With the aging of the world's population, osteoporosis has emerged as a formidable health concern. Bone mineral density (BMD) is the only available clinical parameter for bone strength evaluation and is determined through the use of dual energy x-ray absorptiometry (DEXA), the gold standard for the diagnosis of osteoporosis, and peripheral DEXA, such as calcaneal quantitative ultrasonography (QUS). This is a cross-sectional, descriptive study which aimed to determine the prevalence of osteoporosis among Filipinos, based on T-scores utilizing calcaneal quantitative ultrasonography. Baseline bone mineral density of 20,726 Filipinos were gathered based on the T-scores from calcaneal quantitative ultrasound results. The WHO criteria standardized the classification of BMD based on T-scores. Results showed that 3 percent of Filipinos were osteoporotic, 22 percent were osteopenic, while the rest were normal. The female sex and advanced age were key determinants of osteoporotic risk wheareas geographic location appears to have no influence.
OSTEOPOROSIS ; CALCANEAL ; QUANTITATIVE ; ULTRASONOGRAPHY

Background: Deletion and duplication mutations of dystrophin gene make up from 70 to 75% of patients with Duchenne Muscular Dystrophy (DMD). Two thirds of children with DMD inherited from the heterozygous mothers the mutated gene which is located on one of the sex chromosomes. Objective: To detect the asymptomatic carriers of dystrophin gene mutation using molecular techniques. Subject and methods: 3 DMD patients and their 9 relatives. Using techniques: DNA extraction and quantitative Polymerase Chain Reaction (PCR). Results: Successfully detected 4 heterozygous individuals from 9 female members of three different families that have already confirmed DMD patients. Conclusion: This method could lead to a new way of prenatal diagnosis of DMD as well as other genetic disorders that are caused by deletion or duplication mutation.
Duchenne muscular dystrophy ; carrier ; quantitative PCR

The chemical characterization analysis of a medical device often results in chemical substances with unknown toxicities. While identification of each individual toxicity could result in a time-consuming hurdle with tremendous labor and financial burden, quantitative structure-activity relationship (QSAR) is of great significance for toxicity risk assessment of such chemical substances. By establishing quantitative relationship between the molecular structures or active groups of similar chemical compounds with their biological activities, QSAR can be utilized to predict the toxicity of such target compounds with significantly reduced cost and time. In this article, the authors generally summarized the mechanisms of QSAR approaches, current applications of QSAR modeling in the field of medical device, an introduction of the characteristics of publicly and commercially-available QSAR software, and briefly explored future trends of QSAR modeling in medical device toxicological risk assessment. The utilization of QSAR would undoubtedly further advance the toxicological risk assessment of medical devices.
Quantitative Structure-Activity Relationship ; Risk Assessment ; Software

Three dimensional quantitative structure activity relationship between diazabicyclo[4.2.0]octanes and nicotinic acetylcholine receptor (h alpha4beta2 and h alpha3beta4) agonists was studied using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). From 11 CoMFA and CoMSIA models, CoMSIA with steric and electrostatic fields gave the best predictive models (q2=0.926 and 0.945, r2(ncv)=0.983 and 0.988). This study can be used to develop potent h alpha4beta2 receptor agonists with low activity on h alpha3beta4 subtype.
Quantitative Structure-Activity Relationship ; Receptors, Nicotinic

OBJECTIVES: For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. METHODS: There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. RESULTS: We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. CONCLUSIONS: We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used with predicted toxicity results. Furthermore, by presenting the suitability of individual predicted results, we aimed to provide a foundation that could be used in actual assessments and regulations.
Humans ; Quantitative Structure-Activity Relationship* ; Reproducibility of Results ; Social Control, Formal

Carpamic acid was an alkaloid as a hydrolysate from carpamic alkaloid in the past. Today, the carpamic acid is extracted from leaves of carisa papaya L. by many ways and isolated by column chromatography so it is proven as originated from leaves of carica papaya L. caricaceae.
Quantitative dosage of the total alkaloids in the leaves of some species of branch Crinum. Amryllidaceae

Colorectal carcinoma ranks third among ten leading causes of cancer in Malaysia. The colorectal carcinoma tumourigenesis involves the inactivation of tumour suppressor genes, and activation of proto-oncogenes. The p53 is one of the tumour suppressor genes that is involved in the colorectal carcinogenesis. The p53 gene is located on human chromosome 17p13.1 and comprises of 11 exons. Deficiencies in the p53 gene can cause the cancerous cells to spread to distant organs such as liver, lungs, lymph nodes, spine and bone. The most common p53 abnormalities that can lead to the metastasis of colorectal tumours are mutation and deregulation of the gene. In this study, nine colorectal carcinoma samples were used to establish a simple and sensitive strategy in the study on in vivo p53 expression by using realtime LightCycler SYBR Green I technology.
Colorectal ; Genes, p53 ; Carcinoma ; Quantitative ; Polymerase Chain Reaction

Computational virtual screening has become an essential platform of drug discovery for the efficient identification of active candidates. Moleculardocking, a key technology of receptor-centric virtual screening, is commonly used to predict the binding affinities of chemical compounds on target receptors. Despite the advancement and extensive application of these methods, substantial improvement is still required to increase their accuracy and time-efficiency. Here, we evaluate several advanced structure-based virtual screening approaches for elucidating the rank-order activity of chemical libraries, and the quantitative structureactivity relationship (QSAR). Our results show that the ensemble-average free energy estimation, including implicit solvation energy terms, significantly improves the hit enrichment of the virtual screening. We also demonstrate that the assignment of quantum mechanical-polarized (QM-polarized) partial charges to docked ligands contributes to the reproduction of the crystal pose of ligands in the docking and scoring procedure.
Drug Discovery* ; Ligands ; Mass Screening* ; Quantitative Structure-Activity Relationship ; Reproduction ; Small Molecule Libraries

Cholesterol gallstone formation is influenced by environmental and genetic factors. Cholesterol gallstone susceptible genes (Lith genes) are complex and show polygenic traits. Quantitative trait locus (QTL) analysis in inbred mice is a powerful method for identifying these genetic defects. More than 20 Lith genes were discovered by QTL in inbred mice models. The co-localized, candidate genes responsible for gallstone susceptible QTL can lead to the discovery of pathophysiologic functions of Lith (gallstone) genes. These genetic studies may reveal novel molecular targets for prevention and medical therapy. Presently, the only effective treament for gallstone is cholecystectomy. In the future, new drugs targeting Lith genes can be available not only for the treatment of gallstone disease, but also for "pre-stone" diagnosis.
Animals ; Cholecystectomy ; Cholesterol* ; Diagnosis ; Gallstones* ; Mice ; Molecular Biology* ; Multifactorial Inheritance ; Quantitative Trait Loci

The alteration of alternative splicing patterns has an effect on the quantification of functional proteins, leading to phenotype variation. The splicing quantitative trait locus (sQTL) is one of the main genetic elements affecting splicing patterns. Here, we report the results of genome-wide sQTLs across 141 strains of Arabidopsis thaliana with publicly available next generation sequencing datasets. As a result, we found 1,694 candidate sQTLs in Arabidopsis thaliana at a false discovery rate of 0.01. Furthermore, among the candidate sQTLs, we found 25 sQTLs that overlapped with the list of previously examined trait-associated single nucleotide polymorphisms (SNPs). In summary, this sQTL analysis provides new insight into genetic elements affecting alternative splicing patterns in Arabidopsis thaliana and the mechanism of previously reported trait-associated SNPs.
Alternative Splicing ; Arabidopsis* ; Dataset ; Phenotype ; Polymorphism, Single Nucleotide ; Quantitative Trait Loci*