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This study proposes a deep learning method for pavement defect detection, focusing on identifying potholes and cracks. A dataset comprising 10,828 images is collected, with 8662 allocated for training, 1083 for validation, and 1083 for testing. Vehicle attitude data are categorized based on three-axis acceleration and attitude change, with 6656 (64%) for training, 1664 (16%) for validation, and 2080 (20%) for testing. The Nvidia Jetson Nano serves as the vehicle-embedded system, transmitting IMU-acquired vehicle data and GoPro-captured images over a 5G network to the server. The server recognizes two damage categories, low-risk and high-risk, storing results in MongoDB. Severe damage triggers immediate alerts to maintenance personnel, while less severe issues are recorded for scheduled maintenance. The method selects YOLOv7 among various object detection models for pavement defect detection, achieving a mAP of 93.3%, a recall rate of 87.8%, a precision of 93.2%, and a processing speed of 30–40 FPS. Bi-LSTM is then chosen for vehicle vibration data processing, yielding 77% mAP, 94.9% recall rate, and 89.8% precision. Integration of the visual and vibration results, along with vehicle speed and travel distance, results in a final recall rate of 90.2% and precision of 83.7% after field testing.

Polyglutamine (polyQ)-mediated spinocerebellar ataxia (SCA), including SCA1, 2, 3, 6, 7, and 17, are caused by mutant genes with expanded CAG repeats, leading to the intracellular accumulation of aggregated proteins, the production of reactive oxygen species, and cell death. Among SCA, SCA3 is caused by a mutation in the ATXN3 (ataxin-3) gene. In a circumstance of polyQ aggregation, the autophagic pathway is induced to degrade the aggregated proteins, thereby suppressing downstream deleterious effects and promoting neuronal survival. In this study, we tested the effects of synthetic indole (NC009-1, -2, -3, -6) and coumarin (LM-022, -031) derivatives as chemical chaperones to assist mutant ATXN3-Q75 folding, as well as autophagy inducers to clear aggregated protein. Among the tested compounds, NC009-1, -2, and -6 and LM-031 interfered with Escherichia coli-derived ATXN3-Q75 aggregation in thioflavin T binding and filter trap assays. In SH-SY5Y cells expressing GFP-fused ATXN3-Q75, these compounds displayed aggregation-inhibitory and neurite growth-promoting potentials compared to untreated cells. Furthermore, these compounds activated autophagy by increasing the phosphatidylethanolamine-conjugated LC3 (microtubule associated protein 1 light chain 3)-II:cytosolic LC3-I ratio in these cells. A biochemical co-immunoprecipitation assay by using a mixture of HEK 293T cell lysates containing recombinant ATXN3-Q75-Venus-C-terminus (VC) or Venus-N-terminus (VN)-LC3 protein indicated that NC009-1 and -2 and LM-031 served as an autophagosome-tethering compound (ATTEC) to interact with ATXN3-Q75 and LC3, and the interaction was further confirmed by bimolecular fluorescence complementation analysis in cells co-expressing both ATXN3-Q75-VC and VN-LC3 proteins. The study results suggest the potential of NC009-1 and -2 and LM-031 as an ATTEC in treating SCA3 and, probably, other polyQ diseases. [ABSTRACT FROM AUTHOR]

Background: The aim of this study is to evaluate the efficacy and safety of faecal microbiota transplantation (FMT) for the treatment of irritable bowel syndrome (IBS). Methods: We searched four databases for randomised controlled trials (RCTs) that compared FMT with a control intervention in patients with IBS. The revised Cochrane risk-of-bias (RoB) tool was chosen for appraisal. Meta-analysis with trial sequential analysis (TSA) was conducted. Grading of Recommendations Assessment Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence (CoE). Results: We included 12 RCTs with a total of 615 participants. Meta-analyses showed no significant difference between the FMT and control groups in terms of clinical responses (relative risk [RR] = 1.44, 95% confidence interval [CI] 0.88–2.33) and changes in IBS Severity Scoring System (IBS-SSS) scores (standardised mean difference [SMD] = − 0.31, 95% CI − 0.72 to 0.09) and IBS Quality of Life (IBS-QOL) scores (SMD = 0.30, 95% CI − 0.09 to 0.69). Subgroup analysis revealed that in studies with low RoB and using endoscopy, nasojejunal tube and rectal enema delivery, FMT led to a significant improvement in clinical responses and changes in IBS-SSS and IBS-QOL scores. TSA suggested that the current evidence is inconclusive and that the CoE is very low. Conclusion: This study suggests that patients with IBS may benefit from FMT especially when it is administered via endoscopy, nasojejunal tube or rectal enema. However, the certainty of evidence is very low. Further research is needed to confirm the efficacy and safety of FMT for IBS treatment. Trial Registration: PROSPERO registration number CRD42020211002. [ABSTRACT FROM AUTHOR]

