Assessing the role of surface layer and molecular probe size in diffusion within meniscus tissue.

Diffusion within extracellular matrix is essential to deliver nutrients and larger metabolites to the avascular region of the meniscus. It is well known that both structure and composition of the meniscus vary across its regions; therefore, it is crucial to fully understand how the heterogenous meniscal architecture affects its diffusive properties. The objective of this study was to investigate the effect of meniscal region (core tissue, femoral, and tibial surface layers) and molecular weight on the diffusivity of several molecules in porcine meniscus. Tissue samples were harvested from the central area of porcine lateral menisci. Diffusivity of fluorescein (MW 332 Da) and three fluorescence-labeled dextrans (MW 3k, 40k, and 150k Da) was measured via fluorescence recovery after photobleaching. Diffusivity was affected by molecular size, decreasing as the Stokes' radius of the solute increased. There was no significant effect of meniscal region on diffusivity for fluorescein, 3k and 40k dextrans (p>0.05). However, region did significantly affect the diffusivity of 150k Dextran, with that in the tibial surface layer being larger than in the core region (p = 0.001). Our findings contribute novel knowledge concerning the transport properties of the meniscus fibrocartilage. This data can be used to advance the understanding of tissue pathophysiology and explore effective approaches for tissue restoration.

A Facile NMR Method for Pre-MRI Evaluation of Trigger-Responsive T1 Contrast Enhancement.

There is a growing interest in developing paramagnetic nanoparticles as responsive magnetic resonance imaging (MRI) contrast agents, which feature switchable T1 image contrast of water protons upon biochemical cues for better discerning diseases. However, performing an MRI is pragmatically limited by its cost and availability. Hence, a facile, routine method for measuring the T1 contrast is highly desired in early-stage development. This work presents a single-point inversion recovery (IR) nuclear magnetic resonance (NMR) method that can rapidly evaluate T1 contrast change by employing a single, optimized IR pulse sequence that minimizes water signal for "off-state" nanoparticles and allows for sensitively measuring the signal change with "switch-on" T1 contrast. Using peptide-induced liposomal gadopentetic acid (Gd3+ -DTPA) release and redox-sensitive manganese oxide (MnO2 ) nanoparticles as a demonstration of generality, this method successfully evaluates the T1 shortening of water protons caused by liposomal Gd3+ -DTPA release and Mn2+ formation from MnO2 reduction. Furthermore, the NMR measurement is highly correlated to T1 -weighted MRI scans, suggesting its feasibility to predict the MRI results at the same field strength. This NMR method can be a low-cost, time-saving alternative for pre-MRI evaluation for a diversity of responsive T1 contrast systems.

A >50% Intraoperative Parathyroid Hormone Decrease Into Normal Reference Range Predicts Complete Excision of Malignancy in Patients With Parathyroid Carcinoma.

INTRODUCTION: The mainstay of successful treatment for parathyroid carcinoma remains complete surgical excision. Although intraoperative parathyroid hormone (ioPTH) monitoring is a useful adjunct during parathyroidectomy for benign primary hyperparathyroidism, its utility for parathyroid carcinoma remains unclear. METHODS: A retrospective review of 796 patients who underwent parathyroidectomy with ioPTH monitoring for primary hyperparathyroidism revealed 13 patients with parathyroid carcinoma on final pathology from two academic institutions. A systematic review yielded 5 additional parathyroid carcinoma patients. Complete excision of malignancy, or operative success (eucalcemia ≥6 mo. after parathyroidectomy); operative failure (persistent hypercalcemia <6 mo. after parathyroidectomy); and perioperative complications were evaluated. Comparison of the >50% ioPTH decrease alone to >50% ioPTH decrease into normal reference range was analyzed using Chi-squared, Kolmogorov-Smirnov, Kruskal-Wallis tests. RESULTS: All 18 parathyroid carcinoma patients achieved a >50% ioPTH decrease, and 14 patients also had a final ioPTH level decrease into normal reference range. 93% of patients who met normal parathyroid hormone reference range had operative success, whereas only two of the four (50%) patients with parathyroid carcinoma with a >50% ioPTH decrease alone demonstrated operative success. CONCLUSIONS: Parathyroidectomy guided by a >50% ioPTH decrease into normal reference range may better predict complete excision of malignant tissue in patients with parathyroid carcinoma compared to >50% ioPTH decrease alone. IoPTH monitoring should be used in conjunction with clinical judgment and complete en bloc resection for optimal treatment and success.

