Simulated pathogenic conformational switch regions matched well with the biochemical findings

Pathogenic conformational conversion is a general causation of many disease, such as transmissible spon- giform encephalopathy (TSE) caused by misfolding of prion, sickle cell anemia, and etc. In such structural changes, misfolding occurs in regions important for the stability of native structure firstly. This destabi- lizes the normal conformation and leads to subsequent errors in folding pathway. Sites involved in the first stage can be deemed switch regions of the protein, and are vital for conformational conversion. Namely it could be a switch of disease at residue level. Here we report an algorithm that can identify such sites computationally with an accuracy of 93%, by calculating the probability of the native structure of a short segment jumping to a mistake one. Knowledge of such switch sites could be used to target clinical therapy, study physiological and pathologic mechanism of protein, and etc.

Mitochondrial DNA Haplogroups M7b1 ' 2 and M8a Affect Clinical Expression of Leber Hereditary Optic Neuropathy in Chinese Families with the m.11778G -> A Mutation

Leber hereditary optic neuropathy (LHON) is the most extensively studied mitochondrial disease, with the majority of the cases being caused by one of three primary mitochondrial DNA (mtDNA) mutations. Incomplete disease penetrance and gender bias are two

In vitro activities of small peptides from snake venom against clinical isolates of drug-resistant Mycobacterium tuberculosis

The recent re-emergence of tuberculosis, especially the multidrug-resistant cases, has highlighted the importance of screening effective novel drugs against Mycobacterium tuberculosis. In this study, the in vitro activities of small peptides isolated from snake venom were investigated against multidrug-resistant M. tuberculosis. Minimum inhibitory concentrations (MICs) were determined by the Bactec TB-460 radiometric method. A small peptide with the amino acid sequence ECYRKSDIVTCEPWQKFCYREVTFFPNHPVYLSGCASECTETNSKWCCTTDKCNRARGG (designated as vgf-1) from Naja atra (isolated from Yunnan province of China) venom had in vitro activity against clinically isolated multidrug-resistant strains of M. tuberculosis. The MIC was 8.5 mg/l. The antimycobacterial domain of this 60aa peptide is under investigation. (C) 2003 Elsevier Science B.V. and the International Society of Chemotherapy. All rights reserved.

Multiplex detection of mutations in clinical isolates of rifampin-resistant Mycobacterium tuberculosis by short oligonucleotide Ligation assay on DNA chips

A new approach, short-oligonucleotide-ligation assay on DNA chip (SOLAC), is developed to detect mutations in rifampin-resistant Mycobacterium tuberculosis. The method needs only four common probes to detect 15 mutational variants of the rpoB gene within 12 h. Fifty-five rifampin-resistant M. tuberculosis isolates were analyzed, resulting in 87.3% accuracy and 83.6% concordance relative to DNA sequencing.

Mathematical symbols and computing methods in high dimensional biomimetic informatics and their applications

High dimensional biomimetic informatics (HDBI) is a novel theory of informatics developed in recent years. Its primary object of research is points in high dimensional Euclidean space, and its exploratory and resolving procedures are based on simple geometric computations. However, the mathematical descriptions and computing of geometric objects are inconvenient because of the characters of geometry. With the increase of the dimension and the multiformity of geometric objects, these descriptions are more complicated and prolix especially in high dimensional space. In this paper, we give some definitions and mathematical symbols, and discuss some symbolic computing methods in high dimensional space systematically from the viewpoint of HDBI. With these methods, some multi-variables problems in high dimensional space can be solved easily. Three detailed algorithms are presented as examples to show the efficiency of our symbolic computing methods: the algorithm for judging the center of a circle given three points on this circle, the algorithm for judging whether two points are on the same side of a hyperplane, and the algorithm for judging whether a point is in a simplex constructed by points in high dimensional space. Two experiments in blurred image restoration and uneven lighting image correction are presented for all these algorithms to show their good behaviors.

High-Dimensional Space Geometrical Informatics and its applications to image restoration

With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

High-Dimensional Space Geometrical Informatics and its applications to image restoration

With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

The development of long - Term ambulatory pH monitoring system and its clinical application

This paper introduced a long-term ambulatory intragastric pH monitoring system, which is designed for prolonged ambulatory studies of Gastroesophageal Reflux Diseases. The whole system is composed of the gastric catheter with two pH sensors, a small data logger (Microdatalog), and a notebook PC. In this paper, the design of monitoring system hardware and software are described in detail. Clinical applications reveal good results.

重离子束治疗皮肤恶性肿瘤的初步临床结果；Clinical trial of carbon ion radiotherapy for malignant neoplasm of skin

目的:评价重离子束对皮肤恶性肿瘤放射治疗的近期疗效和毒副反应。方法:29例皮肤恶性肿瘤患者分6批接受重离子束放射治疗,其中恶性黑色素瘤13例,皮肤鳞癌及Bowen’s病各6例,基底细胞癌2例,其他皮肤恶性肿瘤2例。照射总剂量(50～70)GyE/(6～12)d,单次剂量5.5～11.67GyE,1f/d,连续治疗。采用RTOG标准和WHO近期疗效标准分别评价毒副反应和近期疗效。结果:截止2009-05,中位随访时间为13.5个月(1～25个月),随访率为100%。29例患者中完全缓解(CR)24例(82.8%),部分缓解(PR)5例(17.2%),有效率(RR)为100%,中位生存时间为22.8个月(95%CI:20.6～24.9)。皮肤反应0度11例(37.9%),Ⅰ度9例(31.0%),Ⅱ度6例(20.7%),Ⅲ度2例(6.9%),Ⅳ度1例(3.4%);血液毒副反应治疗前后无明显改变。结论:重离子束(12C6+)放射治疗皮肤恶性肿瘤近期疗效好,并发症轻,远期疗效、晚期副反应等尚需进一步长期全面的观察和更多的研究提供依据。

Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data

As a recently developed and powerful classification tool, probabilistic neural network was used to distinguish cancer patients from healthy persons according to the levels of nucleosides in human urine. Two datasets (containing 32 and 50 patterns, respectively) were investigated and the total consistency rate obtained was 100% for dataset 1 and 94% for dataset 2. To evaluate the performance of probabilistic neural network, linear discriminant analysis and learning vector quantization network, were also applied to the classification problem. The results showed that the predictive ability of the probabilistic neural network is stronger than the others in this study. Moreover, the recognition rate for dataset 2 can achieve to 100% if combining, these three methods together, which indicated the promising potential of clinical diagnosis by combining different methods. (C) 2002 Elsevier Science B.V. All rights reserved.

Artificial neural network classification based on high-performance liquid chromatography of urinary and serum nucleosides for the clinical diagnosis of cancer

Nucleosides in human urine and serum have frequently been studied as a possible biomedical marker for cancer, acquired immune deficiency syndrome (AIDS) and the whole-body turnover of RNAs. Fifteen normal and modified nucleosides were determined in 69 urine and 42 serum samples using high-performance liquid chromatography (HPLC). Artificial neural networks have been used as a powerful pattern recognition tool to distinguish cancer patients from healthy persons. The recognition rate for the training set reached 100%. In the validating set, 95.8 and 92.9% of people were correctly classified into cancer patients and healthy persons when urine and serum were used as the sample for measuring the nucleosides. The results show that the artificial neural network technique is better than principal component analysis for the classification of healthy persons and cancer patients based on nucleoside data. (C) 2002 Elsevier Science B.V. All rights reserved.