1,6-Nucleophilic Di- and Trifluoromethylation of para-Quinone Methides with Me3SiCF2H/Me3SiCF3 Facilitated by CsF/18-Crown-6.

The direct 1,6-nucleophilic difluoromethylation, trifluoromethylation, and difluoroalkylation of para-quinone methides (p-QMs) with Me3SiRf (Rf = CF2H, CF3, CF2CF3, CF2COOEt, and CF2SPh) under mild conditions are described. Although Me3SiCF2H shows lower reactivity than Me3SiCF3, it can react with p-QMs promoted by CsF/18-Crown-6 to give structurally diverse difluoromethyl products in good yields. The products can then be further converted into fluoroalkylated para-quinone methides and α-fluoroalkylated diarylmethanes.

AmyloidPETNet: Classification of Amyloid Positivity in Brain PET Imaging Using End-to-End Deep Learning.

Background Visual assessment of amyloid PET scans relies on the availability of radiologist expertise, whereas quantification of amyloid burden typically involves MRI for processing and analysis, which can be computationally expensive. Purpose To develop a deep learning model to classify minimally processed brain PET scans as amyloid positive or negative, evaluate its performance on independent data sets and different tracers, and compare it with human visual reads. Materials and Methods This retrospective study used 8476 PET scans (6722 patients) obtained from late 2004 to early 2023 that were analyzed across five different data sets. A deep learning model, AmyloidPETNet, was trained on 1538 scans from 766 patients, validated on 205 scans from 95 patients, and internally tested on 184 scans from 95 patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) fluorine 18 (18F) florbetapir (FBP) data set. It was tested on ADNI scans using different tracers and scans from independent data sets. Scan amyloid positivity was based on mean cortical standardized uptake value ratio cutoffs. To compare with model performance, each scan from both the Centiloid Project and a subset of the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study were visually interpreted with a confidence level (low, intermediate, high) of amyloid positivity/negativity. The area under the receiver operating characteristic curve (AUC) and other performance metrics were calculated, and Cohen κ was used to measure physician-model agreement. Results The model achieved an AUC of 0.97 (95% CI: 0.95, 0.99) on test ADNI 18F-FBP scans, which generalized well to 18F-FBP scans from the Open Access Series of Imaging Studies (AUC, 0.95; 95% CI: 0.93, 0.97) and the A4 study (AUC, 0.98; 95% CI: 0.98, 0.98). Model performance was high when applied to data sets with different tracers (AUC ≥ 0.97). Other performance metrics provided converging evidence. Physician-model agreement ranged from fair (Cohen κ = 0.39; 95% CI: 0.16, 0.60) on a sample of mostly equivocal cases from the A4 study to almost perfect (Cohen κ = 0.93; 95% CI: 0.86, 1.0) on the Centiloid Project. Conclusion The developed model was capable of automatically and accurately classifying brain PET scans as amyloid positive or negative without relying on experienced readers or requiring structural MRI. Clinical trial registration no. NCT00106899 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Bryan and Forghani in this issue.

Machine learning models for diagnosis of essential tremor and dystonic tremor using grey matter morphological networks.

