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The present study investigates the production of highly charged ions (HCIs) through the novel application of antiprotonic atoms and explores their potential for studying atomic and nuclear structures. Utilizing the Geant4 simulation toolkit, comprehensive simulations were conducted for all known isotopes with atomic numbers below 100. These simulations recorded key parameters of the resulting nuclear fragments, including mass, momentum, charge, and yield. The results obtained from this study offer valuable insights into the mechanisms of HCI production and provide a foundation for planning and analyzing future experimental investigations. This work demonstrates the feasibility of using antiprotonic atoms to advance nuclear and atomic physics research.

At very low energies, a light neutral particle above a horizontal surface can experience quantum reflection. The quantum reflection holds the particle against gravity and leads to gravitational quantum states ( gqs ). So far, gqs were only observed with neutrons as pioneered by Nesvizhevsky and his collaborators at ill . However, the existence of gqs is predicted also for atoms. The Grasian collaboration pursues the first observation and studies of gqs of atomic hydrogen. We propose to use atoms in order to exploit the fact that orders of magnitude larger fluxes compared to those of neutrons are available. Moreover, recently the q - Bounce collaboration, performing gqs spectroscopy with neutrons, reported a discrepancy between theoretical calculations and experiment which deserves further investigations. For this purpose, we set up a cryogenic hydrogen beam at 6  K . We report on our preliminary results, characterizing the hydrogen beam with pulsed laser ionization diagnostics at 243  nm . Graphical abstract

We examine the possible existence of quadrupole resonances in exotic atoms containing odd-\\(A\\) nuclei. We find that the spin-flip of the de-exciting exotic particle can induce a resonance, altering the orbital angular momentum of the nucleus by one quanta. This process results in an excited nucleus with a suppression in x-ray photon emissions during the exotic atom cascade. We provide specific cases of antiprotonic atoms of stable elements where this resonance effect is expected to occur. The study of this phenomena may provide insight into the strong interaction of deeply bound antiprotonic states in the proximity of the unpaired nucleon, and serve as a tool for probing short-lived excited nuclear states.

Imbalances in electrolyte concentrations can have severe consequences, but accurate and accessible measurements could improve patient outcomes. The current measurement method based on blood tests is accurate but invasive and time-consuming and is often unavailable for example in remote locations or an ambulance setting. In this paper, we explore the use of deep neural networks (DNNs) for regression tasks to accurately predict continuous electrolyte concentrations from electrocardiograms (ECGs), a quick and widely adopted tool. We analyze our DNN models on a novel dataset of over 290,000 ECGs across four major electrolytes and compare their performance with traditional machine learning models. For improved understanding, we also study the full spectrum from continuous predictions to a binary classification of extreme concentration levels. Finally, we investigate probabilistic regression approaches and explore uncertainty estimates for enhanced clinical usefulness. Our results show that DNNs outperform traditional models but model performance varies significantly across different electrolytes. While discretization leads to good classification performance, it does not address the original problem of continuous concentration level prediction. Probabilistic regression has practical potential, but our uncertainty estimates are not perfectly calibrated. Our study is therefore a first step towards developing an accurate and reliable ECG-based method for electrolyte concentration level prediction—a method with high potential impact within multiple clinical scenarios.

Forests are of major importance to human society, contributing several crucial ecosystem services. Biodiversity is suggested to positively influence multiple services but evidence from natural systems at scales relevant to management is scarce. Here, across a scale of 400,000 km 2 , we report that tree species richness in production forests shows positive to positively hump-shaped relationships with multiple ecosystem services. These include production of tree biomass, soil carbon storage, berry production and game production potential. For example, biomass production was approximately 50% greater with five than with one tree species. In addition, we show positive relationships between tree species richness and proxies for other biodiversity components. Importantly, no single tree species was able to promote all services, and some services were negatively correlated to each other. Management of production forests will therefore benefit from considering multiple tree species to sustain the full range of benefits that the society obtains from forests. Tree diversity is thought to benefit forest ecosystems, but evidence from large-scale studies is scarce. This study of a 400,000 km 2 forest area shows that higher tree species richness supports higher levels of multiple ecosystem services, and therefore also a more sustainable management of production forests.

