This narrative review aimed to summarize evidence regarding the responses to exercise among patients with preclinical Alzheimer’s disease (AD) and the effectiveness of long-term exercise interventions in improving cognitive function and neuropsychiatric symptoms. We performed a narrative review of existing literature on the effectiveness of long-term exercise interventions in improving cognitive function and neuropsychiatric symptoms in patients with AD. Patients with AD who presented with long-term exercise interventions appeared to have improved blood flow, increased hippocampal volume, and improved neurogenesis. Most prospective studies have proven that physical inactivity is one of the most common preventable risk factors for developing AD and that higher physical activity levels are associated with a reduced risk of AD development. Physical exercise seems to be effective in improving several neuropsychiatric symptoms of AD, notably cognitive function. Compared with medications, exercise has been shown to have fewer side effects and better adherence.

Hepatitis B virus X protein (HBx) and hepatic stellate cells (HSCs) are critical for liver fibrosis development. Anti-fibrosis occurs via reversion to quiescent-type HSCs or clearance of HSCs via apoptosis or ferroptosis. We aimed to elucidate the role of chrysophanol in rat HSC-T6 cells expressing HBx and investigate whether chrysophanol (isolated from Rheum palmatum rhizomes) influences cell death via ferroptosis in vitro. Analysis of lipid reactive oxygen species (ROS), Bip, CHOP, p-IRE1α, GPX4, SLC7A11, α-SMA, and CTGF showed that chrysophanol attenuated HBx-repressed cell death. Chrysophanol can impair HBx-induced activation of HSCs via endoplasmic reticulum stress (ER stress) and ferroptosis-dependent and GPX4-independent pathways.

Ankylosing spondylitis (AS) is a type of axial inflammation. Over time, some patients develop spinal ankylosis and permanent disability; however, current treatment strategies cannot arrest syndesmophyte formation completely. Here, we used mesenchymal stem cells (MSCs) from AS patients (AS MSCs) within the enthesis involved in spinal ankylosis to delineate that the HLA-B27–mediated spliced X-box–binding protein 1 (sXBP1)/retinoic acid receptor-β (RARB)/tissue-nonspecific alkaline phosphatase (TNAP) axis accelerated the mineralization of AS MSCs, which was independent of Runt-related transcription factor 2 (Runx2). An animal model mimicking AS pathological bony appositions was established by implantation of AS MSCs into the lumbar spine of NOD-SCID mice. We found that TNAP inhibitors, including levamisole and pamidronate, inhibited AS MSC mineralization in vitro and blocked bony appositions in vivo. Furthermore, we demonstrated that the serum bone-specific TNAP (BAP) level was a potential prognostic biomarker to predict AS patients with a high risk for radiographic progression. Our study highlights the importance of the HLA-B27–mediated activation of the sXBP1/RARB/TNAP axis in AS syndesmophyte pathogenesis and provides a new strategy for the diagnosis and prevention of radiographic progression of AS.

Background: Incidence of skin cancer is one of the global burdens of malignancies that increase each year, with melanoma being the deadliest one. Imaging-based automated skin cancer detection still remains challenging owing to variability in the skin lesions and limited standard dataset availability. Recent research indicates the potential of deep convolutional neural networks (CNN) in predicting outcomes from simple as well as highly complicated images. However, its implementation requires high-class computational facility, that is not feasible in low resource and remote areas of health care. There is potential in combining image and patient’s metadata, but the study is still lacking. Objective: We want to develop malignant melanoma detection based on dermoscopic images and patient’s metadata using an artificial intelligence (AI) model that will work on low-resource devices. Methods: We used an open-access dermatology repository of International Skin Imaging Collaboration (ISIC) Archive dataset consist of 23,801 biopsy-proven dermoscopic images. We tested performance for binary classification malignant melanomas vs nonmalignant melanomas. From 1200 sample images, we split the data for training (72%), validation (18%), and testing (10%). We compared CNN with image data only (CNN model) vs CNN for image data combined with an artificial neural network (ANN) for patient’s metadata (CNN+ANN model). Results: The balanced accuracy for CNN+ANN model was higher (92.34%) than the CNN model (73.69%). Combination of the patient’s metadata using ANN prevents the overfitting that occurs in the CNN model using dermoscopic images only. This small size (24 MB) of this model made it possible to run on a medium class computer without the need of cloud computing, suitable for deployment on devices with limited resources. Conclusion: The CNN+ANN model can increase the accuracy of classification in malignant melanoma detection even with limited data and is promising for development as a screening device in remote and low resources health care.

