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Marine protected areas (MPAs) represent an example of nature-based solutions for the conservation and sustainable management of marine biodiversity. Despite the number of MPAs growing worldwide, many of them fail to achieve their goals, sometimes up to the point of becoming the so-called “paper parks”: protected areas without real protection or enforcement that are virtually non-existent in terms of their effectiveness in achieving the ecological and socioeconomic goals for which they have been set up. Following the Kunming–Montreal Biodiversity Agreement (COP 15), the EU Biodiversity Strategy for 2030, and the Biodiversity Beyond National Jurisdiction treaty, global MPA coverage should increase substantially in the coming years. Hence, identifying the factors that contribute to raising the effectiveness of MPAs is pivotal to informing their planning and management. Our study introduces a model based on the Bayesian network that allows testing how different socioeconomic factors (e.g., stakeholder involvement, increased communication and enforcement) can impact the effectiveness of MPAs. The system is a user-friendly decision-support tool to quantify the contribution of each factor in the creation of a successful MPA, thus narrowing the gap between science and decision-making. We modelled the evolution of the effectiveness of MPAs under three contrasting policy-relevant scenarios based on the Intergovernmental Panel on Climate Change frameworks. Our results indicate that the highest and lowest the effectiveness of MPAs is achieved under the “global sustainability” and “national enterprise” scenarios, respectively. Our work sheds light on the complexity of the interactions among the different factors underpinning the effectiveness of MPAs and supports the growth process of MPAs at the global level on the pathway towards the sustainable exploitation of marine living resources.

Abstract The aim of this study was to evaluate the antimicrobial efficacy of an air gas soft jet CAP for its potential use in removing oral biofilms, given that plasma-based technologies have emerged as promising methods in periodontology. Two types of biofilms were developed, one by Streptococcus mutans UA 159 bacterial strain and the other by a complex mixture of saliva microorganisms isolated from a patient with periodontitis. This latter biofilm was characterized via Next Generation Sequencing to determine the main bacterial phyla. The CAP source was applied at a distance of 6 mm for different time points. A statistically significant reduction of both CFU count and XTT was already detected after 60 s of CAP treatment. CLSM analysis supported CAP effectiveness in killing the microorganisms inside the biofilm and in reducing the thickness of the biofilm matrix. Cytotoxicity tests demonstrated the possible use of CAP without important side effects towards human gingival fibroblasts cell line. The current study showed that CAP treatment was able to significantly reduce preformed biofilms developed by both S. mutans and microorganisms isolated by a saliva sample. Further studies should be conducted on biofilms developed by additional saliva donors to support the potential of this innovative strategy to counteract oral pathogens responsible for periodontal diseases.

Abstract Recent technological advancements have facilitated the extensive collection of movement data from large-scale fishing vessels, yet a significant data gap remains for small-scale fisheries. This gap hinders the development of consistent exploitation patterns and meeting the information needs for marine spatial planning in fisheries management. This challenge is specifically addressed in the Campania region of Italy, where several Marine Protected Areas support biodiversity conservation and fisheries management. The authors have created a spatially-explicit dataset that encompasses both large-scale (vessels exceeding 12 meters in length) and small-scale (below 12 meters) fishing efforts. This dataset (available at https://doi.org/10.6084/m9.figshare.23592006 ) is derived from vessel tracking data and participatory mapping. It offers insights into potential conflicts between different fishing segments and their interactions with priority species and habitats. The data can assist researchers and coastal management stakeholders in formulating policies that reduce resource competition and promote ecosystem-based fisheries management. Furthermore, the provided mapping approach is adaptable for other regions and decision-making frameworks, as we are committed to sharing the tools and techniques we employed.

