Development and Validation of Liquid Chromatography-Tandem Mass Spectrometry Method for Simultaneous Determination of Tramadol and Its Phase I and II Metabolites in Human Urine

Tramadol (TD) has been prescribed frequently in many countries for more than 40 years, but there is a risk of its misuse and trafficking. As a result, drug analysis has numerous legal and socially relevant implications, making it an essential part of modern analytical chemistry. Thus, the method for the detection of TD and its phase I and phase II metabolites in human urine has been developed and validated using a rapid and efficient approach combining liquid chromatography-tandem mass spectrometry (LC-MS/MS) with electrospray ionization. The sample preparation was best performed using dispersive liquid–liquid microextraction. Analysis was performed using an HyPRITY Cl8 column, and isocratic elution with methanol: water (35:65) with 0.2% formic acid was used. TD and its metabolites were detected at 264.2 (TD/M0) with a base peak at 58.2, 250.3758 (M1), 250.3124 (M2), 236.3976 (M3), 222.5361 (M4), and 236.4475 (M5) m/z peaks. TD showed linearity between 0.1 and 160 ng/mL (R2 = 0.9981). The accuracy ranged from 95.56 to 100.21% for the three concentration levels, while the between- and within-day RSD ranged from 1.58 to 3.92%. The absolute TD recovery was 96.29, 96.91, and 94.31% for the concentrations of 5, 50, and 150 ng/mL, respectively. TD’s phase I metabolites, M1–5 along with nine phase II metabolites, such as sulfo- and glucurono-conjugated metabolites, oxidative TD derivatives, and sulfo-conjugated metabolites were also identified in the urine samples. The pharmacokinetics and metabolism data given provide information for the design of possible future research disorders, evaluating drug mechanism and neurotoxicity and for the effective application screening of TD

Developing, validating, and comparing an analytical method to simultaneously detect z-drugs in urine samples using the QuEChERS approach with both liquid chromatography and gas chromatography-tandem mass spectrometry

Detecting z-drugs, a sedative-hypnotic medication, is also misused for criminal activities. Therefore, the analysis of urine samples is crucial for clinical and forensic purposes. We conducted a study where we developed, validated, and compared an analytical method for simultaneously detecting z-drugs in urine samples. Our approach uses the QuEChERS method for sample preparation, combined with liquid chromatography (LC) and gas chromatography (GC) coupled with tandem mass spectrometry (MS/MS). We optimized the QuEChERS method to effectively extract z-drugs from urine samples while minimizing matrix effects and achieving high recovery rates. After extraction, we split the samples into two parts for analysis using LC-MS/MS and GC–MS/MS. We validated our methods, and the results showed good linearity over a broad concentration range (1–200 ng/mL) for each z-drug. The limits of detection and quantification were within clinically relevant ranges, ensuring sensitivity for detecting z-drugs in urine samples. We compared the two chromatographic techniques by analyzing a set of urine samples spiked with known concentrations of z-drugs using both LC-MS/MS and GC–MS/MS methods and then applied to the real samples. The results were statistically analyzed to assess any significant differences in accuracy and precision above 95 %, and both methods offered reliable and consistent results with the samples as well. In conclusion, our analytical method coupled with both LC-MS/MS and GC–MS/MS using the QuEChERS approach provides a comprehensive and robust solution for the simultaneous detection of z-drugs in urine samples. The choice between the two chromatographic techniques can be based on the specific z-drugs of interest and the required analytical performance. This method holds promise for applications in clinical toxicology, forensic analysis, and monitoring z-drug usage

Computational design and in vitro assay of lantadene-based novel inhibitors of NS3 protease of dengue virus

Dengue virus (DENV) infection is one of the diseases for which no drug is available for the treatment. The DENV NS2B-NS3 protease is considered to be the prime target for anti-dengue drug development because of its importance in the development of new virus subunits via DENV poly-protein breakdown. Pentacyclic triterpenoids (Lantadenes) from the weed Lantana camara L. and its semi-synthetic congeners have shown a wide array of biological activities in the last two decades. The virtual screening strategy was used on the library of 78 natural and semi-synthetic lantadenes to predict the potent antagonists for the NS2B-NS3 protease enzyme of DENV and their experimental validation by in vitro assay of lead molecules. In the in silico analysis of 78 triterpenoids, two lead molecules (−10.60 and −9.93 kcal/mol) were predicted to be inhibitors of protease (viral) when compared to its reference ligand 1,8-dihydroxy-4,5-dinitroanthraquinone (−5.377 kcal/mol). At the same time, binding affinity, pharmacokinetic, and toxicity profiling, along with molecular dynamics simulations, were studied. The in vitro viral infection inhibition assay inferred that lead molecule 62 exhibited a 60% and 45% reduction in DENV titers at 10 and 5 µM concentrations, respectively. The lead molecule 62 can further be optimized for its pharmacophore and has the potential to be developed as a drug-like molecule

