QALY-type preference and willingness-to-pay among end-of-life patients with cancer treatments: a pilot study using discrete choice experiment.

PURPOSE: Quality-adjusted life-year (QALY) is a dominant measurement of health gain in economic evaluations for pricing drugs. However, end-of-life (EoL) patients' preference for QALY gains in life expectancy (LE) and quality of life (QoL) during different disease stages remains unknown and is seldom involved in decision-making. This study aims to measure preferences and willingness-to-pay (WTP) towards different types of QALY gain among EoL cancer patients. METHODS: We attributed QALY gain to four types, gain in LE and QoL, respectively, and during both progression-free survival (PFS) and post-progression survival (PPS). A discrete choice experiment including five attributes (the four QALY attributes and one cost attribute) with three levels each was developed and conducted with 85 Chinese advanced non-small cell lung cancer patients in 2022. All levels were set with QALY gain/cost synthesised from research on anti-lung cancer drugs recently listed by Chinese National Healthcare Security Administration. Each respondent answered six choice tasks in a face-to-face interview. The data were analysed using mixed logit models. RESULTS: Patients valued LE-related QALY gain in PFS most, with a relative importance of 81.8% and a WTP of $43,160 [95% CI 26,751 ~ 59,569] per QALY gain. Respondents consistently preferred LE-related to QoL-related QALY gain regardless of disease stage. Patients with higher income or lower education levels tended to pay more for QoL-related QALY gain. CONCLUSION: Our findings suggest a prioritised resource allocation to EoL-prolonging health technologies. Given the small sample size and large individual heterogeneity, a full-scale study is needed to provide more robust results.

Value of fractional-order calculus (FROC) model diffusion-weighted imaging combined with simultaneous multi-slice (SMS) acceleration technology for evaluating benign and malignant breast lesions.

BACKGROUND: This study explores the diagnostic value of combining fractional-order calculus (FROC) diffusion-weighted model with simultaneous multi-slice (SMS) acceleration technology in distinguishing benign and malignant breast lesions. METHODS: 178 lesions (73 benign, 105 malignant) underwent magnetic resonance imaging with diffusion-weighted imaging using multiple b-values (14 b-values, highest 3000 s/mm2). Independent samples t-test or Mann-Whitney U test compared image quality scores, FROC model parameters (D,, ), and ADC values between two groups. Multivariate logistic regression analysis identified independent variables and constructed nomograms. Model discrimination ability was assessed with receiver operating characteristic (ROC) curve and calibration chart. Spearman correlation analysis and Bland-Altman plot evaluated parameter correlation and consistency. RESULTS: Malignant lesions exhibited lower D, and ADC values than benign lesions (P < 0.05), with higher values (P < 0.05). In SSEPI-DWI and SMS-SSEPI-DWI sequences, the AUC and diagnostic accuracy of D value are maximal, with D value demonstrating the highest diagnostic sensitivity, while value exhibits the highest specificity. The D and combined model had the highest AUC and accuracy. D and ADC values showed high correlation between sequences, and moderate. Bland-Altman plot demonstrated unbiased parameter values. CONCLUSION: SMS-SSEPI-DWI FROC model provides good image quality and lesion characteristic values within an acceptable time. It shows consistent diagnostic performance compared to SSEPI-DWI, particularly in D and values, and significantly reduces scanning time.

Biosynthesis of silver nanoparticles using Burkholderia contaminans ZCC and mechanistic analysis at the proteome level.

The biogenic synthesis of silver nanoparticles (AgNPs) by microorganisms has been a subject of increasing attention. Despite extensive studies on this biosynthetic pathway, the mechanisms underlying the involvement of proteins and enzymes in AgNPs production have not been fully explored. Herein, we reported that Burkholderia contaminans ZCC was able to reduce Ag+ to AgNPs with a diameter of (10±5) nm inside the cell. Exposure of B. contaminans ZCC to Ag+ ions led to significant changes in the functional groups of cellular proteins, with approximately 5.72% of the (C-OH) bonds being converted to (C-C/C-H) (3.61%) and CO (2.11%) bonds, and 4.52% of the CO (carbonyl) bonds being converted to (C-OH) bonds. Furthermore, the presence of Ag+ and AgNPs induced the ability of extracellular electron transfer for ZCC cells via specific membrane proteins, but this did not occur in the absence of Ag+ ions. Proteomic analysis of the proteins and enzymes involved in heavy metal efflux systems, protein secretion system, oxidative phosphorylation, intracellular electron transfer chain, and glutathione metabolism suggests that glutathione S-transferase and ubiquinol-cytochrome c reductase iron-sulfur subunit play importance roles in the biosynthesis of AgNPs. These findings contribute to a deeper understanding of the functions exerted by glutathione S-transferase and ferredoxin-thioredoxin reductase iron-sulfur subunits in the biogenesis of AgNPs, thereby hold immense potential for optimizing biotechnological techniques aimed at enhancing the yield and purity of biosynthetic AgNPs.

