Abnormalities in emotion regulation are associated with negative, but not positive or disorganized schizotypy: An experience sampling study.

BACKGROUND: Schizotypy, a multidimensional construct with positive, negative, and disorganized dimensions, represents a vulnerability marker for the development of schizophrenia. Although there has been increasing evidence linking schizotypy to emotion regulation (ER) deficits, the specific association between different schizotypal dimensions and alterations in ER strategy use in daily life remains poorly understood. METHODS: Using the experience sampling method (ESM), the present study examined the associations between positive, negative, and disorganized schizotypy and ER strategy use in daily life in a nonclinical young adult sample (N = 258). Participants were instructed to report their ER strategy use 5 times a day for 14 days. Four adaptive ER strategies (reflection, reappraisal, social sharing, and distraction) and two maladaptive ER strategies (suppression and rumination) were included. RESULTS: Multilevel modeling analyses showed that positive schizotypal traits predicted greater use of adaptive ER strategies, while negative schizotypal traits predicted less use of adaptive ER strategies and more frequent use of emotional suppression in daily life. No associations between disorganized schizotypal traits and any ER strategy use were found. CONCLUSION: Schizotypy dimensions are differentiated by preferences for different ER strategies in daily life. The findings suggest a strong association between negative schizotypy and notable dysfunctions in ER, emphasizing the significance of negative schizotypy as a vulnerability factor for psychosis.

Knowledge, attitudes, and practices among Chinese reproductive-age women toward uterine adenomyosis.

Objective: This study aimed to assess the knowledge, attitudes and practices (KAP) among Chinese reproductive-age women toward uterine adenomyosis. Methods: This web-based cross-sectional study was conducted between April 2023 and September 2023 at the Second Hospital of Hebei Medical University. A self-designed questionnaire was developed to collect demographic information of reproductive-age women, and assess their KAP toward uterine adenomyosis. Results: A total of 520 valid questionnaires were collected. Among the participants, 127 (24.42%) were diagnosed with uterine adenomyosis, and 120 (23.08%) were accompanied by uterine fibroids. The mean knowledge, attitudes and practices scores were 3.54 ± 3.72 (possible range:0-10), 20.96 ± 3.19 (possible range:5-25) and 24.01 ± 4.95 (possible range:7-35), respectively. The structural equation model demonstrated that knowledge had direct effects on attitudes and practices, as indicated by a path coefficient of 0.714 (p < 0.001) and 1.510 (p < 0.001), respectively. Moreover, attitudes had direct effects on practices, with a path coefficient of 0.226 (p = 0.001). Conclusion: The findings revealed that reproductive-age women have insufficient knowledge, negative attitudes, and poor practices toward the uterine adenomyosis. Comprehensive training programs are needed to improve reproductive-age women practices in this area.

[Effects of thinning on accumulation of soil microbial residue carbon of Picea asperata plantations in sub-alpine region of western Sichuan, China]. / 间伐对川西亚高山云杉人工林土壤微生物残体碳积累的影响.

Microbial residues are an important component of soil organic carbon (SOC). It is unclear how long-term thinning affects the accumulation characteristics of microbial residue carbon (C). We analyzed the differences in soil physicochemical properties, microbial communities, extracellular enzyme activities, and microbial residue C in topsoil (0-10 cm) and subsoil (20-30 cm) in Picea asperata plantation of non-thinned (control, 4950 trees·hm-2) and thinned for 14 years (1160 trees·hm-2) stands, aiming to reveal the regulatory mechanism of thinning on microbial residue C accumulation. The results showed that thinning significantly increased SOC content, total nitrogen content, available phosphorus content, the proportion of particulate organic C, soil water content, C-cycle hydrolase, and acid phosphatase activities, but significantly reduced the proportion of mineral-associated organic C. Thinning significantly affected the content of fungal and microbial residue C, and the contribution of microbial residue C to SOC, and these effects were independent of soil layer. The content of fungal and microbial residue C was 25.0% and 24.5% higher under thinning treatments. However, thinning significantly decreased the contribution of microbial residue C to SOC by 12.3%, indicating an increase in the proportion of plant-derived C in SOC. Stepwise regression analysis showed that total nitrogen and soil water content were key factors influencing fungal and micro-bial residue C accumulation. In summary, thinning promoted microbial residue C sequestration by altering soil pro-perties and changed the composition of SOC sources.

