Overcoming small-bandgap charge recombination in visible and NIR-light-driven hydrogen evolution by engineering the polymer photocatalyst structure.

Designing an organic polymer photocatalyst for efficient hydrogen evolution with visible and near-infrared (NIR) light activity is still a major challenge. Unlike the common behavior of gradually increasing the charge recombination while shrinking the bandgap, we present here a series of polymer nanoparticles (Pdots) based on ITIC and BTIC units with different π-linkers between the acceptor-donor-acceptor (A-D-A) repeated moieties of the polymer. These polymers act as an efficient single polymer photocatalyst for H2 evolution under both visible and NIR light, without combining or hybridizing with other materials. Importantly, the difluorothiophene (ThF) π-linker facilitates the charge transfer between acceptors of different repeated moieties (A-D-A-(π-Linker)-A-D-A), leading to the enhancement of charge separation between D and A. As a result, the PITIC-ThF Pdots exhibit superior hydrogen evolution rates of 279 µmol/h and 20.5 µmol/h with visible (>420 nm) and NIR (>780 nm) light irradiation, respectively. Furthermore, PITIC-ThF Pdots exhibit a promising apparent quantum yield (AQY) at 700 nm (4.76%).

Lack of direct association between viral hepatitis and sleep disturbances.

Background: Individuals with chronic viral hepatitis are at increased risk of experiencing poor sleep quality and sleep disturbances. However, it remains unclear whether the sleep disorders associated with viral hepatitis are secondary to the comorbidities related to viral hepatitis or the direct effect of hepatitis viruses on sleep. This study investigated the direct impact of viral hepatitis B and C on sleep quality. Methods: Individuals with viral hepatitis B or C and their healthy counterparts were recruited for the present study, and they were evaluated with the Parkinson's Disease Sleep Scale-2, the Epworth Sleepiness Scale, and the Pittsburgh Sleep Quality Index in the absence of common comorbidities associated with viral hepatitis. Results: Neither hepatitis B nor hepatitis C was found to cause significant differences in insomnia symptoms or excessive daytime sleepiness. However, individuals with hepatitis C, but not hepatitis B, tended to be less likely to experience restlessness of the legs or arms at night. Conclusions: This study suggests that hepatitis viruses B and C may not cause a significant impact on sleep quality and related disorders directly. Sleep disturbances in individuals with chronic viral hepatitis may instead be attributable to hepatic decompensation or the comorbid factors associated with viral hepatitis.

Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations.

The coronavirus disease 2019 (COVID-19) pandemic has been severely impacting global society since December 2019. The related findings such as vaccine and drug development have been reported in biomedical literature-at a rate of about 10 000 articles on COVID-19 per month. Such rapid growth significantly challenges manual curation and interpretation. For instance, LitCovid is a literature database of COVID-19-related articles in PubMed, which has accumulated more than 200 000 articles with millions of accesses each month by users worldwide. One primary curation task is to assign up to eight topics (e.g. Diagnosis and Treatment) to the articles in LitCovid. The annotated topics have been widely used for navigating the COVID literature, rapidly locating articles of interest and other downstream studies. However, annotating the topics has been the bottleneck of manual curation. Despite the continuing advances in biomedical text-mining methods, few have been dedicated to topic annotations in COVID-19 literature. To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature. The BioCreative LitCovid dataset-consisting of over 30 000 articles with manually reviewed topics-was created for training and testing. It is one of the largest multi-label classification datasets in biomedical scientific literature. Nineteen teams worldwide participated and made 80 submissions in total. Most teams used hybrid systems based on transformers. The highest performing submissions achieved 0.8875, 0.9181 and 0.9394 for macro-F1-score, micro-F1-score and instance-based F1-score, respectively. Notably, these scores are substantially higher (e.g. 12%, higher for macro F1-score) than the corresponding scores of the state-of-art multi-label classification method. The level of participation and results demonstrate a successful track and help close the gap between dataset curation and method development. The dataset is publicly available via https://ftp.ncbi.nlm.nih.gov/pub/lu/LitCovid/biocreative/ for benchmarking and further development. Database URL https://ftp.ncbi.nlm.nih.gov/pub/lu/LitCovid/biocreative/.

A BERT-based ensemble learning approach for the BioCreative VII challenges: full-text chemical identification and multi-label classification in PubMed articles.

