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The study explores the effectiveness of raising prosodic awareness in teaching academic presentations to a mixed proficiency group of adult Polish students majoring in English from the perspective of prosody as well as utterance fluency measures. A 15-week course included a 4-week prosody practice with focus on pausing and pitch accent. In the course students produced two speeches of approximately the same length: an impromptu before the practice and a prepared presentation after the practice. The speeches were recorded and analysed for the number of pitch accents and pauses. The data for three students, representing different general L2 proficiency levels are discussed in this paper. The results of prosodic performance operationalized as the pause to pitch accent ratio show the greatest benefit of prosody training in the case of the lowest proficiency level student. The analysis of selected utterance fluency measures shows a positive effect of prosody practice across speakers, providing additional support for the relevance of pitch accent in academic presentations in L2. The study has theoretical and practical implications, as it suggests the need to include pitch accent/pause proportion in utterance fluency measures in fluency studies as well as in pedagogical practice.

Abstract Attribute inference—the process of analyzing publicly available data in order to uncover hidden information—has become a major threat to privacy, given the recent technological leap in machine learning. One way to tackle this threat is to strategically modify one’s publicly available data in order to keep one’s private information hidden from attribute inference. We evaluate people’s ability to perform this task, and compare it against algorithms designed for this purpose. We focus on three attributes: the gender of the author of a piece of text, the country in which a set of photos was taken, and the link missing from a social network. For each of these attributes, we find that people’s effectiveness is inferior to that of AI, especially when it comes to hiding the attribute in question. Moreover, when people are asked to modify the publicly available information in order to hide these attributes, they are less likely to make high-impact modifications compared to AI. This suggests that people are unable to recognize the aspects of the data that are critical to an inference algorithm. Taken together, our findings highlight the limitations of relying on human intuition to protect privacy in the age of AI, and emphasize the need for algorithmic support to protect private information from attribute inference.

IntroductionRecent work on bats flying over long distances has revealed that single hippocampal cells have multiple place fields of different sizes. At the network level, a multi-scale, multi-field place cell code outperforms classical single-scale, single-field place codes, yet the performance boundaries of such a code remain an open question. In particular, it is unknown how general multi-field codes compare to a highly regular grid code, in which cells form distinct modules with different scales.MethodsIn this work, we address the coding properties of theoretical spatial coding models with rigorous analyses of comprehensive simulations. Starting from a multi-scale, multi-field network, we performed evolutionary optimization. The resulting multi-field networks sometimes retained the multi-scale property at the single-cell level but most often converged to a single scale, with all place fields in a given cell having the same size. We compared the results against a single-scale single-field code and a one-dimensional grid code, focusing on two main characteristics: the performance of the code itself and the dynamics of the network generating it.ResultsOur simulation experiments revealed that, under normal conditions, a regular grid code outperforms all other codes with respect to decoding accuracy, achieving a given precision with fewer neurons and fields. In contrast, multi-field codes are more robust against noise and lesions, such as random drop-out of neurons, given that the significantly higher number of fields provides redundancy. Contrary to our expectations, the network dynamics of all models, from the original multi-scale models before optimization to the multi-field models that resulted from optimization, did not maintain activity bumps at their original locations when a position-specific external input was removed.DiscussionOptimized multi-field codes appear to strike a compromise between a place code and a grid code that reflects a trade-off between accurate positional encoding and robustness. Surprisingly, the recurrent neural network models we implemented and optimized for either multi- or single-scale, multi-field codes did not intrinsically produce a persistent “memory” of attractor states. These models, therefore, were not continuous attractor networks.

Microplastic pollution is a pervasive issue, with remarkably high concentrations observed even in the most remote locations such as Arctic sea ice and snow. The reason for such large microplastic abundances in sea ice is still speculative and applies mainly to saline or freshwater conditions. In this study, we investigated seasonal ice core samples collected in March 2021 from the northern Baltic Sea (Gulf of Bothnia) for their microplastic distributions. The Baltic Sea is characterized by low salinity and can be ice-covered for up to six months annually. Microplastics were analyzed in the melted ice samples using an adsorption technique and Raman microscopy to identify their abundances, colors, shapes, and sizes to calculate their masses. Due to the strong dynamic of the ice layer and the repeated melting and freezing processes during the ice formation, no discernible trends in microplastic abundances, masses, or polymer types were observed throughout the ice core length. The average microplastic abundance (±SD) in the Baltic Sea ice was determined to be 22.3 ± 8.6 N L−1, with 64.9% of the particles exhibiting a particulate shape and 35.1% having a fibrous shape. The most prevalent polymer type was polyethylene terephthalate (PET), accounting for 44.4% of all polymers. This is likely due to the high proportion of PET fibers (93.8%). The majority of particle-shaped microplastics were identified as polyethylene (PE; 37.2%), followed by PET (17.2%), polyvinyl chloride (PVC; 15.9%), and polypropylene (PP; 15.9%). No correlations were found between microplastic concentrations and proximity to land, cities, industries, or rivers, except for PP mass concentrations and particle sizes, which correlated with distances to industries in Luleå, Sweden.

Endocrine disrupting compounds and in particular estrogenic substances have the ability to interact with the hormone system of organisms. Among them are not only synthetic but also natural substances that potentially stress the aquatic ecosystem. High human population densities such as around the Pearl River Estuary (PRE) are suspected of exerting significant anthropogenic pressure onto coastal areas. In this study, natural and synthetic estrogens as well as estrogen-like substances derived from plants and fungi were investigated in the PRE and at the adjacent northern shelf of the South China Sea. Maximum concentration of 3.6 ng L−1 for estrone (E1), 0.7 ng L−1 for 17α-ethinylestradiol (EE2), 12.9 ng L−1 for genistein (GEN), 11.9 ng L−1 for daidzein (DAI) and 1.9 ng L−1 for zearalenone (ZEN) were observed. While E1 and EE2 were detected in fresh and saltwater samples, GEN, DAI and ZEN were observed only at freshwater sampling sites. During the investigations, the analysis of 17β-estradiol (E2) and EE2 indicated a strong matrix dependence. Additionally, an estrogen screen observation showed estrogenic activity in form of estradiol equivalent quotients up to 0.18 ng L−1.

Abstract Nations worldwide are mobilizing to harness the power of Artificial Intelligence (AI) given its massive potential to shape global competitiveness over the coming decades. Using a dataset of 2.2 million AI papers, we study inter-city citations, collaborations, and talent migrations to uncover dependencies between Eastern and Western cities worldwide. Beijing emerges as a clear outlier, as it has been the most impactful city since 2007, the most productive since 2002, and the one housing the largest number of AI scientists since 1995. Our analysis also reveals that Western cities cite each other far more frequently than expected by chance, East–East collaborations are far more common than East–West or West–West collaborations, and migration of AI scientists mostly takes place from one Eastern city to another. We then propose a measure that quantifies each city’s role in bridging East and West. Beijing’s role surpasses that of all other cities combined, making it the central gateway through which knowledge and talent flow from one side to the other. We also track the center of mass of AI research by weighing each city’s geographic location by its impact, productivity, and AI workforce. The center of mass has moved thousands of kilometers eastward over the past three decades, with Beijing’s pull increasing each year. These findings highlight the eastward shift in the tides of global AI research, and the growing role of the Chinese capital as a hub connecting researchers across the globe.

Abstract As the COVID-19 pandemic has demonstrated, identifying the origin of a pandemic remains a challenging task. The search for patient zero may benefit from the widely-used and well-established toolkit of contact tracing methods, although this possibility has not been explored to date. We fill this gap by investigating the prospect of performing the source detection task as part of the contact tracing process, i.e., the possibility of tuning the parameters of the process in order to pinpoint the origin of the infection. To this end, we perform simulations on temporal networks using a recent diffusion model that recreates the dynamics of the COVID-19 pandemic. We find that increasing the budget for contact tracing beyond a certain threshold can significantly improve the identification of infected individuals but has diminishing returns in terms of source detection. Moreover, disease variants of higher infectivity make it easier to find the source but harder to identify infected individuals. Finally, we unravel a seemingly-intrinsic trade-off between the use of contact tracing to either identify infected nodes or detect the source of infection. This trade-off suggests that focusing on the identification of patient zero may come at the expense of identifying infected individuals.