Abstract Background Glioma grade 4 (GG4) tumors, including astrocytoma IDH-mutant grade 4 and the astrocytoma IDH wt are the most common and aggressive primary tumors of the central nervous system. Surgery followed by Stupp protocol still remains the first-line treatment in GG4 tumors. Although Stupp combination can prolong survival, prognosis of treated adult patients with GG4 still remains unfavorable. The introduction of innovative multi-parametric prognostic models may allow refinement of prognosis of these patients. Here, Machine Learning (ML) was applied to investigate the contribution in predicting overall survival (OS) of different available data (e.g. clinical data, radiological data, or panel-based sequencing data such as presence of somatic mutations and amplification) in a mono-institutional GG4 cohort. Methods By next-generation sequencing, using a panel of 523 genes, we performed analysis of copy number variations and of types and distribution of nonsynonymous mutations in 102 cases including 39 carmustine wafer (CW) treated cases. We also calculated tumor mutational burden (TMB). ML was applied using eXtreme Gradient Boosting for survival (XGBoost-Surv) to integrate clinical and radiological information with genomic data. Results By ML modeling (concordance (c)- index = 0.682 for the best model), the role of predicting OS of radiological parameters including extent of resection, preoperative volume and residual volume was confirmed. An association between CW application and longer OS was also showed. Regarding gene mutations, a role in predicting OS was defined for mutations of BRAF and of other genes involved in the PI3K-AKT-mTOR signaling pathway. Moreover, an association between high TMB and shorter OS was suggested. Consistently, when a cutoff of 1.7 mutations/megabase was applied, cases with higher TMB showed significantly shorter OS than cases with lower TMB. Conclusions The contribution of tumor volumetric data, somatic gene mutations and TBM in predicting OS of GG4 patients was defined by ML modeling.

Abstract Introduction Recent evidence confirms that the treatment of acute appendicitis is not necessarily surgical, and selected patients with uncomplicated appendicitis can benefit from a non-operative management. Unfortunately, no cost-effective test has been proven to be able to effectively predict the degree of appendicular inflammation as yet, therefore, patient selection is too often left to the personal choice of the emergency surgeon. Our paper aims to clarify if basic and readily available blood tests can give reliable prognostic information to build up predictive models to help the decision-making process. Methods Clinical notes of 2275 patients who underwent an appendicectomy with a presumptive diagnosis of acute appendicitis were reviewed, taking into consideration basic preoperative blood tests and histology reports on the surgical specimens. Variables were compared with univariate and multivariate analysis, and predictive models were created. Results 18.2% of patients had a negative appendicectomy, 9.6% had mucosal only inflammation, 53% had transmural inflammation and 19.2% had gangrenous appendicitis. A strong correlation was found between degree of inflammation and lymphocytes count and CRP/Albumin ratio, both at univariate and multivariate analysis. A predictive model to identify cases of gangrenous appendicitis was developed. Conclusion Low lymphocyte count and high CRP/Albumin ratio combined into a predictive model may have a role in the selection of patients who deserve appendicectomy instead of non-operative management of acute appendicitis.

Abstract Background Parathyroid hormone-related peptide (PTHrP) overexpression and poor patient outcome have been reported for many human tumors, but no studies are available in laryngeal cancer. Therefore, we studied the expression of PTHrP and its receptor, parathyroid hormone-related peptide receptor type 1 (PTH1R), in primary locally advanced laryngeal squamous cell carcinomas (LALSCC) also in relation to the clinical outcome of patients. Methods We conducted a retrospective exploratory study, using immunohistochemistry, on PTHrP, PTH1R and HER1 expressions in LALSCC of 66 patients treated with bio-radiotherapy with cetuximab. Results The expressions of PTHrP and PTH1R in LALSCC were associated with the degree of tumor differentiation (p = 0.01 and 0.04, respectively). Poorly differentiated tumors, with worse prognosis, expressed PTHrP at nuclear level and were PTH1R negative. PTHrP and PTH1R were expressed at cytoplasmic level in normal larynx epithelium and more differentiated laryngeal cancer cells, suggesting an autocrine/paracrine role of PTHrP in squamous cell differentiation of well differentiated tumors with good prognosis. Eighty-one percent HER1 positive tumors expressed PTHrP (p

