Richard L. Kennedy

Selective serotonin reuptake inhibitors inhibit human osteoclast and osteoblast formation and function.

BACKGROUND Selective serotonin reuptake inhibitors (SSRIs) are widely used antidepressants and one of the most commonly used medications. There is growing concern that SSRIs, which sequester in bone marrow at higher concentrations than brain or blood, increase bone fragility and fracture risk. However, their mechanism of action on human osteoclasts (OC) and osteoblasts (OB) differentiation remains unclear. METHODS Expression of serotonin receptors (5-HTR), transporter (5-HTT), and tryptophan hydroxylase 1 (TPH1) was assessed in human OC (precursors and mature) and OB (nonmineralizing and mineralizing) by polymerase chain reaction. OC formation and resorption was measured in the presence of 5 SSRIs. OBs cultured with SSRIs for 28 days were assessed for alkaline phosphatase (ALP) and bone mineralization. Cell viability and apoptosis were determined by annexin V flow cytometry. RESULTS OCs and OB expressed TPH1, 5-HTT, and 5-HTR1B. The 5-HTR2A was expressed only in OB, whereas 5-HTR2B expression increased from precursor to mature OC. All SSRIs (except citalopram) dose-dependently inhibited OC formation and resorption between 1 μmol/L and 10 μmol/L; order of potency: sertraline > fluoxetine > paroxetine > fluvoxamine > citalopram. Similarly, SSRIs (except citalopram) inhibited ALP and bone mineralization by OB but only at 30 μmol/L. Apoptosis was induced by SSRIs in OC and OB in an identical pattern to inhibitory effects. Serotonin treatment had no effect on either OC or OB parameters. CONCLUSIONS These data demonstrate that SSRIs differentially inhibit bone cell function via apoptosis. This may explain the mechanisms of bone loss with chronic use and aid clinical choices.

Multifunctional and multitargeted nanoparticles for drug delivery to overcome barriers of drug resistance in human cancers

The recurrence and metastatic spread of cancer are major drawbacks in cancer treatment. Although chemotherapy is one of the most effective methods for the treatment of metastatic cancers, it is nonspecific and causes significant toxic damage. The development of drug resistance to chemotherapeutic agents through various mechanisms also limits their therapeutic potential. However, as we discuss here, the use of nanodelivery systems that are a combination of diagnostics and therapeutics (theranostics) is as relatively novel concept in the treatment of cancer. Such systems are likely to improve the therapeutic benefits of encapsulated drugs and can transit to the desired site, maintaining their pharmaceutical properties. The specific targeting of malignant cells using multifunctional nanoparticles exploits theranostics as an improved agent for delivering anticancer drugs and as a new solution for overriding drug resistance.

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Objectives Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes. Setting A regional cancer centre in Australia. Participants Disease-specific data from a purpose-built cancer registry (Evaluation of Cancer Outcomes (ECO)) from 869 patients were used to predict survival at 6, 12 and 24 months. The model was validated with data from a further 94 patients, and results compared to the assessment of five specialist oncologists. Machine-learning prediction using ECO data was compared with that using EAR and a model combining ECO and EAR data. Primary and secondary outcome measures Survival prediction accuracy in terms of the area under the receiver operating characteristic curve (AUC). Results The ECO model yielded AUCs of 0.87 (95% CI 0.848 to 0.890) at 6 months, 0.796 (95% CI 0.774 to 0.823) at 12 months and 0.764 (95% CI 0.737 to 0.789) at 24 months. Each was slightly better than the performance of the clinician panel. The model performed consistently across a range of cancers, including rare cancers. Combining ECO and EAR data yielded better prediction than the ECO-based model (AUCs ranging from 0.757 to 0.997 for 6 months, AUCs from 0.689 to 0.988 for 12 months and AUCs from 0.713 to 0.973 for 24 months). The best prediction was for genitourinary, head and neck, lung, skin, and upper gastrointestinal tumours. Conclusions Machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict clinical outcomes. Importantly, the approach described made use of digital data that is already routinely collected but underexploited by clinical health systems.

Disease burden evaluation of fall-related events in the elderly due to hypoglycemia and other diabetic complications: a clinical review