W szeroko rozumianym obszarze „pracy z ludźmi” superwizja jest jedną z podstawowych form uczenia się i rozwoju zawodowego. W jej ramach można również umieścić badania naukowe – przede wszystkim te prowadzone w terenie i oparte na interakcjach z badanymi. Kwestia krytycznej refleksji nad podejmowanymi przez badaczki i badaczy działaniami, nad ich postawami oraz relacjami z osobami badanymi, nad dylematami etycznymi, a także nad rozwojem umiejętności postępowania z (często dotkniętym cierpieniem) Innym jest szczególnie znacząca w socjologii, naukowej refleksji nad pracą socjalną, antropologii czy pedagogice, czyli dziedzinach bazujących w istotnej części na badaniach jakościowych. Celem artykułu jest przedstawienie podstawowych zagadnień związanych z pojawiającymi się ostatnio postulatami wprowadzenia superwizji w obszar społecznych badań jakościowych. Przedstawiono w nim krótko uwagi na temat superwizji w kontekście uwarunkowań pracy naukowej we współczesnej akademii, a następnie rozważono problem podatności badaczek i badaczy na zranienie i wskazano możliwe funkcje przeznaczonej dla nich superwizji. W ostatniej części tekstu odniesiono się do kwestii terminologicznych dotyczących pojęciowego zakreślenia granic superwizji dla badaczy, oddzielenia jej od superwizji klinicznej czy też promotorstwa i opieki naukowej, także określanych jako superwizja, ukazując skrótowo, jak superwizja badawcza opisywana jest w ostatnich latach w literaturze obcojęzycznej.

Abstract Lewy-body pathology with aggregation of abnormal conformations of the protein alpha-synuclein (α-Syn) represent the histopathological hallmarks of Parkinson’s disease (PD). Genetic prototypes such as PD due to mutations in the alpha-synuclein gene (SNCA) offer the opportunity to evaluate α-Syn-related profiles in patient-derived biomaterial. We identified a family with a SNCA triplication and assessed the index patient for CSF α-Syn seeding capacity and levels of total α-Syn along with other neurodegenerative CSF markers (Aβ1-42, total-Tau, phospho-Tau, NFL). As no published CSF data in patients with SNCA triplication are available, we descriptively compared his CSF profiles to those of sporadic PD patients and PD patients with GBA mutations as these are also specifically associated with prominent α-Syn pathology. Additionally, skin biopsies with staining for phospho-α-Syn were done. To assess cerebral glucose metabolism and brain atrophy combined positron emission tomography and magnetic resonance imaging ([18F]FDG-PET/MRI) was performed. Age at onset was 24 years and motor impairment was accompanied by prominent non-motor symptoms with early development of dementia, depression, REM sleep behavior disorder, hyposmia, and dysautonomia. Correspondingly, PET-MRI showed hypometabolism and atrophy in frontal, temporoparietal and occipital regions. CSF levels of total α-Syn were threefold higher and RT-QuIC showed remarkable α-Syn seeding activity in all kinetic categories in the SNCATriplication patient compared to patients with GBA mutations. Our results are consistent with findings that not only mutant forms but also overexpression of the wild-type α-Syn protein lead to PD and PD dementia and show a striking CSF α-Syn seeding profile, thus substantiating the role of RT-QuIC as a specific in vivo biomarker of α-Syn brain pathology.

