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Abstract Divers commonly breathe air, containing nitrogen. Nitrogen under hyperbaric conditions is a narcotic gas. In dives beyond a notional threshold of 30 m depth (405 kPa) this can cause cognitive impairment, culminating in accidents due to poor decision making. Helium is known to have no narcotic effect. This study explored potential approaches to developing an electroencephalogram (EEG) functional connectivity metric to measure narcosis produced by nitrogen at hyperbaric pressures. Twelve human participants (five female) breathed air and heliox (in random order) at 284 and 608 kPa while recording 32-channel EEG and psychometric function. The degree of spatial functional connectivity, estimated using mutual information, was summarized with global efficiency. Air-breathing at 608 kPa (experienced as mild narcosis) caused a 35% increase in global efficiency compared to surface air-breathing (mean increase = 0.17, 95% CI [0.09–0.25], p = 0.001). Air-breathing at 284 kPa trended in a similar direction. Functional connectivity was modestly associated with psychometric impairment (mixed-effects model r2 = 0.60, receiver-operating-characteristic area, 0.67 [0.51–0.84], p = 0.02). Heliox breathing did not cause a significant change in functional connectivity. In conclusion, functional connectivity increased during hyperbaric air-breathing in a dose-dependent manner, but not while heliox-breathing. This suggests sensitivity to nitrogen narcosis specifically.

Abstract The mechanisms underlying myopia pathogenesis are not well understood. Using publicly-available human and animal datasets, we expound on the roles of known, implicated proteins, and new myopia-related signaling pathways were hypothesized. Proteins identified from human serum or ocular fluids, and from ocular tissues in myopic animal models, were uploaded and analyzed with the QIAGEN Ingenuity Pathway Analysis (IPA) software (March 2023). With each IPA database update, more potentially-relevant proteins and signaling pathways previously unavailable during data acquisition are added, allowing extraction of novel conclusions from existing data. Canonical pathway analysis was used to analyze these data and calculate an IPA activation z-score—which indicates not only whether an association is significant, but also whether the pathway is likely activated or inhibited. Cellular immune response and cytokine signaling were frequently found to be affected in both human and animal myopia studies. Analysis of two publicly-available proteomic datasets highlighted a potential role of the innate immune system and inflammation in myopia development, detailing specific signaling pathways involved such as Granzyme A (GzmA) and S100 family signaling in the retina, and activation of myofibroblast trans-differentiation in the sclera. This perspective in myopia research may facilitate development of more effective and targeted therapeutic agents.

Abstract Sjögren syndrome (SS) is an autoimmune disease characterized by chronic inflammatory infiltrates in the salivary and lacrimal glands. Mucosal-associated invariant T (MAIT) cells are a subset of innate-like T-cells, predominantly found in mucosal tissues with crucial role in epithelial homeostasis. Thus, MAIT cells may be implicated in mucosal alterations of SS patients. Activation markers, inflammatory and cytotoxic cytokines were examined in 23 SS patients and compared to 23 healthy controls (HC). Tissular MAIT cells in salivary gland (SG) biopsies were also analyzed. Circulating MAIT cells were decreased in SS patients with a higher expression of CD69 and a higher CD4/CD8 ratio of MAIT cells. MAIT cells showed a higher production of IFNγ, TNFα and GzB in SS compare to HC. Tissular MAIT cells were present within inflamed SG of SS patients, while they were absent in SG of HC. Overall, circulating MAIT cells are decreased in the peripheral blood of SS albeit producing higher amounts of IFNγ, TNFα, and GzB. Tissular MAIT cells are detected in salivary glands from SS with a proinflammatory tissular cytokine environment. MAIT cells with abnormal phenotype, functions and tissular homeostasis may contribute to epithelial damage in SS.

