Characterization of ovarian progenitor cells for their potential to generate steroidogenic theca cells in vitro.

In brief: Progenitor cells with ovulation-related tissue repair activity were identified with defined markers (LGR5, EPCR, LY6A, and PDGFRA), but their potentials to form steroidogenic cells were not known. This study shows that the cells can generate progenies with different steroidogenic activities. Abstract: Adult mammalian ovaries contain stem/progenitor cells necessary for folliculogenesis and ovulation-related tissue rupture repair. Theca cells are recruited and developed from progenitors during the folliculogenesis. Theca cell progenitors were not well defined. The aim of current study is to compare the potentials of four ovarian progenitors with defined markers (LY6A, EPCR, LGR5, and PDGFRA) to form steroidogenic theca cells in vitro. The location of the progenitors with defined makers was determined by immunohistochemistry and immunofluorescence staining of ovarian sections of adult mice. Different progenitor populations were purified by magnetic-activated cell sorting (MACS) and/or fluorescence-activated cell sorting (FACS) techniques from ovarian cell preparation and were tested for their abilities to generate steroidogenic theca cells in vitro. The cells were differentiated with a medium containing LH, ITS, and DHH agonist for 12 days. The results showed that EPCR+ and LGR5+ cells primarily distributed along the ovarian surface epithelium (OSE), while LY6A+ cells distributed in both the OSE and parenchyma. However, PDGFRA+ cells were exclusively located in interstitial compartment. When the progenitors were purified by these markers and differentiated in vitro, LY6A+ and PDGFRA+ cells formed steroidogenic cells expressing both CYP11A1 and CYP17A1 and primarily producing androgens, showing characteristics of theca-like cells, while LGR5+ cells generated steroidogenic cells devoid of CYP17A1 expression and androgen production, showing a characteristic of progesterone-producing cells (granulosa- or lutea-like cells). In conclusion, progenitors from both OSE and parenchyma of adult mice are capable of generating steroidogenic cells with different steroidogenic capacities, showing a possible lineage preference.

Are the original SARS-CoV-2 novel mutants from in vitro culture able to escape the immune response?

Monitoring variations in the virus genome to understand the SARS-CoV-2 evolution and spread of the virus is extremely important. Seven early SARS-CoV-2 isolates in China were cultured in vitro and were analyzed for their viral infectivity through viral growth assay, tissue culture infectious dose (TCID50 ) assay, spike protein quantification, and next generation sequencing analysis, and the resultant mutations in spike protein were used to generate the corresponding pseudoviruses for analysis of immune escape from vaccination and postinfection immunity. The results revealed that in vitro cultured SARS-CoV-2 virus had much higher mutation frequency (up to ~20 times) than that in infected patients, suggesting that SARS-CoV-2 diversify under favorable conditions. Monitoring viral mutations is not only helpful for better understanding of virus evolution and virulence change, but also the key to prevent virus transmission and disease progression. Compared with the D614G reference strain, a pseudovirus strain of SARS-CoV-2 was constructed with a high mutation rate site on the spike protein. We found some novel spike mutations during in vitro culture, such as E868Q, conferred further immune escape ability.

Evaluation of humoral immune responses induced by different SARS-CoV-2 spike trimers from wild-type and emerging variants with individual, sequential, and combinational delivered strategies.

The spike trimer of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an effective target for inducing neutralizing antibodies by coronavirus disease 2019 (COVID-19) vaccines. However, the diversity of spike protein from emerging SASR-CoV-2 variants has become the major challenge for development of a universal vaccine. To investigate the immunogenicity of spike proteins from various circulating strains including wild type, Delta, and Omicron variants, we produced various natural spike trimers and designed three vaccination strategies, that is, individual, sequential, and bivalent regimens to assess autologous and heterogenous antibody responses in a mouse model. The results indicated that monovalent vaccine strategy with individual spike trimer could only induce binding and neutralizing antibodies against homologous viruses. However, sequential and bivalent immunization with Delta and Omicron spike trimers could induce significantly broader neutralizing antibody responses against heterogenous SARS-CoV-2. Interestingly, the spike trimer from Omicron variant showed superior immunogenicity in inducing antibody response against recently emerging XE variant. Taken together, our data supported the development of novel vaccination strategies or multivalent vaccine against emerging variants.

