified as Hispanic (50%), non-Hispanic Black (23%), non-Hispanic White (7%), Asian (6%), American/Alaskan/Hawaiian Native or Pacific Islander (5%). Half reported earning ≤$40,000 annually; 57% had only a high school education. Post-intervention knowledge scores were increased compared to baseline (9.87/27 points vs 17.53/27 points, p < 0.01). PALS modules were reported as enjoyable to use and understandable (89% and 93%, respectively), and improved participants' understanding of the importance of HPV vaccination (90%). Of the 18 patients unvaccinated at baseline, 39% received 1 shot of the HPV vaccine within one month. CONCLUSION: The PALS HPV vaccine educational intervention was feasible, acceptable, and improved knowledge among a diverse, underserved population. Our intervention may positively influence HPV vaccination rates, with potential to overcome HPV vaccine hesitancy.

Regionalizing ovarian cancer cytoreduction to high-volume centers and the impact on patient travel in New York State.

OBJECTIVE: To evaluate the theoretical impact of regionalizing cytoreductive surgery for ovarian cancer (OC) to high-volume facilities on patient travel. METHODS: We retrospectively identified patients with OC who underwent cytoreduction between 1/1/2004-12/31/2018 from the New York State Cancer Registry and Statewide Planning and Research Cooperative System. Hospitals were stratified by low-volume (<21 cytoreductive surgical procedures for OC annually) and high-volume centers (≥21 procedures annually). A simulation was performed; outcomes of interest were driving distance and time between the centroid of the patient's residence zip code and the treating facility zip code. RESULTS: Overall, 60,493 patients met inclusion criteria. Between 2004 and 2018, 210 facilities were performing cytoreductive surgery for OC in New York; 159 facilities (75.7%) met low-volume and 51 (24.3%) met high-volume criteria. Overall, 10,514 patients (17.4%) were treated at low-volume and 49,979 (82.6%) at high-volume facilities. In 2004, 78.2% of patients were treated at high-volume facilities, which increased to 84.6% in 2018 (P < .0001). Median travel distance and time for patients treated at high-volume centers was 12.2 miles (IQR, 5.6-25.5) and 23.0 min (IQR, 15.2-37.0), and 8.2 miles (IQR, 3.7-15.9) and 16.8 min (IQR, 12.4-26.0) for patients treated at low-volume centers. If cytoreductive surgery was centralized to high-volume centers, median distance and time traveled for patients originally treated at low-volume centers would be 11.2 miles (IQR, 3.8-32.3; P < .001) and 20.2 min (IQR, 13.6-43.0; P < .001). CONCLUSIONS: Centralizing cytoreductive surgery for OC to high-volume centers in New York would increase patient travel burden by negligible amounts of distance and time for most patients.

High-performance presurgical differentiation of glioblastoma and metastasis by means of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics.

OBJECTIVES: To evaluate the performance of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics in distinguishing between glioblastoma (Gb) and solitary brain metastasis (SBM). MATERIALS AND METHODS: In this retrospective study, NODDI images were curated from 109 patients with Gb (n = 57) or SBM (n = 52). Automatically segmented multiple volumes of interest (VOIs) encompassed the main tumor regions, including necrosis, solid tumor, and peritumoral edema. Radiomics features were extracted for each main tumor region, using three NODDI parameter maps. Radiomics models were developed based on these three NODDI parameter maps and their amalgamation to differentiate between Gb and SBM. Additionally, radiomics models were constructed based on morphological magnetic resonance imaging (MRI) and diffusion imaging (diffusion-weighted imaging [DWI]; diffusion tensor imaging [DTI]) for performance comparison. RESULTS: The validation dataset results revealed that the performance of a single NODDI parameter map model was inferior to that of the combined NODDI model. In the necrotic regions, the combined NODDI radiomics model exhibited less than ideal discriminative capabilities (area under the receiver operating characteristic curve [AUC] = 0.701). For peritumoral edema regions, the combined NODDI radiomics model achieved a moderate level of discrimination (AUC = 0.820). Within the solid tumor regions, the combined NODDI radiomics model demonstrated superior performance (AUC = 0.904), surpassing the models of other VOIs. The comparison results demonstrated that the NODDI model was better than the DWI and DTI models, while those of the morphological MRI and NODDI models were similar. CONCLUSION: The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM. CLINICAL RELEVANCE STATEMENT: The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM, and radiomics features can be incorporated into the multidimensional phenotypic features that describe tumor heterogeneity. KEY POINTS: • The neurite orientation dispersion and density imaging (NODDI) radiomics model showed promising performance for preoperative discrimination between glioblastoma and solitary brain metastasis. • Compared with other tumor volumes of interest, the NODDI radiomics model based on solid tumor regions performed best in distinguishing the two types of tumors. • The performance of the single-parameter NODDI model was inferior to that of the combined-parameter NODDI model.

