The pathological role of Wnt5a in psoriasis and psoriatic arthritis.

Psoriasis (PsO) is a chronic inflammatory skin disease with both local and systemic components. PsO-associated arthritis, known as psoriatic arthritis (PsA), develops in approximately 13%-25% of PsO patients. Various factors associated with both PsO and PsA indicate that these conditions are part of a single disease. Identification of novel targets for the development of drugs to treat both PsO and PsA is desirable to provide more patient-friendly treatment regimens. Such targets will likely represent 'common checkpoints' of inflammation, for example key components or transduction cascades of the signalling pathways involved. Emerging evidence supports involvement of the non-canonical Wnt signalling pathways in the development of both PsO and PsA, especially the Wnt5a-activated signalling cascades. These, together with interlinked factors, are crucial in the interactions among keratinocytes, immune cells and inflammatory factors in PsO, as well as among chondrocytes, osteoblasts and osteoclasts that trigger both subchondral bone remodelling and cartilage catabolism in PsA. This review focuses on the pathological role of Wnt5a signalling and its interaction with other interlinked pathways in both PsO and PsA, and also on the main challenges for future research, particularly with respect to molecules targeting Wnt signalling pathways for the treatment of PsO and PsA

Bayesian modeling of ChIP-chip data using latent variables

<p>Abstract</p> <p>Background</p> <p>The ChIP-chip technology has been used in a wide range of biomedical studies, such as identification of human transcription factor binding sites, investigation of DNA methylation, and investigation of histone modifications in animals and plants. Various methods have been proposed in the literature for analyzing the ChIP-chip data, such as the sliding window methods, the hidden Markov model-based methods, and Bayesian methods. Although, due to the integrated consideration of uncertainty of the models and model parameters, Bayesian methods can potentially work better than the other two classes of methods, the existing Bayesian methods do not perform satisfactorily. They usually require multiple replicates or some extra experimental information to parametrize the model, and long CPU time due to involving of MCMC simulations.</p> <p>Results</p> <p>In this paper, we propose a Bayesian latent model for the ChIP-chip data. The new model mainly differs from the existing Bayesian models, such as the joint deconvolution model, the hierarchical gamma mixture model, and the Bayesian hierarchical model, in two respects. Firstly, it works on the difference between the averaged treatment and control samples. This enables the use of a simple model for the data, which avoids the probe-specific effect and the sample (control/treatment) effect. As a consequence, this enables an efficient MCMC simulation of the posterior distribution of the model, and also makes the model more robust to the outliers. Secondly, it models the neighboring dependence of probes by introducing a latent indicator vector. A truncated Poisson prior distribution is assumed for the latent indicator variable, with the rationale being justified at length.</p> <p>Conclusion</p> <p>The Bayesian latent method is successfully applied to real and ten simulated datasets, with comparisons with some of the existing Bayesian methods, hidden Markov model methods, and sliding window methods. The numerical results indicate that the Bayesian latent method can outperform other methods, especially when the data contain outliers.</p

Case-control study on fragility fractures in coal miners: A comparison between surface and underground workers

BackgroundThe prevalence of osteoporosis and osteopenia is higher among underground coal miners than surface workers. The special underground work environment and unhealthy habits such as smoking, drinking, and a high-salt diet may lead to changes in bone metabolism, increasing the risk of fragility fractures and placing a heavy economic burden on individuals and society. ObjectiveTo identify potential factors influencing fragility fractures among coal miners in different working environments and to provide a basis for targeted preventive measures to reduce the occurrence of fragility fractures.MethodsMale participants who attended at least one of the physical examinations in Kailuan Group between June 2006 and December 2020 were included in the study. The participants were divided into two groups based on their working environment: surface or underground. A case-control study was conducted, where patients with new fragility fractures served as the case group and participants without fragility fractures served as the control group. The two groups were matched with a case:control ratio of 1:4 by age (±1 year) and the same year of physical examination. The matching process was repeated twice, once for the surface working population and once for the underground working population. The analysis of risk factors was conducted using conditional logistic regression models.ResultsAmong a total of 113138 employees in Kailuan Group, 82631 surface workers and 30507 underground workers were included, respectively. The number of individuals who suffered fragility fractures was 1375, accounting for 1.22% of the total population. The incidence of fragility fractures in underground workers was significantly higher than that in surface workers (1.63%>1.07%, P<0.001). The results of conditional logistic regression model showed that current smoking (OR=1.26, 95%CI: 1.05, 1.51), manual labor (OR=1.37, 95%CI: 1.06, 1.78), diabetes (OR=1.26, 95%CI: 1.04, 1.54), sinus tachycardia (OR=1.81, 95%CI: 1.23, 2.66), history of stroke (OR=1.51, 95%CI: 1.09, 2.09), education at college and above (OR=0.65, 95%CI: 0.45, 0.95), high income level (OR=0.69, 95%CI: 0.54, 0.90), elevated hemoglobin (OR=0.91, 95%CI: 0.85, 0.98), and elevated total cholesterol (OR=0.90, 95%CI: 0.82, 0.99) were associated with fragility fractures in the surface working population of coal mines; current smoking (OR=1.48, 95%CI: 1.17, 1.87), current drinking (OR=1.26, 95%CI: 1.01, 1.56), manual labor (OR=2.64, 95%CI: 1.41, 4.94), history of dust exposure (OR=1.28, 95%CI: 1.03, 1.58), and obesity (OR=0.72, 95%CI: 0.52, 0.96) were associated with fragility fractures in the underground working population of coal mines.ConclusionIn preventing fragility fractures, special attention should be paid to the bone health of underground workers engaged in manual labor or having a history of dust exposure. It is important to correct their unhealthy behaviors in a timely manner, such as smoking and drinking, and to appropriately increase body weight to prevent fragility fractures. For surface workers, particular attention should be given to the high-risk group for fragility fractures, such as low family income per capita, manual labor, and having a history of stroke or diabetes; in addition, close monitoring of their resting heart rate, hemoglobin levels, and total cholesterol levels may help prevent fragility fractures