Artificial intelligence in clinical decision support systems for oncology.

Artificial intelligence (AI) has been widely used in various medical fields, such as image diagnosis, pathological classification, selection of treatment schemes, and prognosis analysis. Especially in the image-aided diagnosis of tumors, the cooperation of human-computer interactions has become mature. However, the ethics of the application of AI as an emerging technology in clinical decision-making have not been fully supported, so the clinical decision support system (CDSS) based on AI technology has not fully realized human-computer interactions in clinical practice as the image-aided diagnosis system. The CDSS was currently used and promoted worldwide including Watson for Oncology, Chinese society of clinical oncology-artificial intelligence (CSCO AI) and so on. This paper summarized the applications and clarified the principle of AI in CDSS, analyzed the difficulties of AI in oncology decisions, and provided a reference scheme for the application of AI in oncology decisions in the future.

Atg4b Overexpression Extends Lifespan and Healthspan in Drosophila melanogaster.

Autophagy plays important but complex roles in aging, affecting health and longevity. We found that, in the general population, the levels of ATG4B and ATG4D decreased during aging, yet they are upregulated in centenarians, suggesting that overexpression of ATG4 members could be positive for healthspan and lifespan. We therefore analyzed the effect of overexpressing Atg4b (a homolog of human ATG4D) in Drosophila, and found that, indeed, Atg4b overexpression increased resistance to oxidative stress, desiccation stress and fitness as measured by climbing ability. The overexpression induced since mid-life increased lifespan. Transcriptome analysis of Drosophila subjected to desiccation stress revealed that Atg4b overexpression increased stress response pathways. In addition, overexpression of ATG4B delayed cellular senescence, and improved cell proliferation. These results suggest that ATG4B have contributed to a slowdown in cellular senescence, and in Drosophila, Atg4b overexpression may have led to improved healthspan and lifespan by promoting a stronger stress response. Overall, our study suggests that ATG4D and ATG4B have the potential to become targets for health and lifespan interventions.

How is Visual Attention Influenced by Text Guidance? Database and Model.

The analysis and prediction of visual attention have long been crucial tasks in the fields of computer vision and image processing. In practical applications, images are generally accompanied by various text descriptions, however, few studies have explored the influence of text descriptions on visual attention, let alone developed visual saliency prediction models considering text guidance. In this paper, we conduct a comprehensive study on text-guided image saliency (TIS) from both subjective and objective perspectives. Specifically, we construct a TIS database named SJTU-TIS, which includes 1200 text-image pairs and the corresponding collected eye-tracking data. Based on the established SJTU-TIS database, we analyze the influence of various text descriptions on visual attention. Then, to facilitate the development of saliency prediction models considering text influence, we construct a benchmark for the established SJTU-TIS database using state-of-the-art saliency models. Finally, considering the effect of text descriptions on visual attention, while most existing saliency models ignore this impact, we further propose a text-guided saliency (TGSal) prediction model, which extracts and integrates both image features and text features to predict the image saliency under various text-description conditions. Our proposed model significantly outperforms the state-of-the-art saliency models on both the SJTU-TIS database and the pure image saliency databases in terms of various evaluation metrics. The SJTU-TIS database and the code of the proposed TGSal model will be released at: https://github.com/IntMeGroup/TGSal.

Unveiling the magic of mega-city block environments: investigating the intriguing mechanisms shaping children's spontaneous play preferences.

