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Hypertension is a widely prevalent disease and uncontrolled hypertension predisposes affected individuals to severe adverse effects. Though the importance of controlling hypertension is clear, the multitude of therapeutic regimens and patient factors that affect the success of blood pressure control makes it difficult to predict the likelihood to predict whether a patient's blood pressure will be controlled. This project endeavors to investigate whether machine learning can accurately predict the control of a patient's hypertension within 12 months of a clinical encounter. To build the machine learning model, a retrospective review of the electronic medical records of 350,008 patients 18 years of age and older between January 1, 2015 and June 1, 2022 was performed to form model training and testing cohorts. The data included in the model included medication combinations, patient laboratory values, vital sign measurements, comorbidities, healthcare encounters, and demographic information. The mean age of the patient population was 65.6 years with 161,283 (46.1%) men and 275,001 (78.6%) white. A sliding time window of data was used to both prohibit data leakage from training sets to test sets and to maximize model performance. This sliding window resulted in using the study data to create 287 predictive models each using 2 years of training data and one week of testing data for a total study duration of five and a half years. Model performance was combined across all models. The primary outcome, prediction of blood pressure control within 12 months demonstrated an area under the curve of 0.76 (95% confidence interval; 0.75–0.76), sensitivity of 61.52% (61.0–62.03%), specificity of 75.69% (75.25–76.13%), positive predictive value of 67.75% (67.51–67.99%), and negative predictive value of 70.49% (70.32–70.66%). An AUC of 0.756 is considered to be moderately good for machine learning models. While the accuracy of this model is promising, it is impossible to state with certainty the clinical relevancy of any clinical support ML model without deploying it in a clinical setting and studying its impact on health outcomes. By also incorporating uncertainty analysis for every prediction, the authors believe that this approach offers the best-known solution to predicting hypertension control and that machine learning may be able to improve the accuracy of hypertension control predictions using patient information already available in the electronic health record. This method can serve as a foundation with further research to strengthen the model accuracy and to help determine clinical relevance. [ABSTRACT FROM AUTHOR]

Background Barrett's esophagus (BE) is a commonly undiagnosed condition that predisposes to esophageal adenocarcinoma. Routine endoscopic screening for BE is not recommended because of the burden this would impose on the health care system. The objective of this study was to determine whether a novel approach using a minimally invasive cell sampling device, the Cytosponge, coupled with immunohistochemical staining for the biomarker Trefoil Factor 3 (TFF3), could be used to identify patients who warrant endoscopy to diagnose BE. Methods and Findings A case-control study was performed across 11 UK hospitals between July 2011 and December 2013. In total, 1,110 individuals comprising 463 controls with dyspepsia and reflux symptoms and 647 BE cases swallowed a Cytosponge prior to endoscopy. The primary outcome measures were to evaluate the safety, acceptability, and accuracy of the Cytosponge-TFF3 test compared with endoscopy and biopsy. In all, 1,042 (93.9%) patients successfully swallowed the Cytosponge, and no serious adverse events were attributed to the device. The Cytosponge was rated favorably, using a visual analogue scale, compared with endoscopy (p < 0.001), and patients who were not sedated for endoscopy were more likely to rate the Cytosponge higher than endoscopy (Mann-Whitney test, p < 0.001). The overall sensitivity of the test was 79.9% (95% CI 76.4%-83.0%), increasing to 87.2% (95% CI 83.0%-90.6%) for patients with >3 cm of circumferential BE, known to confer a higher cancer risk. The sensitivity increased to 89.7% (95% CI 82.3%-94.8%) in 107 patients who swallowed the device twice during the study course. There was no loss of sensitivity in patients with dysplasia. The specificity for diagnosing BE was 92.4% (95% CI 89.5%-94.7%). The case-control design of the study means that the results are not generalizable to a primary care population. Another limitation is that the acceptability data were limited to a single measure. Conclusions The Cytosponge-TFF3 test is safe and acceptable, and has accuracy comparable to other screening tests. This test may be a simple and inexpensive approach to identify patients with reflux symptoms who warrant endoscopy to diagnose BE., Introduction It is estimated that 5% to 15% of adults in the Western world suffer from reflux symptoms [1], and this is the commonest physician diagnosis for gastrointestinal consultations, accounting [...]