Objective:. To evaluate the influence of enhanced recovery pathway (ERP) on patient-reported outcome measures (PROMs) and return to intended oncologic therapy (RIOT) after colorectal surgery. Background:. ERP improves early outcomes after colorectal surgery; however, little is known about its influence on PROMs and on RIOT. Methods:. Prospective multicenter enrollment of patients who underwent colorectal resection with anastomosis was performed, recording variables related to patient-, institution-, procedure-level data, adherence to the ERP, and outcomes. The primary endpoints were PROMs (administered before surgery, at discharge, and 6 to 8 weeks after surgery) and RIOT after surgery for malignancy, defined as the intended oncologic treatment according to national guidelines and disease stage, administered within 8 weeks from the index operation, evaluated through multivariate regression models. Results:. The study included 4529 patients, analyzed for PROMs, 1467 of which were analyzed for RIOT. Compared to their baseline preoperative values, all PROMs showed significant worsening at discharge and improvement at late evaluation. PROMs values at discharge and 6 to 8 weeks after surgery, adjusted through a generalized mixed regression model according to preoperative status and other variables, showed no association with ERP adherence rates. RIOT rates (overall 54.5%) were independently lower by aged > 69 years, ASA Class III, open surgery, and presence of major morbidity; conversely, they were independently higher after surgery performed in an institutional ERP center and by ERP adherence rates > median (69.2%). Conclusions:. Adherence to the ERP had no effect on PROMs, whereas it independently influenced RIOT rates after surgery for colorectal cancer.

Ultradiffuse galaxies (UDGs) are attractive candidates to probe cosmological models and test theories of galaxy formation at low masses; however, they are difficult to detect because of their low surface brightness. In the Local Group a handful of UDGs have been found to date, most of which are satellites of the Milky Way and M31, and only two are isolated galaxies. It is unclear whether so few UDGs are expected. We address this by studying the population of UDGs formed in hydrodynamic constrained simulations of the Local Group from the HESTIA suite. For a Local Group with a total enclosed mass M _LG ( < 2.5 Mpc) = 8 × 10 ^12 M _⊙ , we predict that there are 12 ± 3 isolated UDGs (68% confidence) with stellar masses 10 ^6 ≤ M _* /M _⊙ < 10 ^9 , and effective radii R _e ≥ 1.5 kpc, within 2.5 Mpc of the Local Group, of which ${2}_{-1}^{+2}$ (68% confidence) are detectable in the footprint of the Sloan Digital Sky Survey (SDSS). Accounting for survey incompleteness, we find that almost the entire population of UDGs in the Local Group field would be observable in a future all-sky survey with a depth similar to the SDSS, the Dark Energy Survey, or the Legacy Survey of Space and Time. Our results suggest that there is a population of UDGs in the Local Group awaiting discovery.

Abstract Background Compared to the other members of human epidermal growth factor family receptors (HER), the role of HER3 has not been well defined in laryngeal cancer. The predictive and prognostic role of HER3 has been the focus of clinical attention but the research findings are contradictory, especially in laryngeal squamous cell carcinoma (LSCC). The variable localization of HER3 within cancer cells and the role of HER3 in primary and acquired resistance to HER1-targeted therapies remain unclear. Methods We performed a retrospective analysis of two cohorts of 66 homogeneous consecutive untreated primary advanced LSCC patients, in which co-expression of HER1, HER2 and HER3 receptors was investigated by semi-quantitative immunohistochemistry. The association of their pattern of expression with survival was evaluated by Kaplan–Meier and Cox’s proportional hazard analyses. Multivariable Cox proportional hazards models were developed to predict median 2- and 3-year RFS and 2.5- and 5-year OS. The Akaike information criterion technique and backwards stepwise procedure were used for model selections. The performance of the final Cox models was assessed with respect to calibration and discrimination. Results Immunohistochemical labeling for HER1 and HER2 was localized both in the cell membrane and in the cytoplasm, while HER3 labeling was observed both in the cell cytoplasm and in the nucleus. HER3 expression was inversely correlated with HER1 positivity. The expression patterns of HERs were associated with tumor differentiation. In both cohorts of patients, HER1 expression was associated with reduced relapse-free (RFS) and overall survival (OS). In HER1 positive tumors, the co-expression with nuclear HER3 was associated with better RFS and OS, compared with HER3 negative tumors or tumors expressing HER3 at cytoplasmic level. HER3 expressing tumors had a higher Geminin/MCM7 ratio than HER3 negative ones, regardless of HER1 co-expression. Multivariable analyses identified age at diagnosis, tumor site, HER1, HER3 and age at diagnosis, tumor stage, HER1, HER3, as covariates significantly associated with RFS and OS, respectively. Bootstrapping verified the good fitness of these models for predicting survivals and the optimism-corrected C-indices were 0.76 and 0.77 for RFS and OS, respectively. Conclusions Nuclear HER3 expression was strongly associated with favourable prognosis and allows to improve the prognostic stratification of patients with HER1 positive advanced LSCC carcinoma.

Glioblastoma (GBM) is the most frequent and aggressive primary central nervous system tumor. Surgery followed by radiotherapy and chemotherapy with alkylating agents constitutes standard first-line treatment of GBM. Complete resection of the GBM tumors is generally not possible given its high invasive features. Although this combination therapy can prolong survival, the prognosis is still poor due to several factors including chemoresistance. In recent years, a comprehensive characterization of the GBM-associated molecular signature has been performed. This has allowed the possibility to introduce a more personalized therapeutic approach for GBM, in which novel targeted therapies, including those employing tyrosine kinase inhibitors (TKIs), could be employed. The GBM tumor microenvironment (TME) exerts a key role in GBM tumor progression, in particular by providing an immunosuppressive state with low numbers of tumor-infiltrating lymphocytes (TILs) and other immune effector cell types that contributes to tumor proliferation and growth. The use of immune checkpoint inhibitors (ICIs) has been successfully introduced in numerous advanced cancers as well as promising results have been shown for the use of these antibodies in untreated brain metastases from melanoma and from non-small cell lung carcinoma (NSCLC). Consequently, the use of PD-1/PD-L1 inhibitors has also been proposed in several clinical trials for the treatment of GBM. In the present review, we will outline the main GBM molecular and TME aspects providing also the grounds for novel targeted therapies and immunotherapies using ICIs for GBM.

Lo studio della proteomica salivare, test economico e non invasivo, rappresenta una fonte di numerose informazioni, ed è utile per la diagnosi di svariate malattie. Da quando siamo entrati nellera della tecnologia genomica e delle scienze omiche, la raccolta di campioni salivari è aumentata esponenzialmente. Recenti piattaforme proteomiche hanno analizzato il proteoma salivare umano, caratterizzando circa 3000 peptidi e proteine, espressi in maniera differente: più del 90% in peso deriva dalla secrezione delle tre ghiandole salivari maggiori, mentre la restante parte proviene dalle ghiandole salivari minori, dal fluido crevicolare gengivale, da essudati mucosi e dalla microflora orale. Lobiettivo principale dellanalisi proteomica è discriminare tra condizioni fisiologiche e patologiche. Ad oggi, tuttavia, non esiste un preciso protocollo che permetta di analizzare lintero proteoma salivare, pertanto sono state realizzate svariate strategie. Innanzitutto, è possibile distinguere due tipologie di piattaforme proteomiche: lapproccio top-down prevede lanalisi delle proteine sotto esame come entità intatte; nellapproccio bottom-up la caratterizzazione della proteina avviene mediante lo studio dei peptidi ottenuti dopo digestione enzimatica (con tripsina tipicamente). A causa di questa eterogeneità, per una stessa patologia sono stati proposti differenti biomarkers. Il proteoma salivare è stato caratterizzato in numerose malattie: carcinoma squamoso e leucoplachie orali, malattia del trapianto contro lospite (GVHD) cronica, sindrome di Sjögren e altri disordini autoimmuni come la sindrome SAPHO (sinovite, acne, pustolosi, iperostosi e osteite), schizofrenia e disordine bipolare, malattie genetiche come la sindrome di Down o la malattia di Wilson. In conclusione, i risultati delle ricerche riportate in questa review suggeriscono che nel prossimo futuro la saliva diverrà un fluido di indubbia rilevanza diagnostica utile per fini clinici, sia diagnostici, sia prognostici.

