Mussel-Inspired, Self-Healing, Highly Effective Fully Polymeric Fire-Retardant Coatings Enabled by Group Synergy.

Fire-retardant coatings represent a universal cost-effective approach to providing fire protection for various substrates without compromising substrates' bulk properties. However, it has been attractive yet highly challenging to create waterborne polymeric fire-retardant coatings combining high-efficiency, generally strong adhesion, and self-repairability due to a lack of rational design principles. Inspired by mussel's unique adhesive, self-healing, and char-forming mechanisms, herein, a "group synergy" design strategy is proposed to realize the combination of self-healing, strong adhesion, and high efficiency in a fully polymeric fire-retardant coating via multiple synergies between catechol, phosphonic, and hydroxyethyl groups. As-created fire-retardant coating exhibits a rapid room-temperature self-healing ability and strong adhesion to (non)polar substrates due to multiple dynamic non-covalent interactions enabled by these groups. Because these functional groups enable the formation of a robust structurally intact yet slightly expanded char layer upon exposure to flame, a 200 µm-thick such coating can make extremely flammable polystyrene foam very difficult to ignite and self-extinguishing, which far outperforms previous strategies. Moreover, this coating can provide universal exceptional fire protection for a variety of substrates from polymer foams, and timber, to fabric and steel. This work presents a promising material design principle to create next-generation sustainable high-performance fire-retardant coatings for general fire protection.

Selective and effective suppression of pancreatic cancer through MNK inhibition.

Objective: The study aimed to explore the role of the Wnt/ß-catenin signaling pathway in pancreatic cancer progression and chemoresistance, with a focus on identifying specific factors that distinguish between normal and tumor cells, thereby offering potential therapeutic targets.Materials and Methods: We analyzed levels of total and phosphorylated eukaryotic translation initiation factor 4E (eIF4E) and ß-catenin in pancreatic cancer and normal pancreatic tissues. Functional assays were used to assess the impact of eIF4E phosphorylation on ß-catenin signaling, cell proliferation, and chemoresistance, with MNK kinase involvement determined through gene depletion studies. The MNK kinase inhibitor eFT508 was evaluated for its effects on eIF4E phosphorylation, ß-catenin activation, and cell viability in both in vitro and in vivo models of pancreatic cancer.Results: Both total and phosphorylated eIF4E, along with ß-catenin, were significantly elevated in pancreatic cancer tissues compared to normal tissues. Phosphorylation of eIF4E at serine 209 was shown to activate ß-catenin signaling, enhance cell proliferation, and contribute to chemoresistance in pancreatic cancer. Importantly, these effects were dependent on MNK kinase activity. Depletion of eIF4E reduced cell viability in both pancreatic cancer and normal cells, while depletion of MNK selectively decreased viability in pancreatic cancer cells. Treatment with eFT508 effectively inhibited eIF4E phosphorylation, suppressed ß-catenin activation, and reduced pancreatic cancer cell growth and survival in vitro and in vivo, with minimal impact on normal cells.Conclusions: The MNK-eIF4E-ß-catenin axis plays a critical role in pancreatic cancer progression and chemoresistance, distinguishing pancreatic cancer cells from normal cells. Targeting MNK kinases with inhibitors like eFT508 presents a promising therapeutic strategy for pancreatic cancer, with potential for selective efficacy and reduced toxicity.

Rational Design of Oil-Resistant and Electrically Conductive Fluorosilicone Rubber Foam Nanocomposites for Sensitive Detectability in Complex Solvent Environments.

Recent years have witnessed the explosive development of highly sensitive smart sensors based on conductive polymer foam materials. However, the design and development of multifunctional polymeric foam composites as smart sensors applied in complex solvent and oil environments remain a critical challenge. Herein, we design and synthesize vinyl-terminated polytrifluoropropylmethylsiloxane through anionic ring-opening polymerization to fabricate fluorosilicone rubber foam (FSiRF) materials with nanoscale wrinkled surfaces and reactive Si-H groups via a green and rapid chemical foaming strategy. Based on the strong adhesion between FSiRF materials and consecutive oxidized ketjen black (OKB) nano-network, multifunctional FSiRF nanocomposites were prepared by a dip-coating strategy followed by fluoroalkylsilane modification. The optimized F-OKB@FSiRF nanocomposites exhibit outstanding mechanical flexibility in wide-temperature range (100 cycle compressions from -20 to 200 °C), structure stability (no detached particles after being immersed into various aqueous solutions for up to 15 days), surface superhydrophobicity (water contact angle of 154° and sliding angle of ∼7°), and tunable electrical conductivity (from 10-5 to 10-2 S m-1). Additionally, benefiting from the combined actions of multiple lines of defense (low surface energy groups, physical barriers, and "shielding effect"), the F-OKB@FSiRF sensor presents excellent anti-swelling property and high sensitivity in monitoring both large-deformation and tiny vibrations generated by knocking the beaker, ultrasonic action, agitating, and sinking objects in weak-polar or nonpolar solvents. This work conceivably provides a chemical strategy for the fabrication of multifunctional polymeric foam nanocomposite materials as smart sensors for broad applications.

Waterborne Intumescent Fire-Retardant Polymer Composite Coatings: A Review.

Intumescent fire-retardant coatings, which feature thinner layers and good decorative effects while significantly reducing heat transfer and air dispersion capabilities, are highly attractive for fire safety applications due to their effective prevention of material combustion and protection of materials. Particularly, the worldwide demand for improved environmental protection requirements has given rise to the production of waterborne intumescent fire-retardant polymer composite coatings, which are comparable to or provide more advantages than solvent-based intumescent fire-retardant polymer composite coatings in terms of low cost, reduced odor, and minimal environmental and health hazards. However, there is still a lack of a comprehensive and in-depth overview of waterborne intumescent fire-retardant polymer composite coatings. This review aims to systematically and comprehensively discuss the composition, the flame retardant and heat insulation mechanisms, and the practical applications of waterborne intumescent fire-retardant polymer composite coatings. Finally, some key challenges associated with waterborne intumescent fire-retardant polymer composite coatings are highlighted, following which future perspectives and opportunities are proposed.

Digital identification and adulteration analysis of Pulsatilla Radix and Pulsatilla Cernua based on "digital identity" and UHPLC-QTOF-MSE.

Under the background of digitalization of traditional Chinese medicine (TCM), to realize the quick identification and adulteration analysis of Pulsatilla Radix (PR), adhering to digital conviction, this study conducted UHPLC-QTOF-MSE analysis on PR and its adulterant-Pulsatilla Cernua (PC) from different batches and based on digital conversion, the shared ions were extracted from different batches of PR and PC as their "ions representation", respectively. Further, the data set of unique ions of PR relative to PC and PC relative to PR were screened out as the "digital identities" of PR and PC respectively. Further, above the "digital identities" of PR and PC were used as the benchmarks for matching and identifying to feedback give a matching credibility (MC). The results showed that based on the "digital identities" of PR and PC, the digital identification of two herbal samples can be realized efficiently and accurately at the individual level with the MC≥70.00 %, even if 5 % of PC in the mixed samples can still be identified efficiently and accurately. The study is of great practical significance for improving the identification efficiency of PR and PC, cracking down on adulterated and counterfeit drugs, and strengthening the quality control of PR. In addition, it has important reference significance for developing non-targeted digital identification of herbal medicines at the individual level based on UHPLC-QTOF-MSE and the "digital identity", which was beneficial to the construction of digital Chinese medicine and digital quality control.

The clinical effect of Dienogest on urinary and sexual symptoms in endometriosis patients.

