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Metabolomics-based identification of bioactive metabolites holds promise for enhancing the diagnosis, prevention, and treatment of rheumatoid arthritis (RA). Targeting specific cell populations with metabolite dysregulation presents novel opportunities for modulating disease progression in RA. The alteration of endogenous ligands is dynamic and cell type specific. Each endogenous ligand contributes a unique mode of metabolic-sensing G protein-coupled receptor (GPCR) activation. Metabolite-sensing GPCR signals originating from the synovial joint and gut have a regulatory role in RA-related inflammatory immune responses. Persistent inflammation in damaged joints results in metabolic dysregulation of the synovial microenvironment, causing pathogenic alteration of cell activity in rheumatoid arthritis (RA). Recently, the role of metabolite and metabolite-sensing G protein-coupled receptors (GPCRs) in the RA-related inflammatory immune response (IIR) has become a focus of research attention. These GPCRs participate in the progression of RA by modulating immune cell activation, migration, and inflammatory responses. Here, we discuss recent evidence implicating metabolic dysregulation in RA pathogenesis, focusing on the connection between RA-related IIR and GPCR signals originating from the synovial joint and gut. Furthermore, we discuss future directions for targeting metabolite-sensing GPCRs for therapeutic benefit, emphasizing the importance of identifying endogenous ligands and investigating the various transduction mechanisms involved. [ABSTRACT FROM AUTHOR]

Remote photoplethysmography (rPPG) enables non-contact measurement of heart rate (HR). However, the stability of rPPG extraction is a bottleneck limiting its application. To address this issue, a signal quality ranking and fusion (SQRF) approach based on HR continuity in the time–frequency domain is introduced. Firstly, the facial region is divided into multiple regions of interest (ROIs), and the raw blood volume pulse (BVP) signal is extracted from each ROI separately using a conventional rPPG method such as the plane orthogonal to skin (POS) method. Then, wavelet synchrosqueezed transform (WSST) is employed to convert the raw pulse signals into spectrograms, which are further ranked according to the HR instantaneous continuity. The selected spectrograms with high-quality HR continuity are then fused using a weighted average to predict the final HR. The proposed SQRF algorithm is verified on three public datasets DDPM, UBFC-Phys and PURE with real scenarios. The obtained mean absolute error (MAE) was reduced by 58.7%, 47.5%, and 16.0% respectively, compared to the original single-ROI method. The results prove that SORF with spectrogram-based HR continuity can consistently boost the stability of POS. • Blood volume pulse quality assessment based on the continuity of heart rate. • Fusion of selected spectrograms across multiple patches to achieve stable heart rate measurement. • Boosting the accuracy and stability of existing remote photoplethysmography methods. [ABSTRACT FROM AUTHOR]

Recently, phase-based methods offer precise measurement of subtle vibrations from videos but face challenges when dealing with moving objects. This paper introduces a novel video-based method for measuring subtle vibrations in the presence of large motions. It employs complex steerable filters to capture phase variations at each pixel, extracting a composite motion signal. Based on the differences in acceleration characteristics between subtle vibrations and large motions, a band-passed acceleration filter is designed to separate them, relying only on limited prior knowledge of the frequency band. The filter design minimizes passband attenuation using a genetic algorithm for iterative parameter optimization. By further incorporating a Gaussian amplitude kernel, we suppress large-amplitude nonlinear motion interference and extract subtle vibrations with acceleration characteristics. Both simulation experiments and real-world tests demonstrate that this method outperforms state-of-the-art techniques in terms of accuracy, providing a more effective approach for measuring subtle vibrations in moving objects. • A vision method for measuring subtle vibrations in large motion is proposed. • A band-pass acceleration kernel is used to reduce reliance on prior information. • Experiments confirm the method's effectiveness with limited prior information. [ABSTRACT FROM AUTHOR]

