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Abstract Spider silk exhibits an excellent combination of high strength and toughness, which originates from the hierarchical self-assembled structure of spidroin during fiber spinning. In this work, superfine nanofibrils are established in polyelectrolyte artificial spider silk by optimizing the flexibility of polymer chains, which exhibits combination of breaking strength and toughness ranging from 1.83 GPa and 238 MJ m−3 to 0.53 GPa and 700 MJ m−3, respectively. This is achieved by introducing ions to control the dissociation of polymer chains and evaporation-induced self-assembly under external stress. In addition, the artificial spider silk possesses thermally-driven supercontraction ability. This work provides inspiration for the design of high-performance fiber materials.

Abstract Background More than half of patients with tuberous sclerosis complex (TSC) suffer from drug-resistant epilepsy (DRE), and resection surgery is the most effective way to control intractable epilepsy. Precise preoperative localization of epileptogenic tubers among all cortical tubers determines the surgical outcomes and patient prognosis. Models for preoperatively predicting epileptogenic tubers using 18F-FDG PET images are still lacking, however. We developed noninvasive predictive models for clinicians to predict the epileptogenic tubers and the outcome (seizure freedom or no seizure freedom) of cortical tubers based on 18F-FDG PET images. Methods Forty-three consecutive TSC patients with DRE were enrolled, and 235 cortical tubers were selected as the training set. Quantitative indices of cortical tubers on 18F-FDG PET were extracted, and logistic regression analysis was performed to select those with the most important predictive capacity. Machine learning models, including logistic regression (LR), linear discriminant analysis (LDA), and artificial neural network (ANN) models, were established based on the selected predictive indices to identify epileptogenic tubers from multiple cortical tubers. A discriminating nomogram was constructed and found to be clinically practical according to decision curve analysis (DCA) and clinical impact curve (CIC). Furthermore, testing sets were created based on new PET images of 32 tubers from 7 patients, and follow-up outcome data from the cortical tubers were collected 1, 3, and 5 years after the operation to verify the reliability of the predictive model. The predictive performance was determined by using receiver operating characteristic (ROC) analysis. Results PET quantitative indices including SUVmean, SUVmax, volume, total lesion glycolysis (TLG), third quartile, upper adjacent and standard added metabolism activity (SAM) were associated with the epileptogenic tubers. The SUVmean, SUVmax, volume and TLG values were different between epileptogenic and non-epileptogenic tubers and were associated with the clinical characteristics of epileptogenic tubers. The LR model achieved the better performance in predicting epileptogenic tubers (AUC = 0.7706; 95% CI 0.70–0.83) than the LDA (AUC = 0.7506; 95% CI 0.68–0.82) and ANN models (AUC = 0.7425; 95% CI 0.67–0.82) and also demonstrated good calibration (Hosmer‒Lemeshow goodness-of-fit p value = 0.7). In addition, DCA and CIC confirmed the clinical utility of the nomogram constructed to predict epileptogenic tubers based on quantitative indices. Intriguingly, the LR model exhibited good performance in predicting epileptogenic tubers in the testing set (AUC = 0.8502; 95% CI 0.71–0.99) and the long-term outcomes of cortical tubers (1-year outcomes: AUC = 0.7805, 95% CI 0.71–0.85; 3-year outcomes: AUC = 0.8066, 95% CI 0.74–0.87; 5-year outcomes: AUC = 0.8172, 95% CI 0.75–0.87). Conclusions The 18F-FDG PET image-based LR model can be used to noninvasively identify epileptogenic tubers and predict the long-term outcomes of cortical tubers in TSC patients.

Abstract The formation of biofilms is closely associated with persistent and chronic infections, and physiological heterogeneity such as pH and oxygen gradients renders biofilms highly resistant to conventional antibiotics. To date, effectively treating biofilm infections remains a significant challenge. Herein, we report the fabrication of micellar nanoparticles adapted to heterogeneous biofilm microenvironments, enabling nitric oxide (NO) release through two distinct photoredox catalysis mechanisms. The key design feature involves the use of tertiary amine (TA) moieties, which function as sacrificial agents to avoid the quenching of photocatalysts under normoxic and neutral pH conditions and proton acceptors at acidic pH to allow deep biofilm penetration. This biofilm-adaptive NO-releasing platform shows excellent antibiofilm activity against ciprofloxacin-resistant Pseudomonas aeruginosa (CRPA) biofilms both in vitro and in a mouse skin infection model, providing a strategy for combating biofilm heterogeneity and biofilm-related infections.

