Women with early maltreatment experience show increased resting-state functional connectivity in the theory of mind (ToM) network.

Background: Experience of childhood maltreatment significantly increases the risk for the development of psychopathology and is associated with impairments in socio-cognitive skills including theory-of-mind (ToM). In turn, neural alterations in ToM processing might then influence future interpersonal interaction and social-emotional understanding. Objective: To assess resting-state activity in the theory-of-mind network in traumatized and non-traumatized persons. Methods: Thirty-five women with a history of childhood maltreatment and 31 unaffected women completed a resting-state scan and a ToM localizer task. The peak coordinates from the localizer were used as the seed regions for the resting-state functional connectivity (RSFC) analyses (temporo-parietal junction, dorsomedial prefrontal cortex, middle temporal gyrus and precuneus). Results: Child abuse was associated with increased RSFC between various ToM regions including the precuneus and the brainstem suggesting altered hierarchical processing in ToM regions. Number of types of abuse was driving the effect for the temporo-parietal junction and the brainstem, while the severity of abuse was linked to increased RSFC between the middle temporal gyrus and the frontal cortex. Post-hoc analyses of brainstem regions indicated the involvement of the serotonergic system (dorsal raphe). Conclusions: The data indicate a lasting impact of childhood maltreatment on the neural networks involved in social information processing that are integral to understanding others' emotional states. Indeed, such altered neural networks may account for some of the interpersonal difficulties victims of childhood maltreatment experience

Factors Associated With Lameness in Tie Stall Housed Dairy Cows in South Germany

Lameness remains a major concern for animal welfare and productivity in modern dairy production. Even though a trend toward loose housing systems exists and the public expects livestock to be kept under conditions where freedom of movement and the expression of natural behavior are ensured, restrictive housing systems continue to be the predominant type of housing in some regions. Factors associated with lameness were evaluated by application of multiple logistic regression modeling on data of 1,006 dairy cows from 56 tie stall farms in Bavaria, South Germany. In this population, approximately every fourth cow was lame (24.44% of scored animals). The mean farm level prevalence of lameness was 23.28%. In total, 22 factors were analyzed regarding their association with lameness. A low Body Condition Score (BCS) (OR 1.54 [95%-CI 1.05-2.25]) as well as increasing parity (OR 1.41 [95%-CI 1.29-1.54]) entailed greater odds of lameness. Moreover, higher milk yield (OR 0.98 [95%-CI 0.96-1.00]) and organic farming (OR 0.48 [95%-0.25-0.92]) appeared to be protectively associated with lameness. Cows with hock injuries (OR 2.57 [95%-CI 1.41-4.67]) or with swellings of the ribs (OR 2.55 [95%-CI 1.53-4.23]) had higher odds of lameness. A similar association was observed for the contamination of the lower legs with distinct plaques of manure (OR 1.88 [95%-CI 1.14-3.10]). As a central aspect of tie stall housing, the length of the stalls was associated with lameness; with stalls of medium [(>158-171 cm) (OR 2.15 [95%-CI 1.29-3.58]) and short (171 cm). These results can help both gaining knowledge on relevant factors associated with lameness as well as approaching the problem of dairy cow lameness in tie stall operations

Fibroblast-secreted hepatocyte growth factor mediates epidermal growth factor receptor tyrosine kinase inhibitor resistance in triple-negative breast cancers through paracrine activation of Met

