Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing.

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.

Repurposing Drugs for the Treatment of COVID-19 and Its Cardiovascular Manifestations.

COVID-19 is an infectious disease caused by SARS-CoV-2 leading to the ongoing global pandemic. Infected patients developed a range of respiratory symptoms, including respiratory failure, as well as other extrapulmonary complications. Multiple comorbidities, including hypertension, diabetes, cardiovascular diseases, and chronic kidney diseases, are associated with the severity and increased mortality of COVID-19. SARS-CoV-2 infection also causes a range of cardiovascular complications, including myocarditis, myocardial injury, heart failure, arrhythmias, acute coronary syndrome, and venous thromboembolism. Although a variety of methods have been developed and many clinical trials have been launched for drug repositioning for COVID-19, treatments that consider cardiovascular manifestations and cardiovascular disease comorbidities specifically are limited. In this review, we summarize recent advances in drug repositioning for COVID-19, including experimental drug repositioning, high-throughput drug screening, omics data-based, and network medicine-based computational drug repositioning, with particular attention on those drug treatments that consider cardiovascular manifestations of COVID-19. We discuss prospective opportunities and potential methods for repurposing drugs to treat cardiovascular complications of COVID-19.

hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy.

There is a lack of robust generalizable predictive biomarkers of response to immune checkpoint blockade in multiple types of cancer. We develop hDirect-MAP, an algorithm that maps T cells into a shared high-dimensional (HD) expression space of diverse T cell functional signatures in which cells group by the common T cell phenotypes rather than dimensional reduced features or a distorted view of these features. Using projection-free single-cell modeling, hDirect-MAP first removed a large group of cells that did not contribute to response and then clearly distinguished T cells into response-specific subpopulations that were defined by critical T cell functional markers of strong differential expression patterns. We found that these grouped cells cannot be distinguished by dimensional-reduction algorithms but are blended by diluted expression patterns. Moreover, these identified response-specific T cell subpopulations enabled a generalizable prediction by their HD metrics. Tested using five single-cell RNA-seq or mass cytometry datasets from basal cell carcinoma, squamous cell carcinoma and melanoma, hDirect-MAP demonstrated common response-specific T cell phenotypes that defined a generalizable and accurate predictive biomarker.

Broadcasters, receivers, functional groups of metabolites, and the link to heart failure by revealing metabolomic network connectivity.

BACKGROUND AND OBJECTIVE: Blood-based small molecule metabolites offer easy accessibility and hold significant potential for insights into health processes, the impact of lifestyle, and genetic variation on disease, enabling precise risk prevention. In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. METHODS: We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. RESULTS: We identified metabolites associated with higher and lower risk of HF incidence, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. These associations were not confounded by the other metabolites due to uncovering the connectivity among metabolites and adjusting each association for the confounding metabolites. Examples of our findings include the direct influence of asparagine on glycine, both of which were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids, which are not synthesized in the human body and are obtained directly from the diet. CONCLUSION: Metabolites may play a critical role in linking genetic background and lifestyle factors to HF incidence. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates studying complex conditions like HF.

Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases.

Cardiovascular diseases (CVD) are the leading cause of death worldwide and display complex phenotypic heterogeneity caused by many convergent processes, including interactions between genetic variation and environmental factors. Despite the identification of a large number of associated genes and genetic loci, the precise mechanisms by which these genes systematically influence the phenotypic heterogeneity of CVD are not well understood. In addition to DNA sequence, understanding the molecular mechanisms of CVD requires data from other omics levels, including the epigenome, the transcriptome, the proteome, as well as the metabolome. Recent advances in multiomics technologies have opened new precision medicine opportunities beyond genomics that can guide precise diagnosis and personalized treatment. At the same time, network medicine has emerged as an interdisciplinary field that integrates systems biology and network science to focus on the interactions among biological components in health and disease, providing an unbiased framework through which to integrate systematically these multiomics data. In this review, we briefly present such multiomics technologies, including bulk omics and single-cell omics technologies, and discuss how they can contribute to precision medicine. We then highlight network medicine-based integration of multiomics data for precision medicine and therapeutics in CVD. We also include a discussion of current challenges, potential limitations, and future directions in the study of CVD using multiomics network medicine approaches.

