Lactation following bereavement: how can midwives support women to make informed choices?

Perinatal loss, defined as the death of a baby within the neonatal period, stillbirth or late miscarriage (determined for the purpose of this paper as 20 weeks’ gestation), has been identified by multiple agencies and organisations as a focus for increased parental support. However, the lactation needs of mothers are broadly overlooked, which can lead to engorgement, mastitis and psychological harm. The most commonly offered option of pharmacological suppression is controversial due to a lack of efficacy, and concerns about physiological effects (Cole 2012). Women may already have stored frozen expressed breast milk (EBM) within the neonatal intensive care unit (NICU), or be discharged home before their milk comes in several days later. In our experience, information and guidance for bereaved mothers about lactation and EBM are often lacking.For preterm neonates, the use of human milk for nutrition has been demonstrated to have significant health benefits compared to artificial formula (Quigley & McGuire 2014). Incidence of infection-related events, such as urinary tract infections, necrotising enterocolitis and sepsis can be reduced, and lengths of stay in the NICU are shortened when human milk is used (Maffei & Schanler 2017). While mother’s-own-milk (MOM) is the optimal form of human milk, the use of donor human milk can act as a bridge whilst a mother establishes her milk production, or in instances where MOM cannot be used. Milk banking has been carried out in the United Kingdom (UK) for over 80 years, based on the voluntary donation of milk from women screened according to national guidelines (NICE 2010). Current research describes a diverse population of milk donors in the UK, for whom key motivators to donate were the encouragement of health professionals alongside the sense of altruism gained from the experience (Thomaz et al 2008). For bereaved parents, with appropriate support, milk donation may aid the grieving process, but previously the evidence had not been examined in a systematic manner. Expressed milk belongs to the mother and its fate after infant loss is her decision. However, bereaved mothers are often overlooked as potential milk donors (Carroll et al 2014). This study aimed to search the literature and examine local practice in order to explore the experience of bereaved mothers; in particular regarding the subject of milk donation following perinatal loss, in order to guide training and inform recommendations for future practice.Peer reviewe

Electrophysiological study of dopamine neurons in the dorsal raphe nucleus & ventrolateral periaqueductal grey

The midbrain dopamine system plays a fundamental conserved role in regulating behaviour, and its dysfunction is associated with several neuropsychiatric disorders including addiction, schizophrenia, and Parkinson’s Disease. Midbrain dopamine neurons display considerable heterogeneity in their neurochemical, electrophysiological, and functional properties, and project to many cortical and subcortical structures. The majority of these neurons reside within the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA), but a less well-known, and understudied, dopamine population are housed within the dorsal raphe nucleus (DRN) and ventrolateral periaqueductal grey (vlPAG). These neurons provide the majority of the dopaminergic input to the central extended amygdala and have been implicated in the sleep-wake cycle and mediating the effects of opiates. However, their electrophysiological properties have not been examined. I have studied these neurons in mice using immunohistochemistry and electrophysiology in an acute brain slice preparation ex vivo. I found that they display similar properties to some VTA dopamine neurons, and noted co-expression of vasoactive intestinal peptide in a subset of this population. A characteristic feature of VTA dopamine neurons is the potentiation observed at glutamatergic synapses following a single dose of addictive drug or an acute stress experience. I investigated whether DRN/vlPAG dopamine neurons would show cocaine-induced plasticity and found that glutamatergic synapses were potentiated not only by a single dose of cocaine, but also by acute social isolation. This potentiation was associated with a change in AMPAR transmission, which is similar to that observed following cocaine in the VTA. I also investigated the hypothesis that this plasticity is a result of acute anxiety using behavioural analysis and administration of anxiolytic compounds. These findings suggest another form of salient stimulus which can induce plasticity in dopamine neurons, and have relevance to several neuropsychiatric diseases including those modelled by social isolation

Politicians, Pundits, and Platform Migration: A Comparison of Political Polarization on Parler and Twitter

