Robust Multifunctional Ultrathin 2 Nanometer Organic Nanofibers.

Ultrathin organic nanofibers (UTONFs) represent an emerging class of nanomaterials as they carry a set of favorable attributes, including ultrahigh specific surface area, lightweight, and mechanical flexibility, over inorganic counterparts, for use in biomedicine and nanotechnology. However, precise synthesis of uniform UTONFs (diameter ≤ 2 nm) with tailored functionalities remained challenging. Herein, we report robust multifunctional UTONFs using hydrophobic interaction-driven self-assembly of amphiphilic alternating peptoids containing hydrophobic photoresponsive azobenzene and hydrophilic hydroxyl moieties periodically arranged along the peptoid backbone. Notably, the as-crafted UTONFs are approximately 2 nm in diameter and tens of micrometers in length (an aspect ratio, AR, of ∼10000), exemplifying the UTONFs with the smallest diameter yielded via self-assembly. Intriguingly, UTONFs were disassembled into short-segmented nanofibers and controllably reassembled into UTONFs, resembling "step-growth polymerization". Photoisomerization of azobenzene moieties leads to reversible transformation between UTONFs and spherical micelles. Such meticulously engineered UTONFs demonstrate potential for catalysis, bioimaging, and antibacterial therapeutics. Our study highlights the significance of the rational design of amphiphiles containing alternating hydrophobic and hydrophilic moieties in constructing otherwise unattainable extremely thin UTONFs with ultrahigh AR and stimuli-responsive functionalities for energy and bionanotechnology.

Pipelined biomedical event extraction rivaling joint learning.

Biomedical event extraction is an information extraction task to obtain events from biomedical text, whose targets include the type, the trigger, and the respective arguments involved in an event. Traditional biomedical event extraction usually adopts a pipelined approach, which contains trigger identification, argument role recognition, and finally event construction either using specific rules or by machine learning. In this paper, we propose an n-ary relation extraction method based on the BERT pre-training model to construct Binding events, in order to capture the semantic information about an event's context and its participants. The experimental results show that our method achieves promising results on the GE11 and GE13 corpora of the BioNLP shared task with F1 scores of 63.14% and 59.40%, respectively. It demonstrates that by significantly improving the performance of Binding events, the overall performance of the pipelined event extraction approach or even exceeds those of current joint learning methods.

Designable Photo-Responsive Micron-Scale Ultrathin Peptoid Nanobelts for Enhanced Performance on Hydrogen Evolution Reaction.

The development of high-reactive single-atom catalysts (SACs) based on long-range-ordered ultrathin organic nanomaterials (UTONMs) (i.e., below 3 nm) provides a significant tactic for the advancement in hydrogen evolution reactions (HER) but remains challenging. Herein, photo-responsive ultrathin peptoid nanobelts (UTPNBs) with a thickness of ≈2.2 nm and micron-scaled length are generated using the self-assembly of azobenzene-containing amphiphilic ternary alternating peptoids. The pendants hydrophobic conjugate stacking mechanism reveals the formation of 1D ultralong UTPNBs, whose thickness is dictated by the length of side groups that are linked to peptoid backbones. The photo-responsive feature is demonstrated by a reversible morphological transformation from UTPNBs to nanospheres (21.5 nm) upon alternative irradiation with UV and visible lights. Furthermore, the electrocatalyst performance of these aggregates co-decorated with nitrogen-rich ligand of terpyridine (TE) and uniformly-distributed atomic platinum (Pt) is evaluated toward HER, with a photo-controllable electrocatalyst activity that highly depended on both the presence of Pt element and structural characteristic of substrates. The Pt-based SACs using TE-modified UTPNBs as support exhibit a favorable electrocatalytic capacity with an overpotential of ≈28 mV at a current density of 10 mA cm-2. This work presents a promising strategy to fabricate stimuli-responsive UTONMs-based catalysts with controllable HER catalytic performance.

Joint learning-based causal relation extraction from biomedical literature.

Causal relation extraction of biomedical entities is one of the most complex tasks in biomedical text mining, which involves two kinds of information: entity relations and entity functions. One feasible approach is to take relation extraction and function detection as two independent sub-tasks. However, this separate learning method ignores the intrinsic correlation between them and leads to unsatisfactory performance. In this paper, we propose a joint learning model, which combines entity relation extraction and entity function detection to exploit their commonality and capture their inter-relationship, so as to improve the performance of biomedical causal relation extraction. Experimental results on the BioCreative-V Track 4 corpus show that our joint learning model outperforms the separate models in BEL statement extraction, achieving the F1 scores of 57.0% and 37.3% on the test set in Stage 2 and Stage 1 evaluations, respectively. This demonstrates that our joint learning system reaches the state-of-the-art performance in Stage 2 compared with other systems.

A prognostic analysis of antisynthetase syndrome-related interstitial lung disease.

