Le rôle des sociétés de capital-investissement dans la formation d'alliances stratégiques

This research analyses the role of Private Equity firms in the formation of strategic alliances within the field of the French Private Equity market. We start to provide evidence of its importance from new survey information, before offering an explanation of the organizational phenomenon. The study addresses the questions of how and why Private Equity firms act as relational intermediaries to help their portfolio companies form alliances. Both questions are investigated in the light of the Private Equity firms’ contribution to the value creation process that comes with alliance formation. Answers are provided by means of three jointly used theoretical frameworks: (1) mainstream theories (transaction cost theory and the positive theory of agency); (2) the knowledge based view; and 3) social network theories to complement the resulting from jointly use of the previous two theories. The theoretical construct is then tested empirically by means of a multi-method study with explanatory design, based on the pattern of joint evidence from both statistical tests and a multiple case study. Results show that French Private Equity firms do play a role in alliance formation. This role can be intentional as well as non-intentional. Furthermore, although arguments from the knowledge-based perspective finds more support in explaining this behavior than from the mainstream theories, our study highlights the benefits of the joint use of these theories and the complementary nature of them to better explaining the phenomenon as a whole.Ce travail analyse le rôle des sociétés de capital-investissement dans la formation d’alliances stratégiques sur le marché français du capital-investissement. Après nous être fait une idée de l’importance du phénomène à l’aide des informations nouvelles que nous avons générées par notre propre enquête, nous apportons une explication au phénomène observé. L’analyse théorique se fait sous l’angle de la création de valeur actionnariale, en recourant conjointement aux théories contractuelles et cognitives. Les théories sociologiques des réseaux viennent compléter les principaux arguments de ces deux cadres théoriques. Le modèle explicatif qui en découle est ensuite mis à l’épreuve empirique à l’aide d’une étude multi-méthodes à visée infirmationniste, combinant une analyse économétrique et une étude de cas multiples. Nos résultats permettent de conclure que les sociétés françaises de capital-investissement jouent un rôle tant intentionnel que non intentionnel dans la formation d’alliances stratégiques pour leurs participations. Ces rôles mettent en avant une intervention tant passive qu’active des sociétés françaises de capital-investissement. Bien que l’argumentation cognitive trouve, dans son ensemble, plus de support que l’argumentation contractuelle, l’analyse fait ressortir l’intérêt de recourir à une utilisation conjointe des théories contractuelles et cognitives qui se révèlent complémentaires

Imaging the tympanic membrane oscillation ex vivo with Doppler optical coherence tomography during simulated Eustachian catarrh

Recently, optical coherence tomography (OCT) was utilized in multiple studies for structural and functional imaging of the middle ear and the tympanic membrane. Since Doppler OCT allows both, the spatially resolved measurement of the tympanic membrane oscillation and high-resolution imaging, it is regarded as a promising tool for future in vivo applications. In this study, Doppler OCT is utilized for the visualization of the tympanic membrane oscillation in temporal bones with simulated Eustachian catarrh, which was realized by generating a depression in the tympanic cavity. The transfer function, meaning the oscillation amplitude normalized to the applied sound pressure, is measured frequency resolved in the range from 0.5 kHz to 6 kHz and with a lateral spatial resolution of 0.4 mm. Typical oscillation patterns could be observed in case of ambient pressure in the tympanic cavity. Under depression the characteristic oscillation patterns were observed with widely congruent appearance but at higher frequencies

Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms

IntroductionPersonalization is a much-discussed approach to improve adherence and outcomes for Digital Mental Health interventions (DMHIs). Yet, major questions remain open, such as (1) what personalization is, (2) how prevalent it is in practice, and (3) what benefits it truly has.MethodsWe address this gap by performing a systematic literature review identifying all empirical studies on DMHIs targeting depressive symptoms in adults from 2015 to September 2022. The search in Pubmed, SCOPUS and Psycinfo led to the inclusion of 138 articles, describing 94 distinct DMHIs provided to an overall sample of approximately 24,300 individuals.ResultsOur investigation results in the conceptualization of personalization as purposefully designed variation between individuals in an intervention's therapeutic elements or its structure. We propose to further differentiate personalization by what is personalized (i.e., intervention content, content order, level of guidance or communication) and the underlying mechanism [i.e., user choice, provider choice, decision rules, and machine-learning (ML) based approaches]. Applying this concept, we identified personalization in 66% of the interventions for depressive symptoms, with personalized intervention content (32% of interventions) and communication with the user (30%) being particularly popular. Personalization via decision rules (48%) and user choice (36%) were the most used mechanisms, while the utilization of ML was rare (3%). Two-thirds of personalized interventions only tailored one dimension of the intervention.DiscussionWe conclude that future interventions could provide even more personalized experiences and especially benefit from using ML models. Finally, empirical evidence for personalization was scarce and inconclusive, making further evidence for the benefits of personalization highly needed.Systematic Review RegistrationIdentifier: CRD42022357408

