Missing Links in Multiple Trade Networks

In this paper we develop a network model of international trade which is able to replicate the concentrated and sparse nature of trade data. Our model extends the preferential attachment (PA) growth model to the case of multiple networks. Countries trade a variety of goods of different complexity. Every country progressively evolves from trading less sophisticated to high-tech goods. The probability to capture more trade opportunities at a given level of complexity and to start trading more complex goods are both proportional to the number of existing trade links. We provide a set of theoretical predictions and simulative results. A calibration exercise shows that our model replicates the same concentration level of world trade as well as the sparsity pattern of the trade matrix. Moreover, we find a lower bound for the share of genuine missing trade links. We also discuss a set of numerical solutions to deal with large multiple networks

Black-Scholes formulae for Asian options in local volatility models

We develop approximate formulae expressed in terms of elementary functions for the density, the price and the Greeks of path dependent options of Asian style, in a general local volatility model. An algorithm for computing higher order approximations is provided. The proof is based on a heat kernel expansion method in the framework of hypoelliptic, not uniformly parabolic, partial differential equations.Asian Options, Degenerate Diffusion Processes, Transition Density Functions, Analytic Approximations, Option Pricing

Preferential attachment in multiple trade networks

In this paper we develop a model for the evolution of multiple networks which is able to replicate the concentrated and sparse nature of world trade data. Our model is an extension of the preferential attachment growth model to the case of multiple networks. Countries trade a variety of goods of different complexity. Every country progressively evolves from trading less sophisticated to high-tech goods. The probabilities of capturing more trade opportunities at a given level of complexity and of starting to trade more complex goods are both proportional to the number of existing trade links. We provide a set of theoretical predictions and simulative results. A calibration exercise shows that our model replicates the same concentration level of world trade as well as the sparsity pattern of the trade matrix. We also discuss a set of numerical solutions to deal with large multiple networks

Black-Scholes formulae for Asian options in local volatility models

We develop approximate formulae expressed in terms of elementary functions for the density, the price and the Greeks of path dependent options of Asian style, in a general local volatility model. An algorithm for computing higher order approximations is provided. The proof is based on a heat kernel expansion method in the framework of hypoelliptic, not uniformly parabolic, partial differential equations

Lactobacilli extracellular vesicles: potential postbiotics to support the vaginal microbiota homeostasis

Background: Lactobacillus species dominate the vaginal microflora performing a first-line defense against vaginal infections. Extracellular vesicles (EVs) released by lactobacilli are considered mediators of their beneficial effects affecting cellular communication, homeostasis, microbial balance, and host immune system pathways. Up to now, very little is known about the role played by Lactobacillus EVs in the vaginal microenvironment, and mechanisms of action remain poorly understood. Results: Here, we hypothesized that EVs can mediate lactobacilli beneficial effects to the host by modulating the vaginal microbiota colonization. We recovered and characterized EVs produced by two vaginal strains, namely Lactobacillus crispatus BC5 and Lactobacillus gasseri BC12. EVs were isolated by ultracentrifugation and physically characterized by Nanoparticle Tracking Analysis (NTA) and Dynamic Light Scattering (DLS). EVs protein and nucleic acids (DNA and RNA) content was also evaluated. We explored the role of EVs on bacterial adhesion and colonization, using a cervical cell line (HeLa) as an in vitro model. Specifically, we evaluated the effect of EVs on the adhesion of both vaginal beneficial lactobacilli and opportunistic pathogens (i.e., Escherichia coli, Staphylococcus aureus, Streptococcus agalactiae, and Enterococcus faecalis). We demonstrated that EVs from L. crispatus BC5 and L. gasseri BC12 significantly enhanced the cellular adhesion of all tested lactobacilli, reaching the maximum stimulation effect on strains belonging to L. crispatus species (335% and 269% of average adhesion, respectively). At the same time, EVs reduced the adhesion of all tested pathogens, being EVs from L. gasseri BC12 the most efficient. Conclusions: Our observations suggest for the first time that EVs released by symbiotic Lactobacillus strains favor healthy vaginal homeostasis by supporting the colonization of beneficial species and preventing pathogens attachment. This study reinforces the concept of EVs as valid postbiotics and opens the perspective of developing postbiotics from vaginal strains to maintain microbiota homeostasis and promote women’s health

Electrical release of dopamine and levodopa mediated by amphiphilic \u3b2-cyclodextrins immobilized on polycrystalline gold

Vesicles of cationic amphiphilic \u3b2-cyclodextrins have been immobilized on polycrystalline gold by exploiting the chemical affinity between their amino groups and Au atoms. The presence of cyclodextrins has been widely investigated by means of AFM, XPS, kelvin probe and electrochemical measurements. This multi-functional coating confers distinct electrochemical features such as pH-dependent behavior and partial/total blocking properties towards electro-active species. The host-guest properties of \u3b2-cyclodextrins have been successfully exploited in order to trap drugs, like dopamine and levodopa. The further release of these drugs was successfully achieved by providing specific electrical stimuli. This proof-of-concept led us to fabricate an electronic device (i.e. an organic transistor) capable of dispensing both dopamine and levodopa in aqueous solution

Whole Genome Sequencing of a Chlamydia trachomatis Strain Responsible for a Case of Rectal Lymphogranuloma Venereum in Italy