BACKGROUND: To evaluate the effect on urinary symptoms and sexual functioning of Dienogest within a 6-month period of follow-up. METHODS: A total of 22 women who were diagnosed as having endometriosis with pelvic pain and irritative urinary symptoms were recruited in this study. The participating patients took a daily dose of 2 mg DNG and underwent outpatient visits at the beginning, 1, 2, 3 and 6 months following treatment. RESULTS: Our data showed a significant improvement of the VAS score since the 1st month till the 6th month after treatment of DNG. OABSS, UDI-6 and IIQ-7 were significantly improved after the treatment of DNG. Besides, serum estradiol was also decreased. Our data also showed that DNG treatment for 6 months did not affect FSFI score. Some patients with heavy menstruation were also improved; however, some patients with regular periods missed or dropped a period after DNG treatment, while other adverse effects were also shown. CONCLUSION: Our study demonstrated that DNG could not only alleviate endometriosis pelvic pain but reduce urinary symptoms within the 6-month follow-up as well. DNG did not affect sexual function in FSFI score, although some adverse effects were recorded.

Ultrafast Response and Threshold Adjustable Intelligent Thermoelectric Systems for Next-Generation Self-Powered Remote IoT Fire Warning.

Fire warning is vital to human life, economy and ecology. However, the development of effective warning systems faces great challenges of fast response, adjustable threshold and remote detecting. Here, we propose an intelligent self-powered remote IoT fire warning system, by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films. The flexible films, prepared by a convenient solution mixing, display p-type characteristic with excellent high-temperature stability, flame retardancy and TE (power factor of 239.7 ± 15.8 µW m-1 K-2) performances. The comprehensive morphology and structural analyses shed light on the underlying mechanisms. And the assembled TE devices (TEDs) exhibit fast fire warning with adjustable warning threshold voltages (1-10 mV). Excitingly, an ultrafast fire warning response time of ~ 0.1 s at 1 mV threshold voltage is achieved, rivaling many state-of-the-art systems. Furthermore, TE fire warning systems reveal outstanding stability after 50 repeated cycles and desired durability even undergoing 180 days of air exposure. Finally, a TED-based wireless intelligent fire warning system has been developed by coupling an amplifier, analog-to-digital converter and Bluetooth module. By combining TE characteristics, high-temperature stability and flame retardancy with wireless IoT signal transmission, TE-based hybrid system developed here is promising for next-generation self-powered remote IoT fire warning applications.

[Chemical constituents from stems and leaves of Artocarpus tonkinensis and their inhibitory effects on proliferation of synovioblasts in vitro].

The chemical constituents from the stems and leaves of Artocarpus tonkinensis in Artocarpus of Moraceae were systematically studied by means of silica gel, octadecylsilyl(ODS), and Sephadex LH-20 gel column chromatographies, as well as preparative high-performance liquid chromatography(Pre-HPLC) and a variety of chromatographic separation techniques. The spectral data and physicochemical properties of the compounds were obtained from separation and compared with those of the compounds reported in the literature. As a result, 11 compounds isolated from the 90% ethanol extract of the stems and leaves of A. tonkinensis were identified as artocatonkine(1), 5,6,7,4'-tetramethoxyflavone(2), apigenin-4'-O-ß-D-glucoside(3), rayalinol(4), psorachalcone A(5), 4-ketopinoresinol(6), ficusesquilignan B(7), pinnatifidanin AI(8), pinnatifidanin A(9), O-methylmellein(10), and trans-4-hydroxymellein(11). Among these compounds, compound 1 was a new prenylated flavone, and compounds 2-11 were isolated from the plants belonging to the genus Artocarpus for the first time. Furthermore, all compounds 1-11 were evaluated for their anti-rheumatoid arthritis activities, and the MTS method was used to measure their inhibitory effects on the proliferation of synovioblasts in vitro. The results of activity evaluation showed that flavonoid compounds 1-3, 5, and lignan compounds 8 and 9 displayed significant anti-rheumatoid arthritis activities, showing the IC_(50) values in inhibiting the proliferation of synovioblasts MH7A from(6.38±0.06) µmol·L~(-1) to(168.58±0.28)µmol·L~(-1).

Close relationship with the glandular capsule：a highly sensitive diagnostic indicator of major salivary gland metastatic malignancies in ultrasound.