The Human Blood Transcriptome in a Large Population Cohort and Its Relation to Aging and Health

Background: The blood transcriptome is expected to provide a detailed picture of an organism’s physiological state with potential outcomes for applications in medical diagnostics and molecular and epidemiological research.We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration. Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features. Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes. Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications

Integration of Genome-Wide SNP Data and Gene-Expression Profiles Reveals Six Novel Loci and Regulatory Mechanisms for Amino Acids and Acylcarnitines in Whole Blood

Profiling amino acids and acylcarnitines in whole blood spots is a powerful tool in the laboratory diagnosis of several inborn errors of metabolism. Emerging data suggests that altered blood levels of amino acids and acylcarnitines are also associated with common metabolic diseases in adults. Thus, the identification of common genetic determinants for blood metabolites might shed light on pathways contributing to human physiology and common diseases. We applied a targeted mass-spectrometry-based method to analyze whole blood concentrations of 96 amino acids, acylcarnitines and pathway associated metabolite ratios in a Central European cohort of 2, 107 adults and performed genome-wide association (GWA) to identify genetic modifiers of metabolite concentrations. We discovered and replicated six novel loci associated with blood levels of total acylcarnitine, arginine (both on chromosome 6;rs12210538, rs17657775),propionylcarnitine (chromosome 10;rs12779637),2-hydroxyisovalerylcarnitine (chromosome 21;rs1571700),stearoylcarnitine (chromosome 1;rs3811444),and aspartic acid traits (chromosome 8;rs750472). Based on an integrative analysis of expression quantitative trait loci in blood mononuclear cells and correlations between gene expressions and metabolite levels, we provide evidence for putative causative genes: SLC22A16 for total acylcarnitines, ARG1 for arginine, HLCS for 2-hydroxyisovalerylcarnitine, JAM3 for stearoylcarnitine via a trans-effect at chromosome 1, and PPP1R16A for aspartic acid traits. Further, we report replication and provide additional functional evidence for ten loci that have previously been published for metabolites measured in plasma, serum or urine. In conclusion, our integrative analysis of SNP, gene-expression and metabolite data points to novel genetic factors that may be involved in the regulation of human metabolism. At several loci, we provide evidence for metabolite regulation via gene-expression and observed overlaps with GWAS loci for common diseases. These results form a strong rationale for subsequent functional and disease-related studies

Association of MICA with rheumatoid arthritis independent of known HLA-DRB1 risk alleles in a family-based and a case control study