Recurrence Network Analysis of Histopathological Images for the Detection of Invasive Ductal Carcinoma in Breast Cancer.

The histopathological image analysis is one of the most crucial diagnostic procedures to identify Invasive ductal carcinoma (IDC) in breast cancers. However, this diagnosis process is currently time-consuming and heavily dependent on human expertise. Prior research has shown that different degrees of tumors present various microstructures in the histopathological images. However, very little has been done to utilize spatial recurrence features of microstructures for identifying IDC. This paper presents a novel recurrence analysis methodology for automatic image-guided IDC detection. We first utilize wavelet decomposition to delineate the subtle information in the images. Then, we model the patches with a weighted recurrence network approach to characterize the recurrence patterns of the histopathological images. Finally, we develop automated IDC detection models leveraging machine learning methods with spatial recurrence features extracted. The developed recurrence analysis models successfully characterize the complex microstructures of histopathological images and achieve the IDC detection performances of at least AUC = 0.96. This research developed a spatial recurrence analysis methodology to effectively identify IDC regions in histopathological images for BC. It shows a high potential to assist physicians in the decision-making process. The proposed methodology can further be applicable to image processing for other medical or biological applications.

Evaluation of aristolochic acid Ι nephrotoxicity in mice via 1H NMR quantitative metabolomics and network pharmacology approaches.

Background: Although many studies have shown that herbs containing aristolochic acids can treat various human diseases, AAΙ in particular has been implicated as a nephrotoxic agent. Methods and results: Here, we detail the nephrotoxic effect of AAΙ via an approach that integrated 1H NMR-based metabonomics and network pharmacology. Our findings revealed renal injury in mice after the administration of AAΙ. Metabolomic data confirmed significant differences among the renal metabolic profiles of control and model groups, with significant reductions in 12 differential metabolites relevant to 23 metabolic pathways. Among them, there were seven important metabolic pathways: arginine and proline metabolism; glycine, serine, and threonine metabolism; taurine and hypotaurine metabolism; ascorbate and aldehyde glycolate metabolism; pentose and glucosinolate interconversion; alanine, aspartate, and glutamate metabolism; and glyoxylate and dicarboxylic acid metabolism. Relevant genes, namely, nitric oxide synthase 1 (NOS1), pyrroline-5-carboxylate reductase 1 (PYCR1), nitric oxide synthase 3 (NOS3) and glutamic oxaloacetic transaminase 2 (GOT2), were highlighted via network pharmacology and molecular docking techniques. Quantitative real-time PCR findings revealed that AAI administration significantly downregulated GOT2 and NOS3 and significantly upregulated NOS1 and PYCR1 expression and thus influenced the metabolism of arginine and proline. Conclusion: This work provides a meaningful insight for the mechanism of AAΙ renal injury.

Urine-derived exosomal PSMA is a promising diagnostic biomarker for the detection of prostate cancer on initial biopsy