OBJECTIVE: To analyze prognostic factors of antisynthetase syndrome (ASS)-related interstitial lung disease (ILD). METHODS: We retrospectively collected the data of 77 inpatients with ASS-ILD at our hospital from January 1, 2018, to January 1, 2021. The improvement/stability group and deterioration/death group were defined according to their follow-up outcome. Clinical data of the 2 groups were compared. Univariate analysis was adopted to screen the possible prognostic factors and then logistic regression was used for multivariate analysis. RESULT: After 6 to 42 months of follow-up, 52 patients (67.5%) were classified into the improvement/stability group, and 25 patients (32.5%) were classified into the deterioration/death group. According to the multivariate stepwise logistic regression analysis, respiratory failure (odds ratio [OR] = 6.71, 95% CI: 1.64-27.38, P = .008) and elevated muscle enzymes (OR = 4.31, 95% CI: 1.03-18.05, P = .045) were found to be independent risk factors, while mechanic's hands (OR = 0.06, 95% CI: 0.01-0.37, P = .003) and anti-Jo-1 antibody (OR = 0.24, 95% CI: 0.06-0.93, P = .039) were protective factors. CONCLUSION: The prognostic assessment of ASS-ILD patients should be emphasized. Patients with a poor prognosis should be identified early based on their risk factors to guide clinical management decisions.

Cyclic γ-Peptides With Transmembrane Water Channel Properties.

Self-assembling peptides can be used to design new materials for medical and biological applications. Here we synthesized and characterized two novel cyclic γ-peptides (γ-CPs) with hydrophobic inner surfaces. The NMR and FT-IR studies confirmed that the CPs could self-assemble into parallel stacking structures via intermolecular H-bonds and π-π interactions. The morphologies of the self-assembly CPs showed bundles of nanotubes via transmission electron microscopy (TEM); these nanotubes form water channels to transport water across the lipid membrane. The properties of blocking the transport of protons like natural water channels showed that the hydrophobic inner surfaces are important in artificial transmembrane water channel designs. These studies also showed that water transport was a function of pore size and length of the assemblies.

Accelerated reduction of serum thyroxine and hippocampal histone acetylation links to exacerbation of spatial memory impairment in aged CD-1 mice pubertally exposed to bisphenol-a.

Age-related cognitive decline has been associated with changes in endogenous hormones and epigenetic modification of chromatin, including histone acetylation. Developmental exposure to endocrine disrupting chemicals, such as bisphenol-A (BPA) that produces endocrine disruption and epigenetic changes, may be a risk factor for accelerating cognitive deficits during aging. Thus, we exposed CD-1 mice to BPA (0, 1, and 100 mg/l BPA in the drinking water) orally during puberty (from postnatal days 28 to 56) and investigated whether pubertal BPA exposure exacerbates the age-related impairment of spatial cognition in old age (18 months old) and whether serum sex and thyroid hormones or hippocampal histone acetylation (H3K9ac and H4K8ac) are associated with cognitive effects. A young control group (6 months old) was added to analyze the age effect. Results showed untreated aged mice had marked decline of spatial learning and memory in the novel location recognition and radial six-arm water maze tasks, with decreased levels of these hormones and hippocampal H3K9ac and H4K8ac compared to young controls. The BPA treatment exacerbated age-related spatial cognitive impairment and accelerated the reduction of free thyroxine (FT4), H3K9ac, and H4K8ac, and the 100 mg/l BPA group showed more significant impact. Additionally, correlation analyses revealed that lower levels of FT4, H3K9ac, and H4K8ac were accompanied by decreased spatial memory abilities. We concluded that accelerated reduction of serum FT4 and hippocampal H3K9ac and H4K8ac might be linked to exacerbation of age-related spatial cognitive impairment due to pubertal BPA exposure.

PIN1-842G/C and -667T/C polymorphisms are not associated with the susceptibility of Alzheimer's disease: pooled analysis of epidemiologic studies.

Associations between PIN1 gene polymorphisms and Alzheimer's disease (AD) risk remain controversial, possibly because single studies often lack sufficient statistical power. In this study, we performed a meta-analysis to evaluate the association of two commonly studied PIN1 polymorphisms, -842G/C and -667T/C, with the risk of AD. Relevant studies were identified from PubMed, EMBASE, and China National Knowledge Infrastructure up to October 2012. Data were available from a total of 7 case-control studies with 2504 cases and 2322 controls. Crude odds ratios (OR) and 95% confidence intervals (CI) were used to investigate the strength of the association. The results showed no significant association between PIN1-842G/C polymorphism and AD risk in all comparison models (GG vs. GC: OR=0.84, 95%CI=0.61-1.18; GG vs. CC: OR=0.70, 95%CI=0.35-1.41; GC vs. CC: OR=0.81, 95%CI=0.39-1.69; G vs. C: OR=0.89, 95%CI=0.69-1.17; GG vs. GC+CC: OR=0.81, 95%CI=0.56-1.17; GG+GC vs. CC: OR=0.72, 95%CI=0.36-1.45). For the PIN1-667T/C polymorphism, lack of an association was also found. Subgroup analyses by the ethnicity and patients with late-onset AD did not change the results. Conclusively, the present meta-analysis revealed that PIN1 gene polymorphisms (-842G/C and -667T/C) were unlikely to contribute to AD susceptibility.