Abstract Introduction Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have shown clinical efficacy in lung, colon, and pancreatic cancers. In lung cancer, resistance to EGFR TKIs correlates with amplification of the hepatocyte growth factor (HGF) receptor tyrosine kinase Met. Breast cancers do not respond to EGFR TKIs, even though EGFR is overexpressed. This intrinsic resistance to EGFR TKIs in breast cancer does not correlate with Met amplification. In several tissue monoculture models of human breast cancer, Met, although expressed, is not phosphorylated, suggesting a requirement for a paracrine-produced ligand. In fact, HGF, the ligand for Met, is not expressed in epithelial cells but is secreted by fibroblasts in the tumor stroma. We have identified a number of breast cancer cell lines that are sensitive to EGFR TKIs. This sensitivity is in conflict with the observed clinical resistance to EGFR TKIs in breast cancers. Here we demonstrate that fibroblast secretion of HGF activates Met and leads to EGFR/Met crosstalk and resistance to EGFR TKIs in triple-negative breast cancer (TNBC). Methods The SUM102 and SUM149 TNBC cell lines were used in this study. Recombinant HGF as well as conditioned media from fibroblasts expressing HGF were used as sources for Met activation. Furthermore, we co-cultured HGF-secreting fibroblasts with Met-expressing cancer cells to mimic the paracrine HGF/Met pathway, which is active in the tumor microenvironment. Cell growth, survival, and transformation were measured by cell counting, clonogenic and MTS assays, and soft agar colony formation, respectively. Student\u27s t test was used for all statistical analysis. Results Here we demonstrate that treatment of breast cancer cells sensitive to EGFR TKIs with recombinant HGF confers a resistance to EGFR TKIs. Interestingly, knocking down EGFR abrogated HGF-mediated cell survival, suggesting a crosstalk between EGFR and Met. HGF is secreted as a single-chain pro-form, which has to be proteolytically cleaved in order to activate Met. To determine whether the proteases required to activate pro-HGF were present in the breast cancer cells, we utilized a fibroblast cell line expressing pro-HGF (RMF-HGF). Addition of pro-HGF-secreting conditioned fibroblast media to TNBC cells as well as co-culturing of TNBC cells with RMF-HGF fibroblasts resulted in robust phosphorylation of Met and stimulated proliferation in the presence of an EGFR TKI. Conclusions Taken together, these data suggest a role for Met in clinical resistance to EGFR TKIs in breast cancer through EGFR/Met crosstalk mediated by tumor-stromal interactions

Amyloid-Beta Mediates Homeostatic Synaptic Plasticity

The physiological role of the amyloid-precursor protein (APP) is insufficiently understood. Recent work has implicated APP in the regulation of synaptic plasticity. Substantial evidence exists for a role of APP and its secreted ectodomain APPsa in Hebbian plasticity. Here, we addressed the relevance of APP in homeostatic synaptic plasticity using organotypic tissue cultures prepared from APP-/-mice of both sexes. In the absence of APP, dentate granule cells failed to strengthen their excitatory synapses homeostatically. Homeostatic plasticity is rescued by amyloid-b and not by APPsa, and it is neither observed in APP+/+ tissue treated with b-or c-secretase inhibitors nor in synaptopodin-deficient cultures lacking the Ca2+-dependent molecular machinery of the spine apparatus. Together, these results suggest a role of APP processing via the amyloidogenic pathway in homeostatic synaptic plasticity, representing a function of relevance for brain physiology as well as for brain states associated with increased amyloid-b levels. Considerable effort has been directed to better understand the pathogenic role of the amyloid precursor protein (APP) and its cleavage products in neurodegeneration, with a major focus on the accumulation and deposition of synaptotoxic amyloid$(A$) peptides, which are produced by sequential cleavage of APP by $ - and y-secretases. Although the amyloidogenic APP processing pathway has recently been targeted in patients with Alzheimer's disease, the physiological role of APP/A

