Single Factor Research Articles

Extraction of 5 benzotriazole ultraviolet filters from soil samples using natural deep eutectic solvent vortex assisted liquid–liquid microextraction combined with GC–MS

Benzotriazole (BTRs) ultraviolet filters are a class of substances found in the environment that pose potential hazards to human health and environment. Therefore, it is essential to develop techniques for determining BTRs in the environment. In this paper, a simple, green, and effective vortex assisted liquid–liquid microextraction (VALLME) was developed to determine trace BTRs in the environment, combining natural deep eutectic solvents (NADES) with Gas chromatography-mass spectrometer (GC–MS). Result parameters were optimized by single factor analysis, Factorial Multilevel Categoric Design and Central Composite Design, and optimal extraction solve (NADES) was obtained by mixing choline chloride (ChCl) and lactic acid (LA) with the ratio 1:1. After optimization, the linearity (r2 ≥ 0.9929), LODs (0.010–0.083 μg/ml), LOQs (0.033–0.276 μg/ml), and RSD (2.96–4.21 %) were verified. For the first time, a method based on the new type of NADES for the determination of BTRs ultraviolet filters in soil was propose, which could replace traditional extractants for BTRs and serve as a sustainable and environmentally friendly extraction medium for other matrices.

Traceability and reuse mechanisms, the most important properties of model transformation languages

ContextDedicated model transformation languages are claimed to provide many benefits over the use of general purpose languages for developing model transformations. However, the actual advantages and disadvantages associated with the use of model transformation languages are poorly understood empirically. There is little knowledge and even less empirical assessment about what advantages and disadvantages hold in which cases and where they originate from. In a prior interview study, we elicited expert opinions on what advantages result from what factors surrounding model transformation languages as well as a number of moderating factors that moderate the influence.ObjectiveWe aim to quantitatively asses the interview results to confirm or reject the influences and moderation effects posed by different factors. We further intend to gain insights into how valuable different factors are to the discussion so that future studies can draw on these data for designing targeted and relevant studies.MethodWe gather data on the factors and quality attributes using an online survey. To analyse the data and examine the hypothesised influences and moderations, we use universal structure modelling based on a structural equation model. Universal structure modelling produces significance values and path coefficients for each hypothesised and modelled interdependence between factors and quality attributes that can be used to confirm or reject correlation and to weigh the strength of influence present.ResultsWe analyzed 113 responses. The results show that the MTL capabilities Tracing and Reuse Mechanisms are most important overall. Though the observed effects were generally 10 times lower than anticipated. Furthermore, we found that moderation effects need to be individually assessed for each influence on a quality attribute. The moderation effects of a single moderating variable vary significantly for each influence, with the strongest effects being 1000 times higher than the weakest.ConclusionThe empirical assessment of MTLs is a complex topic that cannot be solved by looking at a single stand-alone factor. Our results provide clear indication that evaluation should consider transformations of different sizes and use-cases that go beyond mapping one elements attributes to another. Language development on the other hand should focus on providing practical, transformation specific reuse mechanisms that allow MTLs to excel in areas such as maintainability and productivity compared to GPLs.

Real-World Evidence to Inform Regulatory Decision Making: A Scoping Review.

Real-world evidence (RWE) is increasingly considered in regulatory decision making. When, and to which extent, RWE is considered relevant by regulators likely depends on many factors. This review aimed to identify factors that make RWE necessary or desirable to inform regulatory decision making. A scoping review was conducted using literature databases (PubMed, Embase, Emcare, Web of Science, and Cochrane Library) and websites of regulatory agencies, health technology assessment agencies, research institutes, and professional organizations involved with RWE. Articles were included if: (1) they discussed factors or contexts that impact whether RWE could be necessary or desirable in regulatory decision making; (2) focused on pharmacological or biological interventions in humans; and (3) considered decision making in Europe or North America, or without a focus on a specific region. We included 118 articles in the scoping review. Two major themes and six subthemes were identified. The first theme concerns questions addressable with RWE, with subthemes epidemiology and benefit-risk assessment. The second theme concerns contextual factors, with subthemes feasibility, ethical considerations, limitations of available evidence, and disease and treatment-specific aspects. Collectively, these themes encompassed 43 factors influencing the need for RWE in regulatory decisions. Although single factors may not make RWE fully necessary, their cumulative influence could make RWE essential and pivotal in regulatory decision making. This overview contributes to ongoing discussions emphasizing the nuanced interplay of factors influencing the necessity or desirability of RWE to inform regulatory decision making.

