Search Results (22)

Probiotics are posited to enhance exercise performance by influencing muscle protein synthesis, augmenting glycogen storage, and reducing inflammation. This double-blind study randomized 88 participants to receive a six-week intervention with either a placebo, Lactococcus lactis subsp. lactis LY-66, Lactobacillus plantarum PL-02, or a combination of both strains, combined with a structured exercise training program. We assessed changes in maximal oxygen consumption (VO_2max), exercise performance, and gut microbiota composition before and after the intervention. Further analyses were conducted to evaluate the impact of probiotics on exercise-induced muscle damage (EIMD), muscle integrity, and inflammatory markers in the blood, 24 and 48 h post-intervention. The results demonstrated that all probiotic groups exhibited significant enhancements in exercise performance and attenuation of muscle strength decline post-exercise exhaustion (p < 0.05). Notably, PL-02 intake significantly increased muscle mass, whereas LY-66 and the combination therapy significantly reduced body fat percentage (p < 0.05). Analysis of intestinal microbiota revealed an increase in beneficial bacteria, especially a significant rise in Akkermansia muciniphila following supplementation with PL-02 and LY-66 (p < 0.05). Overall, the combination of exercise training and supplementation with PL-02, LY-66, and their combination improved muscle strength, explosiveness, and endurance performance, and had beneficial effects on body composition and gastrointestinal health, as evidenced by data obtained from non-athlete participants. Full article

Combined use of light-emitting diodes (LED) ultraviolet (UV) and chlorination provides alternative disinfection in drinking water, which could affect the biofilm formed subsequently. Two sequential integrations (UV-Cl and Cl-UV) and one simultaneous combination (UV/Cl) were adopted to investigate their impacts on biofilm formation. Natural organic matter after combined processes was more accessible for microbes. This might explain the promoted growth of culturable biofilm bacteria—biofilm bacteria stabilized at 10⁴ CFU/mL without disinfection while increasing continuously to 10⁵ CFU/mL in 106 days after combined processes. Contrarily, the viable biofilm bacteria were efficiently suppressed by combined processes, with the least bacteria observed in UV/Cl. The culturable ciprofloxacin-resistant bacteria in biofilm was suppressed by combined processes, with the survival reduced from 49.9% in the control to 27.7%, 16.0% and 10.8% in UV-Cl, Cl-UV and UV/Cl, respectively. The survival of sulfamethoxazole/trimethoprim-resistant bacteria was lower in UV/Cl (16.8%) than others (43.6–55.0%), consistent with the little sul1 and sul2 detected in UV/Cl. Although combined processes reduced most detected antibiotic resistance genes (i.e., blaTEM-1, tetA, sul1 and sul2), UV-Cl showed the potential to enrich tetA and sul2 in biofilm. Overall, UV/Cl outperformed the sequential combinations in the control of viable bacteria and the antibiotic resistance in the subsequently formed biofilm. Full article

Background: The outcomes for patients with NASH-related HCC after curative resection have not been clarified. This study compared the overall survival (OS), time-to-tumor recurrence (TTR), and recurrence-free survival (RFS) associated with NASH-related HCC and virus-related HCC after resection. Methods: Patients with HCC who underwent curative resection were retrospectively enrolled. Baseline characteristics, including disease etiologies and clinical and tumor features, were reviewed. The primary outcomes were OS, TTR, and RFS. Results: Two hundred and six patients were enrolled (HBV: n = 121, HCV: n = 54, NASH: n = 31). Of those with virus-related HCC, 84.0% achieved viral suppression. In both the overall and propensity-score-matched cohorts, those with NASH-related HCC experienced recurrence significantly earlier than those with virus-related HCC (median TTR: 1108 days vs. non-reached; p = 0.03). Through multivariate analysis, NASH-related HCC (hazard ratio (HR), 2.27; 95% confidence interval (CI), 1.25–4.12) was independently associated with early recurrence. The unadjusted RFS rate of the NASH-related HCC group was lower than the virus-related HCC group. There was no difference in the OS between the two groups. Conclusions: NASH-related HCC was associated with earlier tumor recurrence following curative resection compared to virus-related HCC. Post-surgical surveillance is crucial for detecting early recurrence in patients with NASH-related HCC. Full article

CXCR4 antagonists have been claimed to reduce mortality after myocardial infarction in myocardial infarction (MI) animals, presumably due to suppressing inflammatory responses caused by myocardial ischemia-reperfusion injury, thus, subsequently facilitating tissue repair and cardiac function recovery. This study aims to determine whether a newly designed CXCR4 antagonist DBPR807 could exert better vascular-protective effects than other clinical counterparts (e.g., AMD3100) to alleviate cardiac damage further exacerbated by reperfusion. Consequently, we find that instead of traditional continuous treatment or multiple-dose treatment at different intervals of time, a single-dose treatment of DBPR807 before reperfusion in MI animals could attenuate inflammation via protecting oxidative stress damage and preserve vascular/capillary density and integrity via mobilizing endothelial progenitor cells, leading to a desirable fibrosis reduction and recovery of cardiac function, as evaluated with the LVEF (left ventricular ejection fraction) in infarcted hearts in rats and mini-pigs, respectively. Thus, it is highly suggested that CXCR4 antagonists should be given at a single high dose prior to reperfusion to provide the maximal cardiac functional improvement. Based on its favorable efficacy and safety profiles indicated in tested animals, DBPR807 has a great potential to serve as an adjunctive medicine for percutaneous coronary intervention (PCI) therapies in acute MI patients. Full article

