Ctenidins: antimicrobial glycine-rich peptides from the hemocytes of the spider Cupiennius salei

Three novel glycine-rich peptides, named ctenidin 1-3, with activity against the Gram-negative bacterium E. coli, were isolated and characterized from hemocytes of the spider Cupiennius salei. Ctenidins have a high glycine content (>70%), similarly to other glycine-rich peptides, the acanthoscurrins, from another spider, Acanthoscurria gomesiana. A combination of mass spectrometry, Edman degradation, and cDNA cloning revealed the presence of three isoforms of ctenidin, at least two of them originating from simple, intronless genes. The full-length sequences of the ctenidins consist of a 19 amino acid residues signal peptide followed by the mature peptides of 109, 119, or 120 amino acid residues. The mature peptides are post-translationally modified by the cleavage of one or two C-terminal cationic amino acid residue(s) and amidation of the newly created mature C-terminus. Tissue expression analysis revealed that ctenidins are constitutively expressed in hemocytes and to a small extent also in the subesophageal nerve mas

Uptake of Ecological Farming Practices by EU Farms: A Pan‐European Typology

Understanding and measuring the sustainability of farms is key to evaluating progress towards policy goals for a more sustainable agriculture. In the LIFT project, a farm typology was developed to classify farms according to their ecological performance, based on farm-level variables from the Farm Accountancy Data Network (FADN). Selected variables are used to assess three key ecological dimensions of farming: total input intensity; degree of circularity (reliance on own-produced versus external inputs); and avoidance of the use of specific inputs of concern for the environment and consumers. The combination of these aspects is considered as a measure of the farm proximity to a full agroecological approach. The typology allows comparison of farms across farm types, countries and years. We briefly present the method and discuss two key aspects: 1) how the proposed farm typology can inform policymaking in the context of a new EU policy framework; 2) how it can inform the foreseen transformation of the FADN into a Farm Sustainability Data Network (FSDN). We suggest that the use of a typology approach under the new FSDN provides useful information on the impacts of the implementation of agroecological practices with an acceptable additional effort in terms of data collection.</p

Post-coital intra-cerebral venous hemorrhage in a 78-year-old man with jugular valve incompetence: a case report

<p>Abstract</p> <p>Introduction</p> <p>Spontaneous intra-cerebral hemorrhage can occur in patients with venous disease due to obstructed venous outflow.</p> <p>Case presentation</p> <p>We report the case of a 78-year-old Caucasian man with jugular valve incompetence who experienced an intra-cerebral temporo-occipital hemorrhage following sexual intercourse. He had no other risk factors for an intra-cerebral hemorrhage.</p> <p>Conclusions</p> <p>To the best of our knowledge, this is the first case of intra-cerebral hemorrhage due to jugular valve incompetence in association with the physical exertion associated with sexual intercourse.</p

Maximal surgical tumour load reduction in immune-checkpoint inhibitor naïve patients with melanoma brain metastases correlates with prolonged survival

Background: Recent therapeutic advances in metastatic melanoma have led to improved overall survival (OS) rates, with consequently an increased incidence of brain metastases (BM). The role of BM resection in the era of targeted and immunotherapy should be reassessed. In the current study we analysed the role of residual intracranial tumour load in a cohort of melanoma BM patients. Methods: Retrospective single-centre analysis of a prospective registry of resected melanoma BM from 2013 to 2021. Correlations of residual tumour volume and outcome were determined with respect to patient, tumour and treatment regimens characteristics. Results: 121 individual patients (66% male, mean age 59.9 years) were identified and included in the study. Pre- and postoperative systemic treatments included BRAF/MEK inhibitors, as well as combination or monotherapy of immune-checkpoint inhibitors (ICIs). Median OS of the entire cohort was 20 months. Cox proportional-hazard analysis revealed postoperative anti-CTLA4+anti-PD-1 therapy (HR 0.07, p = .01) and postoperative residual intracranial tumour burden (HR 1.4, p = .027) as significant predictors for OS. Further analysis revealed that ICI-naïve patients with residual tumour volume ≤3.5 cm3 and postoperative ICI showed significantly prolonged OS compared to patients with residual volume &gt;3.5 cm3 (p &lt; .0001). Subgroup analysis of ICI-naïve patients showed steroid intake postoperatively to be negatively associated with OS, however residual tumour volume ≤3.5 cm3 remained independently correlated with superior OS (HR 0.14, p &lt; .001). Conclusion: Besides known predictive factors like postoperative ICI, a maximal intracranial tumour burden reduction seems to be beneficial, especially in ICI-naïve patients. This highlights the importance of local CNS control and the need to further investigating the role of initial surgical tumour load reduction in randomised clinical trials. Keywords: Brain metastases; Extent of resection; Immunotherapy; Melanoma; Tumour residua