Metabolic Nanoregulator Remodels Gut Microenvironment for Treatment of Inflammatory Bowel Disease.

Inflammatory bowel disease (IBD) is strongly related to the occurrence of accumulation of toxic reactive oxygen species (ROS), inflammation of the mucosa, and an imbalance of intestinal microbes. However, current treatments largely focus on a single factor, yielding unsatisfactory clinical outcomes. Herein, we report a biocompatible and IBD-targeted metabolic nanoregulator (TMNR) that synergistically regulates cellular and bacterial metabolism. The TMNR comprises a melanin-gallium complex (MNR) encapsulated within a thermosensitive and colitis-targeting hydrogel, all composed of natural and FDA-approved components. The TMNR confers superior broad-spectrum antioxidant properties, effectively scavenging reactive oxygen species (ROS) and blocking inflammatory signaling pathways. The presence of Ga3+ in TMNR selectively disrupts iron metabolism in pathogenic microorganisms due to its structural resemblance to the iron atom. Additionally, incorporating a thermosensitive injectable hydrogel enables targeted delivery of TMNR to inflammatory regions, prolonging their retention time and providing a physical barrier function for optimizing IBD treatment efficacy. Collectively, TMNR effectively modulates the redox balance of inflamed colonic epithelial tissue and disrupts iron metabolism in pathogenic microorganisms, thereby eliminating inflammation and restoring intestinal homeostasis against IBD. Hence, this work presents a comprehensive approach for precise spatiotemporal regulation of the intestinal microenvironmental metabolism for IBD treatment.

Development and Preliminary Validation of a Novel Convolutional Neural Network Model for Predicting Treatment Response in Patients with Unresectable Hepatocellular Carcinoma Receiving Hepatic Arterial Infusion Chemotherapy.

The goal of this study was to evaluate the performance of a convolutional neural network (CNN) with preoperative MRI and clinical factors in predicting the treatment response of unresectable hepatocellular carcinoma (HCC) patients receiving hepatic arterial infusion chemotherapy (HAIC). A total of 191 patients with unresectable HCC who underwent HAIC in our hospital between May 2019 and March 2022 were retrospectively recruited. We selected InceptionV4 from three representative CNN models, AlexNet, ResNet, and InceptionV4, according to the cross-entropy loss (CEL). We subsequently developed InceptionV4 to fuse the information from qualified pretreatment MRI data and patient clinical factors. Radiomic information was evaluated based on several constant sequences, including enhanced T1-weighted sequences (with arterial, portal, and delayed phases), T2 FSE sequences, and dual-echo sequences. The performance of InceptionV4 was cross-validated in the training cohort (n = 127) and internally validated in an independent cohort (n = 64), with comparisons against single important clinical factors and radiologists in terms of receiver operating characteristic (ROC) curves. Class activation mapping was used to visualize the InceptionV4 model. The InceptionV4 model achieved an AUC of 0.871 (95% confidence interval [CI] 0.761-0.981) in the cross-validation cohort and an AUC of 0.826 (95% CI 0.682-0.970) in the internal validation cohort; these two models performed better than did the other methods (AUC ranges 0.783-0.873 and 0.708-0.806 for cross- and internal validations, respectively; P < 0.01). The present InceptionV4 model, which integrates radiomic information and clinical factors, helps predict the treatment response of unresectable HCC patients receiving HAIC treatment.

Impact of the Structural Parameters on the Performance of a Regenerative-Type Hydrogen Recirculation Blower for Vehicular Proton Exchange Membrane Fuel Cells

