A nomogram and heat map based on LASSO-Cox regression for predicting the risk of early-stage severe fever with thrombocytopenia syndrome patients developing into critical illness at 7-day and 14-day.

Severe fever with thrombocytopenia syndrome (SFTS) represents an emerging infectious disease characterized by a substantial mortality risk. Early identification of patients is crucial for effective risk assessment and timely interventions. In the present study, least absolute shrinkage and selection operator (LASSO)-Cox regression analysis was conducted to identify key risk factors associated with progression to critical illness at 7-day and 14-day. A nomogram was constructed and subsequently assessed for its predictive accuracy through evaluation and validation processes. The risk stratification of patients was performed using X-tile software. The performance of this risk stratification system was assessed using the Kaplan-Meier method. Additionally, a heat map was generated to visualize the results of these analyses. A total of 262 SFTS patients were included in this study, and four predictive factors were included in the nomogram, namely viral copies, aspartate aminotransferase (AST) level, C-reactive protein (CRP), and neurological symptoms. The AUCs for 7-day and 14-day were 0.802 [95% confidence interval (CI): 0.707-0.897] and 0.859 (95% CI: 0.794-0.925), respectively. The nomogram demonstrated good discrimination among low, moderate, and high-risk groups. The heat map effectively illustrated the relationships between risk groups and predictive factors, providing valuable insights with high predictive and practical significance.

Construction and validation of a dynamic nomogram using Lasso-logistic regression for predicting the severity of severe fever with thrombocytopenia syndrome patients at admission.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is a highly fatal infectious disease caused by the SFTS virus (SFTSV), posing a significant public health threat. This study aimed to construct a dynamic model for the early identification of SFTS patients at high risk of disease progression. METHODS: All eligible patients enrolled between April 2014 and July 2023 were divided into training and validation sets. Thirty-four clinical variables in the training set underwent analysis using least absolute shrinkage and selection operator (LASSO) logistic regression. Selected variables were then input into the multivariate logistic regression model to construct a dynamic nomogram. The model's performance was assessed using the area under the receiver operating characteristic curve (AUC-ROC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) in both training and validation sets. Kaplan-Meier survival analysis was utilized to evaluate prognostic performance. RESULTS: 299 SFTS patients entered the final investigation, with 208 patients in the training set and 90 patients in the validation set. LASSO and the multivariate logistic regression identified six significant prediction factors: age (OR, 1.060; 95% CI, 1.017-1.109; P = 0.007), CREA (OR, 1.017; 95% CI, 1.003-1.031; P = 0.019), PT (OR, 1.765; 95% CI, 1.175-2.752; P = 0.008), D-dimer (OR, 1.039; 95% CI, 1.005-1.078; P = 0.032), nervous system symptoms (OR, 8.244; 95% CI, 3.035-26.858; P < 0.001) and hemorrhage symptoms (OR, 3.414; 95% CI, 1.096-10.974; P = 0.035). The AUC-ROC, C-index, calibration plots, and DCA demonstrated the robust performance of the nomogram in predicting severity at admission, and Kaplan-Meier survival analysis indicated its utility in predicting 28-day mortality among SFTS patients. The dynamic nomogram is accessible at https://sfts.shinyapps.io/SFTS_severity_nomogram/ . CONCLUSION: This study provided a practical and readily applicable tool for the early identification of high-risk SFTS patients, enabling the timely initiation of intensified treatments and protocol adjustments to mitigate disease progression.

Few-Human-Interaction Reinforcement Learning for Autonomous Transbronchial Intervention.

The transbronchial interventional surgery presents challenges with winding and convoluted pathways, prone to compression and friction. Current autonomous planning struggles to reach deeper bronchial positions, and hard to consider multiple conflicting goals simultaneously. This article introduces an innovative planning scheme with preference weights to achieve smooth, frictionless, and collision-free autonomous transbronchial intervention with continuum robot (CR). A few-human-interaction twin-delayed deep deterministic policy gradient (FHITD3) generated from surgeon preference guidance is proposed, which determines the optimal strategy for the motion of CR. Preference knowledge is generated through interaction between human and few diversity samples. An abstract actuator space description is proposed for the posture and position representation of CR during movement within bronchus. A contact motion analysis strategy is proposed to calculate real-time attitude of CR in contact with bronchus. In addition, an oscillation suppression approach to address CR's unsmooth distal end trajectory is proposed. Simulated experiments show that the CR autonomously completes intervention tasks with a smooth and stable trajectory, reducing distal end oscillation by over 45%. It achieves a target endpoint within the fourth level bronchus (approximately 5 mm diameter) with over 90% probability.