Circulating long non-coding RNA TTTY15 and HULC serve as potential novel biomarkers for predicting acute myocardial infarction.

INTRODUCTION: Acute myocardial infarction (AMI) is a ubiquitous cardiovascular disease ensuing adverse prognosis caused by myocardial necrosis. Effective and rapid diagnosis of AMI is essential to following treatment in clinical practice while the existed biomarkers have inherent limitations. Consequently, exploration of novel biomarkers is needed. Long noncoding RNA (lncRNA) emerges as the upcoming biomarkers adopted in clinical use, and we aim at investigating the diagnostic power of lncRNA TTTY15 and HULC in AMI patients. METHOD: We measured lncRNA level in 80 AMI patients and 36 healthy volunteers in discovering cohort and 50 AMI patients and 20 healthy volunteers in verification cohort with quantitative RT-PCR method. Receiver operating characteristic (ROC) analysis was administered to detect the diagnostic power of selected lncRNAs. Regression and correlation analyses were performed to explore the related factors. RESULTS: ROC analysis reveals the superiority of TTTY15 and HULC as biomarkers against conventional AMI biomarkers CKMB (AUC of TTTY15: 0.915 versus CKMB: 0.768 versus TnT: 0.869); AUC of HULC: 0.905 versus CKMB: 0.768 versus TnT: 0.869). Regression and correlation analysis indicates that TTTY15 and HULC may be one of the contributing factors to AMI and related to accepted risk factors. CONCLUSION: Our results revealed the diagnostic potency of lncRNA TTTY15 and HULC, and they could also be treated as novel therapeutic targets in AMI therapy, hinting inspiration to the cardiologist in clinical practice.

Neural profiles of observing acceptance and rejection decisions in human mate choice copying.

Mate choice copying refers to an agent copying the choice for a potential sexual/romantic partner made by a relevant model and has been observed across many species. This study investigated the neural profiles of two copying strategies in humans - acceptance and rejection copying - using functional magnetic resonance imaging (fMRI). Female participants observed female models accepting, rejecting, or being undecided about (control), males as potential romantic partners before and after rating their own willingness to choose the same males. We found that observing acceptance shifted participants' own choices towards acceptance, while observing rejection shifted participants' choices towards rejection. A network of motivation-, conflict- and reinforcement learning related brain regions was activated for observing the models' decisions. The rostral anterior cingulate gyrus (rACCg) and the caudate in particular were activated more strongly when observing acceptance. Activation in the inferior parietal lobe directly scaled with the magnitude of changes in choices after observing acceptance, while activation in the ACCg also scaled with changes after observing rejection. These findings point to partly dissociable neural profiles for copying strategies that might be linked to different contributions of incentive-driven and vicarious motivation, potentially reflecting the presence or absence of internalised reward experiences.

Impact of China's zero mark-up drug policy on drug cost of NCDs' outpatients: an interrupted time series analysis.