BACKGROUND: Essential tremor (ET) and dystonic tremor (DT) are the two most common tremor disorders, and misdiagnoses are very common due to similar tremor symptoms. In this study, we explore the structural network mechanisms of ET and DT using brain grey matter (GM) morphological networks and combine those with machine learning models. METHODS: 3D-T1 structural images of 75 ET patients, 71 DT patients, and 79 healthy controls (HCs) were acquired. We used voxel-based morphometry to obtain GM images and constructed GM morphological networks based on the Kullback-Leibler divergence-based similarity (KLS) method. We used the GM volumes, morphological relations, and global topological properties of GM-KLS morphological networks as input features. We employed three classifiers to perform the classification tasks. Moreover, we conducted correlation analysis between discriminative features and clinical characteristics. RESULTS: 16 morphological relations features and 1 global topological metric were identified as the discriminative features, and mainly involved the cerebello-thalamo-cortical circuits and the basal ganglia area. The Random Forest (RF) classifier achieved the best classification performance in the three-classification task, achieving a mean accuracy (mACC) of 78.7%, and was subsequently used for binary classification tasks. Specifically, the RF classifier demonstrated strong classification performance in distinguishing ET vs. HCs, ET vs. DT, and DT vs. HCs, with mACCs of 83.0 %, 95.2 %, and 89.3 %, respectively. Correlation analysis demonstrated that four discriminative features were significantly associated with the clinical characteristics. CONCLUSION: This study offers new insights into the structural network mechanisms of ET and DT. It demonstrates the effectiveness of combining GM-KLS morphological networks with machine learning models in distinguishing between ET, DT, and HCs.

Albumen exosomes alleviate LPS-induced inflammation of intestinal epithelial cells via miR-22/ATM/p53/NF-κB axis.

Biological macromolecules identified in albumen were found benefit to intestinal health, whether albumen contains exosomes and function of their cargos in intestinal inflammation remain unknown. This study aimed to investigate characteristics and cargos of albumen exosomes, as well as their potential roles in alleviating inflammation in intestinal epithelial cells. Our results demonstrated that albumen contains exosomes that are cup-shaped morphology vesicles with diameter ranging from 50 to 200 nm. There were 278 miRNAs and 45 proteins with higher expression levels in albumen exosomes, and they were mainly involved in immune responses and programmed cell death pathways, including apoptosis and p53 signaling pathway. LPS induced overexpression of pro-inflammatory cytokines IL-1ß and TNF-α and excessive apoptosis, which could be reversed by albumen exosomes. The beneficial effects of exosomes could be mainly attributed to miRNA cargos and their inhibition on inflammatory response signaling pathways (p53 and NF-κB pathways). Mechanically, exosome miR-22 targeted ATM and inhibited p53/NF-κB pathway, alleviating LPS-induced overexpression of Caspase-3 and Bax, and inflammatory response. Collectively, albumen exosomes alleviate inflammation of intestinal epithelial cells via miR-22/ATM/p53/NF-κB axis and these findings may provide theoretical basis to the potential application of albumen exosomes for intestinal inflammation.

Consequences of plateau pika disturbance on plant-soil carbon and nitrogen in alpine meadows.

The presence of burrowing mammals can have extensive effects on plants and soils, creating bare soil patches in alpine meadows and potentially altering plant-soil carbon (C) and nitrogen (N). This study focuses on the plateau pika (Ochotona curzoniae) to examine the responses of plant-soil C and N to a small burrowing mammal from quadrat scale to plot scale. The density of active burrow entrances in disturbed plots was used as an indicator of the disturbance intensity of plateau pikas. The study found that the below-ground biomass (BGB) and its C and N, as well as soil C and N concentrations were significantly lower in bare soil areas than in vegetated areas and undisturbed plots. This shows that the quadrat scale limited the estimation of the C and N sequestration potential. Therefore, further research on the plot scale found that the disturbance by plateau pika significantly reduced plant biomass and BGB carbon stock. However, plateau pika did not affect soil C and N stocks or ecosystem C and N stocks. These findings suggest the bare soil patches formed by plateau pika caused plant and soil heterogeneity but had a trade-off effect on plant-soil C and N stocks at the plot scale. Nevertheless, moderate disturbance intensity increased the C and N sequestration potential in grassland ecosystems. These results provide a possible way to estimate how disturbance by small burrowing mammals affects C and N cycling in grassland ecosystems while accurately assessing the effects of small burrowing mammal densities on C and N in grassland ecosystems.

The influence of socio-economic status on child temperament and psychological symptom profiles.

