Delirium during ICU stay is a widespread problem with complex aetiology. A premorbid psychiatric disorder has been associated with an increased incidence of delirium in the general hospital population, but data on the impact of ICU delirium and consequences for morbidity and long-term mortality remain scarce.  In this single-centre retrospective analysis, 472 patients with an ICU stay >48 hours were included during a 2-year period. Postresuscitation and neurosurgical patients were not included. The primary aim of the study was to establish the incidence and duration of delirium during ICU stay in patients with (PS group) and without (NPS group) a premorbid psychiatric disorder. Data were analysed with applicable nonparametric tests. In a secondary analysis, patients were compared according to the presence or absence of delirium. Finally, a binary logistic regression model was constructed to correct for potential confounders. p=0.13). In a univariate analysis, the presence of a psychiatric history was also associated with prolonged mechanical ventilation, length of stay ICU, and hospital stay, but not with long-term all-cause mortality. The presence of delirium at any time during ICU admission was significantly associated with prolonged mechanical ventilation and prolonged ICU and hospital stay, but not with mortality. In a Kaplan–Meier analysis, 5-year all-cause mortality was clearly separated between groups, but the difference remained statistically insignificant . In a binary logistic regression model, age, male sex, APACHE III score, and premorbid psychiatric disorder  were all independently associated with the presence of delirium.  Of all patients, 19.7% were included in the PS group. Baseline characteristics with respect to severity of illness and type of admission did not differ between groups, but PS patients were significantly younger and more often female in comparison with NPS patients. The overall incidence of delirium during ICU was 57% and did not significantly differ between groups (65% in PS group vs. 56% in the NPS group,  In ICU patients with a length of stay >48 hours and a premorbid psychiatric disorder, the incidence of delirium was not significantly higher in comparison with patients without a premorbid psychiatric disorder. Nowadays, delirium is considered a widespread problem in intensive care patients all around the globe. The incidence of ICU-acquired delirium is substantial and varies within specific subgroups, with the highest reported incidence up to 80% in mechanically ventilated patients , 2. The This retrospective single-centre study was performed in a closed-format 20-bed mixed ICU in a tertiary teaching hospital, where all patient categories are treated except for neurosurgical patients. All patients ≥18 years with an ICU stay of >48 hours during the period 2012-2013 were included in the study. Patients admitted after cardiac arrest were excluded, since we considered postanoxic encephalopathy a different entity and hard to differentiate from delirium in the clinical setting. The study was performed in accordance with the Declaration of Helsinki, and anonymised data were used for analysis. According to applicable laws, the need for individual consent was waived by the local ethics committee.Data were collected by the first and second author from the hospital electronic health records (Mirador®) and patient data management system (Metavision®). The following data were recorded at baseline: demographic characteristics; (psychiatric) comorbidity; use of psychoactive medication; substances of abuse; and admission type. Acute Physiology and Chronic Health Evaluation (APACHE) III and Sequential Organ Failure Assessment (SOFA) scores were calculated over the first 24 hours following ICU admission , 20. In Drugs that were administered to treat symptoms of delirium were noted. For the most common drug , the number of days and the maximum given intravenous dose over 24 hours were additionally recorded. In case of enteral administration of haloperidol, the dose was divided by two to convert to an equivalent intravenous dose. Benzodiazepines were only registered when subscribed for agitation and not in case of prescription for isolated sleep disturbance.In general, a history of psychiatric disorder is documented in the hospital electronic medical record. In case we noticed a discrepancy during ICU admission between potential psychiatric medication without a documented history of psychiatric disorder, a dedicated hospital psychiatry paramedic cross-checked the psychiatric history with the family, general practitioner, or treating psychiatric facility. Main categories of a premorbid psychiatric disorder included all forms of depressive, anxiety, psychotic, and personality disorders. Patients with dementia were not included in the study. Main categories of psychoactive drugs included sedatives, tranquilizers, antipsychotic drugs, antidepressant drugs, and mood stabilizers. Use of benzodiazepines for insomnia and tricyclic antidepressants for chronic pain was excluded. Sedation of patients was monitored by the Richmond Agitation-Sedation Scale (RASS). For every patient with RASS score >−3, the Confusion Assessment Method in the Intensive Care Unit (CAM-ICU) was performed three times a day . All  was used for statistical analysis. Distribution of continuous data was tested with a Kolmogorov–Smirnov test. Due to the non-normal distribution, such data are presented as median (IQR). After allocation into groups , a sampling distribution by chi-square testing was performed. A two-sided n = 39, 42%), bipolar disorders , anxiety disorders , psychotic disorders , personality disorders , drug abuse , and multiple disorders . Baseline characteristics with respect to severity of illness and type of admission did not differ between groups, but PS patients were significantly younger and more often female in comparison with NPS patients (All 472 identified patients who fulfilled the entry criteria over a 2-year period (2012-2013) were included in the study: 93 (19.7%) with (PS group) and 379 (80.3%) without (NPS group) a premorbid psychiatric history. Psychiatric disorders in PS group included depressive disorders . The administration of first- and second-line drug for the treatment of delirium was not different between groups , and one group without delirium . Patients in the DEL group had a significantly higher age and were more often male in comparison with the NDEL group. Furthermore, severity of illness scores was significantly higher in the DEL group. However, groups did not differ in terms of type of admission, intoxications, and chronic use of psychoactive drugs cove drugs  and remaX2=3.01, p=0.08; p=0.43). Finally, a binary logic regression model was constructed. In this model, age, sex, APACHE III score, and premorbid psychiatric disorder were all independently associated with the presence of delirium  psychiatric medication, and the availability of medical correspondence in the hospital electronic health records allowed us to minimize the potential bias of missing premorbid psychiatric disorders. Similarly, the assessment of delirium remains a challenge. Although in our setting both ICU nurses and doctors screen for delirium multiple times each day, the incidence may still be underreported. CAM-ICU in general has good specificity but lacks sensitivity for the nonagitated forms of delirium , 31. To In this selected group of ICU patients with a length of stay >48 hours and a premorbid psychiatric disorder, the incidence of delirium was not significantly higher in comparison with patients without a premorbid psychiatric disorder. However, there was a significant increase in duration of delirium in patients with a premorbid psychiatric disorder. A premorbid psychiatric disorder was not associated with 5-year all-cause mortality. In a multivariate analysis, the incidence of delirium per se was independently associated with male sex, age, APACHE III score, and a premorbid psychiatric disorder. However, delirium per se was not associated with a significant increase in long-term all-cause mortality.