A hypoglycemia-induced fall is common in older persons with diabetes. The etiology of falls in this population is usually multifactorial, and includes microvascular and macrovascular complications and age-related comorbidities, with hypoglycemia being one of the major precipitating causes. In this review, we systematically searched the literature that was available up to March 31, 2014 from MEDLINE/PubMed, Embase, and Google Scholar using the following terms: hypoglycemia; insulin; diabetic complications; and falls in elderly. Hypoglycemia, defined as blood glucose <4.0 mmol/L (70 mg/dL) requiring external assistance, occurs in one-third of elderly diabetics on glucose-lowering therapies. It represents a major barrier to the treatment of diabetes, particularly in the elderly population. Patients who experience hypoglycemia are at a high risk for adverse outcomes, including falls leading to bone fracture, seizures, cognitive dysfunction, and prolonged hospital stays. An increase in mortality has been observed in patients who experience any one of these events. Paradoxically, rational insulin therapy, dosed according to a patient’s clinical status and the results of home blood glucose monitoring, so as to achieve and maintain recommended glycemic goals, can be an effective method for the prevention of hypoglycemia and falls in the elderly. Contingencies, such as clinician-directed hypoglycemia treatment protocols that guide the immediate treatment of hypoglycemia, help to limit both the duration and severity of the event. Older diabetic patients with or without underlying renal insufficiency or other severe illnesses represent groups that are at high risk for hypoglycemia-induced falls and, therefore, require lower insulin dosages. In this review, the risk factors of falls associated with hypoglycemia in elderly diabetics were highlighted and management plans were suggested. A target hemoglobin A1c level between 7% and 8% seems to be more appropriate for this population. In addition, the first-choice drugs should have good safety profiles and have the lowest probability of causing hypoglycemia – such as metformin (in the absence of significant renal impairment) and incretin enhancers – while other therapies that may cause more frequent hypoglycemia should be avoided.

Hydroxyoctadecadienoic acids: Oxidised derivatives of linoleic acid and their role in inflammation associated with metabolic syndrome and cancer.

Linoleic acid (LA) is a major constituent of low-density lipoproteins. An essential fatty acid, LA is a polyunsaturated fatty acid, which is oxidised by endogenous enzymes and reactive oxygen species in the circulation. Increased levels of low-density lipoproteins coupled with oxidative stress and lack of antioxidants drive the oxidative processes. This results in synthesis of a range of oxidised derivatives, which play a vital role in regulation of inflammatory processes. The derivatives of LA include, hydroxyoctadecadienoic acids, oxo-​octadecadienoic acids, epoxy octadecadecenoic acid and epoxy-keto-octadecenoic acids. In this review, we examine the role of LA derivatives and their actions on regulation of inflammation relevant to metabolic processes associated with atherogenesis and cancer. The processes affected by LA derivatives include, alteration of airway smooth muscles and vascular wall, affecting sensitivity to pain, and regulating endogenous steroid hormones associated with metabolic syndrome. LA derivatives alter cell adhesion molecules, this initial step, is pivotal in regulating inflammatory processes involving transcription factor peroxisome proliferator-activated receptor pathways, thus, leading to alteration of metabolic processes. The derivatives are known to elicit pleiotropic effects that are either beneficial or detrimental in nature hence making it difficult to determine the exact role of these derivatives in the progress of an assumed target disorder. The key may lie in understanding the role of these derivatives at various stages of development of a disorder. Novel pharmacological approaches in altering the synthesis or introduction of synthesised LA derivatives could possibly help drive processes that could regulate inflammation in a beneficial manner. Chemical Compounds: Linoleic acid (PubChem CID: 5280450), 9- hydroxyoctadecadienoic acid (PubChem CID: 5312830), 13- hydroxyoctadecadienoic acid (PubChem CID: 6443013), 9-oxo-​octadecadienoic acid (PubChem CID: 3083831), 13-oxo-​octadecadienoic acid (PubChem CID: 4163990), 9,10-epoxy-12-octadecenoate (PubChem CID: 5283018), 12,13-epoxy-9-keto-10- trans -octadecenoic acid (PubChem CID: 53394018), Pioglitazone (PubChem CID: 4829).

Predicting unplanned readmission after myocardial infarction from routinely collected administrative hospital data

OBJECTIVE Readmission rates are high following acute myocardial infarction (AMI), but risk stratification has proved difficult because known risk factors are only weakly predictive. In the present study, we applied hospital data to identify the risk of unplanned admission following AMI hospitalisations. METHODS The study included 1660 consecutive AMI admissions. Predictive models were derived from 1107 randomly selected records and tested on the remaining 553 records. The electronic medical record (EMR) model was compared with a seven-factor predictive score known as the HOSPITAL score and a model derived from Elixhauser comorbidities. All models were evaluated for the ability to identify patients at high risk of 30-day ischaemic heart disease readmission and those at risk of all-cause readmission within 12 months following the initial AMI hospitalisation. RESULTS The EMR model has higher discrimination than other models in predicting ischaemic heart disease readmissions (area under the curve (AUC) 0.78; 95% confidence interval (CI) 0.71-0.85 for 30-day readmission). The positive predictive value was significantly higher with the EMR model, which identifies cohorts that were up to threefold more likely to be readmitted. Factors associated with readmission included emergency department attendances, cardiac diagnoses and procedures, renal impairment and electrolyte disturbances. The EMR model also performed better than other models (AUC 0.72; 95% CI 0.66-0.78), and with greater positive predictive value, in identifying 12-month risk of all-cause readmission. CONCLUSIONS Routine hospital data can help identify patients at high risk of readmission following AMI. This could lead to decreased readmission rates by identifying patients suitable for targeted clinical interventions.