Purposes: : Chronic obstructive pulmonary disease (COPD) is a major cause of the rapid decline of health-related quality of life (HRQoL), associated with accelerated frailty in older populations. This study aimed to analyse the long-term dynamic changes of HRQoL and the predictive factors for the rapid decline of HRQoL in older patients with COPD. Methods: Overall 244 patients with COPD, aged ≧ 65 years from one medical centre were enrolled between March 2012 and July 2020. Further, we prospectively assessed HRQoL scores with utility values, using EuroQol Five-Dimension (EQ-5D) questionnaires. Additionally, long-term dynamic changes in HRQoL were analysed using the Kernel smoothing method and examined the factors contributing to the deterioration of HRQoL using a linear mixed effects model. Results: Older patients with COPD with forced expiration volume (FEV1) < 50% of prediction entered the phase of rapid and continuous decline of HRQoL ~ 2 years after enrolment, but patients with FEV1 ≥ 50% of prediction without rapidly declined HRQoL during 7 years follow up. Therefore, FEV1 < 50% of prediction is a novel predictor for the rapid decline of HRQoL. The course of rapidly declining HRQoL occurred, initially in the usual activities and pain/discomfort domains, followed by the morbidity, self-care, and depression/anxiety domains ~ 2 and 4 years after enrolment, respectively. The mixed effects model indicated that both FEV1 < 50% of prediction and a history of severe acute exacerbation (SAE) requiring hospitalisation were contributing factors for deterioration in HRQoL. Conclusions: Both FEV1 < 50% of prediction and exacerbations requiring hospitalisation were contributing factors for the deterioration of HRQoL in long-term follow up. Additionally, FEV1 < 50% of prediction was a novel predictor for patients entering the phase of rapid decline of HRQoL. [ABSTRACT FROM AUTHOR]

An apical lesion is caused by bacteria invading the tooth apex through caries. Periodontal disease is caused by plaque accumulation. Peri-endo combined lesions include both diseases and significantly affect dental prognosis. The lack of clear symptoms in the early stages of onset makes diagnosis challenging, and delayed treatment can lead to the spread of symptoms. Early infection detection is crucial for preventing complications. PAs used as the database were provided by Chang Gung Memorial Medical Center, Taoyuan, Taiwan, with permission from the Institutional Review Board (IRB): 02002030B0. The tooth apex image enhancement method is a new technology in PA detection. This image enhancement method is used with convolutional neural networks (CNN) to classify apical lesions, peri-endo combined lesions, and asymptomatic cases, and to compare with You Only Look Once-v8-Oriented Bounding Box (YOLOv8-OBB) disease detection results. The contributions lie in the utilization of database augmentation and adaptive histogram equalization on individual tooth images, achieving the highest comprehensive validation accuracy of 95.23% with the ConvNextv2 model. Furthermore, the CNN outperformed YOLOv8 in identifying apical lesions, achieving an F1-Score of 92.45%. For the classification of peri-endo combined lesions, CNN attained the highest F1-Score of 96.49%, whereas YOLOv8 scored 88.49%. [ABSTRACT FROM AUTHOR]