Determinants of radiation exposure during mobile cone-beam CT-guided robotic-assisted bronchoscopy.

BACKGROUND AND OBJECTIVE: Robotic-assisted bronchoscopy (RAB) is an emerging modality to sample pulmonary lesions. Cone-beam computed tomography (CBCT) can be incorporated into RAB. We investigated the magnitude and predictors of patient and staff radiation exposure during mobile CBCT-guided shape-sensing RAB. METHODS: Patient radiation dose was estimated by cumulative dose area product (cDAP) and cumulative reference air kerma (cRAK). Staff equivalent dose was calculated based on isokerma maps and a phantom simulation. Patient, lesion and procedure-related factors associated with higher radiation doses were identified by logistic regression models. RESULTS: A total of 198 RAB cases were included in the analysis. The median patient cDAP and cRAK were 10.86 Gy cm2 (IQR: 4.62-20.84) and 76.20 mGy (IQR: 38.96-148.38), respectively. Among staff members, the bronchoscopist was exposed to the highest median equivalent dose of 1.48 µSv (IQR: 0.85-2.69). Both patient and staff radiation doses increased with the number of CBCT spins and targeted lesions (p < 0.001 for all comparisons). Patient obesity, negative bronchus sign, lesion size <2.0 cm and inadequate sampling by on-site evaluation were associated with a higher patient dose, while patient obesity and inadequate sampling by on-site evaluation were associated with a higher bronchoscopist equivalent dose. CONCLUSION: The magnitude of patient and staff radiation exposure during CBCT-RAB is aligned with safety thresholds recommended by regulatory authorities. Factors associated with a higher radiation exposure during CBCT-RAB can be identified pre-operatively and solicit procedural optimization by reinforcing radiation protective measures. Future studies are needed to confirm these findings across multiple institutions and practices.

The impact of regional policy implementation on the decoupling of carbon emissions and economic development.

The contradiction between economic growth demands and the achievement of the "dual-carbon" goals at the regional level is a pressing issue in China. As a significant economic and cultural center in the western region of China, the Guanzhong Plain urban agglomeration has experienced rapid development and urbanization, making it one of the key areas for national development. Therefore, greater attention should be given to carbon emission reduction in this region. This study focuses on the dataset from 2010 to 2019 in the Guanzhong Plain urban agglomeration, utilizing an input-output table to construct a carbon dioxide emission inventory. The research investigates the impact of regional classification on carbon emission levels within the Guanzhong Plain urban agglomeration. Furthermore, the Tapio decoupling analysis method is employed to assess the decoupling coefficient between regional economic development and carbon emissions. Additionally, the Theil index inequality analysis method is utilized to measure the disparities in per capita carbon emissions among cities within the region. Research findings indicate the following: 1) The regional classification of the Guanzhong Plain urban agglomeration is an effective policy for reducing regional carbon emissions and promoting carbon emissions reduction. 2) There exist variations in energy and industrial structures among cities within the urban agglomeration, necessitating tailored measures for low-carbon transition based on the specific circumstances of each city. 3) The regional classification of the urban agglomeration significantly influences the degree of decoupling between economic development and carbon emissions, with a trend towards stronger decoupling. The study suggests that cities within the Guanzhong Plain urban agglomeration should adopt measures aligned with their natural conditions and economic characteristics to achieve a low-carbon transition. Leveraging the regional cooperation capacity of the urban agglomeration is crucial to decouple economic development from carbon emissions, thereby promoting sustainable economic growth and environmental protection in a mutually beneficial manner.