BACKGROUND: China proposed the Zero Markup Drug Policy (ZMDP), which popularized in tertiary hospitals across the country in 2017, to control drug expenditures' rapid growth further and reduce the public's medical burden. This study aims to evaluate the impact of ZMDP on the drug cost of chronic disease outpatients in the tertiary hospital in Chongqing. METHODS: We collected and described the drug-cost data for outpatients with chronic diseases in a Chongqing's tertiary hospital from 2015 to 2019. The instantaneous and long-term changes of the outpatient volume and average drug cost after the ZMDP were evaluated using interrupted time series (ITS). We also analyzed the policy's impact under the stratification of gender, age, and basic medical insurance types. RESULTS: A total of 350,848 outpatients were collected from January 2015 to February 2019. After the ZMDP, the outpatient volume for diabetes, hypertension, and coronary heart disease (CHD) all showed a downward trend, with a decrease of 53.04 (P = 0.012), 142.19 (P < 0.01) and 12.16 (P < 0.001) per month. Simultaneously, the average drug cost decreased by 4.44 yuan (P = 0.029), 5.87 yuan (P < 0.001) and 10.23 yuan (P = 0.036) per month, respectively. By gender, the average drug cost of diabetes in males had the most considerable instantaneous change, reducing by 51.21 yuan (P = 0.017); the decline of CHD in women is the most obvious, with an average monthly decrease of 12.51 yuan (P < 0.001). By age, the instantaneous change of CHD was the greatest for those older than 65 years old, with a decrease of 102.61 yuan (P = 0.030). CHD in 46-65 years old showed the most significant reduction, with an average monthly decline of 11.70 yuan (P < 0.01). BMIUE's hypertension had the most considerable instantaneous change, which decreased 59.63 yuan (P = 0.010). BMIUE's CHD showed the most apparent downward trend, with an average monthly decrease of 10.02 yuan (P = 0.010). CONCLUSION: The ITS analysis is an effective method of health policy evaluation. The implementation of the ZMDP can reduce the drug cost for chronic disease outpatients in the tertiary hospital and their economic burden. Follow-up policies still require targeted price adjustments in the health service system to adjust the drug cost-effectively.

Biochemical characterization of SARS-CoV-2 nucleocapsid protein.

The nucleocapsid (N) protein is an important antigen for coronavirus, which participate in RNA package and virus particle release. In this study, we expressed the N protein of SARS-CoV-2 and characterized its biochemical properties. Static light scattering, size exclusive chromatography, and small-angle X-ray scattering (SAXS) showed that the purified N protein is largely a dimer in solution. CD spectra showed that it has a high percentage of disordered region at room temperature while it was best structured at 55 °C, suggesting its structural dynamics. Fluorescence polarization assay showed it has non-specific nucleic acid binding capability, which raised a concern in using it as a diagnostic marker. Immunoblot assays confirmed the presence of IgA, IgM and IgG antibodies against N antigen in COVID-19 infection patients' sera, proving the importance of this antigen in host immunity and diagnostics.

Characteristics of patients with coronavirus disease (COVID-19) confirmed using an IgM-IgG antibody test.

Coronavirus disease (COVID-19), caused by a novel betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly developed into a pandemic since it was first reported in December 2019. Nucleic acid testing is the standard method for the diagnosis of viral infections. However, this method reportedly has a low positivity rate. To increase the sensitivity of COVID-19 diagnoses, we developed an IgM-IgG combined assay and tested it in patients with suspected SARS-CoV-2 infection. In total, 56 patients were enrolled in this study and SARS-CoV-2 was detected by using both IgM-IgG antibody and nucleic acid tests. Clinical and laboratory data were collected and analyzed. Our findings suggest that patients who develop severe illness might experience longer virus exposure times and develop a more severe inflammatory response. The IgM-IgG test is an accurate and sensitive diagnostic method. A combination of nucleic acid and IgM-IgG testing is a more sensitive and accurate approach for diagnosis and early treatment of COVID-19.

Effects of extracellular ATP on local and systemic responses of bean (Phaseolus vulgaris L) leaves to wounding.

Wounding increased the extracellular Adenosine 5'-triphosphate (eATP) level of kidney bean leaves. Treatment with wounding or exogenous ATP increased the hydrogen peroxide (H2O2) content, activities of catalase and polyphenol oxidase, and malondialdehyde content in both the treated and systemic leaves. Pre-treatment with ATP-degrading enzyme, apyrase, to the wounded leaves reduced the wound-induced local and systemic increases in H2O2 content, activities of catalase and polyphenol oxidase, and malondialdehyde content. Application of dimethylthiourea (DMTU) and diphenylene iodonium (DPI) to the wounded and ATP-treated leaves, respectively, reduced the wound- and ATP-induced local and systemic increases in H2O2 content, activities of catalase and polyphenol oxidase, and malondialdehyde content. Moreover, the wound- and ATP-induced systemic increases of these physiological parameters were suppressed when DMTU or DPI applied to leaf petiole of the wounded and ATP-treated leaves. These results suggest that eATP at wounded sites could mediate the wound-induced local and systemic responses by H2O2-dependent signal transduction.

Epidemiological characteristics of bacillary dysentery from 2009 to 2016 and its incidence prediction model based on meteorological factors.

BACKGROUND: This study aimed to analyse the epidemiological characteristics of bacillary dysentery (BD) caused by Shigella in Chongqing, China, and to establish incidence prediction models based on the correlation between meteorological factors and BD, thus providing a scientific basis for the prevention and control of BD. METHODS: In this study, descriptive methods were employed to investigate the epidemiological distribution of BD. The Boruta algorithm was used to estimate the correlation between meteorological factors and BD incidence. The genetic algorithm (GA) combined with support vector regression (SVR) was used to establish the prediction models for BD incidence. RESULTS: In total, 68,855 cases of BD were included. The incidence declined from 36.312/100,000 to 23.613/100,000, with an obvious seasonal peak from May to October. Males were more predisposed to the infection than females (the ratio was 1.118:1). Children < 5 years old comprised the highest incidence (295.892/100,000) among all age categories, and pre-education children comprised the highest proportion (34,658 cases, 50.335%) among all occupational categories. Eight important meteorological factors, including the highest temperature, average temperature, average air pressure, precipitation and sunshine, were correlated with the monthly incidence of BD. The obtained mean absolute percent error (MAPE), mean squared error (MSE) and squared correlation coefficient (R2) of GA_SVR_MONTH values were 0.087, 0.101 and 0.922, respectively. CONCLUSION: From 2009 to 2016, BD incidence in Chongqing was still high, especially in the main urban areas and among the male and pre-education children populations. Eight meteorological factors, including temperature, air pressure, precipitation and sunshine, were the most important correlative feature sets of BD incidence. Moreover, BD incidence prediction models based on meteorological factors had better prediction accuracies. The findings in this study could provide a panorama of BD in Chongqing and offer a useful approach for predicting the incidence of infectious disease. Furthermore, this information could be used to improve current interventions and public health planning.

MicroRNA-26b inhibits hepatitis B virus transcription and replication by targeting the host factor CHORDC1 protein.

Hepatitis B virus (HBV) causes acute and chronic hepatitis in humans, and HBV infection is a major threat to global health. HBV replication is regulated by a series of host factors, including microRNAs (miRNAs), which are highly conserved small noncoding RNAs that participate in a variety of physiological and pathological processes. Here, we report that a chemically synthesized mimic of miR-26b inhibited HBV antigen expression, transcription, and replication, whereas antisense knockdown of endogenous miR-26b enhanced HBV replication in HepG2 cells. Overexpression and knockdown experiments showed that miR-26b significantly decreased HBV enhancer/promoter activities. We identified the cysteine- and histidine-rich domain containing 1 (CHORDC1) as a novel host factor target of miR-26b. CHORDC1 protein but not mRNA was markedly decreased by miR-26b overexpression via base-pairing with complementary sequences in the 3'UTR of its mRNA. Overexpression and knockdown studies showed that CHORDC1 increased viral antigen expression, transcription, and replication by elevating HBV enhancer/promoter activities. Conversely, HBV infection suppressed miR-26b expression and increased CHORDC1 protein levels in human liver cells. Another mature miRNA of the hsa-miR-26 family, miR-26a, had a similar function as miR-26b in targeting CHORDC1 and affecting HBV production. These results suggest that suppression of miR-26b expression up-regulates its target gene CHORDC1, which increases HBV enhancer/promoter activities and promotes viral transcription, gene expression, and replication. Our study could provide new insights into miRNA expression and the persistence of HBV infection.

Human hepatitis B virus surface and e antigens inhibit major vault protein signaling in interferon induction pathways.