OBJECTIVES: To investigate the ultrasound (US) characteristics of metastatic malignancies (MM) in the major salivary glands and to assess the diagnostic value of the close relationship with the glandular capsule in identifying MM. METHODS: From January 2016 and April 2022, 122 patients with major salivary gland malignancies, including 20 patients with MM and 102 patients with primary malignancies (PM) confirmed by histopathological examination, were enrolled in this study. Their clinicopathologic and US data were recorded and analyzed. The diagnostic performance of the close relationship with the glandular capsule for differentiating MM from PM was analyzed. RESULTS: The mean age of MM were older than that of PM (59.50 ± 14.57 vs. 49.96 ± 15.73, p = 0.013). Compared with PM patients, MM were associated with a higher prevalence of local pain symptoms (p = 0.007) and abnormal facial nerve function (p < 0.001). MM were also more frequently characterized by unclear borders, rough margins, irregular shapes, heterogeneous internal echos, absence of cystic areas, presence of calcifications, close relationship with the glandular capsule, and US-reported positive cervical lymph nodes (all p < 0.05). The close relationship with the glandular capsule showed to be a good indicator in distinguishing between MM and PM, with an area under the receiver operating characteristic curve of 0.863, a sensitivity of 100%, a specificity of 72.5%, and an accuracy of 92.2%. Positive and negative predictive were calculated at 41.7% and 100%, respectively. CONCLUSIONS: The US finding of a close relationship with the glandular capsule is a highly sensitive diagnostic indicator for MM. Following this finding, US-guided needle biopsy should be recommended to further confirm the diagnosis.

A Nomogram Based on Conventional Ultrasound Radiomics for Differentiating Between Radial Scar and Invasive Ductal Carcinoma of the Breast.

ABSTRACT: We aimed to develop and validate a nomogram based on conventional ultrasound (CUS) radiomics model to differentiate radial scar (RS) from invasive ductal carcinoma (IDC) of the breast. In total, 208 patients with histopathologically diagnosed RS or IDC of the breast were enrolled. They were randomly divided in a 7:3 ratio into a training cohort (n = 145) and a validation cohort (n = 63). Overall, 1316 radiomics features were extracted from CUS images. Then a radiomics score was constructed by filtering unstable features and using the maximum relevance minimum redundancy algorithm and the least absolute shrinkage and selection operator logistic regression algorithm. Two models were developed using data from the training cohort: one using clinical and CUS characteristics (Clin + CUS model) and one using clinical information, CUS characteristics, and the radiomics score (radiomics model). The usefulness of nomogram was assessed based on their differentiating ability and clinical utility. Nine features from CUS images were used to build the radiomics score. The radiomics nomogram showed a favorable predictive value for differentiating RS from IDC, with areas under the curve of 0.953 and 0.922 for the training and validation cohorts, respectively. Decision curve analysis indicated that this model outperformed the Clin + CUS model and the radiomics score in terms of clinical usefulness. The results of this study may provide a novel method for noninvasively distinguish RS from IDC.

Comorbid Attention Deficit Hyperactivity Disorder in Women with Premenstrual Dysphoric Disorder.

Background: This study evaluated the associations between inattention, impulsivity, and attention deficit hyperactivity disorder (ADHD) in women with premenstrual dysphoric disorder (PMDD) across the menstrual cycle. Methods: This study enrolled 58 women with PMDD and 50 controls. Symptoms were assessed using the Attention and Performance Self-Assessment Scale and the Dickman Impulsivity Inventory during the pre-ovulatory (PO), mid-luteal (ML), and late luteal (LL) phases of the menstrual cycle. Results: The chi-square analysis revealed a significant association between ADHD and PMDD. Women with PMDD experienced a greater increase in scores of prospective everyday memory problems and difficulties maintaining focused attention from the PO phase to LL phase than the controls; in addition, they had higher scores in dysfunctional impulsivity during the LL phase than the controls. Among women in the PMDD group, those with ADHD had higher scores in prospective everyday memory problems and dysfunctional impulsivity during the PO and ML phases than those without ADHD. Women in the PMDD group without ADHD had a greater increase in scores of prospective everyday memory problems, difficulties maintaining focused attention, and dysfunctional impulsivity from the PO phase to the LL phase than the controls. Conclusion: Our study demonstrated that women with PMDD were more likely to have comorbid ADHD and higher levels of inattention across the menstrual cycle. PMDD was associated with increased impulsivity during the LL phase, independent of ADHD, but it was not associated with a persistent elevation of impulsivity. Furthermore, PMDD women with comorbid ADHD experienced higher inattention and impulsivity during the PO and ML phases than those without it. Thus, ADHD comorbidity should be assessed when assessing or intervening in the symptoms of inattention and impulsivity in women with PMDD.