Oral squamous cell carcinoma (OSCC) carcinogenesis involves heterogeneous tumor cells, and the tumor microenvironment (TME) is highly complex with many different cell types. Cancer cell–TME interactions are crucial in OSCC progression. Candida albicans (C. albicans)—frequently pre-sent in the oral potentially malignant disorder (OPMD) lesions and OSCC tissues—promotes malignant transformation. The aim of the study is to verify the mechanisms underlying OSCC car-cinogenesis with C. albicans infection and identify the biomarker for the early detection of OSCC and as the treatment target. The single-cell RNA sequencing analysis (scRNA-seq) was performed to explore the cell subtypes in normal oral mucosa, OPMD, and OSCC tissues. The cell composi-tion changes and oncogenic mechanisms underlying OSCC carcinogenesis with C. albicans infec-tion were investigated. Gene Set Variation Analysis (GSVA) was used to survey the mechanisms underlying OSCC carcinogenesis with and without C. albicans infection. The results revealed spe-cific cell clusters contributing to OSCC carcinogenesis with and without C. albicans infection. The major mechanisms involved in OSCC carcinogenesis without C. albicans infection are the IL2/STAT5, TNFα/NFκB, and TGFβ signaling pathways, whereas those involved in OSCC carcinogenesis with C. albicans infection are the KRAS signaling pathway and E2F target down-stream genes. Finally, stratifin (SFN) was validated to be a specific biomarker of OSCC with C. albicans infection. Thus, the detailed mechanism underlying OSCC carcinogenesis with C. albicans infection was determined and identified the treatment biomarker with potential precision medicine applications. Full article

Oral squamous cell carcinoma (OSCC) accounts for over 90% of oral cancers and causes considerable morbidity and mortality. Epigenetic deregulation is a common mechanism underlying carcinogenesis. DNA methylation deregulation is the epigenetic change observed during the transformation of normal cells to precancerous and eventually cancer cells. This study investigated the DNA methylation patterns of PTK6 during the development of OSCC. Bisulfite genomic DNA sequencing was performed to determine the PTK6 methylation level. OSCC animal models were established to examine changes in PTK6 expression in the different stages of OSCC development. The DNA methylation of PTK6 was decreased during the development of OSCC. The mRNA and protein expression of PTK6 was increased in OSCC cell lines compared with human normal oral keratinocytes. In mice, the methylation level of PTK6 decreased after treatment with 4-nitroquinoline 1-oxide and arecoline, and the mRNA and protein expression of PTK6 was increased. PTK6 hypomethylation can be a diagnostic marker of OSCC. Upregulation of PTK6 promoted the proliferation, migration, and invasion of OSCC cells. PTK6 promoted carcinogenesis and metastasis by increasing STAT3 phosphorylation and ZEB1 expression. The epigenetic deregulation of PTK6 can serve as a biomarker for the early detection of OSCC and as a treatment target. Full article

The maintenance of uric acid levels is crucial for the human body. In this study, the feasibility of using portable ultraviolet (UV) spectrophotometry to measure the uric acid of spot urine without the need to add reagents has been demonstrated for the first time. UV spectral analysis has been used to inspect the uric acid concentration in urine. It is found that the absorption spectrum of urine has a high correlation with the concentration of uric acid at a wavelength of around 290–300 nm. Uric acid levels measured with a spectral analyzer compared to uric acid concentrations measured with a traditional biochemical analysis showed good agreement. The portable prototype is label-free and capable of displaying the inspection result of each measurement within 10 s. In the long run, this device can assist people in checking uric acid levels of spot urine with higher frequency and can adjust diet or medication in real time for more efficient health management. Full article

Human–computer interactions (HCIs) use computer technology to manage the interfaces between users and computers. Object detection systems that use convolutional neural networks (CNNs) have been repeatedly improved. Computer vision is also widely applied to multiple specialties. However, self-checkouts operating with a faster region-based convolutional neural network (faster R-CNN) image detection system still feature overlapping and cannot distinguish between the color of objects, so detection is inhibited. This study uses a mask R-CNN with data augmentation (DA) and a discrete wavelet transform (DWT) in lieu of a faster R-CNN to prevent trivial details in images from hindering feature extraction and detection for deep learning (DL). The experiment results show that the proposed algorithm allows more accurate and efficient detection of overlapping and similarly colored objects than a faster R-CNN with ResNet 101, but allows excellent resolution and real-time processing for smart retail stores. Full article