Habenaria and Liparis are well-known orchid genera that grow in terrestrial habitats in the tropics, subtropics or temperate zones. Three species have been found in subtropical regions of China, inhabiting terrestrial to epiphytic habitats. This study focuses on three species, H. dentata (distributed in Asia), H. yachangensis, and L. gigantea. For H. yachangensis and L. gigantea, there is no information about the mycorrhizal community in these species. This study aims to conduct the fungal community screening of Chinese ground orchids from subtropical regions. We performed a comparative analysis of the fungal community among H. dentata, H. yachangensis, and L. gigantea, determining their ITS regions using NGS paired-end sequences. The results clarified the diversity and the predominance of fungal genera. Ascomycota was abundant compared to Basidiomycota or other fungi groups in all communities, with a high dominance in all populations, especially for L. gigantea. At different root spatial locations, the fungal community diversity and richness were higher in the soil than in the rhizosphere or inner root. However, the results suggest that L. gigantea has a different fungal community compared to Habenaria species. In this order, the subtropical terrestrial orchids have a different fungal network compared to the northern terrestrial orchids. Also, there is a high probability of co-existence and co-evolution of endophytic fungi in these terrestrial orchids, indicating the potential role of host plants in selecting an endophytic fungal community. Furthermore, our results highlight the need to elucidate the microbe interactions of these unique orchids for long-term purposes, such as isolating indigenous fungi for suitable inoculants for further orchid propagation, restoration, and conservation.

[This corrects the article DOI: 10.1371/journal.pone.0271231.].

Abstract Background In the new International League Against Epilepsy (ILAE) classification of seizure types, generalized seizures such as absence seizures (ASs) may originate from a focal point and rapidly spread to the bilaterally distributed brain network. Increasing evidence from animal and clinical studies has indicated that focal changes may occur prior to ASs; however, the relationship of ASs with epileptogenic lesions remains unclear. Methods We retrospectively collected and analyzed the clinical, imaging, and electrophysiological data of 16 patients who had ASs and structural lesions with seizure-free outcomes after lesion resection. Results In semiology analysis, nine patients displayed focal onset; only two patients showed simple ASs, and seizure types other than ASs were observed in the remaining patients. On ictal electroencephalography (EEG), four patients showed bilateral synchronous symmetric 3 Hz generalized spike-wave discharges (GSWDs), and the remaining patients showed bilateral 1.5–2.5 Hz GSWDs. Moreover, most patients (13/16, 81.3%) exhibited focal features in addition to ASs, while interictal EEG was the same in 12 patients. Furthermore, on stereoelectroencephalogram (SEEG), 2/5 patients showed focal discharges before bilateral burst GSWDs. Additionally, all patients had structural lesions on imaging. In four typical AS patients, the lesions were located in deep brain regions. Notably, in 9 patients (9/16, 56%), the lesions were located in the posterior cortex. All patients underwent lesion resection and had seizure-free outcomes during follow-up, and intelligence quotient (IQ) also improved by 10.71 ± 3.90 one year after surgery. Conclusions Patients with lesion-related epilepsy may present with ASs that have a focal onset and are associated with good surgical outcomes.

In academia, it is rare for an event or issue to foster the extensive participation of multiple disciplines. Research related to COVID-19 has undeniably yielded a wealth of valuable insights and impetus for the progress of interdisciplinary research, encompassing concepts, methodologies, intellectual approaches, theories, frameworks, data integration and analysis, and pertinent considerations. In the academic community, there is a widespread expectation that as science and technology continue to progress, the convergence of medicine with various other fields will gain momentum. Fields like computer science are anticipated to see expanded applications in domains such as medicine, vaccine research, disease diagnosis, and more. This study aims to examine interdisciplinary approaches in health-related research, particularly in the context of COVID-19. The goal is to analyze and comprehend the involvement and collaboration patterns of various disciplines in pandemic research, with a specific emphasis on the role and integration level of computer science. This study analyzed 240,509 COVID-19 related articles published from December 2019 to September 2022 using methods such as chord diagrams, modularity analysis, and eigenvector centrality analysis in Social Networking Analysis (SNA). The findings revealed an emerging trend of integration trend between Humanities & Social Sciences and Natural Sciences. Expectations that computer science would prominently feature in pandemic research during this technology-driven era haven’t materialized. While it maintains links with engineering, it hasn’t formed strong connections with medicine. This indicates a gap between computer science and core medical research in large-scale health crises, where COVID-19 research remains centered on medicine with varying interdisciplinary collaboration, and high-tech disciplines like computer science have not achieved their expected influence in these studies.

Conjugated polymers (CPs) have attracted much attention in recent years due to their structural abundance and tunable energy bands. Compared with CP-based materials, the inorganic semiconductor TiO2 has the advantages of low cost, non-toxicity and high photocatalytic hydrogen production (PHP) performance. However, studies on polymeric-inorganic heterojunctions, composed of D-A type CPs and TiO2, for boosting the PHP efficiency are still rare. Herein, an elucidation that the photocatalytic hydrogen evolution activity can actually be improved by forming polymeric-inorganic heterojunctions TFl@TiO2, TS@TiO2 and TSO2@TiO2, facilely synthesized through efficient in situ direct C–H arylation polymerization, is given. The compatible energy levels between virgin TiO2 and polymeric semiconductors enable the resulting functionalized CP@TiO2 heterojunctions to exhibit a considerable photocatalytic hydrogen evolution rate (HER). Especially, the HER of TSO2@TiO2 heterojunction reaches up to 11,220 μmol g−1 h−1, approximately 5.47 and 1260 times higher than that of pristine TSO2 and TiO2 photocatalysts. The intrinsic merits of a donor-acceptor conjugated polymer and the interfacial interaction between CP and TiO2 account for the excellent PHP activity, facilitating the separation of photo-generated excitons. Considering the outstanding PHP behavior, our work discloses that the coupling of inorganic semiconductors and suitable D-A conjugated CPs would play significant roles in the photocatalysis community.