The influence of socio-economic status (SES) on child temperament and psychological symptoms was examined using a nationally representative sample in Singapore. Data were available for 2169 children from 1987 families. Caregivers' reports were obtained on children aged 4-6. SES was operationalized as an aggregation of household income per capita, parental education level and housing type. Compared to their counterparts from higher SES families, children from low-SES families tended to exhibit (a) higher negative affectivity but lower effortful control, and (b) higher internalizing and externalizing symptoms. In addition, children with a 'resilient' temperamental profile (i.e. low negative affectivity and high effortful control) were more likely to come from families with much higher SES, relative to children with other profiles. Children with high internalizing symptoms tended to come from low-SES backgrounds, regardless of their externalizing symptoms. Among children with low internalizing symptoms, those with high externalizing symptoms came from lower SES backgrounds compared to those with low externalizing symptoms. Parental warmth and distress mediated the association between SES and child temperament and symptom profiles, with the exception of distress in the SES-temperament link. These findings supported the family stress model and highlighted the novel perspective of SES's influence on configurations of child temperament and symptom characteristics.

Combined brain topological metrics with machine learning to distinguish essential tremor and tremor-dominant Parkinson's disease.

BACKGROUND: Essential tremor (ET) and Parkinson's disease (PD) are the two most prevalent movement disorders, sharing several overlapping tremor clinical features. Although growing evidence pointed out that changes in similar brain network nodes are associated with these two diseases, the brain network topological properties are still not very clear. OBJECTIVE: The combination of graph theory analysis with machine learning (ML) algorithms provides a promising way to reveal the topological pathogenesis in ET and tremor-dominant PD (tPD). METHODS: Topological metrics were extracted from Resting-state functional images of 86 ET patients, 86 tPD patients, and 86 age- and sex-matched healthy controls (HCs). Three steps were conducted to feature dimensionality reduction and four frequently used classifiers were adopted to discriminate ET, tPD, and HCs. RESULTS: A support vector machine classifier achieved the best classification performance of four classifiers for discriminating ET, tPD, and HCs with 89.0% mean accuracy (mACC) and was used for binary classification. Particularly, the binary classification performances among ET vs. tPD, ET vs. HCs, and tPD vs. HCs were with 94.2% mACC, 86.0% mACC, and 86.3% mACC, respectively. The most power discriminative features were mainly located in the default, frontal-parietal, cingulo-opercular, sensorimotor, and cerebellum networks. Correlation analysis results showed that 2 topological features negatively and 1 positively correlated with clinical characteristics. CONCLUSIONS: These results demonstrated that combining topological metrics with ML algorithms could not only achieve high classification accuracy for discrimination ET, tPD, and HCs but also help to reveal the potential brain topological network pathogenesis in ET and tPD.

Detecting lies through others' eyes: Children use perceptual access cues to evaluate listeners' beliefs about informants' deception.

Children are often third-party observers of conversations between informants and receivers. Although 5- and 6-year-olds can identify and reject informants' false testimony, it remains unclear whether they expect others to do the same. Accurately assessing others' impressions of informants and their testimony in a conversational setting is essential for children's navigation of the social world. Using a novel second-order lie detection task, the current study examined whether 4- to 7-year-olds (N = 74; Mage = 69 months) take receivers' epistemic states into account when predicting whether a receiver would think an informant is truthful or deceptive. We pitted children's firsthand observations of reality against informants' false testimony while manipulating receivers' perceptual access to a sticker-hiding event. Results showed that when the receiver had perceptual access and was knowledgeable, children predicted that the receiver would think the informant is lying. Critically, when the receiver lacked perceptual access and was ignorant, children were significantly more likely to predict that the receiver would think the informant is telling the truth. Second-order theory of mind and executive function strengthened this effect. Findings are interpreted using a dual-process framework and provide new insights into children's understanding of others' selective trust and susceptibility to deception.

UV-stimulated riboflavin exerts immunosuppressive effects in BALB/c mice and human PBMCs.