Introduction: This study delves into the spatial preferences of children for play spaces within high-density urban block environments, specifically targeting the area of Baihua Second Road in Shenzhen, China. Methods: Recognizing the critical role of play in children's development, and the unique challenges posed by dense urban settings, this research employs multiclass logistic regression models and negative binomial regression models to construct a detailed mathematical analysis of neighborhood spatial elements and children's play space preferences. Data was meticulously gathered through both objective observations of 14 different types of spaces within the block, and subjective assessments via children's responses to a series of environment photos, capturing the essence of over 3,000 child participants' interactions and choices. Results: Key findings reveal a pronounced preference among children for soft facility features and visually appealing spatial experiences, suggesting a nuanced understanding of play space needs beyond traditional playground designs. Notably, the study identifies that while cartoon-style designs in play facilities might increase moderate attractiveness, ordinary designs hold broader appeal, indicating a preference for diversity in play space aesthetics. These insights offer profound implications for urban planners and designers, advocating for a child-centered approach in the creation of urban play environments that prioritize aesthetic diversity, and the integration of natural elements. Conclusion: Moreover, the study situates Baihua Second Road as a paradigmatic case, illustrating the methodology and analytical framework applied in addressing the complex interplay between children's play preferences and urban spatial configurations. By incorporating a comprehensive data-driven analysis, this research contributes significantly to the discourse on child-friendly urban design, offering valuable strategies for cultivating inclusive and engaging urban play spaces for children amidst the constraints of high-density city living.

Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment Study.

BACKGROUND: Artificial intelligence (AI)-powered digital therapies that detect methamphetamine cravings via consumer devices have the potential to reduce health care disparities by providing remote and accessible care solutions to communities with limited care solutions, such as Native Hawaiian, Filipino, and Pacific Islander communities. However, Native Hawaiian, Filipino, and Pacific Islander communities are understudied with respect to digital therapeutics and AI health sensing despite using technology at the same rates as other racial groups. OBJECTIVE: In this study, we aimed to understand the feasibility of continuous remote digital monitoring and ecological momentary assessments in Native Hawaiian, Filipino, and Pacific Islander communities in Hawaii by curating a novel data set of longitudinal Fitbit (Fitbit Inc) biosignals with the corresponding craving and substance use labels. We also aimed to develop personalized AI models that predict methamphetamine craving events in real time using wearable sensor data. METHODS: We will develop personalized AI and machine learning models for methamphetamine use and craving prediction in 40 individuals from Native Hawaiian, Filipino, and Pacific Islander communities by curating a novel data set of real-time Fitbit biosensor readings and the corresponding participant annotations (ie, raw self-reported substance use data) of their methamphetamine use and cravings. In the process of collecting this data set, we will gain insights into cultural and other human factors that can challenge the proper acquisition of precise annotations. With the resulting data set, we will use self-supervised learning AI approaches, which are a new family of machine learning methods that allows a neural network to be trained without labels by being optimized to make predictions about the data. The inputs to the proposed AI models are Fitbit biosensor readings, and the outputs are predictions of methamphetamine use or craving. This paradigm is gaining increased attention in AI for health care. RESULTS: To date, more than 40 individuals have expressed interest in participating in the study, and we have successfully recruited our first 5 participants with minimal logistical challenges and proper compliance. Several logistical challenges that the research team has encountered so far and the related implications are discussed. CONCLUSIONS: We expect to develop models that significantly outperform traditional supervised methods by finetuning according to the data of a participant. Such methods will enable AI solutions that work with the limited data available from Native Hawaiian, Filipino, and Pacific Islander populations and that are inherently unbiased owing to their personalized nature. Such models can support future AI-powered digital therapeutics for substance abuse. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46493.

Rational design of bioengineered recombinant collagen-like protein enhances GelMA hydrogel for diabetic wound healing.

Gelatin methacryloyl (GelMA) holds significant potential in tissue engineering; however, its clinical applications are often constrained by its lack of functional groups. To overcome this limitation, recombinant proteins with multiple biofunctional domains present a promising strategy for GelMA functionalization, enhancing its biological properties. In this study, we developed a rationally designed recombinant collagen-like protein (RC) engineered with multiple biofunctional domains, which demonstrated the ability to upregulate collagen 1α (COL-1α) expression in NIH-3 T3 cells. By utilizing EDC/NHS chemistry, the purified RC was conjugated to GelMA, resulting in GelMA-RC hydrogels that significantly improved cell viability and migration compared to unmodified GelMA. Subsequent in vivo studies showed that RC-modified GelMA exhibited superior wound healing efficacy, largely attributed to enhanced expression of cytokeratin-14 (CK-14) and COL-1α. These findings underscore the potential of RC-functionalized GelMA in promoting diabetic wound repair and suggest broader applicability for functionalizing other biomaterials.