PEGylation, which covalently modifies small-molecule drugs, peptides and proteins with polyethylene glycol (PEG) to improve their pharmacokinetics and efficacy, has become one of the most widely used drug modification techniques. However, PEG and its derivatives have been verified to be immunogenic and antigenic, which directly lead to side effects such as accelerated blood clearance (ABC) phenomenon and allergic reactions to PEGylated drugs or PEG excipients. Recent development of single molecular weight discrete PEG synthesis methodology have led to continuous and extensive focus on the difference in biological activity between conventional polydisperse PEG and single molecular weight precise PEG. Discrete PEG has demonstrated obvious advantages in resisting protein adsorption, cell adhesion and enhancing drug efficacy. These preliminary results not only confirm the significant impact of PEG chain polydispersity on its biological effect, but also reveal the possibility and potential advantages of using discrete PEG to reduce the immunogenicity and antigenicity. Hopefully, single chemical structure and molecular weight ensure the batch repeatability of newly developed discrete PEG products, and facilitate the understanding of their physicochemical properties and biological effects that promoting the clinical conversion of precise PEG drugs.

Introduction: Temporal lobe epilepsy (TLE) is the most common subtype of epilepsy in adults and is characterized by neuronal loss, gliosis, and sprouting mossy fibers in the hippocampus. But the mechanism underlying neuronal loss has not been fully elucidated. A new programmed cell death, cuproptosis, has recently been discovered; however, its role in TLE is not clear.Methods: We first investigated the copper ion concentration in the hippocampus tissue. Then, using the Sample dataset and E-MTAB-3123 dataset, we analyzed the features of 12 cuproptosis-related genes in TLEs and controls using the bioinformatics tools. Then, the expression of the key cuproptosis genes were confirmed using real-time PCR and immunohistochemical staining (IHC). Finally, the Enrichr database was used to screen the small molecules and drugs targeting key cuproptosis genes in TLE.Results: The Sample dataset displayed four differentially expressed cuproptosis-related genes (DECRGs; LIPT1, GLS, PDHA1, and CDKN2A) while the E-MTAB-3123 dataset revealed seven DECRGs (LIPT1, DLD, FDX1, GLS, PDHB, PDHA1, and DLAT). Remarkably, only LIPT1 was uniformly upregulated in both datasets. Additionally, these DECRGs are implicated in the TCA cycle and pyruvate metabolism—both crucial for cell cuproptosis—as well as various immune cell infiltrations, especially macrophages and T cells, in the TLE hippocampus. Interestingly, DECRGs were linked to most infiltrating immune cells during TLE’s acute phase, but this association considerably weakened in the latent phase. In the chronic phase, DECRGs were connected with several T-cell subclasses. Moreover, LIPT1, FDX1, DLD, and PDHB were related to TLE identification. PCR and IHC further confirmed LIPT1 and FDX1’s upregulation in TLE compared to controls. Finally, using the Enrichr database, we found that chlorzoxazone and piperlongumine inhibited cell cuproptosis by targeting LIPT1, FDX1, DLD, and PDHB.Conclusion: Our findings suggest that cuproptosis is directly related to TLE. The signature of cuproptosis-related genes presents new clues for exploring the roles of neuronal death in TLE. Furthermore, LIPT1 and FDX1 appear as potential targets of neuronal cuproptosis for controlling TLE’s seizures and progression.

Research on the efficiency and quality issues faced in aircraft assembly was conducted in this article. A new method of human–machine collaborative riveting was proposed, which combined the flexibility of manual collaboration with the precise control of automatic riveting. The research works include: (1) a theoretical model of pneumatic hammer riveting was established to clarify the principle and parameters of riveting process. (2) A smart bucking bar was designed to support the data collection and extraction of manual collaborative riveting process. (3) An automatic riveting experimental platform was designed to test the automatic riveting process incorporating the extracted manual riveting process parameters, and further an optimization strategy was proposed for the automatic riveting process. (4) A human–machine collaborative riveting experimental platform was developed to conduct the verification work. Through the theoretical analysis, experimental research, system scheme design, and process parameters optimization, the application and verification of human–machine collaborative assembly technology have been achieved. This technology is expected to be comprehensively promoted in the field of aircraft manufacturing, and for breaking through the current difficulties of low production efficiency and poor assembly quality control.

Due to their structural and property tunability, semiconductive conjugated polymers (CPs) have emerged as promising candidates for photocatalytic water splitting. Compared with inorganic materials, the photocatalytic performance of mono-component polymers was limited by the fast recombination of photoexcited charge carriers, and they always needed to catch up to expectations. To this end, researchers established molecular donor–acceptor heterostructures, which could notably promote oxygen production efficiency due to their more effective charge carrier separation. In this work, easy Schiff base reactions between side-chain -CHO groups and terminal -NH2 groups were used to introduce benzene and perylene diimide (PDI) into the molecular heterostructure to serve as electron donors (D) and electron acceptors (A). In particular, for the first time, we employed the molecular heterostructures of CPs to promote photocatalytic O2 production. One prepared molecular heterostructure was demonstrated to improve oxygen generation rate (up to 0.53 mmol g−1 h−1) through visible light-driven water splitting. Interestingly, based on the photoelectric properties, a stepwise two-electron/two-electron pathway constituted the photocatalytic mechanism for oxygen production with the molecular heterostructure. These results provide insights into designing and fabricating high-performance molecular heterostructures for photocatalytic oxygen production.