The compact structure and stable performance of regenerative blowers at small flow rates render them attractive for the development of hydrogen recirculation devices for fuel cells. However, its optimization of structural parameters has not been yet reported in the literature. Along these lines, in this work, a mechanistic study was carried out in terms of examining the role of the flow channel structure on the performance of a regenerative-type hydrogen recirculation blower for the fabrication of automotive fuel cells. A three-dimensional computational fluid dynamics (CFDs) model of the regenerative blower was established, and the accuracy of the proposed model was verified through experimental data. The impact of structural parameter interactions on the performance of the regenerative blower was investigated using CFD technology, response surface methodology (RSM), and genetic algorithm (GA). First, the range of the structural parameters was selected according to the actual operation, and the influence of a single geometric factor on the efficiency was thoroughly investigated using CFD simulation. Then, a second-order regression model was successfully established using RSM. The response surface model was solved using GA to obtain the optimized geometric parameters and the reliability of the GA optimization was verified by performing CFD simulations. From our analysis, it was demonstrated that the interaction of the blade angle and impeller inner diameter has a significant impact on efficiency. The entropy generation analysis showed also that the internal flow loss of the optimized regenerative blower was significantly reduced, and the design point efficiency reached 51.7%, which was significantly improved. Our work provides a novel solution for the design of a recirculation blower and offers a reference for the optimization of regenerative-type hydrogen blowers.

Rare complication – skin atrophy – after systemic conservative therapy of infantile hemangioma

BackgroundHemangiomas, also called infantile hemangiomas (IH) or hemangiomas of infancy are the most frequently seen benign vascular tumors of infancy. Different types of hemangiomas are described in the literature. The current approach is to assess the risk and, if needed, first line treatment is to initiate systemic propranolol.Case presentationA 3-month-old Caucasian female patient was brought as an outpatient. The main complaint was an infantile hemangioma in the facial area, which as per the parents’ story appeared within a week of birth like a small reddish line and it rapidly grew. Systemic propranolol was proposed as a first-line treatment and the adverse effects were explained. The parents, afraid of the side effects, wanted to explore other possibilities such as topical timolol, however, since it had no effect, propranolol was initiated in the end. Hemangioma was completely reduced in size; however, a skin defect was detected. As per the dermatologist’s counsel, topical cream was initiated. The skin defect was reduced but not fully healed. The child is still being monitored periodically.ConclusionAfter successful treatment of hemangioma, we identified a skin defect, which was very similar to steroid-induced skin atrophy. However, we cannot attribute this to a single factor. The only thing that can be concluded is that the subject needs a thorough studying, since rate of infantile hemangioma is high, and pediatricians need a clear management strategy of how to approach skin atrophy after successfully treating the hemangioma itself.

Who benefit from adjuvant chemotherapy in stage I lung adenocarcinoma? A multi-dimensional model for candidate selection

BackgroundDespite promising overall survival of stage I lung adenocarcinoma (LUAD) patients, 10-25 % of them still went through recurrence after surgery. [1] While it is still disputable whether adjuvant chemotherapy is necessary for stage I patients. [2] IASLC grading system for non-mucinous LUAD shows that minor high-grade patterns are significant indicator of poor prognosis. [3] Other risk factors, such as, pleura invasion, lympho-vascular invasion, STAS, etc. are also related to poor prognosis. [4-6] There still lack evidence whether IASLC grade itself or together with other risk factors can guide the use of adjuvant therapy in stage I patients. In this article, we tried to establish a multi-variable recurrence prediction model for stage I LUAD patients that is able to identify candidates of adjuvant chemotherapy. MethodsWe retrospectively collected patients who underwent lung surgery from 2018.8.1 to 2018.12.31 at our institution and diagnosed with lung adenocarcinoma pT1-2aN0M0 (stage I). Clinical data, manifestation on CT scan, pathologic features, driver gene mutations and follow-up information were collected. Cox proportional hazards regression analyses were performed utilizing the non-adjuvant cohort to predict disease free survival (DFS) and a nomogram was constructed and applied to the total cohort. Kaplan-Meier method was used to compare DFS between groups. Statistical analysis was conducted by R version 3.6.3. FindingsA total of 913 stage I LUAD patients were included in this study. Median follow-up time is 48.1 months.4-year and 5-year DFS are 92.9 % and 89.6 % for the total cohort. 65 patient experienced recurrence or death. 4-year DFS are 97.0 %,94.6 % and 76.2 %, and 5-year DFS are 95.5 %, 90.0 % and 74.1 % in IASLC Grade1, 2 and 3, respectively(p < 0.0001). High-risk patients defined by single risk factors, such as, IASLC grade 3, pleura invasion, STAS, less LN resected could not benefit from adjuvant therapy. A LASSO-COX regression model was built and patients are divided into high-risk and low-risk groups. In the high-risk group, patients underwent adjuvant chemotherapy have longer DFS than those who did not (p = 0.024), while in the low-risk group, patients underwent adjuvant chemotherapy have inferior DFS than those who did not (p < 0.001). InterpretationIASLC grading is a significant indicator of DFS, however it could not guide adjuvant therapy in our stage I LUAD cohort. Growth patterns and T indicators together with other risk factors could identify high-risk patients that are potential candidate of adjuvant therapy, including some stage IA LUAD patients.