BACKGROUND & AIMS: We previously demonstrated that major vault protein (MVP) is a novel virus-induced host factor and its expression upregulates type-I interferon production, leading to cellular antiviral response. However, it remains unclear whether the antiviral function of MVP is impaired during hepatitis B virus (HBV) infection and what mechanisms are involved. Therefore, the aim of this study was to assess whether HBV can alter MVP expression despite the lack of type-I IFN induction and shed light on the underlying mechanisms HBV utilizes to evade host innate immune response. METHODS: The ability of HBV surface and e antigens to inhibit MVP signaling in interferon induction pathways was evaluated by co-immunoprecipitation, immunofluorescence, quantitative RT-PCR, Western blot and reporter assays. RESULTS: In our current study, we found high levels of MVP in peripheral blood mononuclear cells, sera, and liver tissue from HBV-infected patients relative to healthy individuals. We determined that MVP intracellularly associates with MyD88, an adapter protein involved in virus-triggered induction of type-I IFN. Protein truncation analysis revealed that the middle domain of MVP (amino acid residues 310-620) was essential for MyD88 binding. Conversely, HBV inhibited MVP-induced type-I IFN production by suppressing MVP/MyD88 interaction. HBV antigens, both HBsAg and HBeAg, suppressed this interaction by competitively binding to the essential MyD88 binding region of MVP and limiting downstream IFN signaling. CONCLUSIONS: MVP is a virus-induced protein capable of binding with MyD88 leading to type-I IFN production. HBV may evade an immune response by disrupting this interaction and limiting type-I IFN antiviral activity.

Inducible interleukin 32 (IL-32) exerts extensive antiviral function via selective stimulation of interferon λ1 (IFN-λ1).

Interleukin (IL)-32 has been recognized as a proinflammatory cytokine that participates in responses to viral infection. However, little is known about how IL-32 is induced in response to viral infection and the mechanisms of IL-32-mediated antiviral activities. We discovered that IL-32 is elevated by hepatitis B virus (HBV) infection both in vitro and in vivo and that HBV induced IL-32 expression at the level of both transcription and post-transcription. Furthermore, microRNA-29b was found to be a key factor in HBV-regulated IL-32 expression by directly targeting the mRNA 3'-untranslated region of IL-32. Antiviral analysis showed that IL-32 was not sufficient to alter HBV replication in HepG2.2.15 cells. To mimic the viremic phase of viral infection, freshly isolated peripheral blood mononuclear cells were treated with IL-32γ, the secretory isoform, and the supernatants were used for antiviral assays. Surprisingly, these supernatants exhibited extensive antiviral activity against multiplex viruses besides HBV. Thus, we speculated that the IL-32γ-treated peripheral blood mononuclear cells produced and secreted an unknown antiviral factor. Using antibody neutralization assays, we identified the factor as interferon (IFN)-λ1 and not IFN-α. Further studies indicated that IL-32γ effectively inhibited HBV replication in a hydrodynamic injection mouse model. Clinical data showed that elevated levels of IFN-λ1 both in serum and liver tissue of HBV patients were positively correlated to the increased levels of IL-32. Our results demonstrate that elevated IL-32 levels during viral infection mediate antiviral effects by stimulating the expression of IFN-λ1.

The causal relationship between diet habits and cholelithiasis: a comprehensive Mendelian randomization (MR) study.

Background: Epidemiological studies show dietary habits can have an impact on the risk of cholelithiasis, but the relationship is still unclear. We used a comprehensive Mendelian randomization (MR) study to explore the relationship between dietary habits and cholelithiasis. Methods: The 18 dietary habits were divided into six categories: meat foods, cereals, vegetables, fruits, dairy products, beverages, and condiments. Cholelithiasis data came from a GWAS meta-analysis and the FinnGen consortium. The inverse variance weighted (IVW), the weighted median (WM), and MR-Egger approaches were used as the main MR analysis methods. In addition, multiple sensitivity analysis and meta-analysis were performed to verify the robustness of the results. Results: Dried fruit intake [odds ratio (OR) = 0.568; 95% confidence interval (CI), 0.405-0.797; p = 0.001] was discovered to reduce the risk of cholelithiasis. The sensitivity analysis and meta-analysis showed reliable results for the relationship between dried fruit intake and cholelithiasis. Conclusion: Our study found that dried fruit intake is a protective factor in the development of cholelithiasis. However, the mechanisms of action need to be further explored.