Molecular Insights into the Inhibition and Disaggregation Effects of EGCG on Aß40 and Aß42 Cofibrillation.

The misfolding and aggregation of amyloid-ß (Aß) peptides play a pivotal role in the pathogenesis of Alzheimer's disease (AD). Aß40 and Aß42, the two primary isoforms of Aß, can not only self-aggregate into homogeneous aggregates but also coaggregate to form mixed fibrils. Epigallocatechin-3-gallate (EGCG), a prominent tea polyphenol, has shown the capability to prevent the self-aggregation of Aß40 and Aß42 peptides and disaggregate their homogeneous fibrils. However, its effects on the cofibrillation of Aß40 and Aß42 have not yet been explored. Here, we employed molecular dynamic simulations to investigate the effects of EGCG on the coaggregation of Aß40 and Aß42, as well as on their mixed fibril. Our findings indicated that EGCG effectively inhibits the codimerization of Aß40 and Aß42 primarily by impeding the interchain interaction between the two isoforms. The key binding sites for EGCG on Aß40 and Aß42 are the polar residues and aromatic residues, engaging in hydrogen-bond , π-π, and cation-π interactions with EGCG. Additionally, EGCG disaggregates the Aß40-Aß42 mixed fibril by reducing its long-range interaction through similar binding sites and interactions as those between EGCG and Aß40-Aß42 heterodimers. Our research reveals the comprehensive inhibition and disaggregation effects of EGCG on the cofibrillation of Aß isoforms, which provides further support for the development of EGCG as an effective antiaggregation agent for AD.

Elucidating the reversible and irreversible self-assembly mechanisms of low-complexity aromatic-rich kinked peptides and steric zipper peptides.

Many RNA-binding proteins such as fused-in sarcoma (FUS) can self-assemble into reversible liquid droplets and fibrils through the self-association of their low-complexity (LC) domains. Recent experiments have revealed that SYG-rich segments in the FUS LC domains play critical roles in the reversible self-assembly behaviors of FUS. These FUS LC segments alone can self-assemble into reversible kinked fibrils, which are markedly different from the canonical irreversible steric zipper ß-sheet fibrils. However, the molecular determinants underlying the reversible and irreversible self-assembly are poorly understood. Herein we conducted extensive all-atom and coarse-grained molecular dynamics simulations of four representative hexapeptides: two low-complexity aromatic-rich kinked peptides from the amyotrophic lateral sclerosis-related FUS protein, FUS37-42 (SYSGYS) and FUS54-59 (SYSSYG); and two steric zipper peptides from Alzheimer's-associated Aß and Tau proteins, Aß16-21 (KLVFFA) and Tau306-311 (VQIVYK). We dissected their reversible and irreversible self-assembly dynamics, predicted their phase separation behaviors, and elucidated the underpinning molecular interactions. Our simulations showed that alternating stickers (Tyr) and spacers (Gly and Ser) in FUS37-42 and FUS54-59 facilitate the formation of highly dynamic coil-rich oligomers and lead to reversible self-assembly, while consecutive hydrophobic residues of LVFF in Aß16-21 and IVY in Tau306-311 act as hydrophobic patches, favoring the formation of stable ß-sheet-rich oligomers and driving the irreversible self-assembly. Intriguingly, we found that FUS37-42 and FUS54-59 peptides, possessing the same amino acid composition and the same number of sticker and spacer residues, display differential self-assembly propensities. This finding suggests that the self-assembly behaviors of FUS peptides are fine-tuned by the site-specific patterning of spacer residues (Ser and Gly). This study provides significant mechanistic insights into reversible and irreversible peptide self-assembly, which would be helpful for understanding the molecular mechanisms underlying the formation of biological liquid condensates and pathological solid amyloid fibrils.