Hereditary factor X deficiency in America survey: impact on quality of life and burden of disease in patients and caregivers.

describe the diagnosis path, disease burden, and HFXD impact on quality of life (QoL) in patients and caregivers.This was a prospective, cross-sectional, web-based survey of patients with HFXD and caregivers addressing the patient/caregiver experience, QoL, humanistic and unmet needs.Thirty patients and 38 caregivers completed the survey with mean ages 24.7 and 44.6 years, respectively. Mean age at diagnosis was 4.1 years. The diagnostic process was somewhat/very difficult for 23% of patients and 26% of caregivers. Approximately half (53%) received single factor replacement (SFR) as prophylaxis or on-demand. Most patients (71%) reported regular prophylaxis treatment. Over one-fourth (27%) reported treatment with fresh frozen plasma. Bleeding episodes were less common in patients using SFR versus non-SFR: three bleeds or fewer were reported by 92% SFR and 75% non-SFR patients. HFXD patients reported low well being in work/school/social activities with mean HFXD-adapted Hemophilia Well being Index. Patient symptoms negatively impacted caregiver burden with a mean HFXD-adapted Hemophilia Caregiver Index (±SD) of 15.9 (4.6), but also unexpectedly had a positive impact on self-worth and inner strength.To our knowledge, this is the first study to assess patient and caregiver burden of HFXD and impact on QoL. Improvements in symptom recognition, prompt diagnosis, and adherence to expert recommendations for treatment could improve QoL and decrease burden on HFXD patients and caregivers.

Production, physico-chemical properties and antioxidant activity of melanin from Annulohypoxylon stygium (Lév.) Y.M. Ju, J.D. Rogers and H.M. Hsieh

To obtain higher melanin production in liquid culture, culture conditions of Annulohypoxylon stygium (Lév.) Y.M. Ju, J.D. Rogers and H.M. Hsieh were optimised. The results showed that using single factor experiment and orthogonal test, the optimised production of melanin reached 2.20 g/L, which was 2.06 times higher than that of the control group. In addition, it was speculated that A. stygium melanin (AsM) was 3,4-dihydroxyphenylalanine (DOPA) melanin and showed an amorphous irregular structure. Moreover, it had good solubility in alkaline solution. AsM showed good antioxidant activity at a concentration of 500 mg/L, with DPPH, ABTS and OH radicals scavenging activities of 90.83%, 75.36% and 70.90%, respectively. AsM prevented alcohol-induced oxidative damage and oxidative stress in HepG2 cells by inhibiting the decrease of antioxidant key enzyme activity under alcohol stimulation. It was proved to have a great potential for application as a natural antioxidant and a substitute for synthetic pigments.

Effects of Dosing and Mechanical Activation on the Performance of Reservoir Sediment-Cement Composite Cementitious Material

To solve the problem of reservoir sediment accumulation, this paper intends to study the feasibility of preparing reservoir sediment-cement composite cementitious material by partially replacing cement with reservoir sediment. Using the single factor test method, the replacement rate of reservoir sediment and mechanical activation time were selected as variables to explore the effects of water requirement of normal consistency, setting time, mortar fluidity, and mechanical properties of mortar specimens. The results show that with the increase of sediment replacement rate, the water requirement of normal consistency of composite cementitious material paste increases, the setting time increases, the fluidity of mortar decreases, and the mechanical properties of mortar specimens decrease significantly. With the increase of mechanical activation time, the water requirement of normal consistency decreases, the setting time decreases, the fluidity of mortar increases, and the mechanical properties of the mortar specimen increase. The microcosmic results show that mechanical activation can promote the formation of C-S-H gel in reservoir sediment, and fill each other with unreacted reservoir sediment particles, resulting in a denser microstructure. The purpose of this paper is to provide theoretical support for the preparation of reservoir mud-cement composite cementitious material.

