Dual blockchain-based data sharing mechanism with privacy protection for medical internet of things.

In the period of big data, the Medical Internet of Things (MIoT) serves as a critical technology for modern medical data collection. Through medical devices and sensors, it enables real-time collection of a large amount of patients' physiological parameters and health data. However, these data are often generated in a high-speed, large-scale, and diverse manner, requiring integration with traditional medical systems, which further exacerbates the phenomenon of scattered and heterogeneous medical data. Additionally, the privacy and security requirements for the devices and sensor data involved in the MIoT are more stringent. Therefore, when designing a medical data sharing mechanism, the data privacy protection capability of the mechanism must be fully considered. This paper proposes an alliance chain medical data sharing mechanism based on a dual-chain structure to achieve secure sharing of medical data among entities such as medical institutions, research institutions, and cloud privacy centers, and at the same time provide privacy protection functions to achieve a balanced combination of privacy protection capability and data accessibility of medical data. First, a knowledge technology based on ciphertext policy attribute encryption with zero-knowledge concise non-interactive argumentation is used, combined with the data sharing structure of the federation chain, to ensure the integrity and privacy-protecting capability of medical data. Second, the approach employs certificate-based signing and proxy re-encryption technology, ensuring that entities can decrypt and verify medical data at the cloud privacy center using this methodology, consequently addressing the confidentiality concerns surrounding medical data. Third, an efficient and secure key identity-based encryption protocol is used to ensure the legitimacy of user identity and improve the security of medical data. Finally, the theoretical and practical performance analysis proves that the mechanism is feasible and efficient compared with other existing mechanisms.

Voluntary wheel exercise ameliorates cognitive impairment, hippocampal neurodegeneration and microglial abnormalities preceded by demyelination in a male mouse model of noise-induced hearing loss.

Acquired peripheral hearing loss (APHL) in midlife has been identified as the greatest modifiable risk factor for dementia; however, the pathophysiological neural mechanisms linking APHL with an increased risk of dementia remain to be elucidated. Here, in an adult male mouse model of noise-induced hearing loss (NIHL), one of the most common forms of APHL, we demonstrated accelerated age-related cognitive decline and hippocampal neurodegeneration during a 6-month follow-up period, accompanied by progressive hippocampal microglial aberrations preceded by immediate-onset transient elevation in serum glucocorticoids and delayed-onset sustained myelin disruption in the hippocampus. Pretreatment with the glucocorticoid receptor antagonist RU486 before stressful noise exposure partially mitigated the early activation of hippocampal microglia, which were present at 7 days post noise exposure (7DPN), but had no impact on later microglial aberrations, hippocampal neurodegeneration, or cognitive decline exhibited at 1 month post noise exposure (1MPN). One month of voluntary wheel exercise following noise exposure barely affected either the hearing threshold shift or hippocampal myelin changes but effectively countered cognitive impairment and the decline in hippocampal neurogenesis in NIHL mice at 1MPN, paralleled by the normalization of microglial morphology, which coincided with a reduction in microglial myelin inclusions and a restoration of microglial hypoxia-inducible factor-1α (HIF1α) expression. Our results indicated that accelerated cognitive deterioration and hippocampal neuroplastic decline following NIHL are most likely driven by the maladaptive response of hippocampal microglia to myelin damage secondary to hearing loss, and we also demonstrated the potential of voluntary physical exercise as a promising and cost-effective strategy to alleviate the detrimental impact of APHL on cognitive function and thus curtail the high and continuously increasing global burden of dementia. Furthermore, the findings of the present study highlight the contribution of myelin debris overload to microglial malfunction and identify the microglial HIF1α-related pathway as an attractive candidate for future comprehensive investigation to obtain a more definitive picture of the underlying mechanisms linking APHL and dementia.

Medimatrix: innovative pre-training of grayscale images for rheumatoid arthritis diagnosis revolutionises medical image classification.

Efficient and accurate medical image classification (MIC) methods face two major challenges: (1) high similarity between images of different disease classes; and (2) generating large medical image datasets for training deep neural networks is challenging due to privacy restrictions and the need for expert ground truth annotations. In this paper, we introduce a novel deep learning method called pre-training grayscale images with supervised learning for MIC (MediMatrix). Instead of pre-training on color ImageNet, our approach uses MediMatrix on grayscale ImageNet. To improve the performance of the network, we introduce ShuffleAttention (SA), a self-attention mechanism. By combining SA with the multiple residual structure (ResSA block) and replacing short-cut connections with dense residual connections between corresponding layers (densepath), our network can dynamically adjust channel attention weights and receive image inputs of different sizes, resulting in improved feature representation and better discrimination of similarities between different categories. MediMatrix effectively classifies X-ray images of rheumatoid arthritis (RA), enabling efficient screening without the need for expert analysis or invasive testing. Through extensive experiments, we demonstrate the superiority of MediMatrix over state-of-the-art methods and that color is not critical for rich natural image classification. Our results highlight the potential of computer-aided diagnosis combined with MediMatrix as a valuable screening tool for early detection and intervention in RA.

Adult mice with noise-induced hearing loss exhibited temporal ordering memory deficits accompanied by microglia-associated neuroplastic changes in the medial prefrontal cortex.

Acquired peripheral hearing loss in midlife is considered the primary modifiable risk factor for dementia, while the underlying pathological mechanism remains poorly understood. Excessive noise exposure is the most common cause of acquired peripheral hearing loss in modern society. This study was designed to investigate the impact of noise-induced hearing loss (NIHL) on cognition, with a focus on the medial prefrontal cortex (mPFC), a brain region that is involved in both auditory and cognitive processes and is highly affected in patients with cognitive impairment. Adult C57BL/6 J mice were randomly assigned to a control group and seven noise groups: 0HPN, 12HPN, 1DPN, 3DPN, 7DPN, 14DPN, and 28DPN, which were exposed to broadband noise at a 123 dB sound pressure level (SPL) for 2 h and sacrificed immediately (0 h), 12 h, or 1, 3, 7, 14, or 28 days post-noise exposure (HPN, DPN), respectively. Hearing assessment, behavioral tests, and neuromorphological studies in the mPFC were performed in control and 28DPN mice. All experimental animals were included in the time-course analysis of serum corticosterone (CORT) levels and mPFC microglial morphology. The results illustrated that noise exposure induced early-onset transient serum CORT elevation and permanent moderate-to-severe hearing loss in mice. 28DPN mice, in which permanent NIHL has been verified, exhibited impaired performance in temporal order object recognition tasks concomitant with reduced structural complexity of mPFC pyramidal neurons. The time-course immunohistochemical analysis in the mPFC revealed significantly higher morphological microglial activation at 14 and 28 DPN, preceded by a remarkably higher amount of microglial engulfed postsynaptic marker PSD95 at 7 DPN. Additionally, lipid accumulation in microglia was observed in 7DPN, 14DPN and 28DPN mice, suggesting a driving role of lipid handling deficits following excessive phagocytosis of synaptic elements in delayed and sustained microglial abnormalities. These findings provide fundamentally novel information concerning mPFC-related cognitive impairment in mice with NIHL and empirical evidence suggesting the involvement of microglial malfunction in the mPFC neurodegenerative consequences of NIHL.

Adherence to the Vegetable-Fruit-Soy Dietary Pattern, a Reference From Mediterranean Diet, Protects Against Postmenopausal Breast Cancer Among Chinese Women.

Background: The diet-center hypothesis has gained much support from the apparent protective effect of the Mediterranean diet on breast cancer. However, the evidence of the association between Mediterranean diet adherence and breast cancer molecular subtypes remains small, especially in non-Mediterranean populations. Methods: The subjects from the Chinese Wuxi Exposure and Breast Cancer Study, a population-based case-control study, included 818 patients and 935 healthy controls. A validated food frequency questionnaire used for diet assessment and a modified version of the alternate Mediterranean Diet Score, which is called the alternate Chinese Diet Score, was developed to assess adherence to a migrated Chinese version of the Mediterranean diet, which we called the vegetable-fruit-soy dietary pattern. Soy foods, rapeseed oil, and coarse cereals replaced legumes, olive oil, and whole grains reflecting the cuisine of the region. We examined the association between the vegetable-fruit-soy diet adherence and breast cancer risk, stratified by menopause status (pre- or postmenopausal) and receptor status [estrogen-receptor (ER), progesterone-receptor (PR) status, and human epidermal growth factor 2 (HER2)] oncogene expression, followed by five specific combinations (ER+, ER-, ER+/PR+,ER-/PR-, and ER-/PR-/HER2-). Results: The results suggest that the vegetable-fruit-soy dietary pattern was inversely associated with postmenopausal breast cancer risk [4th vs. 1st quartile, odds ratio (OR) = 0.57, 95%CI = 0.41, 0.80; P trend < 0.001] and that the inverse association was somewhat stronger to detect among ER- subtypes (OR = 0.63; 95%CI = 0.37, 0.94; P trend = 0.003) and ER-/PR-subtypes (OR = 0.64; 95%CI = 0.41, 0.93; P trend = 0.012). We did not observe any significant association between the vegetable-fruit-soy diet characteristics and ER+ subtype, as well as between PR+ and ER+/PR+ subtypes. Conclusion: The favorable influence from the Mediterranean diet may also apply to Chinese women. The vegetable-fruit-soy dietary pattern may reduce the risk of postmenopausal breast cancer, particularly among ER- subtype, and ER-/PR-subtype.