Elevated Pulmonary Arterial Compliance Is Associated with Survival in Pulmonary Hypertension: Results from a Novel Network Medicine Analysis.

Rationale: Predictors of adverse outcome in pulmonary hypertension (PH) are well established; however, data that inform survival are lacking. Objectives: We aim to identify clinical markers and therapeutic targets that inform the survival in PH. Methods: We included data from patients with elevated mean pulmonary artery pressure (mPAP) diagnosed by right heart catheterization in the U.S. Veterans Affairs system (October 1, 2006-September 30, 2018). Network medicine framework was used to subgroup patients when considering an N of 79 variables per patient. The results informed outcome analyses in the discovery cohort and a sex-balanced validation right heart catheterization cohort from Vanderbilt University (September 24, 1998-December 20, 2013). Measurements and Main Results: From an N of 4,737 complete case patients with mPAP of 19-24 mm Hg, there were 21 distinct subgroups (network modules) (all-cause mortality range = 15.9-61.2% per module). Pulmonary arterial compliance (PAC) drove patient assignment to modules characterized by increased survival. When modeled continuously in patients with mPAP ⩾19 mm Hg (N = 37,744; age, 67.2 yr [range = 61.7-73.8 yr]; 96.7% male; median follow-up time, 1,236 d [range = 570-1,971 d]), the adjusted all-cause mortality hazard ratio was <1.0 beginning at PAC ⩾3.0 ml/mm Hg and decreased progressively to ∼7 ml/mm Hg. A protective association between PAC ⩾3.0 ml/mm Hg and mortality was also observed in the validation cohort (N = 1,514; age, 60.2 yr [range = 49.2-69.1 yr]; 48.0% male; median follow-up time, 2,485 d [range = 671-3,580 d]). The association was strongest in patients with precapillary PH at the time of catheterization, in whom 41% (95% confidence interval, 0.55-0.62; P < 0.001) and 49% (95% confidence interval, 0.38-0.69; P < 0.001) improvements in survival were observed for PAC ⩾3.0 versus <3.0 ml/mm Hg in the discovery and validation cohorts, respectively. Conclusions: These data identify elevated PAC as an important parameter associated with survival in PH. Prospective studies are warranted that consider PAC ⩾3.0 ml/mm Hg as a therapeutic target to achieve through proven interventions.

Characterization of near-field temporal and spatial variations of pesticide residues using honeybee specimens as bio-sensing matrices.

This study was prompted by recent reports of the ubiquity of neonicotinoids (neonics) in environment and the likelihood of exposures and health hazards to non-target organisms. We aimed to quantify neonics levels in time- and location-match pollen and nectar samples foraged by honeybees (Apis mellifera) and characterized the temporal and spatial variations using a relative potency factor method to determine the total neonic levels, expressed as the imidacloprid-adjusted total neonics, IMIRPF (ng/g). Six pairs of pollen and nectar samples, a total of twelve samples, were collected from each of the thirty-two experimental hives during the active foraging months of March, April, and June and analyzed for eight neonics. We found 59% and 64% of pollen and nectar contained at least one neonic, respectively. Among those neonic-detected pollen and nectar samples, 45% and 77% of them contained more than one neonic, respectively. Imidacloprid and acetamiprid in pollen and clothianidin and thiamethoxam in nectar accounted for 60% and 83% detection, respectively. The highest 3-month average of IMIRPF in pollen (6.56 ng/g) and nectar (11.19 ng/g) were detected in a location with the predominant production of citrus fruit. The temporal and spatial variations of IMIRPF levels demonstrated the robustness of using paired pollen and nectar data as the bio-sensing matrices to facilitate the assessment of near-field exposure to total neonics and the delineation of risks.

[Difference of lipid-lowering efficacy of "Xinjianqu" before and after fermentation and its mechanism based on LKB1-AMPK pathway and 16S rDNA sequencing technology].