In this study, the current noise situation in eight hospitals in central and northern Taiwan was investigated and analyzed. Recording equipment was utilized to measure environmental noise levels at the busiest points in the hospital lobby, specifically the pricing and medicine waiting areas. Furthermore, the acoustic data of the recorded audio samples were analyzed to determine the psychoacoustic parameter, namely, loudness. Subsequently, correlation analysis was performed between the analyzed data spectrum and the subjective psychological noise value. Ultimately, it was found that the mid-frequency band (MF) had a greater impact on the subjects compared to the other two frequency bands. When comparing the correlation coefficient analysis with the prior factor analysis, the primary sources of intrusive noise affecting the subjects were identified. The mid-frequency band is predominantly attributed to footsteps and conversations, and the high-frequency band is predominantly attributed to broadcast sound. [ABSTRACT FROM AUTHOR]

The severity of periodontitis can be analyzed by calculating the loss of alveolar crest (ALC) level and the level of bone loss between the tooth's bone and the cemento-enamel junction (CEJ). However, dentists need to manually mark symptoms on periapical radiographs (PAs) to assess bone loss, a process that is both time-consuming and prone to errors. This study proposes the following new method that contributes to the evaluation of disease and reduces errors. Firstly, innovative periodontitis image enhancement methods are employed to improve PA image quality. Subsequently, single teeth can be accurately extracted from PA images by object detection with a maximum accuracy of 97.01%. An instance segmentation developed in this study accurately extracts regions of interest, enabling the generation of masks for tooth bone and tooth crown with accuracies of 93.48% and 96.95%. Finally, a novel detection algorithm is proposed to automatically mark the CEJ and ALC of symptomatic teeth, facilitating faster accurate assessment of bone loss severity by dentists. The PA image database used in this study, with the IRB number 02002030B0 provided by Chang Gung Medical Center, Taiwan, significantly reduces the time required for dental diagnosis and enhances healthcare quality through the techniques developed in this research. [ABSTRACT FROM AUTHOR]

In the field of dentistry, the presence of dental calculus is a commonly encountered issue. If not addressed promptly, it has the potential to lead to gum inflammation and eventual tooth loss. Bitewing (BW) images play a crucial role by providing a comprehensive visual representation of the tooth structure, allowing dentists to examine hard-to-reach areas with precision during clinical assessments. This visual aid significantly aids in the early detection of calculus, facilitating timely interventions and improving overall outcomes for patients. This study introduces a system designed for the detection of dental calculus in BW images, leveraging the power of YOLOv8 to identify individual teeth accurately. This system boasts an impressive precision rate of 97.48%, a recall (sensitivity) of 96.81%, and a specificity rate of 98.25%. Furthermore, this study introduces a novel approach to enhancing interdental edges through an advanced image-enhancement algorithm. This algorithm combines the use of a median filter and bilateral filter to refine the accuracy of convolutional neural networks in classifying dental calculus. Before image enhancement, the accuracy achieved using GoogLeNet stands at 75.00%, which significantly improves to 96.11% post-enhancement. These results hold the potential for streamlining dental consultations, enhancing the overall efficiency of dental services. [ABSTRACT FROM AUTHOR]

Huntington's disease (HD) is characterized by progressive involuntary chorea movements and cognitive decline. Recent research indicates that metabolic disturbance may play a role in its pathogenesis. Bile acids, produced during cholesterol metabolism in the liver, have been linked to neurodegenerative conditions. This study investigated variations in plasma bile acid profiles among individuals with HD. Plasma levels of 16 primary and secondary bile acids and their conjugates were analyzed in 20 healthy controls and 33 HD patients, including 24 with symptoms (symHD) and 9 carriers in the presymptomatic stage (preHD). HD patients exhibited significantly higher levels of glycochenodeoxycholic acid (GCDCA) and glycoursodeoxycholic acid (GUDCA) compared to healthy controls. Conversely, isolithocholic acid levels were notably lower in the HD group. Neurotoxic bile acids (glycocholic acid (GCA) + glycodeoxycholic acid (GDCA) + GCDCA) were elevated in symHD patients, while levels of neuroprotective bile acids (ursodeoxycholic acid (UDCA) + GUDCA + tauroursodeoxycholic acid (TUDCA)) were higher in preHD carriers, indicating a compensatory response to early neuronal damage. These results underscore the importance of changes in plasma bile acid profiles in HD and their potential involvement in disease mechanisms. The identified bile acids (GCDCA, GUDCA, and isolithocholic acid) could potentially serve as markers to distinguish between HD stages and healthy individuals. Nonetheless, further research is warranted to fully understand the clinical implications of these findings and their potential as diagnostic or therapeutic tools for HD. [ABSTRACT FROM AUTHOR]