Ferroptosis promotes valproate-induced liver steatosis in vitro and in vivo.

Valproic acid (VPA), a common antiepileptic drug, can cause liver steatosis after long-term therapy. However, an impact of ferroptosis on VPA-induced liver steatosis has not been investigated. In the study, treatment with VPA promoted ferroptosis in the livers of mice by elevating ferrous iron (Fe2+) levels derived from the increased absorption by transferrin receptor 1 (TFR1) and the decreased storage by ferritin (FTH1 and FTL), disrupting the redox balance via reduced levels of solute carrier family 7 member 11 (SLC7A11), glutathione (GSH), and glutathione peroxidase 4 (GPX4), and augmenting acyl-CoA synthetase long-chain family member 4 (ACSL4) -mediated lipid peroxide generation, accompanied by enhanced liver steatosis. All the changes were significantly reversed by co-treatment with an iron-chelating agent, deferoxamine mesylate (DFO) and a ferroptosis inhibitor, ferrostatin-1 (Fer-1). Similarly, the increases in Fe2+, TFR1, and ACSL4 levels, as well as the decreases in GSH, GPX4, and ferroportin (FPN) levels, were detected in VPA-treated HepG2 cells. These changes were also attenuated after co-treatment with Fer-1. It demonstrates that ferroptosis promotes VPA-induced liver steatosis through iron overload, inhibition of the GSH-GPX4 axis, and upregulation of ACSL4. It offers a potential therapy targeting ferroptosis for patients with liver steatosis following VPA treatment.

Risk Factors and Predictive Nomogram for Survival in Elderly Patients with Brain Glioma.

OBJECTIVE: To determine the factors that contribute to the survival of elderly individuals diagnosed with brain glioma and develop a prognostic nomogram. METHODS: Data from elderly individuals (age ≥65 years) histologically diagnosed with brain glioma were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. The dataset was randomly divided into a training cohort and an internal validation cohort at a 6:4 ratio. Additionally, data obtained from Tangdu Hospital constituted an external validation cohort for the study. The identification of independent prognostic factors was achieved through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, enabling the construction of a nomogram. Model performance was evaluated using C-index, ROC curves, calibration plot and decision curve analysis (DCA). RESULTS: A cohort of 20 483 elderly glioma patients was selected from the SEER database. Five prognostic factors (age, marital status, histological type, stage, and treatment) were found to significantly impact overall survival (OS) and cancer-specific survival (CSS), with tumor location emerging as a sixth variable independently linked to CSS. Subsequently, nomogram models were developed to predict the probabilities of survival at 6, 12, and 24 months. The assessment findings from the validation queue indicate a that the model exhibited strong performance. CONCLUSION: Our nomograms serve as valuable prognostic tools for assessing the survival probability of elderly glioma patients. They can potentially assist in risk stratification and clinical decision-making.

Improving quantitative prediction of protein subcellular locations in fluorescence images through deep generative models.

Machine learning has been employed in recognizing protein localization at the subcellular level, which highly facilitates the protein function studies, especially for those multi-label proteins that localize in more than one organelle. However, existing works mostly study the qualitative classification of protein subcellular locations, ignoring fraction of one multi-label protein in different locations. Actually, about 50 % proteins are multi-label proteins, and the ignorance of quantitative information highly restricts the understanding of their spatial distribution and functional mechanism. One reason of the lack of quantitative study is the insufficiency of quantitative annotations. To address the data shortage problem, here we proposed a generative model, PLocGAN, which could generate cell images with conditional quantitative annotation of the fluorescence distribution. The model was a conditional generative adversarial network, in which the condition learning utilized partial label learning to overcome the lack of training labels and allowed training with only qualitative labels. Meanwhile, it used contrastive learning to enhance diversity of the generated images. We assessed the PLocGAN on four pixel-fused synthetic datasets and one real dataset, and demonstrated that the model could generate images with good fidelity and diversity, outperforming existing state-of-the-art generative methods. To verify the utility of PLocGAN in the quantitative prediction of protein subcellular locations, we replaced the training images with generated quantitative images and built prediction models, and found that they had a boosting effect on the quantitative estimation. This work demonstrates the effectiveness of deep generative models in bioimage analysis, and provides a new solution for quantitative subcellular proteomics.

