SUMMARY Determining the composition of protein complexes is an essential step towards understanding the cell as an integrated system. Using co-affinity purification coupled to mass spectrometry analysis, we examined protein associations involving nearly five thousand individual, FLAG-HA epitope-tagged Drosophila proteins. Stringent analysis of these data, based on a novel statistical framework to define individual protein-protein interactions, led to the generation of a Drosophila Protein interaction Map (DPiM) encompassing 556 protein complexes. The high quality of DPiM and its usefulness as a paradigm for metazoan proteomes is apparent from the recovery of many known complexes, significant enrichment for shared functional attributes and validation in human cells. DPiM defines potential novel members for several important protein complexes and assigns functional links to 586 protein-coding genes lacking previous experimental annotation. DPiM represents, to our knowledge, the largest metazoan protein complex map and provides a valuable resource for analysis of protein complex evolution.

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Coronavirus disease 2019 (COVID-19) is a health emergency worldwide, and gastrointestinal (GI) symptoms are increasingly reported in COVID-19 patients. However, sample size was small and the incidence of GI symptoms in patients was variable across studies, and the correlation between these symptoms and clinical outcomes remains incompletely understood. The objective of this study is to compare clinical characteristics and outcomes between patients with and without GI symptoms admitted to Jianghan Fangcang Shelter Hospital in Wuhan. This retrospective study recruited 1320 COVID-19 patients admitted to hospital from 5 February 2020 to 9 March 2020. On the basis of the presence of GI symptoms, the sample was divided into a GI group (n = 192) and a non-GI group (n = 1128). The three most common GI symptoms were diarrhea (8.1%), anorexia (4.7%), and nausea and vomiting (4.3%). The rate of clinical deterioration was significantly higher in the GI group than in the non-GI group (15.6% vs. 10.1%, P = .032). GI symptoms (P = .045), male gender P < .001), and increased C-reactive protein (P = .008) were independent risk factors for clinical worsening. This study demonstrated that the rate of clinical deterioration was significantly higher in the GI group. Furthermore, potential risk factors for developing GI symptoms, male gender, and increased C-reactive protein can help clinicians predict clinical outcomes in COVID-19 patients.

Objective:To clarify if fracture site is correlated to the occurrence of deep venous thrombosis, and determine the risk factors of deep venous thrombosis in lower extremity fractures, help surgeons make prophylaxis for the disease correctly.Methods:The patients with lower extremity fractures treated surgically in the orthopedics department of our hospital from May 2012 to July 2017 were reviewed retrospectively. The clinical data including age, gender, fracture site, surgery modality, hospital stay, operation time, occupation type, hypertension, coronary heart disease, diabetes, smoking status, drinking status, postoperative exercises were collected and analyzed.Results:Eight hundred and twenty-nine patients were included for analysis, in which 68 were included in deep venous thrombosis group, 761 were included in the non-deep venous thrombosis group, and the incidence of deep venous thrombosis was 8.2%. There were significant differences in age, fracture site, surgery modality, occupation type, operation time, smoking status, hospital stay and postoperative exercises between the two groups (p<0.05), but no significant differences in gender, drinking status, coronary heart disease, diabetes and hypertension (p>0.05). In multivariate analysis, old age greater than 50 years, arthroplasty and operation time more than three hours were independent risk factors, while physical labor and postoperative exercises were protective factors for deep venous thrombosis in lower extremity fractures.Conclusion:Fracture site was correlated to the incidence of deep venous thrombosis, old age, longer operation time, and arthroplasty were independent risk factors, physical labor and postoperative exercises were protective factors for deep venous thrombosis in patients with lower extremity fractures.

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As many small bioactive molecules fulfill their functions through interacting with protein targets, the identification of such targets is crucial in understanding their mechanisms of action (MOA) and side effects. With technological advancements in target identification, it has become possible to accurately and comprehensively study the MOA and side effects of small molecules. While small molecules with therapeutic potential were derived solely from nature in the past, the remodeling and synthesis of such molecules have now been made possible. Presently, while some small molecules have seen successful application as drugs, the majority remain undeveloped, requiring further understanding of their MOA and side effects to fully tap into their potential. Given the typical promiscuity of many small molecules and the complexity of the cellular proteome, a high-flux and high-accuracy method is necessary. While affinity chromatography approaches combined with MS have had successes in target identification, limitations associated with nonspecific results remain. To overcome these complications, quantitative chemical proteomics approaches have been developed including metabolic labeling, chemical labeling, and label-free methods. These new approaches are adopted in conjunction with activity-based protein profiling (ABPP), allowing for a rapid process and accurate results. This review will briefly introduce the principles involved in ABPP, then summarize current advances in quantitative chemical proteomics approaches as well as illustrate with examples how ABPP coupled with quantitative chemical proteomics has been used to detect the targets of drugs and other bioactive small molecules including natural products.