PhbZIP2 regulates photosynthesis-related genes in an intertidal macroalgae, Pyropia haitanensis, under stress.

Intertidal macroalgae are important research subjects in stress biology. Basic region-leucine zipper transcription factors (bZIPs) play an important regulatory role in the expression of target genes under abiotic stress. We herein identified a bZIP2 gene PhbZIP2 to regulate abiotic stress tolerance in Pyropia haitanensis, a representative intertidal macroalgal species. Cloning and sequencing of the cDNA characterized a BRLZ structure and an α coiled-coil structure between amino acids and Expression of PhbZIP2 was detected to upregulate under both high temperature and salt stresses. A DAP-seq analysis revealed the PhbZIP2-binding motifs of (T/C)TCCA(C/G) and A (A/G)AAA (G/A), which differed from the conserved motifs in plants. Overexpression of PhbZIP2 was indicative of a high temperature and salt stress tolerances in transgenic Chlamydomonas reinhardtii. It was suggested that PhbZIP2 was probably involved in regulating expression of the photosynthetic-related genes and the response to the abiotic stresses in P. haitanensis, which provide new insights for elucidating efficient adaptation strategies of intertidal macroalgae.

Chrysin Inhibits TAMs-Mediated Autophagy Activation via CDK1/ULK1 Pathway and Reverses TAMs-Mediated Growth-Promoting Effects in Non-Small Cell Lung Cancer.

The natural flavonoid compound chrysin has promising anti-tumor effects. In this study, we aimed to investigate the mechanism by which chrysin inhibits the growth of non-small cell lung cancer (NSCLC). Through in vitro cell culture and animal models, we explored the impact of chrysin on the growth of NSCLC cells and the pro-cancer effects of tumor-associated macrophages (TAMs) and their mechanisms. We observed that M2-TAMs significantly promoted the growth and migration of NSCLC cells, while also markedly activating the autophagy level of these cells. Chrysin displayed a significant inhibitory effect on the growth of NSCLC cells, and it could also suppress the pro-cancer effects of M2-TAMs and inhibit their mediated autophagy. Furthermore, combining network pharmacology, we found that chrysin inhibited TAMs-mediated autophagy activation in NSCLC cells through the regulation of the CDK1/ULK1 signaling pathway, rather than the classical mTOR/ULK1 signaling pathway. Our study reveals a novel mechanism by which chrysin inhibits TAMs-mediated autophagy activation in NSCLC cells through the regulation of the CDK1/ULK1 pathway, thereby suppressing NSCLC growth. This discovery not only provides new therapeutic strategies for NSCLC but also opens up new avenues for further research on chrysin.

Risk factors and drug discovery for cognitive impairment in type 2 diabetes mellitus using artificial intelligence interpretation and graph neural networks.

Background: Among the 382 million diabetic patients worldwide, approximately 30% experience neuropathy, and one-fifth of these patients eventually develop diabetes cognitive impairment (CI). However, the mechanism underlying diabetes CI remains unknown, and early diagnostic methods or effective treatments are currently not available. Objective: This study aimed to explore the risk factors for CI in patients with type 2 diabetes mellitus (T2DM), screen potential therapeutic drugs for T2DM-CI, and provide evidence for preventing and treating T2DM-CI. Methods: This study focused on the T2DM population admitted to the First Affiliated Hospital of Hunan College of Traditional Chinese Medicine and the First Affiliated Hospital of Hunan University of Chinese Medicine. Sociodemographic data and clinical objective indicators of T2DM patients admitted from January 2018 to December 2022 were collected. Based on the Montreal Cognitive Assessment (MoCA) Scale scores, 719 patients were categorized into two groups, the T2DM-CI group with CI and the T2DM-N group with normal cognition. The survey content included demographic characteristics, laboratory serological indicators, complications, and medication information. Six machine learning algorithms were used to analyze the risk factors of T2DM-CI, and the Shapley method was used to enhance model interpretability. Furthermore, we developed a graph neural network (GNN) model to identify potential drugs associated with T2DM-CI. Results: Our results showed that the T2DM-CI risk prediction model based on Catboost exhibited superior performance with an area under the receiver operating characteristic curve (AUC) of 0.95 (specificity of 93.17% and sensitivity of 78.58%). Diabetes duration, age, education level, aspartate aminotransferase (AST), drinking, and intestinal flora were identified as risk factors for T2DM-CI. The top 10 potential drugs related to T2DM-CI, including Metformin, Liraglutide, and Lixisenatide, were selected by the GNN model. Some herbs, such as licorice and cuscutae semen, were also included. Finally, we discovered the mechanism of herbal medicine interventions in gut microbiota. Conclusion: The method based on Interpreting AI and GNN can identify the risk factors and potential drugs associated with T2DM-CI.