Background: COVID-19-related stigmatization refers to COVID-19-related judgements by others that devalue the individual. Such stigmatization towards healthcare workers may cause psychological burden and negative consequences. Such stigmatization may have particularly overwhelmed allied health trainees (AHTs) and post-graduate year doctors (PGYDs) because they just started their medical career. Social support and resource support have been reported to benefit psychological health and reduce stigmatization. Therefore, the present study used a cross-sectional study design to investigate the association between perceived stigma, self-stigma, psychological distress, and negative outcomes (including emotional exhaustion, insomnia and suicidal ideation) among AHTs and PGYDs in Taiwan. Methods: An online survey distributed between July and December, 2022 received 522 responses. Variables were assessed using the 21-item Depression, Anxiety and Stress Scale, Insomnia Severity Index and a series of self-designed questions to assess social support, resource support, perceived stigma, self-stigma, emotional exhaustion, and suicidal ideation. Results: Structural equation modeling showed that perceived stigma was associated with self-stigma (standardized coefficient [β] = 0.428, p < 0.001), and self-stigma was associated with psychological distress (β = 0.197, p < 0.001), as well as being associated with emotional exhaustion, insomnia, and suicidal ideation (β = 0.349, 0.556 and 0.212, all p-values < 0.001). While social support and resource support were negatively associated with perceived stigma (β= − 0.175 and − 0.152, p < 0.01), additional associations were found between social support and emotional exhaustion (β= − 0.093, p < 0.001), as well as between resource support and insomnia (β= − 0.120, p < 0.001). Conclusions: The results showed that COVID-19 related stigmatization was correlated to the detrimental consequences of emotional exhaustion, insomnia and suicidal ideation. Clear paths regarding the associations of social support and resource support with the three negative associations were found as the possible solutions. Strategies to reduce the stigmatization and these negative outcomes, or improve the psychological health will benefit AHTs and PGYDs in maintaining a healthy mental status. [ABSTRACT FROM AUTHOR]

This study proposes a deep learning method for pavement defect detection, focusing on identifying potholes and cracks. A dataset comprising 10,828 images is collected, with 8662 allocated for training, 1083 for validation, and 1083 for testing. Vehicle attitude data are categorized based on three-axis acceleration and attitude change, with 6656 (64%) for training, 1664 (16%) for validation, and 2080 (20%) for testing. The Nvidia Jetson Nano serves as the vehicle-embedded system, transmitting IMU-acquired vehicle data and GoPro-captured images over a 5G network to the server. The server recognizes two damage categories, low-risk and high-risk, storing results in MongoDB. Severe damage triggers immediate alerts to maintenance personnel, while less severe issues are recorded for scheduled maintenance. The method selects YOLOv7 among various object detection models for pavement defect detection, achieving a mAP of 93.3%, a recall rate of 87.8%, a precision of 93.2%, and a processing speed of 30–40 FPS. Bi-LSTM is then chosen for vehicle vibration data processing, yielding 77% mAP, 94.9% recall rate, and 89.8% precision. Integration of the visual and vibration results, along with vehicle speed and travel distance, results in a final recall rate of 90.2% and precision of 83.7% after field testing. [ABSTRACT FROM AUTHOR]