Cumulative exposure to remnant cholesterol and the risk of fragility fractures: a longitudinal cohort study

ObjectiveTo investigate the association between cumulative remnant cholesterol (cumRC) and the risk of new-onset fragility fractures.MethodsThis study included individuals who participated in the 2006, 2008, and 2010 Kailuan health examinations. Baseline characteristics were compared between groups according to cumRC quartiles. The incidence density was calculated, and the log-rank test was used to compare the cumulative incidence. Cox proportional hazards models were used to estimate the hazard ratio (HR) and 95% confidence interval (CI), and restricted cubic spline was used to examine the possibly non-linear relation between cumRC and the risk of fragility fractures. Additional analyses were performed with stratification by age (≥ or &lt;65 years).ResultsA total of 43,839 individuals were included in this study. During the median follow-up period of 10.97 years, a total of 489 fragility fractures occurred. Multivariable Cox proportional hazards regression model 3 showed that the Q1 and Q4 groups versus the Q2 group were associated with a higher HR of fragility fracture (HR 1.61, 95% CI: 1.23–2.11; HR 1.38, 95% CI: 1.06–1.81), and restricted cubic spline regression analysis showed a non-linear relationship between cumRC level and the risk of fragility fractures (POverall association &lt; 0.001, PNon-linear association = 0.001). The association was significant in the age group &lt;65 years but not in the age group ≥65 years. The sensitivity analyses were consistent with the main results.ConclusionsBoth too high and too low cumRC levels were associated with a greater risk of fragility fractures, and this association was more significant in young and middle-aged people

A highly selective biosensor with nanomolar sensitivity based on cytokinin dehydrogenase

We have developed a N6-dimethylallyladenine (cytokinin) dehydrogenase-based microbiosensor for real-time determination of the family of hormones known as cytokinins. Cytokinin dehydrogenase from Zea mays (ZmCKX1) was immobilised concurrently with electrodeposition of a silica gel film on the surface of a Pt microelectrode, which was further functionalized by free electron mediator 2,6-dichlorophenolindophenol (DCPIP) in supporting electrolyte to give a bioactive film capable of selective oxidative cleavage of the N6- side chain of cytokinins. The rapid electron shuffling between freely diffusible DCPIP and the FAD redox group in ZmCKX1 endowed the microbiosensor with a fast response time of less than 10 s. The immobilised ZmCKX1 retained a high affinity for its preferred substrate N6-(Δ2-isopentenyl) adenine (iP), and gave the miniaturized biosensor a large linear dynamic range from 10 nM to 10 µM, a detection limit of 3.9 nM and a high sensitivity to iP of 603.3 µAmM−1cm−2 (n = 4, R2 = 0.9999). Excellent selectivity was displayed for several other aliphatic cytokinins and their ribosides, including N6-(Δ2-isopentenyl) adenine, N6-(Δ2-isopentenyl) adenosine, cis-zeatin, trans-zeatin and trans-zeatin riboside. Aromatic cytokinins and metabolites such as cytokinin glucosides were generally poor substrates. The microbiosensors exhibited excellent stability in terms of pH and long-term storage and have been used successfully to determine low nanomolar cytokinin concentrations in tomato xylem sap exudates

Blood purine measurements as a rapid real-time indicator of reversible brain ischaemia