Collective States in Molecular Monolayers on 2D Materials

Collective excited states form in organic two-dimensional layers through the Coulomb coupling of the molecular transition dipole moments. They manifest as characteristic strong and narrow peaks in the excitation and emission spectra that are shifted to lower energies compared to the monomer transition. We study experimentally and theoretically how robust the collective states are against homogeneous and inhomogeneous broadening as well as spatial disorder that occur in real molecular monolayers. Using a microscopic model for a two-dimensional dipole lattice in real space we calculate the properties of collective states and their extinction spectra. We find that the collective states persist even for 1-10% random variation in the molecular position and in the transition frequency, with similar peak position and integrated intensity as for the perfectly ordered system. We measure the optical response of a monolayer of the perylene-derivative MePTCDI on two-dimensional materials. On the wide band-gap insulator hexagonal boron nitride it shows strong emission from the collective state with a line width that is dominated by the inhomogeneous broadening of the molecular state. When using the semimetal graphene as a substrate, however, the luminescence is completely quenched. By combining optical absorption, luminescence, and multi-wavelength Raman scattering we verify that the MePTCDI molecules form very similar collective monolayer states on hexagonal boron nitride and graphene substrates, but on graphene the line width is dominated by non-radiative excitation transfer from the molecules to the substrate. Our study highlights the transition from the localized molecular state of the monomer to a delocalized collective state in the two-dimensional molecular lattice that is entirely based on Coulomb coupling between optically active excitations of the electrons or molecular vibrations

Identifying cow – level factors and farm characteristics associated with locomotion scores in dairy cows using cumulative link mixed models

Lameness is a tremendous problem in intensively managed dairy herds all over the world. It has been associated with considerable adverse effects on animal welfare and economic viability. The majority of studies have evaluated factors associated with gait disturbance by categorising cows into lame and non-lame. This procedure yet entails a loss of information and precision. In the present study, we extend the binomial response to five categories acknowledging the ordered categorical nature of locomotion assessments, which conserves a higher level of information. A cumulative link mixed modelling approach was used to identify factors associated with increasing locomotion scores. The analysis revealed that a low body condition, elevated somatic cell count, more severe hock lesions, increasing parity, absence of pasture access, and poor udder cleanliness were relevant variables associated with higher locomotion scores. Furthermore, distinct differences in the locomotion scores assigned were identified in regard to breed, observer, and season. Using locomotion scores rather than a dichotomised response variable uncovers more refined relationships between gait disturbances and associated factors. This will help to understand the intricate nature of gait disturbances in dairy cows more deeply

Integrated Data Analysis of Six Clinical Studies Points Toward Model-Informed Precision Dosing of Tamoxifen

Introduction: At tamoxifen standard dosing, ∼20% of breast cancer patients do not reach proposed target endoxifen concentrations >5.97 ng/mL. Thus, better understanding the large interindividual variability in tamoxifen pharmacokinetics (PK) is crucial. By applying non-linear mixed-effects (NLME) modeling to a pooled ‘real-world’ clinical PK database, we aimed to (i) dissect several levels of variability and identify factors predictive for endoxifen exposure and (ii) assess different tamoxifen dosing strategies for their potential to increase the number of patients reaching target endoxifen concentrations. Methods: Tamoxifen and endoxifen concentrations with genetic and demographic data of 468 breast cancer patients from six reported studies were used to develop a NLME parent-metabolite PK model. Different levels of variability on model parameters or measurements were investigated and the impact of covariates thereupon explored. The model was subsequently applied in a simulation-based comparison of three dosing strategies with increasing degree of dose individualization for a large virtual breast cancer population. Interindividual variability of endoxifen concentrations and the fraction of patients at risk for not reaching target concentrations were assessed for each dosing strategy. Results and Conclusions: The integrated NLME model enabled to differentiate and quantify four levels of variability (interstudy, interindividual, interoccasion, and intraindividual). Strong influential factors, i.e., CYP2D6 activity score, drug–drug interactions with CYP3A and CYP2D6 inducers/inhibitors and age, were reliably identified, reducing interoccasion variability to <20% CV. Yet, unexplained interindividual variability in endoxifen formation remained large (47.2% CV). Hence, therapeutic drug monitoring seems promising for achieving endoxifen target concentrations. Three tamoxifen dosing strategies [standard dosing (20 mg QD), CYP2D6-guided dosing (20, 40, and 60 mg QD) and individual model-informed precision dosing (MIPD)] using three therapeutic drug monitoring samples (5–120 mg QD) were compared, leveraging the model. The proportion of patients at risk for not reaching target concentrations was 22.2% in standard dosing, 16.0% in CYP2D6-guided dosing and 7.19% in MIPD. While in CYP2D6-guided- and standard dosing interindividual variability in endoxifen concentrations was high (64.0% CV and 68.1% CV, respectively), it was considerably reduced in MIPD (24.0% CV). Hence, MIPD demonstrated to be the most promising strategy for achieving target endoxifen concentrations