MicroRNA-106b overexpression suppresses synovial inflammation and alleviates synovial damage in patients with rheumatoid arthritis.

OBJECTIVES: To explore the effect of miR-106b on synovial inflammation and damage in rheumatoid arthritis (RA) patients and further to investigate its possible mechanism. METHODS: Quantitative real-time polymerase chain reaction, immunofluorescence, in situ hybridization, and immunohistochemistry assay were used to verify the levels of miR-106b and cytokines. Pearson's correlation analysis was conducted to examine bivariate relationship between miR-106b and cytokines or receptor activator of nuclear factor-κ B ligand (RANKL). Following the isolation of fibroblast-like synoviocytes (FLS), the cultured cells were separately transfected with or without miR-106b mimic. Thereafter, cell proliferation, invasion and migration were measured by Cell Counting Kit-8 assay and Transwell assay, respectively. Furthermore, concentration and expression of cytokines were separately detected by enzyme-linked immunosorbent assay and Western blot. RESULTS: Compared with osteoarthritis, RA patients had a lower level of miR-106b and higher levels of RANKL, tumour necrosis factor-a (TNF-a), and interleukin-6 (IL-6). The relative transcription of miR-106b level was negatively correlated to TNF-a, IL-6, and RNKAL levels in both patients (all P < 0.05). Furthermore, miR-106b overexpression suppressed cell proliferation, migration, and invasion capacity of RA-FLS. CONCLUSIONS: miR-106b overexpression suppresses synovial inflammation and alleviates synovial damage; thus, it may be served as a potential therapeutic target for RA patients.

Association Between Dietary Patterns and Plasma Lipid Biomarker and Female Breast Cancer Risk: Comparison of Latent Class Analysis (LCA) and Factor Analysis (FA).

Background: Diet research focuses on the characteristics of "dietary patterns" regardless of the statistical methods used to derive them. However, the solutions to these methods are both conceptually and statistically different. Methods: We compared factor analysis (FA) and latent class analysis (LCA) methods to identify the dietary patterns of participants in the Chinese Wuxi Exposure and Breast Cancer Study, a population-based case-control study that included 818 patients and 935 healthy controls. We examined the association between dietary patterns and plasma lipid markers and the breast cancer risk. Results: Factor analysis grouped correlated food items into five factors, while LCA classified the subjects into four mutually exclusive classes. For FA, we found that the Prudent-factor was associated with a lower risk of breast cancer [4th vs. 1st quartile: odds ratio (OR) for 0.70, 95% CI = 0.52, 0.95], whereas the Picky-factor was associated with a higher risk (4th vs. 1st quartile: OR for 1.35, 95% CI = 1.00, 1.81). For LCA, using the Prudent-class as the reference, the Picky-class has a positive association with the risk of breast cancer (OR for 1.42, 95% CI = 1.06, 1.90). The multivariate-adjusted model containing all of the factors was better than that containing all of the classes in predicting HDL cholesterol (p = 0.04), triacylglycerols (p = 0.03), blood glucose (p = 0.04), apolipoprotein A1 (p = 0.02), and high-sensitivity C-reactive protein (p = 0.02), but was weaker than that in predicting the breast cancer risk (p = 0.03). Conclusion: Factor analysis is useful for understanding which foods are consumed in combination and for studying the associations with biomarkers, while LCA is useful for classifying individuals into mutually exclusive subgroups and compares the disease risk between the groups.