Conversion of Propargylic Amines with CO2 Catalyzed by a Highly Stable Copper(I) Iodide Thorium-Based Heterometal-Organic Framework.

The conversion of CO2 to generate high-value-added chemicals has become one of the hot research topics in green synthesis. Thereinto, the cyclization reaction of propargylic amines with CO2 is highly attractive because the resultant oxazolidinones are widely found in pharmaceutical chemistry. Cu(I)-based metal-organic frameworks (MOFs) as catalysts exhibit promising application prospects for CO2 conversion. However, their practical application was greatly limited due to Cu(I) being liable to disproportionation or oxidization. Herein, the solid copper(I) iodide thorium-based porous framework {[Cu5I6Th6(µ3-O)4(µ3-OH)4(H2O)10(L)10]·OH·4DMF·H2O}n (1) (HL = 2-methylpyridine-4-carboxylic acid) constructed by [Th6] clusters and [CuxIy] subunits was successfully prepared and structurally characterized. To our knowledge, this is the first copper(I) iodide-based actinide organic framework. Catalytic investigations indicate that 1 can effectively catalyze the cyclization of propargylic amines with CO2 under ambient conditions, which can be reused at least five times without a remarkable decline of catalytic activity. Importantly, 1 exhibits excellent chemical stability and the oxidation state of Cu(I) in it can remain stable under various conditions. This work can provide a valuable strategy for the synthesis of stable Cu(I)-MOF materials.

PHLDA2 overexpression facilitates senescence and apoptosis via the mitochondrial route in human nucleus pulposus cells by regulating Wnt/ß-catenin signalling pathway.

Low back pain is a common clinical symptom of intervertebral disc degeneration (IVDD), which seriously affects the quality of life of the patients. The abnormal apoptosis and senescence of nucleus pulposus cells (NPCs) play important roles in the pathogenesis of IVDD. PHLDA2 is an imprinted gene related to cell apoptosis and tumour progression. However, its role in NPC degeneration is not yet clear. Therefore, this study was set to explore the effects of PHLDA2 on NPC senescence and apoptosis and the underlying mechanisms. The expression of PHLDA2 was examined in human nucleus pulposus (NP) tissues and NPCs. Immunohistochemical staining, magnetic resonance imaging imaging and western blot were performed to evaluate the phenotypes of intervertebral discs. Senescence and apoptosis of NPCs were assessed by SA-ß-galactosidase, flow cytometry and western blot. Mitochondrial function was investigated by JC-1 staining and transmission electron microscopy. It was found that the expression level of PHLDA2 was abnormally elevated in degenerated human NP tissues and NPCs. Furthermore, knockdown of PHLDA2 can significantly inhibit senescence and apoptosis of NPCs, whereas overexpression of PHLDA2 can reverse senescence and apoptosis of NPCs in vitro. In vivo experiment further confirmed that PHLDA2 knockdown could alleviate IVDD in rats. Knockdown of PHLDA2 could also reverse senescence and apoptosis in IL-1ß-treated NPCs. JC-1 staining indicated PHLDA2's knockdown impaired disruption of the mitochondrial membrane potential and also ameliorated superstructural destruction of NPCs as showed by transmission electron microscopy. Finally, we found the PHLDA2 knockdown promoted Collagen-II expression and suppressed MMP3 expression in NPCs by repressing wnt/ß-catenin pathway. In conclusion, the results of the present study showed that PHLDA2 promotes IL-1ß-induced apoptosis and senescence of NP cells via mitochondrial route by activating the Wnt/ß-catenin pathway, and suggested that therapy targeting PHLDA2 may provide valuable insights into possible IVDD therapies.

Corrigendum: Effect of intravenous immunoglobulin therapy on the prognosis of patients with severe fever with thrombocytopenia syndrome and neurological complications.

[This corrects the article DOI: 10.3389/fimmu.2023.1118039.].

How the Listener's Attention Dynamically Switches Between Different Speakers During a Natural Conversation.

The neural mechanisms underpinning the dynamic switching of a listener's attention between speakers are not well understood. Here we addressed this issue in a natural conversation involving 21 triadic adult groups. Results showed that when the listener's attention dynamically switched between speakers, neural synchronization with the to-be-attended speaker was significantly enhanced, whereas that with the to-be-ignored speaker was significantly suppressed. Along with attention switching, semantic distances between sentences significantly increased in the to-be-ignored speech. Moreover, neural synchronization negatively correlated with the increase in semantic distance but not with acoustic change of the to-be-ignored speech. However, no difference in neural synchronization was found between the listener and the two speakers during the phase of sustained attention. These findings support the attenuation model of attention, indicating that both speech signals are processed beyond the basic physical level. Additionally, shifting attention imposes a cognitive burden, as demonstrated by the opposite fluctuations of interpersonal neural synchronization.