Design and synthesis of nano-iron oxyhydroxide-based molecularly imprinted electrochemical sensors for trace-level carbendazim detection in actual samples.

Carbendazim (CBD) is widely used as a fungicide that acts as a pesticide in farming to prevent crop diseases. However, CBD can remain on crops for a long time. When consumed by humans and animals, it produces a range of toxic symptoms and poses a serious threat to their health. Therefore, the detection of CBD is necessary. Traditional assay strategies for CBD detection, although sensitive and practical, can hardly achieve fast, robust monitoring during food processing and daily life. Here, we designed a novel electrochemical sensor for CBD detection. In this method, iron oxyhydroxide nanomaterial (ß-FeOOH) was first prepared by hydrothermal method. Then, a molecularly imprinted polymer (MIP) layer was electropolymerized on the surface using CBD as the template and resorcinol (RC) as the functional monomer. The synergistic interaction between ß-FeOOH and MIP endows the MIP/ß-FeOOH/CC-based electrochemical sensor with high specificity and sensitivity. Under optimal conditions, the MIP/ß-FeOOH/CC-based sensor showed a wide linear range of 39 pM-80 nM for CBD and a detection limit as low as 25 pM. Therefore, the as-prepared sensor can be a practical and effective tool for pesticide residue detection.

The Inhibition Effect of Epigallocatechin-3-Gallate on the Co-Aggregation of Amyloid-ß and Human Islet Amyloid Polypeptide Revealed by Replica Exchange Molecular Dynamics Simulations.

Alzheimer's disease and Type 2 diabetes are two epidemiologically linked diseases which are closely associated with the misfolding and aggregation of amyloid proteins amyloid-ß (Aß) and human islet amyloid polypeptide (hIAPP), respectively. The co-aggregation of the two amyloid proteins is regarded as the fundamental molecular mechanism underlying their pathological association. The green tea extract epigallocatechin-3-gallate (EGCG) has been extensively demonstrated to inhibit the amyloid aggregation of Aß and hIAPP proteins. However, its potential role in amyloid co-aggregation has not been thoroughly investigated. In this study, we employed the enhanced-sampling replica exchange molecular dynamics simulation (REMD) method to investigate the effect of EGCG on the co-aggregation of Aß and hIAPP. We found that EGCG molecules substantially diminish the ß-sheet structures within the amyloid core regions of Aß and hIAPP in their co-aggregates. Through hydrogen-bond, π-π and cation-π interactions targeting polar and aromatic residues of Aß and hIAPP, EGCG effectively attenuates both inter-chain and intra-chain interactions within the co-aggregates. All these findings indicated that EGCG can effectively inhibit the co-aggregation of Aß and hIAPP. Our study expands the potential applications of EGCG as an anti-amyloidosis agent and provides therapeutic options for the pathological association of amyloid misfolding disorders.

Structural insights into the co-aggregation of Aß and tau amyloid core peptides: Revealing potential pathological heterooligomers by simulations.

