Human Resource Practices and Organizational Commitment: A Deeper Examination

This paper examines newer conceptualizations of HRM practices in the HR-Performance Relationship as well as newer conceptualizations of commitment. Juxtaposing these categories of HR practices and types of commitment provides a clearer theoretical rational for at least some ways that HR practices can influence organizational performance, be that positive or negative. Implications for research are then discussed

Recruitment and Selection

[Excerpt] In this chapter, we look to address the second issue by developing a theoretical model of the link between different staffing systems and firm-level performance. We first look to existing theory on organizational design and structure to better understand the role of recruitment and selection. Specifically, we argue that organizations are structured into unique subunits of employees based on the equivocality of available information in their jobs and the resulting need for organizational rationality or openness. Drawing on existing empirical work on strategic human resource management, we argue that unique systems of recruitment and selection practices are necessary to provide the level of employee knowledge, skills, and abilities to match the level of information equivocality faced by the employees in these roles. In particular, we put forth arguments that recruitment and selection systems that match with the mechanistic organizational structure are the best fit for subunits of employees facing low information uncertainty; whereas recruitment and selection systems that match with the organic organizational structure are the best fit for subunits of employees facing high informational uncertainty

Give Them Some Slack - They\u27re Trying to Change! The Benefits of Excess Cash, Excess Employees, and Increased Human Capital in the Context of Strategic Change

[Excerpt] Human resource strategists perennially struggle with the issue of staffing levels, especially the difficult task of determining the number of people required to meet their units’ business goals. Should they go “lean and mean”, as the saying goes, or is it better to overstaff a bit – to build a little slack in the system? Theory suggests that the answer to this question is “it depends”. Units experiencing periods of stability with little change are advised to opt for the former approach in the interest of enhancing operational efficiency and minimizing labor costs. Those undergoing strategic change, however, would do better to build in some HR slack to allow for the allocation of talent to the exploration and early staffing of new initiatives without detracting from current operations. This notion of contingency has some empirical support with respect to financial slack, but to date there is no comparable research on HR slack. The study reported here fills this gap, while taking the additional step of exploring whether HR slack and financial slack have complementary effects on firm performance (see Figure 1 on page 2). Initially, the study examined whether the role of HR slack differed in firms that were and were not undergoing strategic change. Second, the analysis focused specifically on firms undergoing strategic transitions and explored two questions: (1) To what extent did the existence of financial slack affect the relationship between HR slack and firm performance? And (2) to what extent did it matter whether or not firms chose to allocate a significant portion of their financial slack to developing their human capital? To help answer these questions, the study relied on data provided by the Federal Deposit Insurance Company (FDIC) pertaining to 6,606 commercial banks covering a 12-year period between 2002 and 2014

The Goldilocks Effect of Strategic Human Resource Management? Optimizing the Benefits of a High-Performance Work System Through the Dual Alignment of Vertical and Horizontal Fit

Although vertical and horizontal fit in strategic human resource management are foundational to the links between a high-performance work system (HPWS) and organizational performance, little is known about how these two fits interact to affect organizational performance. We address this shortcoming while also advancing knowledge on each type of fit. We offer a more nuanced examination of vertical fit (which has typically been assessed with respect to organizations\u27 broad strategic types) by focusing on the alignment of an HPWS with an organization\u27s market entry timing mode—a key element of strategy. We propose that among organizations pursuing new product development, the effect of an HPWS on organizational performance is most positive under a fast-follower entry timing, followed by a first-mover and finally a fence-sitter entry timing. We then hypothesize that the benefit of vertical fit is magnified when the complementary human resources practices comprising an HPWS are implemented with greater internal consistency (or with similar intensities) across the ability, motivation, and opportunity domains—reflecting a positive interaction between vertical and horizontal fit in predicting the effectiveness of an HPWS. Analyses of four-wave nationally representative panel data yield strong support for our dual-alignment model of SHRM

A Call to Action: Taking the Untenable out of Women Professors’ Pregnancy, Postpartum, and Caregiving Demands

Despite becoming increasingly represented in academic departments, women scholars face a critical lack of support as they navigate demands pertaining to pregnancy, motherhood, and child caregiving. In addition, cultural norms surrounding how faculty and academic leaders discuss and talk about tenure, promotion, and career success have created pressure for women who wish to grow their family and care for their children, leading to questions about whether it is possible for these women to have a family and an academic career. The current paper is a call to action for academia to build structures that support women professors as they navigate the complexities of pregnancy, the postpartum period, and the caregiving demands of their children. We specifically call on those of us in I-O psychology, management, and related departments to lead the way. In making this call, we first present the realistic, moral, and financial cases for why this issue needs to be at the forefront of discussions surrounding success in the academy. We then discuss how in the U.S. and elsewhere, an absence of policies supporting women places two groups of academics—department heads (as the leaders of departments who have discretion outside of formal policies to make work better for women) and other faculty members (as potential allies both in the department and within our professional organizations)—in a critical position to enact support and change. We conclude with our boldest call—to make a cultural shift that shatters the assumption that having a family is not compatible with academic success. Combined, we seek to launch a discussion that leads directly to necessary and overdue changes in how women scholars are supported in academia

THERAPEUTIC EFFECTS OF HYPOXIC AND PRO-INFLAMMATORY PRIMING OF MESENCHYMAL STEM CELL-DERIVED EXTRACELLULAR VESICLES IN INFLAMMATORY ARTHRITIS

AbstractNovel biological therapies have revolutionised the management of Rheumatoid Arthritis (RA) but no cure currently exists. Mesenchymal stem cells (MSCs) immunomodulate inflammatory responses through paracrine signalling, including via secretion of extracellular vesicles (EVs) in the cell secretome. We evaluated the therapeutic potential of MSCs-derived small EVs in an antigen-induced model of arthritis (AIA).EVs isolated from MSCs cultured normoxically (21% O2, 5% CO2), hypoxically (2% O2, 5% CO2) or with a pro-inflammatory cytokine cocktail were applied into the AIA model. Disease pathology was assessed post-arthritis induction through swelling and histopathological analysis of synovial joint structure. Activated CD4+ T cells from healthy mice were cultured with EVs or MSCs to assess deactivation capabilities prior to application of standard EVs in vivo to assess T cell polarisation within the immune response to AIA.All EVs treatments reduced knee-joint swelling whilst only normoxic and pro-inflammatory primed EVs improved histopathological outcomes. In vitro culture with EVs did not achieve T cell deactivation. Polarisation towards CD4+ helper cells expressing IL17a (Th17) was reduced when normoxic and hypoxic EV treatments were applied in vitro. Normoxic EVs applied into the AIA model reduced Th17 polarisation and improved Th17:Treg homeostatic balance.Priming of MSCs in EV production can be applied to alter the therapeutic efficacy however normoxic EVs present the optimal strategy for broad therapeutic benefit. The varied outcomes observed in MSCs priming may promote EVs optimised for therapies targeted for specific therapeutic priorities. EVs present an effective novel technology with potential for cell-free therapeutic translation.</jats:p

Identification and Validation of Novel Cerebrospinal Fluid Biomarkers for Staging Early Alzheimer's Disease

Ideally, disease modifying therapies for Alzheimer disease (AD) will be applied during the 'preclinical' stage (pathology present with cognition intact) before severe neuronal damage occurs, or upon recognizing very mild cognitive impairment. Developing and judiciously administering such therapies will require biomarker panels to identify early AD pathology, classify disease stage, monitor pathological progression, and predict cognitive decline. To discover such biomarkers, we measured AD-associated changes in the cerebrospinal fluid (CSF) proteome.CSF samples from individuals with mild AD (Clinical Dementia Rating [CDR] 1) (n = 24) and cognitively normal controls (CDR 0) (n = 24) were subjected to two-dimensional difference-in-gel electrophoresis. Within 119 differentially-abundant gel features, mass spectrometry (LC-MS/MS) identified 47 proteins. For validation, eleven proteins were re-evaluated by enzyme-linked immunosorbent assays (ELISA). Six of these assays (NrCAM, YKL-40, chromogranin A, carnosinase I, transthyretin, cystatin C) distinguished CDR 1 and CDR 0 groups and were subsequently applied (with tau, p-tau181 and Aβ42 ELISAs) to a larger independent cohort (n = 292) that included individuals with very mild dementia (CDR 0.5). Receiver-operating characteristic curve analyses using stepwise logistic regression yielded optimal biomarker combinations to distinguish CDR 0 from CDR>0 (tau, YKL-40, NrCAM) and CDR 1 from CDR<1 (tau, chromogranin A, carnosinase I) with areas under the curve of 0.90 (0.85-0.94 95% confidence interval [CI]) and 0.88 (0.81-0.94 CI), respectively.Four novel CSF biomarkers for AD (NrCAM, YKL-40, chromogranin A, carnosinase I) can improve the diagnostic accuracy of Aβ42 and tau. Together, these six markers describe six clinicopathological stages from cognitive normalcy to mild dementia, including stages defined by increased risk of cognitive decline. Such a panel might improve clinical trial efficiency by guiding subject enrollment and monitoring disease progression. Further studies will be required to validate this panel and evaluate its potential for distinguishing AD from other dementing conditions

Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease

Background 1Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Background Late–onset Alzheimer's disease (AD) is heritable with 20 genes showing genome wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (p = 3.27×10-12 after multiple testing correction for pathways), regulation of endocytosis (p = 1.31×10-11), cholesterol transport (p = 2.96 × 10-9) and proteasome-ubiquitin activity (p = 1.34×10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected p 0.002 – 0.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport and protein ubiquitination represent prime targets for AD therapeutics

predictive precision medicine towards the computational challenge

The emerging fields of predictive and precision medicine are changing the traditional medical approach to disease and patient. Current discoveries in medicine enable to deepen the comprehension of diseases, whereas the adoption of high-quality methods such as novel imaging techniques (e.g. MRI, PET) and computational approaches (i.e. machine learning) to analyse data allows researchers to have meaningful clinical and statistical information. Indeed, applications of radiology techniques and machine learning algorithms rose in the last years to study neurology, cardiology and oncology conditions. In this chapter, we will provide an overview on predictive precision medicine that uses artificial intelligence to analyse medical images to enhance diagnosis, prognosis and treatment of diseases. In particular, the chapter will focus on neurodegenerative disorders that are one of the main fields of application. Despite some critical issues of this new approach, adopting a patient-centred approach could bring remarkable improvement on individual, social and business level