Thiolation-Based Protein-Protein Hydrogels for Improved Wound Healing.

The limitations of protein-based hydrogels, including their insufficient mechanical properties and restricted biological functions, arise from the highly specific functions of proteins as natural building blocks. A potential solution to overcome these shortcomings is the development of protein-protein hydrogels, which integrate structural and functional proteins. In this study, a protein-protein hydrogel formed by crosslinking bovine serum albumin (BSA) and a genetically engineered intrinsically disordered collagen-like protein (CLP) through Ag─S bonding is introduced. The approach involves thiolating lysine residues of BSA and crosslinking CLP with Ag+ ions, utilizing thiolation of BSA and the free-cysteines of CLP. The resulting protein-protein hydrogels exhibit exceptional properties, including notable plasticity, inherent self-healing capabilities, and gel-sol transition in response to redox conditions. In comparison to standalone BSA hydrogels, these protein-protein hydrogels demonstrate enhanced cellular viability, and improved cellular migration. In vivo experiments provide conclusive evidence of accelerated wound healing, observed not only in murine models with streptozotocin (Step)-induced diabetes but also in zebrafish models subjected to UV-burn injuries. Detailed mechanistic insights, combined with assessments of proinflammatory cytokines and the expression of epidermal differentiation-related proteins, robustly validate the protein-protein hydrogel's effectiveness in promoting wound repair.

Coral skeletons reveal the impacts of oil pollution on seawater chemistry in the northern South China Sea.

Oil pollution can release trace metals (TMs) with cumulative toxicity into seawater, harming marine ecosystems in the long term. However, the lack of studies has inhibited our understanding of the effects and mechanisms of oil pollution on TMs in seawater. Hence, we investigated the 10-year monthly variation of TMs in Porites coral skeletons from the northern South China Sea (SCS), complemented by spatial distribution of TMs in seawater, sediments and characterization of TMs in fuel oil. The results of principal component-multivariate linear regression showed that the total contribution of oil pollution as a source to TMs in surface seawater was 77.2%, where the residence time of TMs (Ni, V, Cr, Co, Cu, Mn, Fe, and Mo) released from oil spills in surface seawater was approximately 1.4 months. Due to the geochemical nature of the metals, their seasonal variations are controlled by tropical cyclones (Ni, V, Cr, Co, Cu, Mn, Fe, and Mo), winter monsoons (Pb, Cd, Ba, and Zn) and sea surface temperature (Sr). This study shows that coral skeletons can be used as a new tool to study marine oil pollution. This provides valuable reference data for accurately identifying and quantifying the effects of oil pollution on TMs in seawater from a spatial and temporal perspective.

Interannual variation and sources identification of heavy metals in seawater near shipping lanes: Evidence from a coral record from the northern South China Sea.

Heavy metal pollution is a serious environmental problem in the marine ecosystem. Thereinto, marine transportation activities have gradually become an important source of heavy metals in seawater. However, the lack of studies on the temporal dynamics of seawater heavy metals in marine shipping areas has hindered our understanding of the sources and transport mechanisms of heavy metals in seawater of hectic shipping waters. Therefore, we investigated the interannual resolution variation of heavy metals in Porites lutea skeletons during the past 32 years under the rapid development of the shipping sector near Weizhou Island from the northern South China Sea. Results show that most heavy metal concentrations with higher coefficients of variation (≥100 %) in the Porites coral skeletons were higher than those in the uncontaminated or less anthropogenic waters. The results of principal component analysis and multiple linear regression showed that the interannual variations of Ni, V, Cr, Co, Zn, Cu, Mn, Fe and Mo were mainly impacted by marine oil extraction and oil spills generated by shipping activities, accounting for 51.58 %. The effect of sea surface temperature accounts for 13.44 %, and controls the interannual variations of Ba and Sr. The effect of industrial pollution accounts for 13.27 %, and explains the interannual variations of Cd and Y. The fuel consumption of marine shipping accounted for 8.76 %, explaining the interannual variations of Pb. The total contribution of anthropogenic activities reached 73.61 %. The interannual variation of heavy metals indicates that hectic marine shipping activities are the dominant cause of Ni, V, Pb, Cr, Co, Zn, Cu, Mn, Fe and Mo input to surface seawater around Weizhou Island. This provided valuable data for understanding the temporal dynamics and potential sources of heavy metals in the marine environment by using coral skeletons as a high-resolution recording vehicle.