The tumour-derived monoclonal IgM antibody PAT-SM6 specifically kills malignant cells by an apoptotic mechanism linked to the excessive uptake of plasma lipids. The mechanism is postulated to occur via the multi-point attachment of PAT-SM6 to the unfolded protein response regulator GRP78, located on the surface of tumour cells, coupled to the simultaneous binding of plasma low density lipoprotein (LDL). We prepared and characterised LDL and oxidized LDL using sedimentation velocity and small-angle X-ray scattering (SAXS) analysis. Enzyme-linked immunosorbent (ELISA) techniques indicated apparent dissociation constants of approximately 20 nM for the binding of LDL or oxidized LDL to PAT-SM6. ELISA experiments showed cross competition with LDL inhibiting PAT-SM6 binding to immobilised GRP78, while, in the reverse experiment, GRP78 inhibited PAT-SM6 binding to immobilized LDL. In contrast to the results of the ELISA experiments, sedimentation velocity experiments indicated relatively weak interactions between LDL and PAT-SM6, suggesting immunoabsorbance to the microtiter plate is driven by an avidity-based binding mechanism. The importance of avidity and the multipoint attachment of antigens to PAT-SM6 was further investigated using antigen-coated polystyrene beads. Absorption of GRP78 or LDL to polystyrene microspheres led to an increase in the inhibition of PAT-SM6 binding to microtiter plates coated with GRP78 or LDL, respectively. These results support the hypothesis that the biological action of PAT-SM6 in tumour cell apoptosis depends on the multivalent nature of PAT-SM6 and the ability to interact simultaneously with LDL and multiple GRP78 molecules clustered on the tumour cell surface. [ABSTRACT FROM AUTHOR]

Zfp521 is a novel antiadipogenic transcription factor that helps to determine the identity of a mesenchymal cell as bone or fat. [ABSTRACT FROM AUTHOR]

In plants, the lysine biosynthetic pathway is an attractive target for both the development of herbicides and increasing the nutritional value of crops given that lysine is a limiting amino acid in cereals. Dihydrodipicolinate synthase (DHDPS) and dihydrodipicolinate reductase (DHDPR) catalyse the first two committed steps of lysine biosynthesis. Here, we carry out for the first time a comprehensive characterisation of the structure and activity of both DHDPS and DHDPR from Arabidopsis thaliana. The A. thaliana DHDPS enzyme (At-DHDPS2) has similar activity to the bacterial form of the enzyme, but is more strongly allosterically inhibited by (S)-lysine. Structural studies of At-DHDPS2 show (S)-lysine bound at a cleft between two monomers, highlighting the allosteric site; however, unlike previous studies, binding is not accompanied by conformational changes, suggesting that binding may cause changes in protein dynamics rather than large conformation changes. DHDPR from A. thaliana (At-DHDPR2) has similar specificity for both NADH and NADPH during catalysis, and has tighter binding of substrate than has previously been reported. While all known bacterial DHDPR enzymes have a tetrameric structure, analytical ultracentrifugation, and scattering data unequivocally show that At-DHDPR2 exists as a dimer in solution. The exact arrangement of the dimeric protein is as yet unknown, but ab initio modelling of x-ray scattering data is consistent with an elongated structure in solution, which does not correspond to any of the possible dimeric pairings observed in the X-ray crystal structure of DHDPR from other organisms. This increased knowledge of the structure and function of plant lysine biosynthetic enzymes will aid future work aimed at improving primary production. [ABSTRACT FROM AUTHOR]

While there has been significant progress in determining the transcriptional cascade involved in terminal adipocyte differentiation, less is known about early events leading to lineage commitment and cell fate choice. It has been recently discovered that zinc finger protein 423 (Zfp423) is an early actor in adipose determination. Here, we show that a close paralog of Zfp423, Zfp521, acts as a key regulator of adipose commitment and differentiation in vitro and in vivo. Zfp521 exerts its actions by binding to early B cell factor 1 (Ebf1), a transcription factor required for the generation of adipocyte progenitors, and inhibiting the expression of Zfp423. Overexpression of Zfp521 in cells greatly inhibits adipogenic potential, whereas RNAi-mediated knock-down or genetic ablation of Zfp521 enhances differentiation. In addition, \(Zfp521^{−/−}\) embryos exhibit increased mass of interscapular brown adipose tissue and subcutaneous white adipocytes, a cell autonomous effect. Finally, Ebf1 participates in a negative feedback loop to repress Zfp521 as differentiation proceeds. Because Zfp521 is known to promote bone development, our results suggest that it acts as a critical switch in the commitment decision between the adipogenic and osteogenic lineages.

Given the rise in drug-resistant Streptococcus pneumoniae, there is an urgent need to discover new antimicrobials targeting this pathogen and an equally urgent need to characterize new drug targets. A promising antibiotic target is dihydrodipicolinate synthase (DHDPS), which catalyzes the rate-limiting step in lysine biosynthesis. In this study, we firstly show by gene knock out studies that S. pneumoniae (sp) lacking the DHDPS gene is unable to grow unless supplemented with lysine-rich media. We subsequently set out to characterize the structure, function and stability of the enzyme drug target. Our studies show that sp-DHDPS is folded and active with a kcat = 22 s-1, KMPYR = 2.55 ± 0.05 mM and KMASA = 0.044 ± 0.003 mM. Thermal denaturation experiments demonstrate sp-DHDPS exhibits an apparent melting temperature (TMapp) of 72 °C, which is significantly greater than Escherichia coli DHDPS (Ec-DHDPS) (TMapp = 59 °C). Sedimentation studies show that sp-DHDPS exists in a dimer-tetramer equilibrium with a KD4→2 = 1.7 nM, which is considerably tighter than its E. coli ortholog (KD4→2 = 76 nM). To further characterize the structure of the enzyme and probe its enhanced stability, we solved the high resolution (1.9 Å) crystal structure of sp-DHDPS (PDB ID 3VFL). The enzyme is tetrameric in the crystal state, consistent with biophysical measurements in solution. Although the sp-DHDPS and Ec-DHDPS active sites are almost identical, the tetramerization interface of the s. pneumoniae enzyme is significantly different in composition and has greater buried surface area (800 Å2) compared to its E. coli counterpart (500 Å2). This larger interface area is consistent with our solution studies demonstrating that sp-DHDPS is considerably more thermally and thermodynamically stable than Ec-DHDPS. Our study describe for the first time the knock-out phenotype, solution properties, stability and crystal structure of DHDPS from S. pneumoniae, a promising antimicrobial target. [ABSTRACT FROM AUTHOR]