Effective blood pressure (BP) management is crucial for early cardiovascular disease treatment. Photoplethysmography (PPG) waveform analysis presents a promising avenue for non-invasive BP estimation. However, existing methods often overlook the impact of PPG feature changes on BP variations, and the effectiveness and physiological interpretability of the features they employ remain largely unclear. Hence, this work introduces a single-channel BP estimation algorithm founded on the PPG differential features (DFs). A three-month tracking of PPG and BP data was conducted on 90 volunteers, and 68 blood pressure-related features were extracted from their PPG. The features in the first measurement data were used as baseline features. The differential features were obtained by subtracting the baseline features from the features in the subsequent measurement data through differential feature processing, and 11 DFs for BP estimation were retained using feature selection. Subsequently, four machine learning models were applied for the estimation of systolic (SBP) and diastolic blood pressure (DBP) changes, and finally introduced baseline blood pressure values to achieve BP estimation. Investigating the correlation between PPG DFs and BP changes, we observed a more significant correlation with BP changes for PPG DFs compared to PPG features. Among the machine learning models, the Random Forest model exhibited the most accurate estimation results in blood pressure, achieving standard deviation of the error(STD) of 7.15 mmHg for SBP and 5.30 mmHg for DBP, along with Pearson correlation coefficients (PCC) of 0.90 and 0.86, respectively. This work demonstrates that incorporating PPG feature changes with BP changes achieves higher accuracy in BP estimation, confirming the effectiveness of PPG DFs in BP estimation and providing valuable insights for long-term non-invasive blood pressure monitoring. • Estimation of blood pressure (BP) from a single-channel PPG signal. • Combining changes in features with changes in BP, the PPG differential feature is presented. • A collaborative filter-wrapper feature selection method is used to select the optimal subset of differential features. • Improving PPG signal quality using adaptive interception methods. • Introduction of individual baseline BP values improves the accuracy of BP estimation. [ABSTRACT FROM AUTHOR]

Graphical abstract Figure. Mechanism of CP-25 combined with MTX/LEF to ameliorate AA rats In the one hand, CP-25 alone and in combination blocked the activation of P38, ERK, and JNK. CP-25 combined with MTX/LEF exerts synergistic effects to inhibit inflammation of AA rats by inhibiting the MAPK pathway. In the other hand, CP-25 inhibited GRK2 translocation in AA rats which further restored the inhibition of GRK2 on p-ERK. CP-25 synergized with MTX/LEF through GRK2-induced inhibition of p-ERK, thereby suppressing inflammation in AA rats. Highlights • CP-25 combined with low-dose MTX/LEF showed equivalent therapeutic effects of high-dose MTX/LEF. • CP-25 decreased the expression of p-ERK through the inhibition on GRK2 membrane expression. • CP-25 has potential as a useful drug for the combined treatment of patients with RA. Abstract Objective CP-25 attenuates arthritis progression in animal models by inhibiting G protein-coupled receptor kinase 2 (GRK2) membrane expression. This study compared groups treated with high-dose methotrexate (MTX)/leflunomide (LEF) and CP-25 combined with low-dose MTX/LEF in an adjuvant-induced arthritis (AA) rat model and investigated possible mechanisms. Methods AA was induced in rats via complete Freund's adjuvant. Experimental groups were divided into a normal group; vehicle group; monotherapy groups, including CP-25 (50 mg/kg), MTX (0.25, 0.5 mg/kg), and LEF (5, 10 mg/kg); and CP-25 (50 mg/kg)-combined MTX (0.25 mg/kg)/LEF (5 mg/kg) groups. We measured cytokine levels, phosphorylation and protein expression, and interactions between proteins. The role of GRK2 on phosphorylated extracellular signal-regulated kinase (p-ERK) was determined via GRK2-siRNA using a high content imaging system. Results Therapeutic effects, including pathology and cytokine balance, were equivalent between the CP-25-combination groups and the high-dose MTX/LEF groups. P38, ERK, and c-Jun N-terminal kinase (JNK) activation in AA fibroblast-like synoviocytes (FLS) was reduced in the treatment groups; GRK2 expression was only inhibited in the CP-25 group. Interactions between GRK2 and p-ERK decreased in the vehicle group and were restored in the CP-25 group. GRK2 membrane expression and p-ERK nuclear expression increased in FLS pre-treated with tumour necrosis factor alpha and stimulated with prostaglandin E2. Nuclear expression of p-ERK increased in GRK2-siRNA FLS. Conclusion Equivalent therapeutic effects were observed between CP-25-combination groups and high-dose MTX/LEF groups. CP-25 inhibited p-ERK by reducing the membrane expression of GRK2 in FLS from AA rats. [ABSTRACT FROM AUTHOR]