To preserve the disequilibrium between ATP and ADP necessary to drive cellular metabolism, enzymatic pathways rapidly convert ADP to adenosine and the downstream purines inosine and hypoxanthine. During ischaemia, these same pathways result in the production of purines. We performed a prospective observational study to test whether purine levels in arterial blood might correlate with brain ischaemia. We made real-time perioperative measurements, via microelectrode biosensors, of the purine levels in untreated arterial blood from 18 patients undergoing regional anaesthetic carotid endarterectomy. Pre-operatively, the median purine level was 2.4 μM (95% CI 1.3–4.0 μM); during the cross-clamp phase, the purines rose to 6.7 μM (95% CI 4.7–11.5 μM) and fell back to 1.9 μM (95% CI 1.4–2.7 μM) in recovery. Three patients became unconscious during carotid clamping, necessitating insertion of a temporary carotid shunt to restore cerebral blood flow. In these, the pre-operative median purine level was 5.4 μM (range 4.7–6.1 μM), on clamping, 9.6 μM (range 9.4–16.1 μM); during shunting, purines fell to below the pre-operative level (1.4 μM, range 0.4–2.9 μM) and in recovery 1.8 μM (range 1.8–2.6 μM). Our results suggest that blood purines may be a sensitive real-time and rapidly produced indicator of brain ischaemia, even when there is no accompanying neurological obtundation

Gold-antibody-aptamer complexed electrochemical sensing surface for septic arthritis biomarker determination

Septic arthritis (SA) is more severe in patients with rheumatoid arthritis, joint surgical issues, or a weakened immune system. Timely diagnosis of SA is crucial for effective treatment. Traditional diagnostic methods such as ELISA, white blood cell counting, blood culture, qPCR, and imaging techniques are often less accurate and time-consuming. Researchers are focusing on developing highly sensitive biosensors for SA using blood-based biomarkers. Procalcitonin is a protein and a well-established biomarker for SA. This research focuses on developing a procalcitonin interdigitated electrode (IDE) biosensor using a probe made of an aptamer and antibody-modified gold nanoparticle (AuNP) complex. The probe was attached to the IDE through an amine linker and then interacted with procalcitonin. AuNPs increased the attachment of the aptamer and antibody to the IDE, enabling the detection of procalcitonin at levels as low as 10 ng/mL, with a linear regression curve ranging from 10 to 100 ng/mL [y = 4.0691x - 2.1887; R2 = 0.9937]. Furthermore, procalcitonin-spiked serum elevated the current level with increasing procalcitonin concentrations, while control performances did not enhance the current, indicating the selective and specific detection of procalcitonin. This AuNP-aptamer-antibody complexed biosensor effectively identifies procalcitonin at low levels and aids in the diagnosis of SA

Ruthenium purple-mediated microelectrode biosensors based on sol-gel film

Ruthenium Purple (RP), an analogue of Prussian Blue, has potentially advantageous electrochemical characteristics. We now demonstrate its use in microelectrode biosensors for the first time. An RP layer was grown on, and remained stably anchored to, the surface of gold microelectrodes at physiological pH ranges. Crucially, it retained its electrochemical activity in sodium-based phosphate buffers. The RP microelectrodes displayed electrocatalytic reduction of hydrogen peroxide at 0 to -50 mV (vs Ag/AgCl). To fabricate biosensors on the RP microelectrodes, we used a sol-gel film electrodeposition technique to create ATP and hypoxanthine biosensors as examples of the methodology. These RP-mediated biosensors displayed excellent performance including the following: high selectivity against interferences such as 5HT, ascorbic acid, urate, and acetaminophen; high sensitivity with wide linear calibration range; and good stability. These attractive characteristics demonstrate that RP can be universally employed as an electron mediator in fabrication of highly selective oxidase-based microelectrode biosensors. Furthermore, given their ability to operate in the presence of physiological levels of Na+, the RP-mediated biosensors can be potentially applied to the in vitro and in vivo measurement of physiological signaling substances

The role of wnt signaling in diabetes-induced osteoporosis

Abstract Osteoporosis, a chronic complication of diabetes mellitus, is characterized by a reduction in bone mass, destruction of bone microarchitecture, decreased bone strength, and increased bone fragility. Because of its insidious onset, osteoporosis renders patients highly susceptible to pathological fractures, leading to increased disability and mortality rates. However, the specific pathogenesis of osteoporosis induced by chronic hyperglycemia has not yet been fully elucidated. But it is currently known that the disruption of Wnt signaling triggered by chronic hyperglycemia is involved in the pathogenesis of diabetic osteoporosis. There are two main types of Wnt signaling pathways, the canonical Wnt signaling pathway (β-catenin-dependent) and the non-canonical Wnt signaling pathway (non-β-catenin-dependent), both of which play an important role in regulating the balance between bone formation and bone resorption. Therefore, this review systematically describes the effects of abnormal Wnt pathway signaling on bone homeostasis under hyperglycemia, hoping to reveal the relationship between Wnt signaling and diabetic osteoporosis to further improve understanding of this disease