A cellulose-based light-management film incorporated with benzoxazine resin/tannic acid exhibiting UV/blue light double blocking and enhanced mechanical property.

Cellulose, as a biomass resource, has attracted increasingly attention and extensive research by virtue of its widely sources, ideal degradability, good mechanical properties and easy modification due to its rich hydroxyl groups. Nevertheless, it is still a challenge to attain high performance cellulose-based composite film materials with diverse functional combinations. In this work, we developed a multifunctional cellulose-based film via a facile impregnation-curing strategy. Here, benzoxazine resin (BR) is used as an optically functional component to endow the microfibrillated cellulose (MFC) film with powerful light management capabilities including UV and blue light double shielding, high transmittance, and high haze. Meanwhile, the introduction of tannic acid (TA) substantially enhanced the mechanical properties of the film, including tensile strength and toughness, by constructing energy-sacrificial bonds. An effective self-healing of the film was achieved by controlling the degree of BR curing. The final films exhibited 98.24 % UV shielding and 89.98 % blue light blocking, good mechanical properties including a tensile strength of 202.21 MPa and tensile strain of 7.1 %, as well as desirable thermal healing properties supported by incompletely cured BR. This work may provide new insights into the high-value utilization of biomass resources.

Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients.

BACKGROUND: In patients with embolic stroke of undetermined source (ESUS), occult atrial fibrillation (AF) has been implicated as a key source of cardioembolism. However, only a minority acquire implantable cardiac loop recorders (ILRs) to detect occult paroxysmal AF, partly due to financial cost and procedural inconvenience. Without the initiation of appropriate anticoagulation, these patients are at risk of increased ischemic stroke recurrence. Hence, cost-effective and accurate methods of predicting AF in ESUS patients are highly sought after. OBJECTIVE: We aimed to incorporate clinical and echocardiography data into machine learning (ML) algorithms for AF prediction on ILRs in ESUS. METHODS: This was a single-center cohort study that included 157 consecutive patients diagnosed with ESUS from October 2014 to October 2017 who had ILR evaluation. We developed four ML models, with hyperparameters tuned, to predict AF detection on an ILR. RESULTS: The median age of the cohort was 67 (IQR 59-74) years old and the median monitoring duration was 1051 (IQR 478-1287) days. Of the 157 patients, 32 (20.4%) had occult AF detected on the ILR. Support vector machine predicted for AF with a 95% confidence interval area under the receiver operating characteristic curve (AUC) of 0.736-0.737, multilayer perceptron with an AUC of 0.697-0.708, XGBoost with an AUC of 0.697-0.697, and random forest with an AUC of 0.663-0.674. ML feature importance found that age, HDL-C, and admitting heart rate were important non-echocardiography variables, while peak mitral A-wave velocity and left atrial volume were important echocardiography parameters aiding this prediction. CONCLUSION: Machine learning modeling incorporating clinical and echocardiographic variables predicted AF in ESUS patients with moderate accuracy.

Cellulose-based light-management film exhibiting flame-retardant and thermal-healing properties.

The increased use and expansion of biomass applications offer a viable approach to diminish reliance on petroleum-derived resources and promote carbon neutrality. Cellulose, being the most abundant natural polymer on Earth, has garnered considerable attention. This study introduces a straightforward method to fabricate a cellulose-based multifunctional composite film designed for efficient light management, specifically featuring flame retardant and thermal-healing capabilities. The film incorporates a microfibrillated cellulose (MFC) matrix with functional components, namely benzoxazine resin (BR) and 2-hydroxyethyl methacrylate phosphate (HEMAP). Utilizing dynamic covalent crosslinking, the composite films exhibit satisfactory self-healing properties. The combined effects of BR and HEMAP contribute to the effective flame retardancy of the composite film. Furthermore, the resulting film shields ultraviolet and blue light, offering comfortable interior lighting by mitigating harsh light and extending light propagation. The film also demonstrates favorable water resistance and high tensile strength. The exceptional multifunctional properties, coupled with its safety and extended service life, position it as a potential optical management film for smart building materials.

Simultaneous adsorption and biodegradation of polychlorinated biphenyls using resuscitated strain Streptococcus sp. SPC0 immobilized in polyvinyl alcohol­sodium alginate.

