Notes

A versatile solution to distinct complex lipid mixtures using 1-butanol because eluent inside a reverse-phase UHPLC-ESI-MS method.
A new alkylation reaction of monosubstituted tetrazoles via the diazotization of aliphatic amines is reported. This method enables preferential formation of 2,5-disubstituted tetrazoles. A one-pot 1,3-dipolar cycloaddition/diazotization sequence starting from widely available nitriles is also described. Azide residues are quenched in the second step with the nitrite reagent, thus limiting the intrinsic risk associated with trimethylsilyl azide. The reaction conditions were compatible with several functional groups, including thiocyanates, which afford preferentially disubstituted 2-alkyl-5-(substituted-thio)tetrazoles.A new domino mode of assembly was discovered from the one-pot three-component reactions of pyrrole derivatives, active methylene compounds (malononitrile, methyl cyanoacetate, or ethyl cyanoacetate), and sodium cyanide in the presence of piperidinium acetate in EtOH at room temperature, leading to a novel tricyclic skeleton in excellent yield under mild and eco-friendly conditions. This well-choreographed domino process enabled formation of multiple bonds (three C-C and one C-O) for consecutive construction of two rings (pyrrolidine and dihydrofuran) in a diastereoselective manner.The effect of insertion of three geminally dimethyl substituted γ amino acid residues [γ2,2 (4-amino-2,2-dimethylbutanoic acid), γ3,3 (4-amino-3,3-dimethylbutanoic acid), and γ4,4 (4-amino-4,4-dimethylbutanoic acid)] at the (i + 2) position of a two-residue αγ C12 turn segment in a model octapeptide sequence Leu-Phe-Val-Aib-Xxx-Leu-Phe-Val (where Xxx = γ amino acid residues) has been investigated in this study. Solution conformational studies (NMR, CD, and IR) and ab initio calculations indicated that γ3,3 and γ4,4 residues were well accommodated in the β-hairpin nucleating αγ C12 turns, which gave rise to well-registered hairpins, in contrast to γ2,2, which was unable to form a tight C12 β-hairpin nucleating turn and promote a well-registered β-hairpin. Geminal disubstitution at the Cα carbon in γ2,2 led to unfavorable steric contacts, disabling its accommodation in the αγ C12 hairpin nucleating turn unlike the γ3,3 and γ4,4 residues. Geminal substitutions at different carbons along the backbone constrained backbone torsion angles for the three γ amino acid residues differently, generating diverse conformational preferences in them. Folded hairpins were energetically more stable (∼8 to 9 kcal/mol) than the unfolded peptides. Conformational preference of the peptides was independent of the N-terminal protecting group. Such fundamental understanding will instrumentalize the future directed design of foldamers.Freezing of gait (FOG) is a common and complex manifestation of Parkinson's disease (PD) and is associated with impairment of attention. The purpose of this study was to evaluate the functional network connectivity (FNc) changes between the dorsal attention network (DAN) and the other seven intrinsic networks relevant to attention, visual-spatial, executive and motor functions in PD with or without FOG. Forty-three idiopathic PD patients (21 with FOG [FOG+] versus 22 without FOG [FOG-]) and 18 healthy controls (HC) were recruited in this study. The data-driven independent component analysis (ICA) method was used to extract and analyze the above-mentioned resting-state networks (RSNs). Compared with FOG-, FOG+ displayed decreased positive connectivity between the DAN and medial visual network (mVN) and sensory-motor network (SMN) and increased negative connectivity between the DAN and default mode network (DMN). The within-network connectivity in the SMN and visual networks were decreased, whereas the connectivity within DMN was increased significantly in FOG+. Correlation analysis showed that the clock drawing test (CDT) scores were positively correlated with the functional connectivity of mVN (r = 0.573, p = 0.008) and lateral visual network (lVN) (r = 0.510, p = 0.022), the Timed Up and Go Test (TUG) duration were negatively correlated with the connectivity of SMN (r = -0.629, p = 0.003), and the Frontal Assessment Battery (FAB) scores were negatively correlated with the connectivity of DMN in FOG+. Functional connectivity was changed in multiple intra-networks in patients with FOG. Inordinate inter-network connectivity between the DAN and other intrinsic networks may partly contribute to the mechanism of freezing.
Oral squamous cell carcinoma (OSCC), a main type of squamous cell cancer, is associated with considerable morbidity and mortality. Recent reports suggested methyltransferase-like 3 (METTL3)-mediated N6-methyladenosine (m6A) modification to be an essential regulator in the fate determination of stem cells. However, the functional significance of METTL3 in OSCC remains largely unknown.

METTL3 expression was examined in OSCC patient samples, followed by correlation analysis against clinical tumor features. Functional assays, such as assessment of surface marker expression, colony forming, BrdU incorporation, tumor xenograft assay, and m6A dot blot, were conducted to study the impact of METTL3knockdown (KD) in OSCC cells.