Purpose It is well-established that the lack of accurate diagnostic modalities for prostate cancer (PCa) leads to overdiagnosis and overtreatments. Accordingly, this study aimed to assess the value of urine-derived exosomal prostate-specific membrane antigen (PSMA) as a biomarker for the diagnosis of PCa and clinically significant prostate cancer (csPCa). Methods A total of 284 urine samples were collected from patients after the digital rectal examination (DRE). Urinary exosomes were extracted using commercial kits, and urine-derived exosomal PSMA was determined via enzyme-linked immunosorbent assay (ELISA). Evaluation of diagnostic accuracy of PSMA was performed via receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and waterfall plots. Results We found that urine-derived exosomal PSMA was significantly higher in PCa and csPCa than in benign prostatic hyperplasia (BPH) and BPH + non-aggressive prostate cancer (naPCa) groups (P < 0.001). Furthermore, the urine-derived exosome PSMA yielded area under the ROC curve (AUC) values of 0.876 and 0.826 for detecting PCa and csPCa, respectively, suggesting better performance than traditional clinical biomarkers. Besides, when the cutoff value used corresponded to a sensitivity of 95%, urine-derived exosomal PSMA could avoid unnecessary biopsies in 41.2% of cases and missed only 0.7% of csPCa cases. Conclusions Urine-derived exosomal PSMA exhibits a good diagnostic yield for detecting PCa and csPCa. Findings of the present study provide the foothold for future studies on cancer management and research in this patient population (AU)

Assessment of lake area in response to climate change at varying elevations: A case study of Mt. Tianshan, Central Asia.

Changes in lake area (water surface area) are often considered accurate and sensitive representations of climate change. However, the role that elevation plays in this dynamic is somewhat unclear; studies remain inconclusive as to whether lake responses are consistent across elevation gradients. Here, we used Landsat and keyhole satellite images to quantify lake area changes from the 1960s to 2020 at different elevations in Central Asia's Tianshan Mountains and relate them to both climatic and anthropogenic factors. The results revealed that all low-elevation lakes showed a decreasing trend, and the total area of all monitored low-elevation lakes was reduced by 18.50 %. The total area of the mid-elevation lakes decreased by 0.16 %, while the total area of the high-elevation glacial lakes increased by 4.35 %. Lakes are recharged by a variety of influxes including glacial meltwater and precipitation. Notably, human activities (urban and agricultural water consumption) were the dominant factors in the shrinkage of low-elevation lakes. Climatic factors were the main driving factors of mid-elevation lake changes, and these lakes appeared to be more sensitive to temperature changes than lakes at other elevations. In addition, significant warming dominated area changes in high-elevation proglacial and unconnected glacial lakes. Overall, those results emphasized that when using lakes to reconstruct paleoclimates or predict lake evolution, it is necessary to consider how elevation gradients and recharge types may affect lake sensitivity to variations in climatic and anthropogenic activity.

Genetically encoded Runx3 and CD4+ intestinal epithelial lymphocyte deficiencies link SKG mouse and human predisposition to spondyloarthropathy.

Disturbances in immune regulation, intestinal dysbiosis and inflammation characterize ankylosing spondylitis (AS), which is associated with RUNX3 loss-of-function variants. ZAP70W163C mutant (SKG) mice have reduced ZAP70 signaling, spondyloarthritis and ileitis. In small intestine, Foxp3+ regulatory T cells (Treg) and CD4+CD8αα+TCRαß+ intraepithelial lymphocytes (CD4-IEL) control inflammation. TGF-ß and retinoic acid (RA)-producing dendritic cells and MHC-class II+ intestinal epithelial cells (IEC) are required for Treg and CD4-IEL differentiation from CD4+ conventional or Treg precursors, with upregulation of Runx3 and suppression of ThPOK. We show in SKG mouse ileum, that ZAP70W163C or ZAP70 inhibition prevented CD4-IEL but not Treg differentiation, dysregulating Runx3 and ThPOK. TGF-ß/RA-mediated CD4-IEL development, T-cell IFN-γ production, MHC class-II+ IEC, tissue-resident memory T-cell and Runx3-regulated genes were reduced. In AS intestine, CD4-IEL were decreased, while in AS blood CD4+CD8+ T cells were reduced and Treg increased. Thus, genetically-encoded TCR signaling dysfunction links intestinal T-cell immunodeficiency in mouse and human spondyloarthropathy.

Urine-derived exosomal PSMA is a promising diagnostic biomarker for the detection of prostate cancer on initial biopsy.

PURPOSE: It is well-established that the lack of accurate diagnostic modalities for prostate cancer (PCa) leads to overdiagnosis and overtreatments. Accordingly, this study aimed to assess the value of urine-derived exosomal prostate-specific membrane antigen (PSMA) as a biomarker for the diagnosis of PCa and clinically significant prostate cancer (csPCa). METHODS: A total of 284 urine samples were collected from patients after the digital rectal examination (DRE). Urinary exosomes were extracted using commercial kits, and urine-derived exosomal PSMA was determined via enzyme-linked immunosorbent assay (ELISA). Evaluation of diagnostic accuracy of PSMA was performed via receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and waterfall plots. RESULTS: We found that urine-derived exosomal PSMA was significantly higher in PCa and csPCa than in benign prostatic hyperplasia (BPH) and BPH + non-aggressive prostate cancer (naPCa) groups (P < 0.001). Furthermore, the urine-derived exosome PSMA yielded area under the ROC curve (AUC) values of 0.876 and 0.826 for detecting PCa and csPCa, respectively, suggesting better performance than traditional clinical biomarkers. Besides, when the cutoff value used corresponded to a sensitivity of 95%, urine-derived exosomal PSMA could avoid unnecessary biopsies in 41.2% of cases and missed only 0.7% of csPCa cases. CONCLUSIONS: Urine-derived exosomal PSMA exhibits a good diagnostic yield for detecting PCa and csPCa. Findings of the present study provide the foothold for future studies on cancer management and research in this patient population.

Metabonomics and 16S rRNA gene sequencing to study the therapeutic mechanism of Danggui Sini decoction on collagen-induced rheumatoid arthritis rats with Cold Bi syndrome.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by persistent joint inflammation. The development of rheumatoid arthritis is directly correlated with the disturbance of gut microbiome and its metabolites. RA can be effectively treated with the Danggui Sini decoction (DSD), a Traditional Chinese medicine (TCM) prescription from the Treatise on Febrile Diseases. Further research is needed to clarify the precise mechanism of DSD in the treatment of RA. In this study, 1H NMR metabonomics and 16 S rRNA gene sequencing techniques were used to clarify the intervention of DSD on CIA-induced RA. The results of 1H NMR metabolomics of feces revealed that five metabolites (alanine, glucose, taurine, betaine, and xylose) were disturbed, which could be regarded as potential biomarkers of RA. The intestinal microbiome of RA rats had changed, according to the results of 16 S rRNA gene sequencing; eight microbes (g_norank_f_Eubacterium_coprostanoligenes_group, g_Ruminococcus_torques_group, g_Dubosiell, g_Lactobacillus, g_norank_f_Desulfovibrionaceae, g_Bacteroides, g_Oscillibacter, and g_Romboutsia) occurred significantly at the genus level, and DSD significantly impacted six of them (g_Dubosiell, g_Lactobacillus, g_norank_f_Eubacterium_coprostanoligenes_group, g_Ruminococcus_torques_grou, g_Bacteroides, and g_Romboutsia). Three of them (g_norank_f_Eubacterium_ coprostanoligenes_group, g_Romboutsia, and g_Lactobacillus) were regarded as key microbiomes for DSD to treat RA, and three common metabolic pathways (taurine and hypotaurine metabolism; alanine, aspartate, and glutamate metabolism; primary bile acid biosynthesis) were discovered based on the 1H NMR metabonomics and PICRUST2 prediction of 16 S rRNA gene sequencing. Six SCFAs in feces (acetic acid, butyric acid, propionic acid, caproic acid, isobutyric acid, and valeric acid) increased significantly in RA, according to the outcomes of targeting SCFAs, while five SCFAs (acetic acid, butyric acid, propionic acid, caproic acid, and valeric acid) had decreased significantly due to DSD treatment. In conclusion, our study indicated that DSD could regulate RA's metabolic disorder by affecting intestinal microbiome and its metabolites. It also establishes a framework for future research into exploiting gut microbes therapeutic to treat RA.

A Toolkit for Engineering Proteins in Living Cells: Peptide with a Tryptophan-Selective Ru-TAP Complex to Regioselectively Photolabel Specific Proteins.

Using a chemical approach to crosslink functionally versatile bioeffectors (such as peptides) to native proteins of interest (POI) directly inside a living cell is a useful toolbox for chemical biologists. However, this goal has not been reached due to unsatisfactory chemoselectivity, regioselectivity, and protein selectivity in protein labeling within living cells. Herein, we report the proof of concept of a cytocompatible and highly selective photolabeling strategy using a tryptophan-specific Ru-TAP complex as a photocrosslinker. Aside from the high selectivity, the photolabeling is blue light-driven by a photoinduced electron transfer (PeT) and allows the bioeffector to bear an additional UV-responsive unit. The two different photosensitivities are demonstrated by blue light-photocrosslinking a UV-sensitive peptide to POI. Our visible light photolabeling can generate photocaged proteins for subsequent activity manipulation by UV light. Cytoskeletal dynamics regulation is demonstrated in living cells via the unprecedented POI photomanipulation and proves that our methodology opens a new avenue to endogenous protein modification.

The Test Based on Meta-Analysis on "Does Workaholism Prefer Task Performance or Contextual Performance?"

The relationship between workaholism and work performance is explored by meta-analysis in this article. After searching relevant references, we had gained 94 individual effect sizes (n = 57,352), 45 individual samples, and 37 references. Through the heterogeneity test, it was shown that the random effect model is more suitable. The main effect analysis showed that there is a significant positive correlation between workaholism, working excessively, working compulsively, and work performance, and further analysis showed that workaholism emphasizes the improvement of contextual performance. The subgroup test showed that the relationship between workaholism, working excessively, working compulsively, and work performance is influenced by the measurement tools of workaholism, but not influenced by the cultural background differences and time-lag research. The above results show that workaholism and its dimensions have different influences on different aspects of work performance. Besides, it is worthy to consider the moderating function of the measurement tools of workaholism in the relationship between workaholism and work performance.

Liposomal PHD2 Inhibitors and the Enhanced Efficacy in Stabilizing HIF-1α.

Prolyl hydroxylase domain-containing protein 2 (PHD2) inhibition, which stabilizes hypoxia-inducible factor (HIF)-1α and thus triggers adaptation responses to hypoxia in cells, has become an important therapeutic target. Despite the proven high potency, small-molecule PHD2 inhibitors such as IOX2 may require a nanoformulation for favorable biodistribution to reduce off-target toxicity. A liposome formulation for improving the pharmacokinetics of an encapsulated drug while allowing a targeted delivery is a viable option. This study aimed to develop an efficient loading method that can encapsulate IOX2 and other PHD2 inhibitors with similar pharmacophore features in nanosized liposomes. Driven by a transmembrane calcium acetate gradient, a nearly 100% remote loading efficiency of IOX2 into liposomes was achieved with an optimized extraliposomal solution. The electron microscopy imaging revealed that IOX2 formed nanoprecipitates inside the liposome's interior compartments after loading. For drug efficacy, liposomal IOX2 outperformed the free drug in inducing the HIF-1α levels in cell experiments, especially when using a targeting ligand. This method also enabled two clinically used inhibitors-vadadustat and roxadustat-to be loaded into liposomes with a high encapsulation efficiency, indicating its generality to load other heterocyclic glycinamide PHD2 inhibitors. We believe that the liposome formulation of PHD2 inhibitors, particularly in conjunction with active targeting, would have therapeutic potential for treating more specifically localized disease lesions.

Immune cell shuttle for precise delivery of nanotherapeutics for heart disease and cancer.

The delivery of therapeutics through the circulatory system is one of the least arduous and less invasive interventions; however, this approach is hampered by low vascular density or permeability. In this study, by exploiting the ability of monocytes to actively penetrate into diseased sites, we designed aptamer-based lipid nanovectors that actively bind onto the surface of monocytes and are released upon reaching the diseased sites. Our method was thoroughly assessed through treating two of the top causes of death in the world, cardiac ischemia-reperfusion injury and pancreatic ductal adenocarcinoma with or without liver metastasis, and showed a significant increase in survival and healing with no toxicity to the liver and kidneys in either case, indicating the success and ubiquity of our platform. We believe that this system provides a new therapeutic method, which can potentially be adapted to treat a myriad of diseases that involve monocyte recruitment in their pathophysiology.

