Adults are more efficient in creating and transmitting novel signalling systems than children

Iterated language learning experiments have shown that meaningful and structured signalling systems emerge when there is pressure for signals to be both learnable and expressive. Yet such experiments have mainly been conducted with adults using language-like signals. Here we explore whether structured signalling systems can also emerge when signalling domains are unfamiliar and when the learners are children with their well-attested cognitive and pragmatic limitations. In Experiment 1, we compared iterated learning of binary auditory sequences denoting small sets of meanings in chains of adults and 5-7-year old children. Signalling systems became more learnable even though iconicity and structure did not emerge despite applying a homonymy filter designed to keep the systems expressive. When the same types of signals were used in referential communication by adult and child dyads in Experiment 2, only the adults, but not the children, were able to negotiate shared iconic and structured signals. Referential communication using their native language by 4-5-year old children in Experiment 3 showed that only interaction with adults, but not with peers resulted in informative expressions. These findings suggest that emergence and transmission of communication systems is unlikely to be driven by children, and point to the importance of cognitive maturity and pragmatic expertise of learners as well as feedback-based scaffolding of communicative effectiveness by experts during language evolution

Introduction: Interrogating harm and abuse: A lifespan approach

At any time any person faces a possibility of suffering harm from another, and the broad criminal justice framework aims to provide a general level of protection from such harms to the whole population. However, possibilities of abuse, exploitation or neglect are conceptualised as more likely for certain people. These include those in intimate partner relationships, or those whose level of dependency on others is greater as a result of life stage or impairment. Specific legal and policy measures aim to address potential harm in such situations, and are proliferating

Personalized prognostic bayesian network for pancreatic cancer : delivering personalized pancreatic cancer management throughout the patient journey

Background and Objectives: The aim of this study is to create the first Personalized Prognostic Bayesian Network for Pancreatic Cancer (PPBN-PC) to provide personalized predictions of 3-year or more survival time post resection. PPBN-PC’s ability to handle the dynamic nature of the care processes, with predictions evolving as more information becomes available, was assessed at the pre and post-operative stage of the patient journey. Materials and Methods: Parent nodes were identified from PubMed survival analysis studies (n=48691) and included: tumour factors, patient factors, tumour markers, inflammatory markers, neoadjuvant therapy, pathology and adjuvant therapy. Variables underwent a two-stage weighting process to summarise both the weight of the evidence against conflicting findings and a normalized weighting process placing each variable’s weighting within the entirety of the existing body of evidence. Priors for the model were calculated using the normalized weight for each variable as the weighted mean of the TNormal distribution for the corresponding parent node. Results: The PPBN-PC was validated against a dataset of 365 patients who presented to a tertiary referral centre with potentially resectable pancreatic cancer. Model performance measured by Area Under the Curve (AUC) ranged from 0.94 (P-value 0.002; 95% CI 0.859-1.000) for 0 missing data points to AUC 0.74 (P-value 0.000; 95% CI 0.660-0.809) accepting more than 4 missing data points in the validation dataset, for accuracy of pre-operative predictions. PPBN-PC performance for prognostic updating based on post-operatively available information ranged from AUC 0.97 (P-value 0.000; 95% CI 0.908-1.000) for 0 missing data points in pre and post-operative validation dataset to AUC 0.75 (P-value 0.000; 95% CI 0.655-0.838) accepting more than 4 missing data points in the pre and up to and including 2 missing data points in the post-operative validation dataset. The latter was the only point at which AUC fell below 0.80. Validated against every other combination of missing pre and post-operative data points PPBN-PC maintained an AUC greater than 0.8 (range 0.97-0.80) with P-value consistently below 0.001. Conclusion: This marks an important step towards achieving the delivery of precision medicine, as the next step will be to incorporated genomic data into the model hence combining genetic, pathology and clinical data, creating a vehicle to deliver personalized precision medicine

Making personalized predictions of poor outcome post resection of pancreatic ductal adenocarcinoma (PDAC) : a prognostic bayesian network with pre- and post-operative application