Riboflavin (RF) as a photosensitizer has been used in corneal surgery and the inactivation of blood products. However, the effect of RF on immune cells after ultraviolet (UV) light stimulation has not been investigated. This study pioneered a novel application method of RF. Firstly, UV-stimulated RF was co-cultured with human peripheral blood mononuclear cells in vitro, and the apoptosis rate of lymphocyte subsets, cell proliferation inhibition rate and concentrations of IL-1ß, IL-6, IL-10, TNF-α were assessed. UV-stimulated RF was then administered intravenously to mice via the tail vein for a consecutive period of 5 days. The levels of immunoglobulin (IgG, IgM, IgA), complement (C3, C4) and cytokines (IFN-γ, IL-4, IL17, TGF-ß) were detected by ELISA. Flow cytometry was employed to analyze the populations of CD3+T, CD4+T, CD8+T and CD4+T/CD8+T cells in spleen lymphocytes of mice. The data showed that UV-stimulated RF can effectively induce apoptosis in lymphocytes, and different lymphocyte subtypes exhibited varying degrees of treatment tolerance. Additionally, the proliferative capacity of lymphocytes was suppressed, while their cytokine secretion capability was augmented. The animal experiments demonstrated that UV-stimulated RF led to a significant reduction observed in serum immunoglobulin and complement levels, accompanied by an elevation in IFN-γ, IL-17 and TGF-ß levels, as well as a decline in IL-4 level. In summary, the results of both in vitro and in vivo experiments have demonstrated that UV-stimulated RF, exhibits the ability to partially inhibit immune function. This novel approach utilizing RF may offer innovative perspectives for diseases requiring immunosuppressive treatment.

Copper(I)-Catalyzed Dearomatization of Benzofurans with 2-(Chloromethyl)anilines through Radical Addition and Cyclization Cascade.

Herein, we described a copper(I)-catalyzed dearomatization of benzofurans with 2-(chloromethyl)anilines to prepare various tetrahydrobenzofuro[3,2-b]quinolines and 2-(quinolin-2-yl)phenols in good to excellent yields through radical addition and an intramolecular cyclization process. Mechanistic studies revealed that 2-(chloromethyl)anilines served as radical precursors. The present method features broad substrate scope, good functional group tolerance, quinoline scaffold diversity, and radical addition dearomatization of benzofurans.

Colorectal cancer's burden attributable to a diet high in processed meat in the Belt and Road Initiative countries.

BACKGROUND: Colorectal cancer (CRC) plays a significant role in morbidity, mortality, and economic cost in the Belt and Road Initiative ("B and R") countries. In addition, these countries have a substantial consumption of processed meat. However, the burden and trend of CRC in relation to the consumption of a diet high in processed meat (DHPM-CRC) in these "B and R" countries remain unknown. AIM: To analyze the burden and trend of DHPM-CRC in the "B and R" countries from 1990 to 2019. METHODS: We used the 2019 Global Burden of Disease Study to collate information regarding the burden of DHPM-CRC. Numbers and age-standardized rates (ASRs) of deaths along with the disability-adjusted life years (DALYs) were determined among the "B and R" countries in 1990 and 2019. Using joinpoint regression analysis, the average annual percent change (AAPC) was used to analyze the temporal trends of age-standardized DALYs rate (ASDALR) from 1990 to 2019 and in the final decade (2010-2019). RESULTS: We found geographical differences in the burden of DHPM-CRC among "B and R" countries, with the three highest-ranking countries being the Russian Federation, China, and Ukraine in 1990, and China, the Russian Federation, and Poland in 2019. The burden of DHPM-CRC generally increased in most member countries from 1990 to 2019 (all P < 0.05). The absolute number of deaths and DALYs in DHPM-CRC were 3151.15 [95% uncertainty interval (UI) 665.74-5696.64] and 83249.31 (95%UI 15628.64-151956.31) in China in 2019. However, the number of deaths (2627.57-2528.51) and DALYs (65867.39-55378.65) for DHPM-CRC in the Russian Federation has declined. The fastest increase in ASDALR for DHPM-CRC was observed in Vietnam, Southeast Asia, with an AAPC value of 3.90% [95% confidence interval (CI): 3.63%-4.16%], whereas the fastest decline was observed in Kyrgyzstan, Central Asia, with an AAPC value of -2.05% (95% CI: -2.37% to -1.73%). A substantial upward trend in ASR of mortality, years lived with disability, years of life lost, and DALYs from DHPM-CRC changes in 1990-2019 and the final decade (2010-2019) for most Maritime Silk Route members in East Asia, South Asia, Southeast Asia, North Africa, and the Middle East, as well as Central Europe, while those of the most Land Silk Route members in Central Asia and Eastern Europe have decreased markedly (all P < 0.05). The ASDALR for DHPM-CRC increased more in males than in females (all P < 0.05). For those aged 50-74 years, the ASDALR for DHPM-CRC in 40 members exhibited an increasing trend, except for 20 members, including 7 members in Central Asia, Maldives, and 12 high or high-middle social development index (SDI) members in other regions (all P < 0.05). CONCLUSION: The burden of DHPM-CRC varies substantially across "B and R" countries and threatens public health. Relevant evidence-based policies and interventions tailored to the different trends of countries in SDIs or Silk Routes should be adopted to reduce the future burden of CRC in "B and R" countries via extensive collaboration.