LncRNA SNHG26 promotes gastric cancer progression and metastasis by inducing c-Myc protein translation and an energy metabolism positive feedback loop.

Metastasis is a bottleneck in cancer treatment. Studies have shown the pivotal roles of long noncoding RNAs (lncRNAs) in regulating cancer metastasis; however, our understanding of lncRNAs in gastric cancer (GC) remains limited. RNA-seq was performed on metastasis-inclined GC tissues to uncover metastasis-associated lncRNAs, revealing upregulated small nucleolar RNA host gene 26 (SNHG26) expression, which predicted poor GC patient prognosis. Functional experiments revealed that SNHG26 promoted cellular epithelial-mesenchymal transition and proliferation in vitro and in vivo. Mechanistically, SNHG26 was found to interact with nucleolin (NCL), thereby modulating c-Myc expression by increasing its translation, and in turn promoting energy metabolism via hexokinase 2 (HK2), which facilitates GC malignancy. The increase in energy metabolism supplies sufficient energy to promote c-Myc translation and expression, forming a positive feedback loop. In addition, metabolic and translation inhibitors can block this loop, thus inhibiting cell proliferation and mobility, indicating potential therapeutic prospects in GC.

Silver Metal-Organic Framework Derived N-Doped Carbon Nanofibers for CO2 Conversion into ß-Oxopropylcarbamates.

Developing efficient heterogeneous catalysts for chemical fixation of CO2 to produce high-value-added chemicals under mild conditions is highly desired but still challenging. Herein, we first reported an approach to prepare a novel catalyst (Ag@NCNFs), featuring Ag nanoparticles (NPs) embedded within porous nitrogen-doped carbon nanofibers (NCNFs), via growing a Ag metal-organic framework on one-dimensional electrospun nanofibers followed by pyrolysis. Benefiting from the abundant nitrogen species and porous structure, Ag NPs is well dispersed in the obtained Ag@NCNFs. Catalytic studies indicated that Ag@NCNFs exhibited excellent catalytic activity for the three-component coupling reaction of CO2, secondary amines, and propargylic alcohols to generate ß-oxopropylcarbamates under mild conditions with a turnover number (TON) of 16.2, and it can be recycled and reused at least 5 times without an obvious decline in catalytic activity. The reaction mechanism was clearly clarified by FTIR, NMR, 13C isotope labeling, control experiments, and density functional theory calculations. The results suggest that Ag@NCNFs and 1,8-diazabicyclo[5.4.0]undec-7-ene can synergistically activate propargylic alcohol to react with CO2, and then the generated α-alkylidene cyclic carbonate was invaded by secondary amine to produce ß-oxopropylcarbamate. Importantly, to the best of our knowledge, this is the first experimental and theoretical investigation on this reaction.

Lactic acid promotes nucleus pulposus cell senescence and corresponding intervertebral disc degeneration via interacting with Akt.

The accumulation of metabolites in the intervertebral disc is considered an important cause of intervertebral disc degeneration (IVDD). Lactic acid, which is a metabolite that is produced by cellular anaerobic glycolysis, has been proven to be closely associated with IVDD. However, little is known about the role of lactic acid in nucleus pulposus cells (NPCs) senescence and oxidative stress. The aim of this study was to investigate the effect of lactic acid on NPCs senescence and oxidative stress as well as the underlying mechanism. A puncture-induced disc degeneration (PIDD) model was established in rats. Metabolomics analysis revealed that lactic acid levels were significantly increased in degenerated intervertebral discs. Elimination of excessive lactic acid using a lactate oxidase (LOx)-overexpressing lentivirus alleviated the progression of IVDD. In vitro experiments showed that high concentrations of lactic acid could induce senescence and oxidative stress in NPCs. High-throughput RNA sequencing results and bioinformatic analysis demonstrated that the induction of NPCs senescence and oxidative stress by lactic acid may be related to the PI3K/Akt signaling pathway. Further study verified that high concentrations of lactic acid could induce NPCs senescence and oxidative stress by interacting with Akt and regulating its downstream Akt/p21/p27/cyclin D1 and Akt/Nrf2/HO-1 pathways. Utilizing molecular docking, site-directed mutation and microscale thermophoresis assays, we found that lactic acid could regulate Akt kinase activity by binding to the Lys39 and Leu52 residues in the PH domain of Akt. These results highlight the involvement of lactic acid in NPCs senescence and oxidative stress, and lactic acid may become a novel potential therapeutic target for the treatment of IVDD.

Memristor-Based Neural Network Circuit of Associative Memory With Overshadowing and Emotion Congruent Effect.

Most memristor-based neural network circuits consider only a single pattern of overshadowing or emotion, but the relationship between overshadowing and emotion is ignored. In this article, a memristor-based neural network circuit of associative memory with overshadowing and emotion congruent effect is designed, and overshadowing under multiple emotions is taken into account. The designed circuit mainly consists of an emotion module, a memory module, an inhibition module, and a feedback module. The generation and recovery of different emotions are realized by the emotion module. The functions of overshadowing under different emotions and recovery from overshadowing are achieved by the inhibition module and the memory module. Finally, the blocking caused by long-term overshadowing is implemented by the feedback module. The proposed circuit can be applied to bionic emotional robots and offers some references for brain-like systems.

Energy transfer from two luteins to chlorophylls in light-harvesting complex II study by using exciton models with phase correction.

In light-harvesting complex II of plants, the two lutein pigments (LUT1 and LUT2) are always paired and an energy transfer pathway between them is believed to exist. However, it remains unclear whether this pathway is essential for the energy transfer between carotenoids and chlorophylls. In this work, we performed hybrid quantum mechanics/molecular mechanics simulations with Frenkel exciton models to investigate this energy transfer. The results show that the energy transfer pathways between the S2 state of LUT1 and CLAs are not affected by LUT2 S2. The energy transfer between LUT and chlorophyll-a (CLA) also follows a resonance mechanism. The two LUTs have different energy transfer pathways according to their energy gaps and coupling strengths with each CLA. The present work sheds light on the energy transfer pathways involved in the two LUTs.

Inhaled SARS-CoV-2 vaccine for single-dose dry powder aerosol immunization.

The COVID-19 pandemic has fostered major advances in vaccination technologies1-4; however, there are urgent needs for vaccines that induce mucosal immune responses and for single-dose, non-invasive administration4-6. Here we develop an inhalable, single-dose, dry powder aerosol SARS-CoV-2 vaccine that induces potent systemic and mucosal immune responses. The vaccine encapsulates assembled nanoparticles comprising proteinaceous cholera toxin B subunits displaying the SARS-CoV-2 RBD antigen within microcapsules of optimal aerodynamic size, and this unique nano-micro coupled structure supports efficient alveoli delivery, sustained antigen release and antigen-presenting cell uptake, which are favourable features for the induction of immune responses. Moreover, this vaccine induces strong production of IgG and IgA, as well as a local T cell response, collectively conferring effective protection against SARS-CoV-2 in mice, hamsters and nonhuman primates. Finally, we also demonstrate a mosaic iteration of the vaccine that co-displays ancestral and Omicron antigens, extending the breadth of antibody response against co-circulating strains and transmission of the Omicron variant. These findings support the use of this inhaled vaccine as a promising multivalent platform for fighting COVID-19 and other respiratory infectious diseases.

[Screening and expression analysis of transcription factors involved in genuineness of Codonopsis pilosula in Shanxi].

This study aims to mine the transcription factors that affect the genuineness of Codonopsis pilosula in Shanxi based on the transcriptome data of C. pilosula samples collected from Shanxi and Gansu, and then analyze the gene expression patterns, which will provide a theoretical basis for the molecular assisted breeding of C. pilosula. Gene ontology(GO) functional annotation, conserved motif prediction, and gene expression pattern analysis were performed for the differential transcription factors predicted based on the transcriptome data of C. pilosula from different habitats. A total of 61 differentially expressed genes(DEGs) were screened out from the transcriptome data. Most of the DEGs belonged to AP2/ERF-ERF family, with the conserved motif of [2X]-[LG]-[3X]-T-[3X]-[AARAYDRAA]-[3X]-[RG]-[2X]-A-[2X]-[NFP]. Forty-three of the DEGs showed significantly higher gene expression in C. pilosula samples from Shanxi than in the samples from Gansu, including 11 genes in the AP2/ERF-ERF family, 5 genes in the NAC fa-mily, 1 gene in the bHLH family, and 2 genes in the RWP-RK family, while 18 transcription factors showed higher expression levels in the samples from Gansu. GO annotation predicted that most of the DEGs were enriched in GO terms related to transcriptional binding activity(103), metabolic process(26), and stress response(23). The expression of transcription factor genes, CpNAC92, CpNAC100, CpbHLH128, and CpRAP2-7 was higher in the samples from Shanxi and in the roots of C. pilosula. CpNAC92, CpbHLH128, and CpRAP2-7 responded to the low temperature, temperature difference, and iron stresses, while CpNAC100 only responded to low temperature and iron stresses. The screening and expression analysis of the specific transcription factors CpNAC92, CpNAC100, CpbHLH128, and CpRAP2-7 in C. pilosula in Shanxi laid a theoretical foundation for further research on the mechanism of genuineness formation of C. pilosula.