Knowledge: Pain Management of the Nursing Outcomes Classification (NOC) in patients with chronic pain, defined as extent of understanding conveyed about causes, symptoms, and treatment of pain. A three-stage study was designed: (1) translation and cultural adaptation through an expert panel, (2) content validation, (3) clinical validation. This study provides nurses with a Spanish version of this scale adapted to their context, as well as a set of structured indicators to measure patients’ knowledge about chronic pain. The results indicated that the culturally adapted Spanish version of the outcome Knowledge: Pain Management had a high level of content validity (CVI = 0.92), with 27 indicators being distributed between two factors. This version has been shown to be reliable in terms of inter-observer agreement (κ = 0.79) and internal consistency (α = 0.95). In conclusion, Knowledge: Pain Management has been shown to be reliable and valid to measure knowledge of chronic pain.Pain has a major impact on health and quality of life. Since the level of knowledge of painful conditions can influence how these are addressed and managed, assessing this knowledge in patients becomes crucial. As a result, it is necessary to have culturally adapted and validated instruments that specifically measure patients’ knowledge of chronic pain management. The objective of this study was to carry out the Spanish cultural adaptation and the validation of the outcome  Pain is a health issue that affects a large number of individuals ,2. In acHealthcare professionals’ knowledge of pain management and treatment has attracted considerable attention ,8. ConveIn this sense, there is evidence that knowledge about analgesic drugs is associated with adherence to analgesic therapy . CaregivAn association has been found between the satisfaction with pain treatment and patients’ knowledge about the disease and some treatment-specific topics; this association persisted up to 12 months after receiving the education . ParticiImproving patient empowerment requires, first, exploring their beliefs, level of understanding about pain and pain management. Beliefs about pain may influence the behavior of the patients in pain management . MeasuriKnowledge: Pain Management , which is oriented towards measuring the extent of understanding conveyed about causes, symptoms, and treatment of pain. This outcome has 41 indicators  which are used to measure the overall KPN concept. It is measured with a five-point Likert scale . The indicators facilitate the monitoring of progress in knowledge of pain in a given episode of care and in different care settings [The Nursing Outcomes Classification (NOC)  includessettings .The research of the NOC project were carried out in the United States. Subsequently, further studies have been carried out in other countries to increase the knowledge and applicability of the NOC outcomes, although each outcome has undergone its own research and development process. Validation by an expert panel has been used in certain nursing diagnoses ,27, as wKnowledge: Pain Management and to assess its psychometric properties and sensitivity to change in patients with chronic pain.The objective of this study was to provide the Spanish translation and cultural adaptation of the English version (5th edition) of the NOC outcome Knowledge: Pain management: (1) Spanish translation and cultural adaptation; (2) content validation; and (3) clinical validation.A three-stage validation design was used for the outcome Stage 1: The translation/back-translation method ,30 was aStage 2: A panel of 21 pain experts of Spanish nationality (19 nurses and two physiotherapists) assessed the content validity of the first Spanish version in two rounds of consensus using the Delphi technique . The memThe CVI-indicator (CVI-i) was determined for each indicator, taking into consideration that, for six or more experts, this value should not be below 0.78 . The modStage 3: An observational-longitudinal study was carried out to establish the reliability, validity, and sensitivity to change of the Spanish version of the KPM.The study was conducted from March 2013 to April 2014 in 9 settings  in the Andalusian Health Service in the provinces of Jaén (6) and Granada (3), Spain. Twenty nurses (16 women and four men) participated in the data collection. These nurses were working full time, had been working for more than 6 months in their respective healthcare centres, and had a mean experience of 20.7 years in caring for patients with chronic pain (Standard Deviation = 6.59). The nurses were working in the following units: Primary Care Team (50%), Oncology Impatient Unit (30%), Hospital Case Management (Advanced Practice Nurses) (10%), and Chronic Pain Unit (10%).Data published by the authors of the validation of the NOC for use in people with chronic pain were used to estimate the size of the patient sample . A minimKnowledge: Pain management. The adapted Spanish version of KPM with 30 indicators, which was obtained after validation by experts, was used. These indicators measure the knowledge of how pain appears and is maintained, aspects related to medication and treatment, and various strategies and techniques for appropriate pain management. Twenty eight indicators were taken from the original English version  and a fuPain intensity. The Spanish version of the 11-point Numerical Pain Intensity Scale (NPIS) was used. The reliability and validity of this one-dimensional instrument are well-documented, being widely utilised for pain intensity assessment . The aspPain Coping Questionnaire (reduced version) (PCQ-R). The subscale “Seeking instrumental social support” was considered. This subscale assesses how individuals cope with pain by seeking advice, help, or information (problem-focused coping) on a 5-point Likert scale . The psychometric properties of this questionnaire have been studied in the Spanish population. Internal consistency ranged from α = 0.75 to α = 0.94; test-retest reliability was r = 0.81, and convergent validity with other scales was as expected ,39.Ad hoc questions to patients. Knowledge: Pain Management and in the data collection procedure. Most of the interviews with primary care patients were conducted in the nursing offices of the healthcare centres, although some were conducted in the patients’ homes. Inpatients were interviewed in a private area in the hospitalisation area. Patients in the Chronic Pain Unit were interviewed in the nurses’ office of the unit.The principal investigator trained all collaborating nurses in the measurement of the outcome An ad hoc questionnaire were used by the nurses to record the patients’ demographic and clinical data, as well as their own demographic and professional data. Two assessments were conducted. In the first assessment, patients self-reported the NPIS, the PCQ-R, and the ad hoc questions about their knowledge and satisfaction. Two nurses then independently assessed the KPM, concealing their score from the other nurse (to measure inter-observer agreement). In the second assessment, conducted after a 20–30 day interval (to measure sensitivity to change), patients answered the ad hoc questions again and the KPM was reassessed by one of the nurses who conducted the first measurement.The project was approved by the Research Ethics Committee of Jaén, Spain. Nurses and patients were given detailed information on the project and signed an informed consent form. Participant anonymity and data confidentiality were preserved in compliance with current data protection laws in Spain.® SPSS® statistics 19. IBM, International Business Machines Corporation, Armonk, NY, USA). Descriptive statistics were calculated. For nominal variables, frequencies and percentages were used. For continuous variables, means and standard deviations were used. Additionally, 95% confidence intervals were calculated for continuous variables.The data were collected in a spreadsheet  and analysed with SPSS  was performed using the principal components method with quartimax rotation to study the underlying conceptual structure of KPM. Sample adequacy was estimated with the Kaiser-Meyer-Olkin index and Bartlett’s test of sphericity, with riterion . In the Convergent and divergent validity was analysed using the multitrait-multimethod (MTMM) matrix ,41. In sIn order to assess reliability, internal consistency and inter-observer agreement were determined. Cohen’s kappa coefficient with quadratic weighting was used to determine inter-observer agreement, considering kappa values ≤ 0.20 to reflect poor agreement; values of 0.21–0.40, mild agreement; 0.41–0.60, moderate agreement; 0.61–0.80, good agreement; and 0.81–1.00, excellent agreement. Internal consistency was calculated according to Cronbach’s alpha coefficient, considering values > 0.80 to indicate a good level of consistency ,41.p < 0.05.Sensitivity to change. The capacity of KPM to detect change was analysed by administering this outcome at two points in time separated by 20–30 days . Wilcoxon’s rank-sum test was used to evaluate the mean agreement between the measurements, with statistical significance set at A Spanish adaptation of KPM, semantically equivalent to the English version, was obtained. The adapted version has modifications to the label, to 17 indicators, and to the measurement scale, compared to the 5th and 6th Spanish editions of the NOC ,32,33.After review by the panel of experts, a version with 30 indicators was obtained . Overall, the CVI-ua was 0.33 and the CVI-a was 0.92. All indicators were rated as excellent with modified kappa scores ranging from 0.75 to 1.00 . ThirteeThe clinical validation study included 84 pain patients. n = 84), and 44 patients had a second measurement . The mean interval between the initial and final measurements was 42.84 (SD = 19.35) days.The most frequent nursing diagnoses (NANDA-I) were Chronic pain (42.9%) and Acute pain (11.9%). Patients were using different types of drugs , with scheduled non-opioid analgesics being more frequent . All 84 patients underwent a first (baseline) measurement . Pain was mainly located in the back (54.8%), lower extremities (48.8%), and pelvis (45.2%). The mean score obtained in the PCQ-R subscale “Seeking instrumental social support” was 8.73 points (SD = 4.29) (range: 0–16) .Knowledge: Pain Management was 3.24 (SD = 0.87) in the baseline measurement and 3.46 (SD = 0.77) in the final measurement. The lowest mean score was 2.52 (SD = 1.31) for the indicator “Potential medication interactions”, and the highest mean score was 3.98 (SD = 0.88) for “Importance of informing health professional of all current medication”. The scores for the 5 questions to patients about their knowledge and satisfaction with pain management are shown in The overall mean score obtained through the outcome p < 0.0001) showed that the data were suitable for analysis.Construct validity was assessed through an EFA. Taking into consideration the parallel analysis, the 30 indicators can be grouped into two factors. The Kaiser-Meyer-Olkin sample adequacy test (0.806) and Bartlett’s test of sphericity , Effective heat/cold application (variance = 0.353), and Available community resources (variance = 0.279), presented low proportions of explained variance and low factor loading values. As a result, they were eliminated.A second analysis with quartimax rotation showed a structure of 27 indicators distributed between two factors explaining 53.56% of the variance. The matrix of rotated factors shows their composition: (a) Knowledge about pain, made up of 25 indicators explaining 45.73% of the variance; (b) Non-prescription medication, made up of two indicators explaining 7.82% of the remaining variance .p < 0.001); and Q2 How well prepared are you to take care of yourself and to manage and control your painful condition? .Analysis using MTMM makes it possible to