Protein Restriction Effects on Healthspan and Lifespan in Drosophila melanogaster Are Additive With a Longevity-Promoting Diet.

Aging of the organism is associated diminished response to external stimuli including weakened immune function, resulting in diseases that impair health and lifespan. Several dietary restriction modalities have been reported to improve health and lifespan in different animal models, but it is unknown whether any of the lifespan-extending dietary treatments could be combined to achieve an additive effect. Here, we investigated the effects of halving amino acids components in the HUNTaa diet, a synthetic medium known to extend lifespan in Drosophila. We found that dietary restriction by halving the entire amino acid components (DR group) could further extend lifespan and improve resistance to oxidative stress, desiccation stress, and starvation than flies on HUNTaa diet alone (wt group). Transcriptome analysis of Drosophila at 40, 60, and 80 days of age revealed that genes related to cell proliferation and metabolism decreased with age in the wt group, whereas background stimulus response and amino acid metabolism increased with age. However, these trends differed in the DR group, that is, the DR flies had downregulated stress response genes, including reduced background immune activation. Infection experiments demonstrated that these flies survived longer after feeding infection with Serratia marcescens and Enterococcus faecalis, suggesting that these flies had stronger immune function, and therefore reduced immune senescence. These results demonstrated that halving the entire amino acid components in the HUNTaa diet further extended health and lifespan and suggested that lifespan-extending diet and dietary restriction treatment could be combined to achieve additive beneficial results.

Design, Analysis, and Real-Time Simulation of a 3D Soft Robotic Snake.

Snakes are a remarkable source of inspiration for mobile search-and-rescue robots. Their unique slender body structure and multiple modes of locomotion are well-suited to movement in narrow passages and other difficult terrain. The design, manufacturing, modeling, and control techniques of soft robotics make it possible to imitate the structure, mechanical properties, and locomotion gaits of snakes, opening up new possibilities in robotics research. Building on our track record of contributions in this area, this article presents a soft robotic snake made of modules that can actively deform in three-dimensional (3D) and rigorously studies its performance under a range of conditions, including gait parameters, number of modules, and differences in the environment. A soft 3D-printed wave spring sheath is developed to support the robot modules, increasing the snake's performance in climbing steps threefold. Finally, we introduce a simulator and a numerical model to provide a real-time simulation of the soft robotic snake. With the help of the real-time simulator, it is possible to develop and test new locomotion gaits for the soft robotic snake within a short period of time, compared with experimental trial and error. As a result, the soft robotic snake presented in this article is able to locomote on different surfaces, perform different bioinspired and custom gaits, and climb over steps.

Genetically encoded in situ gelation redox-responsive collagen-like protein hydrogel for accelerating diabetic wound healing.

Genetically encoded collagen-like protein-based hydrogels have demonstrated remarkable efficacy in promoting the healing process in diabetic patients. However, the current methods for preparing these hydrogels pose significant challenges due to harsh reaction conditions and the reliance on chemical crosslinkers. In this study, we present a genetically encoded approach that allows for the creation of protein hydrogels without the need for chemical additives. Our design involves the genetic encoding of paired-cysteine residues at the C- and N-terminals of a meticulously engineered collagen-like recombination protein. The protein-based hydrogel undergoes a gel-sol transition in response to redox stimulation, achieving a gel-sol transition. We provide evidence that the co-incubation of the protein hydrogel with 3T3 cells not only enhances cell viability but also promotes cell migration. Moreover, the application of the protein hydrogel significantly accelerates the healing of diabetic wounds by upregulating the expression of collagen-1α (COL-1α) and Cytokeratin 14 (CK-14), while simultaneously reducing oxidant stress in the wound microenvironment. Our study highlights a straightforward strategy for the preparation of redox-responsive protein hydrogels, removing the need for additional chemical agents. Importantly, our findings underscore the potential of this hydrogel system for effectively treating diabetic wounds, offering a promising avenue for future therapeutic applications.