Background: Previous studies have reported that the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio could be a simple clinical indicator of insulin resistance (IR), but the results indicated that there were heterogeneities between different ethnicities. We aimed to investigate the association between TG/HDL-C and IR (as measured by homeostasis model assessment of IR [HOMA-IR]), and establish a clinical prediction rule for IR in middle-aged and elderly Taiwanese. Methods: A total of 398 subjects were recruited, and each subject completed a questionnaire that included personal and medical history data, and underwent anthropometric measurement and blood sampling. IR was defined as HOMA-IR index value ≥2.0. Chi-squared test, independent two-sample t-test, Pearson’s correlation coefficient, and multiple logistic regression were used to evaluate the association between IR and TG/HDL-C ratio. A receiver operating characteristic (ROC) analysis was conducted to evaluate the ability of the developed clinical prediction rule to correctly discriminate between subjects of IR positive and IR negative groups. Results: A significant association between IR and TG/HDL-C ratio was identified with a Pearson’s correlation coefficient of 0.35 (p-value< 0.001). In multiple logistic regression, high BMI (OR = 1.23; 95% C.I. = 1.13–1.33), hypertension (OR = 1.90; 95% C.I. = 1.12–3.21), diabetes mellitus (OR = 5.44; 95% C.I. = 2.93–10.08) and high TG/HDL ratio (OR = 1.45; 95% C.I. = 1.23–1.72) were significantly associated with the risk of elevated HOMA-IR. The area under ROC curves for TG/HDL-C ratio was 0.729 and the optimal threshold value was 2.197 where the corresponding of sensitivity and specificity were 72.4 and 65.1%. Conclusions: Our findings showed that the elevated TG/HDL-C ratio was significantly associated with IR and could be used as an indicator of IR among the middle-aged and elderly population in Taiwan. It is clinically available, thus eliminating any additional costs. Future research is warranted to investigate the use of TG/HDL-C ratio combined with other risk factors for predicting IR under diverse ethnic backgrounds.

Objective: This study determined the impact of the caller’s emotional state and cooperation on out-of-hospital cardiac arrest (OHCA) recognition and dispatcher-assisted cardiopulmonary resuscitation (DA-CPR) performance metrics.Methods: This was a retrospective study using data from November 2015 to October 2016 from the emergency medical service dispatching centre in northern Taiwan. Audio recordings of callers contacting the centre regarding adult patients with non-traumatic OHCA were reviewed. The reviewers assigned an emotional content and cooperation score (ECCS) to the callers. ECCS 1–3 callers were graded as cooperative and ECCS 4–5 callers as uncooperative and highly emotional. The relation between ECCS and OHCA recognition, time to key events and DA-CPR delivery were investigated.Results: Of the 367 cases, 336 (91.6%) callers were assigned ECCS 1–3 with a good inter-rater reliability (k=0.63). Dispatchers recognised OHCA in 251 (68.4%) cases. Compared with callers with ECCS 1, callers with ECCS 2 and 3 were more likely to give unambiguous responses about the patient’s breathing status (adjusted OR (AOR)=2.6, 95% CI 1.1 to 6.4), leading to a significantly higher rate of OHCA recognition (AOR=2.3, 95% CI 1.1 to 5.0). Thirty-one callers were rated uncooperative (ECCS 4–5) but had shorter median times to OHCA recognition and chest compression (29 and 122 s, respectively) compared with the cooperative caller group (38 and 170 s, respectively). Nevertheless, those with ECCS 4–5 had a significantly lower DA-CPR delivery rate (54.2% vs 85.9%) due to ‘caller refused’ or ‘overly distraught’ factors.Conclusions: The caller’s high emotional state is not a barrier to OHCA recognition by dispatchers but may prevent delivery of DA-CPR instruction. However, DA-CPR instruction followed by first chest compression is possible despite the caller’s emotional state if dispatchers are able to skilfully reassure the emotional callers.