Neonatal high pressure hydrocephalus is associated with elevation of pro-inflammatory cytokines IL-18 and IFNgamma in cerebrospinal fluid

BACKGROUND: In human neonatal high pressure hydrocephalus (HPHC), diffuse white matter injury and gliosis predispose to poor neuro-developmental outcome. The underlying mechanism for diffuse white matter damage in neonatal HPHC is still unclear. Analogous to inflammatory white matter damage after neonatal hypoxemia/ischemia, we hypothesized that pro-inflammatory cytokines could be involved in neonatal HPHC. If so, early anti-inflammatory therapy could ameliorate white matter damage in HPHC, before irreversible apoptosis has occurred. In HPHC and control neonates, we therefore aimed to compare cerebrospinal fluid (CSF) concentrations of IL18, IFNγ and sFasL (interleukin 18, interferon gamma and apoptosis marker soluble-Fas ligand, respectively). METHODS: In neonatal HPHC (n = 30) and controls (n = 15), we compared CSF concentrations of IL18, IFNγ and sFasL using sandwich ELISA. HPHC was grouped according to etiology: spina bifida aperta (n = 20), aqueduct stenosis (n = 4), and fetal intra-cerebral haemorrhage (n = 6). Neonatal control CSF was derived from otherwise healthy neonates (n = 15), who underwent lumbar puncture for exclusion of meningitis. RESULTS: In all three HPHC groups, CSF IL18 concentrations were significantly higher than control values, and the fetal intracranial haemorrhage group was significantly higher than SBA group. Similarly, in all HPHC groups CSF-IFNγ concentrations significantly exceeded the control group. In both HPHC and control neonates, CSF FasL concentrations remained within the range of reference values. CONCLUSION: Independent of the pathogenesis, neonatal HPHC is associated with the activation of the pro-inflammatory cytokines (IL-18 and IFNγ) in the CSF, whereas CSF apoptosis biomarkers (sFasL) were unchanged. This suggests that anti-inflammatory treatment (in addition to shunting) could be helpful to preserve cerebral white matter

Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia

In a pandemic with a novel disease, disease-specific prognosis models are available only with a delay. To bridge the critical early phase, models built for similar diseases might be applied. To test the accuracy of such a knowledge transfer, we investigated how precise lethal courses in critically ill COVID-19 patients can be predicted by a model trained on critically ill non-COVID-19 viral pneumonia patients. We trained gradient boosted decision tree models on 718 (245 deceased) non-COVID-19 viral pneumonia patients to predict individual ICU mortality and applied it to 1054 (369 deceased) COVID-19 patients. Our model showed a significantly better predictive performance (AUROC 0.86 [95% CI 0.86-0.87]) than the clinical scores APACHE2 (0.63 [95% CI 0.61-0.65]), SAPS2 (0.72 [95% CI 0.71-0.74]) and SOFA (0.76 [95% CI 0.75-0.77]), the COVID-19-specific mortality prediction models of Zhou (0.76 [95% CI 0.73-0.78]) and Wang (laboratory: 0.62 [95% CI 0.59-0.65]; clinical: 0.56 [95% CI 0.55-0.58]) and the 4C COVID-19 Mortality score (0.71 [95% CI 0.70-0.72]). We conclude that lethal courses in critically ill COVID-19 patients can be predicted by a machine learning model trained on non-COVID-19 patients. Our results suggest that in a pandemic with a novel disease, prognosis models built for similar diseases can be applied, even when the diseases differ in time courses and in rates of critical and lethal courses

