Is Something Missing from Your Company\u27s Satisfaction Package?

Conventional wisdom suggests that salary, benefits, and other monetary factors are important aspects of keeping employees satisfied. But which factors have the biggest impact on overall satisfaction? While companies focus on the monetary factors, there are other components of the overall “satisfaction package,” that are just as important, yet often overlooked. It comes as no surprise that satisfied employees are important to the success of any organization. In short, higher satisfaction increases productivity, improves service levels, and positively impacts a company’s bottom line. While keeping employees satisfied should be an important goal for any organization, a recent job satisfaction survey by the Conference Board shows that job satisfaction has actually declined in the last nine years. So what should a company to do? Conventional wisdom suggests that salary, benefits, and other monetary factors are important aspects of keeping employees satisfied. But will giving these perks to a dissatisfied employee resolve the problem? Maybe in the short-term, but who has unlimited stashes of cash to buy satisfaction? Further, this “fix” is often short-term in nature

Flexibility within the Heads of Muscle Myosin-2 Molecules

We show that negative-stain electron microscopy and image processing of nucleotide-free (apo) striated muscle myosin-2 subfragment-1 (S1), possessing one light chain or both light chains, is capable of resolving significant amounts of structural detail. The overall appearance of the motor and the lever is similar in rabbit, scallop and chicken S1. Projection matching of class averages of the different S1 types to projection views of two different crystal structures of apo S1 shows that all types most commonly closely resemble the appearance of the scallop S1 structure rather than the methylated chicken S1 structure. Methylation of chicken S1 has no effect on the structure of the molecule at this resolution: it too resembles the scallop S1 crystal structure. The lever is found to vary in its angle of attachment to the motor domain, with a hinge point located in the so-called pliant region between the converter and the essential light chain. The chicken S1 crystal structure lies near one end of the range of flexion observed. The Gaussian spread of angles of flexion suggests that flexibility is driven thermally, from which a torsional spring constant of ~ 23 pN·nm/rad2 is estimated on average for all S1 types, similar to myosin-5. This translates to apparent cantilever-type stiffness at the tip of the lever of 0.37 pN/nm. Because this stiffness is lower than recent estimates from myosin-2 heads attached to actin, we suggest that binding to actin leads to an allosteric stiffening of the motor–lever junction

Structures of smooth muscle myosin and heavy meromyosin in the folded, shutdown state

Remodelling of the contractile apparatus within smooth muscle cells is an essential process that allows effective contractile activity over a wide range of cell lengths. The thick filaments may be redistributed via depolymerisation into inactive myosin monomers that have been detected in vitro, in which the long tail has a folded conformation. The structure of this folded molecule has been controversial. Using negative stain electron microscopy of individual folded molecules from turkey gizzard we show they are more compact than previously described, with heads and the three segments of the folded tail closely packed. Smooth muscle heavy meromyosin (HMM), which lacks two-thirds of the tail, closely resembles the equivalent parts of whole myosin. Image processing reveals a characteristic head region morphology for both HMM and myosin whose features are identifiable by comparison with less compact molecules. The two heads associate asymmetrically: the tip of one motor domain touches the base of the other, resembling the blocked and free heads of this HMM when it forms 2-D crystals on lipid. The tail of HMM lies between the heads, contacting the blocked motor domain, unlike in the 2-D crystal. The tail of the intact myosin is bent sharply and consistently at two positions close to residues 1175 and 1535. The first bend position correlates with a skip in the coiled coil sequence, the second does not. The first segment runs between the heads from the head-tail junction. Unexpectedly, the other segments associate only with the blocked head rather than both heads, such that the second bend lies at a specific position near the C-lobe of the blocked head regulatory light chain. Quantitative analysis of tail flexibility shows that the single coiled coil of HMM has an apparent Young’s modulus of about 0.5 GPa. The folded tail of the intact molecule is less flexible indicating interactions between the segments. The folded tail does not modify the compact head arrangement but stabilises it, indicating a structural mechanism for the very low ATPase activity of the folded molecule