We have prospectively studied wheezing disorder and allergy in 47 children hospitalized with respiratory syncytial virus (RSV) bronchiolitis in infancy and 93 matched control subjects. Subjects with at least three episodes of wheezing were defined as recurrent wheezers and as having asthma if the episodes were doctor verified. Here we report the outcome at age 13 years in 46/47 children with RSV and 92/93 control subjects. Wheezing disorder and clinical allergy were estimated using a questionnaire. Skin prick tests were performed and serum IgE antibodies measured. Spirometry was undertaken at rest, after dry air challenge, and after beta2-agonist inhalation. The occurrence of symptoms over the previous 12 months was significantly higher in the RSV group than among the control subjects, 43% versus 8% for asthma/recurrent wheezing and 39% versus 15% for allergic rhinoconjunctivitis. Sensitization to common inhaled allergens was more frequent in the RSV group than in the control subjects, judged by skin prick tests (50% versus 28%; p = 0.022), or by serum IgE antibodies (45% versus 26%; p = 0.038). Compared with the control subjects, the RSV group showed mild airway obstruction both at rest and after bronchodilation, and had slightly more reactive airways. RSV bronchiolitis in infancy severe enough to cause hospitalization is a risk factor for allergic asthma in early adolescence.

Eutrophication of the Baltic Sea has potentially increased the frequency and magnitude of cyanobacteria blooms. Eutrophication leads to increased sedimentation of organic material, increasing the extent of anoxic bottoms and subsequently increasing the internal phosphorus loading. In addition, the hypoxic water volume displays a negative relationship with the total dissolved inorganic nitrogen pool, suggesting greater overall nitrogen removal with increased hypoxia. Enhanced internal loading of phosphorus and the removal of dissolved inorganic nitrogen leads to lower nitrogen to phosphorus ratios, which are one of the main factors promoting nitrogen-fixing cyanobacteria blooms. Because cyanobacteria blooms in the open waters of the Baltic Sea seem to be strongly regulated by internal processes, the effects of external nutrient reductions are scale-dependent. During longer time scales, reductions in external phosphorus load may reduce cyanobacteria blooms; however, on shorter time scales the internal phosphorus loading can counteract external phosphorus reductions. The coupled processes inducing internal loading, nitrogen removal, and the prevalence of nitrogen-fixing cyanobacteria can qualitatively be described as a potentially self-sustaining “vicious circle.” To effectively reduce cyanobacteria blooms and overall signs of eutrophication, reductions in both nitrogen and phosphorus external loads appear essential.

Two cDNA libraries were prepared, one from leaves of a field-grown aspen (Populus tremula) tree, harvested just before any visible sign of leaf senescence in the autumn, and one from young but fully expanded leaves of greenhouse-grown aspen (Populus tremula X tremuloides). Expressed sequence tags (ESTs; 5,128 and 4,841, respectively) were obtained from the two libraries. A semiautomatic method of annotation and functional classification of the ESTs, according to a modified Munich Institute of Protein Sequences classification scheme, was developed, utilizing information from three different databases. The patterns of gene expression in the two libraries were strikingly different. In the autumn leaf library, ESTs encoding metallothionein, early light-inducible proteins, and cysteine proteases were most abundant. Clones encoding other proteases and proteins involved in respiration and breakdown of lipids and pigments, as well as stress-related genes, were also well represented. We identified homologs to many known senescence-associated genes, as well as seven different genes encoding cysteine proteases, two encoding aspartic proteases, five encoding metallothioneins, and 35 additional genes that were up-regulated in autumn leaves. We also indirectly estimated the rate of plastid protein synthesis in the autumn leaves to be less that 10% of that in young leaves.

Multiple Sclerosis (MS) is a heterogeneous inflammatory and neurodegenerative disease with an unpredictable course towards progressive disability. Treating progressive MS is challenging due to limited insights into the underlying mechanisms. We examined the molecular changes associated with primary progressive MS (PPMS) using a cross-tissue (blood and post-mortem brain) and multilayered data (genetic, epigenetic, transcriptomic) from independent cohorts. In PPMS, we found hypermethylation of the 1q21.1 locus, controlled by PPMS-specific genetic variations and influencing the expression of proximal genes ( CHD1L , PRKAB2 ) in the brain. Evidence from reporter assay and CRISPR/dCas9 experiments supports a causal link between methylation and expression and correlation network analysis further implicates these genes in PPMS brain processes. Knock-down of CHD1L in human iPSC-derived neurons and knock-out of chd1l in zebrafish led to developmental and functional deficits of neurons. Thus, several lines of evidence suggest a distinct genetic-epigenetic-transcriptional interplay in the 1q21.1 locus potentially contributing to PPMS pathogenesis. This study identifies distinct genetic-epigenetictranscriptional interplay at the 1q21.1 locus in relation to neuronal deficits in primary progressive multiple sclerosis (PPMS).