Parler, a self-proclaimed free speech social media platform founded in 2018, attracted a large influx of new members in 2020 as the result of a highly visible platform migration campaign. Parler usage was linked to the planning of the Jan. 6, 2021 attack on the United States Capitol building, leading to a shutdown of the Parler platform. Parler, which is now back online, offers an important lens through which to examine the broader attempts at platform migration in response to changing content moderation and platform governance policies and their impact on political polarization. We begin by examining the network connections between US Congressional Representatives on both Twitter and Parler. We find that Parler has a homogenous population of users, consisting of a single isolated group, where polarization seems irrelevant, while Twitter demonstrates two clearly polarized groups. We compare how politicians and political pundits use Parler differently. Finally, we examine the evolution of Parler including comparing Parler’s own policies before and after the shutdown and reflecting on the future of platforms like Parler and similar platform migration experiments

Automatic categorization of diverse experimental information in the bioscience literature

Background: Curation of information from bioscience literature into biological knowledge databases is a crucial way of capturing experimental information in a computable form. During the biocuration process, a critical first step is to identify from all published literature the papers that contain results for a specific data type the curator is interested in annotating. This step normally requires curators to manually examine many papers to ascertain which few contain information of interest and thus, is usually time consuming. We developed an automatic method for identifying papers containing these curation data types among a large pool of published scientific papers based on the machine learning method Support Vector Machine (SVM). This classification system is completely automatic and can be readily applied to diverse experimental data types. It has been in use in production for automatic categorization of 10 different experimental datatypes in the biocuration process at WormBase for the past two years and it is in the process of being adopted in the biocuration process at FlyBase and the Saccharomyces Genome Database (SGD). We anticipate that this method can be readily adopted by various databases in the biocuration community and thereby greatly reducing time spent on an otherwise laborious and demanding task. We also developed a simple, readily automated procedure to utilize training papers of similar data types from different bodies of literature such as C. elegans and D. melanogaster to identify papers with any of these data types for a single database. This approach has great significance because for some data types, especially those of low occurrence, a single corpus often does not have enough training papers to achieve satisfactory performance. Results: We successfully tested the method on ten data types from WormBase, fifteen data types from FlyBase and three data types from Mouse Genomics Informatics (MGI). It is being used in the curation work flow at WormBase for automatic association of newly published papers with ten data types including RNAi, antibody, phenotype, gene regulation, mutant allele sequence, gene expression, gene product interaction, overexpression phenotype, gene interaction, and gene structure correction. Conclusions: Our methods are applicable to a variety of data types with training set containing several hundreds to a few thousand documents. It is completely automatic and, thus can be readily incorporated to different workflow at different literature-based databases. We believe that the work presented here can contribute greatly to the tremendous task of automating the important yet labor-intensive biocuration effort

Artificial intelligence in digital pathology: a diagnostic test accuracy systematic review and meta-analysis

Ensuring diagnostic performance of AI models before clinical use is key to the safe and successful adoption of these technologies. Studies reporting AI applied to digital pathology images for diagnostic purposes have rapidly increased in number in recent years. The aim of this work is to provide an overview of the diagnostic accuracy of AI in digital pathology images from all areas of pathology. This systematic review and meta-analysis included diagnostic accuracy studies using any type of artificial intelligence applied to whole slide images (WSIs) in any disease type. The reference standard was diagnosis through histopathological assessment and / or immunohistochemistry. Searches were conducted in PubMed, EMBASE and CENTRAL in June 2022. We identified 2976 studies, of which 100 were included in the review and 48 in the full meta-analysis. Risk of bias and concerns of applicability were assessed using the QUADAS-2 tool. Data extraction was conducted by two investigators and meta-analysis was performed using a bivariate random effects model. 100 studies were identified for inclusion, equating to over 152,000 whole slide images (WSIs) and representing many disease types. Of these, 48 studies were included in the meta-analysis. These studies reported a mean sensitivity of 96.3% (CI 94.1-97.7) and mean specificity of 93.3% (CI 90.5-95.4) for AI. There was substantial heterogeneity in study design and all 100 studies identified for inclusion had at least one area at high or unclear risk of bias. This review provides a broad overview of AI performance across applications in whole slide imaging. However, there is huge variability in study design and available performance data, with details around the conduct of the study and make up of the datasets frequently missing. Overall, AI offers good accuracy when applied to WSIs but requires more rigorous evaluation of its performance.Comment: 26 pages, 5 figures, 8 tables + Supplementary material