assess the convergent and divergent validity of KPM . For conp = 0.16) and with the PCQ-R subscale “Seeking instrumental social support” ; and no correlations with the three questions about satisfaction: Q3 How satisfied are you with the care provided by the nurses in relieving your pain? ; Q4 How satisfied are you with the treatment of your pain? ; and Q5 How much have you managed to improve your pain with the treatment and care provided by professionals? .For divergent validity, weak correlations lacking statistical significance were found with the score for the outcome Client satisfaction: Pain management . Agreement was excellent for 6 indicators and good for 20 indicators ), nor for either of the two ad-hoc questions: How much do you know about the causes, symptoms, and treatment of pain?  and How well prepared are you to take care of yourself and to manage and control your painful condition? . However, in the analysis of indicators, statistically significant differences were observed in six of them between the baseline and final measurements: Strategies for preventive pain management , Effective relaxation techniques , Effective distraction , Effective heat/cold application , Benefits of ongoing self-monitoring of pain , Available community resources .No differences were found between the baseline and final scores for the outcome KPM  of this outcome were tested in a sample of patients with pain. Nurses in Spanish-speaking contexts could use this adapted version of KPM to measure the degree of knowledge that their patients have about the causes, symptoms, and treatment of pain.This article report on the process to translate and adapt to Spanish context and culture the set of indicators included in the nursing outcome Following the principles of good practice ,42, duriThe content validity data suggest that the set of indicators is adequate for the conceptualisation of the KPM outcome in accordance with the recommendations made by Polit et al. , who proThe two-factor structure proposed in the final model for the KPM outcome makes it possible to explain a significant percentage of the overall variance, although a fraction of the variance remains unexplained, so it is likely that other indicators may be added in the future. Further studies are required to verify the suitability of this structure in other clinical settings and types of pain patients. Factor 1, Knowledge about pain, includes a considerable number of indicators addressing various concepts of pain, such as treatment and improvement strategies (13), aspects related to medication (9), and, to a lesser extent, signs and symptoms associated with pain (3), which point to the complexity of this factor. Factor 2, Non-prescription medication, has only two indicators. The correlations of these indicators with the total are the lowest on the whole list, which suggests that factor 2 needs an improved definition of the overall set and/or its indicators. This distribution of outcome indicators into two factors may be useful for nurses when deciding which indicators to use in assessing patients’ knowledge of different aspects related to pain and pain management, in line with other validation studies of other NOC outcomes ,44,45.We found evidence of validity of convergent and divergent criteria for the KPM outcome. Convergent validity was verified drawing on the strong correlations with the specific questions about knowledge and ability to control pain, as well as on each of the two proposed factors. In addition, the KPM outcome is well differentiated from other related yet different concepts, such as satisfaction with pain management and ability to cope, as shown by the divergent validity analysis.A more detailed analysis showed that some of the indicators referring to medication aspects had a weak correlation with the score on the ad hoc question about knowledge. At this point, it is pertinent to wonder whether the question was well configured in terms of content and scope for the population studied, as this suggests that knowledge about medication can be challenging for patients. The level of knowledge is associated with adherence to analgesic therapy , but knoWe found evidence of the reliability of KPM when used by nurses in patients with chronic pain. Inter-observer agreement was high for the overall set and most of the indicators. However, five indicators relating to medication had a low or moderate correlation , which mIt could not be established that KPM showed sensitivity to changes in patient knowledge in the overall score. Patients may not have experienced substantial changes in their knowledge which would explain why no significant changes were observed between the baseline and final scores. However, significant changes were observed in a group of indicators relating to various pain management and treatment strategies. In this study, the mean time interval between measurements was almost 43 days, longer than the interval in the study on the outcome Pain control (code 1605) , with 30Although no validation studies have been identified with which to compare the psychometric tests in this study, the usefulness of KPM has been demonstrated in other studies. As such, KPM has been validated for certain nursing diagnoses, Lucena et al.  validateA comprehension and cognitive equivalence test carried out with nurses, patients, healthy individuals, and even native speakers representing the target population  may improve the cultural adaptation process and provide a better adjustment of the concepts used to the cultural characteristics of the given geographical area ,51.Homogeneity in the training of participating nurses cannot be ensured, as they were included in the study because they were willing to collaborate and this may, therefore, lead to an overestimation of reliability. Attempts have been made to control bias by training participants in the conditions of the study, by diversifying participation , and by seeking the participation of advanced practice nurses .Patients were selected using convenience sampling and the sample size was relatively small. However, the representativeness of the study was improved by sampling at 9 different locations. Broader randomised samples and other additional care settings should be included to further increase knowledge of the psychometric properties of KPM. Some of the indicators included in the English version of this outcome were not included in the two-factor Spanish version, which may require further assessments. Additional studies are also necessary to increase the time between the baseline and the final measurements, seeking significant differences in the sensitivity to change of KPM and its indicators in patients with chronic pain.Knowledge: Pain Management, adapted to a Spanish context, includes 27 indicators. Evidence has been obtained of the reliability and validity of these indicators for use in nursing practice in Spanish-speaking contexts.The final version of the nursing outcome An internal structure of two factors, referred to as Knowledge about pain and Non-prescription medication, can be observed. This structure is novel and thus requires further research with larger patient samples, additional care settings, and acute pain scenarios. Being able to make an appropriate selection of indicators based on this two-factor structure may help nurses in their decision-making, especially the less experienced.The present study highlights an interesting field of research. Improving the definition and conceptual configuration of the outcome KPM, presenting an operational list of indicators, and increasing the input of psychometric testing through further research will not only consolidate the reliability and validity of this outcome, but will also make it more useful in the complex process of caring for individuals with pain.


Poly/graphite (PET/G) micro-composites were fabricated by the melt compounding method using a minilab extruder. The carbon fillers were found to act as nucleating agents for the PET matrix and hence accelerated crystallization and increased the degree of crystallinity. TGA showed that carbon fillers improved the resistance to thermal and thermo-oxidative degradation under both air and nitrogen atmospheres. However, a poor agreement was observed at higher loadings of the filler where the composites displayed reduced reinforcement efficiency. The results demonstrate that the addition of graphite at loading >14.5 wt.% made electrically conductive composites. It was calculated that the electric conductivities of PET/graphite micro-composites were enhanced, above the percolation threshold values by two orders of magnitudes compared to the PET matrix. The minimum value of conductivity required to avoid electrostatic charge application of an insulating polymer was achieved, just above the threshold values. The addition of graphite also improved thermal stability of PET, accelerated its crystallization process and increased the degree of crystallinity. Microscopic results exhibit no indication of aggregations at 2 wt.% graphite, whereas more agglomeration and rolling up could be seen as the graphite content was increased in the PET matrix . Furthermore, based on the mechanical experimental characterization of the PET/graphite micro-composites, a large deformation-based mathematical model is proposed for material behavior predictions. The model fits well the experimental data and predicts other mechanical data that are not included in the parameter identification. Much research have been focused on preparing polymeric matrix composites (PMC) for high performance applications, particularly using carbon and its allotropes, which include both micro- and nano-size fillers such as carbon black (CB), graphite, carbon fibers, graphite nanoplatelets (GNP), graphene and carbon nanotubes (CNT) ,2,3,4. TMicromechanics show that the properties of polymer composites are a function of the behavior of the individual constituents, their shapes and arrangements, volume fractions, and the interfaces between matrices and reinforcements . For theThe most commonly used and extensively researched particulate carbon fillers and various types of polymers can be used as matrices to produce PMC including thermoplastics, thermosetting polymers, and elastomers ,20,21,22agonally . In grapagonally . Graphiterature) ,23,27,28tivities . It is otivities ,29,30. Ttivities . The envtivities . Hence, The properties of polymer composites depend on sizes and dimensions of fillers. Micro-fillers are used to fabricate composites due to their good mechanical properties, lower costs, and easy availability. Therefore, in this study, conductive carbon filled PET composites were prepared by using graphite to study the electrical conductivity, morphology, and thermal properties of PET matrix and its micro-composites. At first, the percolation threshold . Note that, to be consistent with the company’s (Equipolymers) manual , we hereMelt compounding technique was used for the preparation of PET/graphite micro-composites. The PET and the graphite filler were dried in a vacuum oven at 120 °C for 24 h prior to the melt compounding. The micro-composites were mixed by melt compounding using a laboratory scale . Each sample was examined five times to check the result accuracy. The morphology state of graphite in the micro-composites was characterized by using a scanning electron microscope (Philips SEM XL30), at an accelerating voltage of 10–20 kV. For SEM images of the micro-composites, their films were cryogenically fractured in a liquid nitrogen bath. After that, samples were mounted on 0.5-inch pin stubs using a carbon adhesive tape and then coated with thin layer gold using an Edwards S150B sputter coater, to prevent any charging. The samples were chosen to examine their morphologies below, close, and above the percolation threshold value of PET/graphite composite