Effect of early hemostasis strategy on secondary post-traumatic sepsis in trauma hemorrhagic patients.

INTRODUCTION: Fibrinogen and platelet, as the two main components of hemostatic resuscitation, are frequently administered in traumatic massive hemorrhage patients. It is reasonable to infer that they may have an impact on post-traumatic sepsis as more and more recognition of their roles in inflammation and immunity. This study aims to determine the association between the fibrinogen/platelet transfusion ratio during the first 24 h after trauma and the risk of the post- traumatic sepsis. METHODS: We analyzed the data from the National Trauma Data Bank (NTDB). Subjects included the critically injured adult patients admitted to Level I/II trauma center from 2013 to 2017 who received fibrinogen and platelet supplementation and more than 10 units (about 4000 ml) packed red blood cells (pRBCs) during the first 24 h after trauma. Two parts of analyses were performed: (1) multivariable stepwise regression was used to determine the variables that influence the risk of post-traumatic sepsis; (2) propensity score matching (PSM), to compare the influences of different transfusion ratio between fibrinogen and platelet on the risk of sepsis and other outcomes after trauma. RESULTS: 8 features were screened out by bi-directional multivariable stepwise logistic regression to predict the post-traumatic sepsis. They are age, sex, BMI, ISSabdomen, current smoker, COPD, Fib4h/24h and Fib/PLT24h. Fib/PLT24h was negatively related to sepsis (p < 0.05). A total of 1601 patients were included in the PSM cohort and grouped by Fib/PLT24h = 0.025 according to the fitting generalized additive model (GAM) model curve. The incidence of sepsis was significantly decreased in the high Fib/PLT group [3.3 % vs 9.4 %, OR = 0.33, 95 %CI (0.17-0.60)]; the length of stay in ICU and mechanical ventilation were both shortened as well [8 (IQR 2.00,17.00) vs 9 (IQR 3.00,19.25), p = 0.006 and 4 (IQR 2.00,10.00) vs 5 (IQR 2.00,14.00), p = 0.003, respectively. CONCLUSIONS: Early and sufficient supplementation of fibrinogen was a convenient way contribute to reduce the risk of sepsis after trauma.

124I-labeled anti-CD147 antibody for noninvasive detection of CD147-positive pan-cancers: construction and preclinical studies.