On the basis of establishing the prescription of Xinjianqu and clarifying the increase of the lipid-lowering active ingredients of Xinjianqu by fermentation, this paper further compared the differences in the lipid-lowering effects of Xinjianqu before and after fermentation, and studied the mechanism of Xinjianqu in the treatment of hyperlipidemia. Seventy SD rats were randomly divided into seven groups, including normal group, model group, positive drug simvastatin group(0.02 g·kg~(-1)), and low-dose and high-dose Xinjianqu groups before and after fermentation(1.6 g·kg~(-1) and 8 g·kg~(-1)), with ten rats in each group. Rats in each group were given high-fat diet continuously for six weeks to establish the model of hyperlipidemia(HLP). After successful modeling, the rats were given high-fat diet and gavaged by the corresponding drugs for six weeks, once a day, to compare the effects of Xinjianqu on the body mass, liver coefficient, and small intestine propulsion rate of rats with HLP before and after fermentation. The effects of Xinjianqu before and after fermentation on total cholesterol(TC), triacylglyceride(TG), high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-C), alanine aminotransferase(ALT), aspartate aminotransferase(AST), blood urea nitrogen(BUN), creatinine(Cr), motilin(MTL), gastrin(GAS), and the Na~+-K~+-ATPase levels were determined by enzyme-linked immunosorbent assay(ELISA). The effects of Xinjianqu on liver morphology of rats with HLP were investigated by hematoxylin-eosin(HE) staining and oil red O fat staining. The effects of Xinjianqu on the protein expression of adenosine 5'-monophosphate(AMP)-activated protein kinase(AMPK), phosphorylated AMPK(p-AMPK), liver kinase B1(LKB1), and 3-hydroxy-3-methylglutarate monoacyl coenzyme A reductase(HMGCR) in liver tissues were investigated by immunohistochemistry. The effects of Xinjianqu on the regulation of intestinal flora structure of rats with HLP were studied based on 16S rDNA high-throughput sequencing technology. The results showed that compared with those in the normal group, rats in the model group had significantly higher body mass and liver coefficient(P<0.01), significantly lower small intestine propulsion rate(P<0.01), significantly higher serum levels of TC, TG, LDL-C, ALT, AST, BUN, Cr, and AQP2(P<0.01), and significantly lower serum levels of HDL-C, MTL, GAS, Na~+-K~+-ATP levels(P<0.01). The protein expression of AMPK, p-AMPK, and LKB1 in the livers of rats in the model group was significantly decreased(P<0.01), and that of HMGCR was significantly increased(P<0.01). In addition, the observed＿otus, Shannon, and Chao1 indices were significantly decreased(P<0.05 or P<0.01) in rat fecal flora in the model group. Besides, in the model group, the relative abundance of Firmicutes was reduced, while that of Verrucomicrobia and Proteobacteria was increased, and the relative abundance of beneficial genera such as Ligilactobacillus and Lachnospiraceae＿NK4A136＿group was reduced. Compared with the model group, all Xinjianqu groups regulated the body mass, liver coefficient, and small intestine index of rats with HLP(P<0.05 or P<0.01), reduced the serum levels of TC, TG, LDL-C, ALT, AST, BUN, Cr, and AQP2, increased the serum levels of HDL-C, MTL, GAS, and Na~+-K~+-ATP, improved the liver morphology, and increased the protein expression gray value of AMPK, p-AMPK, and LKB1 in the liver of rats with HLP and decreased that of LKB1. Xinjianqu groups could regulate the intestinal flora structure of rats with HLP, increased observed＿otus, Shannon, Chao1 indices, and increased the relative abundance of Firmicutes, Ligilactobacillus(genus), Lachnospiraceae＿NK4A136＿group(genus). Besides, the high-dose Xinjianqu-fermented group had significant effects on body mass, liver coefficient, small intestine propulsion rate, and serum index levels of rats with HLP(P<0.01), and the effects were better than those of Xinjianqu groups before fermentation. The above results show that Xinjianqu can improve the blood lipid level, liver and kidney function, and gastrointestinal motility of rats with HLP, and the improvement effect of Xinjianqu on hyperlipidemia is significantly enhanced by fermentation. The mechanism may be related to AMPK, p-AMPK, LKB1, and HMGCR protein in the LKB1-AMPK pathway and the regulation of intestinal flora structure.