Abstract Stability of silver sulfide nanoparticle (Ag 2 S-NP) in the environment has recently drawn considerable attention since it is associated with environmental risk. Although the overestimated stability of Ag 2 S-NP in aqueous solution has already been recognized, studies on transformation of Ag 2 S-NP in environmental water are still very scarce. Here we reported that Ag 2 S-NP could undergo dissolution by manganese(IV) oxide (MnO 2), an important naturally occurring oxidant in the environment, even in environmental water, although the dissolved silver would probably be adsorbed onto the particles (>0.45 μm) in environmental water, mitigating the measurable levels of dissolved silver. The extent and rate of Ag 2 S-NP dissolution rose with the increasing concentration of MnO 2. In addition, environmental factors including natural organic matter, inorganic salts and organic acids could accelerate the Ag 2 S-NP dissolution by MnO 2 , wherein an increase in dissolution extent was also observed. We further documented that Ag 2 S-NP dissolution by MnO 2 was highly dependent on O 2 and it was an oxidative dissolution, with the production of SO 4 2−. Finally, dissolution of Ag 2 S-NP by MnO 2 affected zebra fish (Danio rerio) embryo viability, showing significant reduction in embryo survival and hatching rates, compared to embryos exposed to Ag 2 S-NP, MnO 2 or dissolved manganese alone. These findings would further shed light on the stability of Ag 2 S-NP in the natural environment - essential for comprehensive nano risk assessment. Graphical abstract Image 1 Highlights • Ag 2 S-NP underwent dissolution by manganese(IV) oxide even in environmental water. • The extent and rate of Ag 2 S-NP dissolution were dependent on MnO 2 concentration. • Environmental factors would affect the Ag 2 S-NP dissolution by MnO 2. • Ag 2 S-NP dissolution by MnO 2 , an oxidative dissolution, was dependent on O 2. • Dissolution of Ag 2 S-NP by MnO 2 reduced zebra fish (Danio rerio) embryo viability. Ag 2 S-NP could undergo dissolution by manganese oxide (MnO 2) even in environmental water, which would affect zebra fish embryo viability, showing potential risks of Ag 2 S-NP in the environment. [ABSTRACT FROM AUTHOR]

Long-term monitoring and effective management of triglycerides (TG) are crucial to reducing morbidity in patients with cardiovascular diseases. However, frequent invasive TG detection increases patient inconvenience and discomfort. Many efforts have been made to estimate TG based on photoplethysmogram (PPG), but current studies dissatisfy the practical application due to unclear quantitative relationship between PPG features and TG. This study investigated a framework for non-invasive TG detection based on finger PPG signals to quantify the contribution of PPG features to TG estimation. 58 features for TG detection are extracted from the PPG of 133 cardiovascular patients. The relationship between PPG features and TG is analyzed for quantitative purposes, and the pathological significance of features is further combined to remove irrelevant ones. To improve the accuracy of TG estimation, a complementary feature selection method is proposed that uses the complementary coefficient and feature stability as evaluation indicators to select the optimal feature combination from the mixed features. Finally, the Transformer algorithm strengthens the link between complementary features for TG estimation. Our results demonstrated that many PPG features are moderately correlated with TG, and feature K shows the highest correlation score (r = 0.48). When using a subset of 6 selected PPG features, the performance of TG estimation based on complementary features is significantly better than that using normal mixed features, which combined with the Transformer model reduced MAE and SDE to 0.37 mmol/L and 5.26 mmol/L, respectively, and increased PCC to 0.86. The proposed PPG-based TG detection method clarifies the quantitative relationship between PPG features and TG and provides a new idea for non-invasive TG detection. • Noninvasive triglyceride estimation is possible only using PPG. • Quantifying the contribution of PPG features to triglyceride estimation. • Complementary feature selection methods obtain an optimal feature combination. • The interaction between features is measured by the complementarity coefficient. [ABSTRACT FROM AUTHOR]