Given the rise in drug-resistant Streptococcus pneumoniae, there is an urgent need to discover new antimicrobials targeting this pathogen and an equally urgent need to characterize new drug targets. A promising antibiotic target is dihydrodipicolinate synthase (DHDPS), which catalyzes the rate-limiting step in lysine biosynthesis. In this study, we firstly show by gene knock out studies that S. pneumoniae (sp) lacking the DHDPS gene is unable to grow unless supplemented with lysine-rich media. We subsequently set out to characterize the structure, function and stability of the enzyme drug target. Our studies show that sp-DHDPS is folded and active with a kcat = 22 s-1, KMPYR = 2.55 ± 0.05 mM and KMASA = 0.044 ± 0.003 mM. Thermal denaturation experiments demonstrate sp-DHDPS exhibits an apparent melting temperature (TMapp) of 72 °C, which is significantly greater than Escherichia coli DHDPS (Ec-DHDPS) (TMapp = 59 °C). Sedimentation studies show that sp-DHDPS exists in a dimer-tetramer equilibrium with a KD4→2 = 1.7 nM, which is considerably tighter than its E. coli ortholog (KD4→2 = 76 nM). To further characterize the structure of the enzyme and probe its enhanced stability, we solved the high resolution (1.9 Å) crystal structure of sp-DHDPS (PDB ID 3VFL). The enzyme is tetrameric in the crystal state, consistent with biophysical measurements in solution. Although the sp-DHDPS and Ec-DHDPS active sites are almost identical, the tetramerization interface of the s. pneumoniae enzyme is significantly different in composition and has greater buried surface area (800 Å2) compared to its E. coli counterpart (500 Å2). This larger interface area is consistent with our solution studies demonstrating that sp-DHDPS is considerably more thermally and thermodynamically stable than Ec-DHDPS. Our study describe for the first time the knock-out phenotype, solution properties, stability and crystal structure of DHDPS from S. pneumoniae, a promising antimicrobial target. [ABSTRACT FROM AUTHOR]

Given the rise in drug-resistant Streptococcus pneumoniae, there is an urgent need to discover new antimicrobials targeting this pathogen and an equally urgent need to characterize new drug targets. A promising antibiotic target is dihydrodipicolinate synthase (DHDPS), which catalyzes the rate-limiting step in lysine biosynthesis. In this study, we firstly show by gene knock out studies that S. pneumoniae (sp) lacking the DHDPS gene is unable to grow unless supplemented with lysine-rich media. We subsequently set out to characterize the structure, function and stability of the enzyme drug target. Our studies show that sp-DHDPS is folded and active with a k(cat) = 22 s(-1), K(M)(PYR) = 2.55 ± 0.05 mM and K(M)(ASA) = 0.044 ± 0.003 mM. Thermal denaturation experiments demonstrate sp-DHDPS exhibits an apparent melting temperature (T(M)(app)) of 72 °C, which is significantly greater than Escherichia coli DHDPS (Ec-DHDPS) (T(M)(app) = 59 °C). Sedimentation studies show that sp-DHDPS exists in a dimer-tetramer equilibrium with a K(D)(4→2) = 1.7 nM, which is considerably tighter than its E. coli ortholog (K(D)(4→2) = 76 nM). To further characterize the structure of the enzyme and probe its enhanced stability, we solved the high resolution (1.9 Å) crystal structure of sp-DHDPS (PDB ID 3VFL). The enzyme is tetrameric in the crystal state, consistent with biophysical measurements in solution. Although the sp-DHDPS and Ec-DHDPS active sites are almost identical, the tetramerization interface of the s. pneumoniae enzyme is significantly different in composition and has greater buried surface area (800 Å(2)) compared to its E. coli counterpart (500 Å(2)). This larger interface area is consistent with our solution studies demonstrating that sp-DHDPS is considerably more thermally and thermodynamically stable than Ec-DHDPS. Our study describe for the first time the knock-out phenotype, solution properties, stability and crystal structure of DHDPS from S. pneumoniae, a promising antimicrobial target.