Background and Objectives: The high-risk field of pancreatic cancer surgery, where surgical benefits are often nullified by early disease reoccurrence, mandates better patient selection for surgical intervention. Existing predictive models are limited in value and scope, relying heavily on post-operative information. The objective of this study was to combine PubMed and patient level data to create and validate a Bayesian Network that can make accurate personalized predictions of poor prognosis (12 months or less) post resection of PDAC preoperatively and perform prognostic updating postoperatively. Materials and Methods: A weighted Bayesian network, based on PubMed post-resection survival analysis studies (n=31,214), was created using AgenaRisk software. Input variables included: inflammatory markers, tumour factors, tumour markers, patient factors and, if applicable, response to neoadjuvant treatment for pre-operative predictions. Prognostic updating was performed by inclusion of post-operative input variables including: pathology and adjuvant therapy. The model was validated against the database of a prospectively maintained tertiary referral centre (n=387). Results: For pre-operative predictions an Area Under the Curve (AUC) of 0.70 (P value: 0.001; 95% CI 0.589-0.801) was achieved accepting up to two missing data points in the pre-operative validation dataset. For prognostic updating an AUC 0.79 (P value: 0.000; 95% CI:0.710-0.870) was achieved when validated against a dataset that had up to 6 missing pre-operative data points but full post-operative data. This dropped to 0.72 (P value: 0.000; 95% CI:0.660-0.788) when the validation dataset had up to 6 missing pre-operative, and up to 3 missing post-operative data points. Conclusion: The Bayesian network presented here demonstrates a predictive performance rivalling existing models. Benefits over existing models include: pre-operative application, application to neoadjuvant and upfront surgery management pathways, and greater generalizability. As patient databases mature globally and our understanding of disease at genomic level deepens so too will the accuracy of predictions of this model with associated benefits at clinical level by supporting better shared decision making. The future application of this work will be to include emerging genomic data and combine this with clinical and pathological data to make personalized predictions of outcome, hence effectively creating a vehicle to deliver precision medicine

Markov decision analysis of neoadjuvant treatment pathway versus surgery first pathway for resectable pancreatic cancer

Background: Surgery first (SF) versus neoadjuvant approach (NAT) to management of potentially resectable pancreatic ductal adenocarcinoma (PDAC) is controversial. This study is unique in utilizing institutional data to offer Markov decision-analysis of overall treatment pathways for resectable PDAC. Methods: An advanced Markov decision analysis model was constructed and populated with data from a retrospective institutional database. Patients presenting with resectable PDAC from 2008-2012 were included in the SF arm. Those presenting with resectable PDAC from 2012-2016 and treated within NAT pathway populated the NAT arm. Model uncertainties were tested with one and two-way deterministic sensitivity analysis and probabilistic Monte Carlo sensitivity analysis set to 1000 cycles with variables altered between highest and lowest observed values. Results: NAT pathway gave an additional 0.58 QALMs (22.43 vs. 21.85 QALMs). Monte Carlo analysis reported indifference between treatment strategies. One-way deterministic sensitivity analysis showed that probability of resection in the SF pathway must be greater than 0.82, or below 0.72 in NAT pathway, and probability of receiving adjuvant therapy above 0.6 to alter pathway superiority. Two-way deterministic sensitivity analysis demonstrated treatment superiority depended on resection rate in each pathway and receiving adjuvant therapy in SF pathway. Markov cohort analysis demonstrated superiority of neoadjuvant pathway (Table). Conclusions: Optimal treatment pathway remains debatable on an intention-to-treat Markov decision analysis. Markov cohort analysis of treatment received demonstrated benefit with NAT pathway

Ruthenium polypyridyl complexes and their modes of interaction with DNA : is there a correlation between these interactions and the antitumor activity of the compounds?

Various interaction modes between a group of six ruthenium polypyridyl complexes and DNA have been studied using a number of spectroscopic techniques. Five mononuclear species were selected with formula [Ru(tpy) L1L2](2-n)?, and one closely related dinuclear cation of formula [{Ru(apy)(tpy)}2{l-H2N(CH2)6NH2}]4?. The ligand tpy is 2,20:60,200-terpyridine and the ligand L1 is a bidentate ligand, namely, apy (2,20-azobispyridine), 2-phenylazopyridine, or 2-phenylpyridinylmethylene amine. The ligand L2 is a labile monodentate ligand, being Cl-, H2O, or CH3CN. All six species containing a labile L2 were found to be able to coordinate to the DNA model base 9-ethylguanine by 1H NMR and mass spectrometry. The dinuclear cationic species, which has no positions available for coordination to a DNA base, was studied for comparison purposes. The interactions between a selection of four representative complexes and calf-thymus DNA were studied by circular and linear dichroism. To explore a possible relation between DNA-binding ability and toxicity, all compounds were screened for anticancer activity in a variety of cancer cell lines, showing in some cases an activity which is comparable to that of cisplatin. Comparison of the details of the compound structures, their DNA binding, and their toxicity allows the exploration of structure–activity relationships that might be used to guide optimization of the activity of agents of this class of compounds

Timing and conditions of peak metamorphism and cooling across the Zimithang Thrust, Arunachal Pradesh, India

The Zimithang Thrust juxtaposes two lithotectonic units of the Greater Himalayan Sequence in Arunachal Pradesh, NE India. Monazite U–Pb, muscovite 40Ar/39Ar and thermobarometric data from rocks in the hanging and footwall constrain the timing and conditions of their juxtaposition across the structure, and their subsequent cooling. Monazite grains in biotite–sillimanite gneiss in the hanging wall yield LA-ICP-MS U–Pb ages of 16 ± 0.2 to 12.7 ± 0.4 Ma. A schistose gneiss within the high strain zone yields overlapping-to-younger monazite ages of 14.9 ± 0.3 to 11.5 ± 0.3 Ma. Garnet–staurolite–mica schists in the immediate footwall yield older monazite ages of 27.3 ± 0.6 to 17.1 ± 0.2 Ma. Temperature estimates from Ti-in-biotite and garnet–biotite thermometry suggest similar peak temperatures were achieved in the hanging and footwalls (~ 525–650 °C). Elevated temperatures of ~ 700 °C appear to have been reached in the high strain zone itself and in the footwall further from the thrust. Single grain fusion 40Ar/39Ar muscovite data from samples either side of the thrust yield ages of ~ 7 Ma, suggesting that movement along the thrust juxtaposed the two units by the time the closure temperature of Ar diffusion in muscovite had been reached. These data confirm previous suggestions that major orogen-parallel out-of-sequence structures disrupt the Greater Himalayan Sequence at different times during Himalayan evolution, and highlight an eastwards-younging trend in 40Ar/39Ar muscovite cooling ages at equivalent structural levels along Himalayan strike

Antivirals Reduce the Formation of Key Alzheimer's Disease Molecules in Cell Cultures Acutely Infected with Herpes Simplex Virus Type 1

Alzheimer's disease (AD) afflicts around 20 million people worldwide and so there is an urgent need for effective treatment. Our research showing that herpes simplex virus type 1 (HSV1) is a risk factor for AD for the brains of people who possess a specific genetic factor and that the virus causes accumulation of key AD proteins (β-amyloid (Aβ) and abnormally phosphorylated tau (P-tau)), suggests that anti-HSV1 antiviral agents might slow AD progression. However, currently available antiviral agents target HSV1 DNA replication and so might be successful in AD only if Aβ and P-tau accumulation depend on viral DNA replication. Therefore, we investigated firstly the stage(s) of the virus replication cycle required for Aβ and P-tau accumulation, and secondly whether antiviral agents prevent these changes using recombinant strains of HSV1 that progress only partly through the replication cycle and antiviral agents that inhibit HSV1 DNA replication. By quantitative immunocytochemistry we demonstrated that entry, fusion and uncoating of HSV1, are insufficient to induce Aβ and P-tau production. We showed also that none of the “immediate early” viral proteins is directly responsible, and that Aβ and P-tau are produced at a subsequent stage of the HSV1 replication cycle. Importantly, the anti-HSV1 antiviral agents acyclovir, penciclovir and foscarnet reduced Aβ and P-tau accumulation, as well as HSV1, with foscarnet being less effective in each case. P-tau accumulation was found to depend on HSV1 DNA replication, whereas Aβ accumulation was not. The antiviral-induced decrease in Aβ is attributable to the reduced number of new viruses, and hence the reduction in viral spread. Since antiviral agents reduce greatly Aβ and P-tau accumulation in HSV1-infected cells, they would be suitable for treating AD with great advantage unlike current AD therapies, only the virus, not the host cell, would be targeted