Interferon-γ Impairs Human Coronary Artery Endothelial Glucose Metabolism by Tryptophan Catabolism and Activates Fatty Acid Oxidation.

BACKGROUND: Endothelial cells depend on glycolysis for much of their energy production. Impaired endothelial glycolysis has been associated with various vascular pathobiologies, including impaired angiogenesis and atherogenesis. IFN-γ (interferon-γ)-producing CD4+ and CD8+ T lymphocytes have been identified as the predominant pathological cell subsets in human atherosclerotic plaques. Although the immunologic consequences of these cells have been extensively evaluated, their IFN-γ-mediated metabolic effects on endothelial cells remain unknown. The purpose of this study was to determine the metabolic consequences of the T-lymphocyte cytokine, IFN-γ, on human coronary artery endothelial cells. METHODS: The metabolic effects of IFN-γ on primary human coronary artery endothelial cells were assessed by unbiased transcriptomic and metabolomic analyses combined with real-time extracellular flux analyses and molecular mechanistic studies. Cellular phenotypic correlations were made by measuring altered endothelial intracellular cGMP content, wound-healing capacity, and adhesion molecule expression. RESULTS: IFN-γ exposure inhibited basal glycolysis of quiescent primary human coronary artery endothelial cells by 20% through the global transcriptional suppression of glycolytic enzymes resulting from decreased basal HIF1α (hypoxia-inducible factor 1α) nuclear availability in normoxia. The decrease in HIF1α activity was a consequence of IFN-γ-induced tryptophan catabolism resulting in ARNT (aryl hydrocarbon receptor nuclear translocator)/HIF1ß sequestration by the kynurenine-activated AHR (aryl hydrocarbon receptor). In addition, IFN-γ resulted in a 23% depletion of intracellular nicotinamide adenine dinucleotide in human coronary artery endothelial cells. This altered glucose metabolism was met with concomitant activation of fatty acid oxidation, which augmented its contribution to intracellular ATP balance by >20%. These metabolic derangements were associated with adverse endothelial phenotypic changes, including decreased basal intracellular cGMP, impaired endothelial migration, and a switch to a proinflammatory state. CONCLUSIONS: IFN-γ impairs endothelial glucose metabolism by altered tryptophan catabolism destabilizing HIF1, depletes nicotinamide adenine dinucleotide, and results in a metabolic shift toward increased fatty acid oxidation. This work suggests a novel mechanistic basis for pathological T lymphocyte-endothelial interactions in atherosclerosis mediated by IFN-γ, linking endothelial glucose, tryptophan, and fatty acid metabolism with the nicotinamide adenine dinucleotide balance and ATP generation and their adverse endothelial functional consequences.

2-mercaptobenzothiazole generates γ-H2AX via CYP2E1-dependent production of reactive oxygen species in urothelial cells.

Ortho (o)-toluidine is a widely known carcinogenic substance associated with cancers of the human bladder. A study on British chemical factory workers exposed to 2-mercaptobenzothiazole, phenyl-ß-naphthylamine, aniline, and o-toluidine demonstrated the crucial roles of o-toluidine, 2-mercaptobenzothiazole, and phenyl-ß-naphthylamine in the development of bladder cancer. As genotoxic events are crucial steps in the initiation of cancer, in the present study, we aimed to examine the genotoxic potential of the four chemicals using phosphorylated histone H2AX (γ-H2AX), which is a sensitive and reliable marker of DNA damage, in cultured human urothelial cells. Of the four chemicals, 2-mercaptobenzothiazole was a particularly potent DNA-damaging agent. Moreover, mechanistic studies revealed that γ-H2AX generation by 2-mercaptobenzothiazole was mainly associated with the generation of reactive oxygen species via cytochrome P450 2E1-mediated metabolism. The findings of this study may provide information that is important for the assessment of risks associated with chemicals as well as the interpretation of epidemiological studies investigating occupational bladder cancer.

