BiMPADR: A Deep Learning Framework for Predicting Adverse Drug Reactions in New Drugs.

Detecting the unintended adverse reactions of drugs (ADRs) is a crucial concern in pharmacological research. The experimental validation of drug-ADR associations often entails expensive and time-consuming investigations. Thus, a computational model to predict ADRs from known associations is essential for enhanced efficiency and cost-effectiveness. Here, we propose BiMPADR, a novel model that integrates drug gene expression into adverse reaction features using a message passing neural network on a bipartite graph of drugs and adverse reactions, leveraging publicly available data. By combining the computed adverse reaction features with the structural fingerprints of drugs, we predict the association between drugs and adverse reactions. Our models obtained high AUC (area under the receiver operating characteristic curve) values ranging from 0.861 to 0.907 in an external drug validation dataset under differential experiment conditions. The case study on multiple BET inhibitors also demonstrated the high accuracy of our predictions, and our model's exploration of potential adverse reactions for HWD-870 has contributed to its research and development for market approval. In summary, our method would provide a promising tool for ADR prediction and drug safety assessment in drug discovery and development.

Identifying survival of pan-cancer patients under immunotherapy using genomic mutation signature with large sample cohorts.

Although immune checkpoint inhibitors have led to durable clinical response in multiple cancers, only a small proportion of patients respond to this treatment. Therefore, we aim to develop a predictive model that utilizes gene mutation profiles to accurately identify the survival of pan-cancer patients with immunotherapy. Here, we develop and evaluate three different nomograms using two cohorts containing 1,594 cancer patients whose mutation profiles are obtained by MSK-IMPACT sequencing and 230 cancer patients receiving whole-exome sequencing, respectively. Using eighteen genes (SETD2, BRAF, NCOA3, LATS1, IL7R, CREBBP, TET1, EPHA7, KDM5C, MET, KMT2D, RET, PAK7, CSF1R, JAK2, FAT1, ASXL1 and SPEN), the first nomogram stratifies patients from both cohorts into High-Risk and Low-Risk groups. Pan-cancer patients in the High-Risk group exhibit significantly shorter overall survival and progression-free survival than patients in the Low-Risk group in both cohorts. Meanwhile, the first nomogram also accurately identifies the survival of patients with melanoma or lung cancer undergoing immunotherapy, or pan-cancer patients treated with anti-PD-1/PD-L1 inhibitor or anti-CTLA-4 inhibitor. The model proposed is not a prognostic model for the survival of pan-cancer patients without immunotherapy, but a simple, effective and robust predictive model for pan-cancer patients' survival under immunotherapy, and could provide valuable assistance for clinical practice.

E2EFP-MIL: End-to-end and high-generalizability weakly supervised deep convolutional network for lung cancer classification from whole slide image.

Efficient and accurate distinction of histopathological subtype of lung cancer is quite critical for the individualized treatment. So far, artificial intelligence techniques have been developed, whose performance yet remained debatable on more heterogenous data, hindering their clinical deployment. Here, we propose an end-to-end, well-generalized and data-efficient weakly supervised deep learning-based method. The method, end-to-end feature pyramid deep multi-instance learning model (E2EFP-MIL), contains an iterative sampling module, a trainable feature pyramid module and a robust feature aggregation module. E2EFP-MIL uses end-to-end learning to extract generalized morphological features automatically and identify discriminative histomorphological patterns. This method is trained with 1007 whole slide images (WSIs) of lung cancer from TCGA, with AUCs of 0.95-0.97 in test sets. We validated E2EFP-MIL in 5 real-world external heterogenous cohorts including nearly 1600 WSIs from both United States and China with AUCs of 0.94-0.97, and found that 100-200 training images are enough to achieve an AUC of >0.9. E2EFP-MIL overperforms multiple state-of-the-art MIL-based methods with high accuracy and low hardware requirements. Excellent and robust results prove generalizability and effectiveness of E2EFP-MIL in clinical practice. Our code is available at https://github.com/raycaohmu/E2EFP-MIL.

Critical review on quality of methodology and recommendations of clinical practice guidelines for peri-implantitis.

BACKGROUND: Peri-implantitis is of high prevalence with the popularity of dental implants nowadays. Guidelines or consensus have been developed in succession, and we are little-known about their quality. The objective of this study is to evaluate the methodological quality of these guidelines and analyze the consistency of the clinical recommendations. METHODS: We searched for guidelines or consensus on prevention, diagnosis, and/or treatment of peri-implantitis through PubMed, Web of Science, Cochrane Library until January 15th, 2022. In addition, we also searched the websites of the American Dental Association, International Team for Implantology, FDI World Dental Federation, and some guideline collection databases. Appraisal of Guidelines for Research & Evaluation II methodological quality instrument was used to assess the selected guidelines. Furthermore, we described the consistency of recommendations across the included guidelines. RESULTS: In total, 15 guidelines were included. The mean values of the six domains score all below 50%. The mean scores of Applicability were lowest (mean:15%, range:4-29%). As to the overall quality, eleven (73%) were recommended after being modified, and four (27%) were not recommended. Among the clinical recommendations, 53 (67.09%) are for treatment of peri-implantitis, 13 (16.46%) for monitoring issue, 7 (8.86%) for diagnosis, 3 (3.80%) for the disease prevention. CONCLUSIONS: Improving methodology quality and strengthening clinical evidence is essential in the future guideline development in a range of disciplines for improving the treatment effectiveness of people with peri-implantitis. And there is a lack of integrated guidelines in the case of the COVID-19 pandemic.

HiRAND: A novel GCN semi-supervised deep learning-based framework for classification and feature selection in drug research and development.

The prediction of response to drugs before initiating therapy based on transcriptome data is a major challenge. However, identifying effective drug response label data costs time and resources. Methods available often predict poorly and fail to identify robust biomarkers due to the curse of dimensionality: high dimensionality and low sample size. Therefore, this necessitates the development of predictive models to effectively predict the response to drugs using limited labeled data while being interpretable. In this study, we report a novel Hierarchical Graph Random Neural Networks (HiRAND) framework to predict the drug response using transcriptome data of few labeled data and additional unlabeled data. HiRAND completes the information integration of the gene graph and sample graph by graph convolutional network (GCN). The innovation of our model is leveraging data augmentation strategy to solve the dilemma of limited labeled data and using consistency regularization to optimize the prediction consistency of unlabeled data across different data augmentations. The results showed that HiRAND achieved better performance than competitive methods in various prediction scenarios, including both simulation data and multiple drug response data. We found that the prediction ability of HiRAND in the drug vorinostat showed the best results across all 62 drugs. In addition, HiRAND was interpreted to identify the key genes most important to vorinostat response, highlighting critical roles for ribosomal protein-related genes in the response to histone deacetylase inhibition. Our HiRAND could be utilized as an efficient framework for improving the drug response prediction performance using few labeled data.

TEMPO-Catalyzed Aminophosphinoylation of Ethers via Tandem C(sp3)-H and C(sp3)-O Bond Cleavage.

A new TEMPO-catalyzed aminophosphinoylation of ethers with amines and H-phosphine oxides was developed for the synthesis of α-aminophosphine oxides. This metal-free aminophosphinoylation reaction could be conducted under mild conditions through tandem C(sp3)-H and C(sp3)-O bond cleavage. The present method offers a facile and efficient approach to broad range of α-aminophosphine oxide derivatives in moderate to good yields with excellent functional group tolerance.

FAK inhibitors induce cell multinucleation and dramatically increase pro-tumoral cytokine expression in RAW 264.7 macrophages.

Macrophages are abundant in the tumor microenvironment. They are highly plastic and able to acquire pro-tumoral phenotypes in response to microenvironmental stimuli. When we treated RAW 264.7 macrophages with inhibitors of various oncogenic pathways, we found that the focal adhesion kinase (FAK) inhibitors PF573228 and TAE226 could induce cell multinucleation by suppressing furrowing and cytokinesis. This failure in cytokinesis involves Rac1, whose activity is elevated by FAK inhibitors, and the p21-activated kinases, comprising the downstream effectors of Rac. We also investigated the influence of cell multinucleation on macrophage physiology in RAW 264.7 cells. This is the first study to report that FAK inhibitors suppress furrow ingression and early cytokinesis. Of note, we found that FAK inhibitors caused a dramatic increase in pro-tumoral cytokines in multinuclear cells, suggesting the potential to convert macrophages into pro-tumoral phenotypes.

Saponins from Sanguisorba officinalis Improve Hematopoiesis by Promoting Survival through FAK and Erk1/2 Activation and Modulating Cytokine Production in Bone Marrow.

Radix Sanguisorbae, the root of Sanguisorba officinalis L. is used as traditional Chinese medicine. In recent decades, it has been reported to be clinically effective against myelosuppression induced by chemotherapy and/ or radiotherapy. However, the underlining mechanism has not been well studied. In this work, we evaluated the hematopoietic effect of total saponins from S. officinalis L. on myelosuppressive mice induced by cyclophosphamide and by60Co-γ-irradiation and confirmed the therapeutic effect. Then, we found total saponins and their characteristic constituents Ziyuglycoside I and Ziyuglycoside II can inhibit apoptosis of TF-1 cells caused by cytokine deprivation, and promote survival of mouse bone marrow nuclear cells through focal adhesion kinase (FAK) and extracellular signal-regulated kinase 1/2 (Erk1/2) activation in vitro. In addition, they can down-regulate macrophage inflammatory protein 2 (MIP-2), platelet factor 4 (PF4) and P-selectin secretion, which are reported to be suppressive to hematopoiesis, both in vitro and in vivo. These results suggest that promotion of survival through FAK and Erk1/2 activation and inhibition of suppressive cytokines in the bone marrow is likely to be the pharmacological mechanism underlying the hematopoietic effect of saponins from S. officinalis L.

Direct use of dioxygen as an oxygen source: catalytic oxidative synthesis of amides.

The first transition-metal-catalyzed direct oxidative synthesis of amides by using dioxygen as an oxygen source has been developed under mild conditions, in which DBU was used as the key additive. The present methodology, which utilizes dioxygen as an oxidant and oxygen source and cheap copper salts as catalysts, opens up an interesting and attractive avenue for the synthesis of amide functionality.

[Review on community herbal monographs for traditional herbal medicinal products].

This article discusses the characteristics of cmmunity herbal monographs for traditional herbal medicinal products and its establishment procedure. It also reviews the new development of cmmunity traditional herbal monographs. The purpose is to clarify the relationship between cmmunity herbal monographs and simplified registration for traditional herbal medicinal product in European Union and provide reference to the registration of taditional Chinese mdicinal products in Europe.

Gold-catalyzed three-component tandem process: an efficient and facile assembly of complex butenolides from alkynes, amines, and glyoxylic acid.

An efficient and facile gold-catalyzed three-component tandem process for the assembly of two types of highly functionalized butenolides has been developed. In this reaction system, more than four chemical bonds are formed by a single gold catalyst. The present tandem protocol includes a direct coupling of alkynes, amines, and glyoxylic acid and subsequent exclusively endo-selective cycloisomerization of alkynoic acids along with intermolecular electrophilic trapping; it utilizes three simple and commercially available starting materials to assemble architecturally complex and appealing butenolide scaffolds bearing other reactive sites for further manipulation.

Synthesis and evaluation of structurally constrained imidazolidin derivatives as potent dipeptidyl peptidase IV inhibitors.

To find potent and selective inhibitors of dipeptidyl peptidase IV (DPP-IV), we synthesized a series of 2-cyanopyrrolidine derivatives with constrained imidazolidin ring and tested their activities against DPP-IV. Most of them exhibited submicromolar inhibitory activities against DPP-IV. The most potent compound among these is (S)-1-(2-(2-(3-(3,4-dimethoxyphenyl)-2-oxoimidazolidin-1-yl)ethyl-amino)acetyl)pyrrolidine-2-carbonitrile (6n), which is a 2 nM DPP-IV inhibitor.

Phospholipid-protein adducts of lipid peroxidation: synthesis and study of new biotinylated phosphatidylcholines.