Allyl isothiocyanate (AITC) is abundant in cruciferous vegetables and it present pharmacological activity including anticancer activity in many types of human cancer cells in vitro and in vivo. Currently, no available information to show AITC affecting DNA damage and repair‐associated protein expression in human gastric cancer cells. Therefore, in the present studies, we investigated AITC‐induced cytotoxic effects on human gastric cancer in AGS and SNU‐1 cells whether or not via the induction of DNA damage and affected DNA damage and repair associated poteins expressions in vitro. Cell viability and morphological changes were assayed by flow cytometer and phase contrast microscopy, respectively, the results indicated AITC induced cell morphological changes and decreased total viable cells in AGS and SNU‐1 cells in a dose‐dependently. AITC induced DNA condensation and damage in a dose‐dependently which based on the cell nuclei was stained by 4′, 6‐diamidino‐2‐phenylindole present in AGS and SNU‐1 cells. DNA damage and repair associated proteins expression in AGS and SNU‐1 cells were measured by Western blotting. The results indicated AITC decreased nuclear factor erythroid 2‐related factor 2 (NRF2), heme oxygenase‐1 (HO‐1), glutathione, and catalase, but increased superoxide dismutase (SOD (Cu/Zn)), and nitric oxide synthase (iNOS) in AGS cells, however, in SNU‐1 cells are increased HO‐1. AITC increased DNA‐dependent protein kinase (DNA‐PK), phosphorylation of gamma H2A histone family member X on Ser139 (γH2AXpSer139), and heat shock protein 90 (HSP90) in AGS cells. AITC increased DNA‐PK, mediator of DNA damage checkpoint protein 1 (MDC1), γH2AXpSer139, topoisomerase II alpha (TOPIIα), topoisomerase II beta (TOPIIβ), HSP90, and heat shock protein 70 (HSP70) in SNU‐1 cells. AITC increased p53, p53pSer15, and p21 but decreased murine double minute 2 (MDM2)pSer166 and O6‐methylguanine‐DNA methyltransferase (MGMT) in AGS cells; however, it has a similar effect of AITC except increased ataxia telangiectasia and Rad3‐related protein (ATR)pSer428, checkpoint kinase 1 (CHK1), and checkpoint kinase 2 (CHK2) in SNU‐1 cells. Apparently, both cell responses to AITC are different, nonetheless, all of these observations suggest that AITC inhibits the growth of gastric cancer cells may through induction off DNA damage in vitro. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant increase in collaboration between medical imaging and artificial intelligence technology. The use of automated techniques for detecting medical symptoms has become increasingly prevalent. However, there has been a lack of research on the relationship between impacted teeth and the inferior alveolar nerve (IAN) in DPR images. The severe compression of teeth against the IAN may necessitate the requirement for nerve canal treatment. To reduce the occurrence of such events, this study aims to develop an auxiliary detection system capable of precisely locating the relative positions of the IAN and impacted teeth through object detection and image enhancement. This system is designed to shorten the duration of examinations for dentists while concurrently mitigating the chances of diagnostic errors. The innovations in this research are as follows: (1) using YOLO_v4 to identify impacted teeth and the IAN in DPR images achieves an accuracy of 88%. However, the developed algorithm in this study achieves an accuracy of 93%. (2) Image enhancement is utilized in this study to expand the dataset, with an accuracy of up to 2~3% enhancement in detecting diseases. (3) The segmentation technique proposed in this study surpasses previous methods by achieving 6% higher accuracy in dental diagnosis. [ABSTRACT FROM AUTHOR]

Huntington's disease (HD) is associated with dysregulated choline metabolism, but the underlying mechanisms remain unclear. This study investigated the expression of key enzymes in this pathway in R6/2 HD mice and human HD postmortem brain tissues. We further explored the therapeutic potential of modulating choline metabolism for HD. Both R6/2 mice and HD patients exhibited reduced expression of glycerophosphocholine phosphodiesterase 1 (GPCPD1), a key enzyme in choline metabolism, in the striatum and cortex. The striatum of R6/2 mice also showed decreased choline and phosphorylcholine, and increased glycerophosphocholine, suggesting disruption in choline metabolism due to GPCPD1 deficiency. Treatment with citicoline significantly improved motor performance, upregulated anti‐apoptotic Bcl2 expression, and reduced oxidative stress marker malondialdehyde in both brain regions. Metabolomic analysis revealed partial restoration of disrupted metabolic patterns in the striatum and cortex following citicoline treatment. These findings strongly suggest the role of GPCPD1 deficiency in choline metabolism dysregulation in HD. The therapeutic potential of citicoline in R6/2 mice highlights the choline metabolic pathway as a promising target for future HD therapies. [ABSTRACT FROM AUTHOR]