Radiomic texture analysis based on neurite orientation dispersion and density imaging to differentiate glioblastoma from solitary brain metastasis.

BACKGROUND: We created discriminative models of different regions of interest (ROIs) using radiomic texture features of neurite orientation dispersion and density imaging (NODDI) and evaluated the feasibility of each model in differentiating glioblastoma multiforme (GBM) from solitary brain metastasis (SBM). METHODS: We conducted a retrospective study of 204 patients with GBM (n = 146) or SBM (n = 58). Radiomic texture features were extracted from five ROIs based on three metric maps (intracellular volume fraction, orientation dispersion index, and isotropic volume fraction of NODDI), including necrosis, solid tumors, peritumoral edema, tumor bulk volume (TBV), and abnormal bulk volume. Four feature selection methods and eight classifiers were used for the radiomic texture feature selection and model construction. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the models. Routine magnetic resonance imaging (MRI) radiomic texture feature models generated in the same manner were used for the horizontal comparison. RESULTS: NODDI-radiomic texture analysis based on TBV subregions exhibited the highest accuracy (although nonsignificant) in differentiating GBM from SBM, with area under the ROC curve (AUC) values of 0.918 and 0.882 in the training and test datasets, respectively, compared to necrosis (AUCtraining:0.845, AUCtest:0.714), solid tumor (AUCtraining:0.852, AUCtest:0.821), peritumoral edema (AUCtraining:0.817, AUCtest:0.762), and ABV (AUCtraining:0.834, AUCtest:0.779). The performance of the five ROI radiomic texture models in routine MRI was inferior to that of the NODDI-radiomic texture model. CONCLUSION: Preoperative NODDI-radiomic texture analysis based on TBV subregions shows great potential for distinguishing GBM from SBM.

Histogram Analysis Based on Neurite Orientation Dispersion and Density MR Imaging for Differentiation Between Glioblastoma Multiforme and Solitary Brain Metastasis and Comparison of the Diagnostic Performance of Two ROI Placements.

BACKGROUND: Preoperative differentiation of glioblastoma multiforme (GBM) and solitary brain metastasis (SBM) contributes to guide neurosurgical decision-making. PURPOSE: To explore the value of histogram analysis based on neurite orientation dispersion and density imaging (NODDI) in differentiating between GBM and SBM and comparison of the diagnostic performance of two region of interest (ROI) placements. STUDY TYPE: Retrospective. POPULATION: In all, 109 patients with GBM (n = 57) or SBM (n = 52) were enrolled. FIELD STRENGTH/SEQUENCE: A 3.0 T scanners. T2 -dark-fluid sequence, contrast-enhanced T1 magnetization-prepared rapid gradient echo sequence, and NODDI. ASSESSMENT: ROIs were placed on the peritumoral edema area (ROI1) and whole tumor area (ROI2, included the cystic, necrotic, and hemorrhagic areas). Histogram parameters of each isotropic volume fraction (ISOVF), intracellular volume fraction (ICVF), and orientation dispersion index (ODI) from NODDI images for two ROIs were calculated, respectively. STATISTICAL TESTS: Mann-Whitney U test, independent t-test, chi-square test, multivariate logistic regression analysis, DeLong's test. RESULTS: For the ROI1 and ROI2, the ICVFmin and ODImean obtained the highest area under curve (AUC, AUC = 0.741 and 0.750, respectively) compared to other single parameters, and the AUC of the multivariate logistic regression model was 0.851 and 0.942, respectively. DeLong's test revealed significant difference in diagnostic performance between optimal single parameter and multivariate logistic regression model within the same ROI, and the multivariate logistic regression models between two different ROIs. DATA CONCLUSION: The performance of multivariate logistic regression model is superior to optimal single parameter in both ROIs based on NODDI histogram analysis to distinguish SBM from GBM, and the ROI placed on the whole tumor area exhibited better diagnostic performance. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Diverse roles of glucocorticoids in the ruminant mammary gland: modulation of mammary growth, milk production, and mastitis.