The self-aggregation of amyloid-ß (Aß) and tau proteins are closely implicated in Alzheimer's disease (AD). Recent evidence indicates that Aß and tau proteins can cross-interact to form co-aggregates, which aggravates the development of AD. However, their transient heterooligomer conformations and co-aggregation molecular mechanisms are largely unknown. Herein, we utilize replica exchange molecular dynamics simulations to investigate the conformational ensembles formed by the central hydrophobic core of Aß (Aß16-22) and each of two fibril-nucleating core segments of tau (PHF6* and PHF6). Both PHF6 and PHF6* are found to co-aggregate with Aß16-22 into ß-sheet-rich heterooligomers. Intriguingly, PHF6 and Aß16-22 peptides formed closed ß-barrels, while PHF6* and Aß16-22 formed open ß-barrels, implying their distinct co-aggregation property. Compared to Aß16-22-PHF6*, Aß16-22-PHF6 heterooligomers have higher ß-sheet content, and contain longer ß-strands and larger ß-sheets, indicative of stronger co-aggregation ability of PHF6 with Aß16-22. Further analyses reveal that hydrophobic and π-π stacking interactions between Y310 of PHF6 and Aß16-22 are crucial for the closed ß-barrel/larger ß-sheet formation in Aß16-22-PHF6 heterooligomers. These results highlight the paramount importance of PHF6 fragment, particularly Y310 residue, as a potential target for inhibiting Aß-tau co-aggregation, which could help for effective therapeutic design in mitigating Aß-tau co-aggregation related amyloidogenesis.

Five similar anthocyanidin molecules display distinct disruptive effects and mechanisms of action on Aß1-42 protofibril: A molecular dynamic simulation study.

Alzheimer's disease (AD) is associated with the deposition of amyloid-ß (Aß) fibrillary aggregates. Disaggregation of Aß fibrils is considered as one of the promising AD treatments. Recent experimental studies showed that anthocyanidins, one type of flavonoids abundant in fruits/vegetables, can disaggregate Aß fibrillary aggregates. However, their relative disruptive capacities and underlying mechanisms are largely unknown. Herein, we investigated the detailed interactions between five most common anthocyanidins (cyanidin, aurantinidin, peonidin, delphinidin, and pelargonidin) and Aß protofibril (an intermediate of Aß fibrillization) by performing microsecond molecular dynamic simulations. We found that all five anthocyanidins can destroy F4-L34-V36 hydrophobic core and K28-A42 salt bridge, leading to Aß protofibril destabilization. Aurantinidin exhibits the strongest damage to Aß protofibril (with the most severe disruption on K28-A42 salt bridges), followed by cyanidin (with the most destructive effect on F4-L34-V36 core). Detailed analyses reveal that the protofibril-destruction capacities of anthocyanidins are subtly modulated by the interplay of anthocyanidin-protofibril hydrogen bonding, hydrophobic, aromatic stacking interactions, which are dictated by the number or location of hydroxyl/methyl groups of anthocyanidins. These findings provide important mechanistic insights into Aß protofibril disaggregation by anthocyanidins, and suggest that aurantinidin/cyanidin may serve as promising starting-points for the development of new drug candidates against AD.

Dissecting the Molecular Mechanisms of the Co-Aggregation of Aß40 and Aß42 Peptides: A REMD Simulation Study.

The aggregation of amyloid-ß protein (Aß) into oligomers and amyloid fibrils is closely related to Alzheimer's disease (AD). Aß40 and Aß42, as two most prominent isoforms of Aß peptides, can cross-interact with each other and form co-aggregates, which affect the progression of the disease. However, the molecular determinants underlying Aß40 and Aß42 cross-interaction and the structural details of their co-oligomers remain elusive. Herein, we performed all-atom explicit-solvent replica exchange molecular dynamics simulations on Aß40-Aß42 heterogeneous and Aß40/Aß42 homogeneous dimer systems to dissect the co-aggregation mechanisms of the two isoforms. Our results show that the interpeptide main-chain interaction of Aß40-Aß42 is stronger than that of Aß40-Aß40 and Aß42-Aß42. The positions of hotspot residues in heterodimers and homodimers display high similarity, implying similar molecular recognition sites for both cross-interaction and self-interaction. Contact maps of Aß40-Aß42 heterodimers reveal that residue pairs crucial for cross-interaction are mostly located in the C-terminal hydrophobic regions of Aß40 and Aß42 peptides. Conformational analysis shows that Aß40 and Aß42 monomers can co-assemble into ß-sheet-rich heterodimers with shorter ß-sheets than those in homodimers, which is decremental to monomer addition. Similar molecular recognition sites and ß-sheet distribution of Aß40 and Aß42 peptides are observed in heterodimers and homodimers, which may provide the molecular basis for the two isoforms' co-aggregation and cross-seeding. Our work dissects the co-aggregation mechanisms of Aß40 and Aß42 peptides at the atomic level, which will help for in-depth understanding of the cross-talk between the two Aß isoforms and the pathogenesis of AD.

