Composición química y cinética de degradación ruminal del ensilado de pasto elefante con inclusión de cáscara de maracuyá

Se evaluó los parámetros de composición química, degradación y cinética ruminal del ensilado de pasto elefante (Pennisetum purpureum) con inclusión  residuos de  cascara de maracuyá (Passiflora edulis). Se aplico un diseño de bloques completos al azar con cuatro tratamientos (T1:0%; T2:10%;  T3:20% ,k  30% T4:40%) de inclusión de residuos de maracuyá, tres bloques (bovinos con rumen fistulados)  y siete tiempos de incubación  ruminal (0, 3, 6, 12, 24, 48 y 72 horas).  Las diferencias entre medias de tratamientos se establecieron mediante la prueba de Tukey (p<0.05). Tras 30 días de almacenamientos se  aperturaron  los minisilos y fueron similares en materia seca (MS)  y diferentes  (p<0.05)  en materia orgánica (MO),  el T1 (81.73%) presentó  menor porcentaje que los T2, T3, T4 y T5( 85.32, 85.54, 84.57 y 82,02% correspondientemente ), la cenizas (Cen) T1(18.27%) fue mayor (p<0.05) a los  T1; T2; T3; T4 y T5  ( 14.86, 14.46, 15.43 y 17.987% en su orden), la proteína cruda (PC) el T1 (4.42%) fue  menor   (p<0.05), a mayor inclusión de  residuos de maracuyá  se incrementa  la PC en los T1; T2; T3; T4 y  T5  (5.693; 5.25; 5.58 y 5.59%)  y el extracto etereo (EE) el T5: (0.90%)  fue diferente (p<0.05)  con los   T1; T2; T3 y  T4 (1.10; 1.43, 1.18 y 0.92% en su orden). Los contenidos de FDN y FDA fue mayor el T1 con (79.19 y 50.83% respectivamente), sin embargo, con la mezcla de 10% de RM (76.65 y 48.87%), 20% de RM (76.81 y 47.49%%) y 30% de RM (74.98 y 45.74%) se redujeron los porcentajes de fibra detergente neutra y ácida  (FDN y FDA). El porcentaje de digestibilidad in situ  de la materia seca    fue similar  (p>0.05) a las 0, 3, 6 12, 48 y 72 horas de incubación ruminal con la  inclusión de residuos de maracuyá  en el  pasto elefante y aumenta la degradabilidad del ensilaje y la cinética de degradación es similar

(Pre)treatment risk factors for late fatigue and fatigue trajectories following radiotherapy for breast cancer

