Predicting transcriptional responses to novel chemical perturbations using deep generative model for drug discovery.

Understanding transcriptional responses to chemical perturbations is central to drug discovery, but exhaustive experimental screening of disease-compound combinations is unfeasible. To overcome this limitation, here we introduce PRnet, a perturbation-conditioned deep generative model that predicts transcriptional responses to novel chemical perturbations that have never experimentally perturbed at bulk and single-cell levels. Evaluations indicate that PRnet outperforms alternative methods in predicting responses across novel compounds, pathways, and cell lines.

Clinical value of a radiomics model based on machine learning for the prediction of prostate cancer.

Objective: Radiomics models have demonstrated good performance for the diagnosis and evaluation of prostate cancer (PCa). However, there are currently no validated imaging models that can predict PCa or clinically significant prostate cancer (csPCa). Therefore, we aimed to identify the best such models for the prediction of PCa and csPCa.

The pathological mechanisms and potential therapeutic drugs for myocardial ischemia reperfusion injury.

Background: Cardiovascular disease is the main cause of death and disability, with myocardial ischemia being the predominant type that poses a significant threat to humans. Reperfusion, an essential therapeutic approach, promptly reinstates blood circulation to the ischemic myocardium and stands as the most efficacious clinical method for myocardial preservation. Nevertheless, the restoration of blood flow associated with this process can potentially induce myocardial ischemia-reperfusion injury (MIRI), thereby diminishing the effectiveness of reperfusion and impacting patient prognosis.

Thyroid dysfunction associated with iodine-contrast media: A real-world pharmacovigilance study based on the FDA adverse event reporting system.

Objective: To comprehensively analyze characteristics of thyroid dysfunction associated with iodine contrast media (ICM) based on data from the FDA adverse event reporting system (FAERS).

Methods: Disproportionate analysis was employed to identify signals of thyroid dysfunction caused by ICM, and descriptive analysis was performed to examine the clinical characteristics of reported cases involving ICM-related thyroid dysfunctions.

Results: A total of 83 adverse event reports were identified, documenting thyroid dysfunctions associated with ICM agents.

Comparative Analysis of Chemical Cross-Linking Mass Spectrometry Data Indicates That Protein STY Residues Rarely React with -Hydroxysuccinimide Ester Cross-Linkers.

When it comes to mass spectrometry data analysis for identification of peptide pairs linked by -hydroxysuccinimide (NHS) ester cross-linkers, search engines bifurcate in their setting of cross-linkable sites. Some restrict NHS ester cross-linkable sites to lysine (K) and protein N-terminus, referred to as K only for short, whereas others additionally include serine (S), threonine (T), and tyrosine (Y) by default. Here, by setting amino acids with chemically inert side chains such as glycine (G), valine (V), and leucine (L) as cross-linkable sites, which serves as a negative control, we show that software-identified STY-cross-links are only as reliable as GVL-cross-links.

Are Older People Really More Susceptible to SARS-CoV-2?

Since the outbreak, COVID-19 has spread rapidly across the globe due to its high infectivity and lethality. Age appears to be one of the key factors influencing the status and progression of SARS-CoV-2 infection, as multiple reports indicated that the majority of COVID-19 infections and severe cases are elderly. Most people simply assume that the elderly are more susceptible to SARS-CoV-2 than the young, but the mechanism behind it is still open to question.

Efficacy and Safety of Lianhua Qingwen for Patients with COVID-19: A Systematic Review and Meta-Analysis.

Background: Corona virus disease 2019 (COVID-19) has spread around the world since its outbreak, and there is no ascertained effective drug up to now. Lianhua Qingwen (LHQW) has been widely used in China and overseas Chinese, which had some advantages in the treatment of COVID-19.

Objective: To evaluate the efficacy and safety of LHQW for COVID-19 by conducting a systematic review with meta-analysis.

Efficacy and Safety of "Three Chinese Patent Medicines and Three TCM Prescriptions" for COVID-19: A Systematic Review and Network Meta-Analysis.

Objective: To systematically evaluate the efficacy, safety, and precision of TMTP for COVID-19.

Methods: Randomized controlled trials and retrospective studies were searched in 11 electronic databases. This network meta-analysis included trials using TMTP to treat patients with COVID-19.