Abstract Termites are widely distributed globally and serve as a valuable food source in many countries. However, information on the myriad nutritional benefits of processed termite products in African markets remain largely unexploited. This study evaluated the phytochemicals, fatty acids, amino acids, minerals, vitamins and proximate composition of the edible winged termites (Macrotermes spp.) from three major Counties of Kenya. A total of 9 flavonoids, 5 alkaloids, and 1 cytokinin were identified. The oil content varied from 33 to 46%, exhibiting significant levels of beneficial omega 3 fatty acids, such as methyl (9Z,12Z,15Z)-octadecatrienoate and methyl (5Z,8Z,11Z,14Z,17Z)-eicosapentaenoate, ranging from 82.7–95.1 to 6.3–8.1 µg/g, respectively, across the different regions. Four essential and cereal-limiting amino acids lysine (1.0–1.3 mg/g), methionine (0.08–0.1 mg/g), leucine (0.6–0.9 mg/g) and threonine (0.1–0.2 mg/g), were predominant. Moreover, termites had a rich profile of essential minerals, including iron (70.7–111.8 mg/100 g), zinc (4.4–16.2 mg/100 g) and calcium (33.1–53.0 mg/100 g), as well as vitamins A (2.4–6.4 mg/kg), C (0.6–1.9 mg/kg) and B12 (10.7–17.1 mg/kg). The crude protein (32.2–44.8%) and fat (41.2–49.1%) contents of termites from the various Counties was notably high. These findings demonstrated the promising nutrients potential of winged termites and advocate for their sustainable utilization in contemporary efficacious functional food applications to combat malnutrition.

Abstract Duchenne muscular dystrophy (DMD) patients exhibit a late left ventricular systolic dysfunction preceded by an occult phase, during which myocardial fibrosis progresses and some early functional impairments can be detected. These latter include electrocardiographic (ECG) and heart rate variability (HRV) abnormalities. This longitudinal study aimed at describing the sequence of ECG and HRV abnormalities, using Holter ECG in the GRMD (Golden retriever muscular dystrophy) dog model, known to develop a DMD-like disease, including cardiomyopathy. Most of the known ECG abnormalities described in DMD patients were also found in GRMD dogs, including increased heart rate, prolonged QT and shortened PR intervals, ventricular arrhythmias, and several of them could be detected months before the decrease of fractional shortening. The HRV was impaired like in DMD patients, one of the earliest evidenced abnormalities being a decrease in the very low frequency (VLF) component of the power spectrum. This decrease was correlated with the further reduction of fractional shortening. Such decreased VLF probably reflects impaired autonomic function and abnormal vasomotor tone. This study provides new insights into the knowledge of the GRMD dog model and DMD cardiomyopathy and emphasizes the interest to monitor the VLF power in DMD patients, still unexplored in this disease, whilst it is highly predictive of deleterious clinical events in many other pathological conditions.

Abstract Biomass burning is the main source of air pollution in several regions worldwide nowadays. This predominance is expected to increase in the upcoming years as a result of the rising number of devastating wildfires due to climate change. Harmful pollutants contained in the smoke emitted by fires can alter downwind air quality both locally and remotely as a consequence of the recurrent transport of biomass burning plumes across thousands of kilometers. Here, we demonstrate how observations of carbon monoxide and aerosol optical depth retrieved from polar orbiting and geostationary meteorological satellites can be used to study the long-range transport and evolution of smoke plumes. This is illustrated through the megafire events that occurred during summer 2020 in the Western United States and the transport of the emitted smoke across the Atlantic Ocean to Europe. Analyses from the Copernicus Atmosphere Monitoring Service, which combine satellite observations with an atmospheric model, are used for comparison across the region of study and along simulated air parcel trajectories. Lidar observation from spaceborne and ground-based instruments are used to verify consistency of passive observations. Results show the potential of joint satellite-model analysis to understand the emission, transport, and processing of smoke across the world.

Abstract Climate change poses a serious risk to sustainable forest management, particularly in boreal forests where natural disturbances have been projected to become more severe. In three Quebec boreal forest management units, biomass carbon storage under various climate change and management scenarios was projected over 300 years (2010–2310) with a process-based dynamic landscape model (PnET-succession for Landis-II). Several strategies varying in their use of partial cuts and clear cuts, including business as usual (BAU) (clear-cut applied on more than 95% of the managed area), were tested and compared to conservation scenarios (no-harvest). Based on simulation results at the landscape scale, the clearcut-based scenarios such as BAU could result in a decrease of biomass carbon stock by 10 tC ha−1 yr−1 compared to the natural scenario. However, this reduction in carbon stock could be offset in the long term through changes in composition, as clearcut systems promote the expansion of trembling aspen and white birch. In contrast, the use of strategies based on partial cuts on more than 75% or 50% of the managed area was closer to or better than the natural scenario and resulted in greater coniferous cover retention. These strategies seemed to be the best to maximize and stabilize biomass carbon storage and ensure wood supply under different climate change scenarios, yet they would require further access and appropriate infrastructure. Furthermore, these strategies could maintain species compositions and age structures similar to natural scenarios, and thus may consequently help achieve forest ecosystem-based management targets. This study presents promising strategies to guide sustainable forest management in Eastern Canada in the context of climate change.