NEDD9 Is a Novel and Modifiable Mediator of Platelet-Endothelial Adhesion in the Pulmonary Circulation.

Rationale: Data on the molecular mechanisms that regulate platelet-pulmonary endothelial adhesion under conditions of hypoxia are lacking, but may have important therapeutic implications. Objectives: To identify a hypoxia-sensitive, modifiable mediator of platelet-pulmonary artery endothelial cell adhesion and thrombotic remodeling. Methods: Network medicine was used to profile protein-protein interactions in hypoxia-treated human pulmonary artery endothelial cells. Data from liquid chromatography-mass spectrometry and microscale thermophoresis informed the development of a novel antibody (Ab) to inhibit platelet-endothelial adhesion, which was tested in cells from patients with chronic thromboembolic pulmonary hypertension (CTEPH) and three animal models in vivo. Measurements and Main Results: The protein NEDD9 was identified in the hypoxia thrombosome network in silico. Compared with normoxia, hypoxia (0.2% O2) for 24 hours increased HIF-1α (hypoxia-inducible factor-1α)-dependent NEDD9 upregulation in vitro. Increased NEDD9 was localized to the plasma-membrane surface of cells from control donors and patients with CTEPH. In endarterectomy specimens, NEDD9 colocalized with the platelet surface adhesion molecule P-selectin. Our custom-made anti-NEDD9 Ab targeted the NEDD9-P-selectin interaction and inhibited the adhesion of activated platelets to pulmonary artery endothelial cells from control donors in vitro and from patients with CTEPH ex vivo. Compared with control mice, platelet-pulmonary endothelial aggregates and pulmonary hypertension induced by ADP were decreased in NEDD9-/- mice or wild-type mice treated with the anti-NEDD9 Ab, which also decreased chronic pulmonary thromboembolic remodeling in vivo. Conclusions: The NEDD9-P-selectin protein-protein interaction is a modifiable target with which to inhibit platelet-pulmonary endothelial adhesion and thromboembolic vascular remodeling, with potential therapeutic implications for patients with disorders of increased hypoxia signaling pathways, including CTEPH.

Analysis of Chemical Constituents of Traditional Chinese Medicine Jianqu before and after Fermentation Based on LC-MS/MS.

OBJECTIVE: To detect the chemical constituents in Jianqu samples under different fermentated states by using UPLC-QTOF-MS/MS technology, to conduct preliminary analyses, and to establish an HPLC method for the simultaneous determination of hesperidin and naringenin in Jianqu, and the variation of the two components during fermentation were compared. METHODS: Waters ACQUITYTM UPLC HSST3 column (2.1 mm × 100 mm, 1.8 µm) was used; the mobile phase was 0.1% formic acid aqueous solution (A)-0.1% formic acid acetonitrile (B); The flow rate was 0.4 mL·min-1 with gradient elution; the column temperature was 45 °C; injection volume was 5 µL. The mass spectra of the samples were collected by negative ion mode under the electrospray ion source, and the data were screened and matched by UNIFI software. Hypersil gold C18 column (100 mm × 2.1 mm, 1.9 µm) was used; the mobile phase was acetonitrile (A)-0.1% acetic acid (B);; the flow rate with gradient elution was 0.3 mL·min-1; the column temperature was 30 °C; the injection volume was 2 µL. The content changes of hesperetin and naringenin in Jianqu at different fermentation time were detected. RESULTS: A total of 54 compounds were identified, including flavonoids, amino acids, organic acids, terpenoids, coumarins, lignans, and other compounds. Under the selected HPLC conditions, the linear relationship between hesperidin and naringenin was discovered (r2 = 0.9996). The content of hesperidin and naringenin changed significantly in the whole fermentation process. The highest concentration of content was observed at 36 h of fermentation and then decreased to varying degrees. CONCLUSION: This experiment can effectively identify various chemical components in Jianqu during different fermentation periods, and determine the content of the characteristic components, so as to provide a scientific basis for further study of Jianqu fermentation processing technology as well as a sound pharmacodynamic material basis.