system. Melting and crystallization behavior of the micro-composites were examined by differential scanning calorimetry (TA Instrument DSC Q-100). All measurements were scanned from room temperature to 270 °C and the test was performed under nitrogen gas condition using a heat–cool–heat run at a heating/cooling rate of 10 °C/min. To confirm accuracy of the results, three samples from each material were measured. The thermal stability of pure PET and its micro-composites was investigated as a function of graphite contents by using a thermogravimetric analyzer . All samples (≈5 mg) were scanned from 23 to 700 °C under nitrogen and air gas condition at a heating rate of 10 °C/min.The as-received graphite was examined using the SEM to study their morphology before incorporation into the PET matrix. The graphite exhibits large platelets of the scale of ∼20–100 ch other a. As a rther , A is the cross sectional area of the sample σ=aterials . At thisaterials . The thet describes the dimensionality of the system that depends on the geometry of the network. In theory, t of 1.3 and 2.2 represent two- and three-dimensional systems, respectively. However, experimental values outside this range are also reported in the literature [According to the percolation theory ,39,40,41terature . The fita et al.  examinede et al.  also reprobotics ,44. TherOne of the objectives of performing thermal analyses is to obtain thermodynamic properties. Thermodynamics denotes the motion of energy on all levels. These properties control the rate of energy exchange and absorbance from an energy source. Properties such as specific heat and latent heats of phase change are essential parameters in the study of thermal behavior and stability of polymer composites. The TG/DTA Thermal analyzer used in this study gives a DSC signal as well. The DSC study shows the rate and magnitude of energy changes experienced by the sample. From the DSC curve, properties such as specific heat, latent heats of phase change or transition, and temperature of transition can be obtained directly.The pure PET and its micro-composites with varying concentration of synthetic graphite  were subjected to a heat–cool–heat cycle at 10 °C/min in the DSC. The DSC curves in at units ,45, causTypically, an efficient nucleating agent reduces the energy required for nucleation and hence accelerates the crystallization process . The hetequation ,49:(3)Xc140 J/g) ,51 and vThe nucleation process is also reflected in the uenching . Values Equation  as thesemposites , PP/grapmposites  and PET/mposites . Howevermposites  found th4 ± 1 °C . Similarr chains ,57. The decrease ,57, incrdecrease  or no chdecrease  in the Tncreased .Graphite agglomerates were observed in the PET matrix at higher loadings using SEM images, as shown in mposites .It has been reported that PET generates a large amount of carbonaceous residue in a nitrogen atmosphere . FurtherThe Graphite has been used in previous studies for the enhancement of thermal stabilities of several polymer matrices. For example, Otieno et al.  studied xy resin  by 25 °CWe conducted as a series of mechanical experiments on the graphite-filled PET composite for two reasons. First, an experimental study on the filled PET with tensile tests can provide a good understanding on its mechanical properties. Secondly, these experimental results facilitate developing mathematical models for a computer-based simulation for predicting some material behaviors. For these, specimens for tensile testing were prepared using Haake Minijet II injection molding machine . The tensile testing was performed using an Instron instrument of model 4301 at crosshead speed of 5 mm/min by following ASTM D638 standard. To ensure accuracy and reproducibility, five tests were performed and the average of them was reported as the final value of tensile properties. All the tensile tests were carried out at room temperature.As expected, a rigid micro-filler-like graphite increases the composite stiffness, which is reflected in The understanding of mechanical behavior of filler-reinforced polymer has been an active field of research for last several decades. Particularly, the constitutive modeling to predict mechanical responses under the influence of micro-scale fillers have increasingly been studied ,33,34. Mc) and the matrix (m), respectively, and g is related to length/breadth of a cluster and its value is assumed larger than 1. There are small-strain based material models for composites that can be easily be incorporated. However, our target is to model the experimental data presented in For small strain-based problems, the prediction of the equilibrium behavior is considered as a composite theory problem that can be approached in two different ways: one can derive rigorous bounds for the behavior or one can try to estimate the overall behavior. For the second case, one of the earliest and simplest approaches was due to Guth  and GuthMost of the small strain-inspired models are based on the so-called mixture theories, which have taken some sort of account of the complex behaviors of filler–matrix interactions, e.g., particle size, shape, orientation, and interaction between particle and matrix. However, finite strain based models develop mainly around the concept of the amplification factor in a homogenized sense. For modeling polymeric materials at large deformations, the starting point is the deformation gradient x direction while y and z directions, respectively. Note that for the incompressible materials, the third invariant p is a scalar quantity that serves as an indeterminate Lagrange multiplier and will be removed from the above equation using appropriate boundary conditions. In Equation . Note tn et al. ,64,65,66n et al. ,66,67. On et al. ,67. It sX is the stretch amplification factor that depends on the fraction of filler g is a factor describing the asymmetric nature of the aggregated clusters. Therefore, to obtain complete stress–stretch expressions, according to Mullins–Tubin assumption, the actual stretch For detailed derivations of Equation , readersP which relates to the uniaxial Cauchy stress via Note that, in our studies, we have calculated the uniaxial engineering stress  g is identified as 2.67, which is within the range (larger than one).As shown in the previous section, t fillers increase the mechanical stiffness of the reinforced-PET composites, which is depicted with increments of the elastic moduli see . At firsAfter the parameter identification within elastic enhancement model in Equation , first, rves see , bottom.g appearing in the amplification factor X needs to be identified first. In this case, we used the value 2.67 already identified by the linear model of modulus of elasticity enhancements (data in Next, a nonlinear model, i.e., the Carrol model presented in Equation  data in , top usiIn this study, conductive graphite filled PET micro-composites were prepared from PET as a matrix and graphite as a micro-filler by a melt compounding technique using a co-rotating twin-screw extruder and molded into films and tensile test pieces by compression and injection moldings, respectively. The electrical conductivity, morphology, thermal stability, crystallization rate, and degree of crystallinity of these composites were studied and characterized. In particular, at ∼14.5 wt.% of graphite, a significant enhancement in the electrical conductivity (


Climate change has significantly altered species distributions in the wild and has the potential to affect the interactions between pests and diseases and their human, animal and plant hosts. While several studies have projected changes in disease distributions in the future, responses to historical climate change are poorly understood. Such analyses are required to dissect the relative contributions of climate change, host availability and dispersal to the emergence of pests and diseases. Here, we model the influence of climate change on the most damaging disease of a major tropical food plant, Black Sigatoka disease of banana. Black Sigatoka emerged from Asia in the late twentieth Century and has recently completed its invasion of Latin American and Caribbean banana-growing areas. We parametrize an infection model with published experimental data and drive the model with hourly microclimate data from a global climate reanalysis dataset. We define infection risk as the sum of the number of modelled hourly spore cohorts that infect a leaf over a time interval. The model shows that infection risk has increased by a median of 44.2% across banana-growing areas of Latin America and the Caribbean since the 1960s, due to increasing canopy wetness and improving temperature conditions for the pathogen. Thus, while increasing banana production and global trade have probably facilitated Black Sigatoka establishment and spread, climate change has made the region increasingly conducive for plant infection.This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. BiologiMusa spp.). Bananas and plantains are the seventh most important crop by production in the developing world, with India, China and Brazil being the most important producers [Fusarium oxysporum f. sp. cubense), also known as Panama Disease, in the form of Tropical Race 4 (TR4) from Southeast Asia, is of particular concern to the export industries of Latin America and the Caribbean, because planted cultivars of Cavendish bananas are highly susceptible to the disease [Crop pests and pathogens are spreading rapidly around the world , and latroducers . It is troducers . The re- disease .Pseudocercospora fijiensis (formerly Mycosphaerella fijiensis). P. fijiensis spreads via aerial spores, infecting banana leaves via the stomata and causing characteristic streaked lesions and cell death when fungal toxins are exposed to light [While the focus on control of TR4 is justified given potential production impacts and economic consequences, Fusarium Wilt is not currently the most important disease in banana production globally. Another fungal disease, known as Black Sigatoka or Black Leaf Streak Disease, has recently emerged from Asia and now causes the greatest yield losses in banana plantations globally . Black Sto light . The disto light .Establishment of an emerging plant disease in new territories requires the presence of the host and a suitable climate . Thus, w2.P. fijiensis is strongly determined by weather and microclimate [P. fijiensis forms relatively few of them in comparison with ascospores. Ascospores are dispersed over long distances by wind [P. fijiensis spores require a wet leaf surface or very high relative humidity (RH) to germinate and infect the leaf, and the rate of germination and infection during wet or humid periods is governed by temperature [The life cycle of oclimate . Ascospo by wind , while cperature .et al. [Several experimental studies have investigated the dependence of spore germination, infection and Black Sigatoka disease development on microclimate. Uchôa et al. ,25 measut during wet periods and has a Weibull hazard function H dependent upon temperature T (equations (2.1) and (2.2)). The temperature-dependent rate r is determined by the cardinal temperatures, namely the minimum (Tmin), optimum (Topt) and maximum (Tmax) (equation (2.3)). Full details of the model are provided in ref. [Tmin, Topt, Tmax, the scale factor of the Weibull hazard function α, the shape parameter of the Weibull hazard function γ and a scaling factor β such that βF(t) = AUDPC(t) where F(t) is the fraction of a cohort of spores that have germinated by time t.We treated infection as a probabilistic survival process of spores transitioning to infections, which proceeds over time  in ref.  and in e in ref. : Tmin, TAs previously ,28, we einfection risk, our metric for disease pressure in relation to weather. These were summed to give annual infection risk in each