Abstract This research aims to advance knowledge on the impact of four processing methods on volatile compounds from insect-based baked products (cookies) to provide insights on consumer acceptance. Samples were exposed to double step enzyme digestive test, volatiles characterized through headspace analysis, while semi-trained panelists were recruited for the sensory test. Blanched and boiled samples of R. differens had considerably higher digestibility (83.42% and 81.61%, respectively) (p

Abstract Dermatological conditions are a relevant health problem. Machine learning (ML) models are increasingly being applied to dermatology as a diagnostic decision support tool using image analysis, especially for skin cancer detection and disease classification. The objective of this study was to perform a prospective validation of an image analysis ML model, which is capable of screening 44 skin diseases, comparing its diagnostic accuracy with that of General Practitioners (GPs) and teledermatology (TD) dermatologists in a real-life setting. Prospective, diagnostic accuracy study including 100 consecutive patients with a skin problem who visited a participating GP in central Catalonia, Spain, between June 2021 and October 2021. The skin issue was first assessed by the GPs. Then an anonymised skin disease picture was taken and uploaded to the ML application, which returned a list with the Top-5 possible diagnosis in order of probability. The same image was then sent to a dermatologist via TD for diagnosis, as per clinical practice. The GPs Top-3, ML model’s Top-5 and dermatologist’s Top-3 assessments were compared to calculate the accuracy, sensitivity, specificity and diagnostic accuracy of the ML models. The overall Top-1 accuracy of the ML model (39%) was lower than that of GPs (64%) and dermatologists (72%). When the analysis was limited to the diagnoses on which the algorithm had been explicitly trained (n = 82), the balanced Top-1 accuracy of the ML model increased (48%) and in the Top-3 (75%) was comparable to the GPs Top-3 accuracy (76%). The Top-5 accuracy of the ML model (89%) was comparable to the dermatologist Top-3 accuracy (90%). For the different diseases, the sensitivity of the model (Top-3 87% and Top-5 96%) is higher than that of the clinicians (Top-3 GPs 76% and Top-3 dermatologists 84%) only in the benign tumour pathology group, being on the other hand the most prevalent category (n = 53). About the satisfaction of professionals, 92% of the GPs considered it as a useful diagnostic support tool (DST) for the differential diagnosis and in 60% of the cases as an aid in the final diagnosis of the skin lesion. The overall diagnostic accuracy of the model in this study, under real-life conditions, is lower than that of both GPs and dermatologists. This result aligns with the findings of few existing prospective studies conducted under real-life conditions. The outcomes emphasize the significance of involving clinicians in the training of the model and the capability of ML models to assist GPs, particularly in differential diagnosis. Nevertheless, external testing in real-life conditions is crucial for data validation and regulation of these AI diagnostic models before they can be used in primary care.

Abstract Despite beneficial effects in acute heart failure, the full therapeutic potential of recombinant relaxin-2 has been hampered by its short half-life and the need for intravenous administration limiting its use to intensive care units. A multiparametric optimization of the relaxin B-chain led to the identification of single chain lipidated peptide agonists of RXFP1 like SA10SC-RLX with subcutaneous bioavailability and extended half-life. SA10SC-RLX has sub nanomolar activity on cells expressing human RXFP1 and molecular modeling associated with the study of different RXFP1 mutants was used to decipher the mechanism of SA10SC-RLX interaction with RXFP1. Telemetry was performed in rat where SA10SC-RLX was able to engage RXFP1 after subcutaneous administration without tachyphylaxis after repeated dosing. Renal blood flow was then used as a translational model to evaluate RXFP1 activation. SA10SC-RLX increased renal blood flow and decreased renal vascular resistance in rats as reported for relaxin in humans. In conclusion, SA10SC-RLX mimics relaxin activity in in vitro and in vivo models of acute RXFP1 engagement. SA10SC-RLX represents a new class of long-lasting RXFP1 agonist, suitable for once daily subcutaneous administration in patients and potentially paving the way to new treatments for chronic fibrotic and cardiovascular diseases.