The aggregation and deposition of carbon nanotubes (CNTs) determines their transport and fate in natural waters. Therefore, the aggregation kinetics of humic-acid treated multi-walled carbon nanotubes (HA-MWCNTs) was investigated by time-resolved dynamic light scattering in NaCl and CaCl 2 electrolyte solutions. Increased ionic strength induced HA-MWCNT aggregation due to the less negative zeta potential and the reduced electrostatic repulsion. The critical coagulation concentration (CCC) values of HA-MWCNTs were 80 mmol/L in NaCl and 1.3 mmol/L in CaCl 2 electrolyte, showing that Ca 2 + causes more serious aggregation than Na + . The aggregation behavior of HA-MWCNTs was consistent with Derjaguin–Landau–Verwey–Overbeek theory. The deposition kinetics of HA-MWCNTs was measured by the optical absorbance at 800 nm. The critical deposition concentrations for HA-MWCNT in NaCl and CaCl 2 solutions were close to the CCC values, therefore the rate of deposition cannot be increased by changing the ionic strength in the diffusion-limited aggregation regime. The deposition process was correlated to the aggregation since larger aggregates increased gravitational deposition and decreased random Brownian diffusion. HA-MWCNTs hydrodynamic diameters were evaluated at 5, 15 and 25°C. Higher temperature caused faster aggregation due to the reduced electrostatic repulsion and increased random Brownian motion and collision frequency. HA-MWCNTs aggregate faster at higher temperature in either NaCl or CaCl 2 electrolyte due to the decreased electrostatic repulsion and increased random Brownian motion. Our results suggest that CNT aggregation and deposition are two correlated processes governed by the electrolyte, and CNT transport is favored at low ionic strength and low temperature. [ABSTRACT FROM AUTHOR]

Abstract: The solubility of levofloxacin in six solvents including ethanol, 1-propanol, 2-propanol, 1-butanol, acetic acid and ethyl acetate in the temperature range of 288.15–328.15K at atmospheric pressure was measured by a balance method. It is indicated that the solubility data of levofloxacin in selected solvents increase with increasing temperature. The experimental solubilities were correlated by the modified Apelblat equation which fits well with the experimental data. Further the molecular modeling studies indicate that the higher solubility of levofloxacin in acetic acid is due to the stronger hydrogen bonds between the solute and solvent molecules. The dissolution enthalpy, dissolution entropy and the molar Gibbs energy were predicted. Finally, the solubility data were correlated using two local composition models of NRTL 1 and UNIQUAC. [Copyright &y& Elsevier]

Wavelet transform is able to characterize the fabric texture at multiscale and multiorientation, which provides a promising way to the classification of fabric defects. For the objective of minimum error rate in the defect classification, this paper compares six wavelet transform-based classification methods, using different discriminative training approaches to the design of the feature extractor and classifier. These six classification methods are: methods of using an Euclidean distance classifier and a neural network classifier trained by maximum likelihood method and backpropagation algorithm, respectively; methods of using an Euclidean distance classifier and a neural network classifier trained by minimum classification error method, respectively; method of using a linear transformation matrix-based feature extractor and an Euclidean distance classifier, designed by discriminative feature extraction (DFE) method; method of using an adaptive wavelet-based feature extractor and an Euclidean distance classifier, designed by the DFE method. These six approaches have been evaluated on the classification of 466 defect samples containing eight classes of fabric defects, and 434 nondefect samples. The DFE training approach using adaptive wavelet has been shown to outperform the other approaches, where 95.8% classification accuracy was achieved. [Copyright &y& Elsevier]

