Subtyping patients with heroin addiction at treatment entry: factor derived from the Self-Report Symptom Inventory (SCL-90)

<p>Abstract</p> <p>Background</p> <p>Addiction is a relapsing chronic condition in which psychiatric phenomena play a crucial role. Psychopathological symptoms in patients with heroin addiction are generally considered to be part of the drug addict's personality, or else to be related to the presence of psychiatric comorbidity, raising doubts about whether patients with long-term abuse of opioids actually possess specific psychopathological dimensions.</p> <p>Methods</p> <p>Using the Self-Report Symptom Inventory (SCL-90), we studied the psychopathological dimensions of 1,055 patients with heroin addiction (884 males and 171 females) aged between 16 and 59 years at the beginning of treatment, and their relationship to age, sex and duration of dependence.</p> <p>Results</p> <p>A total of 150 (14.2%) patients with heroin addiction showed depressive symptomatology characterised by feelings of worthlessness and being trapped or caught; 257 (24.4%) had somatisation symptoms, 205 (19.4%) interpersonal sensitivity and psychotic symptoms, 235 (22.3%) panic symptomatology, 208 (19.7%) violence and self-aggression. These dimensions were not correlated with sex or duration of dependence. Younger patients with heroin addiction were characterised by higher scores for violence-suicide, sensitivity and panic anxiety symptomatology. Older patients with heroin addiction showed higher scores for somatisation and worthlessness-being trapped symptomatology.</p> <p>Conclusions</p> <p>This study supports the hypothesis that mood, anxiety and impulse-control dysregulation are the core of the clinical phenomenology of addiction and should be incorporated into its nosology.</p

Comparison of the Full Outline of UnResponsiveness and Glasgow Liege Scale/Glasgow Coma Scale in an Intensive Care Unit Population.

peer reviewedBACKGROUND: The Full Outline of UnResponsiveness (FOUR) has been proposed as an alternative for the Glasgow Coma Scale (GCS)/Glasgow Liege Scale (GLS) in the evaluation of consciousness in severely brain-damaged patients. We compared the FOUR and GLS/GCS in intensive care unit patients who were admitted in a comatose state. METHODS: FOUR and GLS evaluations were performed in randomized order in 176 acutely (<1 month) brain-damaged patients. GLS scores were transformed in GCS scores by removing the GLS brainstem component. Inter-rater agreement was assessed in 20% of the studied population (N = 35). A logistic regression analysis adjusted for age, and etiology was performed to assess the link between the studied scores and the outcome 3 months after injury (N = 136). RESULTS: GLS/GCS verbal component was scored 1 in 146 patients, among these 131 were intubated. We found that the inter-rater reliability was good for the FOUR score, the GLS/GCS. FOUR, GLS/GCS total scores predicted functional outcome with and without adjustment for age and etiology. 71 patients were considered as being in a vegetative/unresponsive state based on the GLS/GCS. The FOUR score identified 8 of these 71 patients as being minimally conscious given that these patients showed visual pursuit. CONCLUSIONS: The FOUR score is a valid tool with good inter-rater reliability that is comparable to the GLS/GCS in predicting outcome. It offers the advantage to be performable in intubated patients and to identify non-verbal signs of consciousness by assessing visual pursuit, and hence minimal signs of consciousness (11% in this study), not assessed by GLS/GCS scales

Use of ecstasy and other psychoactive substances among school-attending adolescents in Taiwan: national surveys 2004–2006

<p>Abstract</p> <p>Background</p> <p>With the backdrop of a global ecstasy epidemic, this study sought to examine the trend, correlates, and onset sequence of ecstasy use among adolescents in Taiwan, where a well-established gateway drug such as marijuana is much less popular.</p> <p>Methods</p> <p>A multistage probability survey of school-attending adolescents in grades 7, 9, 10, and 12, aged 11–19 years, was conducted in 2004, 2005, and 2006. A self-administered anonymous questionnaire elicited response rates ranging from 94.3% to 96.6%. The sample sizes were 18232 respondents in 2004, 17986 in 2005, and 17864 in 2006.</p> <p>Results</p> <p>In terms of lifetime prevalence and incidence, ecstasy and ketamine by and large appeared as the first and second commonly used illegal drugs, respectively, among middle (grades 7 and 9) and high school students (grades 10 and 12) during the 3-year survey period; however, this order was reversed in the middle school-aged students starting in 2006. Having sexual experience, tobacco use, and betel nut use were factors consistently associated with the onset of ecstasy use across years. The majority of ecstasy users had been involved in polydrug use, such as the use of ketamine (41.4%–53.5%), marijuana (12.7%–18.7%), and methamphetamine (4.2%–9.5%).</p> <p>Conclusion</p> <p>From 2004 to 2006, a decline was noted in the prevalence and incidence rate of ecstasy, a leading illegal drug used by school-attending adolescents in Taiwan since the early 2000s. The emerging ketamine use trend may warrant more attention in the future.</p

Review on catalytic cleavage of C-C inter-unit linkages in lignin model compounds: Towards lignin depolymerisation

Lignin depolymerisation has received considerable attention recently due to the pressing need to find sustainable alternatives to fossil fuel feedstock to produce chemicals and fuels. Two types of interunit linkages (C–C and C–O linkages) link several aromatic units in the structure of lignin. Between these two inter-unit linkages, the bond energies of C–C linkages are higher than that of C–O linkages, making them harder to break. However, for an efficient lignin depolymerisation, both types of inter-unit linkages have to be broken. This is more relevant because of the fact that many delignification processes tend to result in the formation of additional C–C inter-unit bonds. Here we review the strategies reported for the cleavage of C–C inter-unit linkages in lignin model compounds and lignin. Although a number of articles are available on the cleavage of C–O inter-unit linkages, reports on the selective cleavage of C–C inter-unit linkages are relatively less. Oxidative cleavage, hydrogenolysis, two-step redox-neutral process, microwave assisted cleavage, biocatalytic and photocatalytic methods have been reported for the breaking of C–C inter-unit linkages in lignin. Here we review all these methods in detail, focused only on the breaking of C–C linkages. The objective of this review is to motivate researchers to design new strategies to break this strong C–C inter-unit bonds to valorise lignins, technical lignins in particular

Nucleation and crystallization in bio-based immiscible polyester blends

Bio-based thermoplastic polyesters are highly promising materials as they combine interesting thermal and physical properties and in many cases biodegradability. However, sometimes the best property balance can only be achieved by blending in order to improve barrier properties, biodegradability or mechanical properties. Nucleation, crystallization and morphology are key factors that can dominate all these properties in crystallizable biobased polyesters. Therefore, their understanding, prediction and tailoring is essential. In this work, after a brief introduction about immiscible polymer blends, we summarize the crystallization behavior of the most important bio-based (and immiscible) polyester blends, considering examples of double-crystalline components. Even though in some specific blends (e.g., polylactide/polycaprolactone) many efforts have been made to understand the influence of blending on the nucleation, crystallization and morphology of the parent components, there are still many points that have yet to be understood. In the case of other immiscible polyester blends systems, the literature is scarce, opening up opportunities in this environmentally important research topic.The authors would like to acknowledge funding by the BIODEST project ((RISE) H2020-MSCA-RISE-2017-778092

ICAR: endoscopic skull‐base surgery

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Comprehensive molecular characterization of the hippo signaling pathway in cancer

Hippo signaling has been recognized as a key tumor suppressor pathway. Here, we perform a comprehensive molecular characterization of 19 Hippo core genes in 9,125 tumor samples across 33 cancer types using multidimensional “omic” data from The Cancer Genome Atlas. We identify somatic drivers among Hippo genes and the related microRNA (miRNA) regulators, and using functional genomic approaches, we experimentally characterize YAP and TAZ mutation effects and miR-590 and miR-200a regulation for TAZ. Hippo pathway activity is best characterized by a YAP/TAZ transcriptional target signature of 22 genes, which shows robust prognostic power across cancer types. Our elastic-net integrated modeling further reveals cancer-type-specific pathway regulators and associated cancer drivers. Our results highlight the importance of Hippo signaling in squamous cell cancers, characterized by frequent amplification of YAP/TAZ, high expression heterogeneity, and significant prognostic patterns. This study represents a systems-biology approach to characterizing key cancer signaling pathways in the post-genomic era

Spatial prediction of rainfall-induced landslides for the Lao Cai area (Vietnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization

© 2016, Springer-Verlag Berlin Heidelberg. The main objective of this study is to produce a landslide susceptibility map for the Lao Cai area (Vietnam) using a new hybrid intelligent method based on least squares support vector machines (LSSVM) and artificial bee colony (ABC) optimization, namely LSSVM-BC. LSSVM and ABC are state-of-the-art soft computing techniques that have been rarely utilized in landslide susceptibility assessment. LSSVM is adopted to develop landslide prediction model whereas ABC was used to optimize the prediction model by identifying an appropriate set of the LSSVM hyper-parameters. To establish the hybrid intelligent method, a GIS database with ten landslide-influencing factors and 340 landslide locations that occurred mainly during the last 20-years was constructed. These historical landslide locations were collected from the existing inventories that sourced from (i) five landslide projects carried out in this study areas before and (ii) interpretations of SPOT satellite images with resolution of 2.5 m. The study area was geographically split into two different parts, with landslides located in the first part was used for building models whereas the other landslides in the second part was used for the model validation. Performance of the LSSVM-BC model was assessed using the receiver operating characteristic (ROC) curve and area under the curve (AUC). Result shows that the prediction power of the model is good with the area under the curve (AUC) = 0.900. Experiments have pointed out the prediction power of the LSSVM-BC is better than that obtained from the popular support vector machines. Therefore, the proposed model is a promising tool for spatial prediction of landslides at the study area. The landslide susceptibility map is useful for landuse planning for the Lao Cai area