Abstract Apathy and fatigue have a high prevalence in many pathological populations, but they are also present in healthy adults. The relationship between apathy and fatigue, which are both multidimensional, is still poorly understood. This study aims to describe the associations between the subdimensions of both apathy and fatigue and to investigate their overlaps and dissociations in healthy people. 729 participants (mean age = 30.8 ± 10.7 years) completed online self-assessment questionnaires. The Apathy Motivation Index and Dimensional Apathy Scale were used to assess apathy. The Multidimensional Fatigue Inventory was used to assess fatigue. The executive dimension of apathy showed the strongest correlations with mental fatigue and the two appeared to be underpinned by the same latent factor, according to exploratory factor analysis (EFA). The factor structure of EFA showed overlaps between behavioral apathy and both reduced motivation and activity in fatigue. Emotional and social dimensions of apathy were separately underpinned by a latent factor that comprised no items of fatigue. Apathy and fatigue have reduced activity and mental difficulties in common, whereas emotional and social disorders distinguish apathy from fatigue. This has important implications for assessing apathy and fatigue in the general population, and may be relevant for clinical practice.

Abstract Dual species interactions in co-isolated pairs of Staphylococcus aureus and Pseudomonas aeruginosa from patients with tracheobronchitis or bronchial colonization were examined. The genetic and phenotypic diversity between the isolates was high making the interactions detected strain-specific. Despite this, and the clinical origin of the strains, some interactions were common between some co-isolated pairs. For most pairs, P. aeruginosa exoproducts affected biofilm formation and reduced growth in vitro in its S. aureus counterpart. Conversely, S. aureus did not impair biofilm formation and stimulated swarming motility in P. aeruginosa. Co-culture in a medium that mimics respiratory mucus promoted coexistence and favored mixed microcolony formation within biofilms. Under these conditions, key genes controlled by quorum sensing were differentially regulated in both species in an isolate-dependent manner. Finally, co-infection in the acute infection model in Galleria mellonella larvae showed an additive effect only in the co-isolated pair in which P. aeruginosa affected less S. aureus growth. This work contributes to understanding the complex interspecies interactions between P. aeruginosa and S. aureus by studying strains isolated during acute infection.

Abstract Food additives (e.g. artificial sweeteners, emulsifiers, dyes, etc.) are ingested by billions of individuals daily. Some concerning results, mainly derived from animal and/or cell-based experimental studies, have recently emerged suggesting potential detrimental effects of several widely consumed additives. Profiles of additive exposure as well as the potential long-term impact of multiple exposure on human health are poorly documented. This work aimed to estimate the usual intake of food additives among participants of the French NutriNet-Santé cohort and to identify and describe profiles of exposure (single substances and mixtures). Overall, 106,489 adults from the French NutriNet-Santé cohort study (2009-ongoing) were included. Consumption of 90 main food additives was evaluated using repeated 24 h dietary records including information on brands of commercial products. Qualitative information (as presence/absence) of each additive in food products was determined using 3 large-scale composition databases (OQALI, Open Food Facts, GNPD), accounting for the date of consumption of the product. Quantitative ingested doses were estimated using a combination of laboratory assays on food matrixes (n = 2677) and data from EFSA and JECFA. Exposure was estimated in mg per kg of body weight per day. Profiles of exposure to food additive mixtures were extracted using Non-negative Matrix Factorization (NMF) followed by k-means clustering as well as Graphical Lasso. Sociodemographic and dietary comparison of clusters of participants was performed by Chi-square tests or linear regressions. Data were weighted according to the national census. Forty-eight additives were consumed by more than 10% of the participants, with modified starches and citric acid consumed by more than 90%. The top 50 also included several food additives for which potential adverse health effects have been suggested by recent experimental studies: lecithins (86.6% consumers), mono- and diglycerides of fatty acids (78.1%), carrageenan (77.5%), sodium nitrite (73.9%), di-, tri- and polyphosphates (70.1%), potassium sorbate (65.8%), potassium metabisulphite (44.8%), acesulfame K (34.0%), cochineal (33.9%), potassium nitrate (31.6%), sulfite ammonia caramel (28.8%), bixin (19.5%), monosodium glutamate (15.1%) and sucralose (13.5%). We identified and described five clusters of participants more specifically exposed to five distinct additive mixtures and one additional cluster gathering participants with overall low additive exposure. Food additives, including several for which health concerns are currently debated, were widely consumed in this population-based study. Furthermore, main mixtures of additives were identified. Their health impact and potential cocktail effects should be explored in future epidemiological and experimental studies.

