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Background Identification of protein-protein interactions (PPIs) is essential for a better understanding of biological processes, pathways and functions. However, experimental identification of the complete set of PPIs in a cell/organism (“an interactome”) is still a difficult task. To circumvent limitations of current high-throughput experimental techniques, it is necessary to develop high-performance computational methods for predicting PPIs. Results In this article, we propose a new computational method to predict interaction between a given pair of protein sequences using features derived from known homologous PPIs. The proposed method is capable of predicting interaction between two proteins (of unknown structure) using Averaged One-Dependence Estimators (AODE) and three features calculated for the protein pair: (a) sequence similarities to a known interacting protein pair (F Seq ), (b) statistical propensities of domain pairs observed in interacting proteins (F Dom ) and (c) a sum of edge weights along the shortest path between homologous proteins in a PPI network (F Net ). Feature vectors were defined to lie in a half-space of the symmetrical high-dimensional feature space to make them independent of the protein order. The predictability of the method was assessed by a 10-fold cross validation on a recently created human PPI dataset with randomly sampled negative data, and the best model achieved an Area Under the Curve of 0.79 (pAUC 0.5%  = 0.16). In addition, the AODE trained on all three features (named PSOPIA) showed better prediction performance on a separate independent data set than a recently reported homology-based method. Conclusions Our results suggest that F Net , a feature representing proximity in a known PPI network between two proteins that are homologous to a target protein pair, contributes to the prediction of whether the target proteins interact or not. PSOPIA will help identify novel PPIs and estimate complete PPI networks. The method proposed in this article is freely available on the web at http://mizuguchilab.org/PSOPIA .

The kidney possesses a highly organised vasculature that is required for its filtration function. While recent advances in stem cell biology have enabled the in vitro generation of kidney tissues, at least partially, recapitulation of the complicated vascular architecture remains a huge challenge. Herein we develop a method to reconstitute both the kidney and its vascular architecture in vitro , using dissociated and sorted mouse embryonic kidney cells. Upon transplantation, arteriolar networks were re-established that ran through the interstitial space between branching ureteric buds and eventually entered glomeruli. Using this system, we found that donor-derived endothelial cells significantly contributed to the arterioles and glomerular capillaries formed after transplantation. Unexpectedly, the near-complete depletion of canonical endothelial cells from the donor embryonic kidney suggested the existence of unidentified donor-derived endothelial precursors that were negative for canonical endothelial markers, but still contributed significantly to the vasculature in the transplants. Thus, our protocol will serve as a useful platform for identification of renal endothelial precursors and induction of these precursors from pluripotent stem cells.

Covalently bonded crystalline substances with micropores have broad applications. Covalent organic frameworks (COFs) are representative of such substances. They have so far been classified into two-dimensional (2D) and three-dimensional (3D) COFs. 2D-COFs have planar shapes useful for broad purposes, but obtaining good crystals of 2D-COFs with sizes larger than 10 μm is significantly challenging, whereas yielding 3D-COFs with high crystallinity and larger sizes is easier. Here, we show COFs with 2.5-dimensional (2.5D) skeletons, which are microscopically constructed with 3D bonds but have macroscopically 2D planar shapes. The 2.5D-COFs shown herein achieve large single-crystal sizes above 0.1 mm and ultrahigh-density primary amines regularly allocated on and pointing perpendicular to the covalently-bonded network plane. Owing to the latter nature, the COFs are promising as CO 2 adsorbents that can simultaneously achieve high CO 2 /N 2 selectivity and low heat of adsorption, which are usually in a mutually exclusive relationship. 2.5D-COFs are expected to broaden the frontier and application of covalently bonded microporous crystalline systems. Covalent organic frameworks (COFs) have wide applications but are difficult to enhance crystallinity. Here, the authors show COFs with 2.5-dimensional skeletons. The COFs attain planar shapes useful for applications, large crystal sizes of above 0.1 mm, and better CO2 separation properties over previous organic porous materials.