New Insight of Tetraphenylethylene-based Raman Signatures for Targeted SERS Nanoprobe Construction Toward Prostate Cancer Cell Detection

We have designed and synthesized novel tetraphenylethylene (TPE) appended organic fluorogens and unfold their unique Raman fingerprinting reflected by surface-enhanced Raman scattering (SERS) upon adsorption on nanoroughened gold surface as a new insight in addition to their prevalent aggregation-induced emission (AIE) and aggregation-caused quenching (ACQ) phenomena. A series of five TPE analogues has been synthesized consisting of different electron donors such as (1) indoline with propyl (TPE-In), (2) indoline with lipoic acid (TPE-In-L), (3) indoline with Boc-protected propyl amine (TPE-In-Boc), (4) benzothaizole (TPE-B), and (5) quinaldine (TPE-Q). Interestingly, all five TPE analogues produced multiplexing Raman signal pattern, out of which TPE-In-Boc showed a significant increase in signal intensity in the fingerprint region. An efficient SERS nanoprobe has been constructed using gold nanoparticles as SERS substrate, and the TPE-In as the Raman reporter, which conjugated with a specific peptide substrate, Cys-Ser-Lys-Leu-Gln-OH, well-known for the recognition of prostate-specific antigen (PSA). The designated nanoprobe TPE-In-PSA@Au acted as SERS “ON/OFF” probe in peace with the vicinity of PSA protease, which distinctly recognizes PSA expression with a limit of detection of 0.5 ng in SERS platform. Furthermore, TPE-In-PSA@Au nanoprobe was efficiently recognized the overexpressed PSA in human LNCaP cells, which can be visualized through SERS spectral analysis and SERS mapping

Oxidative Coupling and Self-Assembly of Polyphenols for the Development of Novel Biomaterials

In recent years, the development of biomaterials from green organic sources with nontoxicity and hyposensitivity has been explored for a wide array of biotherapeutic applications. Polyphenolic compounds have unique structural features, and self-assembly by oxidative coupling allows molecular species to rearrange into complex biomaterial that can be used for multiple applications. Self-assembled polyphenolic structures, such as hollow spheres, can be designed to respond to various chemical and physical stimuli that can release therapeutic drugs smartly. The self-assembled metallic-phenol network (MPN) has been used for modulating interfacial properties and designing biomaterials, and there are several advantages and challenges associated with such biomaterials. This review comprehensively summarizes current challenges and prospects of self-assembled polyphenolic hollow spheres and MPN coatings and self-assembly for biomedical applications.</p

Multi-centre radiomics for prediction of recurrence following radical radiotherapy for head and neck cancers: Consequences of feature selection, machine learning classifiers and batch-effect harmonization

Background and purpose: Radiomics models trained with limited single institution data are often not reproducible and generalisable. We developed radiomics models that predict loco-regional recurrence within two years of radiotherapy with private and public datasets and their combinations, to simulate small and multi-institutional studies and study the responsiveness of the models to feature selection, machine learning algorithms, centre-effect harmonization and increased dataset sizes. Materials and methods: 562 patients histologically confirmed and treated for locally advanced head-and-neck cancer (LA-HNC) from two public and two private datasets; one private dataset exclusively reserved for validation. Clinical contours of primary tumours were not recontoured and were used for Pyradiomics based feature extraction. ComBat harmonization was applied, and LASSO-Logistic Regression (LR) and Support Vector Machine (SVM) models were built. 95% confidence interval (CI) of 1000 bootstrapped area-under-the-Receiver-operating-curves (AUC) provided predictive performance. Responsiveness of the models’ performance to the choice of feature selection methods, ComBat harmonization, machine learning classifier, single and pooled data was evaluated. Results: LASSO and SelectKBest selected 14 and 16 features, respectively; three were overlapping. Without ComBat, the LR and SVM models for three institutional data showed AUCs (CI) of 0.513 (0.481–0.559) and 0.632 (0.586–0.665), respectively. Performances following ComBat revealed AUCs of 0.559 (0.536–0.590) and 0.662 (0.606–0.690), respectively. Compared to single cohort AUCs (0.562–0.629), SVM models from pooled data performed significantly better at AUC = 0.680. Conclusions: Multi-institutional retrospective data accentuates the existing variabilities that affect radiomics. Carefully designed prospective, multi-institutional studies and data sharing are necessary for clinically relevant head-and-neck cancer prognostication models

Global, regional, and national burden of suicide mortality 1990 to 2016 : Systematic analysis for the Global Burden of Disease Study 2016

