Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials.

AIMS/HYPOTHESIS: The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events. METHODS: Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately. Poisson mixed models, adjusted for age, sex, diabetes duration and trial identifier were fitted to assess the association of clinical variables with hypoglycaemia event counts. Tree-based gradient-boosting algorithms (XGBoost) were fitted using training data and their predictive performance in terms of area under the receiver operating characteristic curve (AUC) evaluated on test data. Baseline models including age, sex and diabetes duration were compared with models that further included a score of hypoglycaemia in the first 6 weeks from study entry, and full models that included further clinical variables. The relative predictive importance of each covariate was assessed using XGBoost's importance procedure. Prediction across the entire trial duration for each trial (mean of 34.8 weeks for type 1 diabetes and 25.3 weeks for type 2 diabetes) was assessed. RESULTS: For both type 1 and type 2 diabetes, variables associated with more frequent hypoglycaemia included female sex, white ethnicity, longer diabetes duration, treatment with human as opposed to analogue-only insulin, higher glucose variability, higher score for hypoglycaemia across the 6 week baseline period, lower BP, lower lipid levels and treatment with psychoactive drugs. Prediction of any hypoglycaemia event of any severity was greater than prediction of hypoglycaemia requiring assistance (level 3 hypoglycaemia), for which events were sparser. For prediction of level 1 or worse hypoglycaemia during the whole follow-up period, the AUC was 0.835 (95% CI 0.826, 0.844) in type 1 diabetes and 0.840 (95% CI 0.831, 0.848) in type 2 diabetes. For level 3 hypoglycaemia, the AUC was lower at 0.689 (95% CI 0.667, 0.712) for type 1 diabetes and 0.705 (95% CI 0.662, 0.748) for type 2 diabetes. Compared with the baseline models, almost all the improvement in prediction could be captured by the individual's hypoglycaemia history, glucose variability and blood glucose over a 6 week baseline period. CONCLUSIONS/INTERPRETATION: Although hypoglycaemia rates show large variation according to sociodemographic and clinical characteristics and treatment history, looking at a 6 week period of hypoglycaemia events and glucose measurements predicts future hypoglycaemia risk.

Estimating risk of consequences following hypoglycaemia exposure using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials.

AIMS/HYPOTHESIS: Whether hypoglycaemia increases the risk of other adverse outcomes in diabetes remains controversial, especially for hypoglycaemia episodes not requiring assistance from another person. An objective of the Hypoglycaemia REdefining SOLutions for better liVEs (Hypo-RESOLVE) project was to create and use a dataset of pooled clinical trials in people with type 1 or type 2 diabetes to examine the association of exposure to all hypoglycaemia episodes across the range of severity with incident event outcomes: death, CVD, neuropathy, kidney disease, retinal disorders and depression. We also examined the change in continuous outcomes that occurred following a hypoglycaemia episode: change in eGFR, HbA1c, blood glucose, blood glucose variability and weight. METHODS: Data from 84 trials with 39,373 participants were pooled. For event outcomes, time-updated Cox regression models adjusted for age, sex, diabetes duration and HbA1c were fitted to assess association between: (1) outcome and cumulative exposure to hypoglycaemia episodes; and (2) outcomes where an acute effect might be expected (i.e. death, acute CVD, retinal disorders) and any hypoglycaemia exposure within the last 10 days. Exposures to any hypoglycaemia episode and to episodes of given severity (levels 1, 2 and 3) were examined. Further adjustment was then made for a wider set of potential confounders. The within-person change in continuous outcomes was also summarised (median of 40.4 weeks for type 1 diabetes and 26 weeks for type 2 diabetes). Analyses were conducted separately by type of diabetes. RESULTS: The maximally adjusted association analysis for type 1 diabetes found that cumulative exposure to hypoglycaemia episodes of any level was associated with higher risks of neuropathy, kidney disease, retinal disorders and depression, with risk ratios ranging from 1.55 (p=0.002) to 2.81 (p=0.002). Associations of a similar direction were found when level 1 episodes were examined separately but were significant for depression only. For type 2 diabetes cumulative exposure to hypoglycaemia episodes of any level was associated with higher risks of death, acute CVD, kidney disease, retinal disorders and depression, with risk ratios ranging from 2.35 (p<0.0001) to 3.00 (p<0.0001). These associations remained significant when level 1 episodes were examined separately. There was evidence of an association between hypoglycaemia episodes of any kind in the previous 10 days and death, acute CVD and retinal disorders in both type 1 and type 2 diabetes, with rate ratios ranging from 1.32 (p=0.017) to 2.68 (p<0.0001). These associations varied in magnitude and significance when examined separately by hypoglycaemia level. Within the range of hypoglycaemia defined by levels 1, 2 and 3, we could not find any evidence of a threshold at which risk of these consequences suddenly became pronounced. CONCLUSIONS/INTERPRETATION: These data are consistent with hypoglycaemia being associated with an increased risk of adverse events across several body systems in diabetes. These associations are not confined to severe hypoglycaemia requiring assistance.