pixel.For each pixel, we linearly interpolated the 3-hourly micro-climate data to hourly, then modelled cumulative infection probabilities for hourly cohorts of spores, with rates determined by our temperature response function. The hazard function was calculated piecewise by the temperature in each hour of each wet period. We assumed that ascospores had identical temperature requirements to conidia, as ascospore data are unavailable. Cohorts were assumed not to accumulate on leaves during dry periods, i.e. only one cohort began to germinate in each hour under conditions of leaf wetness or with RH greater than or equal to 98%. Cohorts were assumed to stop germinating and die under drier conditions. The cumulative number of infections was summed over all preceding cohorts for each hour to give Further details of data and analyses are given in the electronic supplementary material, including details of the infection risk model and its parametrization (with computer code examples), additional data sources, details of the JRA55 dataset and consideration of sub-pixel variation in microclimate estimates, the geographical distribution of banana production and an analysis of the effects of weather on the disease incubation and latent periods.3.et al. [Tmin = 16.6, Topt = 27.2 and Tmax = 30.3°C, α = 32.6, γ = 1.76, and scaling parameter β = 37.6  were most frequent in the western Amazon basin of Brazil and Colombia, the Andean regions of Bolivia, Peru, Ecuador and Colombia, and southern Panama, while dry conditions occurred in southern Brazil, Mexico, Cuba, coastal Venezuela, northern Colombia (a). Over the study period, the central area comprising western Brazil, Venezuela, southern and central Colombia, much of Ecuador and Peru, and the Dominican Republic became wetter, while Mexico, Central America, Cuba and southern Brazil became drier (b). The canopy temperature suitability for Black Sigatoka infection, as defined by the beta function r(T), was greatest on average in the Amazon basin, Panama and eastern Nicaragua, and lowest in Mexico and high-elevation regions of the Andes and the Guiana Shield (c). The canopy temperature suitability for infection increased over much of Latin America and the Caribbean, particularly in the Amazon basin, coastal Ecuador and Dominican Republic (d).The best-fitting model parameters for the Uchôa et al. ,25 diseaβ = 37.6 . Thus, aColombia a. Over tme drier b. The caa Shield c. The caRepublic d.Figuree), with up to 2000 cohorts of spores infecting per year. In context, the model would allow for up to 8760 cohorts to infect per year (this being the number of hours per year). Potential infection risk increased most rapidly across the Amazon basin, and parts of Nicaragua, Ecuador, Guyana, Suriname, French Guiana and the Dominican Republic, and decreased in southern Brazil, much of Central America, and the north coast of Colombia (f). Considering only the banana-growing pixels with greater than 0.1% banana-growing area per pixel (approx. 20% of the region), the median annual average infection number was 234, with a median trend of +0.32  framework of Sobéron and colleagues , in whicPhaeosphaeria nodorum and Zymoseptoria tritici in the UK revealed air pollution as the main driver of their relative abundance [We employed a ‘forward modelling’ approach  in whichbundance , invalidbundance ,22,41–43Z. tritici [Leptinotarsa decemlineata into China, due to the evolution of burrowing behaviour that was not considered in the model [P. fijiensis populations has been made , we have insufficient information on adaptation to adjust our model accordingly. Our modelling used the JRA55 climate reanalysis dataset, which may be subject to biases, particularly in the hydrological cycle [Other potential weaknesses of our approach include local evolutionary adaptation, as observed in  tritici , which whe model . Though al cycle . The JRAal cycle . AdditioWe employed a mechanistic model  driven by high temporal resolution  historical weather estimates. An alternative would have been a statistical model that correlated historical disease incidences with weather. Such observational data are not, to our knowledge, available, although we attempted to model the disease latent period in this way . Hence, our reliance on experimental data to parametrize the infection process in relation to temperature. Both process-based and statistical models (and models combining elements of both approaches) are widely used to model climatic effects on species distributions, biological invasions and the epidemiology and occurrence of human, animal and plant pathogens ,39,46. ECorrelative models have been far more prevalent for modelling of human infectious diseases in relation to climate change . For exaet al. [P. fijiensis infection, quadratic and Briére functions were fitted to data from laboratory studies. The beta function was introduced for crop physiology in 1995 [A vector-borne human disease with a long history of mechanistic modelling is malaria . The impet al.  publishe in 1995  and crop in 1995 , so it i in 1995 , but at  in 1995 ,49.We did not attempt to model the potential effects of future climate on Black Sigatoka distribution and impact. Based upon temperature ranges (25–28°C) and RH (greater than 90%), declines in the area favourable to the pathogen globally and within Latin America and the Caribbean by 2080 have been projected using earlier climate projections . A poten


Background: Both depression and anxiety  are associated with difficulties in emotion regulation (ER). Little is known about whether anxiety as a comorbid condition has an effect on the habitual use of different ER strategies in youngsters with depression histories. We aimed 1) to compare ER in adolescents with histories of childhood onset major depressive disorder (MDD) with and without comorbid anxiety and 2) to examine whether certain ER response clusters  characterize comorbid children and adolescents.Methods: We analyzed data on 217 youth (11–18 years old) with depression history: 85 subjects with lifetime anxiety comorbidity (comorbid group) and 132 without lifetime anxiety (non-comorbid group). Psychiatric diagnosis was established by a comprehensive Diagnostic and Statistical Manual of Mental Disorders (DSM) IV-based diagnostic procedure. ER strategies were examined via the self-rated “Feelings and Me” Child version questionnaire (FAM-C).Results: The comorbid group used maladaptive ER strategies significantly more frequently than the non-comorbid youngsters. The Behavioral/Physical and Social ER skills, especially those reflecting social withdrawal and self-harm, were responsible for the higher maladaptive scores.Limitations: Because our study is a cross-sectional analysis, we have no information about the development or the onset of maladaptive ER strategies. Therefore, we were unable to examine whether maladaptive ER was a risk factor or a consequence of the internalizing psychopathology and comorbidity.Conclusions: Comorbid anxiety worsens the impaired use of ER strategies in depression-prone youths. Further longitudinal research is needed to explore the causal role of dysfunctional ER in the development of internalizing psychopathology. The ability to regulate emotions and attenuate negative emotions is considered fundamental to healthy child development and functioning , 2. The Depressed youngsters use a greater number of maladaptive mood repair strategies and fewer adaptive ones than do healthy controls , 13. TheER also seems to be impaired in individuals with anxiety symptoms , 15. A gDepression and anxiety disorders are the most common comorbid mental disorders. Based on comprehensive epidemiological data, the estimated rate of comorbid anxiety disorders in children and adolescents with depression ranges from 30% to 75% , 24. ComResearch on the impact of comorbidity of depression and anxiety disorder suggests that patients with comorbidity have greater impairment and symptom severity, more chronic course of illness, and decreased response to treatment relative to patients with these conditions in isolation –31. FurtPrevious ER research on anxiety and depression comorbid patients focused mainly on maladaptive cognitive skills and the role of ruminative thinking , 34. ResThe relationship between self-blame and depressive and anxiety symptoms was stronger in adolescents than in adults. Positive reappraisal, an adaptive coping strategy, was less often used by adolescents, indicating that they were less likely than adults to try to add positive meaning to a negative life event .In summary, anxiety and depressive disorders are both associated with abnormalities in the processing and regulation of emotions. Understanding the link between these dysfunctional strategies and the psychopathology of children and adolescents with depression and anxiety may facilitate the development of more efficient prevention and treatment approaches.The goal of this study was to compare the ER strategies of youngsters with histories of MDD with and without comorbid anxiety disorders. Specifically, we aimed 1) to compare the adaptive and maladaptive ER repertoires of youngsters with histories of MDD with and without comorbid anxiety and 2) to examine whether certain ER response clusters  characterize comorbid children and adolescents.This study was approved by the institutional review boards of the University of Pittsburgh, USA, and the University of Szeged, Hungary. Parents provided written informed consent, and youths provided either assent or consent (depending on their ages) before any data were gathered. All procedures, schedules, rating scales, and instruments used in this study were first developed in English, translated to Hungarian, and then retranslated to English by bi-lingual child psychiatrists and clinical psychologists. Original and back-translated versions were compared, and discrepancies were resolved.Diagnostic and Statistical Manual of Mental Disorders (DSM) IV MDD, 7 to 14 years old at initial assessment, no evidence of mental retardation or major systemic medical disorder, availability of at least one biological parent, and having at least one sibling aged 7–18 years.The subjects in our study were selected from a genetic and other risk factor study of childhood onset depression (Program Project Hungarian study) described elsewhere . The oriChildren in the cohort were clinical patients at 23 child psychiatry inpatient and outpatient facilities in Hungary at the time of study entry. For the present paper, we analyzed data on 217 children who were invited to participate in the Biobehavioral Inflexibility and Risk for Juvenile-onset Depression study. Their age ranged from 11 to 18 years at the time of assessment.The Interview Schedule for Children and Adolescents—Diagnostic Version (ISCA-D) was used for establishing psychiatric diagnoses. ISCA-D is an extension and modification of the Interview Schedule for Children and Adolescents (ISCA) . It is aSelf-rating scales for the present study were administered at the time of Biobehavioral Inflexibility and Risk for Juvenile-onset Depression study, after the FU-ISCA-D interview, on the same day. Interviewers were available to help younger children as needed.via the self-rated “Feelings and Me” Child (FAM-C) version questionnaire, which evaluates the use of responses to depressed, dysphoric mood  and 22 strategies that are “maladaptive” . Besides the Total Adaptive and Maladaptive scores, the items reflect three regulatory domains—Behavioral/Physical (24 items), Social-Interpersonal (12 items), and Cognitive (18 items)—with adaptive and maladaptive strategies in each. Each response is scored 0, 1, or 2, corresponding to the choice of “not true,” “sometimes true,” or “often true.” We have previously reported good psychometric properties of this measure across clinical and non-clinical populations , 44.In order to control for depressive symptoms, the Child Depression Inventory (CDI-R) was administered. CDI-R is a 27-item, self-rated, symptom-oriented scale suitable for youths aged 7 to 17, sensitive to changes in depressive symptoms over time, and is a useful index of the severity of the depressive episode. It measures depressive symptoms in the last 2 weeks .We used SPSS Statistics 22.0 package for all the performed statistical analyses.The percentage of missing data was very low: 0.4% in the whole dataset. By default, SPSS treated missing values as “missing,” and these items were not included in the statistical analyses.t-test for continuous and chi-square test for categorical variables. The general linear model (GLM)-univariate analysis was used to explore the differences in the ER responses between the groups. False discovery rate (Benjamini–Hochberg procedure) was used to control for multiple comparisons.To examine possible differences between groups on baseline characteristics, we used independent dependent variables were Total Adaptive, Total Maladaptive, Adaptive Cognitive, Maladaptive Cognitive, Adaptive Social, Maladaptive Social, Adaptive Behavioral/Physical, and Maladaptive Behavioral/Physical scores as measured by the FAM-C.The The independent variable was group membership. The two groups were youth with any lifetime depression disorder and any lifetime anxiety disorder (comorbid group) and youth with any lifetime depression disorder and no lifetime anxiety disorder (non-comorbid group).Covariates included CDI-R scores, number of MDD episodes, age, sex, and age of onset of first mood disorder (MDD or dysthymia). Based on the literature, depression severity and ER deficits are directly related  were excluded from the statistical analysis.Our sample included 217 children  who had had at least one lifetime MDD episode: 54.8% had one, 30% had two, and 15.2% had three or more MDD episodes. Of the whole sample, 13.4% were currently in depressive episode. The exact pattern of past and current MDD and anxiety episodes in our sample is shown in The characteristics of the comorbid and non-comorbid groups are shown in The two groups did not differ in gender and age distribution, age of onset of first MDD episode, or the number of youths currently in MDD episode. However, the CDI-R scores, age of onset of first mood disorder, and the number of MDD episodes showed statistically significant differences in the two groups. Therefore, we used these variables as covariates in our group analyses  = 1.023, p = 0.313, partial η2 = 0.005], while the Total Maladaptive score was significantly higher in the comorbid compared with non-comorbid subjects .The Total Adaptive score of the FAM-C did not show statistically significant difference between the groups , Social , and Behavioral/Physical . However, Maladaptive Social  and Maladaptive Behavioral/Physical  subscales were significantly higher in comorbid children  = 4.794, p = 0.03, partial η2 = 0.023].When we looked at specific items of the above-mentioned maladaptive subscales, the item reflecting social withdrawal in the Social subscale and the item reflecting self-harm in the Behavioral/Physical subscale were more frequently used by comorbid youth (data not shown). The Maladaptive Cognitive subscale was not significantly different across groups. However, one of the cognitive items similar to rumination was significantly more frequently endorsed by the patients in the comorbid group (think of being sad) [The aim of our study was to examine whether anxiety as a comorbid condition was associated with the use of different ER strategies in youngsters with histories of depression. Our study included a large clinical sample of Hungarian children and adolescents with depressive history, of whom about 39% had lifetime comorbid anxiety disorder as well.Poor regulation of emotions appears to be a factor common to anxiety and depression, but the nature of ER in comorbid patients has not been fully characterized. In fact, there is scant information about how anxiety as a comorbid condition affects the habitual use of different ER strategies in depressed youngsters. Queen and Ehrenreich-May  found thThe current study extended previous findings in several ways: We examined multiple adaptive and maladaptive ER strategies; we used a large clinical sample of youngsters with childhood onset depression; and our sample was carefully diagnosed by trained psychiatrists and psychologists. We found that anxiety comorbidity in youngsters with lifetime depression was associated with dysfunctional ER, as children with comorbidity used maladaptive ER responses more frequently than non-comorbid peers. Our results are in line with findings from previous studies that showed more frequent use of maladaptive ER strategies in youths with comorbid depression and anxiety symptoms , 37, 47.We found in our clinical sample that the presence or absence of anxiety comorbidity in patients with depression histories made no significant difference to these two groups’ use of adaptive ER responses. Our results are in line with those of Aldao et al. , whose mOur study can also serve to augment existing data on the possible role of dysfunctional ER in internalizing psychopathology. In our study of youths diagnosed with lifetime comorbid depression and anxiety, we examined not only their cognitive strategies but also their coping strategies in the social and behavioral domains. When comparing ER response clusters, we found that youths with comorbid anxiety and depression were more likely to use maladaptive social and behavioral/physical responses than were their depressed peers without anxiety. Social withdrawal (“hide from people”) within the Social domain can be considered as social avoidant strategy consistent with the nature of anxiety. As reported by Schafer et al. , avoidanFinally, these findings suggest that patients with comorbid depression and anxiety may benefit from psychotherapeutic methods that aim to replace maladaptive ER responses with adaptive ones , 52, 53.Limitations of this research should also be mentioned. Since our study was cross-sectional, it was not possible to examine the causal relationship among the internalizing disorders and ER. We did not have enough subjects in current MDD and anxiety episodes in order to stratify our groups according to present or past diagnoses.The datasets generated for this study are available on request to the corresponding author.This study was carried out in accordance with the recommendations of Federalwide Assurance for the Protection of Human Subjects with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Institutional Review Board (IRB number: IRB00003344) and Medical Research Council .MK, KK, ÁV, EK, and IB conceptualized and received funding for the study. MK, KK, ÁV, EK, IB, EL, LB, IY, and JR planned and executed the study protocol. RD, KK, ÁV, EK, and IB contributed to data analysis and writing of the manuscript. RD, MK, KK, ÁV, EK, and IB assisted with the analysis of the data and contributed to the final draft of the manuscript.This study was supported by NIH Grant MH084938-01 and by Hungarian Scientific Research Fund Grant NN85285.The authors declare that the research was conducted in the absence of any commercial or financial relationship that could be construed as a potential conflict of interest.


Background: There are no recent estimates of incidence rates of mild traumatic brain injury (MTBI) from Norway. Moreover, reported incidence rates rarely comprise cases of MTBI evaluated in the primary care setting. In this study, we utilized existing data collected as part of the recruitment to a large, follow-up study of patients with MTBI. We estimated the incidence rate of MTBI, including patients who visited outpatient clinics, in the age group 16–59 years in a Norwegian region.Methods: During 81 weeks in 2014 and 2015, all persons aged 16–59 years, presenting with possible MTBI to the emergency department (ED) at St. Olavs Hospital, Trondheim University Hospital or to the general practitioner (GP)-run Trondheim municipal outpatient ED, were evaluated for a diagnosis of MTBI. Patients were identified by computerized tomography (CT) referrals and patient lists. Patients referred to acute CT from their primary GP with suspicion of MTBI were also recorded. This approach identified 732 patients with MTBI. Age- and sex-specific incidence rates of MTBI were calculated using population figures from the regional catchment area.Results: Overall incidence of MTBI in people between 16 and 59 years was 302 per 100,000 person-years . The incidence rate was highest in the age group 16–20 years, where rates were 835 per 100,000 person-years in males and 726 in females.Conclusion: The overall incidence rate of MTBI was lower than expected from existing estimates. Like other reports, the incidence was highest in the late teens. Traumatic brain injury (TBI) is a complex injury comprising a spectrum from mild TBI (MTBI) with low risk of persistent disability, to the most severe TBI with devastating brain damage. However, MTBI constitutes 80–90 % of all TBI. It can therefore be appropriate to study characteristics of MTBI, such as incidence, separately. Moreover, a review recently highlighted that the monitoring of the epidemiology of MTBI was incomplete . InternaThe Nordic countries have been considered safe communities with a decreasing number of TBI , 11, butIn the present study, the aim was to estimate the incidence of MTBI in an adult population within a regional Norwegian catchment area. We utilized existing data collected as part of the recruitment to a large, prospective cohort study of patients with MTBI aged 16–59 years . Cases wPatients aged 16–59 years with MTBI were identified during 81 weeks between April 1st 2014 and December 5th 2015 in two emergency departments (ED): St. Olav's Hospital, Trondheim University Hospital, a Norwegian regional level 1 trauma center and the Trondheim Municipal Emergency clinic (only out-patients), run by the GPs in the area, working shifts. This ED is co-located at the hospital. Their catchment area for MTBI is mostly urban: the city of Trondheim and four neighboring municipal entities with 229,000 residents. The EDs are state run, like most health care in Norway. During normal weekday work hours, patients can contact either their primary GP at one of the 41 GP centers in the catchment area, or one of the EDs. After 3 p.m. on workdays and the whole weekend, patients present to one of the Eds, since the GP centers are closed Mostly, however, patients with mild TBI present directly to the municipal ED at all times of the day. During the study period, indication for CT was assessed with the Scandinavian Guidelines for Head Injury Management from 2000 . In thesTBI were further categorized as mild (MTBI) according to the WHO criteria: GCS score 13–15 at presentation, LOC <30 min, and posttraumatic amnesia (PTA) <24 h  <24 h . Patientlication .During the study period, 1,095 patients were examined with head CT due to trauma, 624 of these were evaluated to have MTBI. Furthermore, 79 patients who had not been examined with head CT, but who had been clinically evaluated to meet the MTBI criteria and enrolled in the original follow-up study were included in the incidence analysis. In addition, 29 patients were retrospectively identified as being directly referred to CT from their primary GP center. Hence, 732 patients were identified with MTBI . As receWe estimated age- and sex specific incidence per 100,000 person-years by dividing cases of MTBI during the study period by the population at risk, i.e., total population of catchment area. Cases of MTBI were identified from; (1) all patients who had head CT at the study hospital and who met the diagnostic criteria for MTBI; (2) patients meeting MTBI criteria who eventually consented to participation in the longitudinal study, but who had not been examined with head CT; and (3) patients who had been referred directly to head CT by their primary GPs in the catchment area, and were considered to meet the diagnostic criteria.The population at risk was obtained from the Norwegian National Registry and Norwegian State Educational Loan Fund, and the total number of people, as well as number of men and women between 16.0 and 59.9 years residing in the catchment area was extracted. This figure included students attending school/college/university in the area, but who had home address elsewhere, and conversely, excluded students with a home address in the catchment area, but who attended school/college/university elsewhere. For the computation of incidence rates, we used the Stata Statistical Software: Release 12. College Station, TX: Stata Corp LP (2011).Applying the total of 732 patients who had been identified with MTBI in the catchment area, the overall incidence rate of MTBI in persons aged 16–59 years was 302 per 100,000 person-years . The incidence rate was 357  in males and 242  in females. The rate was highest in the age group 16–20 years, where males had a rate of 835 per 100,000 person-years and females a rate of 726 per 100,000 person-years. The estimated incidence rates in this study were derived from visits at all medical services available for patients with acute MTBI; the hospital, the GP-run municipal out-patient ED, and the primary GPs in the catchment area. Importantly, 71% were treated without hospital admission. Few other epidemiological studies report such complete coverage. A population-based study from a region in New Zealand also applied case ascertainment at the community level as well as the WHO criteria for MTBI . They foIn contrast, the incidence rate found in the present study corresponds with an overall incidence rate of 354 per 100,000 person-years found in a population based Swedish study of all TBI, where the proportion of MTBI was 97.5% . The SweIn line with most previous studies , 19, 26,more than 24 h after injury, are more likely to present to their GP, and may not be examined with CT is the risk of intracranial bleeding is over.We assume, however, that the incidence of MTBI was underestimated in the present study since there will always be missed cases of MTBI in a screening process. First, our study procedures did not capture patients seen only by their primary GP unless they were referred to CT, and results must be interpreted with some caution. While it is most common that patients with acute MTBI present directly to the municipal ED, patients who present Second, we did not register patients not examined with CT, yet meeting criteria for MTBI, unless they were enrolled in the follow-up study. In the recruitment to the follow-up study, we experienced that around 50% of eligible patients eventually got enrolled . Hence, Since there is a large university in the catchment area, there were many students in the population at risk, and the average level of education in the population may be somewhat higher than in Norway as a whole. The incidence of MTBI might therefore not be the same in more rural parts of the country.Taken together, MTBI was estimated to be less frequent in this Norwegian area than in many other high-income countries, especially among persons older than 20 years. A similar trend has also been shown in previous Norwegian epidemiological studies of all hospitalized  and all In summary, our data indicate that the incidence of medically evaluated MTBI in Norway is lower than 600 per 100,000 person-years anticipated in a recent review, but likely higher than 302 per 100,000 person-years as computed here due to inherent difficulties identifying all MTBI cases as discussed above.The Regional committee for research ethics approved the study . According to this approval, patients in the follow-up study gave written consent, while consent was not required for use of the information obtained via the screening and case ascertainment procedures.TS, IN, DM, AH, and AV designed the study. TS and TN performed the analyses. TS, IN, and CE collected the data. TS drafted the manuscript. All authors critically reviewed the manuscript. All authors read and approved the last version of this manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


F-values and P-values using the R programming language. We obtained an average highest accuracy of 92.7% using level-1 wavelet texture and colour features. The MLP classifier performed well, and our study shows promising results based on multi-feature classification of histological sections of prostate carcinomas.Microscopic biopsy images are coloured in nature because pathologists use the haematoxylin and eosin chemical colour dyes for biopsy examinations. In this study, biopsy images are used for histological grading and the analysis of benign and malignant prostate tissues. The following PCa grades are analysed in the present study: benign, grade 3, grade 4, and grade 5. Biopsy imaging has become increasingly important for the clinical assessment of PCa. In order to analyse and classify the histological grades of prostate carcinomas, pixel-based colour moment descriptor (PCMD) and gray-level co-occurrence matrix (GLCM) methods were used to extract the most significant features for multilayer perceptron (MLP) neural network classification. Haar wavelet transformation was carried out to extract GLCM texture features, and colour features were extracted from RGB (red/green/blue) colour images of prostate tissues. The MANOVA statistical test was performed to select significant features based on  The diagnosis of medical images is relatively challenging, and the purpose of digital medical image analysis is to extract meaningful information to support disease diagnosis. At present, an enormous quantity of medical images is produced worldwide in hospitals, and the database of these images is expected to increase exponentially in the future. The analysis of medical images is the science of solving medical problems based on different imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, mammography, radiography X-ray, biopsy, and combined modalities, among others. To study detailed tissue structures, pathologists use different histological methods, such as the paraffin technique, frozen sections, and semi-thin sections. The biopsy technique is used to remove a piece of tissue from the body so that it can be analysed in a laboratory. Most cells contained in the tissue are colourless, and therefore this histological section has to be stained to make the cells visible. The most commonly used stain is haematoxylin and eosin (H&E). H&E are chemical compounds used in histology to stain tissue and cell sections pink and blue, respectively .CKAP2 and MKI67 genes, respectively. Ki-67 is a cellular marker that is used to measure the growth rate of cancer cells, and a high percentage (over 30%) for Ki-67 means that the cancer is likely to grow and spread more quickly.Immunocytochemistry is a common laboratory technique that is used to automatically visualise the localisation of a specific protein and analyse the cells by use of a specific primary antibody that binds it. Paraffin-embedded cell blocks are not commonly used in most laboratories. Preferably, non-paraffin-embedded cells are employed in subcellular localisation studies, and fluorescence is used instead of chromogen. For the determination of protein expression levels, immunofluorescent staining is the commonly used method in research employing cell cultures. Moreover, immunofluorescent staining slides require protection from bright light while preserving cells morphological information. Cytoskeleton-associated protein 2 (CKAP2) and Ki-67 are proteins in humans that are encoded by the Prostate cancer (PCa) is a malignancy that may develop into metastatic disease and is most common in men older than 60 years of age ,3. DiagnThe image analysis of histological sections holds promise for cancer diagnosis and monitoring disease progression. Compared with Western PCa patients, Korean patients exhibit high scores for risk factors such as high Gleason scores and increased prostate volume. Gleason grading is an important metric in PCa. This system is used to evaluate the prognosis of men with PCa using samples from a prostate biopsy . CancersA statistical approach, especially the GLCM texture analysis method, is very common in a medical image analysis and processing system. Textures are generally random and possess consistent properties. Various features based on gray-level intensity computed from a digital image can be used to describe statistical properties such as entropy, contrast, correlation, homogeneity, energy, dissimilarity. Another way to analyse image texture is the use of the frequency domain because it contains information from all parts of the image and is useful for global texture analysis. In order to extract meaningful information from an image, wavelet transformation was performed in this paper for texture analysis.Feature extraction is very important when performing cancer grading using biopsy images. Generally, the classification of PCa grading is carried out based on morphological, texture, nuclei cluster, architectural, and colour moment features. However, the current study focuses on wavelet transformation and colour histogram analysis for stained biopsy tissue image processing. At present, automated computerised techniques are in high demand for medical image analysis and processing, and the multilayer perceptron (MLP) is a commonly used technique for feature classification. Texture and colour features are highly significant in tissue image analysis and provide information about the intensity and distribution of colour in an image. The arrangement of the glands and cell nuclei in tissue images and their shape and size differ among Gleason grade groups, shown in Ethical Approval: All subjects’ written informed consent waived for their participation in the study, which was approved by the Institutional Ethics Committee at College of Medicine, Yonsei University, Korea (IRB no. 1-2018-0044). Prostate tissue images were obtained from the Severance Hospital of Yonsei University in Seoul, Korea. The size of the whole slide image was 33,584 × 70,352 pixels. These slides were scanned into a computer workstation at 40× optical magnification with a 0.3 NA objective using a digital camera (Olympus C-3000) attached to a microscope (Olympus BX-51), and images were cropped to a size of 512 × 512 pixels and 256 × 256 pixels. We used a total of 400 samples with an image size of 256 × 256 pixels, and each image slice had a resolution of 24 bits/pixel. The collected samples were divided into four groups: benign, grade 3, grade 4, and grade 5. The biopsy tissue was sectioned in 16H24O6. Eosin is negatively charged and can react with positively charged, acidophilic components, such as amino groups in proteins in the cytoplasm. The stain colour for this compound is pink, and the chemical formula is C20H6Br4Na2O5. The detail explanation of cell block preparation, tissue processing, and immunocytochemical analysis is in The H&E stain has been used for over a century and remains essential for identifying different tissue types. This stain reveals a broad range of nuclear, cytoplasmic, and extracellular-matrix features. Briefly, haematoxylin is used in combination with a “mordant”, which is a compound that helps it associate with the tissue. This compound is also called “hematin”, which is positively charged and can react with negatively charged, basophilic cell components, such as nucleic acids in the nucleus. The stain colour for this compound is blue, and the chemical formula is CMLP classification was performed using a combination of features extracted from microscopic biopsy images of tissue samples. We used a DWT algorithm for wavelet decomposition and computed the GLCM to extract texture features. Colour-feature extraction was also carried out for PCa grading. These features are suitable for the different pathology categories for image analysis chosen for the study. After Haar wavelet transformation, we generated the first and second levels of images and extracted features from each level depth. Artificial neural network (ANN) classification methods were used to classify prostate carcinomas. The proposed methodology in Wavelet functions are concentrated in time as well as in frequency around a certain point. The wavelet transform is most appropriate for non-stationary signals and basic functions, which vary both in frequency and spatial range. The wavelet transform is designed to provide good frequency resolution for low-frequency components, which are essentially the average intensity values of the image, and high temporal resolution for high-frequency components, which are basically the edges of the image. In the present study, a DWT was performed to divide the information of an image into approximation and detailed sub-signals and extract the most discriminative multi-scale features . In FiguThe simplest type of wavelet transform is called a Haar wavelet. It is related to a mathematical operation called the Haar transform. It is performed in several stages, or levels. Haar transform decomposes a discrete signal into two sub-signals of half its length ,9. One sormation ,11. FiguThere are two functions that play a primary role in wavelet analysis, the scaling function In colour moment analysis, a colour histogram is used to represent the colour distribution in microscopic biopsy tissue images. Colour information is a very important factor for tissue image analysis, and each peak of the histogram represents a different colour, as shown in Colour moment analysis is essential in digital medical image processing to carry out colour image enhancement or information retrieval. Two-dimensional (2D) grey-level co-occurrence matrix (GLCM) and colour moment techniques were used to extract texture and pixel-based colour moment features, respectively. Texture features were extracted from Haar wavelet-transformed images, and colour features were extracted from 8-bit grayscale images that were separated into three channels from an original colour image. We extracted a total of 11 features and carried out a multivariate analysis of variance (MANOVA) statistical test to identify the significant features ,14,15,16p(i – j) signifies the co-occurrence probability matrix for a combination of two pixels with intensity  that occur in an image, separated by a given distance. N signifies the quantized grey level, and xµ and yµ are the means, and i and column j, respectively, within the GLCM.GLCM is a statistical method that examines texture based on the spatial relationship of pixels. To analyse image texture, we first created a GLCM to calculate how often pairs of pixels with specific values and in a specified spatial relationship occurred in an image, and then extracted statistical measures from the matrix. The directions of the co-occurrence matrix for feature extraction were as follows: 0° , 45° , 90° , and 135° . So, the values of GLCM matrix are always within the range . The size of the GLCM matrix used for texture analysis was 128 × 128 and 64 × 64, for first- and second-level sub-images, respectively. GLCM texture features were separately extracted after wavelet transformation at level-1 and level-2 from each orientation, shown in The pixel-based colour moment descriptor (PCMD) technique was used to extract colour-based features from prostate tissue images. This technique is useful for analysing the colour distribution among the three different channels of RGB colour images. To extract useful colour moment features from tissue images, the three colour channels were separated from RGB colour images, as shown in MLP is a supervised classification system that consists of at least three layers of nodes: the first layer is the input layer, the middle layer is the hidden layer, and the last layer is the output layer. Input and output layers are used to feed in data and obtain the output results, respectively ,24,25,26To train the model, we input data into the model, multiplied the data with the weights, and obtained the computed output of the model, which is called a forward pass. We also carried out backward passes, in which model weight was updated based on the calculated loss from the expected and predicted outputs. The learning rate is a hyperparameter in the neural network that controls how the model is changed in response to the estimated error each time the model weight is updated based on the learning rate and momentum. Momentum is a technique that frequently improves both training speed and accuracy ,29. The F-values and P-values obtained from MANOVA statistical tests performed using the R programming language in RStudio. In the present study, we extracted wavelet-based texture and colour moment features for MLP neural network classification. Images were 256 × 256 pixels (24 bits/pixel) in size and were converted to 8 bits/pixel for wavelet transformation (first- and second-level), colour moment analysis, and feature extraction. A total of 400 images were used for PCa grading classification and were divided equally among four classes: benign, grade 3, grade 4, and grade 5. A ratio of 7:3 was fixed for training and test data sets, respectively. The algorithms used for image transformation, feature extraction, and classification were implemented in MATLAB R2018a and the WAIKATO environment ,31. We sAccuracy: How many TP and TN were obtained out of all outcomes among all samples.Sensitivity: The rate of correctly classifying samples positively.Specificity: The rate of correctly classifying samples negatively.F1-score: It is calculated using a combination of the “Precision” and “Recall” metrics. The precision metric indicates how many classified samples are relevant, and the recall metric represents how many relevant samples are classified.MCC: An index of the performance binary of classification. Indicates the correlation between the observed and predicted binary classification.We used a number of metrics to evaluate the performance of the classification model and deep learning algorithm, including accuracy, sensitivity, specificity, F1-score, and Matthew’s correlation coefficient (MCC). The four types of confusion matrices used for computing performance metrics were true positive (TP), true negative (TN), false positive (FP), and false negative (FN). The following metrics were used:The accuracy rates listed in The learning rate and momentum for each group classification changed based on the accuracy of the training and test dataset. The weighted average accuracy rates obtained from MLP Classifications 1 and 2 were 92.7% and 90.0%, respectively. The combination of texture and colour moment features in MLP Classification 1 produced the most accurate results using the neural network MLP technique. In neural network classification, the network parameters “Learning Rate” and “Momentum” were adjusted several times to accurately construct the network architecture and increase the accuracy for the test dataset. (a)It provides concurrent localisation in time and frequency domains.(b)Small wavelets can be used to separate fine details in an image, and large wavelets can identify coarse details.(c)An image can be de-noised without appreciable degradation.As shown in Haar and Daubechies wavelets are usually used to extract texture features, detect multi-resolution characteristics, and for texture discrimination and pattern recognition. However, in the current study, we used Haar wavelet features extracted from the detailed coefficients of the transformed image at levels 1 and 2. These features revealed the characteristics of the image and were used for classifying grades of cancer observed in histological sections. Texture analysis has been an important topic in image processing and computer vision. This method is an important issue in many areas like object recognition, image retrieval study, medical imaging, robotics and remote sensing. RGB colour images were used to extract colour moment features from each channel depth. Colour texture extraction is critically important for microscopic biopsy image analysis of histological tissue sections. Texture is a connected set of pixels that occurs repeatedly in an image, and it provides information about the variation in the intensity of a surface by quantifying properties such as smoothness, coarseness, and regularity. Therefore, we performed an MLP classification using a combination of colour and wavelet texture features. The performance measures we used to evaluate the classification results included accuracy, sensitivity, specificity, F1-score, and MCC.Our approach has been distinguishing different grade groups of prostate carcinoma: benign, grade 3, grade 4, and grade 5. In PCa grading system, grade 1 and grade 2 are classified as a benign/normal tumor, whereas grades 3, 4, and 5 are classified as a malignant/abnormal tumor. The Gleason grade groups, we used for MLP neural network classification are: “Benign vs. Malignant”, “Benign vs. Grade 3”, “Benign vs. Grade 4”, “Benign vs. Grade 5”, and “Grade 3 vs. Grades 4,5”. We have extracted six texture features  and five colour moment features , from 40× optical magnification biopsy images. After going through this research, it is clear that an image texture carries useful diagnostic information, which is very essential for medical image processing and discrimination with benign and malignant tumors. However, the proposed features are not sufficient to identify and discriminate between benign and malignant; it is necessary to identify and discriminate them with more reliable features. We have compared our proposed approach with the other methods to show the performance accuracy of each method achieved by using different types of features and classification groups, shown in Hae-Gil et al.  analysedFrom the above related works, it can be analysed that few authors used multi- and binary-classification. In this paper, our proposed approach is binary MLP neural network classification. Among all the authors described in Among all the binary classification approaches mentioned in In conclusion, biopsy tissue images are widely used for PCa diagnosis and to determine the level of malignancy for cancerous tissue. To determine the histological grades of PCa, biopsied tissue is stained with H&E and viewed by pathologists under a microscope. By applying DWT to predict the cancer grades in biopsy images, we were able to capture relevant information from the sub-band transformed images. Similarly, the colour moment technique can be used to extract the different types of colour information present in histological biopsy images. In the current study, a colour histogram was used to visualise the colour variation in tissue images. Our study shows that GLCM and PCMD methods can be used to extract significant features from histological images of prostate carcinomas. Haar wavelet transformation was carried out up to level-2, and texture features were separately extracted from sub-images at each level depth.Paraffin cell block preparation, tissue processing and paraffin embedding, and immunocytochemical analysis were carried out in the Severance Hospital of the Yonsei University, South Korea. It is very important to carry out de-paraffinization and rehydration process for staining the tissue slides using H&E chemical compounds.The present study employed an ANN method, and classification was performed using an MLP classifier. Wavelet-based texture and colour features have the potential to be used in the analysis of microscopic biopsy images of histological sections. According to the proposed model in