Abstract Oceanic frontal zones have been shown to deeply influence the distribution of primary producers and, at the other extreme of the trophic web, top predators. However, the relationship between these structures and intermediate trophic levels is much more obscure. In this paper we address this knowledge gap by comparing acoustic measurements of mesopelagic fish concentrations to satellite-derived fine-scale Lagrangian Coherent Structures in the Indian sector of the Southern Ocean. First, we demonstrate that higher fish concentrations occur more frequently in correspondence with strong Lagrangian Coherent Structures. Secondly, we illustrate that, while increased fish densities are more likely to be observed over these structures, the presence of a fine-scale feature does not imply a concomitant fish accumulation, as other factors affect fish distribution. Thirdly, we show that, when only chlorophyll-rich waters are considered, front intensity modulates significantly more the local fish concentration. Finally, we discuss a model representing fish movement along Lagrangian features, specifically built for mid-trophic levels. Its results, obtained with realistic parameters, are qualitatively consistent with the observations and the spatio-temporal scales analysed. Overall, these findings may help to integrate intermediate trophic levels in trophic models, which can ultimately support management and conservation policies.

Abstract Intestinal dysbiosis is key in the onset and development of Crohn’s disease (CD). We evaluated the microbiota changes in CD patients before and after a six-month anti-TNF treatment, comparing these changes with the microbiota of healthy subjects. This prospective multicenter observational study involved 27 CD patients initiating anti-TNF treatment and 16 healthy individuals. Inflammatory activity was determined at baseline, 3 and 6 months, classifying patients into responders and non-responders. Fecal microbiota was analyzed by massive genomic sequencing thought 16S rRNA amplicon sequencing before and after six months of anti-TNF treatment. The CD cohort showed a decrease in genera of the class Clostridia, short-chain fatty acid producers, and an increase in the phylum Proteobacteria (p

Abstract Species with small geographic ranges do not tend to have a high genetic structure, but some land snail species seem to be an exception. Xerocrassa montserratensis, an endangered land snail endemic to Catalonia (northeastern Iberian Peninsula), is an excellent model to study the processes affecting the phylogeography of specialized species of conservation concern. This species is restricted to xerophilous stony slopes and occurs within a small and fragmented area of ca. 500 km2. We sequenced the COI barcode region of 152 individuals from eight sites covering the entire range of the species. We found four genetic groups mostly coincident with their geographic distribution: a central ancestral group containing shared haplotypes among five localities and three groups restricted to a single locality each. Two of these derived groups were geographically and genetically isolated, while the third and most differentiated group was not geographically isolated. Geomorphologic and paleoclimatic processes during the Pleistocene can explain the divergence found between populations of this low dispersal species with historical fragmentation and secondary contacts. Nonetheless, recent passive large dispersal through streams was also detected in the central group. Overall, our study uncovered four evolutionary units, partially matching morphologically described subspecies, which should be considered in future conservation actions.

Abstract Despite efforts to improve tuberculosis (TB) detection, limitations in access, quality and timeliness of diagnostic services in low- and middle-income countries are challenging for current TB diagnostics. This study aimed to identify and characterise a metabolic profile of TB in urine by high-field nuclear magnetic resonance (NMR) spectrometry and assess whether the TB metabolic profile is also detected by a low-field benchtop NMR spectrometer. We included 189 patients with tuberculosis, 42 patients with pneumococcal pneumonia, 61 individuals infected with latent tuberculosis and 40 uninfected individuals. We acquired the urine spectra from high and low-field NMR. We characterised a TB metabolic fingerprint from the Principal Component Analysis. We developed a classification model from the Partial Least Squares-Discriminant Analysis and evaluated its performance. We identified a metabolic fingerprint of 31 chemical shift regions assigned to eight metabolites (aminoadipic acid, citrate, creatine, creatinine, glucose, mannitol, phenylalanine, and hippurate). The model developed using low-field NMR urine spectra correctly classified 87.32%, 85.21% and 100% of the TB patients compared to pneumococcal pneumonia patients, LTBI and uninfected individuals, respectively. The model validation correctly classified 84.10% of the TB patients. We have identified and characterised a metabolic profile of TB in urine from a high-field NMR spectrometer and have also detected it using a low-field benchtop NMR spectrometer. The models developed from the metabolic profile of TB identified by both NMR technologies were able to discriminate TB patients from the rest of the study groups and the results were not influenced by anti-TB treatment or TB location. This provides a new approach in the search for possible biomarkers for the diagnosis of TB.