As endocrine hormones, glucocorticoids (GCs) play a pivotal role in numerous physiological processes, including mammary growth and lactation, circulatory metabolism, and responses to external stimuli. In the dairy industry, milk production from cows or goats is important for newborns and economic benefits. However, the milk yields from ruminant animals are always affected by the extent of mammary development, mammary disease, stress, or changes in metabolism. Thus, it is necessary to clarify how GCs changes in ruminants affect ruminant mammary gland function and mammary disease. This review summarizes the findings identifying that GCs modulate mammary gland development before lactation, but the stress-induced excessive release of GCs leads to milk production loss. In addition, the manner of GCs release may change under different concentrations of metabolites or during mastitis or inflammatory challenge. Nevertheless, exogenous GCs administration to animals may alleviate the clinical symptoms of mastitis. This review demonstrates that GCs offer a fascinating contribution to both physiologic and pathogenic conditions of the mammary gland in ruminant animals. Characterizing and understanding these changes or functions of endogenous and exogenous GCs in animals will be crucial for developing more endocrine regulators and therapies for improving milk production in ruminants.

Antiemetic Administration and Its Association with Race: A Retrospective Cohort Study.

BACKGROUND: Anesthesiologists' contribution to perioperative healthcare disparities remains unclear because patient and surgeon preferences can influence care choices. Postoperative nausea and vomiting is a patient- centered outcome measure and a main driver of unplanned admissions. Antiemetic administration is under the sole domain of anesthesiologists. In a U.S. sample, Medicaid insured versus commercially insured patients and those with lower versus higher median income had reduced antiemetic administration, but not all risk factors were controlled for. This study examined whether a patient's race is associated with perioperative antiemetic administration and hypothesized that Black versus White race is associated with reduced receipt of antiemetics. METHODS: An analysis was performed of 2004 to 2018 Multicenter Perioperative Outcomes Group data. The primary outcome of interest was administration of either ondansetron or dexamethasone; secondary outcomes were administration of each drug individually or both drugs together. The confounder-adjusted analysis included relevant patient demographics (Apfel postoperative nausea and vomiting risk factors: sex, smoking history, postoperative nausea and vomiting or motion sickness history, and postoperative opioid use; as well as age) and included institutions as random effects. RESULTS: The Multicenter Perioperative Outcomes Group data contained 5.1 million anesthetic cases from 39 institutions located in the United States and The Netherlands. Multivariable regression demonstrates that Black patients were less likely to receive antiemetic administration with either ondansetron or dexamethasone than White patients (290,208 of 496,456 [58.5%] vs. 2.24 million of 3.49 million [64.1%]; adjusted odds ratio, 0.82; 95% CI, 0.81 to 0.82; P < 0.001). Black as compared to White patients were less likely to receive any dexamethasone (140,642 of 496,456 [28.3%] vs. 1.29 million of 3.49 million [37.0%]; adjusted odds ratio, 0.78; 95% CI, 0.77 to 0.78; P < 0.001), any ondansetron (262,086 of 496,456 [52.8%] vs. 1.96 million of 3.49 million [56.1%]; adjusted odds ratio, 0.84; 95% CI, 0.84 to 0.85; P < 0.001), and dexamethasone and ondansetron together (112,520 of 496,456 [22.7%] vs. 1.0 million of 3.49 million [28.9%]; adjusted odds ratio, 0.78; 95% CI, 0.77 to 0.79; P < 0.001). CONCLUSIONS: In a perioperative registry data set, Black versus White patient race was associated with less antiemetic administration, after controlling for all accepted postoperative nausea and vomiting risk factors.

Safety and efficacy of Cesium-131 brachytherapy for brain tumors.