Lymphogranuloma venereum (LGV) is a systemic sexually transmitted infection caused by Chlamydia trachomatis serovars L1 to L3. The current LGV cases in Europe are mainly characterized by an anorectal syndrome, spreading within men who have sex with men (MSM). Whole-genome sequencing of LGV strains is crucial to the study of bacterial genomic variants and to improve strategies for contact tracing and prevention. In this study, we described the whole genome of a C. trachomatis strain (LGV/17) responsible for a case of rectal LGV. LGV/17 strain was isolated in 2017 in Bologna (North of Italy) from a HIV-positive MSM, presenting a symptomatic proctitis. After the propagation in LLC-MK2 cells, the strain underwent whole-genome sequencing by means of two platforms. Sequence type was determined using the tool MLST 2.0, whereas the genovariant was characterized by an ompA sequence evaluation. A phylogenetic tree was generated by comparing the LGV/17 sequence with a series of L2 genomes, downloaded from the NCBI website. LGV/17 belonged to sequence type ST44 and to the genovariant L2f. Nine ORFs encoding for polymorphic membrane proteins A-I and eight encoding for glycoproteins Pgp1-8 were detected in the chromosome and in the plasmid, respectively. LGV/17 was closely related to other L2f strains, even in the light of a not-negligible variability. The LGV/17 strain showed a genomic structure similar to reference sequences and was phylogenetically related to isolates from disparate parts of the world, indicative of the long-distance dynamics of transmission

Immune inflammation indicators and ALBI score to predict liver cancer in HCV-patients treated with direct-acting antivirals

Background: Unexpectedly high occurrence or recurrence rate of hepatocellular carcinoma (HCC) has been observed in patients with chronic hepatitis C receiving direct-acting antivirals (DAAs) therapy. Aims: We evaluated the predictive value of albumin-bilirubin (ALBI) score and immune-inflammation indicators to identify the risk of occurrence or recurrence of HCC in patients treated with DAAs in a real life setting. Methods: In this retrospective cohort study, we analysed data from 514 patients with cirrhosis who were prospectively enrolled for treatment with DAAs. We assessed baseline neutrophil to lymphocyte ratio (NLR), systemic immune-inflammation index (SII), platelet to lymphocyte ratio (PLR), aspartate aminotransferase-lymphocyte ratio (ALRI) index and ALBI score. Results: In patients with no history of HCC (N = 416), increased AST, bilirubin, ALRI, and ALBI score, and decreased albumin and platelets were significantly associated with an increased risk of HCC development, at univariate analysis. At multivariate analysis, increase in ALBI grade (p = 0.038, HR: 2.35, 95% CI: 1.05\u20135.25) and decrease in platelets (p = 0.048, HR: 0.92, 95% CI: 0.85\u20131.0) were independently associated with HCC development. In patients with previous HCC (N = 98), adjusting for the time from HCC treatment, increased ALRI (p = 0.008, HR: 1.05, 95% CI: 1.01\u20131.09) was significantly associated with a risk of recurrence. Conclusion: ALBI score, platelet count and ALRI are promising, easy to perform and inexpensive tools for identifying patients with higher risk of HCC after treatment with DAAs

Profile of lenvatinib in the treatment of hepatocellular carcinoma: design, development, potential place in therapy and network meta-analysis of hepatitis B and hepatitis C in all Phase III trials

Purpose: Sorafenib is the only approved drug in first-line treatment for hepatocellular carcinoma. Recently, the Phase III REFLECT trial proved lenvatinib not inferior to sorafenib, potentially establishing a new standard of care in this setting. The study showed that both have similar overall survivals, yet with longer time to progression for lenvatinib. Currently, the selection of one or other is not based on clinical or biological parameters for this reason we performed a network meta-analysis and we also analyzed the REFLECT trial and its implications in the current and future clinical practice. Materials and methods: We performed the meta-analysis according to the Prisma statement recommendations. HR was the measure of association for time to progression and overall survival. The pooled analysis of HR was performed using a random effect model, fixing a 5% error as index of statistical significance. Results: For HBV-positive patients, there was a clear trend in favor of lenvatinib over sorafenib (HR 0.82 95% credible interval [CrI] 0.60\u20131.15). For HCV-positive no differences between lenvatinib and sorafenib were observed (HR 0.91 95% CrI 0.41\u20132.01). The data showed that lenvatinib could be the best drug for HBV-positive patients in 59% of cases compared to only 1% of patients treated with sorafenib. Conclusion: The identification of clinical or biological markers that could predict response or resistance to treatments is needed to guide treatment decision. This network meta-analysis demonstrates that the etiology is a good candidate and this result should be validated in a specific trial.Purpose: Sorafenib is the only approved drug in first-line treatment for hepatocellular carcinoma. Recently, the Phase III REFLECT trial proved lenvatinib not inferior to sorafenib, potentially establishing a new standard of care in this setting. The study showed that both have similar overall survivals, yet with longer time to progression for lenvatinib. Currently, the selection of one or other is not based on clinical or biological parameters for this reason we performed a network meta-analysis and we also analyzed the REFLECT trial and its implications in the current and future clinical practice.Materials and methods: We performed the meta-analysis according to the Prisma statement recommendations. HR was the measure of association for time to progression and overall survival. The pooled analysis of HR was performed using a random effect model, fixing a 5% error as index of statistical significance.Results: For HBV-positive patients, there was a clear trend in favor of lenvatinib over sorafenib (HR 0.82 95% credible interval [CrI] 0.60-1.15). For HCV-positive no differences between lenvatinib and sorafenib were observed (HR 0.91 95% CrI 0.41-2.01). The data showed that lenvatinib could be the best drug for HBV-positive patients in 59% of cases compared to only 1% of patients treated with sorafenib.Conclusion: The identification of clinical or biological markers that could predict response or resistance to treatments is needed to guide treatment decision. This network meta-analysis demonstrates that the etiology is a good candidate and this result should be validated in a specific trial