Abstract NMR spectroscopy is a technology that is widely used in metabolomic studies. The information that these studies most commonly use from NMR spectra is the metabolite concentration. However, as well as concentration, pH and ionic strength information are also made available by the chemical shift of metabolite signals. This information is typically not used even though it can enhance sample discrimination, since many conditions show pH or ionic imbalance. Here, we demonstrate how chemical shift information can be used to improve the quality of the discrimination between case and control samples in three public datasets of different human matrices. In two of these datasets, chemical shift information helped to provide an AUROC value higher than 0.9 during sample classification. In the other dataset, the chemical shift also showed discriminant potential (AUROC 0.831). These results are consistent with the pH imbalance characteristic of the condition studied in the datasets. In addition, we show that this signal misalignment dependent on sample class can alter the results of fingerprinting approaches in the three datasets. Our results show that it is possible to use chemical shift information to enhance the diagnostic and predictive properties of NMR.

Abstract Some obese subjects overeat lipid-rich foods. The origin of this eating behavior is unknown. We have here tested the hypothesis that these subjects could be characterized by an impaired fatty taste sensitivity linked to a change in the gustatory papillae microbial and salivary environment. The composition of microbiota and saliva surrounding the circumvallate papillae was analyzed in combination with the orosensory lipid detection threshold in normal weight (NW) and obese (O) adults. Microbial architecture was similar to what was known in feces, but with an increased frequency of Proteobacteria. No difference in the orosensory sensitivity to lipids and composition of oral microbiota and saliva was observed between NW and O subjects. By contrast, specific bacterial and salivary signatures were found in lipid non-tasters, irrespectively of BMI. A multivariate approach highlighted that the salivary flow, lysozyme activity, total antioxidant capacity and TM7 bacterial family discriminated between tasters and non-tasters. Subgroup analysis of obese tasters (OT) versus obese non-tasters (ONT) identified specific bacterial metabolic pathways (i.e. phosphotransferase and simple sugar transport systems) as being higher in ONT. Altogether with the identification of a set of significant salivary variables, our study suggests that an “obese tongue” phenotype is associated with decreased orosensory sensitivity to lipids in some obese subjects.

Abstract Resveratrol (RES), a polyphenol found in natural foods, displays anti-oxidant, anti-inflammatory and anti-proliferative properties potentially beneficial in cancers, in particular in the prevention of tumor growth. However, the rapid metabolism of resveratrol strongly limits its bioavailability. The molecular mechanisms sustaining the potential biological activity of low doses of resveratrol has not been extensively studied and, thus, needs better characterization. Here, we show that resveratrol (10 µM, 48 hr) induces both a cell growth arrest and a metabolic reprogramming in colon cancer cells. Resveratrol modifies the lipidomic profile, increases oxidative capacities and decreases glycolysis, in association with a decreased pentose phosphate activity and an increased ATP production. Resveratrol targets the pyruvate dehydrogenase (PDH) complex, a key mitochondrial gatekeeper of energy metabolism, leading to an enhanced PDH activity. Calcium chelation, as well as the blockade of the mitochondrial calcium uniport, prevents the resveratrol-induced augmentation in oxidative capacities and the increased PDH activity suggesting that calcium might play a role in the metabolic shift. We further demonstrate that the inhibition of the CamKKB or the downstream AMPK pathway partly abolished the resveratrol-induced increase of glucose oxidation. This suggests that resveratrol might improve the oxidative capacities of cancer cells through the CamKKB/AMPK pathway.

Dopamine is well known to regulate movement through the differential control of direct and indirect pathways in the striatum that express D 1 and D 2 receptors respectively. The spinal cord also expresses all dopamine receptors; however, how the specific receptors regulate spinal network output in mammals is poorly understood. We explore the receptor-specific mechanisms that underlie dopaminergic control of spinal network output of neonatal mice during changes in spinal network excitability. During spontaneous activity, which is a characteristic of developing spinal networks operating in a low excitability state, we found that dopamine is primarily inhibitory. We uncover an excitatory D 1 -mediated effect of dopamine on motoneurons and network output that also involves co-activation with D 2 receptors. Critically, these excitatory actions require higher concentrations of dopamine; however, analysis of dopamine concentrations of neonates indicates that endogenous levels of spinal dopamine are low. Because endogenous levels of spinal dopamine are low, this excitatory dopaminergic pathway is likely physiologically-silent at this stage in development. In contrast, the inhibitory effect of dopamine, at low physiological concentrations is mediated by parallel activation of D 2 , D 3 , D 4 and α 2 receptors which is reproduced when endogenous dopamine levels are increased by blocking dopamine reuptake and metabolism. We provide evidence in support of dedicated spinal network components that are controlled by excitatory D 1 and inhibitory D 2 receptors that is reminiscent of the classic dopaminergic indirect and direct pathway within the striatum. These results indicate that network state is an important factor that dictates receptor-specific and therefore dose-dependent control of neuromodulators on spinal network output and advances our understanding of how neuromodulators regulate neural networks under dynamically changing excitability.