Enhancing the physical properties of cemented ultrafine tailings backfill (CUTB) with fiber and rice husk ash: Performance, mechanisms, and optimization

A series of experiments was conducted to study the performance and mechanisms of Cemented Ultrafine Tailings Backfill (CUTB). Firstly, the optimum fiber type was selected by single factor multilevel test. Secondly, the effects of cement content, rice husk ash content, fiber content and fiber length on backfill properties were analyzed by orthogonal test and microstructure test, and the influence mechanism of fiber and rice husk ash content was revealed. Finally, fuzzy mathematics theory is used to optimize the ratio parameters. The results show, compared to glass and basalt fiber, polypropylene fiber yields the most substantial enhancement in backfill strength. The increase of cement content, polypropylene fiber content and length can reduce slump, but the change of rice husk ash content has no obvious effect. Increased cement or fiber content effectively restrained the formation of primary fractures in CUTB, thus enhancing its integrity. Adding an optimal dosage range of 0–4 % of rice husk ash boosted the early compressive strength, albeiting at the expense of later compressive strength. Fiber addition with the optimum content range between 0.1 and 0.4 % enhanced the strengthening effect of cement content on compressive strength. Fiber primarily enhances the macroscopic strength of backfill through the dispersion and co-loading of forces, whereas rice husk ash enhances strength by optimizing void structure distribution. The optimal ratio parameters of a cement content of 310 kg/m³, rice husk ash content of 8.0 %, fiber content of 0.4 %, and fiber length of 9 mm were proposed finally.

Multiscale Analysis for Identifying the Impact of Human and Natural Factors on Water-Related Ecosystem Services

Accurately identifying and obtaining changes in ecosystem drivers and the spatial heterogeneity of their impacts on ecosystem services can provide comprehensive support information for ecological governance. In this study, we investigate the changes in the relationship between human and natural factors and water-related ecosystem services (WESs) in different sub-watersheds across various time periods, focusing on four aspects: single-factor effect, nonlinear effect, interactive effects, and spatial characteristics. Taking the southern basins, which have complex topographic, climatic, and economic characteristics, as a study area, the study area was divided into four sub-basins with different characteristics. WESs of water yield, soil conservation, and water purification were quantified using the InVEST model for five periods from 2000 to 2020, and the OPGD and MGWR models were integrated to assess the impacts of 15 factors on WESs and their spatial characteristics. The results show the following: (1) After comparing the data over multiple time periods, climate factors such as precipitation (0.4033) are the primary factors affecting WESs in the southern basins, and human factors such as construction area (0.0688) have a weaker influence. The direct impact of human factors on WESs is not significant in the short term but increases over time. (2) Different sub-watersheds have different impacts on WESs. For instance, human activity intensity (0.3518) is a key factor affecting WESs in the Inward Flowing Area, while precipitation is the primary factor influencing WESs in other sub-watersheds. (3) Influencing factors and WES changes are often nonlinearly correlated; however, once a certain threshold is exceeded, they may have adverse impacts on WESs. (4) When a single factor interacts with other factors, its explanatory power tends to increase. (5) Compared to traditional methods, the estimation accuracy of MGWR is higher. Intense human activities can adversely affect WESs, while abundant precipitation creates favorable conditions for the formation of WESs. Therefore, integrating long-time-series multi-remote sensing data with OPGD and MGWR models is suitable for identifying and analyzing the driving mechanisms of human and natural factors that influence changes in WESs. Against the backdrop of global change, elucidating the driving factors of ecosystem services can provide crucial insights for developing practical policies and land management applications.

Risk management opportunities in auto insurance: A focus on the value of vehicles

AbstractRatemaking and risk‐based pricing revolve around the value at risk, involving a tendency of higher values implying higher premiums. Traditionally, vehicle values are set at “list price” and depreciate over time on a one‐size‐fits‐all factor model. If values change over time, so should premiums, but a single factor table that only goes downward to flat is out of sorts with today. In today's transactional data streams, vehicle features, and values can be easily observed—of note, a shift in product mix that has more options and higher retained values creates a gap in actual versus traditionally expected insurance values. This gap most acutely appears at the vehicle “as built” level, which is more granular than current segmentation levels of insurance ratemaking vehicle valuation analysis. The result is leaving companies to simply raise base rates universally until they can adapt more flexible price‐to‐value methods at an “as built” price accuracy sophistication level.

