Impact of modified-release opioid use on clinical outcomes following total hip and knee arthroplasty: a propensity score-matched cohort study

Modified-release opioids are often prescribed for the management of moderate to severe acute pain following total hip and knee arthroplasty, despite recommendations against their use due to increasing concerns regarding harm. The primary objective of this multicentre study was to examine the impact of modified-release opioid use on the incidence of opioid-related adverse events compared with immediate-release opioid use, among adult inpatients following total hip or knee arthroplasty. Data for total hip and knee arthroplasty inpatients receiving an opioid analgesic for postoperative analgesia during hospitalisation were collected from electronic medical records of three tertiary metropolitan hospitals in Australia. The primary outcome was the incidence of opioid-related adverse events during hospital admission. Patients who received modified with or without immediate-release opioids were matched to those receiving immediate-release opioids only (1:1) using nearest neighbour propensity score matching with patient and clinical characteristics as covariates. This included total opioid dose received. In the matched cohorts, patients given modified-release opioids (n = 347) experienced a higher incidence of opioid-related adverse events overall, compared with those given immediate-release opioids only (20.5%, 71/347 vs. 12.7%, 44/347; difference in proportions 7.8% [95%CI 2.3–13.3%]). Modified-release opioid use was associated with an increased risk of harm when used for acute pain during hospitalisation after total hip or knee arthroplasty.     

Nanotechnology for colorectal cancer detection and treatment

Colorectal cancer (CRC) is the third most diagnosed cancer and the second leading cause of cancer-related mortality in the United States. Across the globe, people in the age group older than 50 are at a higher risk of CRC. Genetic and environmental risk factors play a significant role in the development of CRC. If detected early, CRC is preventable and treatable. Currently, available screening methods and therapies for CRC treatment reduce the incidence rate among the population, but the micrometastasis of cancer may lead to recurrence. Therefore, the challenge is to develop an alternative therapy to overcome this complication. Nanotechnology plays a vital role in cancer treatment and offers targeted chemotherapies directly and selectively to cancer cells, with enhanced therapeutic efficacy. Additionally, nanotechnology elevates the chances of patient survival in comparison to traditional chemotherapies. The potential of nanoparticles includes that they may be used simultaneously for diagnosis and treatment. These exciting properties of nanoparticles have enticed researchers worldwide to unveil their use in early CRC detection and as effective treatment. This review discusses contemporary methods of CRC screening and therapies for CRC treatment, while the primary focus is on the theranostic approach of nanotechnology in CRC treatment and its prospects. In addition, this review aims to provide knowledge on the advancement of nanotechnology in CRC and as a starting point for researchers to think about new therapeutic approaches using nanotechnology.     

Antitumor Activity of Choerospondias axillaris Fruit Extract by Regulating the Expression of SNCAIP and SNCA on MDA-MB-231 Cells

Objective: Cancer is a huge problem of disease globally. Today, the percentage of people die from cancer is more than a combination of various diseases. In females, most common types of malignancies that occur are breast and cervical. The present focus has been shifted on medicinal plants as a form of therapy and there is a constant need to identify new therapeutic agents. Choerospondias axillaris (C. axillaris), an underutilized fruit, has been used in the remedy of various diseases. In the present communication, we evaluated the molecular mechanism of C. axillaris methanol extract in regulating cell death in human breast cancer cells (MDA-MB-231). Methods: Methanol extract of C. axillaris was prepared and compounds were screened by Gas chromatography-mass spectrometry. The effect of fruit extract was determined on MDA-MB-231 cells by MTT ((3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide) assay and to analyse the molecular mechanism of human breast cancer cells after treating with fruit extract, protein profiling study was performed by two-dimensional gel electrophoresis. Results: A total 9 differentially expressed proteins were identified by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS/MS) analysis. Among 9 identified proteins, synphilin-1 protein was found to be significantly downregulated, validated by western blot and RT-qPCR analysis. Possible interacting partners of synphilin-1 (SNCAIP) were analyzed for their possible role in cancer by the in-silico method. Conclusion: Our data implicate that the presence of bioactive compound(s) in C. axillaris fruits might play an important role in inhibiting the proliferation of breast carcinoma cells and Synphilin-1 protein may play a role of apoptotic function.     

Bacterial and fungal co-infection is a major barrier in COVID-19 patients: A specific management and therapeutic strategy is required

Microbial co-infections are another primary concern in patients with coronavirus disease 2019 (COVID-19), yet it is an untouched area among researchers. Preliminary data and systematic reviews only show the type of pathogens responsible for that, but its pathophysiology is still unknown. Studies show that these microbial co-infections are hospital-acquired/nosocomial infections, and patients admitted to intensive care units with invasive mechanical ventilation are highly susceptible to it. Patients with COVID-19 had elevated inflammatory cytokines and a weakened cell-mediated immune response, with lower CD4⁺ T and CD8⁺ T cell counts, indicating vulnerability to various co-infections. Despite this, there are only a few studies that recommend the management of co-infections.     

Quantitative Assessment and Predicting the Effects of Soil Pollutants on Herbaceous Biomass Production in Reserved Forests

Proceedings of the National Academy of Sciences, India Section B: Biological Sciences - Heavy metal concentrations in surface soils of Reserved Forests (RFs) have a significant impact on...     

Diagnostic difficulty,delayed diagnosis,and increased tendencies of surgical treatment in fibromyalgia syndrome

Clinical Rheumatology - Aimed to evaluate the time elapsed between the onset of early symptoms and the diagnosis of fibromyalgia syndrome (FMS), the delays in diagnosis and frequent physician...     

Education Outcomes of Children Born Late Preterm: A Retrospective Whole-Population Cohort Study

Maternal and Child Health Journal - Early life exposures can have an impact on a child’s developmental trajectory and children born late preterm (34–36 weeks gestational age)...     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.