Combining 1H-NMR-based metabonomics and network pharmacology to dissect the mechanism of antidepression effect of Milletia speciosa Champ on mouse with chronic unpredictable mild stress-induced depression.

OBJECTIVES: Milletia speciosa Champ (MS), a traditional Chinese medicine, has the abilities of antistress, antifatigue, anti-oxidation and so on. In our previous study, MS was found to antidepression while the underlying mechanism of which needs further elucidation. METHODS: Here, a proton nuclear magnetic resonance (1H-NMR)-based metabonomics combined network pharmacology research approach was performed to investigate the antidepressive mechanism of MS act on mouse with chronic unpredictable mild stress-induced depression. KEY FINDINGS: Results showed that MS could alleviate the ethology of depression (including sucrose preference degree, crossing lattice numbers and stand-up times) and disordered biochemical parameters (5-hydroxytryptamine, norepinephrine and brain-derived neurotrophic factor). Metabonomics study and network pharmacology analysis showed that MS might improve depression through synergistically regulating five targets including Maoa, Maob, Ache, Ido1 and Comt, and three metabolic pathways such as tryptophan metabolism, synthesis of neurotransmitter and phospholipid metabolism. CONCLUSIONS: This study for the first time preliminary clarified the potential antidepressive mechanism of MS and provided theoretical basis for developing MS into novel effective antidepressant.

Response of altitudinal vegetation belts of the Tianshan Mountains in northwestern China to climate change during 1989-2015.

Within the mountain altitudinal vegetation belts, the shift of forest tree lines and subalpine steppe belts to high altitudes constitutes an obvious response to global climate change. However, whether or not similar changes occur in steppe belts (low altitude) and nival belts in different areas within mountain systems remain undetermined. It is also unknown if these, responses to climate change are consistent. Here, using Landsat remote sensing images from 1989 to 2015, we obtained the spatial distribution of altitudinal vegetation belts in different periods of the Tianshan Mountains in Northwestern China. We suggest that the responses from different altitudinal vegetation belts to global climate change are different. The changes in the vegetation belts at low altitudes are spatially different. In high-altitude regions (higher than the forest belts), however, the trend of different altitudinal belts is consistent. Specifically, we focused on analyses of the impact of changes in temperature and precipitation on the nival belts, desert steppe belts, and montane steppe belts. The results demonstrated that the temperature in the study area exhibited an increasing trend, and is the main factor of altitudinal vegetation belts change in the Tianshan Mountains. In the context of a significant increase in temperature, the upper limit of the montane steppe in the eastern and central parts will shift to lower altitudes, which may limit the development of local animal husbandry. The montane steppe in the west, however, exhibits the opposite trend, which may augment the carrying capacity of pastures and promote the development of local animal husbandry. The lower limit of the nival belt will further increase in all studied areas, which may lead to an increase in surface runoff in the central and western regions.

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Soil nitrogen cycling in forests may be accelerated or inhibited by global warming, with consequences on forest productivity. Such an impact will be more complicated with extending period of warming. We examined the effects of warming on soil inorganic nitrogen content in the young and mature Cunninghamia lanceolata plantations. Warming was simulated by means of soil cable warming, simulating a future climate change scenario of 4 ℃ warming. The results showed that after three years warming, both total soil inorganic nitrogen and ammonium contents in the young and mature plantations were significantly reduced. The sharp decline occurred in the young plantation, with soil ammonium content in 0-10, 10-20, 20-40, 40-60 cm soil layers decreased by 32.1%, 37.1%, 20.8% and 19.9%, respectively. Dissolved organic nitrogen was reduced and N2O emission was accelerated in the both plantations. The main reasons for the reduction of soil inorganic nitrogen concentration were lower input of organic nitrogen substrate and higher gaseous nitrogen loss. The decrease in soil organic nitrogen substrate and increase in gaseous nitrogen emissions in the young plantation were larger than those in the mature plantation, indicating that soils in the young plantation were more sensitive to increasing temperature. The 3-year warming decreased soil inorganic nitrogen contents in the two C. lanceolata plantations, which might negatively affect productivity of the C. lanceolata plantations in subtropic China.