Sinking particles were studied by analyzing samples collected in a sediment trap at 180 m depth in the Gotland Basin, eastern Baltic Sea between 1999 and 2020. The aim of this study was to determine the temporal variability of the particle flux and its components and how their changes are linked to phytoplankton blooms. The variables studied included total particle flux, particulate organic carbon and nitrogen, biogenic silica, C:N ratio and the isotopic composition of organic carbon and nitrogen. The total particle flux and its components reached maximum values in 2003, 2012 and 2015. Long-term means over the 22-year period of the total particle flux and its components particulate organic carbon and nitrogen, biogenic silica were estimated at around 152, 22, 3 and 8 mg m−2 d−1, respectively. The C:N ratio and the isotopic composition of organic carbon and nitrogen showed high variability around their long-term means of 9, -25‰ and 4‰, respectively. The annual variability of the components of the flux particulate organic carbon (3–65 mg m−2 d−1), particulate organic nitrogen (0.4–9 mg m−2 d−1) and biogenic silica (1–24 mg m−2 d−1) exhibited the same general pattern as the total particle flux (11–450 mg m−2 d−1) over the study period. On the seasonal scale, sinking material in summer contributed roughly one-third (31%) to the total particle flux, followed by winter (27%), spring (24%) and autumn (19%). The highest particle flux occurred mostly in April, July and November, during and after the appearance of phytoplankton blooms in the Gotland Basin. The phytoplankton community changed from silicon-rich species to nitrogen-fixing cyanobacteria, indicating a shift in nitrogen sources from nitrate-based to N2-based over the year. The spring bloom, dominated by diatoms, was characterized by a lighter carbon and heavier nitrogen isotopic composition, while the summer bloom, mainly of diazotrophic cyanobacteria, was characterized in contrary by heavier carbon and lighter nitrogen isotopes. Although no trend was found in the data, the variability observed in the sinking material was related to the changes over time in the phytoplankton community in the Gotland Basin. The findings of this study provide new and valuable information for our understanding of the temporal variability of sinking material linked to the development of phytoplankton blooms and nutrient sources in the Gotland Basin, and underscore the importance of continued monitoring to understand the potential impacts of environmental changes on this fragile ecosystem.

This paper investigates new strategies of cultural interpretation of literary texts in order to probe depths of meaning with which the blank spaces can be filled in. Either a semiotic or a semantic approach can reveal various facets of a cultural product. The text refers to something, to a reality that is recreated, and projected into a fictional reality. The narrative acts as an attempt to shape a world after the resemblance of the real one. The temporal background of human experience always offers an intrigue for the complex interplay between the indirect reference to the past and the shaping reference to fiction. The essential step in the exploration of textual semantics can be achieved through multiple readings. The concept of how the reader understands the texts of artistic literature is a synthesis of learning theories in psychology and text theories in semiotics, pragmatics, and linguistics of the twenty first century and subsumes the stated intention to study interpretation as a complex process. The issue of the subjective dimension of understanding was addressed in the sequence devoted to reading literary texts justified by the different profile of readers specified in different cognitive structures, affective structures, and reading intentions. The personal character of reception is highlighted in the case of comprehension and interpretation of literary texts, whose structure creates spaces, manifestation of subjectivity, and type of text that places readers with different profiles. Outlined from the perspective of these demands, the literature lecture should be a space for initiation in reading and culture, and a space for intellectual debates and critical thinking. [ABSTRACT FROM AUTHOR]