High METTL3 expression was positively correlated with more severe clinical features of OSCC tumors. METTL3KD caused impairment of stem-like capacities in OSCC cells, such as tumorigenicity in vivo and colony-forming ability in vitro. Furthermore, METTL3-KD and cycloleucine, a methylation inhibitor, decreased m6A levels and down-regulated p38 expression in OSCC cells. On the contrary, the impaired cell proliferation capacity of OSCC cells after METTL3-KD was restored by exogenous expression of p38.

Our findings identified m6A methyltransferase METTL3 as a key element in the regulation of tumorigenesis in OSCC.
Our findings identified m6A methyltransferase METTL3 as a key element in the regulation of tumorigenesis in OSCC.
Diabetes is common in tobacco-consuming individuals, hypoxia-encountering people, and post-menopausal women. The mechanism behind diabetes-associated vascular-dysfunction remains speculative. Dermcidin (DCD), an 11 kDa-protein plays a detrimental role in acute myocardial-infarction through the impairment of endothelial-nitric-oxide-synthase (eNOS).

DCD mediated genesis of diabetes has been manifested in human and rodent-models under various stress-conditions. Here, plasma levels of DCD have been significantly correlated with the diabetic-conditions in postmenopausal-women, in tobacco-consuming individuals and in hypoxia indicating a common pathway. In mice, DCD infusion augmented the blood glucose with a concomitant reduction of nitric oxide levels. DCD triggers the release of glucose from the liver/muscle/kidney and antagonizes the effects of insulin. This has been demonstrated by the glucose tolerance and insulin tolerance test. Herein our studies showed that DCD inhibited GLUT-4 and impaired NO productr (Ectodomain1/2). IWP-4 supplier Synergism of all these effects resulted in the breakdown of glucose homeostasis-machinery i.e. insulin-resistance, and further dermcidin induced NO/cGMP down-regulation in individuals under a variety of stressors.
To introduce and analyse current trends in Public Health and Epidemiology Informatics.

PubMed search of 2020 literature on public health and epidemiology informatics was conducted and all retrieved references were reviewed by the two section editors. Then, 15 candidate best papers were selected among the 920 references. These papers were then peer-reviewed by the two section editors, two chief editors, and external reviewers, including at least two senior faculty, to allow the Editorial Committee of the 2021 International Medical Informatics Association (IMIA) Yearbook to make an informed decision regarding the selection of the best papers.

Among the 920 references retrieved from PubMed, four were suggested as best papers and the first three were finally selected. The fourth paper was excluded because of reproducibility issues. The first best paper is a very public health focused paper with health informatics and biostatistics methods applied to stratify patients within a cohort in order to identify thots to mitigate suicide risk. Further, they also demonstrate that well informing and empowering patients could help them to be involved more in their care process.
To analyze the content of publications within the medical NLP domain in 2020.

Automatic and manual preselection of publications to be reviewed, and selection of the best NLP papers of the year. Analysis of the important issues.

Three best papers have been selected in 2020. We also propose an analysis of the content of the NLP publications in 2020, all topics included.

The two main issues addressed in 2020 are related to the investigation of COVID-related questions and to the further adaptation and use of transformer models. Besides, the trends from the past years continue, such as diversification of languages processed and use of information from social networks.
The two main issues addressed in 2020 are related to the investigation of COVID-related questions and to the further adaptation and use of transformer models. Besides, the trends from the past years continue, such as diversification of languages processed and use of information from social networks.
We survey recent work in biomedical NLP on building more adaptable or generalizable models, with a focus on work dealing with electronic health record (EHR) texts, to better understand recent trends in this area and identify opportunities for future research.

We searched PubMed, the Institute of Electrical and Electronics Engineers (IEEE), the Association for Computational Linguistics (ACL) anthology, the Association for the Advancement of Artificial Intelligence (AAAI) proceedings, and Google Scholar for the years 2018-2020. We reviewed abstracts to identify the most relevant and impactful work, and manually extracted data points from each of these papers to characterize the types of methods and tasks that were studied, in which clinical domains, and current state-of-the-art results.

The ubiquity of pre-trained transformers in clinical NLP research has contributed to an increase in domain adaptation and generalization-focused work that uses these models as the key component. Most recently, work has sta domain pre-training does not always transfer adequately to the clinical domain due to its highly specialized language. There is also much work to be done in showing that the gains obtained by pre-trained transformers are beneficial in real world use cases. The amount of work in domain adaptation and transfer learning is limited by dataset availability and creating datasets for new domains is challenging. The growing body of research in languages other than English is encouraging, and more collaboration between researchers across the language divide would likely accelerate progress in non-English clinical NLP.
To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select best papers published in 2020.

A bibliographic search using a combination of Medical Subject Headings (MeSH) descriptors and free-text terms on CRI was performed using PubMed, followed by a double-blind review in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. After peer-review ranking, a consensus meeting between two section editors and the editorial team was organized to finally conclude on the selected four best papers.

Among the 877 papers published in 2020 and returned by the search, there were four best papers selected. The first best paper describes a method for mining temporal sequences from clinical documents to infer disease trajectories and enhancing high-throughput phenotyping. The authors of the second best paper demonstrate that the generation of synthetic Electronic Health Record (EHR) data through Generative Adversarial Networks (GANs) could be substantially improved by more appropriate training and evaluation criteria.
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