Optimization of Fermentation Conditions for 2,3,5-Trimethylpyrazine Produced by Bacillus amyloliquefaciens from Daqu

2,3,5-trimethylpyrazine (TMP), as a volatile heterocyclic nitrogen compound, has a wide range of applications. To explore an efficient and environmentally friendly way to produce TMP, Bacillus strains were isolated from Daqu using traditional separation and purification methods. The fermentation products were detected by gas chromatography–mass spectrometry (GC-MS), and the species relationship of strains was analyzed by morphological and phylogenetic tree construction. Single factors were selected to optimize the fermentation process of TMP production, and a Box–Behnken design was used for response surface testing. The LC-6 strain isolated from Daqu was Bacillus amyloliquefaciens, and its fermentation products contained TMP, with a relatively high value of 0.071 ± 0.011 mg/g, indicating that the LC-6 strain was a potentially valuable TMP-producing bacterium. The results of single-factor testing showed that temperature, bottle capacity, and water addition significantly affected TMP production. Box–Behnken design and response surface analysis revealed that the order of influence on TMP yield was as follows: water addition &gt; temperature &gt; bottle capacity. Response surface optimization results showed that the optimal parameters for wheat medium fermentation were temperature 37 °C, bottle capacity 100 g/250 mL, and water addition 39 mL. Under these fermentation conditions, the average production of TMP was 0.446 ± 0.052 mg/g, which was 0.375 mg/g higher than that obtained before optimization. Compared with the previous period, the production of TMP indeed increased, providing a basis for further research on the solid-state fermentation process of TMP synthesis.

A Generative and Causal Pharmacokinetic Model for Factor VIII in Hemophilia A: A Machine Learning Framework for Continuous Model Refinement.

In rare diseases, such as hemophilia A, the development of accurate population pharmacokinetic (PK) models is often hindered by the limited availability of data. Most PK models are specific to a single recombinant factor VIII (rFVIII) concentrate or measurement assay, and are generally unsuited for answering counterfactual ("what-if") queries. Ideally, data from multiple hemophilia treatment centers are combined but this is generally difficult as patient data are kept private. In this work, we utilize causal inference techniques to produce a hybrid machine learning (ML) PK model that corrects for differences between rFVIII concentrates and measurement assays. Next, we augment this model with a generative model that can simulate realistic virtual patients as well as impute missing data. This model can be shared instead of actual patient data, resolving privacy issues. The hybrid ML-PK model was trained on chromogenic assay data of lonoctocog alfa and predictive performance was then evaluated on an external data set of patients who received octocog alfa with FVIII levels measured using the one-stage assay. The model presented higher accuracy compared with three previous PK models developed on data similar to the external data set (root mean squared error = 14.6 IU/dL vs. mean of 17.7 IU/dL). Finally, we show that the generative model can be used to accurately impute missing data (< 18% error). In conclusion, the proposed approach introduces interesting new possibilities for model development. In the context of rare disease, the introduction of generative models facilitates sharing of synthetic data, enabling the iterative improvement of population PK models.

Flexible Antibacterial Respiratory Monitoring Sensor Based on Controllable Au-Modified Surface of Highly {001} Preferred Anatase Titanium Dioxide Thin Film.

Respiratory signals are critical clinical diagnostic criteria for respiratory diseases and health conditions, and respiratory sensors play a crucial role in achieving the desired respiratory monitoring effect. High sensitivity to a single factor can improve the reliability of respiratory monitoring, and maintaining the hygiene of the sensors is also important for daily health monitoring. Herein, we propose a flexible Au-modified anatase titanium dioxide resistive respiratory sensor, which can be mechanically compliantly attached to curved surfaces for respiratory monitoring in different modalities (i.e., respiratory intensity, frequency, and rate). The uniform and preferentially oriented anatase titanium dioxide films gained by the polymer-assisted deposition technique can be fabricated on flexible substrates through a liquid-assisted transferring process. The Au modification can enhance surface plasmon resonance to facilitate the photocatalytic activity of titanium dioxide, and the optimized distribution of Au on the surface of titanium dioxide film made the sensor have an excellent antibacterial effect. The uniquely designed encapsulation can effectively control the contact between the surface of titanium dioxide films and electrodes, allowing the flexible sensor to exhibit fast response time (0.71 s) and recovery time (1.06 s) to respiratory as well as insensitivity or low sensitivity to other factors (i.e., gas composition, humidity, temperature, stress, and strain). This work provided an effective strategy for flexible wearable respiratory sensors and has great potential in daily respiratory monitoring for health management and pandemic control.