The prepower stroke conformation of myosin V

eW have used electron microscopy and single-particle image processing to study head conformation in myosin V molecules. We find that in the presence of ATP, many heads have a sharply angled conformation that is rare in its absence. The sharply angled conformation is similar to a myosin II atomic structure proposed to mimic the prepower stroke state. The leading head in molecules attached to actin by both heads has a similar conformation, but is also sharply angled in a second plane by tethering through the trail head. The lead head lever joins the motor domain ∼5 nm axially from where it joins the trail motor. These positions locate the converter subdomain and show the lead motor is in the prepower stroke conformation. Tethering by the trail head places the lead head motor domain at the correct axial position along the actin for binding, but at the wrong orientation. Attachment is achieved either by bending the lead head lever throughout its length or at the pliant point. The microscopy shows that most of the walking stride is produced by changes in lever angle brought about by converter movement, but is augmented by distortion produced by thermal energy

The potential shared role of inflammation in insulin resistance and schizophrenia:a bidirectional two-sample mendelian randomization study

BACKGROUND: Insulin resistance predisposes to cardiometabolic disorders, which are commonly comorbid with schizophrenia and are key contributors to the significant excess mortality in schizophrenia. Mechanisms for the comorbidity remain unclear, but observational studies have implicated inflammation in both schizophrenia and cardiometabolic disorders separately. We aimed to examine whether there is genetic evidence that insulin resistance and 7 related cardiometabolic traits may be causally associated with schizophrenia, and whether evidence supports inflammation as a common mechanism for cardiometabolic disorders and schizophrenia. METHODS AND FINDINGS: We used summary data from genome-wide association studies of mostly European adults from large consortia (Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) featuring up to 108,557 participants; Diabetes Genetics Replication And Meta-analysis (DIAGRAM) featuring up to 435,387 participants; Global Lipids Genetics Consortium (GLGC) featuring up to 173,082 participants; Genetic Investigation of Anthropometric Traits (GIANT) featuring up to 339,224 participants; Psychiatric Genomics Consortium (PGC) featuring up to 105,318 participants; and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium featuring up to 204,402 participants). We conducted two-sample uni- and multivariable mendelian randomization (MR) analysis to test whether (i) 10 cardiometabolic traits (fasting insulin, high-density lipoprotein and triglycerides representing an insulin resistance phenotype, and 7 related cardiometabolic traits: low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance, and type 2 diabetes) could be causally associated with schizophrenia; and (ii) inflammation could be a shared mechanism for these phenotypes. We conducted a detailed set of sensitivity analyses to test the assumptions for a valid MR analysis. We did not find statistically significant evidence in support of a causal relationship between cardiometabolic traits and schizophrenia, or vice versa. However, we report that a genetically predicted inflammation-related insulin resistance phenotype (raised fasting insulin (raised fasting insulin (Wald ratio OR = 2.95, 95% C.I, 1.38–6.34, Holm-Bonferroni corrected p-value (p) = 0.035) and lower high-density lipoprotein (Wald ratio OR = 0.55, 95% C.I., 0.36–0.84; p = 0.035)) was associated with schizophrenia. Evidence for these associations attenuated to the null in multivariable MR analyses after adjusting for C-reactive protein, an archetypal inflammatory marker: (fasting insulin Wald ratio OR = 1.02, 95% C.I, 0.37–2.78, p = 0.975), high-density lipoprotein (Wald ratio OR = 1.00, 95% C.I., 0.85–1.16; p = 0.849), suggesting that the associations could be fully explained by inflammation. One potential limitation of the study is that the full range of gene products from the genetic variants we used as proxies for the exposures is unknown, and so we are unable to comment on potential biological mechanisms of association other than inflammation, which may also be relevant. CONCLUSIONS: Our findings support a role for inflammation as a common cause for insulin resistance and schizophrenia, which may at least partly explain why the traits commonly co-occur in clinical practice. Inflammation and immune pathways may represent novel therapeutic targets for the prevention or treatment of schizophrenia and comorbid insulin resistance. Future work is needed to understand how inflammation may contribute to the risk of schizophrenia and insulin resistance