Network determinants of cardiovascular calcification and repositioned drug treatments.

Ectopic cardiovascular calcification is a highly prevalent pathology for which there are no effective novel or repurposed pharmacotherapeutics to prevent disease progression. We created a human calcification endophenotype module (ie, the "calcificasome") by mapping vascular calcification genes (proteins) to the human vascular smooth muscle-specific protein-protein interactome (218 nodes and 632 edges, P < 10-5 ). Network proximity analysis was used to demonstrate that the calcificasome overlapped significantly with endophenotype modules governing inflammation, thrombosis, and fibrosis in the human interactome (P < 0.001). A network-based drug repurposing analysis further revealed that everolimus, temsirolimus, and pomalidomide are predicted to target the calcificasome. The efficacy of these agents in limiting calcification was confirmed experimentally by treating human coronary artery smooth muscle cells in an in vitro calcification assay. Each of the drugs affected expression or activity of their predicted target in the network, and decreased calcification significantly (P < 0.009). An integrated network analytical approach identified novel mediators of ectopic cardiovascular calcification and biologically plausible candidate drugs that could be repurposed to target calcification. This methodological framework for drug repurposing has broad applicability to other diseases.

Immunoglobulin-driven Complement Activation Regulates Proinflammatory Remodeling in Pulmonary Hypertension.

Rationale: Pulmonary hypertension (PH) is a life-threatening cardiopulmonary disorder in which inflammation and immunity have emerged as critical early pathogenic elements. Although proinflammatory processes in PH and pulmonary arterial hypertension (PAH) are the focus of extensive investigation, the initiating mechanisms remain elusive.Objectives: We tested whether activation of the complement cascade is critical in regulating proinflammatory and pro-proliferative processes in the initiation of experimental hypoxic PH and can serve as a prognostic biomarker of outcome in human PAH.Methods: We used immunostaining of lung tissues from experimental PH models and patients with PAH, analyses of genetic murine models lacking specific complement components or circulating immunoglobulins, cultured human pulmonary adventitial fibroblasts, and network medicine analysis of a biomarker risk panel from plasma of patients with PAH.Measurements and Main Results: Pulmonary perivascular-specific activation of the complement cascade was identified as a consistent critical determinant of PH and PAH in experimental animal models and humans. In experimental hypoxic PH, proinflammatory and pro-proliferative responses were dependent on complement (alternative pathway and component 5), and immunoglobulins, particularly IgG, were critical for activation of the complement cascade. We identified Csf2/GM-CSF as a primary complement-dependent inflammatory mediator. Furthermore, using network medicine analysis of a biomarker risk panel from plasma of patients with PAH, we demonstrated that complement signaling can serve as a prognostic factor for clinical outcome in PAH.Conclusions: This study establishes immunoglobulin-driven dysregulated complement activation as a critical pathobiological mechanism regulating proinflammatory and pro-proliferative processes in the initiation of experimental hypoxic PH and demonstrates complement signaling as a critical determinant of clinical outcome in PAH.

cAST: Capillary-Based Platform for Real-Time Phenotypic Antimicrobial Susceptibility Testing.