BACKGROUND: The introduction of Cesium-131 (Cs-131) as a radiation source has led to a resurgence of brachytherapy for central nervous system (CNS) tumors. The aim of this study was to evaluate the safety and efficacy of the largest cohort of Cs-131 patients to-date. METHODS: A retrospective review of all CNS tumors treated with resection and adjuvant Cs-131 brachytherapy at New York-Presbyterian/Weill Cornell from 2010 to 2021 was performed. Overall survival (OS) and local control (LC) were assessed with Kaplan-Meier methodology. Univariable analysis was conducted to identify patient factors associated with local recurrence or radiation necrosis. RESULTS: Adjuvant Cs-131 brachytherapy following resection was performed in 119 patients with a median follow-up time of 11.8 (IQR 4.7-23.6) months and a mean of 22.3 +/-30.3 months. 1-year survival rates were 53.3% (95%CI 41.9-64.6%) for brain metastases (BrM), 45.9% (95%CI 24.8-67.0%) for gliomas, and 73.3% (95%CI 50.9-95.7%) for meningiomas. 1-year local control rates were 84.7% for BrM, 34.1% for gliomas, and 83.3% for meningiomas (p < 0.001). For BrM, local control was superior in NSCLC relative to other BrM pathologies (90.8% versus 76.5%, p = 0.039). Radiographic radiation necrosis (RN) was identified in 10 (8.4%) cases and demonstrated an association with smaller median tumor size (2.4 [IQR 1.8-2.7 cm] versus 3.1 [IQR 2.4-3.8 cm], p = 0.034). Wound complications occurred in 14 (11.8%) patients. CONCLUSIONS: Cs-131 brachytherapy demonstrated a favorable safety and efficacy profile characterized by high rates of local control for all treated pathologies. The concept of brachytherapy has seen a resurgence given the excellent results when Cs-131 is used as a source.

Engineered Macrophage-Membrane-Coated Nanoparticles with Enhanced PD-1 Expression Induce Immunomodulation for a Synergistic and Targeted Antiglioblastoma Activity.

Glioblastoma (GBM), the most common subtype of malignant gliomas, is characterized by aggressive infiltration, high malignancy, and poor prognosis. The frustrating anti-GBM outcome of conventional therapeutics is due to the immunosuppressive milieu, in addition to the formidable obstacle of the blood-brain barrier (BBB). Combination therapy with an immune checkpoint blockade (ICB) has emerged as a critical component in the treatment of GBM. Here, we report an engineered macrophage-membrane-coated nanoplatform with enhanced programmed cell death-1 (PD-1) expression (PD-1-MM@PLGA/RAPA). Using both in vitro and in vivo GBM models, we demonstrate that PD-1-MM@PLGA/RAPA can efficiently traverse across the BBB in response to the tumor microenvironment (TME) recruitment with nanoparticles accumulating at the tumor site. Furthermore, we show a boosted immune response as a result of enhancing CD8+ cytotoxic T-lymphocyte (CTL) infiltration. Together we provide a new nanoplatform for enhancing ICB in combination with conventional chemotherapy for GBM and many other cancers.

Sex Differences in In-Hospital Mortality After Open Cardiac Valve Surgery.

BACKGROUND: Cardiac valvular disease affects millions of people worldwide and is a major cause of morbidity and mortality. Female patients have been shown to experience inferior clinical outcomes after nonvalvular cardiac surgery, but recent data are limited regarding open valve surgical cohorts. The primary objective of our study was to assess whether female sex is associated with increased in-hospital mortality after open cardiac valve operations. METHODS: Utilizing the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID), we conducted a retrospective cohort study of patients who underwent open cardiac valve surgery from 2007 to 2018 in Washington, Maryland, Kentucky, and Florida; from 2007 to 2011 in California; and from 2007 to 2016 in New York. The primary objective of this study was to estimate the confounder-adjusted association between sex and in-hospital mortality (as recorded and coded by SID HCUP) after open cardiac valve surgery. We used multilevel multivariable models to account for potential confounders, including intrahospital practice patterns. RESULTS: A total of 272,954 patients (108,443 women; 39.73% of sample population with mean age of 67.6 ± 14.3 years) were included in our analysis. The overall mortality rates were 3.8% for male patients and 5.1% for female patients. The confounder-adjusted odds ratio (OR) for in-hospital mortality for female patients compared to male patients was 1.41 (95% confidence interval [CI], 1.35-1.47; P < .001). When stratifying by surgical type, female patients were also at increased odds of in-hospital mortality ( P < .001) in populations undergoing aortic valve replacement (adjusted OR [aOR], 1.38; 95% CI, 1.25-1.52); multiple valve surgery (aOR, 1.38; 95% CI, 1.22-1.57); mitral valve replacement (aOR, 1.22; 95% CI, 1.12 - 1.34); and valve surgery with coronary artery bypass grafting (aOR, 1.64; 95% CI, 1.54 - 1.74; all P < .001). Female patients did not have increased odds of in-hospital mortality in populations undergoing mitral valve repair (aOR, 1.26; 95% CI, 0.98 - 1.64; P = .075); aortic valve repair (aOR, 0.87; 95% CI, 0.67 - 1.14; P = .32); or any other single valve repair (aOR, 1.10; 95% CI, 0.82 - 1.46; P = .53). CONCLUSIONS: We found an association between female patients and increased confounder-adjusted odds of in-hospital mortality after open cardiac valve surgery. More research is needed to better understand and categorize these important outcome differences. Future research should include observational analysis containing granular and complete patient- and surgery-specific data.