Multi-omics analysis reveals a molecular landscape of the early recurrence and early metastasis in pan-cancer.

Cancer remains a formidable challenge in medicine due to its propensity for recurrence and metastasis, which can result in unfavorable treatment outcomes. This challenge is particularly acute for early-stage patients, who may experience recurrence and metastasis without timely detection. Here, we first analyzed the differences in clinical characteristics among the primary tumor, recurrent tumor, and metastatic tumor in different stages of cancer, which may be caused by the molecular level. Moreover, the importance of predicting early cancer recurrence and metastasis is emphasized by survival analyses. Next, we used a multi-omics approach to identify key molecular changes associated with early cancer recurrence and metastasis and discovered that early metastasis in cancer demonstrated a high degree of genomic and cellular heterogeneity. We performed statistical comparisons for each level of omics data including gene expression, mutation, copy number variation, immune cell infiltration, and cell status. Then, various analytical techniques, such as proportional hazard model and Fisher's exact test, were used to identify specific genes or immune characteristics associated with early cancer recurrence and metastasis. For example, we observed that the overexpression of BPIFB1 and high initial B-cell infiltration levels are linked to early cancer recurrence, while the overexpression or amplification of ANKRD22 and LIPM, mutation of IGHA1 and MUC16, high fibroblast infiltration level, M1 polarization of macrophages, cellular status of DNA repair are all linked to early cancer metastasis. These findings have led us to construct classifiers, and the average area under the curve (AUC) of these classifiers was greater than 0.75 in The Cancer Genome Atlas (TCGA) cancer patients, confirming that the features we identified could be biomarkers for predicting recurrence and metastasis of early cancer. Finally, we identified specific early sensitive targets for targeted therapy and immune checkpoint inhibitor therapy. Once the biomarkers we identified changed, treatment-sensitive targets can be treated accordingly. Our study has comprehensively characterized the multi-omics characteristics and identified a panel of biomarkers of early cancer recurrence and metastasis. Overall, it provides a valuable resource for cancer recurrence and metastasis research and improves our understanding of the underlying mechanisms driving early cancer recurrence and metastasis.

Integration of multi-omics data reveals a novel hybrid breast cancer subtype and its biomarkers.

Tumor heterogeneity in breast cancer hinders proper diagnosis and treatment, and the identification of molecular subtypes may help enhance the understanding of its heterogeneity. Therefore, we proposed a novel integrated multi-omics approach for breast cancer typing, which led to the identification of a hybrid subtype (Mix_Sub subtype) with a poor survival prognosis. This subtype is characterized by lower levels of the inflammatory response, lower tumor malignancy, lower immune cell infiltration, and higher T-cell dysfunction. Moreover, we found that cell-cell communication mediated by NCAM1-FGFR1 ligand-receptor interaction and cellular functional states, such as cell cycle, DNA damage, and DNA repair, were significantly altered and upregulated in patients with this subtype, and that such patients displayed greater sensitivity to targeted therapies. Subsequently, using differential genes among subtypes as biomarkers, we constructed prognostic risk models and subtype classifiers for the Mix_Sub subtype and validated their generalization ability in external datasets obtained from the GEO database, indicating their potential therapeutic and prognostic significance. These biomarkers also showed significant spatially variable expression in malignant tumor cells. Collectively, the identification of the Mix_Sub breast cancer subtype and its biomarkers, based on the driving relationship between omics, has deepened our understanding of breast cancer heterogeneity and facilitated the development of breast cancer precision therapy.