Antimicrobial resistance is recognized as one of the greatest emerging threats to public health. Antimicrobial resistant (AMR) microorganisms affect nearly 2 million people a year in the United States alone and place an estimated $20 billion burden on the healthcare system. The rise of AMR microorganisms can be attributed to a combination of overprescription of antimicrobials and a lack of accessible diagnostic methods. Delayed diagnosis is one of the primary reasons for empiric therapy, and diagnostic methods that enable rapid and accurate results are highly desirable to facilitate evidence-based treatment. This is particularly true for clinical situations at the point-of-care where access to state-of-the-art diagnostic equipment is scarce. Here, we present a capillary-based antimicrobial susceptibility testing platform (cAST), a unique approach that offers accelerated assessment of antimicrobial susceptibility in a low-cost and simple testing format. cAST delivers an expedited time-to-readout by means of optical assessment of bacteria incubated in a small capillary form factor along with a resazurin dye. cAST was designed using a combination of off-the-shelf and custom 3D-printed parts, making it extremely suitable for use in resource-limited settings. We demonstrate that growth of bacteria in cAST is approximately 25% faster than in a conventional microplate, further validate the diagnostic performance with clinical isolates, and show that cAST can deliver accurate antimicrobial susceptibility test results within 4-8 h.

Network Analysis to Risk Stratify Patients With Exercise Intolerance.

RATIONALE: Current methods assessing clinical risk because of exercise intolerance in patients with cardiopulmonary disease rely on a small subset of traditional variables. Alternative strategies incorporating the spectrum of factors underlying prognosis in at-risk patients may be useful clinically, but are lacking. OBJECTIVE: Use unbiased analyses to identify variables that correspond to clinical risk in patients with exercise intolerance. METHODS AND RESULTS: Data from 738 consecutive patients referred for invasive cardiopulmonary exercise testing at a single center (2011-2015) were analyzed retrospectively (derivation cohort). A correlation network of invasive cardiopulmonary exercise testing parameters was assembled using |r|>0.5. From an exercise network of 39 variables (ie, nodes) and 98 correlations (ie, edges) corresponding to P<9.5e-46 for each correlation, we focused on a subnetwork containing peak volume of oxygen consumption (pVo2) and 9 linked nodes. K-mean clustering based on these 10 variables identified 4 novel patient clusters characterized by significant differences in 44 of 45 exercise measurements (P<0.01). Compared with a probabilistic model, including 23 independent predictors of pVo2 and pVo2 itself, the network model was less redundant and identified clusters that were more distinct. Cluster assignment from the network model was predictive of subsequent clinical events. For example, a 4.3-fold (P<0.0001; 95% CI, 2.2-8.1) and 2.8-fold (P=0.0018; 95% CI, 1.5-5.2) increase in hazard for age- and pVo2-adjusted all-cause 3-year hospitalization, respectively, were observed between the highest versus lowest risk clusters. Using these data, we developed the first risk-stratification calculator for patients with exercise intolerance. When applying the risk calculator to patients in 2 independent invasive cardiopulmonary exercise testing cohorts (Boston and Graz, Austria), we observed a clinical risk profile that paralleled the derivation cohort. CONCLUSIONS: Network analyses were used to identify novel exercise groups and develop a point-of-care risk calculator. These data expand the range of useful clinical variables beyond pVo2 that predict hospitalization in patients with exercise intolerance.

Aldehyde dehydrogenase 2 deficiency significantly exacerbates tert-butyl alcohol-induced toxicity in mice.

Owing to the use of ethyl tert-butyl ether (ETBE) as a fuel additive, the possible adverse effects of ETBE exposure have become a public concern. Our previous study showed that ETBE-induced toxicity in aldehyde dehydrogenase 2 (Aldh2) gene knockout (KO) mice was caused by its primary metabolite acetaldehyde, which was toxic. However, it is unclear whether tert-butyl alcohol (TBA), another main metabolite of ETBE, plays a role in ETBE-induced toxicity. To investigate this relationship, we analyzed the changes of TBA concentrations in tissues after ETBE exposure, and then evaluated the toxicity after direct TBA treatment in both KO and wild-type (WT) mice. An exposure to 500 ppm ETBE via inhalation resulted in the formation of its three metabolites, TBA, 2-methyl-1,2-propanediol and ethanol, whose concentrations in the liver, brain, fat and testis of male KO mice were significantly higher than the corresponding concentrations observed in male WT mice. Direct treatment to TBA (20 mg/mL of drinking water) caused significant changes in relative organ weights and histopathology, and increased levels of genetic damages in both types of mice. These toxic effects were also seen in KO mice exposed to a lower concentration of TBA (5 mg/mL), which was associated with increased oxidative stress in serum (reduced glutathione and reduced glutathione/oxidized glutathione ratio decreased). Our findings indicate that ALDH2 is involved in the metabolism of ETBE and TBA, and ALDH2 deficiency could greatly increase the sensitivity to TBA-induced toxicity.

