PTRF/Cavin-1 and MIF Proteins Are Identified as Non-Small Cell Lung Cancer Biomarkers by Label-Free Proteomics

With the completion of the human genome sequence, biomedical sciences have entered in the “omics” era, mainly due to high-throughput genomics techniques and the recent application of mass spectrometry to proteomics analyses. However, there is still a time lag between these technological advances and their application in the clinical setting. Our work is designed to build bridges between high-performance proteomics and clinical routine. Protein extracts were obtained from fresh frozen normal lung and non-small cell lung cancer samples. We applied a phosphopeptide enrichment followed by LC-MS/MS. Subsequent label-free quantification and bioinformatics analyses were performed. We assessed protein patterns on these samples, showing dozens of differential markers between normal and tumor tissue. Gene ontology and interactome analyses identified signaling pathways altered on tumor tissue. We have identified two proteins, PTRF/cavin-1 and MIF, which are differentially expressed between normal lung and non-small cell lung cancer. These potential biomarkers were validated using western blot and immunohistochemistry. The application of discovery-based proteomics analyses in clinical samples allowed us to identify new potential biomarkers and therapeutic targets in non-small cell lung cancer

The 2017 May 20th^{\rm th} stellar occultation by the elongated centaur (95626) 2002 GZ32_{32}

We predicted a stellar occultation of the bright star Gaia DR1 4332852996360346368 (UCAC4 385-75921) (m$_{\rm V}$= 14.0 mag) by the centaur 2002 GZ$_{32}$ for 2017 May 20$^{\rm th}$. Our latest shadow path prediction was favourable to a large region in Europe. Observations were arranged in a broad region inside the nominal shadow path. Series of images were obtained with 29 telescopes throughout Europe and from six of them (five in Spain and one in Greece) we detected the occultation. This is the fourth centaur, besides Chariklo, Chiron and Bienor, for which a multi-chord stellar occultation is reported. By means of an elliptical fit to the occultation chords we obtained the limb of 2002 GZ$_{32}$ during the occultation, resulting in an ellipse with axes of 305 $\pm$ 17 km $\times$ 146 $\pm$ 8 km. From this limb, thanks to a rotational light curve obtained shortly after the occultation, we derived the geometric albedo of 2002 GZ$_{32}$ ($p_{\rm V}$ = 0.043 $\pm$ 0.007) and a 3-D ellipsoidal shape with axes 366 km $\times$ 306 km $\times$ 120 km. This shape is not fully consistent with a homogeneous body in hydrostatic equilibrium for the known rotation period of 2002 GZ$_{32}$. The size (albedo) obtained from the occultation is respectively smaller (greater) than that derived from the radiometric technique but compatible within error bars. No rings or debris around 2002 GZ$_{32}$ were detected from the occultation, but narrow and thin rings cannot be discarded.Comment: Accepted for publication in MNRAS (8-Dec.-2020), 15 pages, 9 figure

An immunohistochemical perspective of PPARβ and one of its putative targets PDK1 in normal ovaries, benign and malignant ovarian tumours

Peroxisome proliferator-activated receptor β (PPARβ) is a member of the nuclear hormone receptor family and is a ligand-activated transcription factor with few known molecular targets including 3-phosphoinositide-dependent protein kinase 1(PDK1). In view of the association of PPARβ and PDK1 with cancer, we have examined the expression of PPARβ and PDK1 in normal ovaries and different histological grades of ovarian tumours. Normal ovaries, benign, borderline, grades 1, 2 and 3 ovarian tumours of serous, muciuous, endometrioid, clear cell and mixed subtypes were analysed by immunohistochemistry for PPARβ and PDK1 expression. All normal ovarian tissues, benign, borderline and grade 1 tumours showed PPARβ staining localised in the epithelium and stroma. Staining was predominantly nuclear, but some degree of cytoplasmic staining was also evident. Approximately 20% of grades 2 and 3 tumours lacked PPARβ staining, whereas the rest displayed some degree of nuclear and cytoplasmic staining of the scattered epithelium and stroma. The extent of epithelial and stromal PPARβ staining was significantly different among the normal and the histological grades of tumours (χ2=59.25, d.f.=25, P<0.001; χ2=64.48, d.f.=25, P<0.001). Significantly different staining of PPARβ was observed in the epithelium and stroma of benign and borderline tumours compared with grades 1, 2 and 3 tumours (χ2=11.28, d.f.=4, P<0.05; χ2=16.15, d.f.=4, P<0.005). In contrast, PDK1 immunostaining was absent in 9 out of 10 normal ovaries. Weak staining for PDK1 was observed in one normal ovary and 40% of benign ovarian tumours. All borderline and malignant ovarian tumours showed positive cytoplasmic and membrane PDK1 staining. Staining of PDK1 was confined to the epithelium and the blood vessels, and no apparent staining of the stroma was evident. Significantly different PDK1 staining was observed between the benign/borderline and malignant ovarian tumours (χ2=22.45, d.f.=5, P<0.001). In some borderline and high-grade tumours, staining of the reactive stroma was also evident. Our results suggest that unlike the colon, the endometrial, head and neck carcinomas, overexpression of PPARβ does not occur in ovarian tumours. However, overexpression of PDK1 was evident in borderline and low- to high-grade ovarian tumours and is consistent with its known role in tumorigenesis

Physical properties of the trans-Neptunian binary 2000 YW₁₃₄

The study of trans-Neptunian binaries (TNBs) remains one of the most active areas of progress in understanding the solar system beyond Neptune. TNBs have been found in every dynamical population of the trans-Neptunian region (Noll et al. 2020), with proportions ranging from 29 % in the cold classical population to 5.5 % for the remaining classes combined (Brunini 2020). The formation of the contact TNB Arrokoth is one of the challenges that formation models face nowadays. The current angular momentum of Arrokoth is too low and the current binary formation scenarios, by either rotational fission or streaming instability (Nesvorný et al. 2019), require also loss of angular momentum (McKinnon et al. 2020). Additionally, formation mechanisms of close binaries may be distinct from those for the wider pairs. As the angular momentum of a system approaches that of an object spinning near its critical rotation period, rotational fission is the most likely explanation for their formation (Descamps et al. 2008), which is thought to be the case for the proposed satellites of Varuna and 2002 TC302 systems (Fernández-Valenzuela et al. 2019; Ortiz et al. 2020). If close TNBs turn out to be common for objects rotating close to the breakup limit, that could reveal important clues about angular momentum evolution during accretion for TNOs (Petit et al. 2011). However, characterizing binary systems at such distances is challenging. From the ~120 known TNBs, only around 40 have their mutual orbit fully determined, let alone physical characterization. 2000 YW134 is a TNB in a 3:8 resonance with an orbital semi-major axis of 57.4 au (a rare occurrence). On February 23rd, 2022, it occulted the Gaia EDR3 star 627356458358636544 (V = 17.1 mag). The stellar occultation was initially predicted using the JPL orbit solution #24, and updated using data from the 1.5-m and 1.23-m telescopes at Sierra Nevada and Calar Alto Observatories, using the same methodology as explained in Ortiz et al (2020). From the 17 observatories involved, seven reported positive chords, with five of them corresponding to the main body and the other two chords corresponding to its satellite. We are currently working on the analysis of these data in order to obtain the physical properties that characterize the system. Preliminary results show that the lower limit for the equivalent projected diameter of the satellite is twice the previously estimated size from HST observations (Stephens et al. 2006). We will also compare our results with the area-equivalent diameter and albedo obtained using thermal data from Herschel and Spitzer observations (Farkas-Takács et al. 2020)

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability