Structural elucidation of phosphoglycolipids from strains of the bacterial thermophiles Thermus and Meiothermus.

The structures of two major phosphoglycolipids from the thermophilic bacteria Thermus oshimai NTU-063, Thermus thermophilus NTU-077, Meiothermus ruber NTU-124, and Meiothermus taiwanensis NTU-220 were determined using spectroscopic and chemical analyses to be 2'-O-(1,2-diacyl-sn-glycero-3-phospho) -3'-O-(alpha-N-acetyl-glucosaminyl)-N-glyceroyl alkylamine [PGL1 (1)] and the novel structure 2'-O-(2-acylalkyldio-1-O-phospho)-3'-O-(alpha-N-acetylglucosaminyl)-N-glyceroyl alkylamine [PGL2 (2)]. PGL2 (2) is the first phosphoglycolipid identified with a 2-acylalkyldio-1-O-phosphate moiety. The fatty acids of the phosphoglycolipids are mainly iso-C(15:0), -C(16:0), and -C(17:0) and anteiso-C(15:0) and -C(17:0). The ratios of PGL2 (2) to PGL1 (1) are significantly altered when grown at different temperatures for three strains, T. thermophilus NTU-077, M. ruber NTU-124, and M. taiwanensis NTU-220, but not for T. oshimai NTU-063. Accordingly, the ratios of iso- to anteiso-branched fatty acids increase when grown at the higher temperature

Photoproducts of indomethacin exhibit decreased hydroxyl radical scavenging and xanthine oxidase inhibition activities

AbstractIndomethacin (IN) is a widely used nonsteroidal anti-inflammatory drug. In this study, four photoproducts of IN (IN1–IN4) were produced and isolated from photoirradiated IN. This study investigated the abilities of IN and its photoproducts to scavenge hydroxyl radicals and inhibit xanthine oxidase (XO). The hydroxyl radical-scavenging activity was measured in vitro by electron spin resonance spectrometry using 5,5-dimethyl-1-pyrroline-N-oxide as a spin trapping agent. Enzyme activity was measured by continuous monitoring of uric acid formation, using xanthine as a substrate. The results showed that, among all the related products, IN has the strongest hydroxyl radical-scavenging (IC50 = 65 μM) and XO inhibitory (IC50 = 86 μM) effects. To further understand the stereochemistry of the reactions between these IN derivatives and XO, we performed computer-aided molecular modeling. IN was the most potent inhibitor with the most favorable interaction in the reactive site. Various photoproducts exhibited affinity toward XO as a result of the absence of hydrogen bonding with molybdopterin domain

Effects of Functional Electrical Stimulation on Peak Torque and Body Composition in Patients with Incomplete Spinal Cord Injury

The aim of this study was to investigate the change in body composition, leg girths, and muscle strength of patients with incomplete spinal cord injury (SCI) after functional electrical stimulation cycling exercises (FESCE). Eighteen subjects with incomplete SCI were recruited. Each patient received FESCE three times per week for 8 weeks. Body composition, thigh and calf girths of bilateral legs, muscle strength of bilateral knee flexors and extensors were measured before and after 4 and 8 weeks of FESCE. A significant increase in bilateral thigh girth after 4 weeks of FESCE and significant increase in muscular peak torque of knee flexion and extension were found after 8 weeks of training. Besides, lean body mass increased significantly after complete treatment. FESCE can increase the thigh girth and muscular peak torque of patients with incomplete spinal cord injury

Clinical experience in intracranial stenting of Wingspan stent system under local anesthesia

ObjectiveThe use of endovascular treatments for symptomatic intracranial atherosclerosis disease (ICAD) remains contentious due to high periprocedural complications. Many centers resort to general anesthesia for airway protection and optimal periprocedural conditions; however, this approach lacks real-time monitoring of patients’ neurological status during procedures. In this study, we employed intracranial stenting with the Wingspan system under local anesthesia to address this challenge.MethodsWe conducted a retrospective study of 45 consecutive ICAD patients who underwent intracranial stenting with the Wingspan system at our hospital from August 2013 to May 2021. These stenting procedures were performed under local anesthesia in a hybrid operation room. Neurological assessments were conducted during the procedure. The patients with periprocedural complications were analyzed for the risk factors.ResultsThe study included 45 ICAD patients (median age 62 years; 35 male and 10 female individuals). Among them, 30 patients had anterior circulation ICAD, and 15 had posterior circulation ICAD. The periprocedural complication rate was 8.9% (4/45), with an overall mortality rate of 2.2% (1/45). Notably, no procedure-related perforation complications were found, and all ischemic complications occurred in the perforating bearing artery, specifically in patients with stents placed in the middle cerebral artery or basilar artery, while no complications were observed in the non-perforating bearing artery of the internal carotid artery and vertebral artery (p = 0.04).ConclusionOur study demonstrates the safety and efficacy of the Wingspan stent system when performed on selected patients under local anesthesia. This approach seems to reduce procedural-related morbidity and be a safe intervention. In addition, it is crucial for surgeons to be aware that patients with perforator-bearing artery stenosis may be at a higher risk of complications