Permselectivity of cellular membranes is crucial to normal cellular function but this has been hard to replicate in artificial cells. Here, the authors use pH-responsive polymersomes containing Schiff base moieties which can be used to control mesh size allowing for selective permeability control creating responsive systems.

BackgroundGenetic factors have been found to be associated with the efficacy and adverse reactions of antiseizure medications. BCL11A is an important regulator of the development of neuronal networks. However, the role of BCL11A in epilepsy remains unclear. This study aimed to evaluate the genetic association of BCL11A with the susceptibility to develop epileptic seizures and therapeutic response of patients with epilepsy in Han Chinese.MethodsWe matched 450 epilepsy cases with 550 healthy controls and 131 drug-resistant epilepsy patients with 319 drug-responsive epilepsy patients from two different centers. Genetic association analysis, genetic interaction analysis, expression quantitative trait loci analysis and protein–protein interaction analysis were conducted.ResultsOur results showed that rs2556375 not only increases susceptibility to develop epileptic seizures (OR = 2.700, 95% = 1.366–5.338, p = 0.004 and OR = 2.984, 95% = 1.401–6.356, p = 0.005, respectively), but also increases the risk of drug resistance(OR = 21.336, 95%CI =2.489–183.402, p = 0.005). The interaction between rs2556375 and rs12477097 results in increased risk for pharma coresistant. In addition, rs2556375 regulated BCL11A expression in human brain tissues (p = 0.0096 and p = 0.033, respectively). Furthermore, the protein encoded by BCL11A interacted with targets of approved antiepileptic drugs.ConclusionBCL11A may be a potential therapeutic target for epilepsy. Rs2556375 may increase the risks of epilepsy and drug resistance by regulating BCL11A expression in human brain tissues. Moreover, the interaction between rs2556375 and rs12477097 results in increased risk for drug resistance.

Abstract Background Focal cortical dysplasia type IIb (FCDIIb) and tuberous sclerosis complex (TSC) show persistent neuroinflammation, which promotes epileptogenesis and epilepsy progression, suggesting that endogenous resolution of inflammation is inadequate to relieve neuronal network hyperexcitability. To explore the potential roles of formyl peptide receptor 2 (FPR2), which is a key regulator of inflammation resolution, in epilepsy caused by FCDIIb and TSC, we examined the expression and cellular distribution of FPR2. Method The expression of FPR2 and nuclear factor‐κB (NF‐κB) signaling pathway was examined by real‐time PCR, western blots, and analyzed via one‐way analysis of variance. The distribution of FPR2 was detected using immunostaining. The expression of resolvin D1 (RvD1, the endogenous ligand of FPR2) was observed via enzyme‐linked immunosorbent assay. Pearson's correlation test was used to evaluate the correlation between the expression levels of FPR2 and RvD1 and the clinical variants. Results The expression of FPR2 was significantly lower in FCDIIb (p = .0146) and TSC (p = .0006) cortical lesions than in controls, as was the expression of RvD1 (FCDIIb: p = .00431; TSC: p = .0439). Weak FPR2 immunoreactivity was observed in dysmorphic neurons (DNs), balloon cells (BCs), and giant cells (GCs) in FCDIIb and TSC tissues. Moreover, FPR2 was mainly distributed in dysplastic neurons; it was sparse in microglia and nearly absent in astrocytes. The NF‐κB pathway was significantly activated in patients with FCDIIb and TSC, and the protein level of NF‐κB was negatively correlated with the protein level of FPR2 (FCDIIb: p = .00395; TSC: p = .0399). In addition, the protein level of FPR2 was negatively correlated with seizure frequency in FCDIIb (p = .0434) and TSC (p = .0351) patients. Conclusion In summary, these results showed that the expression and specific distribution of FPR2 may be involved in epilepsy caused by FCDIIb and TSC, indicating that downregulation of FPR2 mediated the dysfunction of neuroinflammation resolution in FCDIIb and TSC.

Abstract Background Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear. Methods A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model and was validated with real-world data. The input data were obtained from official websites and the published literature. Results The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies. Conclusions The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic. Keyords COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.

Conjugated polymer photocatalysts for hydrogen production have the advantages of an adjustable structure, strong response in the visible light region, adjustable energy levels, and easy functionalization. Using an atom- and step-economic direct C–H arylation method, dibromocyanostilbene was polymerized with thiophene, dithiophene, terthiophene, and fused thienothiophene and dithienothiophene, respectively, to produce donor–acceptor (D-A)-type linear conjugated polymers containing different thiophene derivatives with different conjugation lengths. Among them, the D-A polymer photocatalyst constructed from dithienothiophene could significantly broaden the spectral response, with a hydrogen evolution rate up to 12.15 mmol h−1 g−1. The results showed that the increase in the number of fused rings on thiophene building blocks was beneficial to the photocatalytic hydrogen production of cyanostyrylphene-based linear polymers. For the unfused dithiophene and terthiophene, the increase in the number of thiophene rings enabled more rotation freedom between the thiophene rings and reduced the intrinsic charge mobility, resulting in lower hydrogen production performance accordingly. This study provides a suitable process for the design of electron donors for D-A polymer photocatalysts.

