COL1A1 and FGFR2 Single-Nucleotide Polymorphisms Found in Class II and Class III Skeletal Malocclusions in Javanese Population.

OBJECTIVE: The aim of this article is to analyze and compare the presence of single-nucleotide polymorphisms (SNPs) of COL1A1 and FGFR2 in class II and class III Javanese populations. MATERIALS AND METHODS: Cephalometric radiographs from total 63 patients of class II and III were analyzed. SNP analysis was performed based on both COL1A1 and FGFR2 sequences amplified from total DNA of patients' fresh blood. Principal component analysis was done to calculate the data and find the correlation of the cephalometric indicators influenced by each mutation. t-test and Mann-Whitney analysis were performed to check the significance of differences occurred in each studied parameter (p < 0.05). RESULT: There were three COL1A1 SNPs found in class II and only two in class III, while three FGFR2 SNPs found in both classes. Class II phenotype seemed to be strongly influenced by Y-axis and mandibular plane angle, while class III by lower gonial angle and mandibular plane angle. CONCLUSION: Based on this study, we suggest that rs2249492 of COL1A1 and rs2981582 of FGFR2 play important roles in class III, while rs2277632 of COL1A1 and rs2981582 of FGFR2 play important role in class II skeletal malocclusion in Javanese population.

Electronic nose homogeneous data sets for beef quality classification and microbial population prediction.

OBJECTIVES: In recent years, research on the use of electronic noses (e-nose) has developed rapidly, especially in the medical and food fields. Typically, e-nose is coupled with machine learning algorithms to detect or predict multiple sensory classes in a given sample. In many cases, comprehensive and complete experiments are required to ensure the generalizability of the predictive model. For this reason, homogeneous data sets are important to use. Homogeneous data sets refer to the data sets obtained from different observations in almost similar environmental condition. In this data article, e-nose homogeneous data sets are provided for beef quality classification and microbial population prediction. DATA DESCRIPTION: This data set is originated from 12 type of beef cuts. The process of beef spoilage is recorded using 11 Metal-Oxide Semiconductor (MOS) gas sensors for 2220 min. The formal standards, issued by the Meat Standards Committee, are used as a reference in labeling beef quality. Based on the number of microbial populations, meat quality was grouped into four classes, namely excellent, good, acceptable, and spoiled. The data set is formatted in "xlsx" file. Each sheet represents one beef cut. Moreover, data sets are good cases for feature selection algorithm stability test, especially to solve sensor array optimization problems.

VIM Line Technique for Determining the Ventral Intermediate Location.

AIM: To prove that VIM line technique created by using a mathematical model, can be used to identify the location of the ventral intermediate nucleus of the thalamus (VIM) MATERIAL and METHODS: Eleven patients with Parkinson?s disease (PD) were assessed. To determine the VIM location, 3-T magnetic resonance imaging and stereotactic protocol 128-slice computed tomography were used. The VIM line technique was performed by drawing a line from the end-point of the right external globus pallidus to that of the left external globus pallidus in the intercommissural plane. PD severity was measured using the Unified Parkinson?s Disease Rating Scale (UPDRS). RESULTS: A mathematical model was constructed to describe the VIM line technique for determining the VIM location. UPDRS scores before and after thalamotomy showed a significant decreasing trend (p=0.003). CONCLUSION: The VIM line technique using the mathematical model can be considered a referential method to determine the VIM location. Its effectiveness was demonstrated by decreased UPDRS scores in patients after VIM thalamotomy.

Electronic nose dataset for pork adulteration in beef.

This article provides a dataset of several weight combinations from the adulteration of pork in beef using an electronic nose (e-nose). Seven combinations mixtures have been built, they were 100% pure beef, 10% mixed with pork, 25% mixed with pork, 50% mixed with pork, 75% mixed with pork, 90% mixed with pork, and 100% pure pork. By using this combination, a minimum of 10% of a mixture of pork or beef can be detected. In each experiment cycle, data were collected for 120 s using an e-nose. The availability of this dataset can enable further research about meat adulteration, Halal authentication, etc. For several cases, food adulteration is one of the main concerns in food science, for example, due to economic, religious reasons, etc. This dataset can also be utilized as the data source for several interesting topics such as signal processing, sensor selection, e-nose development, machine learning algorithms, etc.

Stereotactic aspiration of spontaneous intracerebral hematoma: Case series.

INTRODUCTION: Minimally invasive techniques such as stereotactic aspiration of spontaneous intracerebral hematoma (SICH) evacuation can minimize brain tissue damage due to surgery. We share our experience of adopting stereotactic aspiration of SICH in our center without compromising safety. PRESENTATION OF CASES: Three stereotactic aspiration procedures for SICH immediately after 24 h of onset are reported. All cases showed good results. Level of consciousness of all the patient returned to normal. Two patients could carry out routine activities independently. One patient has left hemiparesis. DISCUSSION: Stereotactic aspiration of SICH has been newly implemented at our center with acceptable results achieved. Patient selection has an important role in determining the choice of technique. The procedures were done without anticoagulant agent. Stereotactic aspiration of SICH is associated with limited brain tissue damage, shorter duration of surgery, reduced length of stay, faster postoperative healing, and better functional improvement. CONCLUSION: Stereotactic aspiration of SICH is a minimally invasive defined strategy for hematoma evacuation without compromising safety.

Vim line technique thalamotomy for Parkinson tremor: Case series.

INTRODUCTION: The ventral intermediate (Vim) nucleus of the thalamus is difficult to identify even with 3 T magnetic resonance imaging. Stereotactic Vim thalamotomy is a usual procedure to control Parkinson tremor. Successful relieving of the tremor depends on the accuracy of defining the Vim location. PRESENTATION OF CASES: Three patients with Parkinson tremor were subjected to stereotactic thalamotomy using the Vim line technique (VLT) so as to precisely determine the Vim location. All patients showed good results, with improved tremors, as indicated by the UPDRS score, without any complications. DISCUSSION: The precise targeting of the Vim nucleus is crucial importance for the successful Vim thalamotomy. Various method has been developed to determine Vim location. Atlas based and Guiot's technique routinely used by neurosurgeon. VLT is a new technique that has been developed to determine the Vim location on MRI. CONCLUSION: VLT is useful for the determination of the Vim location. However, further research is warranted to prove its effectiveness.

Electronic nose dataset for beef quality monitoring in uncontrolled ambient conditions.

In recent years, the development of a rapid, simple, and low-cost meat assessment system using an electronic nose (e-nose) has been the concern of researchers. In this data article, we provide a time series dataset that was obtained from a beef quality monitoring experiment using an e-nose in uncontrolled ambient conditions. The availability of this dataset will enable discussion on how to deal with noisy e-nose signals and non-optimum sensor array in beef quality monitoring. Hence, the development of proper signal processing and robust machine learning algorithm are several challenges that must be faced. Furthermore, this dataset can also be useful as a comparison dataset for similar e-nose applications, such as air quality monitoring, smart packaging system, and food quality monitoring.