Background Acquired hemophilia A (AHA) is a rare disorder, and clinical practices for treating AHA have not been fully clarified in Japan. Objectives This study aims to investigate the epidemiology of AHA and real-world treatment practices in Japan. Patients/methods This observational study was based on a health administrative database of hospitalized patients diagnosed with AHA who were treated with immunosuppressants. Results The study included 214 males and 124 females (mean age 75.7 years). The most frequently used bypassing agent was recombinant activated factor VII. The predominant choice of immunosuppressant for first-line treatment was steroid monotherapy. Median days from the index date to the start of rehabilitation was 65.0 for cardiovascular, 35.5 for respiratory and 23.0 for locomotor. The proportion of patients with an activities of daily living (ADL) score < 70 points was high at both first admission and final discharge (47.4% and 38.8%). The percentage of deaths during hospitalization was 18.6%. Conclusions This study clarified the treatment patterns and clinical outcomes of AHA in a large population in Japan. This was the first study showing ADL score distribution and time to rehabilitation. Further investigation is needed to develop better clinical practices for treatment of AHA.

Congenital hemangioma (CH) is a rare form of vascular anomaly that develops prenatally, is difficult to differentiate from other vascular anomalies, and poses significant risks, including heart failure and severe hemorrhage. Herein, we present the case of a female infant born with a dark red mass measuring 30 mm × 20 mm in size, located on the right temporal region. She was referred to us for outpatient follow-up but presented to the emergency department on day 21 of life with a massive pulsatile hemorrhage originating from the mass. The patient simultaneously presented with tachycardia and cold extremities. We initiated artificial respiration and compression of the vascular anomalies, and the bleeding was well-controlled. Red blood cell transfusion stabilized her circulation, allowing transfer of the patient to Iwate Medical University Hospital for further evaluation. Owing to difficulties in differentiating CH from other vascular anomalies on imaging, a biopsy was performed. Histological examination revealed a dilated vascular cavity, lined with a single layer of endothelial-like cells with no arterial components. Although hemorrhage from rapidly involutingCH is rare, it is possible that ulceration of the CH could induce hemorrhage.

The acquisition of endocrine resistance is a common obstacle in endocrine therapy of patients with oestrogen receptor-α (ERα)-positive breast tumours. We previously demonstrated that the BIG3–PHB2 complex has a crucial role in the modulation of oestrogen/ERα signalling in breast cancer cells. Here we report a cell-permeable peptide inhibitor, called ERAP, that regulates multiple ERα-signalling pathways associated with tamoxifen resistance in breast cancer cells by inhibiting the interaction between BIG3 and PHB2. Intrinsic PHB2 released from BIG3 by ERAP directly binds to both nuclear- and membrane-associated ERα, which leads to the inhibition of multiple ERα-signalling pathways, including genomic and non-genomic ERα activation and ERα phosphorylation, and the growth of ERα-positive breast cancer cells both in vitro and in vivo . More importantly, ERAP treatment suppresses tamoxifen resistance and enhances tamoxifen responsiveness in ERα-positive breast cancer cells. These findings suggest inhibiting the interaction between BIG3 and PHB2 may be a new therapeutic strategy for the treatment of luminal-type breast cancer. Oestrogen receptor-α (ERα) signalling has a role in breast cancer drug resistance. Here, the authors report a synthetic peptide that disrupts the interaction between the signalling molecules BIG3 and PHB2, and thereby suppresses tamoxifen resistance.

Treatment of congenital hemophilia A (HA) in Japan has greatly improved with the widespread adoption of prophylactic factor (F)VIII concentrates. However, it is unknown ifhas translated into a real‐world reduction in disease and treatment burden. To describe HA disease burden in Japan based on information from two medical information databases, JMDC and Real World Data Co., Ltd. (RWD). Eligible individuals were diagnosed with congenital HA and prescribed FVIII concentrates, bypassing agents, or emicizumab. Treatment patterns and disease burden data were derived from health insurance claims and electronic medical records. Data on 459 people with HA were retrospectively collected from 2005 to 2020 in the JMDC database (median [min, max] of 37 [2, 186] months of available records), and 229 people with HA from 1985 to 2020 in the RWD database (median [min, max] of 154 [0, 409] months of available records). Mean (standard deviation) ages at the time of the first record were 25.0 (16.8) years (JMDC) and 19.2 (20.3) years (RWD). In the JMDC database, mean monthly FVIII dose increased from 2201 IU in 2005 to 8239 IU in 2013 to 11,377 IU in 2019; HA‐related drug costs increased accordingly. Mean (95% confidence interval) annual outpatient and out‐of‐hours visits decreased slightly between 2013 and 2019 (outpatient visits: from 22.9 [16.8–29.0] to 14.3 [12.6–16.1] per person; out‐of‐hours visits: from 1.3 [0.2–2.5] to 0.6 [0–1.4]). There was no change in mean number of hospitalizations. Challenges remain in HA, including treatment burden, outpatient visits, and hospitalizations. [Display omitted]