Abstract Background Partial- or full-lockdowns, among other interventions during the COVID-19 pandemic, may disproportionally affect people (their behaviors and health outcomes) with lower socioeconomic status (SES). This study examines income-related health inequalities and their main contributors in China during the pandemic. Methods The 2020 China COVID-19 Survey is an anonymous 74-item survey administered via social media in China. A national sample of 10,545 adults in all 31 provinces, municipalities, and autonomous regions in mainland China provided comprehensive data on sociodemographic characteristics, awareness and attitudes towards COVID-19, lifestyle factors, and health outcomes during the lockdown. Of them, 8448 subjects provided data for this analysis. Concentration Index (CI) and Corrected CI (CCI) were used to measure income-related inequalities in mental health and self-reported health (SRH), respectively. Wagstaff-type decomposition analysis was used to identify contributors to health inequalities. Results Most participants reported their health status as “very good” (39.0%) or “excellent” (42.3%). CCI of SRH and mental health were − 0.09 (p

In this paper, an atom- and step-economic direct C-H arylation polymerization (DArP) strategy was developed to access cyanostyrylthiophene (CST)-based donor–acceptor (D–A) conjugated polymers (CPs) used for photocatalytic hydrogen production (PHP) from water reduction. The new CST-based CPs CP1–CP5 with varied building blocks were systematically studied by X-ray single-crystal analysis, FTIR, scanning electron microscopy, UV-vis, photoluminescence, transient photocurrent response, cyclic voltammetry measurements, and a PHP test, which showed that the phenyl-cyanostyrylthiophene-based CP3 exhibits a superior hydrogen evolution rate (7.60 mmol h−1 g−1) compared to other conjugated polymers. The structure–property–performance correlation results obtained in this study will provide an important guideline for the rational design of high-performance D–A CPs for PHP applications.

The rapid spread of COVID-19 in Ethiopia was attributed to joint effects of multiple factors such as low adherence to face mask-wearing, failure to comply with social distancing measures, many people attending religious worship activities and holiday events, extensive protests, country election rallies during the pandemic, and the war between the federal government and Tigray Region. This study built a system dynamics model to capture COVID-19 characteristics, major social events, stringencies of containment measures, and vaccination dynamics. This system dynamics model served as a framework for understanding the issues and gaps in the containment measures against COVID-19 in the past period (16 scenarios) and the spread dynamics of the infectious disease over the next year under a combination of different interventions (264 scenarios). In the counterfactual analysis, we found that keeping high mask-wearing adherence since the outbreak of COVID-19 in Ethiopia could have significantly reduced the infection under the condition of low vaccination level or unavailability of the vaccine supply. Reducing or canceling major social events could achieve a better outcome than imposing constraints on people's routine life activities. The trend analysis found that increasing mask-wearing adherence and enforcing more stringent social distancing were two major measures that can significantly reduce possible infections. Higher mask-wearing adherence had more significant impacts than enforcing social distancing measures in our settings. As the vaccination rate increases, reduced efficacy could cause more infections than shortened immunological periods. Offsetting effects of multiple interventions (strengthening one or more interventions while loosening others) could be applied when the levels or stringencies of one or more interventions need to be adjusted for catering to particular needs (e.g., less stringent social distancing measures to reboot the economy or cushion insufficient resources in some areas).

Abstract Background The central nervous system (CNS) is vulnerable to viral infection, yet few host factors in the CNS are known to defend against invasion by neurotropic viruses. Long noncoding RNAs (lncRNAs) have been revealed to play critical roles in a wide variety of biological processes and are highly abundant in the mammalian brain, but their roles in defending against invasion of pathogens into the CNS remain unclear. Results We report here that multiple neurotropic viruses, including rabies virus, vesicular stomatitis virus, Semliki Forest virus, and herpes simplex virus 1, elicit the neuronal expression of a host-encoded lncRNA EDAL. EDAL inhibits the replication of these neurotropic viruses in neuronal cells and rabies virus infection in mouse brains. EDAL binds to the conserved histone methyltransferase enhancer of zest homolog 2 (EZH2) and specifically causes EZH2 degradation via lysosomes, reducing the cellular H3K27me3 level. The antiviral function of EDAL resides in a 56-nt antiviral substructure through which its 18-nt helix-loop intimately contacts multiple EZH2 sites surrounding T309, a known O-GlcNAcylation site. EDAL positively regulates the transcription of Pcp4l1 encoding a 10-kDa peptide, which inhibits the replication of multiple neurotropic viruses. Conclusions Our findings show that a neuronal lncRNA can exert an effective antiviral function via blocking a specific O-GlcNAcylation that determines EZH2 lysosomal degradation, rather than the traditional interferon-dependent pathway.

Polyion complex vesicles have advantageous applications but have poorly tuneable permeability and nanostructure stability. Here, the authors develop polyion complex vesicles created using a stimuli-triggered transition from polymersomes and show high stability and switchable bilayer permaselectivity.

Abstract Background A hallmark of temporal lobe epilepsy (TLE) is brain inflammation accompanied by neuronal demise. Accumulating evidence demonstrates that Rev-Erbα is involved in regulating neuroinflammation and determining the fate of neurons. Therefore, we studied the expression and cellular distribution of Rev-Erbα in the epileptogenic zone of TLE and the effect of treatment with the Rev-Erbα specific agonist SR9009 in the pilocarpine model. Methods The expression pattern of Rev-Erbα was investigated by western blotting, immunohistochemistry, and immunofluorescence labeling in patients with TLE. Next, the effects of SR9009 on neuroinflammation, neuronal apoptosis, and neuronal loss in the mouse hippocampus 7 days after status epilepticus (SE) were assessed by western blotting, immunofluorescence labeling staining, and TUNEL staining. Results The western blotting, immunohistochemistry, and immunofluorescence labeling results revealed that Rev-Erbα was downregulated in the epileptogenic zone of TLE patients and mainly localized in neurons, astrocytes, and presumably microglia. Meanwhile, the expression of Rev-Erbα was decreased in the hippocampus and temporal neocortex of mice treated with pilocarpine in the early post-SE and chronic phases. Interestingly, the expression of Rev-Erbα in the normal hippocampus showed a 24-h rhythm; however, the rhythmicity was disturbed in the early phase after SE, and this disturbance was still present in epileptic animals. Our further findings revealed that treatment with SR9009 inhibited NLRP3 inflammasome activation, inflammatory cytokine (IL-1β, IL-18, IL-6, and TNF-α) production, astrocytosis, microgliosis, and neuronal damage in the hippocampus after SE. Conclusions Taken together, these results suggested that a decrease in Rev-Erbα in the epileptogenic zone may contribute to the process of TLE and that the activation of Rev-Erbα may have anti-inflammatory and neuroprotective effects.

Abstract Background Meningiomas typically manifest on magnetic resonance imaging (MRI) as iso- to hypointense on T1-weighted imaging and iso- to hyperintense on T2-weighted imaging. After contrast administration, they usually homogeneously enhance and exhibit a visible dural tail. Meningiomas with atypical findings may be misdiagnosed. Case presentation We report a 50-year-old female patient with a pathologically diagnosed fibrous meningioma (World Health Organization grade I) that exhibited ring enhancement on MRI. Conclusions Meningiomas may rarely present with ring enhancement on MRI. The natural history and mechanisms of cystic degeneration and enhancement in the various types of meningioma require further study.

Abstract Background RNA-protein 3D complex structure prediction is still challenging. Recently, a template-based approach PRIME is proposed in our team to build RNA-protein 3D complex structure models with a higher success rate than computational docking software. However, scoring function of RNA alignment algorithm SARA in PRIME is size-dependent, which limits its ability to detect templates in some cases. Results Herein, we developed a novel RNA 3D structural alignment approach RMalign, which is based on a size-independent scoring function RMscore. The parameter in RMscore is then optimized in randomly selected RNA pairs and phase transition points (from dissimilar to similar) are determined in another randomly selected RNA pairs. In tRNA benchmarking, the precision of RMscore is higher than that of SARAscore (0.88 and 0.78, respectively) with phase transition points. In balance-FSCOR benchmarking, RMalign performed as good as ESA-RNA with a non-normalized score measuring RNA structural similarity. In balance-x-FSCOR benchmarking, RMalign achieves much better than a state-of-the-art RNA 3D structural alignment approach SARA due to a size-independent scoring function. Take the advantage of RMalign, we update our RNA-protein modeling approach PRIME to version 2.0. The PRIME2.0 significantly improves about 10% success rate than PRIME. Conclusion Based on a size-independent scoring function RMscore, a novel RNA 3D structural alignment approach RMalign is developed and integrated into PRIME2.0, which could be useful for the biological community in modeling protein-RNA interaction.

Cortical dysplasia (CD) is a common cause of drug-resistant epilepsy. Increasing studies have implicated innate immunity in CD with epilepsy. However, it is unclear whether innate immune factors induce epileptogenic CD. Here, we injected recombinant human high mobility group box 1 (rHMGB1) into embryonic rat ventricles to determine whether rHMGB1 can induce epileptogenic CD with pathophysiological characteristics similar to those of human CD. Compared with controls and 0.1 μg rHMGB1-treated rats, the cortical organization was severely disrupted in the 0.2 μg rHMGB1-treated rats, and microgyria and heterotopia also emerged; additionally, disoriented and deformed neurons were observed in the cortical lesions and heterotopias. Subcortical heterotopia appeared in the white matter and the gray–white junction of the 0.2 μg rHMGB1-treated rats. Moreover, there was decreased number of neurons in layer V–VI and an increased number of astrocytes in layer I and V of the cortical lesions. And the HMGB1 antagonist dexmedetomidine alleviated the changes induced by rHMGB1. Further, we found that TLR4 and NF-κB were increased after rHMGB1 administration. In addition, the excitatory receptors, N-methyl-D-aspartate receptor 1 (NR1), 2A (NR2A), and 2B (NR2B) immunoreactivity were increased, and immunoreactivity of excitatory amino acid transporter 1 (EAAT1) and 2 (EAAT2) were reduced in 0.2 μg rHMGB1-treated rats compared with controls. While there were no differences in the glutamic acid decarboxylase 65/67 (GAD65/67) immunoreactivity between the two groups. These results indicate that the excitation of cortical lesions was significantly increased. Furthermore, electroencephalogram (EEG) showed a shorter latency of seizure onset and a higher incidence of status epilepticus in the 0.2 μg rHMGB1-treated rats; the frequency and amplitude of EEG were higher in the treated rats than controls. Intriguingly, spontaneous electrographic seizure discharges were detected in the 0.2 μg rHMGB1-treated rats after 5 months of age, and spike-wave discharges of approximately 8 Hz were the most significantly increased synchronous propagated waves throughout the general brain cortex. Taken together, these findings indicate that rHMGB1 exposure during pregnancy could contribute to the development of epileptogenic CD, which mimicked some pathophysiological characteristics of human CD.