Synthesis and evaluation of 1,ω-bis(1,2,3,5-thiatriazol-5-yl)alkanes as in vitro and in vivo α-amylase and lipase inhibitors.

Thionyl chloride reacts with 1,ω-bis-(1-tosylamidrazone)alkanes 1 to give a series of 1,ω-bis-(4-alkyl-2-tosyl-1,2,3,5-thiatriazol-5-yl)alkanes 2. All the newly synthesized compounds were characterized by IR, 1H NMR, 13C NMR, elemental analysis, and ESI-MS spectral data. All the new compounds were screened for their inhibitory effect on key enzymes related to diabetes and obesity, such as α-amylase and lipase. In vitro and in vivo studies revealed that these thiatriazole derivatives exert an inhibitory action against these key enzymes. Moreover the administration of these compounds to surviving diabetic rats induced a significant decrease in plasma glucose level. Additively 2d significantly protected the liver-kidney functions and modulated lipid metabolism, which were evidenced by the decrease in aspartate transaminase (AST), alanine transaminase (ALT), and gamma-glutamyl transpeptidase (GGT) activities and creatinine, urea albumin, LDL-cholesterol and triglycerides levels as well as an increase in the HDL-cholesterol level in surviving diabetic rats. Overall, the findings of the current study indicate that 2d exhibits attractive properties and can, therefore, be considered for future application in the development of anti-diabetic and hypolipidemic drugs.

Addressing Diverse Petroleum Industry Problems Using Machine Learning Techniques: Literary Methodology-Spotlight on Predicting Well Integrity Failures.

Artificial intelligence (AI) and machine learning (ML) are transforming industries, where low-cost, big data can utilize computing power to optimize system performance. Oil and gas (O&G) fields are getting mature, where well integrity (WI) problems become more common and field operations are now more challenging. Hence, they are good candidates for transformation due to the low cost of data storage, highlighting the oil market decline, along with dynamic risk posed during operations. This paper is presenting a comprehensive compilation of different ML applications in diverse disciplines of the petroleum industry. The pool of AI and ML with respect to different areas of applications along with publication years has been categorized. The main focus of this study is classifying well integrity failures where the authors found that the potential of AI and ML in predicting well integrity failures has not been efficiently tapped, and there is an explicit gap in the literature. First, the applications of AI, ML, and data analytics in the O&G industry are discussed thoroughly, so this paper can be a comprehensive reference for readers and future researchers. Then data preprocessing is explained. This includes data gathering, cleaning, and feature engineering. Next, the different ML models are compared and discussed. Finally, model performance evaluation and best model selection are described. This study would be a concrete foundation in the design and construction of ML programs that can be deployed for WI risk management. The developed model can be simply used for any well stock, providing quick and easy assessment instead of subjective and tedious assessment. The layout can be simply adjusted to reflect the risk profile of any well type or any field.

Molecular drug-organiser: synthesis, characterization and biological evaluation of penicillin V and/or nalidixic acid calixarene-based podands.

Two well-known antibiotic heterocycles, the 'quinolone' nalidixic acid and the ß-lactam penicillin V, active at different levels of the bacterial growth process, have been attached via an ether-ester junction to the p-tert-butylcalix[4]arene lower rim, in alternate position. The resulting hydrophobic molecular drug-organisers were fully characterized, and evaluated over two Gram negative and three Gram positive reference strains, using disk diffusion assays with disks impregnated with solution of title compound in pure DMSO. An interesting activity was observed over Staphylococcus aureus ATCC 25923 with the dis-symmetrical podand incorporating one penicillin and one nalidixic ester moieties.