Oxidative stress gives rise to a number of electrophilic aldehydes from membrane phospholipids, and these compounds have been linked to pathophysiologic events associated with the progression of cardiovascular disease. A headgroup biotinylated phosphatidylcholine (PC) has been prepared, and its oxidation chemistry has been studied. Biotin or biotin-sulfoxide groups were attached to PC at the ammonium headgroup via a di-ethylene glycol link. The modified phospholipids have calorimetric and colloidal properties similar to those of the parent. The oxidation of PLPBSO (the biotin-sulfoxide analogue of 1-palmitoyl-2-linoleoylglycerylphosphatidylcholine, PLPC) was studied under a variety of conditions. PLPBSO, like PLPC, undergoes oxidation to give electrophiles that adduct to small model peptides as well as to isolated proteins such as human serum albumin. PLPBSO incorporates into human blood plasma, and treatment of the plasma with water soluble free radical initiators gives rise to a number of biotinylated plasma proteins that can be isolated via (strept)avidin affinity. Isolated peptide or protein-lipid adducts can be identified by proteomics analyses, and studies on model peptides show that phospholipid-protein adduction sites can be identified by known algorithms. Biotinylated lipids such as PLPBSO and modern proteomics tools would appear to provide a new approach to exploring the chemistry and biology of membrane peroxidation associated with oxidative stress.

Catalytic asymmetric alkynylation of alpha-imino ester: a versatile approach to optically active unnatural alpha-amino acid derivatives.

The catalytic asymmetric introduction of alkynyl functionality to alpha-amino acid derivatives was realized by the direct addition of terminal alkynes to alpha-imino ester in the presence of chiral Cu(I) complex under mild reaction conditions. Owing to the rich chemistry to which alkyne can be subjected, the present system provides a remarkably versatile tool for the construction of optically active alpha-amino acid derivatives. Good yields and enantiomeric excess values were achieved with an array of terminal alkynes and challenging, biologically active, unnatural alpha-amino acid derivatives could be conveniently obtained.

Air-stable Ir-(P-Phos) complex for highly enantioselective hydrogenation of quinolines and their immobilization in poly(ethylene glycol) dimethyl ether (DMPEG).

An air-stable catalyst system Ir-(P-Phos) catalyst was found to be highly effective in the asymmetric hydrogenation of quinoline derivatives. The catalyst immobilized in DMPEG was efficiently recovered and reused eight times, retaining reactivity and enantioselectivity.

A remarkably effective copper(II)-dipyridylphosphine catalyst system for the asymmetric hydrosilylation of ketones in air.

The combination of catalytic amounts of optically active dipyridylphosphine and CuF(2) along with hydride donor PhSiH(3) generated in situ a remarkably reactive catalyst system (substrate-to-ligand molar ratio up to 100,000) for the highly enantioselective hydrosilylation of a broad spectrum of aryl alkyl ketones (up to 97% enantiomeric excess) in normal atmosphere and at mild conditions (ambient temperature to -20 degrees C, compatible with traces of moisture) in the absence of base additives. Furthermore, a highly effective catalytic asymmetric hydrosilylation of unsymmetrical diarylketones using this catalyst system was also realized (up to 98% enantiomeric excess). The introduction of the dipyridylphosphine ligands in the air-accelerated and inexpensive metal-mediated asymmetric hydrosilylation of ketones makes the present system highly attractive and thus provides an excellent opportunity for practical applications.

Highly enantioselective phenyl transfer to aryl aldehydes catalyzed by easily accessible chiral tertiary aminonaphthol.

A new chiral tertiary aminonaphthol ligand 3b served as a highly efficient ligand for the asymmetric catalytic phenyl transfer to aromatic aldehydes and a variety of chiral diarylmethanols was prepared in high ee values (ee up to 99%) and chemical yields. The straightforward syntheses of both 3b and its enantiomer provide an excellent opportunity for large-scale applications.

Remarkably diastereoselective synthesis of a chiral biphenyl diphosphine ligand and its application in asymmetric hydrogenation.

Essentially complete atropdiastereoselectivity was realized in the preparation of biaryl diphosphine dioxide by asymmetric intramolecular Ullmann coupling and oxidative coupling with central-to-axial chirality transfer. A bridged C(2)-symmetric biphenyl phosphine ligand possessing additional chiral centers on the linking unit of the biphenyl groups was synthesized. No resolution step was required for the preparation of the enantiomerically pure chiral ligand. These findings offer a general and practical tool for the development of previously uninvestigated atropdiastereomeric biaryl phosphine ligands. The diphosphine ligand was found to be highly effective in the asymmetric hydrogenation of alpha- and beta-ketoesters, 2-(6'-methoxy-2'-naphthyl)propenoic acid, beta-(acylamino)acrylates, and enol acetates.