Abstract The clinicopathological heterogeneity in Lewy-body diseases (LBD) highlights the need for pathology-driven biomarkers in-vivo. Misfolded alpha-synuclein (α-Syn) is a lead candidate based on its crucial role in disease pathophysiology. Real-time quaking-induced conversion (RT-QuIC) analysis of CSF has recently shown high sensitivity and specificity for the detection of misfolded α-Syn in patients with Parkinson's disease (PD) and dementia with Lewy bodies (DLB). In this study we performed the CSF RT-QuIC assay in 236 PD and 49 DLB patients enriched for different genetic forms with mutations in GBA, parkin, PINK1, DJ1, and LRRK2. A subgroup of 100 PD patients was also analysed longitudinally. We correlated kinetic seeding parameters of RT-QuIC with genetic status and CSF protein levels of molecular pathways linked to α-Syn proteostasis. Overall, 85% of PD and 86% of DLB patients showed positive RT-QuIC α-Syn seeding activity. Seeding profiles were significantly associated with mutation status across the spectrum of genetic LBD. In PD patients, we detected positive α-Syn seeding in 93% of patients carrying severe GBA mutations, in 78% with LRRK2 mutations, in 59% carrying heterozygous mutations in recessive genes, and in none of those with bi-allelic mutations in recessive genes. Among PD patients, those with severe GBA mutations showed the highest seeding activity based on RT-QuIC kinetic parameters and the highest proportion of samples with 4 out of 4 positive replicates. In DLB patients, 100% with GBA mutations showed positive α-Syn seeding compared to 79% of wildtype DLB. Moreover, we found an association between α-Syn seeding activity and reduced CSF levels of proteins linked to α-Syn proteostasis, specifically lysosome-associated membrane glycoprotein 2 and neurosecretory protein VGF. These findings highlight the value of α-Syn seeding activity as an in-vivo marker of Lewy-body pathology and support its use for patient stratification in clinical trials targeting α-Syn.

Abstract Disinformation continues to raise concerns due to its increasing threat to society. Nevertheless, a threat of a disinformation-based attack on critical infrastructure is often overlooked. Here, we consider urban traffic networks and focus on fake information that manipulates drivers’ decisions to create congestion at a city scale. Specifically, we consider two complementary scenarios, one where drivers are persuaded to move towards a given location, and another where they are persuaded to move away from it. We study the optimization problem faced by the adversary when choosing which streets to target to maximize disruption. We prove that finding an optimal solution is computationally intractable, implying that the adversary has no choice but to settle for suboptimal heuristics. We analyze one such heuristic, and compare the cases when targets are spread across the city of Chicago vs. concentrated in its business district. Surprisingly, the latter results in more far-reaching disruption, with its impact felt as far as 2 km from the closest target. Our findings demonstrate that vulnerabilities in critical infrastructure may arise not only from hardware and software, but also from behavioral manipulation.

A high-quality hydrographic CTD and Argo float data was used to study the property changes along the westward branch of the Mediterranean Outflow Water (MOW) in the northeast Atlantic between 1981 and 2018. In this period, the temperature and salinity are marked by periods of cooling/freshening and warming/salinification. Since 1981, the MOW properties at the core decreased by −0.015 ± 0.07 °C year−1 and −0.003 ± 0.002 year−1. The different phases of the North Atlantic Oscillation (NAO) influence the main propagation pathways of the MOW into the North Atlantic basin, thus affecting the trends determined within different NAO-phases. The temperature and salinity show a strong correlation with NAO, with NAO leading the properties by 8 and 7 years, respectively, indicating a delayed response of the ocean to different forcing conditions. A decrease in oxygen concentration (−0.426 ± 0.276 μmol kg−1 year−1) was calculated for the same period; however, no connection with the NAO was found.

Changes in environmental conditions may have an effect on the occurrence and intensity of phytoplankton blooms. However, few studies have been carried out on this subject, mainly due to the lack of long-term in situ observations. We study the inter-annual variability and phenology of spring and summer blooms in the eastern Baltic Sea using a physical-biological model. The one-dimensional NPZD model simulates the development of both blooms in the water column with realistic atmospheric forcing and initial conditions representative of the eastern Baltic Sea between 1990 and 2019. On average, the spring bloom started on day 85 ± 7, reached its maximum biomass on day 115 ± 6 and declined after day 144 ± 5. The summer bloom started on day 158 ± 5, had its maximum biomass on day 194 ± 9 and ended after day 237 ± 8. The results showed that the summer bloom occurs 9 days earlier and last 15 days longer over the 30-year simulation period, but changes in the phenology of the spring bloom were not statistically significant. There is strong evidence that warmer periods favor both blooms, but in different ways. Warmer periods caused spring blooms to peak earlier, while summer blooms reached higher abundance. Additionally, a higher energy gain by the ocean led to longer summer blooms of greater abundance and higher biomass maxima. Overall, summer blooms are more sensitive to changes in the environment than spring blooms, being therefore more vulnerable to changes generated by climate change in the Baltic Sea.