Targeted multimodal liposomes for nano-delivery and imaging: An avenger for drug resistance and cancer

Understanding the cellular target structure and thereby proposing the best delivery system to achieve sustained release of drugs has always been a significant area of focus in biomedical research for translational benefits. Specific targeting of the receptors expressed on the target cell represents an effective strategy for increasing the pharmacological efficacy of the administered drug. Liposomes offer enhanced conveyance as a potential carrier of biomacromolecules such as anti-cancer proteins, drugs and siRNA for targeting tumour cell death. Commonly used liposomal constructs for various therapies are Doxil, Myocet, DepoCyt and Abraxanes. However, recent strategy of using multifunctional liposomes for the sustained release of drugs with increased plasma residence time and monoclonal antibody-based targeting of tumours coupled with imaging modalities have attracted enormous scientific attention. The ability of liposomes coated with specific ligands such as Apo-E derived RGD R9 and Tat peptide, to reverse the conceptualisation of drug resistance and cross the blood brain barrier, provides promising future for their use as an efficient drug delivery system. By outlining the recent advancements and innovations in the established concept of liposomal drug delivery, this review will focus on the multifunctional liposomes as an emerging novel lipid based drug delivery system.

The vitamin K-dependent Gla proteins and risk of type 2 diabetes.

[Extract] Recently Haase et al [1] reported that maternal low-protein diet in rats was associated with decreased beta cell mass and decreased expression of growth arrest specific protein 6 (GAS6) in islets of Langerhans, and that incubation of neonatal islets with GAS6 enhanced beta cell proliferation. Low beta cell mass early in life is associated with increased future risk of type 2 diabetes. Consistent with a protective effect of GAS6, the c.834+7G>A polymorphism is associated with type 2 diabetes risk in humans [2]. The AA phenotype is associated with higher levels of GAS6, lower glucose levels, and decreased diabetes risk. Currently used drugs affecting the incretin axis have stimulated interest in therapeutic approaches that either preserve or enhance beta cell mass or function, and GAS6 (secreted by alpha cells) is, therefore, an attractive therapeutic target.

Role of telehealth in diabetic foot ulcer management - A systematic review.

OBJECTIVES To review the use of telehealth in subjects with diabetic foot ulcer; evaluating its clinical outcomes, diagnostic accuracy, cost-effectiveness and behavioural perceptions. DESIGN Systematic review. SETTING Selected studies were conducted in Australia, USA, the Netherlands, Denmark, Poland and UK. PARTICIPANTS A total of 948 identified studies were evaluated against the inclusion criteria. Eleven eligible studies were included for review. Patients with diabetic foot ulcer had to have telehealth guided management. MAIN OUTCOME MEASURES Telehealth systems were evaluated against at least one of the following: clinical implications on ulcer healing and disease prognosis; diagnostic accuracy; cost-effectiveness; behavioural perceptions among health professionals or patients. RESULT Eleven eligible studies were included for review. Studies that evaluated telehealth against clinical outcomes were underpowered by study design, sample sizes and short duration follow-up. Telehealth systems demonstrated good intra- and inter-observer reproducibility, high diagnostic accuracy and agreement with live assessments. Authors rationalised the cost-effectiveness of their respective telehealth systems, but could not support this with long-term cost analysis. Both patient and health professionals responded positively towards telehealth in surveys and face-to-face interviews. CONCLUSION Telehealth yields high diagnostic accuracy, reproducibility and positive behavioural perceptions. However, it is not clear if telehealth use in diabetic foot management has favourable clinical and economic outcomes. More long-term prospective controlled trials on larger populations are needed to further characterise our findings.

Short-chain fatty acids increase expression and secretion of stromal cell-derived factor-1 in mouse and human pre-adipocytes

OBJECTIVEStromal cell-derived factor-1 (SDF-1) is expressed in pre-adipocytes but its role is unknown. We investigated butyrate (a histone deacetylase inhibitor — HDACi) and other short-chain fatty acids (SCFA) in the regulation of SDF-1. We further investigated whether effects of SCFA were signalled through G protein-coupled receptors FFA2 and FFA3.DESIGN AND RESULTSSDF-1 mRNA expression and protein secretion were studied in 3T3-L1 cells and human pre-adipocytes. SDF-1 was abundant, with mRNA and protein levels increased by butyrate. This was replicated with acetate and propionate, but not with trichostatin or valproate. Trichostatin inhibited SDF-1 secretion. Pertussis toxin blocked stimulation by butyrate. The order of potency of SCFA in stimulating SDF-1 (C3 > C4 > C2) is consistent with action through FFA3. Silencing the FFA3 gene abolished butyrate-stimulated SDF-1 expression and secretion. FFA3 was expressed in both pre-adipocytes and adipocytes, while FFA2 was expressed in adipocytes only. SDF-1 expression was low in murine macrophage J774.2 cells, while the SDF-1 receptor CXCR4 was absent from 3T3-L1 cells but abundant in J774.2 macrophages. In human pre-adipocytes, FFA3 was also expressed and SCFA increased SDF-1 secretion.CONCLUSIONSSDF-1 and CXCR4 may mediate the interaction between adipose stromal cells and macrophages. Effects of SCFA are mediated through FFA3, but not histone deacetylase inhibition.