Towards calixarene-based prodrugs: Drug release and antibacterial behaviour of a water-soluble nalidixic acid/calix[4]arene ester adduct.

A water-soluble calixarene-based heterocyclic podand incorporating a quinolone antibiotic subunit, the nalidixic acid, was synthesised and fully characterised. Its prodrug behaviour was assessed in vitro by HPLC, demonstrating the release of the tethered quinolone in model biological conditions. Microbiological studies performed on various Gram-positive and Gram-negative reference strains showed very interesting antibacterial activities.

Calixarenes in a membrane environment: a monolayer study on the miscibility of three p-tert-butylcalix[4]arene beta-lactam derivatives with 1,2-dimyristoyl-sn-glycero-3-phosphoethanolamine.

Literature data indicate that some calixarene derivatives with antimicrobial activities may be useful as drugs; one of the aspects of the biological activity of different classes of antibiotics concerns interactions with lipid membranes. Here, the possibility of incorporation and/or translocation of three amphiphilic p-tert-butylcalix[4]arene derivatives across membranes was studied using lipid monolayers. The derivatives used have 6-aminopenicillanic acid or benzylpenicillin moieties grafted in alternate positions at the calixarene lower rim; 1,2-dimyristoyl-sn-glycero-3-phosphoethanolamine (DMPE), a model bacterial membrane lipid, was used to prepare the monolayers. The miscibility of calixarene-antibiotic conjugates with lipid films was studied using surface pressure and surface potential measurements, as well as Brewster angle microscopy. The results obtained show that the miscibility is significantly different for the 6-aminopenicillanic acid and the two benzylpenicillin derivatives. Molecular modeling allowed the assessment of the lowest energy conformations of the calixarene derivatives and gave more insight into the interactions with the DMPE films.

Interaction of a ß-lactam calixarene derivative with a model eukaryotic membrane affects the activity of PLA2.

In this research, the interaction between a membrane phospholipid, 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC), and a p-tert-butylcalix[4]arene derivative bearing 6-aminopenicillanic acid (Calix), conceived as a possible drug carrier, was studied. The Langmuir film balance technique was used to measure surface pressure and electrical surface potential of pure and mixed Calix/DLPC monolayers spread on water at different temperatures. Phospholipase A2 (PLA2) activity was used as well to detect the impact of the calixarene derivative on the monolayer properties. Interaction between the molecules in mixed monolayers has been described quantitatively using thermodynamic functions. Interestingly, low amounts of Calix introduce ordering in the lipid film. This effect may be analogous to that of cholesterol interacting with phospholipids. A lower activity of PLA2 observed with the Calix/DLPC films compared to pure DLPC may be related to structural modifications of the mixed systems.

The mechanism of metal cation binding in two nalidixate calixarene conjugates. A langmuir film and molecular modeling study.

The two new p-tert-butylcalix[4]arene derivatives described here bear one or two nalidixic acid arms linked to the lower calixarene rim via the quinolone carboxylate moiety. These derivatives were synthesized in order to investigate two important features of molecules conceived as potential antibiotics, namely, metal cation complexation and interfacial properties, and the way in which they interrelate. The properties of the calixarene derivatives were studied in monomolecular films spread on pure water and on aqueous subphases containing biologically relevant mono- and divalent metal cations. These systems were examined via surface pressure and surface electrical potential measurements, polarization modulation infrared reflection absorption spectroscopy, and molecular modeling. Molecular modeling shows that important differences exist, first, between the structure and stability of the complexes formed with the two derivatives and, second, between their mono- and dication complexes. Correlating the properties of the monolayers with those of the modeled molecules lets us propose that the derivatives bearing one or two nalidixic pending arms form preferentially inter- and intramolecular complexes, respectively. The results obtained in this study indicate that a possible biological role of the nalidixic arms grafted on the calixarene crown may be revealed upon cation complexation.