The potential shared role of inflammation in insulin resistance and schizophrenia: A bidirectional two-sample mendelian randomization study

Background: Insulin resistance predisposes to cardiometabolic disorders, which are commonly comorbid with schizophrenia and are key contributors to the significant excess mortality in schizophrenia. Mechanisms for the comorbidity remain unclear, but observational studies have implicated inflammation in both schizophrenia and cardiometabolic disorders separately. We aimed to examine whether there is genetic evidence that insulin resistance and 7 related cardiometabolic traits may be causally associated with schizophrenia, and whether evidence supports inflammation as a common mechanism for cardiometabolic disorders and schizophrenia. Methods and findings: We used summary data from genome-wide association studies of mostly European adults from large consortia (Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) featuring up to 108,557 participants; Diabetes Genetics Replication And Meta-analysis (DIAGRAM) featuring up to 435,387 participants; Global Lipids Genetics Consortium (GLGC) featuring up to 173,082 participants; Genetic Investigation of Anthropometric Traits (GIANT) featuring up to 339,224 participants; Psychiatric Genomics Consortium (PGC) featuring up to 105,318 participants; and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium featuring up to 204,402 participants). We conducted two-sample uni- and multivariable mendelian randomization (MR) analysis to test whether (i) 10 cardiometabolic traits (fasting insulin, high-density lipoprotein and triglycerides representing an insulin resistance phenotype, and 7 related cardiometabolic traits: low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance, and type 2 diabetes) could be causally associated with schizophrenia; and (ii) inflammation could be a shared mechanism for these phenotypes. We conducted a detailed set of sensitivity analyses to test the assumptions for a valid MR analysis. We did not find statistically significant evidence in support of a causal relationship between cardiometabolic traits and schizophrenia, or vice versa. However, we report that a genetically predicted inflammation-related insulin resistance phenotype (raised fasting insulin (raised fasting insulin (Wald ratio OR = 2.95, 95% C.I, 1.38–6.34, Holm-Bonferroni corrected p-value (p) = 0.035) and lower high-density lipoprotein (Wald ratio OR = 0.55, 95% C.I., 0.36–0.84; p = 0.035)) was associated with schizophrenia. Evidence for these associations attenuated to the null in multivariable MR analyses after adjusting for C-reactive protein, an archetypal inflammatory marker: (fasting insulin Wald ratio OR = 1.02, 95% C.I, 0.37–2.78, p = 0.975), high-density lipoprotein (Wald ratio OR = 1.00, 95% C.I., 0.85–1.16; p = 0.849), suggesting that the associations could be fully explained by inflammation. One potential limitation of the study is that the full range of gene products from the genetic variants we used as proxies for the exposures is unknown, and so we are unable to comment on potential biological mechanisms of association other than inflammation, which may also be relevant. Conclusions: Our findings support a role for inflammation as a common cause for insulin resistance and schizophrenia, which may at least partly explain why the traits commonly co-occur in clinical practice. Inflammation and immune pathways may represent novel therapeutic targets for the prevention or treatment of schizophrenia and comorbid insulin resistance. Future work is needed to understand how inflammation may contribute to the risk of schizophrenia and insulin resistance

The potential shared role of inflammation in insulin resistance and schizophrenia: A bidirectional two-sample mendelian randomization study