Antioxidant CeO2 doped with carbon dots enhance ammonia production by an electroactive Azospirillum humicireducens SgZ-5T.

Microbial nitrogen fixation is a fundamental process in the nitrogen cycle, providing a continuous supply of biologically available nitrogen essential for life. In this study, we combined cerium oxide-doped carbon dots (CeO2/CDs) with electroactive nitrogen-fixing bacterium Azospirillum humicireducens SgZ-5T to enhance nitrogen fixation through ammonium production. Our research demonstrates that treatment of SgZ-5T cells with CeO2/CDs (0.2 mg mL-1) resulted in a 265.70% increase in ammonium production compared to SgZ-5T cells alone. CeO2/CDs facilitate electron transfer in the biocatalytic process, thereby enhancing nitrogenase activity. Additionally, CeO2/CDs reduce the concentration of reactive oxygen species in SgZ-5T cells, leading to increased ammonium production. The upregulation of nifD, nifH and nifK gene expression upon incorporation of CeO2/CDs (0.2 mg mL-1) into SgZ-5T cells supports this observation. Our findings not only provide an economical and environmentally friendly approach to enhance biological nitrogen fixation but also hold potential for alleviating nitrogen fertilizer scarcity.

Percentage of Tumor Invasion at Pretreatment High-Resolution Magnetic Resonance Imaging: Associating With Aggressive and Tumor Response in Chinese T3 Rectal Cancer-Preliminary Results.

Purpose: The purpose of the study was to assess the ability of percentage of tumor invasion (PTI) of T3 rectal cancer on pretreatment MRI as an imaging biomarker to reflect aggressiveness and to predict tumor response after neoadjuvant chemoradiation (NCRT) in Chinese population. Methods: A total of 107 Chinese rectal cancer patients who underwent pretreatment MRI staging as T3 were included. The extramural depth of tumor invasion (EMD), the distance between outer border of muscularis propria (MP) and mesorectal fascia (MRF) we called "thickness of the mesorectum (TM)") at the same slice and direction were measured at pretreatment MRI, and PTI was equal to EMD/TM, was calculated. The EMD and PTI of subgroups based on pretreatment CEA, CA19-9 levels; N category and pathological complete response (pCR) were compared. The parameters, which described tumor invasion, were compared between pCR and non-pCR group. Student t-tests and logistic analysis were applied. Results: The pretreatment PTI was higher in CEA ≥5.2 ng/ml patients (58.52% ± 27.68%) than in CEA <5.2 ng/ml patients (47.27% ± 24.15%) (p = 0.034). The pretreatment EMD in non-pCR group (7.21 ± 2.85 mm) was higher than in pCR group (6.14 ± 3.56 mm) (p = 0.049). The pretreatment PTI in non-pCR group (57.4% ± 26.4%) was higher than in pCR group (47.3% ± 29.1%) (p = 0.041). Compared with patients with PTI ≥50%, MRF (+), more patients with PTI <50%, MRF (-) showed pCR (OR = 8.44, p = 0.005; OR = 6.32, p = 0.024). Conclusion: The PTI obtained at pretreatment MRI may serve as an imaging biomarker to reflect tumor aggressiveness and predict which T3 rectal cancer patients may benefit from NCRT in Chinese population.

Ecological health evaluation of rivers based on phytoplankton biological integrity index and water quality index on the impact of anthropogenic pollution: A case of Ashi River Basin.

Based on the phytoplankton community matrices in the Ashi River Basin (ASRB), Harbin city, we developed an evaluation method using the phytoplankton index of biotic integrity (P-IBI) to evaluate ecological health while investigating the response of P-IBI to anthropogenic activities. We compared the effectiveness of P-IBI with that of the water quality index (WQI) in assessing ecological health. Between April and October 2019, phytoplankton and water samples were collected at 17 sampling sites in the ASRB on a seasonal basis. Our results showed that seven phyla were identified, comprising 137 phytoplankton species. From a pool of 35 candidate indices, five critical ecological indices (Shannon-Wiener index, total biomass, percentage of motile diatoms, percentage of stipitate diatom, and diatom quotient) were selected to evaluate the biological integrity of phytoplankton in the ASRB. The ecological status of the ASRB as measured by the P-IBI and WQI exhibited a similar spatial pattern. It showed a spatial decline in ecological status in accordance with the flow of the river. These results highlighted that P-IBI was a reliable tool to indicate the interaction between habitat conditions and environmental factors in the ASRB. Our findings contribute to the ecological monitoring and protection of rivers impacted by anthropogenic pollution.