Extracellular matrix metalloproteinase inducer CD147 is a glycoprotein on the cell surface. There is minimal expression of CD147 in normal epithelial and fetal tissues, but it is highly expressed in a number of aggressive tumors. CD147 has been implicated in pan-cancer immunity and progression. With the development of CD147-targeting therapeutic strategy, accurate detection of CD147 expression in tumors and its changes during the therapy is necessary. In this study we constructed a novel radiotracer by labeling the anti-CD147 mAb with radionuclide 124/125I (124/125I-anti-CD147) for noninvasive detection of CD147 expression in pan-cancers, and characterized its physicochemical properties, affinity, metabolic characteristics, biodistribution and immunoPET imaging with 124I-IgG and 18F-FDG as controls. By examining the expression of CD147 in cancer cell lines, we found high CD147 expression in colon cancer cells LS174T, FADU human pharyngeal squamous cancer cells and 22RV1 human prostate cancer cells, and low expression of CD147 in human pancreatic cancer cells ASPC1 and human gastric cancer cells BGC823. 124/125I-anti-CD147 was prepared using N-bromine succinimide (NBS) as oxidant and purified by PD-10 column. Its radiochemical purity (RCP) was over 99% and maintained over 85% in saline or 5% human serum albumin (HSA) for more than 7 d; the RCP of 125I-anti-CD147 in blood was over 90% at 3 h post injection (p.i.) in healthy mice. The Kd value of 125I-anti-CD147 to CD147 protein was 6.344 nM, while that of 125I-IgG was over 100 nM. 125I-anti-CD147 showed much greater uptake in CD147 high-expression cancer cells compared to CD147 low-expression cancer cells. After intravenous injection in healthy mice, 125I-anti-CD147 showed high initial uptake in blood pool and liver, the uptake was decreased with time. The biological half-life of distribution and clearance phases in healthy mice were 0.63 h and 19.60 h, respectively. The effective dose of 124I-anti-CD147 was estimated as 0.104 mSv/MBq. We conducted immunoPET imaging in tumor-bearing mice, and demonstrated a significantly higher tumor-to-muscle ratio of 124I-anti-CD147 compared to that of 124I-IgG and 18F-FDG in CD147 (+) tumors. The expression levels of CD147 in cells and tumors were positively correlated with the maximum standardized uptake value (SUVmax) (P < 0.01). In conclusion, 124/125I-anti-CD147 displays high affinity to CD147, and represents potential for the imaging of CD147-positive tumors. The development of 124I-anti-CD147 may provide new insights into the regulation of tumor microenvironment and formulation of precision diagnosis and treatment programs for tumors.

Scalable Orthonormal Projective NMF via Diversified Stochastic Optimization.

The increasing availability of large-scale neuroimaging initiatives opens exciting opportunities for discovery science of human brain structure and function. Data-driven techniques, such as Orthonormal Projective Non-negative Matrix Factorization (opNMF), are well positioned to explore multivariate relationships in big data towards uncovering brain organization. opNMF enjoys advantageous interpretability and reproducibility compared to commonly used matrix factorization methods like Principal Component Analysis (PCA) and Independent Component Analysis (ICA), which led to its wide adoption in clinical computational neuroscience. However, applying opNMF in large-scale cohort studies is hindered by its limited scalability caused by its accompanying computational complexity. In this work, we address the computational challenges of opNMF using a stochastic optimization approach that learns over mini-batches of the data. Additionally, we diversify the stochastic batches via repulsive point processes, which reduce redundancy in the mini-batches and in turn lead to lower variance in the updates. We validated our framework on gray matter tissue density maps estimated from 1000 subjects part of the Open Access Series of Imaging (OASIS) dataset. We demonstrated that operations over mini-batches of data yield significant reduction in computational cost. Importantly, we showed that our novel optimization does not compromise the accuracy or interpretability of factors when compared to standard opNMF. The proposed model enables new investigations of brain structure using big neuroimaging data that could improve our understanding of brain structure in health and disease.

Proteome efficiency of metabolic pathways in Escherichia coli increases along the nutrient flow.