Background: Insulin resistance predisposes to cardiometabolic disorders, which are commonly comorbid with schizophrenia and are key contributors to the significant excess mortality in schizophrenia. Mechanisms for the comorbidity remain unclear, but observational studies have implicated inflammation in both schizophrenia and cardiometabolic disorders separately. We aimed to examine whether there is genetic evidence that insulin resistance and 7 related cardiometabolic traits may be causally associated with schizophrenia, and whether evidence supports inflammation as a common mechanism for cardiometabolic disorders and schizophrenia. Methods and findings: We used summary data from genome-wide association studies of mostly European adults from large consortia (Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) featuring up to 108,557 participants; Diabetes Genetics Replication And Meta-analysis (DIAGRAM) featuring up to 435,387 participants; Global Lipids Genetics Consortium (GLGC) featuring up to 173,082 participants; Genetic Investigation of Anthropometric Traits (GIANT) featuring up to 339,224 participants; Psychiatric Genomics Consortium (PGC) featuring up to 105,318 participants; and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium featuring up to 204,402 participants). We conducted two-sample uni- and multivariable mendelian randomization (MR) analysis to test whether (i) 10 cardiometabolic traits (fasting insulin, high-density lipoprotein and triglycerides representing an insulin resistance phenotype, and 7 related cardiometabolic traits: low-density lipoprotein, fasting plasma glucose, glycated haemoglobin, leptin, body mass index, glucose tolerance, and type 2 diabetes) could be causally associated with schizophrenia; and (ii) inflammation could be a shared mechanism for these phenotypes. We conducted a detailed set of sensitivity analyses to test the assumptions for a valid MR analysis. We did not find statistically significant evidence in support of a causal relationship between cardiometabolic traits and schizophrenia, or vice versa. However, we report that a genetically predicted inflammation-related insulin resistance phenotype (raised fasting insulin (raised fasting insulin (Wald ratio OR = 2.95, 95% C.I, 1.38–6.34, Holm-Bonferroni corrected p-value (p) = 0.035) and lower high-density lipoprotein (Wald ratio OR = 0.55, 95% C.I., 0.36–0.84; p = 0.035)) was associated with schizophrenia. Evidence for these associations attenuated to the null in multivariable MR analyses after adjusting for C-reactive protein, an archetypal inflammatory marker: (fasting insulin Wald ratio OR = 1.02, 95% C.I, 0.37–2.78, p = 0.975), high-density lipoprotein (Wald ratio OR = 1.00, 95% C.I., 0.85–1.16; p = 0.849), suggesting that the associations could be fully explained by inflammation. One potential limitation of the study is that the full range of gene products from the genetic variants we used as proxies for the exposures is unknown, and so we are unable to comment on potential biological mechanisms of association other than inflammation, which may also be relevant. Conclusions: Our findings support a role for inflammation as a common cause for insulin resistance and schizophrenia, which may at least partly explain why the traits commonly co-occur in clinical practice. Inflammation and immune pathways may represent novel therapeutic targets for the prevention or treatment of schizophrenia and comorbid insulin resistance. Future work is needed to understand how inflammation may contribute to the risk of schizophrenia and insulin resistance

Protocol for the "four steps to control your fatigue (4-STEPS)" randomised controlled trial: a self-regulation based physical activity intervention for patients with unexplained chronic fatigue

<p>Abstract</p> <p>Background</p> <p>Unexplained Chronic Fatigue is a medical condition characterized by the presence of persistent, severe and debilitating medically unexplained fatigue, leading to impaired functioning and lower quality of life. Research suggests that physical activity can contribute to the reduction of fatigue and other somatic symptoms and can thus significantly improve physical functioning and quality of life in these patients. Based on the self-regulation (SR) theory of behaviour change, we developed a brief physical activity program for patients suffering from unexplained chronic fatigue which focuses on the training of self-regulation skills, the "4-STEPS to control your fatigue" program.</p> <p>Methods/Design</p> <p>This is a multi-centre, randomised controlled trial (RCT) that will be carried out in local primary care centres and at the Portuguese Fibromyalgia and Chronic Fatigue Syndrome Patients Association. Patients aged between 18 and 65 and fulfilling operationalized criteria for Idiopathic Chronic Fatigue (ICF) and Chronic Fatigue Syndrome (CFS) will be recruited and randomly allocated to standard care (SC) or standard care plus a self-regulation based physical activity program (4-STEPS). Patients will be assessed at baseline, after the intervention (3 months) and at 12 months follow-up. The primary outcome is fatigue severity.</p> <p>Discussion</p> <p>The results of the RCT will provide information about the effectiveness of a brief self-regulation intervention for promoting physical activity in patients with unexplained chronic fatigue. If the program proves to be effective, it may be considered as an adjunctive treatment for these patients.</p> <p>Trial Registration</p> <p>ISRCTN: <a href="http://www.anzctr.org.au/ISRCTN70763996.aspx">ISRCTN70763996</a></p