The northern shelf and off-shelf regions of the South China Sea (SCS) present a stark contrast between being eutrophic from terrestrial runoffs of nutrients and biota and being oligotrophic with multiple nutrient limitations due to the distance to land sources and stable permanent stratification. The abundance, size, and trophic structures of plankton in the shelf and off-shelf regions were studied in a joint Sino-German cruise conducted between September 1 and 24, 2018. A laser optical plankton counter was mounted on a water sampler-CTD (conductivity–temperature–depth) system for studying the horizontal and vertical distributions of plankton structures in a size range between 0.1 and 35 mm and their relationships with hydrographic and biological features in the northern SCS and its shelf region. Results revealed the subsurface chlorophyll maximum layer (SCM) below the pycnocline and plankton aggregation near the SCM about a depth of 50–60 m. The distributions of small plankton between 0.1 and 0.5 mm were strongly correlated with stratification and SCM compared to those of large plankton. Analyzing the intercept and slope of a normalized biovolume spectrum (NBVS) as an indicator for abundance and size structure of a plankton community, results revealed that in the shelf region, the slopes exhibited no significant vertical variations in the water column regardless of stratification and SCM. In contrast, in the off-shelf stratified water column, the intercepts and slopes were lower and flatter in the surface layer, higher and steeper in the SCM layer, and the lowest and flattest in the deep layer. Stirring by the typhoon also altered both the abundances and size structures of the plankton communities, with significant regional differences. This study elucidates the variances of plankton abundances, distributions, NBVS slopes, and intercepts among different water column structures in both shelf and off-shelf regions of the northern SCS.

This study aimed to identify stable indicator contaminants of pharmaceuticals and personal care products (PPCPs) to trace the anthropogenic fingerprint of the Pearl River plume in the coastal waters of the northern South China Sea. 40 PPCPs were under investigation, of which 14 were detected along the Pearl River Estuary and 4 on the shelf of the northern South China Sea. Results show that caffeine, metoprolol, diclofenac, and carbamazepine can be utilized to detect the human impact. They are diluted along the Pearl River, as their concentrations decrease from low salinity towards high salinity. Sulfonamide antibiotics and trimethoprim are suitable to determine the veterinary and human impact. Their highest concentrations were detected along the river yet still in low saline water whereas, the origin of the organic UV-filter is diverse. Their source could not be precisely determined. Only caffeine, metoprolol, octocrylene, and PBSA were detected at the near-coastal stations in the South China Sea. They can be utilized as suitable indicators to detect an anthropogenic impact on the northern South China Sea. The detected concentrations are of low risk to organisms in the Pearl River and the northern South China Sea.

The Atlantic Meridional Overturning Circulation (AMOC) and its surface limb, the Gulf Stream, are in their weakest state since the last millennium. The consequences of this weakening in the Northeast Atlantic are not yet known. We show that the slowdown of the Gulf Stream in the 1960s, 1970s, and after 2000 may have caused a delayed weakening of the Azores Current. Concurrently, the Azores Front associated with the Azores Current migrated northward since the 1970s due to gradual changes in the Atlantic Multidecadal Oscillation and ocean heat content. We argue that the AMOC slowdown is also detectable in the low-energy region of the Northeast Atlantic and that the dynamics of Azores Current tightly connects to that of the dynamics of the Gulf Stream and AMOC on decadal and longer time scales.