Objectives To use the estimates from the Global Burden of Disease Study 2016 to describe patterns of suicide mortality globally, regionally, and for 195 countries and territories by age, sex, and Socio-demographic index, and to describe temporal trends between 1990 and 2016. Design Systematic analysis. Main outcome measures Crude and age standardised rates from suicide mortality and years of life lost were compared across regions and countries, and by age, sex, and Socio-demographic index (a composite measure of fertility, income, and education). Results The total number of deaths from suicide increased by 6.7% (95% uncertainty interval 0.4% to 15.6%) globally over the 27 year study period to 817 000 (762 000 to 884 000) deaths in 2016. However, the age standardised mortality rate for suicide decreased by 32.7% (27.2% to 36.6%) worldwide between 1990 and 2016, similar to the decline in the global age standardised mortality rate of 30.6%. Suicide was the leading cause of age standardised years of life lost in the Global Burden of Disease region of high income Asia Pacific and was among the top 10 leading causes in eastern Europe, central Europe, western Europe, central Asia, Australasia, southern Latin America, and high income North America. Rates for men were higher than for women across regions, countries, and age groups, except for the 15 to 19 age group. There was variation in the female to male ratio, with higher ratios at lower levels of Socio-demographic index. Women experienced greater decreases in mortality rates (49.0%, 95% uncertainty interval 42.6% to 54.6%) than men (23.8%, 15.6% to 32.7%). Conclusions Age standardised mortality rates for suicide have greatly reduced since 1990, but suicide remains an important contributor to mortality worldwide. Suicide mortality was variable across locations, between sexes, and between age groups. Suicide prevention strategies can be targeted towards vulnerable populations if they are informed by variations in mortality rates. © Published by the BMJ Publishing Group Limited.Peer reviewe

Subnational mapping of under-5 and neonatal mortality trends in India: the Global Burden of Disease Study 2000-17

Background India has made substantial progress in improving child survival over the past few decades, but a comprehensive understanding of child mortality trends at disaggregated geographical levels is not available. We present a detailed analysis of subnational trends of child mortality to inform efforts aimed at meeting the India National Health Policy (NHP) and Sustainable Development Goal (SDG) targets for child mortality. Methods We assessed the under-5 mortality rate (U5MR) and neonatal mortality rate (NMR) from 2000 to 2017 in 5 × 5 km grids across India, and for the districts and states of India, using all accessible data from various sources including surveys with subnational geographical information. The 31 states and groups of union territories were categorised into three groups using their Socio-demographic Index (SDI) level, calculated as part of the Global Burden of Diseases, Injuries, and Risk Factors Study on the basis of per-capita income, mean education, and total fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using the coefficient of variation. We projected U5MR and NMR for the states and districts up to 2025 and 2030 on the basis of the trends from 2000 to 2017 and compared these projections with the NHP 2025 and SDG 2030 targets for U5MR (23 deaths and 25 deaths per 1000 livebirths, respectively) and NMR (16 deaths and 12 deaths per 1000 livebirths, respectively). We assessed the causes of child death and the contribution of risk factors to child deaths at the state level. Findings U5MR in India decreased from 83·1 (95% uncertainty interval [UI] 76·7–90·1) in 2000 to 42·4 (36·5–50·0) per 1000 livebirths in 2017, and NMR from 38·0 (34·2–41·6) to 23·5 (20·1–27·8) per 1000 livebirths. U5MR varied 5·7 times between the states of India and 10·5 times between the 723 districts of India in 2017, whereas NMR varied 4·5 times and 8·0 times, respectively. In the low SDI states, 275 (88%) districts had a U5MR of 40 or more per 1000 livebirths and 291 (93%) districts had an NMR of 20 or more per 1000 livebirths in 2017. The annual rate of change from 2010 to 2017 varied among the districts from a 9·02% (95% UI 6·30–11·63) reduction to no significant change for U5MR and from an 8·05% (95% UI 5·34–10·74) reduction to no significant change for NMR. Inequality between districts within the states increased from 2000 to 2017 in 23 of the 31 states for U5MR and in 24 states for NMR, with the largest increases in Odisha and Assam among the low SDI states. If the trends observed up to 2017 were to continue, India would meet the SDG 2030 U5MR target but not the SDG 2030 NMR target or either of the NHP 2025 targets. To reach the SDG 2030 targets individually, 246 (34%) districts for U5MR and 430 (59%) districts for NMR would need a higher rate of improvement than they had up to 2017. For all major causes of under-5 death in India, the death rate decreased between 2000 and 2017, with the highest decline for infectious diseases, intermediate decline for neonatal disorders, and the smallest decline for congenital birth defects, although the magnitude of decline varied widely between the states. Child and maternal malnutrition was the predominant risk factor, to which 68·2% (65·8–70·7) of under-5 deaths and 83·0% (80·6–85·0) of neonatal deaths in India could be attributed in 2017; 10·8% (9·1–12·4) of under-5 deaths could be attributed to unsafe water and sanitation and 8·8% (7·0–10·3) to air pollution. Interpretation India has made gains in child survival, but there are substantial variations between the states in the magnitude and rate of decline in mortality, and even higher variations between the districts of India. Inequality between districts within states has increased for the majority of the states. The district-level trends presented here can provide crucial guidance for targeted efforts needed in India to reduce child mortality to meet the Indian and global child survival targets. District-level mortality trends along with state-level trends in causes of under-5 and neonatal death and the risk factors in this Article provide a comprehensive reference for further planning of child mortality reduction in India