The protein kinase C inhibitor, Ro-31-7459, is a potent activator of ERK and JNK MAP kinases in HUVECs and yet inhibits cyclic AMP-stimulated <i>SOCS-3</i> gene induction through inactivation of the transcription factor c-Jun

Induction of the suppressor of cytokine signalling 3 (SOCS-3) gene is vital to the normal control of inflammatory signalling. In order to understand these processes we investigated the role of the proto-oncogene component of the AP-1 transcription factor complex, c-Jun, in the regulation of SOCS-3 gene induction. We found that cyclic AMP stimulation of HUVECs promoted phosphorylation and activation of JNK MAP kinase and its substrate c-Jun. The JNK responsive element of the human SOCS-3 promoter mapped to a putative AP-1 site within 1000 bp of the transcription start site. The PKC inhibitors, GF-109203X, Gö-6983 and Ro-317549, were all found to inhibit AP-1 transcriptional activity, transcriptional activation of this minimal SOCS-3 promoter and SOCS-3 gene induction in HUVECs. Interestingly, Ro-317549 treatment was also found to promote PKC-dependent activation of ERK and JNK MAP kinases and promote JNK-dependent hyper-phosphorylation of c-Jun, whereas GF-109203X and Gö-6983 had little effect. Despite this, all three PKC inhibitors were found to be effective inhibitors of c-Jun DNA-binding activity. The JNK-dependent hyper-phosphorylation of c-Jun in response to Ro-317549 treatment of HUVECs does therefore not interfere with its ability to inhibit c-Jun activity and acts as an effective inhibitor of c-Jun-dependent SOCS-3 gene induction

Inhibitory Input from the Lateral Hypothalamus to the Ventral Tegmental Area Disinhibits Dopamine Neurons and Promotes Behavioral Activation

Projections from the lateral hypothalamus (LH) to the ventral tegmental area (VTA), containing both GABAergic and glutamatergic components, encode conditioned responses and control compulsive reward-seeking behavior. GABAergic neurons in the LH have been shown to mediate appetitive and feeding-related behaviors. Here we show that the GABAergic component of the LH-VTA pathway supports positive reinforcement and place preference, while the glutamatergic component mediates place avoidance. In addition, our results indicate that photoactivation of these projections modulates other behaviors, such as social interaction and perseverant investigation of a novel object. We provide evidence that photostimulation of the GABAergic LH-VTA component, but not the glutamatergic component, increases dopamine (DA) release in the nucleus accumbens (NAc) via inhibition of local VTA GABAergic neurons. Our study clarifies how GABAergic LH inputs to the VTA can contribute to generalized behavioral activation across multiple contexts, consistent with a role in increasing motivational salience.National Institute of Mental Health (U.S.) (Grant R01-MH102441-01

Decoding Neural Circuits that Control Compulsive Sucrose Seeking

SummaryThe lateral hypothalamic (LH) projection to the ventral tegmental area (VTA) has been linked to reward processing, but the computations within the LH-VTA loop that give rise to specific aspects of behavior have been difficult to isolate. We show that LH-VTA neurons encode the learned action of seeking a reward, independent of reward availability. In contrast, LH neurons downstream of VTA encode reward-predictive cues and unexpected reward omission. We show that inhibiting the LH-VTA pathway reduces “compulsive” sucrose seeking but not food consumption in hungry mice. We reveal that the LH sends excitatory and inhibitory input onto VTA dopamine (DA) and GABA neurons, and that the GABAergic projection drives feeding-related behavior. Our study overlays information about the type, function, and connectivity of LH neurons and identifies a neural circuit that selectively controls compulsive sugar consumption, without preventing feeding necessary for survival, providing a potential target for therapeutic interventions for compulsive-overeating disorder