Inhalation of respirable silica particles can cause serious lung diseases (e.g., silicosis and lung cancer), and the toxicity of respirable silica is highly dependent on its crystal form. Common combustion processes such as coal and biomass burning can provide high temperature environments that may alter the crystal forms of silica and thus affect its toxic effects. Although crystalline silica (i.e., quartz, tridymite, and cristobalite) were widely found at different temperatures during the burning processes, the sources and crystal transformation pathways of silica in the burning processes are still not well understood. Here, we investigate the crystal transformation of silica in the coal and biomass combustion processes and clarify the detailed transformation pathways of silica for the first time. Specifically, in coal burning process, amorphous silica can transform into quartz and cristobalite starting at 1100 °C, and quartz transforms into cristobalite starting at 1200 °C; in biomass burning process, amorphous silica can transform into cristobalite starting at 800 °C, and cristobalite transforms into tridymite starting at 1000 °C. These transformation temperatures are significantly lower than those predicted by the classic theory due to possibly the catalysis of coexisting metal elements (e.g., aluminum, iron, and potassium). Our results not only enable a deeper understanding on the combustion-induced crystal transformation of silica, but also contribute to the mitigation of population exposure to respirable silica. [Display omitted] • Coal and biomass burning processes can alter the crystal forms of silica particles. • Environmental media can facilitate the crystal transformation of silica particles. • Crystalline respirable silica have multiple sources in the coal burning process. • Our results help to better understand the health risks of respirable silica. [ABSTRACT FROM AUTHOR]

• The ascending and descending phases of BOLD signal modulates face recognition. • Inter-regional phase lag distinguishes the face processing and frontoparietal systems. • Inter-regional phase lag in the infra-slow frequency range is essential for cognitive performance. Low frequency phase synchronization is an essential mechanism of information communication among brain regions. In the infra-slow frequency range (<0.1 Hz), inter-regional phase lag is of importance for brain function (e.g., anti-phase between the default mode network and task positive network). However, the role of phase lag in cognitive processing remains unclear. Based on the frequency tagging experimental paradigm and functional magnetic resonance imaging (fMRI) technique, we investigated inter-regional phase lag and phase coherence using a face recognition task (n = 30, 15 males/15 females). Phase coherence within the face processing system was significantly increased during task state, highlighting the importance of regular inter-regional phase relationship for face recognition. Moreover, results showed decreased phase lag within the core and extended face areas (face processing system) and increased phase lag between the face processing system and frontoparietal network, indicating a reorganization of inter-regional relationships of the two systems. Inter-regional phase lag was modulated by the task at ascending and descending phases of the fMRI signal, suggesting a phase-dependent inter-regional relationship. Furthermore, phase lags between visual cortex and amygdala and between visual cortex and motor area were positively related to reaction time, indicating better task performance depends on both rapid emotional detection pathway and visual-motor pathway. Overall, inter-regional phase synchronization in the infra-slow frequency range is of important for effective information communication and cognitive performance. [ABSTRACT FROM AUTHOR]

Background: Is it healthy to be chaotic? Recent studies have argued that mental disorders are associated with more orderly neural activities, corresponding to a less flexible functional system. These conclusions were derived from altered temporal complexity. However, the relationship between spatial complexity and health is unknown, although spatial configuration is of importance for normal brain function.Methods: Based on resting-state functional magnetic resonance imaging data, we used Sample entropy (SampEn) to evaluate the altered spatial complexity in patients with generalized anxiety disorder (GAD; n = 47) compared to healthy controls (HCs; n = 38) and the relationship between spatial complexity and anxiety level.Results: Converging results showed increased spatial complexity in patients with GAD, indicating more chaotic spatial configuration. Interestingly, inverted-U relationship was revealed between spatial complexity and anxiety level, suggesting complex relationship between health and the chaos of human brain.Limitations: Anxiety-related alteration of spatial complexity should be verified at voxel level in a larger sample and compared with results of other indices to clarify the mechanism of spatial chaotic of anxiety.Conclusions: Altered spatial complexity in the brain of GAD patients mirrors inverted-U relationship between anxiety and behavioral performance, which may reflect an important characteristic of anxiety. These results indicate that SampEn is a good reflection of human health or trait mental characteristic. [ABSTRACT FROM AUTHOR]

In this paper, we propose a robust respiratory rate (RR) measurement method using a two-level fusion of video and FMCW (frequency modulated continuous wave) radar information. Specifically, the video pixel displacement signals and the radar phase variation signals are extracted independently in shoulders and chest regions, which are then denoised by the serial-CEEMDAN (SCEEMDAN) method to obtain the corresponding single modal RR values. Next, at the feature level, the multivariate singular spectrum analysis (MSSA) is employed to extract the shared respiratory components in the video and radar modalities. Finally, at the decision level, we calculate the target RR value based on a signal-to-noise ratio (SNR) weighting of all single-modality and MSSA results. The proposed two-level fusion method is evaluated on a self-collected dataset, which includes 15 healthy subjects acting five challenging activities. The experimental results show that the proposed fusion method significantly outperform that of the single modality. • The serial-CEEMDAN method is introduced to denoise the respiratory signals. • A two-level fusion method is proposed for motion robust respiratory measurements. • Experimental results in challenging scenarios verify the benefits of the method. [ABSTRACT FROM AUTHOR]

Many populations worldwide are suffering from central nervous system (CNS) diseases such as brain tumors, neurodegenerative diseases (Alzheimer's disease, Parkinson's disease and Huntington's disease) and stroke. There is a shortage of effective drugs for most CNS diseases. As one of the regulatory mechanisms of epigenetics, the particular role and therapeutic benefits of histone deacetylases (HDACs) in the CNS have been extensively studied. In recent years, HDACs have attracted increasing attention as potential drug targets for CNS diseases. In this review, we summarize the recent applications of representative histone deacetylases inhibitors (HDACis) in CNS diseases and discuss the challenges in developing HDACis with different structures and better blood-brain barrier (BBB) permeability, hoping to promote the development of more effective bioactive HDACis for the treatment of CNS diseases. [Display omitted] • HDACis have received considerable attention as potential therapeutics for various CNS diseases. • Designing HDACis with different structures and better BBB permeability is of great significance but also challenging. • More research is needed on the correlation between specific subtypes of HDACs and CNS diseases. [ABSTRACT FROM AUTHOR]

Ethnopharmacological relevance Total glucosides of paeony (TGP) is the first anti-inflammatory immune regulatory drug approved for the treatment of rheumatoid arthritis in China. A novel compound, paeoniflorin-6′-O-benzene sulfonate (code CP-25), comes from the structural modification of paeoniflorin (Pae), which is the effective active ingredient of TGP. The aim of the present study is to investigate the effect of CP-25 on adjuvant arthritis (AA) fibroblast-like syn oviocytes (FLS) co-cultured with BAFF-activated CD4 + T cells and the expression of BAFF-R in CD4 + T cells. Methods The mRNA expression of BAFF and its receptors was assessed by qPCR. The expression of BAFF receptors in CD4 + T cells was analyzed by flow cytometry. The effect of CP-25 on AA rats was evaluated by their joint histopathology. The cell culture growth of thymocytes and FLS was detected by cell counting kit (CCK-8). The concentrations of IL-1β, TNF-α, and IL-6 were measured by Enzyme-linked immunosorbent assay (ELISA). Results The mRNA expression levels of BAFF and BAFF-R were enhanced in the mesenteric lymph nodes of AA rats, TACI expression was reduced, and BCMA had no change. The expression of BAFF-R in CD4 + T cells was also enhanced. CP-25 alleviated the joint histopathology and decreased the expression of BAFF-R in CD4 + T cells from AA rats in vivo . In vitro, CP-25 inhibited the abnormal cell culture growth of BAFF-stimulated thymocytes and FLS. In the co-culture system, IL-1β, IL-6 and TNF-α production was enhanced by FLS co-cultured with BAFF-activated CD4 + T cells. Moreover, BAFF-stimulated CD4 + T cells promoted the cell culture growth of FLS. The addition of CP-25 decreased the expression of BAFF-R in CD4 + T cells and inhibited the cell culture growth and cytokine secretion ability of FLS co-cultured with BAFF-activated CD4 + T cells. Conclusion The present study indicates that CP-25 may repress the cell culture growth and cytokine secretion ability of FLS, and its inhibitory effects might be associated with its ability to inhibit the expression of BAFF-R in CD4 + T cells in a co-culture. These observations might provide a scientific basis for the development of new drugs for the treatment of autoimmune diseases by CP-25. [ABSTRACT FROM AUTHOR]