CAR cell design strategies in solid tumors.

In addition to chimeric antigen receptor (CAR)-αß T-cell therapy, CAR-NK, CAR-NKT, CAR-M and CAR-γδ T-cell therapy have gradually been applied to the treatment of solid tumors. Compared to hematological tumors, solid tumors have the characteristics of strong tumor heterogeneity, limited target antigen selection, and low T-cell infiltration to build immunosuppressive tumor microenvironment. These features would present great obstacles to CAR cell therapy. This paper comprehensively analyzed the application of different CAR cells to solid tumors and summarized the design principles of different CAR cells to provide the direction for the development of CAR cell therapy in solid tumors.

Preparation and evaluation of novel bio-based Bis-GMA-free dental composites with low estrogenic activity.

OBJECTIVE: Although bisphenol Aglycidyl methacrylate (Bis-GMA) are widely used in the dental composite, its raw materials include the petroleum-based product bisphenol A (BPA) with high estrogenic activity (EA). In this study, two new BPA-free dimethacrylate monomers from bio-based material creosol were synthesized and evaluated. METHODS: The renewable bisphenol monomer 5, 5'-methylenedicreosol (BCF) was prepared from bio-based material creosol. By the human breast cancer cells (MCF-7 cells) proliferation assay, a risk assessment of BCF was performed to determine if BCF possessed reduced EA in comparison to BPA. Then, the novel monomers 5, 5'-methylenedicreosol diglycidyl ether diacrylate (BCF-EA) and 5, 5'-methylenedicreosol diglycidyl ether dimethacrylate (BCF-GMA) were synthesized from BCF with epichlorohydrin and (meth)acrylate. All products were investigated by 1H NMR and FT-IR spectra. The control resin was a mixture based on Bis-GMA and tri(ethyleneglycol) dimethacrylate (TEGDMA) with a weight ratio of 5:5 (5B5T). Similarly, experimental resin matrix was a mixture based on BCF-EA/TEGDMA (5E5T) and BCF-GMA/TEGDMA (5G5T). And their corresponding composites were then prepared with corresponding resin matrices and hybrid SiO2 (5E5TC, 5G5TC and 5B5TC). The properties of these composites were investigated according to the standard or referenced methods. Each sample was evaluated for double bond conversion (DC), shrinkage stress (SS) and volumetric polymerization shrinkage (VS). Water sorption (WS), water solubility (SL), mechanical properties and cytotoxicity were also measured. RESULTS: 1H NMR and FT-IR spectra confirmed the chemical structure of each monomer. EA test revealed that bio-based bisphenol monomer BCF as the precursor of BCF-EA and BCF-GMA showed lower EA than BPA. Cured resin matrix: Both 5E5T and 5G5T had nearly the same DC (p < 0.05), which was higher than 5B5T (p < 0.05); 5E5T and 5G5T had lower VS, SL and cytotoxicity than 5B5T (p < 0.05); mechanical properties of 5E5T and 5G5T were all better than those of 5B5T (p < 0.05). Cured composite: There was no significant difference in conversion (p < 0.05); 5E5TC and 5G5TC had significantly lower VS (p < 0.05); WS of 5E5TC and 5G5TC were similar (p < 0.05), but higher compared to 5B5TC (p < 0.05); 5E5TC and 5G5TC had the deeper depth of cure (p > 0.05); before water immersion, there was no significant difference in flexural strength between 5E5TC and 5G5TC (p > 0.05), and higher than 5B5TC (p < 0.05); 5E5TC and 5G5TC showed less cytotoxicity than 5B5TC (p < 0.05). SIGNIFICANCE: The new BPA-free di(meth)acrylates are promising photocurable dental monomers owning to bio-based raw material, high degree of conversion coupled with low curing shrinkage and good mechanical properties. Therefore, BCF-EA and BCF-GMA has a potential to be used as the substitution for Bis-GMA to prepare Bis-GMA-free dental composite.