The present work extends the scope of prior studies through analysis, modelling and simulation of the As, Cd, Co, Cu, Fe Mn, Mo, Ni and Zn release from Gentoo (Pygoscelis papua) and Chinstrap (Pygoscelis antarcticus) penguin guano to the Southern Ocean seawater and to Antarctic snow meltwater. Laboratory experimental results have been modelled considering kinetic processes between water and guano using two element pools in the guano compartment; its application allows us to interpret behaviours and predict release concentrations of dissolved trace elements from guano which are potentially useful for incorporation as elements source into biogeochemical models applied in the Southern Ocean. Variations in quantities and release patterns depending on the type of guano and aqueous medium in contact have been identified. The release percentages from the guano to the aqueous medium, once the steady state has been reached, vary depending on the water medium and guano type in the ranges of 100-2.9 % for Mo; 91.5-68.6 % for Ni; 81.8-22.8 % As; 52.0-43.9 % Cu; 26.9-7.4 % Mn; 24.9-5.4 for Co; 4.4-3.2 % for Zn and 0.94-0.51 % for Fe. Considering a penguin population of 774,000 Gentoo and 8,000,000 Chinstrap, the estimated annual mass released to the both seawater and freshwater would be ≈18,500 kg for Cu, ≈1710 kg for Zn, ≈1944 kg for Fe, ≈1640 kg for Mn, ≈499 kg for As, ≈289 kg for Ni, ≈155 kg for Mo, ≈36.7 kg for Cd and ≈8.1 kg for Co. These contributions can be locally significant both in promoting phytoplankton growth and in their role as inhibitors of primary productivity.

Mismanagement of the nitrogen (N) fertilization in agriculture leads to low N use efficiency (NUE) and therefore pollution of waters and atmosphere due to NO3- leaching, and N2O and NH3 emissions. The use of N simulation models of the soil-plant system can help improve the N fertilizer management increasing NUE and decreasing N pollution issues. However, many N simulation models lack balance between complexity and uncertainty with the result that they are not applied in actual practice. The NITIRSOIL is a one-dimensional transient-state model with a monthly time step that aims at addressing this lack in the estimation of, mainly, dry matter yield (DMY), crop N uptake (Nupt), soil mineral N (Nmin), and NO3- leaching in agricultural fields. According to its global sensitivity analysis for horticulture, the NITIRSOIL simulations of the aforementioned outputs mostly depend on the critical N dilution curve, harvest index, dry matter fraction, potential fresh yield and nitrification coefficients. According to its validation for 35 nitrogen fertilization trials with 11 vegetables under semi-arid Mediterranean climate in Eastern Spain, the NITIRSOIL presents indices of agreement between 0.87 and 0.97 for the prediction of total dry matter, DMY, Nupt, NO3- leaching and soil Nmin at crop season end. Therefore, the NITIRSOIL model can be used in actual practice to improve the sustainability of the N management in, particularly horticulture, due to the balance it features between complexity and prediction uncertainty. For this aim, the NITRISOIL can be used either on its own, or in combination with \"Nmin\" on-site N fertilization recommendation methods, or even could be implemented as the calculation core of decision support systems.

BACKGROUND: This review aims to synthesise the literature on the efficacy, evolution, and challenges of implementing Clincian Decision Support Systems (CDSS) in the realm of mental health, addiction, and concurrent disorders.
METHODS: Following PRISMA guidelines, a systematic review and meta-analysis were performed. Searches conducted in databases such as MEDLINE, Embase, CINAHL, PsycINFO, and Web of Science through 25 May 2023, yielded 27,344 records. After necessary exclusions, 69 records were allocated for detailed synthesis. In the examination of patient outcomes with a focus on metrics such as therapeutic efficacy, patient satisfaction, and treatment acceptance, meta-analytic techniques were employed to synthesise data from randomised controlled trials.
RESULTS: A total of 69 studies were included, revealing a shift from knowledge-based models pre-2017 to a rise in data-driven models post-2017. The majority of models were found to be in Stage 2 or 4 of maturity. The meta-analysis showed an effect size of -0.11 for addiction-related outcomes and a stronger effect size of -0.50 for patient satisfaction and acceptance of CDSS.
CONCLUSIONS: The results indicate a shift from knowledge-based to data-driven CDSS approaches, aligned with advances in machine learning and big data. Although the immediate impact on addiction outcomes is modest, higher patient satisfaction suggests promise for wider CDSS use. Identified challenges include alert fatigue and opaque AI models.
CONCLUSIONS: CDSS shows promise in mental health and addiction treatment but requires a nuanced approach for effective and ethical implementation. The results emphasise the need for continued research to ensure optimised and equitable use in healthcare settings.