In this research, we explored various state-of-the-art biomedical-specific pre-trained Bidirectional Encoder Representations from Transformers (BERT) models for the National Library of Medicine - Chemistry (NLM CHEM) and LitCovid tracks in the BioCreative VII Challenge, and propose a BERT-based ensemble learning approach to integrate the advantages of various models to improve the system's performance. The experimental results of the NLM-CHEM track demonstrate that our method can achieve remarkable performance, with F1-scores of 85% and 91.8% in strict and approximate evaluations, respectively. Moreover, the proposed Medical Subject Headings identifier (MeSH ID) normalization algorithm is effective in entity normalization, which achieved a F1-score of about 80% in both strict and approximate evaluations. For the LitCovid track, the proposed method is also effective in detecting topics in the Coronavirus disease 2019 (COVID-19) literature, which outperformed the compared methods and achieve state-of-the-art performance in the LitCovid corpus. Database URL: https://www.ncbi.nlm.nih.gov/research/coronavirus/.

Hypermethylation of the TGF-ß target, ABCA1 is associated with poor prognosis in ovarian cancer patients.

BACKGROUND: The dysregulation of transforming growth factor-ß (TGF-ß) signaling plays a crucial role in ovarian carcinogenesis and in maintaining cancer stem cell properties. Classified as a member of the ATP-binding cassette (ABC) family, ABCA1 was previously identified by methylated DNA immunoprecipitation microarray (mDIP-Chip) to be methylated in ovarian cancer cell lines, A2780 and CP70. By microarray, it was also found to be upregulated in immortalized ovarian surface epithelial (IOSE) cells following TGF-ß treatment. Thus, we hypothesized that ABCA1 may be involved in ovarian cancer and its initiation. RESULTS: We first compared the expression level of ABCA1 in IOSE cells and a panel of ovarian cancer cell lines and found that ABCA1 was expressed in HeyC2, SKOV3, MCP3, and MCP2 ovarian cancer cell lines but downregulated in A2780 and CP70 ovarian cancer cell lines. The reduced expression of ABCA1 in A2780 and CP70 cells was associated with promoter hypermethylation, as demonstrated by bisulfite pyro-sequencing. We also found that knockdown of ABCA1 increased the cholesterol level and promoted cell growth in vitro and in vivo. Further analysis of ABCA1 methylation in 76 ovarian cancer patient samples demonstrated that patients with higher ABCA1 methylation are associated with high stage (P = 0.0131) and grade (P = 0.0137). Kaplan-Meier analysis also found that patients with higher levels of methylation of ABCA1 have shorter overall survival (P = 0.019). Furthermore, tissue microarray using 55 ovarian cancer patient samples revealed that patients with a lower level of ABCA1 expression are associated with shorter progress-free survival (P = 0.038). CONCLUSIONS: ABCA1 may be a tumor suppressor and is hypermethylated in a subset of ovarian cancer patients. Hypermethylation of ABCA1 is associated with poor prognosis in these patients.

Effect of air-drying and oven-drying treatment on Cr(VI) content and Cr bond forms in soil.

Air-drying and oven-drying are pretreatment processes often used before testing and analyzing various soil characteristics in the laboratory. This study selected three kinds of soil, including red soil, entisol, and alluvial soil, and examined the variation of the Cr(VI) content and Cr bond forms in these soils during air-drying and oven-drying. The results show that when the soil is air-dried in natural environment, the Cr(VI) content decreases with air-drying time. On day 10 of air-drying, the Cr(VI) content in these soils is 22.8∼47.9 % of the initial value. When the soil is oven-dried, the Cr(VI) concentration decays faster; on day 8, the Cr(VI) is no longer detected in these soil samples. When the Cr(VI)-contaminated soil is treated by air-drying and oven-drying, the Cr bond form converts into a more stable form. After oven-drying, the Cr mainly exists in Fe-Mn oxide form, organic bond form, and residual form. The air-drying and oven-drying pretreatment processes of soil reduce the Cr(VI) content and stabilize the Cr bond form. If the laboratory analytic results are applied to risk analysis or remediation strategy planning for chromium-contaminated soil, the toxicity, bioavailability, and mobility of Cr in soil may be underrated.

Mixed micelle systems formed from critical micelle concentration and temperature-sensitive diblock copolymers for doxorubicin delivery.

Mixed micelles formed by critical micelle concentration (Cmc) character's diblock copolymer, and temperature-sensitive character's diblock copolymer were studied for their capabilities in improving stability with and without drug. Experimental results showed that this type of mixed micellar systems possessed complementary effects in adjusting external temperature shift (storage vs. body temperature) and concentration change (dilution after intravenous injection). Therefore, they provided excellent stability as drug carriers. Further results obtained from physicochemical property and drug release kinetics studies demonstrated such systems could also be applied to physiological conditions, in compliance with varied pH environments. We concluded that the newly developed mixed micelles can serve as a potential injectable drug delivery system for anticancer drugs, such as doxorubicin and many others.