Enhanced bioremediation of polychlorinated biphenyls (PCBs) is a promising and effective strategy for eliminating the risks posed by PCBs. In the present study, the feasibility of utilizing an immobilization approach to enhance the PCBs degradation performance of a resuscitated strain Streptococcus sp. SPC0 was evaluated. The results indicated that a mixed matrix containing polyvinyl alcohol (PVA) and sodium alginate (SA) used as immobilized carriers provided a porous microstructure space for SPC0 colonization and proliferation. The enhanced removal of PCBs by immobilized SPC0 was attributed to simultaneous adsorption and biodegradation performances of PVA-SA-SPC0 beads. The relative equilibrium adsorption capacity of immobilized beads increased with elevated initial concentration, and the maximum theoretical value calculated was 1.64 mg/g. The adsorption process of PCBs by immobilized beads was well fitted to the quasi-second-order kinetic model, and most suitable for Langmuir isotherm model. Immobilized SPC0 enhanced PCB removal with 1.0-7.1 times higher than free cells. Especially, more effective removal of PCBs at higher concentrations could be achieved, in which 73.9 % of 20 mg/L PCBs was removed at 12 h by immobilized SPC0, whereas only 12.0 % by free cells. Moreover, the immobilized SPC0 with excellent stability and reusability retained almost 100 % of the original PCBs removal activity after reusing four times. These results revealed the application potential of immobilizing resuscitated strains for enhanced bioremediation of PCBs.

Motivations and experiences of patients with advanced cancer participating in Phase 1 clinical trials: A qualitative study.

BACKGROUND: Persons with advanced cancer may participate in Phase 1 clinical trials - first-in-human trials that are conducted with the main objectives of safety and dosing. The motivations for participation are not well understood and may include hope for cure. AIM: To explore the perspectives of persons with advanced cancer in order to understand the motivations for participating in Phase 1 clinical trials, experiences while being on trial and views on palliative care provision. DESIGN: Qualitative study with a constructivist stance, using thematic analysis based upon the grounded theory approach. SETTING/PARTICIPANTS: 20 persons with advanced cancer who were participating in a Phase 1 clinical trial. RESULTS: Many participants described how Phase 1 clinical trial participation was their last hope, as they were cognisant of their advanced disease. Information-seeking needs differed - some needed comprehensive information while others relied on the doctor's recommendation. Participants experienced varied negative and positive physical and psycho-emotional concerns, and needed to draw on multiple sources of support such as family, friends and healthcare professionals. Some could list potential benefits of palliative care but felt they did not require it yet. The overarching theme was hope and positive thinking as a way of coping. CONCLUSIONS: The concepts of hope as a way of coping and the supportive presence of healthcare professionals could be weaved into a future model of palliative care to improve the illness journey for patients considering Phase 1 clinical trial participation and other persons with advanced cancer.

MV2Net: Multi-Variate Multi-View Brain Network Comparison over Uncertain Data.

Visually identifying effective bio-markers from human brain networks poses non-trivial challenges to the field of data visualization and analysis. Existing methods in the literature and neuroscience practice are generally limited to the study of individual connectivity features in the brain (e.g., the strength of neural connection among brain regions). Pairwise comparisons between contrasting subject groups (e.g., the diseased and the healthy controls) are normally performed. The underlying neuroimaging and brain network construction process is assumed to have 100% fidelity. Yet, real-world user requirements on brain network visual comparison lean against these assumptions. In this work, we present MV^2Net, a visual analytics system that tightly integrates multi-variate multi-view visualization for brain network comparison with an interactive wrangling mechanism to deal with data uncertainty. On the analysis side, the system integrates multiple extraction methods on diffusion and geometric connectivity features of brain networks, an anomaly detection algorithm for data quality assessment, single- and multi-connection feature selection methods for bio-marker detection. On the visualization side, novel designs are introduced which optimize network comparisons among contrasting subject groups and related connectivity features. Our design provides level-of-detail comparisons, from juxtaposed and explicit-coding views for subject group comparisons, to high-order composite view for correlation of network comparisons, and to fiber tract detail view for voxel-level comparisons. The proposed techniques are inspired and evaluated in expert studies, as well as through case analyses on diffusion and geometric bio-markers of certain neurology diseases. Results in these experiments demonstrate the effectiveness and superiority of MV^2Net over state-of-the-art approaches.