Epidemiological studies to better understand wheat blast (WB) spatial and temporal patterns were conducted in three field environments in Bolivia between 2019 and 2020. The temporal dynamics of wheat leaf blast (WLB) and spike blast (WSB) were best described by the logistic model compared to the Gompertz and exponential models. The non-linear logistic infection rates (rL) were higher under defined inoculation in experiments two and three than under undefined inoculation in experiment one, and they were also higher for WSB than for WLB. The onset of WLB began with a spatial cluster pattern according to autocorrelation analysis and Moran\'s Index (I) values, with higher severity and earlier onset for defined than for undefined inoculation until the last sampling time. The WSB onset did not start with a spatial cluster pattern; instead, it was detected later until the last sampling date across experiments, with higher severity and earlier onset for defined than for undefined inoculation. Maximum severity (Kmax) was 1.0 for WSB, and less than 1.0 for WLB. Aggregation of WLB and WSB was higher for defined than for undefined inoculation. The directionality of hotspot development was similar for both WLB and WSB, mainly occurring concentrically for defined inoculation. Our results show no evidence of synchronized development but suggest a temporal and spatial progression of disease symptoms on wheat leaves and spikes. Thus, we recommend that monitoring and management of WB should be considered during early growth stages of wheat planted in areas of high risk.

Phenological models for insect pests often rely on knowledge of thermal reaction norms. These may differ in shape depending on developmental thermal conditions (e.g. constant vs. fluctuating) and other factors such as life-stages. Here, we conducted an extensive comparative study of the thermal reaction norms for development and viability in the invasive fly, Drosophila suzukii, under constant and fluctuating thermal regimes. Flies, were submitted to 15 different constant temperatures (CT) ranging from 8 to 35 °C. We compared responses under CT with patterns observed under 15 different fluctuating temperature (FT) regimes. We tested several equations for thermal performance curves and compared various models to obtain thermal limits and degree-day estimations. To validate the model\'s predictions, the phenology was monitored in two artificial field-like conditions and two natural conditions in outdoor cages during spring and winter. Thermal reaction norm for viability from egg to pupa was broader than that from egg to adult. FT conditions yielded a broader thermal breadth for viability than CT, with a performance extended towards the colder side, consistent with our field observations in winter. Models resulting from both CT and FT conditions made accurate predictions of degree-day as long as the temperature remained within the linear part of the developmental rate curve. Under cold artificial and natural winter conditions, a model based on FT data made more accurate predictions. Model based on CT failed to predict adult\'s emergence in winter. We also document the first record of development and adult emergence throughout winter in D. suzukii. Population dynamics models in D. suzukii are all based on summer phenotype and CT. Accounting for variations between seasonal phenotypes, stages, and thermal conditions (CT vs. FT) could improve the predictive power of the models.

Artificial intelligence has revolutionized the field of protein structure prediction. However, with more powerful and complex software being developed, it is accessibility and ease of use rather than capability that is quickly becoming a limiting factor to end users. LazyAF is a Google Colaboratory-based pipeline which integrates the existing ColabFold BATCH software to streamline the process of medium-scale protein-protein interaction prediction. LazyAF was used to predict the interactome of the 76 proteins encoded on the broad-host-range multi-drug resistance plasmid RK2, demonstrating the ease and accessibility the pipeline provides.

Ixodes ricinus is the most medically relevant tick species in Europe because it transmits the pathogens that cause Lyme borreliosis and tick-borne encephalitis. Northern Spain represents the southernmost margin of its main European range and has the highest rate of Lyme borreliosis hospitalisations in the country. Currently, the environmental determinants of the spatiotemporal patterns of I. ricinus abundance remain unknown in this region and these may differ from drivers in highly favourable areas for the species in Europe. Therefore, our study aimed to understand the main factors modulating questing I. ricinus population dynamics to map abundance patterns in northern Spain. From 2012 to 2014, monthly/fortnightly samplings were conducted at 13 sites in two regions of northern Spain to estimate spatiotemporal variation in I. ricinus questing abundance. Local abundance of I. ricinus was modelled in relation to variation in local biotic and abiotic environmental conditions by constructing generalised linear mixed models with a zero-inflated negative binomial distribution for overdispersed data. The different developmental stages of I. ricinus were most active at different times of the year. Adults and nymphs showed a peak of abundance in spring, while questing larvae were more frequent in summer. The main determinants affecting the spatiotemporal abundance of the different stages were related to humidity and temperature. For adults and larvae, summer seemed to be the most influential period for their abundance, while for nymphs, winter conditions and those of the preceding months seemed to be determining factors. The highest abundances of nymphs and adults were predicted for the regions of northern Spain with the highest rate of Lyme borreliosis hospitalisations. Our models could be the basis on which to build more accurate predictive models to identify the spatiotemporal windows of greatest potential interaction between animals/humans and I. ricinus that may lead to the transmission of I. ricinus-borne pathogens.