IMPORTANCE: Protein translation is the most expensive cellular process in fast-growing bacteria, and efficient proteome usage should thus be under strong natural selection. However, recent studies show that a considerable part of the proteome is unneeded for instantaneous cell growth in Escherichia coli. We still lack a systematic understanding of how this excess proteome is distributed across different pathways as a function of the growth conditions. We estimated the minimal required proteome across growth conditions in E. coli and compared the predictions with experimental data. We found that the proteome allocated to the most expensive internal pathways, including translation and the synthesis of amino acids and cofactors, is near the minimally required levels. In contrast, transporters and central carbon metabolism show much higher proteome levels than the predicted minimal abundance. Our analyses show that the proteome fraction unneeded for instantaneous cell growth decreases along the nutrient flow in E. coli.

Synthesis, Crystal Structure, Spectral Characterization and Antifungal Activity of Novel Phenolic Acid Triazole Derivatives.

At present, phenolic acid derivatives and triazole derivatives have a good antifungal effect, which has attracted widespread attention. A series of novel phenolic acid triazole derivatives were synthesized, and their structures were characterized by IR, MS, NMR, and X-ray crystal diffraction. Compound methyl 4-(2-bromoethoxy)benzoate, methyl 4-(2-(1H-1,2,4-triazol-1-yl) ethoxy)benzoate, 4-(2-(1H-1,2,4-triazol-1-yl)ethoxy)benzoic acid and 4-(2-(1H-1,2,4-triazol-1-yl) ethoxy)-3-methoxybenzoic acid crystallize in the monoclinic system with space group P21/n, the monoclinic system with space group P21, the monoclinic system with space group P21 and the orthorhombic system with space group Pca21, respectively. At a concentration of 100 µg/mL and 200 µg/mL, the antifungal activity against seven plant pathogen fungi was determined. Compound methyl 4-(2-bromoethoxy)benzoate has the best inhibitory effect on Rhizoctonia solani AG1, and the inhibitory rate reached 88.6% at 200 µg/mL. The inhibitory rates of compound methyl 4-(2-(1H-1,2,4-triazol-1-yl) ethoxy)benzoate against Fusarium moniliforme and Sphaeropsis sapinea at a concentration of 200 µg/mL were 76.1% and 75.4%, respectively, which were better than that of carbendazim.

Socio-cognitive correlates of primary school children's deceptive behavior toward peers in competitive settings.

Competing for limited resources with peers is common among children from an early age, illustrating their propensity to use deceptive strategies to win. We focused on how primary school-age (6-8 years old) children's strategic deception toward peers is associated with their socio-cognitive development (theory of mind and executive functions). In a novel computerized competitive hide-and-seek game, we manipulated the peer opponents' familiarity (familiar vs. unfamiliar) and actions (following vs. not following children's indications), as well as the stimuli likability (liked vs. disliked cards). Our findings demonstrated that children deceived the familiar opponent less than the unfamiliar one, indicating their determination to preserve positive peer interactions. We showed that theory of mind and executive functions significantly predicted children's willingness to deceive. Notably, second-order false belief understanding and visuospatial working memory positively predicted children's use of truths to deceive, whereas inhibitory control and cognitive flexibility efficacy scores were negatively related to their deceptive performance when using the same strategy. Implications for children's competitive behavior toward peers involving lie-telling are discussed.

[Effects of Platelet-Rich Plasma on Macrophage Phenotype and Its Influencing Factors].