Acculturation and language proficiency have been found to be inter-related both from the perspective of second language acquisition (Schumann, 1978, 1986) and socio-psychological adaptation in cross-cultural contacts (Ward, Bochner, & Furnham, 2001). However, the predictions as to the effect of a particular strategy on success differ, with assimilation believed to create most favourable conditions for SLA and integration for general well-being. The present study explores acculturation patterns in three expert users of English as a second language, recent Polish immigrants to the UK, in relation to their language experience. The qualitative data were collected with the use of a questionnaire and analysed with respect to language experience and socio-affective factors. The analysis aimed at better understanding of the relationship between language learning in a formal context and language use in a natural setting on the one hand and the relationship between language expertise and acculturation strategy choice on the other. The results show that in spite of individual differences, expert language users tend to adopt an assimilation rather than integration acculturation strategy. This may suggest that attitudes are related to expertise in English as a second language in a more conservative way than advocated by cross-cultural approaches.

BackgroundAn involvement of the central-nervous and peripheral, innate and adaptive immune system in the pathogenesis of Parkinson's disease (PD) is nowadays well established.ObjectivesWe face several open questions in preparation of clinical trials aiming at disease-modification by targeting the immune system: Do peripheral (blood) inflammatory profiles reflect central (CSF) inflammatory processes? Are blood/CSF inflammatory markers associated with CSF levels of neurodegenerative/PD-specific biomarkers?MethodsUsing a multiplex assay we assessed 41 inflammatory markers in CSF/serum pairs in 453 sporadic PD patients. We analyzed CSF/serum correlation as well as associations of inflammatory markers with clinical outcome measures (UPDRS-III, H&Y, MoCA) and with CSF levels of α-synuclein, Aβ1−42, t-Tau, p181-Tau and NFL. All analyses were stratified by sex as the immune system shows relevant sex-specific differences.ResultsCorrelations between CSF and serum were sparse and detected in only 25% (9 out of 36) of the analysable inflammatory markers in male PD patients and in only 38% (12 out of 32) of female PD patients. The most important pro-inflammatory mediators associated with motor and cognitive decline as well as with neurodegenerative/PD-specific biomarkers were FABP, ICAM-1, IL-8, MCP-1, MIP-1-beta, and SCF. Results were more robust for CSF than for serum.InterpretationLevels of central-nervous and peripheral inflammatory markers might be regulated independently of each other with CSF inflammatory markers reflecting CNS pathology more accurately than peripheral markers. These findings along with sex-specific characteristics have to be considered when designing clinical trials aiming at disease-modification by targeting the immune system.

Dissolved and particulate organic carbon (DOC, POC) and nitrogen (DON, PON) constitute essential nutrient and energy sources to heterotrophic microbes in aquatic systems. Especially in the shallow coastal ocean, the concentrations are highly variable on short timescales, and cycling is heavily affected by different sources and environmental drivers. We analyzed surface water organic carbon and nitrogen concentrations determined weekly from 2010 to 2020 in the nearshore southwestern Baltic Sea (Heiligendamm, Germany) in relation to physical, chemical and biological parameters available since 1988. Mixing of low-DOC North Sea water with high-DOC Baltic Sea water, as well as in situ primary production, were confirmed as the main drivers of organic carbon and nitrogen concentrations. Tight coupling between POC, PON, chlorophyll a and phytoplankton carbon with DON seasonal dynamics corroborated the close relationship between phytoplankton production and degradation of organic nutrients with preferential remineralization of nitrogen. Significant changes in air and water temperature, salinity, and inorganic nutrients over time indicated effects of climate change and improved water quality management in the eutrophic Baltic Sea. Bulk organic nutrient concentrations did not change over time, while the salinity-corrected fraction of the DOC increased by about 0.6 μmol L–1yr–1. Concurrently, chlorophyll a and Bacillariophyceae and Cryptophyceae carbon increased, denoting a potential link to primary productivity. The high variability of the shallow system exacerbates the detection of trends, but our results emphasize the value of these extended samplings to understand coupled biogeochemical cycling of organic matter fractions and to detect trends in these important carbon reservoirs.