Introduction The gene MICA encodes the protein major histocompatibility complex class I polypeptide-related sequence A. It is expressed in synovium of patients with rheumatoid arthritis (RA) and its implication in autoimmunity is discussed. We analyzed the association of genetic variants of MICA with susceptibility to RA. Methods Initially, 300 French Caucasian individuals belonging to 100 RA trio families were studied. An additional 100 independent RA trio families and a German Caucasian case-control cohort (90/182 individuals) were available for replication. As MICA is situated in proximity to known risk alleles of the HLA-DRB1 locus, our analysis accounted for linkage disequilibrium either by analyzing the subgroup consisting of parents not carrying HLA-DRB1 risk alleles with transmission disequilibrium test (TDT) or by implementing a regression model including all available data. Analysis included a microsatellite polymorphism (GCT)n and single-nucleotide polymorphisms (SNPs) rs3763288 and rs1051794. Results In contrast to the other investigated polymorphisms, the non-synonymously coding SNP MICA-250 (rs1051794, Lys196Glu) was strongly associated in the first family cohort (TDT: P = 0.014; regression model: odds ratio [OR] 0.46, 95% confidence interval [CI] 0.25 to 0.82, P = 0.007). Although the replication family sample showed only a trend, combined family data remained consistent with the hypothesis of MICA-250 association independent from shared epitope (SE) alleles (TDT: P = 0.027; regression model: OR 0.56, 95% CI 0.38 to 0.83, P = 0.003). We also replicated the protective association of MICA-250A within a German Caucasian cohort (OR 0.31, 95% CI 0.1 to 0.7, P = 0.005; regression model: OR 0.6, 95% CI 0.37 to 0.96, P = 0.032). We showed complete linkage disequilibrium of MICA-250 (D' = 1, r2= 1) with the functional MICA variant rs1051792 (D' = 1, r2= 1). As rs1051792 confers differential allelic affinity of MICA to the receptor NKG2D, this provides a possible functional explanation for the observed association. Conclusions We present evidence for linkage and association of MICA-250 (rs1051794) with RA independent of known HLA-DRB1 risk alleles, suggesting MICA as an RA susceptibility gene. However, more studies within other populations are necessary to prove the general relevance of this polymorphism for RA

Cellular Adhesion Gene SELP Is Associated with Rheumatoid Arthritis and Displays Differential Allelic Expression.

In rheumatoid arthritis (RA), a key event is infiltration of inflammatory immune cells into the synovial lining, possibly aggravated by dysregulation of cellular adhesion molecules. Therefore, single nucleotide polymorphisms of 14 genes involved in cellular adhesion processes (CAST, ITGA4, ITGB1, ITGB2, PECAM1, PTEN, PTPN11, PTPRC, PXN, SELE, SELP, SRC, TYK2, and VCAM1) were analyzed for association with RA. Association analysis was performed consecutively in three European RA family sample groups (Nfamilies = 407). Additionally, we investigated differential allelic expression, a possible functional consequence of genetic variants. SELP (selectin P, CD62P) SNP-allele rs6136-T was associated with risk for RA in two RA family sample groups as well as in global analysis of all three groups (ptotal = 0.003). This allele was also expressed preferentially (p<10-6) with a two- fold average increase in regulated samples. Differential expression is supported by data from Genevar MuTHER (p1 = 0.004; p2 = 0.0177). Evidence for influence of rs6136 on transcription factor binding was also found in silico and in public datasets reporting in vitro data. In summary, we found SELP rs6136-T to be associated with RA and with increased expression of SELP mRNA. SELP is located on the surface of endothelial cells and crucial for recruitment, adhesion, and migration of inflammatory cells into the joint. Genetically determined increased SELP expression levels might thus be a novel additional risk factor for RA

Coronavirus disease 2019 induces multi‐lineage, morphologic changes in peripheral blood cells

The clinical course of coronavirus disease 2019 (COVID‐19) varies from mild symptoms to acute respiratory distress syndrome, hyperinflammation, and coagulation disorder. The hematopoietic system plays a critical role in the observed hyperinflammation, particularly in severely ill patients. We conducted a prospective diagnostic study performing a blood differential analyzing morphologic changes in peripheral blood of COVID‐19 patients. COVID‐19 associated morphologic changes were defined in a training cohort and subsequently validated in a second cohort (n = 45). Morphologic aberrations were further analyzed by electron microscopy (EM) and flow cytometry of lymphocytes was performed. We included 45 COVID‐19 patients in our study (median age 58 years; 82% on intensive care unit). The blood differential showed a specific pattern of pronounced multi‐lineage aberrations in lymphocytes (80%) and monocytes (91%) of patients. Overall, 84%, 98%, and 98% exhibited aberrations in granulopoiesis, erythropoiesis, and thrombopoiesis, respectively. Electron microscopy revealed the ultrastructural equivalents of the observed changes and confirmed the multi‐lineage aberrations already seen by light microscopy. The morphologic pattern caused by COVID‐19 is characteristic and underlines the serious perturbation of the hematopoietic system. We defined a hematologic COVID‐19 pattern to facilitate further independent diagnostic analysis and to investigate the impact on the hematologic system during the clinical course of COVID‐19 patients