Rapid Determination of Polysaccharides in Cistanche Tubulosa Using Near-Infrared Spectroscopy Combined with Machine Learning.

BACKGROUND: Cistanche tubulosa, as a homology of medicine and food, not only has a unique medicinal value but also is widely used in healthcare products. Polysaccharide is one of its important quality indicators. OBJECTIVE: In this study, an analytical model based on near-infrared (NIR) spectroscopy combined with machine learning was established to predict the polysaccharide content of C. tubulosa. METHODS: The polysaccharide content in the samples determined by the phenol-sulfuric acid method was used as a reference value, and machine learning was applied to relate the spectral information to the reference value. Dividing the samples into a calibration set and a prediction set using the Kennard-Stone algorithm. The model was optimized by various preprocessing methods, including Savitzky-Golay (SG), standard normal variate (SNV), multiple scattering correction (MSC), first-order derivative (FD), second-order derivative (SD), and combinations of them. Variable selection was performed through the successive projections algorithm (SPA) and stability competitive adaptive reweighted sampling (sCARS). Four machine learning models were used to build quantitative models, including the random forest (RF), partial least-squares (PLS), principal component regression (PCR), and support vector machine (SVM). The evaluation indexes of the model were the coefficient of determination (R2), root-mean-square error (RMSE), and residual prediction deviation (RPD). RESULTS: RF performs best among the four machine learning models. R2c （calibration set coefficient of determination） and RMSEC （root mean square error of the calibration set）, %, were 0.9763. and 0.3527 for calibration, respectively. R2p （prediction set coefficient of determination）, RMSEP （root mean square error of the prediction set）, %, and RPD were 0.9230, 0.5130, and 3.33 for prediction, respectively. CONCLUSION: The results indicate that NIR combined with the RF is an effective method applied to the quality evaluation of the polysaccharides of C. tubulosa. HIGHLIGHTS: Four quantitative models were developed to predict the polysaccharide content in C. tubulosa, and good results were obtained. The characteristic variables were basically determined by the sCARS algorithm, and the corresponding characteristic groups were analyzed.

Learning from in-group and out-group models induces separative effects on human mate copying.

Mate copying is a social learning process in which individuals gather public information about potential mates by observing models' choices. Previous studies have reported that individual attributes of female models affect mate copying, yet little is known about whether and how the group attributes of models influence mate copying. In the current behavioral and functional magnetic resonance imaging studies, female participants were asked to rate their willingness to choose the depicted males as potential romantic partners before and after observing in-group or out-group female models accepting, rejecting or being undecided (baseline) about the males. Results showed that participants changed their ratings to align with the models' acceptance or rejection choices. Compared to rejection copying, the effect of acceptance copying was stronger and regulated by in- and out-group models, manifesting a discounting copying effect when learning from out-group models. At the neural level, for acceptance copying, stronger temporoparietal junction (TPJ) activity and connectivity between TPJ and anterior medial prefrontal cortex (amPFC) were observed when female models belonged to out-group members; meanwhile, the functional connection of TPJ and amPFC positively predicted the rating changes when learning from out-group models. The results indicated that participants might need more resources to infer out-group members' intentions to overcome the in-group bias during acceptance copying.