Perspectives on Model-Informed Precision Dosing in the Digital Health Era: Challenges, Opportunities, and Recommendations

Drug approval is based on exposure, response, and variability of studied populations, typically excluding comorbidities/medications and very ill patients, thus not representing real‐world populations. This results in wide variability in therapeutic outcome for individual patients. Model‐informed precision dosing (MIPD) can characterize/quantify this variability, support optimal dose selection, and enable individualized therapy. The aim of this perspective is to raise awareness for MIPD, identify challenges hindering its implementation in clinical practice, provide recommendations, and highlight opportunities

Obesity alters endoxifen plasma levels in young breast cancer patients: A pharmacometric simulation approach

Endoxifen is one of the most important metabolites of the prodrug tamoxifen. High interindividual variability in endoxifen steady‐state concentrations (CSS,min ENDX) is observed under tamoxifen standard dosing and patients with breast cancer who do not reach endoxifen concentrations above a proposed therapeutic threshold of 5.97 ng/mL may be at a 26% higher recurrence risk compared with patients with endoxifen concentrations exceeding this value. In this investigation, 10 clinical tamoxifen studies were pooled (1,388 patients) to investigate influential factors on CSS,min ENDX using nonlinear mixed‐effects modeling. Age and body weight were found to significantly impact CSS,min ENDX in addition to CYP2D6 phenotype. Compared with postmenopausal patients, premenopausal patients had a 30% higher risk for subtarget CSS,min ENDX at tamoxifen 20 mg per day. In treatment simulations for distinct patient subpopulations, young overweight patients had a 3.1–13.8‐fold higher risk for subtarget CSS,min ENDX compared with elderly low‐weight patients. Considering ever‐rising obesity rates and the clinical importance of tamoxifen for premenopausal patients, this subpopulation may benefit most from individualized tamoxifen dosing

Simulation-Based Assessment of the Impact of Non-Adherence on Endoxifen Target Attainment in Different Tamoxifen Dosing Strategies

Tamoxifen is widely used in breast cancer treatment and minimum steady-state concentrations of its active metabolite endoxifen (CSS,min ENDX) above 5.97 ng/mL have been associated with favourable disease outcome. Yet, about 20% of patients do not reach target CSS,min ENDX applying conventional tamoxifen dosing. Moreover, 4–75% of patients are non-adherent, resulting in worse disease outcomes. Assuming complete adherence, we previously showed model-informed precision dosing (MIPD) to be superior to conventional and CYP2D6-guided dosing in minimising the proportion of patients with subtarget CSS,min ENDX. Given the high non-adherence rate in long-term tamoxifen therapy, this study investigated the impact of non-adherence on CSS,min ENDX target attainment in different dosing strategies. We show that MIPD allows to account for the expected level of non-adherence (here: up to 2 missed doses/week): increasing the MIPD target threshold from 5.97 ng/mL to 9 ng/mL (the lowest reported CSS,min ENDX in CYP2D6 normal metabolisers) as a safeguard resulted in the lowest interindividual variability and proportion of patients with subtarget CSS,min ENDX even in non-adherent patients. This is a significant improvement to conventional and CYP2D6-guided dosing. Adding a fixed increment to the originally selected dose is not recommended, since it inflates interindividual variability