Identification of Potential Lead Compounds Targeting Novel Druggable Cavity of SARS-CoV-2 Spike Trimer by Molecular Dynamics Simulations.

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become an urgent public health problem. Spike (S) protein mediates the fusion between the virus and the host cell membranes, consequently emerging as an important target of drug design. The lack of comparisons of in situ full-length S homotrimer structures in different states hinders understanding the structures and revealing the function, thereby limiting the discovery and development of therapeutic agents. Here, the steady-state structures of the in situ full-length S trimer in closed and open states (Sclosed and Sopen) were modeled with the constraints of density maps, associated with the analysis of the dynamic structural differences. Subsequently, we identified various regions with structure and property differences as potential binding pockets for ligands that promote the formation of inactive trimeric protein complexes. By using virtual screening strategy and a newly defined druggable cavity, five ligands were screened with potential bioactivities. Then molecular dynamic (MD) simulations were performed on apo protein structures and ligand bound complexes to reveal the conformational changes upon ligand binding. Our simulation results revealed that sulforaphane (SFN), which has the best binding affinity, could inhibit the conformational changes of S homotrimer that would occur during the viral membrane fusion. Our results could aid in the understanding of the regulation mechanism of S trimer aggregation and the structure-activity relationship, facilitating the development of potential antiviral agents.

Molecular insights into the inhibition mechanism of harringtonine against essential proteins associated with SARS-CoV-2 entry.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has recently posed a serious threat to global public health. Harringtonine (HT), as a small-molecule antagonist, has antiviral activity against a variety of viruses. There is evidence that HT can inhibit the SARS-CoV-2 entry into host cells by blocking the Spike protein and transmembrane protease serine 2 (TMPRSS2). However, the molecular mechanism underlying the inhibition effect of HT is largely elusive. Here, docking and all-atom molecular dynamics simulations were used to investigate the mechanism of HT against the receptor binding domain (RBD) of Spike, TMPRSS2, as well as the complex of RBD and angiotensin-converting enzyme 2 complex (RBD-ACE2). The results reveal that HT binds to all proteins primarily through hydrogen bond and hydrophobic interactions. Binding with HT influences the structural stability and dynamic motility processes of each protein. The interactions of HT with residues N33, H34 and K353 of ACE2, and residue K417 and Y453 of RBD contribute to disrupting the binding affinity between RBD and ACE2, which may hinder the virus entry into host cells. Our research provides molecular insights into the inhibition mechanism of HT against SARS-CoV-2 associated proteins, which will help for the novel antiviral drugs development.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior.

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

ALS-Linked A315T and A315E Mutations Enhance ß-Barrel Formation of the TDP-43307-319 Hexamer: A REST2 Simulation Study.

Pathogenic mutations of transactivation response element DNA-binding protein 43 (TDP-43) are closely linked with amyotrophic lateral sclerosis (ALS). It was recently reported that two ALS-linked familial mutants A315T and A315E of TDP-43307-319 peptides can self-assemble into oligomers including tetramers, hexamers, and octamers, among which hexamers were suggested to form the ß-barrel structure. However, due to the transient nature of oligomers, their conformational properties and the atomic mechanisms underlying the ß-barrel formation remain largely elusive. Herein, we investigated the hexameric conformational distributions of the wild-type (WT) TDP-43307-319 fragment and its A315T and A315E mutants by performing all-atom explicit-solvent replica exchange with solute tempering 2 simulations. Our simulations reveal that each peptide can self-assemble into diverse conformations including ordered ß-barrels, bilayer ß-sheets and/or monolayer ß-sheets, and disordered complexes. A315T and A315E mutants display higher propensity to form ß-barrel structures than the WT, which provides atomic explanation for their enhanced neurotoxicity reported previously. Detailed interaction analysis shows that A315T and A315E mutations increase inter-molecular interactions. Also, the ß-barrel structures formed by the three different peptides are stabilized by distinct inter-peptide side-chain hydrogen bonding, hydrophobic, and aromatic stacking interactions. This study demonstrates the enhanced ß-barrel formation of the TDP-43307-319 hexamer by the pathogenic A315T and A315E mutations and reveals the underlying molecular determinants, which may be helpful for in-depth understanding of the ALS-mutation-induced neurotoxicity of TDP-43 protein.

EGCG attenuates α-synuclein protofibril-membrane interactions and disrupts the protofibril.

The fibrillary aggregates of α-synuclein (α-syn) are closely associated with the etiology of Parkinson's disease (PD). Mounting evidence shows that the interaction of α-syn with biological membranes is a culprit for its aggregation and cytotoxicity. While some small molecules can effectively inhibit α-syn fibrillization in solution, their potential roles in the presence of membrane are rarely studied. Among them, green tea extract epigallocatechin gallate (EGCG) is currently under active investigation. Herein, we investigated the effects of EGCG on α-syn protofibril (an intermediate of α-syn fibril formation) in the presence of a model membrane and on the interactions between α-syn protofibril and the membrane, as well as the underlying mechanisms, by performing microsecond all-atom molecular dynamics simulations. The results show that EGCG has destabilization effects on α-syn protofibril, albeit to a lesser extent than that in solution. Intriguingly, we find that EGCG forms overwhelming H-bonding and cation-π interactions with membrane and thus attenuates protofibril-membrane interactions. Moreover, the decreased protofibril-membrane interactions impede the membrane damage by α-syn protofibril and enable the membrane integrity. These findings provide atomistic understanding towards the attenuation of α-syn protofibril-induced cytotoxicity by EGCG in cellular environment, which is helpful for the development of EGCG-based therapeutic strategies against PD.

Au/Fe3O4-based nanozymes with peroxidase-like activity integrated in immunochromatographic strips for highly-sensitive biomarker detection.

Because of their simplicity, rapidity, and cost-effectiveness, immunochromatographic strips (ICTs) have been widely used as an effective tool in various fields. However, typical strips for the preliminary screening suffer from limited detection sensitivity, particularly in biomarker detection with trace concentration. Herein, to tackle this challenge, we integrated homemade gold-decorated Fe3O4 nanoparticles (Au/Fe3O4 NPs) with flexible strips, exploring the excellent peroxidase-like activity of this labeled material, and then enhancing the detection sensitivity via signal amplification. The limit of detection (LOD) of the strips is as low as 0.05 mIU mL-1 when human chorionic gonadotropin (hCG) is as a biomarker model, which is 500 times lower than that of the traditional color-based strip. Overall, our results demonstrated the potential for Au/Fe3O4 NP based-ICTs for the rapid detection of the biomarker in an instrument-free and point-of-care testing format.

Accounting Conformational Dynamics into Structural Modeling Reflected by Cryo-EM with Deep Learning.

With the continuous development of structural biology, the requirement for accurate threedimensional structures during functional modulation of biological macromolecules is increasing. Therefore, determining the dynamic structures of bio-macromolecular at high resolution has been a highpriority task. With the development of cryo-electron microscopy (cryo-EM) techniques, the flexible structures of biomacromolecules at the atomic resolution level grow rapidly. Nevertheless, it is difficult for cryo-EM to produce high-resolution dynamic structures without a great deal of manpower and time. Fortunately, deep learning, belonging to the domain of artificial intelligence, speeds up and simplifies this workflow for handling the high-throughput cryo-EM data. Here, we generalized and summarized some software packages and referred algorithms of deep learning with remarkable effects on cryo-EM data processing, including Warp, user-free preprocessing routines, TranSPHIRE, PARSED, Topaz, crYOLO, and self-supervised workflow, and pointed out the strategies to improve the resolution and efficiency of three-dimensional reconstruction. We hope it will shed some light on the bio-macromolecular dynamic structure modeling with the deep learning algorithms.