Vaccination against COVID-19 was integral to controlling the pandemic that persisted with the continuous emergence of SARS-CoV-2 variants. Using a mathematical model describing SARS-CoV-2 within-host infection dynamics, we estimate differences in virus and immunity due to factors of infecting variant, age, and vaccination history (vaccination brand, number of doses and time since vaccination). We fit our model in a Bayesian framework to upper respiratory tract viral load measurements obtained from cases of Delta and Omicron infections in Singapore, of whom the majority only had one nasopharyngeal swab measurement. With this dataset, we are able to recreate similar trends in URT virus dynamics observed in past within-host modelling studies fitted to longitudinal patient data.We found that Omicron had higher R0,within values than Delta, indicating greater initial cell-to-cell spread of infection within the host. Moreover, heterogeneities in infection dynamics across patient subgroups could be recreated by fitting immunity-related parameters as vaccination history-specific, with or without age modification. Our model results are consistent with the notion of immunosenescence in SARS-CoV-2 infection in elderly individuals, and the issue of waning immunity with increased time since last vaccination. Lastly, vaccination was not found to subdue virus dynamics in Omicron infections as well as it had for Delta infections.This study provides insight into the influence of vaccine-elicited immunity on SARS-CoV-2 within-host dynamics, and the interplay between age and vaccination history. Furthermore, it demonstrates the need to disentangle host factors and changes in pathogen to discern factors influencing virus dynamics. Finally, this work demonstrates a way forward in the study of within-host virus dynamics, by use of viral load datasets including a large number of patients without repeated measurements.

BACKGROUND: Anaemia is a disease of public health importance with multi-causal pathways. Previous literature suggests the role of indoor air pollution (IAP) on haemoglobin levels, but this has been studied less due to logistic constraints. A high proportion of the population in developing countries, including India, still depends on unclean fuel, which exacerbates IAP. The objective was to study the association between anaemia and IAP among the older Indian adult population (≥ 45 years) as per gender.
METHODS: Our study analysed the nationally representative dataset of the Longitudinal Ageing Study in India (LASI 2017-18, Wave-1). We have documented the association of anaemia (outcome variable) with IAP (explanatory variable). To reduce the confounding effects of demographic and socioeconomic; health related and behavioural covariates; propensity score matching (PSM) was conducted. Nested multilevel regression modelling was conducted. States and union territories were categorised cross tabulated as low, middle and high as per anaemia and IAP exposure. P value < 0.05 was considered statistically significant. SATA version 17 was used for analysis.
RESULTS: More than half (52.52%) of the participants were exposed to IAP (male (53.55%) > female (51.63%)). The odds of having anaemia was significantly 1.19 times higher (AOR 1.19 (1.09-1.31)) among participants using unclean/ solid fuel. The adjusted odds were significantly higher among participants exposed to pollution-generating sources (AOR 1.30; 1.18-1.43), and household indoor smoking (AOR 1.17 (1.07-1.29). The odds of having anaemia were significantly higher (AOR 1.26; 1.15-1.38) among participants exposed to IAP, which was higher in males (AOR 1.36; 1.15-1.61) than females (AOR 1.21; 1.08-1.35). Empowered Action Group (EAG) states like Uttar Pradesh, Chhattisgarh, Madhya Pradesh, Bihar had both high anaemia and IAP exposure.
CONCLUSIONS: This study established the positive association of anaemia with indoor air pollution among older Indian adults through a nationally representative large dataset. The association was higher among men. Further research is recommended to understand detailed causation and to establish temporality. It is a high time to implement positive intervention nationally to decrease solid/ unclean fuel usage, vulnerable ventilation, indoor smoking, IAP and health hazards associated with these with more focused actions towards EAG states.

UNASSIGNED: Medulloblastoma (MB) is the most common malignant pediatric brain tumor, with 5-year survival rates > 70%. Cranial radiotherapy (CRT) to the whole brain, with posterior fossa boost (PFB), underpins treatment for non-infants; however, radiotherapeutic insult to the normal brain has deleterious consequences to neurocognitive and physical functioning, and causes accelerated aging/frailty. Approaches to ameliorate radiotherapy-induced late-effects are lacking and a paucity of appropriate model systems hinders their development.
UNASSIGNED: We have developed a clinically relevant in vivo model system that recapitulates the radiotherapy dose, targeting, and developmental stage of childhood medulloblastoma. Consistent with human regimens, age-equivalent (postnatal days 35-37) male C57Bl/6J mice received computerized tomography image-guided CRT (human-equivalent 37.5 Gy EQD2, n = 12) ± PFB (human-equivalent 48.7 Gy EQD2, n = 12), via the small animal radiation research platform and were longitudinally assessed for > 12 months.
UNASSIGNED: CRT was well tolerated, independent of PFB receipt. Compared to a sham-irradiated group (n = 12), irradiated mice were significantly frailer following irradiation (frailty index; P = .0002) and had reduced physical functioning; time to fall from a rotating rod (rotarod; P = .026) and grip strength (P = .006) were significantly lower. Neurocognitive deficits were consistent with childhood MB survivors; irradiated mice displayed significantly worse working memory (Y-maze; P = .009) and exhibited spatial memory deficits (Barnes maze; P = .029). Receipt of PFB did not induce a more severe late-effect profile.
UNASSIGNED: Our in vivo model mirrored childhood MB radiotherapy and recapitulated features observed in the late-effect profile of MB survivors. Our clinically relevant model will facilitate both the elucidation of novel/target mechanisms underpinning MB late effects and the development of novel interventions for their amelioration.