A Spitzer Survey for Dust in Type IIn Supernovae

Recent observations suggest that Type IIn supernovae (SNe IIn) may exhibit late-time (>100 days) infrared (IR) emission from warm dust more than other types of core-collapse SNe. Mid-IR observations, which span the peak of the thermal spectral energy distribution, provide useful constraints on the properties of the dust and, ultimately, the circumstellar environment, explosion mechanism, and progenitor system. Due to the low SN IIn rate (<10% of all core-collapse SNe), few IR observations exist for this subclass. The handful of isolated studies, however, show late-time IR emission from warm dust that, in some cases, extends for five or six years post-discovery. While previous Spitzer/IRAC surveys have searched for dust in SNe, none have targeted the Type IIn subclass. This article presents results from a warm Spitzer/IRAC survey of the positions of all 68 known SNe IIn within a distance of 250 Mpc between 1999 and 2008 that have remained unobserved by Spitzer more than 100 days post-discovery. The detection of late-time emission from ten targets (~15%) nearly doubles the database of existing mid-IR observations of SNe IIn. Although optical spectra show evidence for new dust formation in some cases, the data show that in most cases the likely origin of the mid-IR emission is pre-existing dust, which is continuously heated by optical emission generated by ongoing circumstellar interaction between the forward shock and circumstellar medium. Furthermore, an emerging trend suggests that these SNe decline at ~1000--2000 days post-discovery once the forward shock overruns the dust shell. The mass-loss rates associated with these dust shells are consistent with luminous blue variable (LBV) progenitors.Comment: Accepted for publication to ApJ, 17 pages, 10 figures, 10 table

The death of massive stars - I. Observational constraints on the progenitors of type II-P supernovae

We present the results of a 10.5 yr, volume limited (28 Mpc) search for supernova (SN) progenitor stars. We compile all SNe discovered within this volume (132, of which 27% are type Ia) and determine the relative rates of each sub-type from literature studies : II-P (59%), Ib/c (29%), IIb (5%), IIn (4%) and II-L (3%). Twenty II-P SNe have high quality optical or near-IR pre-explosion images that allow a meaningful search for the progenitor stars. In five cases they are clearly red supergiants, one case is unconstrained, two fall on compact coeval star clusters and the other twelve have no progenitor detected. We review and update all the available data for the host galaxies (distance, metallicity and extinction) and determine masses and upper mass estimates using the STARS stellar evolutionary code and a single consistent homogeneous method. A maximum likelihood calculation suggests that the minimum stellar mass for a type II-P to form is m(min)=8.5 +1/-1.5 Msol and the maximum mass for II-P progenitors is m(max)=16.5 +/- 1.5 Msol, assuming a Salpeter initial mass function (in the range Gamma = -1.35 +0.3/-0.7). The minimum mass is consistent with current estimates for white dwarf progenitor masses, but the maximum mass does not appear consistent with massive star populations. Red supergiants in the Local Group have masses up to 25Msol and the minimum mass to produce a Wolf-Rayet star in single star evolution (between solar and LMC metallicity) is similarly 25-30 Msol. We term this discrepancy the "red supergiant problem" and speculate that these stars could have core masses high enough to form black holes and SNe which are too faint to have been detected. Low luminosity SNe with low 56Ni production seem to arise from explosions of low mass progenitors near the mass threshold for core-collapse. (abridged).Comment: 37 pages, 9 figs, accepted for publication in MNRA