Controlled polypeptide synthesis via α-amino acid N-carboxylic anhydride (NCA) polymerization using conventional primary amine initiators encounters two major obstacles: (i) normal amine mechanism (NAM) and activated monomer mechanism (AMM) coexist due to amine basicity and nucleophilicity and (ii) NCA is notoriously sensitive towards moisture and heat and unstable upon storage. We serendipitously discover that N-phenoxycarbonyl-functionalized α-amino acid (NPCA), a latent NCA precursor, could be polymerized solely based on NAM with high initiating efficiency by using primary amine hydrochloride as an initiator. The polymerization affords well-defined polypeptides with narrow polydispersity and high-fidelity terminal functionalities, as revealed by the clean set of MALDI-TOF MS patterns. We further demonstrate successful syntheses of random and block copolypeptides, even under open-vessel conditions. Overall, the integration of moisture-insensitive and air-tolerant NPCA precursors with stable primary amine hydrochloride initiators represents a general strategy for controlled synthesis of high-fidelity polypeptides with sophisticated functions.

Introduction: According to WHO’s statistical evidence, accidental falls are the second leading causes of death worldwide. This systematic literature review and meta-analysis aims to provide a holistic view of risk factors and unfold the missing or less addressed but crucial factors that lead to accidental falls of the older adults. It also intends to profile the risk factors at different levels, which helps exhibit the level of consistency relationship between various risk factors and falls. Study design: Systematic literature review. Methods: A systematic review on the risk factors leading to accidental falls of older adults by retrieving English journal papers published starting from 1980 was conducted on April 2018. A method of literature synthesis and causal mapping was adopted to aggregate those fall-leading factors into macro variables and a coherent causal tracing network was thereby built, which can reflect not only the causal relationship of various macro variables but also the “consistency of agreement” between macro variables and falls of the older adults. Results: A hypothesized causal relationship diagram of 19 aggregated macro variables and their 31 causal relationship suggested by the observational evidences is demonstrated. The consistency relationship between macro variables and elderly accidental fall are summarized and demonstrated. Our analysis reveals that “Time”, “Season” and “Weather” are three less-studied factors in the literature. In our comprehensive analysis, our study also indicates neglected countries and senior populations such as Africa and Oceania, which requires more attention from the research community and global funding agencies. It is found that major quantitative tools focus on the traditional statistical analysis. Conclusion: With the accelerated aging and increase of longevity worldwide, national and regional policies, and public health programs to provide adequate care services for the older people are crucially needed in both industrialized and developing countries. Evidences identified in the research are valuable inputs for policy design and decision makers of different stakeholders and prevention design of risk factors for falls in the older adults. The categorization of research methods in different literature also suggests that more quantitative approaches including simulation, optimization in operational research, and maybe machine learning are needed to enrich the research paradigm. We suggest researchers to consider using our presented causal map and the way of building it and explore the possibility of extending this framework to uncover more research topics in health-related research.

This study systematically examines the diffusion of the discrete event simulation (DES) approach in health services and health care management by examining relevant factors such as research areas, channels with the objective of promoting the application of DES in the health field. We examined 483 journal papers referencing this approach that were published in 230 journals during 1981 to 2014. The application of DES has extended from health service operational research evaluation to the assessment of interventions in diverse health arenas. The increase in the number of adopters (paper authors) of DES and the increase in number of related channels (journals publishing DES-related articles) are highly correlated, which suggests an increase of DES-related publications in health research. The same conclusion is reached, that is, an increased diffusion of DES in health research, when we focus on the temporal trends of the channels and adopters. The applications of DES in health research cover 22 major areas based on our categorization. The expansion in the health areas also suggests to a certain extent the rapid diffusion of DES in health research.

