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The Allier River and its alluvial aquifer constitute a shallow but highly productive water resource due to their hydrodynamic properties. This hydrosystem provides almost all of the water requirements for domestic supply and irrigation. Recent dry summers (such as those in 2015, 2019, and 2022) and the lack of winter recharge have led managers to question the sustainability of this resource. We proposed the use of hydrological modelling with Gardenia with which the water balance can be determined at the watershed scale (7020 km2) and with which forecasting simulations can be performed for 2030–2070. Thus, this work was divided into (1) model calibration (2000–2020), (2) the determination of the main drivers of the water balance (2000–2020), (3) and river flow and groundwater level simulation (2030–2070). For the latter, Gardenia was used considering a “better case”, using the RCM Aladin63 in RCP2.6, and considering a “worst case”, using the RCM RegCM4-6 in RCP8.5. The calibration for 2000–2014 showed good reproducibility of river flows (NSE = 0.91) and groundwater levels (NSE = 0.85). The model showed that the major drivers in 2000–2020 were actual evapotranspiration and effective precipitation, which, respectively, represented 68% and 32% of mean annual precipitation. Water withdrawals did not significantly contribute to the water balance with the exception of those in very dry summers, such as those in 2003, 2005, 2015, and 2019. Climate appeared, therefore, as a prevalent factor of the Allier hydrosystem functioning compared to global withdrawals except for that during these dry years. Prospective simulations showed a decline in annual river flows and groundwater levels by a maximum of −15% and −0.08 m asl (“worst case”), respectively. These simulations showed that the Allier hydrosystem will be able to meet the water needs for various uses until 2070. In detail, it is likely that summer shortages will no longer be compensated by the Naussac Dam if the hydrosystem faces more than two years of drought. In this case, water-saving solutions will have to be found. This study is, thus, a good example of the application of hydrological modelling to address management issues in such a hydrosystem.

Abstract A total of 34,749 pigs were used in two experiments to evaluate the effects of a postbiotic dried fermentation product (DFP) administered through drinking water on nursery pig growth performance, antibiotic injection frequency, morbidity, mortality, fecal consistency, and characterization of fecal Escherichia coli. The DFP is composed of bioactive molecules derived from Lactococcus lactis. In Exp. 1, 350 barrows (DNA Line 200 × 400; initial body weight [BW] 6.1 ± 0.01 kg) were used in a 42-d study with five pigs per pen and 35 pens per treatment. The DFP was supplied for 14 d at a target dosage of 24 mg/kg BW using a water medicator at a 1:128 dilution. On days 7 and 14, fecal samples were collected for dry matter (DM) and to determine, by a multiplex polymerase chain reaction (PCR) assay, prevalence of 11 virulence genes characteristic of E. coli pathotypes. There was no evidence (P > 0.10) for differences for growth, incidence of diarrhea, number of antibiotic injections, removals, or fecal DM. On both fecal collection days, E. coli virulence genes were present with day 7 samples positive for genes that encode for hemolysins (hlyA, exhA), intimin (eae), and enteroaggregative heat-stable enterotoxin (astA). Prevalence of enterotoxin genes (elt, estA, estB, astA) increased on day 14, but DFP had no effects on the prevalence of any of the virulence genes. A total of 32 out of 72 E. coli isolates were identified as enterotoxigenic pathotype and all except one were from day 14 fecal samples. Fourteen isolates were positive for F4 fimbria and one isolate was positive for F4 and F18 fimbriae. In Exp. 2, 34,399 nursery pigs (initially 5.6 kg) were used in 20 nursery barns with 10 barns per treatment (control or DFP). The target dosage of the DFP for the first 14 d was 35 mg/kg BW. Following the 14-d supplementation period, pigs continued to be monitored for approximately 31 d. There was no evidence (P > 0.05) for the DFP to influence the overall percentage of pigs that died or growth performance. From days 0 to 14, providing the DFP reduced (P < 0.05) the percentage of pigs that were euthanized. However, providing the DFP increased (P < 0.05) the overall percentage of pigs that were euthanized and total mortality. For the number of antibiotic injections (treatment interventions), providing the DFP reduced the number of injections for the common period (P < 0.001) and overall (P = 0.002). These results indicate that the DFP did not influence growth performance but providing the DFP in Exp. 2 led to increased total nursery pig mortality. The use of a bacterial dried fermentation product provided in drinking water did not impact growth, decreased need for antibiotic injections, but increased mortality in nursery pigs. Lay Summary These experiments were designed to determine the effects of a dried fermentation product (DFP) produced from Lactococcus lactis provided in drinking water to nursery pigs on the growth, frequency of antibiotic injection, and mortality. The DFP is designed to interfere with Escherichia coli pathogenicity and decrease the apparent need for antibiotic administration. The first study was done at a research facility, where providing the DFP did not impact growth, mortalities, antibiotic injection criteria (count of antibiotic injections per pen and injection percentage), or prevalence of genes and types of pathogenic E. coli. The second study was conducted at commercial nurseries, where providing the DFP did not improve growth and increased the percentage of pigs euthanized posttreatment and overall. However, including the DFP for the first 14 d postweaning lowered the percentage of pigs euthanized from days 0 to 14, antibiotic injections per day from day 14 to the end of the nursery, and overall antibiotic injections per day.

Controlled human malaria infection (CHMI) provides a highly informative means to investigate host-pathogen interactions and enable in vivo proof-of-concept efficacy testing of new drugs and vaccines. However, unlike Plasmodium falciparum , well-characterized P . vivax parasites that are safe and suitable for use in modern CHMI models are limited. Here, 2 healthy malaria-naive United Kingdom adults with universal donor blood group were safely infected with a clone of P . vivax from Thailand by mosquito-bite CHMI. Parasitemia developed in both volunteers, and prior to treatment, each volunteer donated blood to produce a cryopreserved stabilate of infected RBCs. Following stringent safety screening, the parasite stabilate from one of these donors (PvW1) was thawed and used to inoculate 6 healthy malaria-naive United Kingdom adults by blood-stage CHMI, at 3 different dilutions. Parasitemia developed in all volunteers, who were then successfully drug treated. PvW1 parasite DNA was isolated and sequenced to produce a high-quality genome assembly by using a hybrid assembly method. We analyzed leading vaccine candidate antigens and multigene families, including the vivax interspersed repeat (VIR) genes, of which we identified 1145 in the PvW1 genome. Our genomic analysis will guide future assessment of candidate vaccines and drugs, as well as experimental medicine studies.

Functional music applications, from consumer focus and sleep aids to clinical interventions, share a distinctive recommendation problem: success is defined by the listener's affective state, but online experimentation on emotion is ethically constrained, particularly for clinical populations who cannot reliably skip a song or report distress. We describe AMRS, the Affective Music Recommendation System deployed on LUCID's health-and-wellness platforms, which serve clinical users (primarily older adults with neurocognitive conditions) and consumer-wellness users across energize, focus, calm, and sleep modes. AMRS is built around a rollout-based world model: a causal transformer trained on logged listening data to jointly predict engagement, binary rating, and self-reported valence and arousal. The world model serves both as an in-silico simulator for offline policy training and as a stress-testing tool before deployment. A recommender policy initialized by behaviour cloning is fine-tuned offline with Direct Preference Optimization (DPO) against a configurable multi-objective utility function. Under a strict cold-start protocol, the world model predicts both behavioural and affective signals with usable fidelity; DPO improves predicted valence and arousal over the cloned baseline while maintaining a similar diversity profile and avoiding the distributional collapse produced by greedy optimization. We position the work as an early deployed validation of a methodology for affective recommendation when online experimentation is ethically untenable.