NLDB (Natural Ligand DataBase; URL: http://nldb.hgc.jp ) is a database of automatically collected and predicted 3D protein–ligand interactions for the enzymatic reactions of metabolic pathways registered in KEGG. Structural information about these reactions is important for studying the molecular functions of enzymes, however a large number of the 3D interactions are still unknown. Therefore, in order to complement such missing information, we predicted protein–ligand complex structures, and constructed a database of the 3D interactions in reactions. NLDB provides three different types of data resources; the natural complexes are experimentally determined protein–ligand complex structures in PDB, the analog complexes are predicted based on known protein structures in a complex with a similar ligand, and the ab initio complexes are predicted by docking simulations. In addition, NLDB shows the known polymorphisms found in human genome on protein structures. The database has a flexible search function based on various types of keywords, and an enrichment analysis function based on a set of KEGG compound IDs. NLDB will be a valuable resource for experimental biologists studying protein–ligand interactions in specific reactions, and for theoretical researchers wishing to undertake more precise simulations of interactions.

Brefeldin A-inhibited guanine nucleotide-exchange protein 3 (BIG3) has been identified recently as a novel regulator of estrogen signalling in breast cancer cells. Despite being a potential target for new breast cancer treatment, its amino acid sequence suggests no association with any well-characterized protein family and provides little clues as to its molecular function. In this paper, we predicted the structure, function and interactions of BIG3 using a range of bioinformatic tools. Homology search results showed that BIG3 had distinct features from its paralogues, BIG1 and BIG2, with a unique region between the two shared domains, Sec7 and DUF1981. Although BIG3 contains Sec7 domain, the lack of the conserved motif and the critical glutamate residue suggested no potential guaninyl-exchange factor (GEF) activity. Fold recognition tools predicted BIG3 to adopt an [alpha]-helical repeat structure similar to that of the armadillo (ARM) family. Using state-of-the-art methods, we predicted interaction sites between BIG3 and its partner PHB2. The combined results of the structure and interaction prediction led to a novel hypothesis that one of the predicted helices of BIG3 might play an important role in binding to PHB2 and thereby preventing its translocation to the nucleus. This hypothesis has been subsequently verified experimentally.

Background Brefeldin A-inhibited guanine nucleotide-exchange protein 3 (BIG3) has been identified recently as a novel regulator of estrogen signalling in breast cancer cells. Despite being a potential target for new breast cancer treatment, its amino acid sequence suggests no association with any well-characterized protein family and provides little clues as to its molecular function. In this paper, we predicted the structure, function and interactions of BIG3 using a range of bioinformatic tools. Results Homology search results showed that BIG3 had distinct features from its paralogues, BIG1 and BIG2, with a unique region between the two shared domains, Sec7 and DUF1981. Although BIG3 contains Sec7 domain, the lack of the conserved motif and the critical glutamate residue suggested no potential guaninyl-exchange factor (GEF) activity. Fold recognition tools predicted BIG3 to adopt an α-helical repeat structure similar to that of the armadillo (ARM) family. Using state-of-the-art methods, we predicted interaction sites between BIG3 and its partner PHB2. Conclusions The combined results of the structure and interaction prediction led to a novel hypothesis that one of the predicted helices of BIG3 might play an important role in binding to PHB2 and thereby preventing its translocation to the nucleus. This hypothesis has been subsequently verified experimentally.