Umbria is located in Central Italy and took the name from its ancient inhabitants, the Umbri, whose origins are still debated. Here, we investigated the mitochondrial DNA (mtDNA) variation of 545 present-day Umbrians (with 198 entire mitogenomes) and 28 pre-Roman individuals (obtaining 19 ancient mtDNAs) excavated from the necropolis of Plestia. We found a rather homogeneous distribution of western Eurasian lineages across the region, with few notable exceptions. Contemporary inhabitants of the eastern part, delimited by the Tiber River and the Apennine Mountains, manifest a peculiar mitochondrial proximity to central-eastern Europeans, mainly due to haplogroups U4 and U5a, and an overrepresentation of J (30%) similar to the pre-Roman remains, also excavated in East Umbria. Local genetic continuities are further attested to by six terminal branches (H1e1, J1c3, J2b1, U2e2a, U8b1b1 and K1a4a) shared between ancient and modern mitogenomes. Eventually, we identified multiple inputs from various population sources that likely shaped the mitochondrial gene pool of ancient Umbri over time, since early Neolithic, including gene flows with central-eastern Europe. This diachronic mtDNA portrait of Umbria fits well with the genome-wide population structure identified on the entire peninsula and with historical sources that list the Umbri among the most ancient Italic populations.

There are presently no reliable ways to quantify endocrine cell mass (ECM) in vivo, which prevents an accurate understanding of the progressive beta cell loss in diabetes or following islet transplantation. To address this unmet need, we coupled RNA sequencing of human pancreatic islets to a systems biology approach to identify new biomarkers of the endocrine pancreas. Dipeptidyl-Peptidase 6 (DPP6) was identified as a target whose mRNA expression is at least 25-fold higher in human pancreatic islets as compared to surrounding tissues and is not changed by proinflammatory cytokines. At the protein level, DPP6 localizes only in beta and alpha cells within the pancreas. We next generated a high-affinity camelid single-domain antibody (nanobody) targeting human DPP6. The nanobody was radiolabelled and in vivo SPECT/CT imaging and biodistribution studies were performed in immunodeficient mice that were either transplanted with DPP6-expressing Kelly neuroblastoma cells or insulin-producing human EndoC-βH1 cells. The human DPP6-expressing cells were clearly visualized in both models. In conclusion, we have identified a novel beta and alpha cell biomarker and developed a tracer for in vivo imaging of human insulin secreting cells. This provides a useful tool to non-invasively follow up intramuscularly implanted insulin secreting cells.

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Mechanistic studies of deregulated ERG in prostate cancer and other cancers continue to enhance its role in cancer biology and its utility as a biomarker and therapeutic target. Here, we show that ERG, through its physical interaction with androgen receptor, induces AR aggregation and endoplasmic reticulum stress in the prostate glands of ERG transgenic mice. Histomorphological alterations and the expression of ER stress sensors Atf6, Ire1α, Perk, their downstream effectors Grp78/BiP and eIF2α in ERG transgenic mouse prostate glands indicate the presence of chronic ER stress. Transient activation of apoptotic cell death during early age correlated well with the differential regulation of ER stress sensors, in particular Perk. Epithelial cells derived from ERG transgenic mouse prostates have increased prostasphere formation with resistance to radiation induced cell death. Continued activation of cell survival factors, Atf6 and Ire1α during chronic ER stress due to presence of ERG in prostate epithelium induces survival pathways and provides a selection pressure in the continuum of ERG dependent neoplastic process. These novel insights will enhance the understanding of the mechanistic functions of ERG in prostate tumor biology and towards development of early targeted therapeutic strategies for prostate cancer.