Leptin attenuates the osteogenic induction potential of BMP9 by increasing ß-catenin malonylation modification via Sirt5 down-regulation.

BMP9 has demonstrated significant osteogenic potential. In this study, we investigated the effect of Leptin on BMP9-induced osteogenic differentiation. Firstly, we found Leptin was decreased during BMP9-induced osteogenic differentiation and serum Leptin concentrations were increased in the ovariectomized (OVX) rats. Both in vitro and in vivo, exogenous expression of Leptin inhibited the process of osteogenic differentiation, whereas silencing Leptin enhanced. Exogenous Leptin could increase the malonylation of ß-catenin. However, BMP9 could increase the level of Sirt5 and subsequently decrease the malonylation of ß-catenin; the BMP9-induced osteogenic differentiation was inhibited by silencing Sirt5. These data suggested that Leptin can inhibit the BMP9-induced osteogenic differentiation, which may be mediated through reducing the activity of Wnt/ß-catenin signalling via down-regulating Sirt5 to increase the malonylation level of ß-catenin partly.

Mechanistic exploration of the shenlian formula in the suppression of atherosclerosis progression via network pharmacology and in vivo experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: The Shenlian formula (SL) is a Chinese medicine formula used to curb the development of atherosclerosis (AS) and cardiovascular disease in clinical practice. However, owing to the complexity of compounds and their related multiple targets in traditional Chinese medicine (TCM), it remains difficult and urgent to elucidate the underlying mechanisms at a holistic level. AIM: To investigate the intrinsic mechanisms by which SL suppresses AS progression and to gain new insight into its clinical use. METHODS: We proposed a network pharmacology-based workflow to evaluate the mechanism by which SL affects AS via data analysis, target prediction, PPI network construction, GO and KEGG analyses, and a "drug-core ingredient-potential target-key pathway" network. Then, non-targeted lipidomic analysis was performed to explore the differential lipid metabolites in AS rats, revealing the possible mechanism by which SL affects atherosclerotic progression. Moreover, an AS rabbit model was constructed and gavaged for SL intervention. Serum lipid profiles and inflammatory cytokine indices were tested as an indication of the mitigating effect of SL on AS. RESULTS: A total of 89 bioactive compounds and 298 targets related to SL and AS, which play essential roles in this process, were identified, and a component-target-disease network was constructed. GO and KEGG analyses revealed that SL regulated metabolic pathway, lipids and atherosclerosis, the PI3K-Akt pathway, the MAPK pathway and so on. In vivo experimental validation revealed that a total of 43 different lipid metabolites regulated by SL were identified by non-targeted lipidomics, and glycerophospholipid metabolism was found to be an important mechanism for SL to interfere with AS. SL reduced the plaque area and decreased the levels of inflammatory cytokines (TNF-α and IL-4) and blood lipids (TC, TG, LDL-C, and ApoB) in HFD-induced AS models. In addition, HDL and ApoA1 levels are increased. PLA2 and Lipin1 are highly expressed in AS model, indicating their role in destabilizing glycerophosphatidylcholine metabolism and contributing to the onset and progression of ankylosing spondylitis. Moreover, SL intervention significantly reduced the level of pro-inflammatory cytokines; significantly down-regulated NF-kB/p65 expression, exhibiting anti-inflammatory activity. CONCLUSION: The Shenlian formula (SL) plays a pivotal role in the suppression of AS progression by targeting multiple pathways and mechanisms. This study provides novel insights into the essential genes and pathways associated with the prognosis and pathogenesis of AS.