Rapid diagnostic testing platform for iron and vitamin A deficiency.

Micronutrient deficiencies such as those of vitamin A and iron affect a third of the world's population with consequences such as night blindness, higher child mortality, anemia, poor pregnancy outcomes, and reduced work capacity. Many efforts to prevent or treat these deficiencies are hampered by the lack of adequate, accessible, and affordable diagnostic methods that can enable better targeting of interventions. In this work, we demonstrate a rapid diagnostic test and mobile enabled platform for simultaneously quantifying iron (ferritin), vitamin A (retinol-binding protein), and inflammation (C-reactive protein) status. Our approach, enabled by combining multiple florescent markers and immunoassay approaches on a single test, allows us to provide accurate quantification in 15 min even though the physiological range of the markers of interest varies over five orders of magnitude. We report sensitivities of 88%, 100%, and 80% and specificities of 97%, 100%, and 97% for iron deficiency (ferritin <15 ng/mL or 32 pmol/L), vitamin A deficiency (retinol-binding protein <14.7 µg/mL or 0.70 µmol/L) and inflammation status (C-reactive protein >3.0 µg/mL or 120 nmol/L), respectively. This technology is suitable for point-of-care use in both resource-rich and resource-limited settings and can be read either by a standard laptop computer or through our previously developed NutriPhone technology. If implemented as either a population-level screening or clinical diagnostic tool, we believe this platform can transform nutritional status assessment and monitoring globally.

Large-scale ALS Data Semantic Classification Integrating Location-Context-Semantics Cues by Higher-Order CRF.

We designed a location-context-semantics-based conditional random field (LCS-CRF) framework for the semantic classification of airborne laser scanning (ALS) point clouds. For ALS datasets of high spatial resolution but with severe noise pollutions, more contexture and semantics cues, besides location information, can be exploited to surmount the decrease of discrimination of features for classification. This paper mainly focuses on the semantic classification of ALS data using mixed location-context-semantics cues, which are integrated into a higher-order CRF framework by modeling the probabilistic potentials. The location cues modeled by the unary potentials can provide basic information for discriminating the various classes. The pairwise potentials consider the spatial contextual information by establishing the neighboring interactions between points to favor spatial smoothing. The semantics cues are explicitly encoded in the higher-order potentials. The higher-order potential operates at the clusters level with similar geometric and radiometric properties, guaranteeing the classification accuracy based on semantic rules. To demonstrate the performance of our approach, two standard benchmark datasets were utilized. Experiments show that our method achieves superior classification results with an overall accuracy of 83.1% on the Vaihingen Dataset and an overall accuracy of 94.3% on the Graphics and Media Lab (GML) Dataset A compared with other classification algorithms in the literature.

Rapid Diagnostic Platform for Colorimetric Differential Detection of Dengue and Chikungunya Viral Infections.

In this work, we demonstrate a rapid diagnostic platform with potential to transform clinical diagnosis of acute febrile illnesses in resource-limited settings. Acute febrile illnesses such as dengue and chikungunya, which pose high burdens of disease in tropical regions, share many nonspecific symptoms and are difficult to diagnose based on clinical history alone in the absence of accessible laboratory diagnostics. Through a unique color-mixing encoding and readout strategy, our platform enabled consistent and accurate multiplexed detection of dengue and chikungunya IgM/IgG antibodies in human clinical samples within 30 min. Our multiplex assay offers several advantages over conventional rapid diagnostic tests deployed in resource-limited settings, including a low sample volume requirement and the ability to concurrently detect four analytes. Our platform is a step toward multiplexed diagnostics that will be transformative for disease management in resource-limited settings by enabling informed treatment decisions through accessible evidence-based diagnosis.