OBJECTIVE: To evaluate the effects of platelet-rich plasma (PRP) supernatants with different activation methods and storage time on human monocyte-derived macrophages phenotype and explore the possible mechanism. METHODS: Human monocyte-derived macrophages were cultured in vitro with PRP or activated PRP supernatants activated with different activators. The expression of marker molecules on the surface of macrophages was detected by flow cytometry, and the concentration of growth factors in PRP supernatants was detected by ELISA. RESULTS: After 24 h of coculture, the expression level of CD86 in macrophages stimulated by PRP supernatant (thrombin and Cacl2 activated) was significantly higher than that by PRP group (P<0.05), and the expression of CD163 in macrophages was increased by Cacl2 activated PRP supernatant. Compared with different activator groups, the expression of CD163 in macrophages of Cacl2 activated group was significantly higher than that of thrombin and ADP groups (P<0.05). ELISA results showed that the concentrations of FGF (P<0.001) and EGF (P<0.05) in the supernatant of PRP stored at -80 ℃ for more than 20 months and 10-20 months were significantly higher than those in the group stored at less than 10 months after Cacl2 activation, and the expressions of CD86 (P<0.01), CD163 (P<0.001) and CD206 (P<0.001) in macrophages cocultured with the supernatant of the two groups were significantly increased. CONCLUSION: PRP activated by different activators has different effects on the phenotype of macrophages. Meanwhile, the storage time will also affect the growth factor concentration and effect of PRP.

Robotic-assisted proctosigmoidectomy for Hirschsprung's disease: A multicenter prospective study.

BACKGROUND: Robotic surgery is a cutting-edge minimally invasive technique that overcomes many shortcomings of laparoscopic techniques, yet few studies have evaluated the use of robotic surgery to treat Hirschsprung's disease (HSCR). AIM: To analyze the feasibility and medium-term outcomes of robotic-assisted proctosigmoidectomy (RAPS) with sphincter- and nerve-sparing surgery in HSCR patients. METHODS: From July 2015 to January 2022, 156 rectosigmoid HSCR patients were enrolled in this multicenter prospective study. Their sphincters and nerves were spared by dissecting the rectum completely from the pelvic cavity outside the longitudinal muscle of the rectum and then performing transanal Soave pull-through procedures. Surgical outcomes and continence function were analyzed. RESULTS: No conversions or intraoperative complications occurred. The median age at surgery was 9.50 months, and the length of the removed bowel was 15.50 ± 5.23 cm. The total operation time, console time, and anal traction time were 155.22 ± 16.77, 58.01 ± 7.71, and 45.28 ± 8.15 min. There were 25 complications within 30 d and 48 post-30-d complications. For children aged ≥ 4 years, the bowel function score (BFS) was 17.32 ± 2.63, and 90.91% of patients showed moderate-to-good bowel function. The postoperative fecal continence (POFC) score was 10.95 ± 1.04 at 4 years of age, 11.48 ± 0.72 at 5 years of age, and 11.94 ± 0.81 at 6 years of age, showing a promising annual trend. There were no significant differences in postoperative complications, BFS, and POFC scores related to age at surgery being ≤ 3 mo or > 3 mo. CONCLUSION: RAPS is a safe and effective alternative for treating HSCR in children of all ages; it offers the advantage of further minimizing damage to sphincters and perirectal nerves and thus providing better continence function.

Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning.

The turnover number kcat, a measure of enzyme efficiency, is central to understanding cellular physiology and resource allocation. As experimental kcat estimates are unavailable for the vast majority of enzymatic reactions, the development of accurate computational prediction methods is highly desirable. However, existing machine learning models are limited to a single, well-studied organism, or they provide inaccurate predictions except for enzymes that are highly similar to proteins in the training set. Here, we present TurNuP, a general and organism-independent model that successfully predicts turnover numbers for natural reactions of wild-type enzymes. We constructed model inputs by representing complete chemical reactions through differential reaction fingerprints and by representing enzymes through a modified and re-trained Transformer Network model for protein sequences. TurNuP outperforms previous models and generalizes well even to enzymes that are not similar to proteins in the training set. Parameterizing metabolic models with TurNuP-predicted kcat values leads to improved proteome allocation predictions. To provide a powerful and convenient tool for the study of molecular biochemistry and physiology, we implemented a TurNuP web server.