Serum metabolomics reveals the intervention mechanism and compatible regularity of Chaihu Shu Gan San on chronic unpredictable mild stress-induced depression rat model.

OBJECTIVES: To provide a comprehensive study of the intervention mechanism and compatible regularity of Chaihu Shu Gan San (CSGS) in a chronic unpredictable mild stress (CUMS)-induced depression model. METHODS: Ethological study and ELISA assay were applied to measure the phenotypes of depression after CUMS stimulate and assess the antidepressant activity of fluoxetine, CSGS and its compatibilities. The serum metabolic profile changes were revealed by untargeted Q/TOF MS-based metabolomics followed by multivariate statistical analysis. KEY FINDINGS: CSGS exhibits an significant intervention effect on CUMS-induced depression. After the multivariate statistical analysis, 17 potential serum biomarkers were identified and 16 of them could be regulated by CSGS. The intervention of CSGS on CUMS-induced depression involved five key pathways. Moreover, each functional unit (monarch, minister, assistant and guide medicine) in CSGS regulates different metabolites and metabolic pathways to achieve different effects on antidepressant; however, their intervention efficacies are inferior to the holistic formula, which may be due to the synergism of bioactive ingredients in the seven herbs of CSGS. CONCLUSIONS: CSGS produced an obvious antidepressant activity. The comprehensive and holistic metabolomics approach could be a powerful tool to study the intervention mechanism and the compatibility rule of traditional Chinese medicine.

Heterogeneous recurrence analysis of spatial data.

Nonlinear dynamical systems often generate significant amounts of observational data such as time series, as well as high-dimensional spatial data. To delineate recurrence dynamics in the spatial data, prior efforts either extended the recurrence plot, which is a widely used tool for time series, to a four-dimensional hyperspace or utilized the network approach for recurrence analysis. However, very little has been done to differentiate heterogeneous types of recurrences in the spatial data (e.g., recurrence variations of state transitions in the spatial domain). Therefore, we propose a novel heterogeneous recurrence approach for spatial data analysis. First, spatial data are traversed with the Hilbert Space-Filling Curve to transform the variations of recurrence patterns from the spatial domain to the state-space domain. Second, we design an Iterated Function System to derive the fractal representation for the state-space trajectory of spatial data. Such a fractal representation effectively captures self-similar behaviors of recurrence variations and multi-state transitions in the spatial data. Third, we develop the Heterogeneous Recurrence Quantification Analysis of spatial data. Experimental results in both simulation and real-world case studies show that the proposed approach yields superior performance in the extraction of salient features to characterize and quantify heterogeneous recurrence dynamics in spatial data.

Semi-Supervised Learning Algorithm for Identifying High-Priority Drug-Drug Interactions Through Adverse Event Reports.

Identifying drug-drug interactions (DDIs) is a critical enabler for reducing adverse drug events and improving patient safety. Generating proper DDI alerts during prescribing workflow has the potential to prevent DDI-related adverse events. However, the implementation of DDI alerting system remains a challenge as users are experiencing alert overload which causes alert fatigue. One strategy to optimize the current system is to establish a list of high-priority DDIs for alerting purposes, though it is a resource-intensive task. In this study, we propose a machine learning framework to extract useful features from the FDA adverse event reports and then identify potential high-priority DDIs using an autoencoder-based semi-supervised learning algorithm. The experimental results demonstrate the effectiveness of using adverse event feature representations in differentiating high- and low-priority DDIs. Additionally, the proposed algorithm utilizes stacked autoencoders and weighted support vector machine for boosting classification performance, which outperforms other competing methods in terms of F-measure and AUC score. This framework integrates multiple information sources, leverages domain knowledge and clinical evidence, and provides a practical approach for pre-screening high-priority DDI candidates for medication alerts.