Probiotics attenuate valproate-induced liver steatosis and oxidative stress in mice.

Valproate (valproic acid, VPA), a drug for the treatment of epilepsy and bipolar disorder, causes liver steatosis with enhanced oxidative stress. Accumulating evidences exhibite that gut microbiota plays an important role in progression of nonalcoholic fatty liver disease (NAFLD). However, whether gut microbiota contributes to VPA-caused hepatic steatosis needs to be elucidated. A mixture of five probiotics was selected to investigate their effects on liver steatosis and oxidative stress in mice orally administered VPA for 30 days. Probiotics treatment significantly attenuated the hepatic lipid accumulation in VPA-treated mice via inhibiting the expression of cluster of differentiation 36 (CD36) and distinct diacylglycerol acyltransferase 2 (DGAT2). Meanwhile, probiotics exerted a protective effect against VPA-induced oxidative stress by decreasing the pro-oxidant cytochrome P450 2E1 (CYP2E1) level and activating the Nrf2/antioxidant enzyme pathway. Moreover, VPA treatment altered the relative abundance of gut microbiota at the phylum, family and genera levels, while probiotics partially restored these changes. Spearman's correlation analysis showed that several specific genera and family were significantly correlated with liver steatosis and oxidative stress-related indicators. These results suggest that probiotics exert their health benefits in the abrogation of liver steatosis and oxidative stress in VPA-treated mice by manipulating the microbial homeostasis.

Neurocomputations on dual-brain signals underlie interpersonal prediction during a natural conversation.

Prediction on the partner's speech plays a key role in a smooth conversation. However, previous studies on this issue have been majorly conducted at the single-brain rather than dual-brain level, leaving the interpersonal prediction hypothesis untested. To fill this gap, this study combined a neurocomputational modeling approach with a natural conversation paradigm in which two salespersons persuaded a customer to buy their product with their haemodynamic signals being collected using functional near-infrared spectroscopy hyperscanning. First, the results showed a cognitive hierarchy in a natural conversation, with the lower-level process (i.e., pragmatic representation of the persuasion) in the salesperson interacting with the higher-level process (i.e., value representation of the product) in the customer. Next, we found that the right dorsal lateral prefrontal cortex (rdlPFC) and temporoparietal junction (rTPJ) were associated with the representation of the product's value in the customer, while the right inferior frontal cortex (rIFC) was associated with the representation of the pragmatic processes in the salesperson. Finally, neurocomputational modeling results supported the prediction of the salesperson's lower-level brain activity based on the customer's higher-level brain activity. Moreover, the updating weight of the prediction model based on the neural computation between the rIFC of the salesperson and the rTPJ of the customer was closely associated with the interaction context, whereas that based on the rIFC-rdlPFC was not. In summary, these findings provide initial support for the interpersonal prediction hypothesis at the dual-brain level and reveal a hierarchy for the interpersonal prediction process.

Intermolecular resonance energy transfer between two lutein pigments in light-harvesting complex II studied by frenkel exciton models.

The energy transfer pathways in light-harvesting complex II are complicated and the discovery of the energy transfer between the two luteins revealed an unelucidated important role of carotenoids in the energy flow. This energy transfer between the two S2 states of luteins was for the first time investigated using Frenkel exciton models, using a hybrid scheme of molecular mechanics and quantum mechanics. The results show the energy flow between the two luteins under the Förster resonance energy transfer mechanism. The energy transfer caused by energy level resonance occurs in configurations with small energy gaps. This energy transfer pathway is particularly sensitive to conformation. Moreover, according to the statistical characteristics of the data of the energy gaps and coupling values between LUTs, we proposed stochastic exciton Hamiltonian models to facilitate clarification of the energy transfer among pigments in antenna complexes.