Preparation and identification of antioxidant peptides from Quasipaa spinosa skin through two-step enzymatic hydrolysis and molecular simulation

Frog skin, a by-product of Quasipaa Spinosa farming, is rich in protein and potentially a valuable raw material for obtaining antioxidant peptides. This study used papain combined with acid protease to digest frog skin in a two-step enzymatic hydrolysis method. Based on a single factor and response surface experiments, experimental conditions were optimized, and the degree of hydrolysis was 30 %. A frog skin hydrolysate (QSPH-Ⅰ-3) was obtained following ultrafiltration and gel filtration chromatography. IC50 for DPPH, ABTS, and hydroxyl radical scavenging capacities were 1.68 ± 0.05, 1.20 ± 0.14 and 1.55 ± 0.11 mg/mL, respectively. Peptide sequences (17) were analyzed and, through molecular docking, peptides with low binding energies for KEAP1 were identified, which might affect the NRF2-KEAP1 pathway. These findings suggest protein hydrolysates and antioxidant peptide derivatives might be used in functional foods.

Prognostic Significance of Biologic Factors in Patients with a Modest Radiologic Response to Neoadjuvant Treatment for Resectable and Borderline Resectable Pancreatic Cancers: Impact of the Combination Index of Sialyl-Lewis Antigen-Related Tumor Markers.

Appropriate re-evaluation after neoadjuvant treatment (NAT) is important for optimal treatment selection. Nonetheless, determining the operative eligibility of patients with a modest radiologic response remains controversial. This study aimed to assess the prognostic significance of biologic factors for patients showing a modest radiologic response to NAT and investigate the tumor markers (TMs), CA19-9 alone, DUPAN-II alone, and their combination, to create an index that combines these sialyl-Lewis antigen-related TMs associated with treatment outcomes. This study enrolled patients deemed to have a "stable disease" by RECIST classification with slight progression (tumor size increase rate, ≤20%) as their radiologic response after NAT. A sialyl-Lewis-related index (sLe index), calculated by adding one fourth of the serum DUPAN-II value to the CA19-9 value, was created. The prognostic significances of CA19-9, DUPAN-II, and the sLe index were assessed in relation to postoperative outcomes. An sLe index lower than the cutoff value (45.25) was significantly associated with favorable disease-free survival. Moreover, the post-NAT sLe index had a higher area under the curve value for recurrence within 24 months than the post-NAT levels of CA19-9 or DUPAN-II alone. Multivariable analysis showed that a post-NAT sLe index higher than 45.25 was the single independent predictive factor for recurrence within 24 months. Additional evaluation of biologic factors can potentially enhance patient selection, particularly for patients showing a limited radiologic response to NAT. The authors' index is a simple indicator for the biologic evaluation of multiple combined sialyl-Lewis antigen-related TMs and may offer a better predictive significance.

Deep eutectic solvent combined with soybean as an efficient approach to enhance the content of apigenin in the Chrysanthemum indicum L. extract

Our research aimed to cost-effectively enhance apigenin content in Chrysanthemum indicum L. extract using soybeans combined with a deep eutectic solvent. First, various deep eutectic solvents were investigated for the extraction of apigenin, followed by soybean treatment to increase aglycon levels. Combining single factor experiments with response surface methodology and optimization algorithms (genetic algorithm and particle swarm optimization), the optimal conditions were also determined. The results revealed that choline chloride-propylene glycol emerged as the optimal solvent. The optimized treatment conditions involved a temperature of 54 °C, a time of 2 h, and the addition of 3 mL of soybean extract, yielding an apigenin content of 3.380 ± 0.031 mg/g − a remarkable eightfold increase compared to the initial extract. The computational study suggested that the deep eutectic solvent may play an important role in stabilizing β-glucosidase in soybeans. However, further research is needed to scale up and fully elucidate soybean's mechanism.