Efficacy and Safety of Decoction for Patients with Coronary Heart Disease: A Systematic Review and Meta-Analysis.

Objective: To systematically evaluate the efficacy and safety of XFZYD for coronary heart disease (CHD).

Methods: A comprehensive literature search of randomized controlled trials using XFZYD for CHD was conducted in 10 electronic databases from their establishment to December 20, 2020. The researchers screened the relevant trials in NoteExpress, extracted the data in duplicate independently, assessed the risk of bias in the trials using the Cochrane collaboration tool, and then used Rev Man 5.

pDeepXL: MS/MS Spectrum Prediction for Cross-Linked Peptide Pairs by Deep Learning.

In cross-linking mass spectrometry, the identification of cross-linked peptide pairs heavily relies on the ability of a database search engine to measure the similarities between experimental and theoretical MS/MS spectra. However, the lack of accurate ion intensities in theoretical spectra impairs the performance of search engines, in particular, on proteome scales. Here we introduce pDeepXL, a deep neural network to predict MS/MS spectra of cross-linked peptide pairs.

Qiju Dihuang Decoction for Hypertension: A Systematic Review and Meta-Analysis.

Objective: To systematically evaluate the efficacy of Chinese herbal medicine Qiju Dihuang Decoction (QDD) for hypertension.

Methods: A comprehensive literature search of randomized controlled trials using QDD to treat hypertension was conducted in 7 electronic databases, including Chinese databases. Subjects and abstracts of the trials were read in NoteExpress for preliminary screening, and the full text was read for further screening.

Improving mass spectrometry analysis of protein structures with arginine-selective chemical cross-linkers.

Chemical cross-linking of proteins coupled with mass spectrometry analysis (CXMS) is widely used to study protein-protein interactions (PPI), protein structures, and even protein dynamics. However, structural information provided by CXMS is still limited, partly because most CXMS experiments use lysine-lysine (K-K) cross-linkers. Although superb in selectivity and reactivity, they are ineffective for lysine deficient regions.

A high-speed search engine pLink 2 with systematic evaluation for proteome-scale identification of cross-linked peptides.

We describe pLink 2, a search engine with higher speed and reliability for proteome-scale identification of cross-linked peptides. With a two-stage open search strategy facilitated by fragment indexing, pLink 2 is ~40 times faster than pLink 1 and 3~10 times faster than Kojak. Furthermore, using simulated datasets, synthetic datasets, N metabolically labeled datasets, and entrapment databases, four analysis methods were designed to evaluate the credibility of ten state-of-the-art search engines.

Comprehensive identification of peptides in tandem mass spectra using an efficient open search engine.

We present a sequence-tag-based search engine, Open-pFind, to identify peptides in an ultra-large search space that includes coeluting peptides, unexpected modifications and digestions. Our method detects peptides with higher precision and speed than seven other search engines. Open-pFind identified 70-85% of the tandem mass spectra in four large-scale datasets and 14,064 proteins, each supported by at least two protein-unique peptides, in a human proteome dataset.

Mapping disulfide bonds from sub-micrograms of purified proteins or micrograms of complex protein mixtures.

Disulfide bonds are vital for protein functions, but locating the linkage sites has been a challenge in protein chemistry, especially when the quantity of a sample is small or the complexity is high. In 2015, our laboratory developed a sensitive and efficient method for mapping protein disulfide bonds from simple or complex samples (Lu . in Nat Methods 12:329, 2015).

pSite: Amino Acid Confidence Evaluation for Quality Control of De Novo Peptide Sequencing and Modification Site Localization.

MS-based de novo peptide sequencing has been improved remarkably with significant development of mass-spectrometry and computational approaches but still lacks quality-control methods. Here we proposed a novel algorithm pSite to evaluate the confidence of each amino acid rather than the full-length peptides obtained by de novo peptide sequencing. A semi-supervised learning approach was used to discriminate correct amino acids from random one; then, an expectation-maximization algorithm was used to adaptively control the false amino-acid rate (FAR).

[Quantitative analysis of galangin from propolis in different areas by HPLC].

Objective: To establish an HPLC method for determination of galangin in propolis.

Methods: HPLC method was established. Diamonsil C18 column was used, CH3OH-4% H3PO4 solution (65:35) as mobile phase, at the flow rate of 1.