Ordered Packing of ß-Sheet Nanofibrils into Nanotubes: Multi-hierarchical Assembly of Designed Short Peptides.

Although it is well-known proteins and their complexes are hierarchically organized and highly ordered structures, it remains a major challenge to replicate their hierarchical self-assembly process and to fabricate multihierarchical architectures with well-defined shapes and monodisperse characteristic sizes via peptide self-assembly. Here we describe an amphiphilic short peptide Ac-I3GGHK-NH2 that first preassembles into thin, left-handed ß-sheet nanofibrils, followed by their ordered packing into right-handed nanotubes. The key intermediate morphology and structures featuring the hierarchical process are simultaneously demonstrated. Further mechanistic exploration with the variants Ac-I3GGGK-NH2, Ac-I3GGFK-NH2, and Ac-I3GGDHDK-NH2 reveals the vital role of multiple His-His side chain interactions between nanofibrils in mediating higher-order assembly and architectures. Altogether, our findings not only advance current understanding of hierarchical assembly of peptides and proteins but also afford a paradigm of how to take advantage of side chain interactions to construct higher-order assemblies with enhanced complexities.

Development of an AI system for accurately diagnose hepatocellular carcinoma from computed tomography imaging data.

BACKGROUND AND AIMS: Computed tomography (CT) scan is frequently used to detect hepatocellular carcinoma (HCC) in routine clinical practice. The aim of this study is to develop a deep-learning AI system to improve the diagnostic accuracy of HCC by analysing liver CT imaging data. METHODS: We developed a deep-learning AI system by training on CT images from 7512 patients at Henan Provincial Peoples' Hospital. Its performance was validated on one internal test set (Henan Provincial Peoples' Hospital, n = 385) and one external test set (Henan Provincial Cancer Hospital, n = 556). The area under the receiver-operating characteristic curve (AUROC) was used as the primary classification metric. Accuracy, sensitivity, specificity, precision, negative predictive value and F1 metric were used to measure the performance of AI systems and radiologists. RESULTS: AI system achieved high performance in identifying HCC patients, with AUROC of 0.887 (95% CI 0.855-0.919) on the internal test set and 0.883 (95% CI 0.855-0.911) on the external test set. For internal test set, accuracy was 81.0% (76.8-84.8%), sensitivity was 78.4% (72.4-83.7%), specificity was 84.4% (78.0-89.6%) and F1 (harmonic average of precision and recall rate) was 0.824. For external test set, accuracy was 81.3% (77.8-84.5%), sensitivity was 89.4% (85.0-92.8%), specificity was 74.0% (68.5-78.9%) and F1 was 0.819. Compared with radiologists, AI system achieved comparable accuracy and F1 metric on internal test set (0.853 versus 0.818, P = 0.107; 0.863 vs. 0.824, P = 0.082) and external test set (0.805 vs. 0.793, P = 0.663; 0.810 vs. 0.814, P = 0.866). The predicted HCC risk scores by AI system in HCC patients with multiple tumours and high fibrosis stage were higher than those with solitary tumour and low fibrosis stage (tumour number: 0.197 vs. 0.138, P = 0.006; fibrosis stage: 0.183 vs. 0.127, P < 0.001). Radiologists' review showed that the accuracy of saliency heatmaps predicted by algorithms was 92.1% (95% CI: 89.2-95.0%). CONCLUSIONS: AI system achieved high performance in the detection of HCC compared with a group of specialised radiologists. Further investigation by prospective clinical trials was necessitated to verify this model.

Active Surveillance for Men with Intermediate Risk Prostate Cancer.

