Random forest differentiation of Escherichia coli in elderly sepsis using biomarkers and infectious sites.

This study addresses the challenge of accurately diagnosing sepsis subtypes in elderly patients, particularly distinguishing between Escherichia coli (E. coli) and non-E. coli infections. Utilizing machine learning, we conducted a retrospective analysis of 119 elderly sepsis patients, employing a random forest model to evaluate clinical biomarkers and infection sites. The model demonstrated high diagnostic accuracy, with an overall accuracy of 87.5%, and impressive precision and recall rates of 93.3% and 87.5%, respectively. It identified infection sites, platelet distribution width, reduced platelet count, and procalcitonin levels as key predictors. The model achieved an F1 Score of 90.3% and an area under the receiver operating characteristic curve of 88.0%, effectively differentiating between sepsis subtypes. Similarly, logistic regression and least absolute shrinkage and selection operator analysis underscored the significance of infectious sites. This methodology shows promise for enhancing elderly sepsis diagnosis and contributing to the advancement of precision medicine in the field of infectious diseases.

Mechanisms of mTORC1 activation by RHEB and inhibition by PRAS40.

The mechanistic target of rapamycin complex 1 (mTORC1) controls cell growth and metabolism in response to nutrients, energy levels, and growth factors. It contains the atypical kinase mTOR and the RAPTOR subunit that binds to the Tor signalling sequence (TOS) motif of substrates and regulators. mTORC1 is activated by the small GTPase RHEB (Ras homologue enriched in brain) and inhibited by PRAS40. Here we present the 3.0 ångström cryo-electron microscopy structure of mTORC1 and the 3.4 ångström structure of activated RHEB-mTORC1. RHEB binds to mTOR distally from the kinase active site, yet causes a global conformational change that allosterically realigns active-site residues, accelerating catalysis. Cancer-associated hyperactivating mutations map to structural elements that maintain the inactive state, and we provide biochemical evidence that they mimic RHEB relieving auto-inhibition. We also present crystal structures of RAPTOR-TOS motif complexes that define the determinants of TOS recognition, of an mTOR FKBP12-rapamycin-binding (FRB) domain-substrate complex that establishes a second substrate-recruitment mechanism, and of a truncated mTOR-PRAS40 complex that reveals PRAS40 inhibits both substrate-recruitment sites. These findings help explain how mTORC1 selects its substrates, how its kinase activity is controlled, and how it is activated by cancer-associated mutations.

Evaluation of the diagnostic value of alpha-l-fucosidase, alpha-fetoprotein and thymidine kinase 1 with ROC and logistic regression for hepatocellular carcinoma.

The purpose of this study was to evaluate the diagnostic efficiency for hepatocellular carcinoma (HCC) with the combined analysis of alpha-l-fucosidase (AFU), alpha-fetoprotein (AFP) and thymidine kinase 1 (TK1). Serum levels of AFU, AFP and TK1 were measured in: 116 patients with HCC, 109 patients with benign hepatic diseases, and 104 normal subjects. The diagnostic value was analyzed using the logistic regression equation and receiver operating characteristic curves (ROC). Statistical distribution of the three tested tumor markers in every group was non-normally distributed (Kolmogorov-Sminov test, Z = 0.156-0.517, P < 0.001). The serum levels of AFP and TK1 in patients with HCC were significantly higher than those in patients with benign hepatic diseases (Mann-Whitney U test, Z = -8.570 to -5.943, all P < 0.001). However, there was no statistically significant difference of AFU between these two groups (Mann-Whitney U test, Z = -1.820, P = 0.069). The levels of AFU were significantly higher in patients with benign hepatic diseases than in normal subjects (Mann-Whitney U test, Z = -7.984, P < 0.001). Receiver operating characteristic curves (ROC) in patients with HCC versus those without HCC indicated the optimal cut-off value was 40.80 U/L for AFU, 10.86 µg/L for AFP and 1.92 pmol/L for TK1, respectively. The area under ROC curve (AUC) was 0.718 for AFU, 0.832 for AFP, 0.773 for TK1 and 0.900 for the combination of the three tumor markers. The combination resulted in a higher Youden index and a sensitivity of 85.3%. The combined detection of serum AFU, AFP and TK1 could play a complementary role in the diagnosis of HCC, and could significantly improve the sensitivity for the diagnosis of HCC.

Crystal structures of Klebsiella pneumoniae pantothenate kinase in complex with N-substituted pantothenamides.

N-Substituted pantothenamides are derivatives of pantothenate, the precursor in the biosynthesis of the essential metabolic cofactor coenzyme A (CoA). These compounds are substrates of pantothenate kinase (PanK) in the first step of CoA biosynthesis and possess antimicrobial activity against various pathogenic bacteria. Here we solved the crystal structure of the Klebsiella pneumoniae PanK (KpPanK) in complex with N-pentylpantothenamide (N5-Pan) to understand the molecular basis of its antimicrobial activity. The structure reveals a polar pocket interacting with the pantothenate moiety of N5-Pan and an aromatic pocket loosely protecting the pentyl tail, suggesting that the introduction of an aromatic ring to a new pantothenamide may enhance the compound's affinity to KpPanK. To test this idea, we synthesized N-pyridin-3-ylmethylpantothenamide (Np-Pan) and solved its co-crystal structure with KpPanK. The structure reveals two alternat conformations of the aromatic ring of Np-Pan bound at the aromatic pocket, providing the basis for further improvement of pantothenamide binding to KpPanK.

Structural basis of Rnd1 binding to plexin Rho GTPase binding domains (RBDs).

Plexin receptors regulate cell adhesion, migration, and guidance. The Rho GTPase binding domain (RBD) of plexin-A1 and -B1 can bind GTPases, including Rnd1. By contrast, plexin-C1 and -D1 reportedly bind Rnd2 but associate with Rnd1 only weakly. The structural basis of this differential Rnd1 GTPase binding to plexin RBDs remains unclear. Here, we solved the structure of the plexin-A2 RBD in complex with Rnd1 and the structures of the plexin-C1 and plexin-D1 RBDs alone, also compared with the previously determined plexin-B1 RBD.Rnd1 complex structure. The plexin-A2 RBD·Rnd1 complex is a heterodimer, whereas plexin-B1 and -A2 RBDs homodimerize at high concentration in solution, consistent with a proposed model for plexin activation. Plexin-C1 and -D1 RBDs are monomeric, consistent with major residue changes in the homodimerization loop. In plexin-A2 and -B1, the RBD ß3-ß4 loop adjusts its conformation to allow Rnd1 binding, whereas minimal structural changes occur in Rnd1. The plexin-C1 and -D1 RBDs lack several key non-polar residues at the corresponding GTPase binding surface and do not significantly interact with Rnd1. Isothermal titration calorimetry measurements on plexin-C1 and -D1 mutants reveal that the introduction of non-polar residues in this loop generates affinity for Rnd1. Structure and sequence comparisons suggest a similar mode of Rnd1 binding to the RBDs, whereas mutagenesis suggests that the interface with the highly homologous Rnd2 GTPase is different in detail. Our results confirm, from a structural perspective, that Rnd1 does not play a role in the activation of plexin-C1 and -D1. Plexin functions appear to be regulated by subfamily-specific mechanisms, some of which involve different Rho family GTPases.