Tooth Position Determination by Automatic Cutting and Marking of Dental Panoramic X-ray Film in Medical Image Processing

This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, using the difference in pixel values to cut the image into several equal sections and then connecting each cavity feature point to extend a curve that completes the description of the separated jaw. The curve is shifted up and down to look for the gap between the teeth, to identify and address missing teeth and overlapping. Under FDI World Dental Federation notation, the left and right sides receive eight-code sequences to mark each tooth, which provides improved convenience in clinical use. According to the literature, X-ray film cannot be marked correctly when a tooth is missing. This paper utilizes artificial center positioning and sets the teeth gap feature points to have the same count. Then, the gap feature points are connected as a curve with the curve of the jaw to illustrate the dental segmentation. In addition, we incorporate different image-processing methods to sequentially strengthen the X-ray film. The proposed procedure had an 89.95% accuracy rate for tooth positioning. As for the tooth cutting, where the edge of the cutting box is used to determine the position of each tooth number, the accuracy of the tooth positioning method in this proposed study is 92.78%

Caries and Restoration Detection Using Bitewing Film Based on Transfer Learning with CNNs

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early; the treatment will be relatively easy; which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However; the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of professionals. In addition to the use of Gaussian high-pass filter and Otsu’s threshold image enhancement technology; this research solves the problem that the original cutting technology cannot extract certain single teeth; and it proposes a caries and lesions area analysis model based on convolutional neural networks (CNN); which can identify caries and restorations from the bitewing images. Moreover; it provides dentists with more accurate objective judgment data to achieve the purpose of automatic diagnosis and treatment planning as a technology for assisting precision medicine. A standardized database established following a defined set of steps is also proposed in this study. There are three main steps to generate the image of a single tooth from a bitewing image; which can increase the accuracy of the analysis model. The steps include (1) preprocessing of the dental image to obtain a high-quality binarization; (2) a dental image cropping procedure to obtain individually separated tooth samples; and (3) a dental image masking step which masks the fine broken teeth from the sample and enhances the quality of the training. Among the current four common neural networks; namely; AlexNet; GoogleNet; Vgg19; and ResNet50; experimental results show that the proposed AlexNet model in this study for restoration and caries judgments has an accuracy as high as 95.56% and 90.30%; respectively. These are promising results that lead to the possibility of developing an automatic judgment method of bitewing film

Detection of Dental Apical Lesions Using CNNs on Periapical Radiograph

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion

Tear secretion dysfunction among women workers engaged in light-on tests in the TFT-LCD industry

BACKGROUND: The TFT-LCD (thin film transistor liquid crystal display) industry is rapidly growing in Taiwan and many other countries. A large number of workers, mainly women, are employed in the light-on test process to detect the defects of products. At the light-on test workstation, the operator is generally exposed to low humidity (in the clean room environment), flashing light, and low ambient illumination for long working hours. Many workers complained about eye discomfort, and therefore we conducted a study to evaluate the tear secretion function of light-on test workers of a TFT-LCD company. METHODS: We recruited workers engaged in light-on tests in the company during their periodical health examination. In addition to a questionnaire survey of demographic characteristics and ophthalmic symptoms, we evaluated the tear secretion function of both eyes of each participant using the Schirmer's lacrimal basal secretion test with anaesthesia. A participant with one or both eyes yielding abnormal test results was defined as a case of tear secretion dysfunction. RESULTS: During the study period, a total of 371 light-on test workers received the health examination at the clinic of the park, and 52 of them were excluded due to having ophthalmic diseases and other systemic diseases that may affect ophthalmic function. All the remaining 319 qualified workers agreed to participate in this study, and they were all females working by 4-shift rotations. The average age was 24.2 years old (standard deviation [SD] = 3.8), and the average employment duration was 13.6 months (SD = 5.7). Among the 11 ophthalmic symptoms evaluated, eye dryness was the most prevalent (prevalence = 43.3%). In addition, the prevalence of tear secretion dysfunction in at least one eye was 40.1% (128 cases), and contact lens users had an odds ratio of 1.73 (95% confidence interval = 1.02–2.94) in comparison with non-contact lens users. Comparing the Schirmer's test results of those who also participated in the screening in the previous year, we found 40 of the 156 participants (17.2%) with normal test results in the previous year turned abnormal in 2001. In contrast, only 21 of the 76 participants (9.1%) with abnormal test results in the previous year turned normal, and the difference was statistically significant (p = 0.02 for McNemar's test). CONCLUSION: The prevalence of tear secretion dysfunction in woman workers engaged in light-on tests is high and increases with a one-year duration of employment. The use of contact lens may further increase the risk