A study on combination of non-ablative local RFA with PD-1 and angiogenesis blocking to prolong survival through improvement of immune microenvironment in advanced Hepatocellular Carcinoma.

Radiofrequency ablation (RFA), an effective local treatment method for early-stage Hepatocellular Carcinoma (HCC), combined with PD-1 blocking and anti-angiogenic therapy is being extensively explored in advanced HCC, however, the definite results and underlying mechanisms still remain to be elucidated. Therefore, whether non-ablative RFA-based combined therapy can play a synergistic anti-tumor effect through improving tumor immune microenvironment was investigated by us in HCC mouse models. Our results showed that non-ablative RFA could regulate multilayered immunity, such as inducing immunogenic death of tumor cells, upregulating the secretion of inflammatory cytokines, mainly IFN-γ, TNF-α, and IL-10, and subsequently promoting the infiltration of CD8 + T cells. As a result, a significant synergistic anti-tumor effect was demonstrated in the combination therapy group. Similarly, in the real-world setting, non-curative RFA combined with PD-1 blocking and Lenvatinib for 12 patients with Barcelona Clinic Liver Cancer (BCLC) stage C achieve promising results, with 6.9 months (95 % CI: 3.23-15.73) median progression-free survival (mPFS) and 12.7 months (95 % CI: 7.40-19.73) median overall survival (mOS). The common treatment-related adverse reactions were pneumonia and thyroiditis with low prevalence, both less than grade 3 and manageable by symptomatic treatment. Summarily, local non-ablative RFA should be a clinically preferred strategy in combination with PD-1 blocking and anti-angiogenic therapy, because this more flexible scheme abandons its historical concept of tumor eradication, but fully utilizes the immune regulatory function by inducing immunogenic tumor death and has higher-level of safety. Therefore, this is a two-pronged and highly balanced approach to achieved favorable treatment outcomes, while conclusive evidence is still pending, it can be attempted in the real world anyway.

Upregulation of LHPP by saRNA inhibited hepatocellular cancer cell proliferation and xenograft tumor growth.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer worldwide and no pharmacological treatment is available that can achieve complete remission of HCC. Phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP) is a recently identified HCC tumor suppressor gene which plays an important role in the development of HCC and its inactivation and reactivation has been shown to result in respectively HCC tumorigenesis and suppression. Small activating RNAs (saRNAs) have been used to achieve targeted activation of therapeutic genes for the restoration of their encoded protein through the RNAa mechanism. Here we designed and validated saRNAs that could activate LHPP expression at both the mRNA and protein levels in HCC cells. Activation of LHPP by its saRNAs led to the suppression of HCC proliferation, migration and the inhibition of Akt phosphorylation. When combined with targeted anticancer drugs (e.g., regorafenib), LHPP saRNA exhibited synergistic effect in inhibiting in vitro HCC proliferation and in vivo antitumor growth in a xenograft HCC model. Findings from this study provides further evidence for a tumor suppressor role of LHPP and potential therapeutic value of restoring the expression of LHPP by saRNA for the treatment of HCC.

The Use of Generative Adversarial Network and Graph Convolution Network for Neuroimaging-Based Diagnostic Classification.

Functional connectivity (FC) obtained from resting-state functional magnetic resonance imaging has been integrated with machine learning algorithms to deliver consistent and reliable brain disease classification outcomes. However, in classical learning procedures, custom-built specialized feature selection techniques are typically used to filter out uninformative features from FC patterns to generalize efficiently on the datasets. The ability of convolutional neural networks (CNN) and other deep learning models to extract informative features from data with grid structure (such as images) has led to the surge in popularity of these techniques. However, the designs of many existing CNN models still fail to exploit the relationships between entities of graph-structure data (such as networks). Therefore, graph convolution network (GCN) has been suggested as a means for uncovering the intricate structure of brain network data, which has the potential to substantially improve classification accuracy. Furthermore, overfitting in classifiers can be largely attributed to the limited number of available training samples. Recently, the generative adversarial network (GAN) has been widely used in the medical field for its generative aspect that can generate synthesis images to cope with the problems of data scarcity and patient privacy. In our previous work, GCN and GAN have been designed to investigate FC patterns to perform diagnosis tasks, and their effectiveness has been tested on the ABIDE-I dataset. In this paper, the models will be further applied to FC data derived from more public datasets (ADHD, ABIDE-II, and ADNI) and our in-house dataset (PTSD) to justify their generalization on all types of data. The results of a number of experiments show the powerful characteristic of GAN to mimic FC data to achieve high performance in disease prediction. When employing GAN for data augmentation, the diagnostic accuracy across ADHD-200, ABIDE-II, and ADNI datasets surpasses that of other machine learning models, including results achieved with BrainNetCNN. Specifically, in ADHD, the accuracy increased from 67.74% to 73.96% with GAN, in ABIDE-II from 70.36% to 77.40%, and in ADNI, reaching 52.84% and 88.56% for multiclass and binary classification, respectively. GCN also obtains decent results, with the best accuracy in ADHD datasets at 71.38% for multinomial and 75% for binary classification, respectively, and the second-best accuracy in the ABIDE-II dataset (72.28% and 75.16%, respectively). Both GAN and GCN achieved the highest accuracy for the PTSD dataset, reaching 97.76%. However, there are still some limitations that can be improved. Both methods have many opportunities for the prediction and diagnosis of diseases.

Engineering Sulfur-Containing Polymeric Fire-Retardant Coatings for Fire-Safe Rigid Polyurethane Foam.

With the advantages of lightweight and low thermal conductivity properties, polymeric foams are widely employed as thermal insulation materials for energy-saving buildings but suffer from inherent flammability. Flame-retardant coatings hold great promise for improving the fire safety of these foams without deteriorating the mechanical-physical properties of the foam. In this work, four kinds of sulfur-based flame-retardant copolymers are synthesized via a facile radical copolymerization. The sulfur-containing monomers serve as flame-retardant agents including vinyl sulfonic acid sodium (SPS), ethylene sulfonic acid sodium (VS), and sodium p-styrene sulfonate (VSS). Additionally, 2-hydroxyethyl acrylate (HEA) and 4-hydroxybutyl acrylate are employed to enable a strong interface adhesion with polymeric foams through interfacial H-bonding. By using as-synthesized waterborne flame-retardant polymeric coating with a thickness of 600 µm, the coated polyurethane foam (PUF) can achieve a desired V-0 rating during the vertical burning test with a high limiting oxygen index (LOI) of >31.5 vol%. By comparing these sulfur-containing polymeric fire-retardant coatings, poly(VS-co-HEA) coated PUF demonstrates the best interface adhesion capability and flame-retardant performance, with the lowest peak heat release rate of 166 kW m-2 and the highest LOI of 36.4 vol%. This work provides new avenues for the design and performance optimization of advanced fire-retardant polymeric coatings.

High Dietary Folic Acid Supplementation Reduced the Composition of Fatty Acids and Amino Acids in Fortified Eggs.

AIMS: The study aimed to evaluate the effects of dietary folic acid (FA) on the production performance of laying hens, egg quality, and the nutritional differences between eggs fortified with FA and ordinary eggs. METHODS: A total of 288 26-week-old Hy-Line Brown laying hens (initial body weights 1.65 ± 0.10 kg) with a similar weight and genetic background were used. A completely randomized design divided the birds into a control group and three treatment groups. Each group consisted of six replicates, with twelve chickens per replicate. Initially, all birds were fed a basal diet for 1 week. Subsequently, they were fed a basal diet supplemented with 0, 5, 10, or 15 mg/kg FA in a premix for a duration of 6 weeks. RESULTS: Supplementation of FA could significantly (p < 0.05) enhance the FA content in egg yolks, particularly when 10 mg/kg was used, as it had the most effective enrichment effect. Compared to the control group, the Glu content in the 10 and 15 mg/kg FA groups showed a significant (p < 0.05) decrease. Additionally, the contents of Asp, Ile, Tyr, Phe, Cys, and Met in the 15 mg/kg FA group were significantly (p < 0.05) lower compared to the other groups. Adding FA did not have significant effects on the levels of vitamin A and vitamin E in egg yolk, but the vitamin D content in the 5 and 10 mg/kg FA groups showed a significant (p < 0.05) increase. Furthermore, the addition of FA did not have a significant effect on the levels of Cu, Fe, Mn, Se, and Zn in egg yolk. The dietary FA did not have a significant effect on the total saturated fatty acids (SFA) and polyunsaturated fatty acid (PUFA) content in egg yolk. However, the total monounsaturated fatty acid (MUFA) content in the 5 and 10 mg/kg groups significantly (p < 0.05) increased. These changes in nutritional content might be attributed to the increased very low-density lipoprotein (VLDL) protein content. The significant decrease in solute carrier family 1 Member 1 (SLC1A1), solute carrier family 1 Member 2 (SLC1A2), and solute carrier family 1 Member 3 (SLC1A3) gene expression compared to the control group appeared to be the reason for the decrease in amino acid content in egg yolk within the dietary FA group. CONCLUSION: The findings suggest that the appropriate addition of FA can enhance the levels of MUFA and vitamin D in egg yolks, thereby improving their nutritional value. Excessive intake of FA can decrease the effectiveness of enriching FA in egg yolk and impact the enrichment of certain amino acids. The yolk of eggs produced by adding 10 mg/kg of FA to the feed contains the optimal amount of nutrients. This study informs consumers purchasing FA-fortified eggs.

Ni-Catalyzed Csp2 and Csp3 Coupling for Divergent Bisboronic Ester Synthesis.

Bisboronic esters are critical compounds in various research fields, including drug discovery, chemical biology, and material sciences. Currently, the bisboronic esters with reactive functional groups are difficult to synthesize; this is partially due to the lack of a robust method to produce these products with diverse structures and various functional groups at specific locations. To overcome this issue, this study introduced a Ni-catalysis approach to produce bisboronic esters efficiently via cross-coupling and homocoupling using readily available halogenated boronic esters as the starting material under mild reaction conditions. This newly developed strategy enables Csp2-Csp2, Csp3-Csp3, and Csp2-Csp3 couplings, demonstrating a broad substrate scope and excellent compatibility with various functional groups.

An ultrasound-based histogram analysis model for prediction of tumour stroma ratio in pleomorphic adenoma of the salivary gland.

OBJECTIVES: Preoperative identification of different stromal subtypes of pleomorphic adenoma (PA) of the salivary gland is crucial for making treatment decisions. We aimed to develop and validate a model based on histogram analysis (HA) of ultrasound (US) images for predicting tumour stroma ratio (TSR) in salivary gland PA. METHODS: A total of 219 PA patients were divided into low-TSR (stroma-low) and high-TSR (stroma-high) groups and enrolled in a training cohort (n = 151) and a validation cohort (n = 68). The least absolute shrinkage and selection operator regression algorithm was used to screen the most optimal clinical, US, and HA features. The selected features were entered into multivariable logistic regression analyses for further selection of independent predictors. Different models, including the nomogram model, the clinic-US (Clin + US) model, and the HA model, were built based on independent predictors using logistic regression. The performance levels of the models were evaluated and validated on the training and validation cohorts. RESULTS: Lesion size, shape, cystic areas, vascularity, HA_mean, and HA_skewness were identified as independent predictors for constructing the nomogram model. The nomogram model incorporating the clinical, US, and HA features achieved areas under the curve of 0.839 and 0.852 in the training and validation cohorts, respectively, demonstrating good predictive performance and calibration. Decision curve analysis and clinical impact curves further confirmed its clinical usefulness. CONCLUSIONS: The nomogram model we developed offers a practical tool for preoperative TSR prediction in PA, potentially enhancing clinical decision-making.