PURPOSE: Optimal treatment of intermediate risk prostate cancer remains unclear. National Comprehensive Cancer Network® guidelines recommend active surveillance, prostatectomy or radiotherapy. Recent trials demonstrated no difference in prostate cancer specific mortality for men undergoing active surveillance for low risk prostate cancer compared to prostatectomy or radiotherapy. The use of active surveillance for intermediate risk prostate cancer is less clear. In this study we characterize U.S. national trends for demographic, clinical and socioeconomic factors associated with active surveillance for men with intermediate risk prostate cancer. MATERIALS AND METHODS: This retrospective cohort study examined 176,122 men diagnosed with intermediate risk prostate cancer from 2010 to 2016 in the National Cancer Database. Temporal trends in demographic, clinical and socioeconomic factors among men with intermediate risk prostate cancer and association with the use of active surveillance were characterized. The analysis was performed in April 2020. RESULTS: In total, 176,122 men were identified with intermediate risk prostate cancer from 2010 to 2016. Of these men 57.3% underwent prostatectomy, 36.4% underwent radiotherapy and 3.2% underwent active surveillance. Active surveillance nearly tripled from 1.6% in 2010 to 4.6% in 2016 (p <0.001). On multivariate analysis use of active surveillance was associated with older age, diagnosis in recent years, lower Gleason score and tumor stage, type of insurance, treatment at an academic center and proximity to facility, and attaining higher education (p <0.05). Race and comorbidities were not associated with active surveillance. CONCLUSIONS: Our findings highlight increasing active surveillance use for men with intermediate risk prostate cancer demonstrating clinical and socioeconomic disparities. Prospective data and improved risk stratification are needed to guide optimal treatment for men with intermediate risk prostate cancer.

Factors Driving Citizen Engagement With Government TikTok Accounts During the COVID-19 Pandemic: Model Development and Analysis.

BACKGROUND: During the COVID-19 pandemic, growth in citizen engagement with social media platforms has enabled public health departments to accelerate and improve health information dissemination, developing transparency and trust between governments and citizens. In light of these benefits, it is imperative to learn the antecedents and underlying mechanisms for this to maintain and enhance engagement. OBJECTIVE: The aim of this study is to determine the factors and influencing mechanisms related to citizen engagement with the TikTok account of the National Health Commission of China during the COVID-19 pandemic. METHODS: Using a web crawler, 355 short videos were collected from the Healthy China account on TikTok (with more than 3 million followers throughout China), covering the period from January 21, 2020, to April 25, 2020. The title and video length, as well as the number of likes, shares, and comments were collected for each video. After classifying them using content analysis, a series of negative binomial regression analyses were completed. RESULTS: Among the 355 videos, 154 (43.4%) related to guidance for clinicians, patients, and ordinary citizens, followed by information concerning the government's handling of the pandemic (n=100, 28.2%), the latest news about COVID-19 (n=61, 17.2%), and appreciation toward frontline emergency services (n=40, 11.3%). Video length, titles, dialogic loop, and content type all influenced the level of citizen engagement. Specifically, video length was negatively associated with the number of likes (incidence rate ratio [IRR]=0.19, P<.001) and comments (IRR=0.39, P<.001). Title length was positively related to the number of shares (IRR=24.25, P=.01), likes (IRR=8.50, P=.03), and comments (IRR=7.85, P=.02). Dialogic loop negatively predicted the number of shares (IRR=0.56, P=.03). In comparison to appreciative information, information about the government's handling of the situation (IRR=5.16, P<.001) and guidelines information (IRR=7.31, P<.001) were positively correlated with the number of shares, while the latest news was negatively related to the number of likes received (IRR=0.46, P=.004). More importantly, the relationship between predictors and citizen engagement was moderated by the emotional valence of video titles. Longer videos with positive titles received a higher number of likes (IRR=21.72, P=.04) and comments (IRR=10.14, P=.047). Furthermore, for short videos related to government handling of the pandemic (IRR=14.48, P=.04) and guidance for stakeholders (IRR=7.59, P=.04), positive titles received a greater number of shares. Videos related to the latest news (IRR=66.69, P=.04) received more likes if the video title displayed higher levels of positive emotion. CONCLUSIONS: During the COVID-19 pandemic, videos were frequently published on government social media platforms. Video length, title, dialogic loop, and content type significantly influenced the level of citizen engagement. These relationships were moderated by the emotional valence of the video's title. Our findings have implications for maintaining and enhancing citizen engagement via government social media.

Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry.

AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and the coronary artery calcium score (CACS), to predict the presence of obstructive CAD on coronary computed tomography angiography (CCTA). METHODS AND RESULTS: The study screened 35 281 participants enrolled in the CONFIRM registry, who underwent ≥64 detector row CCTA evaluation because of either suspected or previously established CAD. A boosted ensemble algorithm (XGBoost) was used, with data split into a training set (80%) on which 10-fold cross-validation was done and a test set (20%). Performance was assessed of the (1) ML model (using 25 clinical and demographic features), (2) ML + CACS, (3) CAD consortium clinical score, (4) CAD consortium clinical score + CACS, and (5) updated Diamond-Forrester (UDF) score. The study population comprised of 13 054 patients, of whom 2380 (18.2%) had obstructive CAD (≥50% stenosis). Machine learning with CACS produced the best performance [area under the curve (AUC) of 0.881] compared with ML alone (AUC of 0.773), CAD consortium clinical score (AUC of 0.734), and with CACS (AUC of 0.866) and UDF (AUC of 0.682), P < 0.05 for all comparisons. CACS, age, and gender were the highest ranking features. CONCLUSION: A ML model incorporating clinical features in addition to CACS can accurately estimate the pretest likelihood of obstructive CAD on CCTA. In clinical practice, the utilization of such an approach could improve risk stratification and help guide downstream management.

Disparities in mortality after abdominal aortic aneurysm repair are linked to insurance status.

OBJECTIVE: The objective of this study was to determine differences in mortality after abdominal aortic aneurysm (AAA) repair based on insurance type. METHODS: In this retrospective cohort study, data from all-payer patients in nonpsychiatric hospitals in New York, Maryland, Florida, Kentucky, and California from January 2007 to December 2014 (excluding California, ending December 2011) were extracted from the State Inpatient Databases, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. There were 90,102 patients ≥18 years old with available insurance data who underwent open AAA repair or endovascular aneurysm repair (EVAR) identified using International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes 3844, 3925, and 3971. EVAR patients were identified using the procedure code 3971, and the remainder of cases were categorized as open. Patients were divided into cohorts by insurance type as Medicare, Medicaid, uninsured (self-pay/no charge), other, or private insurance. Patients were further stratified for subgroup analyses by procedure type. Unadjusted rates of in-hospital mortality, the primary outcome, as well as secondary outcomes, such as surgical urgency, 30-day and 90-day readmissions, length of stay, total charges, and postoperative complications, were examined by insurance type. Adjusted odds ratios (ORs) for in-hospital mortality were calculated using multivariate logistic regression models fitted to the data. The multivariate models included patient-, surgical-, and hospital-specific factors with bivariate baseline testing suggestive of association with insurance status in addition to variables that were selected a priori. RESULTS: Medicaid and uninsured patients had the highest rates of mortality relative to private insurance beneficiaries in all cohorts. Medicaid patients incurred a 47% increase in the odds of mortality, the highest among the insured, after all AAA repairs (OR, 1.47; 95% confidence interval [CI], 1.23-1.76), whereas uninsured patients experienced a 102% increase in the odds of mortality (OR, 2.02; 95% CI, 1.54-2.67). Subgroup analyses for open AAA repair and EVAR corroborated that Medicaid insurance (open repair OR, 1.37 [95% CI, 1.14-1.64]; EVAR OR, 2.06 [95% CI, 1.40-3.04]) and uninsured status (open repair OR, 1.85 [95% CI, 1.35-2.54]; EVAR OR, 2.96 [95% CI, 1.82-4.81]) were associated with the highest odds of mortality after both procedures separately. CONCLUSIONS: This study demonstrates that Medicaid insurance and uninsured status are associated with higher unadjusted rates and adjusted ORs for in-hospital mortality after AAA repair relative to private insurance status. Primary payer status therefore serves as an independent predictor of the risk of death subsequent to AAA surgical interventions.