Small molecule theranostic agents suffer from fast blood clearance whereas nanoparticle ones are incapable of molecular functions and often nondegradable. We propose to bridge the gap between nanoparticles and small molecule agents based on self-immolative polymers which undergo triggered cascade depolymerization at the chain level. Amphiphilic block copolymers containing side chain-functionalized depolymerizable block self-assemble into micellar nanoparticles. Upon triggering with reactive oxygen species (ROS) and acidic pH, nanoparticles self-immolate into electron-deficient small molecule azaquinone methide (AQM) derivatives, which are capable of efficient addition reactions with biologically relevant nucleophiles. By taking advantage of this feature, we achieve stimuli-activatable 19F NMR/MR imaging and 19F/1H dual-modality MR imaging. Upon cellular uptake, AQMs generated during depolymerization react with intracellular thiol-relevant substrates including GSH and thiol-containing proteins. Starting from self-immolative nanoparticles functionalized with DOTA-Gd, we demonstrate unprecedented long-term in vivo 1H MR imaging of tumor-bearing mice via the in situ covalent trapping strategy.

Existing extended one-versus-rest multi-label support vector machine (OVR-ESVM) adopting non-linear kernel is seriously restricted by excessive training time when it is applied to large-scale data set. In order to overcome this problem, we improve the OVR-ESVM by introducing the principle of approximate extreme points and new approximate ranking loss to construct a novel extended OVR-ESVM using approximate extreme points (AEML-ESVM). By optimizing only on the representative set which can be acquired via adopting the approximate extreme points method, the AEML-ESVM classification algorithm can substantially shorten the training time and its classification performance is comparable to that of the OVR-ESVM classification algorithm. And it uses the new approximate ranking loss as empirical loss term to exploit label correlation of individual instance directly. Experimental study on three benchmark large-scale data sets illustrates that AEML-ESVM classification algorithm can reduce training time greatly and achieve comparable classification performance with OVR-ESVM classification algorithm. And it is also superior to the existing fast multi-label SVM classification algorithms in terms of classification performance and training time.

In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model.In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions.In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM.This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data meaningful and quantifiable in a simulation environment. This research can help practitioners and decision makers to gain better understanding on the dynamics and complexities of precision intervention in healthcare. It can aid the improvement of the optimal allocation of resources for targeted group (s) and the achievement of maximum utility. As this technology becomes more mature, one can design policy flight simulators by which policy/intervention designers can test a variety of assumptions when they evaluate different alternatives interventions.

Cortical dysplasia accounts for at least 14% of epilepsy cases, and is mostly seen in children. However, the understanding of molecular mechanisms and pathogenesis underlying cortical dysplasia is limited. The aim of this cross-sectional study is to identify potential key molecules in the mechanisms of cortical dysplasia by screening the proteins expressed in brain tissues of childhood cortical dysplasia patients with epilepsy using isobaric tags for relative and absolute quantitation-based tandem mass spectrometry compared to controls, and several differentially expressed proteins that are not reported to be associated with cortical dysplasia previously were selected for validation using real-time polymerase chain reaction, immunoblotting and immunohistochemistry. 153 out of 3340 proteins were identified differentially expressed between childhood cortical dysplasia patients and controls. And FSCN1, CRMP1, NDRG1, DPYSL5, MAP4, and FABP3 were selected for validation and identified to be increased in childhood cortical dysplasia patients, while PRDX6 and PSAP were identified decreased. This is the first report on differentially expressed proteins in childhood cortical dysplasia. We identified differential expression of FSCN1, CRMP1, NDRG1, DPYSL5, MAP4, FABP3, PRDX6 and PSAP in childhood cortical dysplasia patients, these proteins are involved in various processes and have various function. These results may provide new directions or targets for the research of childhood cortical dysplasia, and may be helpful in revealing molecular mechanisms and pathogenesis and/or pathophysiology of childhood cortical dysplasia if further investigated.

Protein-RNA complexes formed by specific recognition between RNA and RNA-binding proteins play an important role in biological processes. More than a thousand of such proteins in human are curated and many novel RNA-binding proteins are to be discovered. Due to limitations of experimental approaches, computational techniques are needed for characterization of protein-RNA interactions. Although much progress has been made, adequate methodologies reliably providing atomic resolution structural details are still lacking. Although protein-RNA free docking approaches proved to be useful, in general, the template-based approaches provide higher quality of predictions. Templates are key to building a high quality model. Sequence/structure relationships were studied based on a representative set of binary protein-RNA complexes from PDB. Several approaches were tested for pairwise target/template alignment. The analysis revealed a transition point between random and correct binding modes. The results showed that structural alignment is better than sequence alignment in identifying good templates, suitable for generating protein-RNA complexes close to the native structure, and outperforms free docking, successfully predicting complexes where the free docking fails, including cases of significant conformational change upon binding. A template-based protein-RNA interaction modeling protocol PRIME was developed and benchmarked on a representative set of complexes.

Most inhibitors of Cyclin-dependent kinase 2 (CDK2) target its ATP-binding pocket. It is difficult, however, to use this pocket to design very specific inhibitors because this catalytic pocket is highly conserved in the protein family of CDKs. Here we report some short peptides targeting a noncatalytic pocket near the interface of the CDK2/Cyclin complex. Docking and molecular dynamics simulations were used to select the peptides, and detailed dynamical network analysis revealed that these peptides weaken the complex formation via allosteric interactions. Our experiments showed that upon binding to the noncatalytic pocket, these peptides break the CDK2/Cyclin complex partially and diminish its kinase activity in vitro. The binding affinity of these peptides measured by Surface Plasmon Resonance can reach as low as 0.5 µM.