We study the nonequilibrium steady states of a one-dimensional fluid in a finite-space region of length L. Particles interact among themselves by multi-particle collisions and are in contact with two thermal-wall heat reservoirs, located at the boundaries of the region. After an initial ballistic regime, we find a crossover from a normal (kinetic) transport regime to an anomalous (hydrodynamic) one, above a characteristic size L_{*}. We argue that L_{*} is proportional to the cube of the collision time among particles. Motivated by the physics of emissive divertors in fusion plasma, we consider the more general case of thermal walls injecting particles with given average (nonthermal) velocity. For fast and relatively cold particles, short systems fail to establish local equilibrium and display non-Maxwellian distributions of velocities.

Gliomas are the most common primary neoplasm of the central nervous system. A promising frontier in the definition of glioma prognosis and treatment is represented by epigenetics. Furthermore, in this study, we developed a machine learning classification model based on epigenetic data (CpG probes) to separate patients according to their state of immunosuppression. We considered 573 cases of low-grade glioma (LGG) and glioblastoma (GBM) from The Cancer Genome Atlas (TCGA). First, from gene expression data, we derived a novel binary indicator to flag patients with a favorable immune state. Then, based on previous studies, we selected the genes related to the immune state of tumor microenvironment. After, we improved the selection with a data-driven procedure, based on Boruta. Finally, we tuned, trained, and evaluated both random forest and neural network classifiers on the resulting dataset. We found that a multi-layer perceptron network fed by the 338 probes selected by applying both expert choice and Boruta results in the best performance, achieving an out-of-sample accuracy of 82.8%, a Matthews correlation coefficient of 0.657, and an area under the ROC curve of 0.9. Based on the proposed model, we provided a method to stratify glioma patients according to their epigenomic state.

Laura, vinte e seis anos, chega a nossa observação em junho de 2009 em seguida a uma descompensação psicótica devido a uma soma de cocaína e corticóides. Revelar-se-á afetada por um distúrbio do humor com personalidade borderline. Depois do enquadramento psicopatológico Laura é tratada em um hospital dia de orientação fenomenológica. Conseguiu, neste período, atingir a compensação da sintomatologia psicótica, uma maior lucidez e crítica na relação com a realidade, lidando ao mesmo tempo com as vicissitudes ligadas ao retorno em cena da substância.

Abstract Introduction Hydatid disease is a helminthic anthropozoonosis with worldwide distribution due to the close associations among sheep, dogs, and humans. It can occur almost anywhere in the body with a variety of imaging features, which may change according to the growth stage, associated complications, and affected tissues. A definitive diagnosis requires a combination of imaging, serologic and immunologic studies. Ultrasonography, computed tomography and magnetic resonance imaging are highly accurate in detecting a hepatic hydatid cyst. However, hepatic hydatid cysts in an unusual location and/or of an unusual dimension, with atypical imaging findings, may complicate the differential diagnosis. Surgical treatment remains the best treatment. Case presentation We describe an unusual case of a giant hydatid cyst, with exophytic growth from the right lobe of the liver of a 55-year-old Egyptian man. The cyst was strongly adhered to his ipsilateral kidney, which was displaced in a downwards and anterior direction, close to his abdominal wall, simulating a retroperitoneal origin. This atypical growth raised doubts about the most appropriate surgical approach. Magnetic resonance imaging easily clarified the origin of the cyst as our patient’s liver, allowing accurate surgical planning. Conclusion Rarely, hydatid cysts can reach an extremely large size without any additional symptoms. Giant cysts need radical therapy because they might lead to perforation and anaphylaxis in some patients. Magnetic resonance imaging is very useful in the study of hydatid disease because of its capacity to allow a large field of view, multiplanar acquisition, and high contrast resolution. In some unusual hepatic presentations, magnetic resonance imaging can be used to determine the correct anatomical relationships.