During the coronavirus disease (COVID-19) pandemic, we admitted suspected or confirmed COVID-19 patients to our isolation wards between 2 March 2020 and 4 May 2020, following a well-designed and efficient assessment protocol. We included 217 patients suspected of COVID-19, of which 27 had confirmed COVID-19. The clinical characteristics of these patients were used to train artificial intelligence (AI) models such as support vector machine (SVM), decision tree, random forest, and artificial neural network for diagnosing COVID-19. When analyzing the performance of the models, SVM showed the highest sensitivity (SVM vs. decision tree vs. random forest vs. artificial neural network: 100% vs. 42.86% vs. 28.57% vs. 71.43%), while decision tree and random forest had the highest specificity (SVM vs. decision tree vs. random forest vs. artificial neural network: 88.37% vs. 100% vs. 100% vs. 94.74%) in the diagnosis of COVID-19. With the aid of AI models, physicians may identify COVID-19 patients earlier, even with few baseline data available, and segregate infected patients earlier to avoid hospital cluster infections and to ensure the safety of medical professionals and ordinary patients in the hospital. Full article

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%. Full article

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. Full article

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. Full article

In this study, by combining a large-area MoS₂ monolayer with silver plasmonic nanostructures in a deformable polydimethylsiloxane substrate, we theoretically and experimentally studied the photoluminescence (PL) enhancement of MoS₂ by surface lattice resonance (SLR) modes of different silver plasmonic nanostructures. We also observed the stable PL enhancement of MoS₂ by silver nanodisc arrays under differently applied stretching strains, caused by the mechanical holding effect of the MoS₂ monolayer. We believe the results presented herein can guarantee the possibility of stably enhancing the light emission of transition metal dichalcogenides using SLR modes in a deformable platform. Full article

Oral carcinogenesis involves the progression of the normal mucosa into potentially malignant disorders and finally into cancer. Tumors are heterogeneous, with different clusters of cells expressing different genes and exhibiting different behaviors. 4-nitroquinoline 1-oxide (4-NQO) and arecoline were used to induce oral cancer in mice, and the main factors for gene expression influencing carcinogenesis were identified through single-cell RNA sequencing analysis. Male C57BL/6J mice were divided into two groups: a control group (receiving normal drinking water) and treatment group (receiving drinking water containing 4-NQO (200 mg/L) and arecoline (500 mg/L)) to induce the malignant development of oral cancer. Mice were sacrificed at 8, 16, 20, and 29 weeks. Except for mice sacrificed at 8 weeks, all mice were treated for 16 weeks and then either sacrificed or given normal drinking water for the remaining weeks. Tongue lesions were excised, and all cells obtained from mice in the 29- and 16-week treatment groups were clustered into 17 groups by using the Louvain algorithm. Cells in subtypes 7 (stem cells) and 9 (keratinocytes) were analyzed through gene set enrichment analysis. Results indicated that their genes were associated with the MYC_targets_v1 pathway, and this finding was confirmed by the presence of cisplatin-resistant nasopharyngeal carcinoma cell lines. These cell subtype biomarkers can be applied for the detection of patients with precancerous lesions, the identification of high-risk populations, and as a treatment target. Full article

Impairment of the ubiquitin-proteasome-system (UPS) and autophagy causing cytoplasmic aggregation of ubiquitin andp62 have been implicated in the pathogenesis of most neurodegenerative disorders, yet, they have not been fully elucidated in leukodystrophies. The relationship among impairment of UPS, autophagy, and globoid cell leukodystrophy (GLD), one of the most common demyelinating leukodystrophies, is clarified in this study. We examined the ubiquitin and autophagy markers in the brains of twitcher mice, a murine model of infantile GLD, and in human oligodendrocytes incubated with psychosine. Immunohistochemical examinations showed spatiotemporal accumulation of ubiquitin- and p62-aggregates mainly in the white matter of brain and spinal cord at disease progression. Western blot analysis demonstrated a significant accumulation of ubiquitin, p62, and LC3-II in insoluble fraction in parallel with progressive demyelination and neuroinflammation in twitcher brains. In vitro study validated a dose- and time-dependent cytotoxicity of psychosine upon autophagy and UPS machinery. Inhibition of autophagy and UPS exacerbated the accumulation of insoluble ubiquitin, p62, and LC3-II proteins mediated by psychosine cytotoxicity as well as increased cytoplasmic deposition of ubiquitin- and p62-aggregates, and accumulation of autophagosomes and autolysosomes. Further, the subsequent accumulation of reactive oxygen species and reduction of mitochondrial respiration led to cell death. Our studies validate the impairment of proteasome and autophagy underlying the pathogenesis of GLD. These findings provide a novel insight into pathogenesis of GLD and suggest a specific pathomechanism as an ideal target for therapeutic approaches. Full article