Breast cancer; Fatigue; RadiotherapyCáncer de mama; Fatiga; RadioterapiaCàncer de mama; Fatiga; RadioteràpiaFatigue is common in breast-cancer survivors. Our study assessed fatigue longitudinally in breast cancer patients receiving adjuvant radiotherapy (RT) and aimed to identify risk factors associated with long-term fatigue and underlying fatigue trajectories. Fatigue was measured in a prospective multicenter cohort (REQUITE) using the Multidimensional Fatigue Inventory (MFI-20) and analyzed using mixed models. Multivariable logistic models identified factors associated with fatigue dimensions at 2 years post-RT and latent class growth analysis identified individual fatigue trajectories. A total of 1443, 1302, 1203 and 1098 patients completed the MFI-20 at baseline, end of RT, after 1 and 2 years. Overall, levels of fatigue significantly increased from baseline to end of RT for all fatigue dimensions (P < .05) and returned to baseline levels after 2 years. A quarter of patients were assigned to latent trajectory high (23.7%) and moderate (24.8%) fatigue classes, while 46.3% and 5.2% to the low and decreasing fatigue classes, respectively. Factors associated with multiple fatigue dimensions at 2 years include age, BMI, global health status, insomnia, pain, dyspnea and depression. Fatigue present at baseline was consistently associated with all five MFI-20 fatigue dimensions (ORGeneralFatigue = 3.81, P < .001). From latent trajectory analysis, patients with a combination of factors such as pain, insomnia, depression, younger age and endocrine therapy had a particularly high risk of developing early and persistent high fatigue years after treatment. Our results confirmed the multidimensional nature of fatigue and will help clinicians identify breast cancer patients at higher risk of having persistent/late fatigue so that tailored interventions can be delivered.We thank all patients who participated in the REQUITE study and all the REQUITE staff involved in this project. Belgium: Ghent University Hospital; KU Leuven. France: ICM Montpellier, CHU Nîmes (Department of Radiation Oncology, CHU Nîmes, Nîmes, France). Germany: Zentrum für Strahlentherapie Freiburg (Dr. Petra Stegmaier); Städtisches Klinikum Karlsruhe (Dr. Bernhard Neu); ViDia Christliche Kliniken Karlsruhe (Prof. Johannes Claßen); Klinikum der Stadt Ludwigshafen GmbH (PD Dr. Thomas Schnabel); Universitätsklinikum Mannheim: Anette Kipke and Christiane Zimmermann; Strahlentherapie Speyer (Dr. Jörg Schäfer). The researchers at DKFZ also thank Anusha Müller, Irmgard Helmbold, Thomas Heger, Sabine Behrens, Axel Benner, Nicholas Schreck. Petra Seibold is supported by ERA PerMed 2018 funding (BMBF #01KU1912) and BfS funding (#3619S42261). Italy: Fondazione IRCCS Istituto Nazionale dei Tumori, Milano; Candiolo Cancer Institute – FPO, IRCCS. Tiziana Rancati was partially funded by Fondazione Italo Monzino. The Netherlands: Sylvie Canisius at Maastro Clinics, Maastricht. Spain: Barcelona: Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus; VHIO acknowledge the Cellex Foundation for providing research facilities and thank CERCA Programme/Generalitat de Catalunya for institutional support. Sara Gutiérrez-Enríquez is supported by ERAPerMed JTC2018 funding (ERAPERMED2018-244 and SLT011/18/00005). Santiago: Complexo Hospitalario Universitario de Santiago. Ana Vega: supported by Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds (PI22/00589, PI19/01424; INT20/00071); the ERAPerMed JTC2018 funding (AC18/00117); the Autonomous Government of Galicia (Consolidation and structuring program: IN607B), by the Fundación Mutua Madrileña (call 2018) and by the AECC (PRYES211091VEGA); UK: University Hospitals of Leicester NHS Trust; Theresa Beaver, Kaitlin Walker and Sara Barrows. Dr Tim Rattay was funded by a National Institute of Health Research (NIHR) Clinical Lectureship (CL 2017-11-002) and is currently supported by the NIHR Leicester Biomedical Research Centre. He was previously funded by a National Institute of Health Research (NIHR) Doctoral Research Fellowship (DRF 2014-07-079). This publication presents independent research funded by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Manchester: Catharine West and Rebecca Elliott are supported by NIHR Manchester Biomedical Research Centre and Catharine West is supported by Cancer Research UK (C1094/A18504, C147/A25254). USA: Mount Sinai Hospital, New York. Open Access funding enabled and organized by Projekt DEAL

Elaboración de Ensilaje de Maíz Forrajero (Zea Mays) y Residuos de Banano Verde (Musa Paradisiaca) para Ovinos Tropicales

Background: Forage corn and green banana residue are potential options in silage production, the study was carried out to evaluate the chemical composition of forage corn silage and green banana rejection in different proportions in a base diet. Objective: To meet the objective, microsilos containing the evaluated treatments were prepared: Methods: T1: 50% forage corn, 0% banana rejection; T2 45% forage corn, 5% banana rejection; T3: 40% forage corn, 10% banana rejection; T4: 35% forage corn, 15% banana rejection; T5: 30% forage corn, 20% banana rejection, in all treatments 27% dust, 20% soybean paste and 3% mineral salt were added, completing the base diet at 100%. The variables were evaluated: dry matter (DM), organic matter (OM), inorganic matter (IM), crude fiber (FB), crude fat (GB), gross energy (EB), crude protein (CP), fiber fractions : neutral detergent fiber (NDF) and acid detergent fiber (ADF). A completely randomized design (DCA) was used. The evaluated variables were subjected to the analysis of variance and the Tukey test at 5% probability. Results: T4 and T5 reported significant values ​​in DM while MI and PB demonstrated similar values ​​in their treatments, however, T1 obtained the highest PB content (18.62%). The BE of the base diet did not present differences. The fiber fractions do not influence the composition of NDF and ADF in the analyzes carried out.Antecedentes: El maíz forrajero y el residuo de banano verde son opciones potenciales en la producción de ensilaje, el estudio se realizó para evaluar la composición química de ensilaje de maíz forrajero y rechazo de banano verde en diferentes proporciones en una dieta base. Objetivo: Para cumplir con el objetivo, se prepararon microsilos que contenían los tratamientos evaluados: Métodos: T1: 50% maíz forrajero, 0% rechazo de banano; T2 45% maíz forrajero, 5% rechazo de banano; T3: 40% maíz forrajero, 10% rechazo de banano; T4: 35% maíz forrajero, 15% rechazo de banano; T5: 30% maíz forrajero, 20% rechazo de banano, en todos los tratamientos se agregaron polvillo 27%, pasta de soya 20% y sal mineral 3% completando la dieta base al 100%. Se evaluaron las variables: materia seca (MS), materia orgánica (MO), materia inorgánica (MI), fibra bruta (FB), grasa bruta (GB), energía bruta (EB), proteína bruta (PB), fracciones de fibra: fibra detergente neutra (FDN) y fibra detergente ácida (FDA). Se empleó un diseño completamente al azar (DCA). Las variables evaluadas fueron sometidas al análisis de varianza y a la prueba de Tukey al 5% de probabilidad. Resultados: El T4 y T5 reportaron valores significativos en MS mientras que la MI y la PB demostraron valores similares en sus tratamientos, sin embargo, el T1 obtuvo el mayor contenido de PB (18,62%). La EB de la dieta base no presentó diferencias. Las fracciones de fibra no influyen en la composición de FDN y FDA en los análisis realizados

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types

Meta-genome; Toxicities; CancerMetagenoma; Toxicidades; CáncerMetagenoma; Toxicitats; CàncerBackground This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung). Methods A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV—formerly SNP)–based heritability of rSTATacute in all patients and for each cancer type. Results Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified ‘RNA splicing via endonucleolytic cleavage and ligation’ (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected). Conclusions There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta–genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.E.N. was supported by a scholarship for a PhD from the University of Groningen, Groningen, The Netherlands. T.D. is funded as an Academic Clinical Fellow by the National Institute for Health Research, UK. D.J.T. is supported by a grant from The Taylor Family Foundation and Cancer Research UK [C19941/A30286]. M.L.K.C. is supported by the National Medical Research Council Singapore Clinician Scientist Award (NMRC/CSA-INV/0027/2018), National Research Foundation Proton Competitive Research Program (NRF-CRP17-2017-05), Ministry of Education Tier 3 Academic Research Fund (MOE2016-T3-1-004), the Duke-NUS Oncology Academic Program Goh Foundation Proton Research Programme, NCCS Cancer Fund, and the Kua Hong Pak Head and Neck Cancer Research Programme. G.C.B. is supported by Cancer research UK RadNet Cambridge [C17918/A28870]. RADIOGEN research was supported by Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds (INT20/00071, INT15/00070, INT17/00133, INT16/00154; PI19/01424; PI16/00046; PI13/02030; PI10/00164); by AECC grant PRYES211091VEGA and through the Autonomous Government of Galicia (Consolidation and structuring program: IN607B). C.N.A. and L.M.H.S. received funding from the Danish Cancer Society (grant R231-A14074-B2537). T.R. was funded by a National Institutes of Health Research (NIHR) Clinical Lectureship (CL 2017-11-002) and is supported by the NIHR Leicester Biomedical Research Centre. This publication presents independent research funded by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. REQUITE received funding from the European Union’s Seventh Framework Programme for research, technological development, and demonstration under grant agreement No. 601826. S.G.E. is supported by the government of Catalonia 2021SGR01112. L.D. was supported by the European Union Horizon 2020 research and innovation programs BRIDGES (grant No. 634935)

Small Deletion Variants Have Stable Breakpoints Commonly Associated with Alu Elements

Copy number variants (CNVs) contribute significantly to human genomic variation, with over 5000 loci reported, covering more than 18% of the euchromatic human genome. Little is known, however, about the origin and stability of variants of different size and complexity. We investigated the breakpoints of 20 small, common deletions, representing a subset of those originally identified by array CGH, using Agilent microarrays, in 50 healthy French Caucasian subjects. By sequencing PCR products amplified using primers designed to span the deleted regions, we determined the exact size and genomic position of the deletions in all affected samples. For each deletion studied, all individuals carrying the deletion share identical upstream and downstream breakpoints at the sequence level, suggesting that the deletion event occurred just once and later became common in the population. This is supported by linkage disequilibrium (LD) analysis, which has revealed that most of the deletions studied are in moderate to strong LD with surrounding SNPs, and have conserved long-range haplotypes. Analysis of the sequences flanking the deletion breakpoints revealed an enrichment of microhomology at the breakpoint junctions. More significantly, we found an enrichment of Alu repeat elements, the overwhelming majority of which intersected deletion breakpoints at their poly-A tails. We found no enrichment of LINE elements or segmental duplications, in contrast to other reports. Sequence analysis revealed enrichment of a conserved motif in the sequences surrounding the deletion breakpoints, although whether this motif has any mechanistic role in the formation of some deletions has yet to be determined. Considered together with existing information on more complex inherited variant regions, and reports of de novo variants associated with autism, these data support the presence of different subgroups of CNV in the genome which may have originated through different mechanisms

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan. [Abstract copyright: © 2022 The Authors.

A survey of the clinicopathological and molecular characteristics of patients with suspected Lynch syndrome in Latin America

Background: Genetic counselling and testing for Lynch syndrome (LS) have recently been introduced in several Latin America countries. We aimed to characterize the clinical, molecular and mismatch repair (MMR) variants spectrum of patients with suspected LS in Latin America. Methods: Eleven LS hereditary cancer registries and 34 published LS databases were used to identify unrelated families that fulfilled the Amsterdam II (AMSII) criteria and/or the Bethesda guidelines or suggestive of a dominant colorectal (CRC) inheritance syndrome. Results: We performed a thorough investigation of 15 countries and identified 6 countries where germline genetic testing for LS is available and 3 countries where tumor testing is used in the LS diagnosis. The spectrum of pathogenic MMR variants included MLH1 up to 54%, MSH2 up to 43%, MSH6 up to 10%, PMS2 up to 3% and EPCAM up to 0.8%. The Latin America MMR spectrum is broad with a total of 220 different variants which 80% were private and 20% were recurrent. Frequent regions included exons 11 of MLH1 (15%), exon 3 and 7 of MSH2 (17 and 15%, respectively), exon 4 of MSH6 (65%), exons 11 and 13 of PMS2 (31% and 23%, respectively). Sixteen international founder variants in MLH1, MSH2 and MSH6 were identified and 41 (19%) variants have not previously been reported, thus representing novel genetic variants in the MMR genes. The AMSII criteria was the most used clinical criteria to identify pathogenic MMR carriers although microsatellite instability, immunohistochemistry and family history are still the primary methods in several countries where no genetic testing for LS is available yet. Conclusion: The Latin America LS pathogenic MMR variants spectrum included new variants, frequently altered genetic regions and potential founder effects, emphasizing the relevance implementing Lynch syndrome genetic testing and counseling in all of Latin America countries.Radium Hospital Foundation (Oslo, Norway) in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript, Helse Sør-Øst (Norway) in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript, the French Association Recherche contre le Cancer (ARC) in the analysis, and interpretation of data, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (Gefluc) in the analysis, and interpretation of data, the Association Nationale de la Recherche et de la Technologie (ANRT, CIFRE PhD fellowship to H.T.) in the analysis, and interpretation of data and by the OpenHealth Institute in the analysis, and interpretation of data. Barretos Cancer Hospital received financial support by FINEP-CT-INFRA (02/2010)info:eu-repo/semantics/publishedVersio

REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer

Purpose: REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data. Methods: An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated. Results: The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician-(47,025 forms) and patient-(54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade >= 2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung). Conclusion: The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers. Patient summary: Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short-and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity

Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis