Miracle-dz/UniFAR-FTUs huggingface dataset:
Fascin-induced bundling protects actin filaments from disassembly by cofilin

Actin filament turnover plays a central role in shaping actin networks, yet the feedback mechanism between network architecture and filament assembly dynamics remains unclear. The activity of ADF/cofilin, the main protein family responsible for filament disassembly, has been mainly studied at the single filament level. Here, we report that fascin, by crosslinking filaments into bundles, strongly slows down filament disassembly by cofilin. We show that this is mainly due to a slower nucleation of the first cofilin clusters, which occurs up to 100-fold slower on large bundles compared to single filaments. In contrast, severing at cofilin cluster boundaries is unaffected by fascin bundling. After the nucleation of an initial cofilin cluster on a filament of a bundle, we observe the local removal of fascin. Surprisingly, the nucleation of cofilin clusters on adjacent filaments is highly enhanced, locally. We propose that this inter-filament cooperativity in cofilin binding arises from the local propagation of the cofilin-induced change in helicity from one filament to the other filaments of the bundle. Taken together, these observations reveal the molecular events explaining why, despite inter-filament cooperativity, fascin crosslinking protects actin filaments from cofilin-induced disassembly. These findings highlight the important role played by crosslinkers in organizing actin networks and modulating the activity of other regulatory proteins.
Genomic and metabolic plasticity drive alternative scenarios for adapting Pseudomonas putida to non-native substrate D-xylose

D-Xylose, a major constituent of plant biomass and second most abundant sugar on Earth, holds a considerable potential as a substrate for sustainable bio-production. Pseudomonas putida KT2440 is an attractive bacterial host for valorizing biogenic feedstocks but lacks a xylose utilization pathway. While several attempts to engineer P. putida for growth on xylose have been reported, a comprehensive understanding of xylose metabolism in this bacterium is lacking, hindering its further improvement and rational tailoring for specific biotechnological purposes. In this study, we elucidated the xylose metabolism in the genome-reduced P. putida strain, EM42, endowed with xylose isomerase pathway (xylAB) and transporter (xylE) from Escherichia coli and used the obtained knowledge in combination with adaptive laboratory evolution to accelerate the bacterium’s growth on the pentose sugar. Carbon flux analyses, targeted gene knock-outs, and in vitro enzyme assays portrayed xylose assimilation in P. putida and confirmed a partially cyclic upper xylose metabolism. Deletion of the local transcriptional regulator gene hexR de-repressed genes of several key catabolic enzymes and reduced the lag phase on xylose. Guided by metabolic modeling, we augmented P. putida with additional heterologous pentose phosphate pathway genes and subjected rationally prepared strains to adaptive laboratory evolution (ALE) on xylose. The descendants showed accelerated growth and reduced growth lag. Genomic and proteomic analysis of engineered and evolved mutants revealed the importance of a large genomic re-arrangement, transaldolase overexpression, and balancing gene expression in the synthetic xylABE operon. Importantly, omics analyses found that similar growth characteristics of two superior mutants were achieved through distinct evolutionary paths. This work provides a unique insight into how cell metabolism adjusts to a non-native substrate; it highlights the remarkable genomic and metabolic plasticity of P. putida and demonstrates the power of combining knowledge-driven engineering with ALE in generating desirable microbial phenotypes. Highlights Elucidated xylose catabolism via exogenous isomerase pathway in P. putida EM42. Deletion of transcriptional regulator HexR improved growth on xylose. Knowledge-guided interventions and adaptive evolution accelerated growth. Omics analyses of selected mutants highlighted the genomic and metabolic plasticity of P. putida. Two mutants with superior characteristics emerged from distinct evolutionary paths.
Multicore fiber optic imaging reveals that astrocyte calcium activity in the cerebral cortex is modulated by internal motivational state

Astrocytes are a direct target of neuromodulators and can influence neuronal activity on broad spatial and temporal scales through their close proximity to synapses. However, our knowledge about how astrocytes are functionally recruited during different animal behaviors and their diverse effects on the CNS remains limited. To enable measurement of astrocyte activity patterns in vivo during normative behaviors, we developed a high-resolution, long working distance, multi-core fiber optic imaging platform that allows visualization of cortical astrocyte calcium transients through a cranial window in freely moving mice. Using this platform, we defined the spatiotemporal dynamics of astrocytes during diverse behaviors, ranging from circadian fluctuations to novelty exploration, showing that astrocyte activity patterns are more variable and less synchronous than apparent in head-immobilized imaging conditions. Although the activity of astrocytes in visual cortex was highly synchronized during quiescence to arousal transitions, individual astrocytes often exhibited distinct thresholds and activity patterns during explorative behaviors, in accordance with their molecular diversity, allowing temporal sequencing across the astrocyte network. Imaging astrocyte activity during self-initiated behaviors revealed that noradrenergic and cholinergic systems act synergistically to recruit astrocytes during state transitions associated with arousal and attention, which was profoundly modulated by internal state. The distinct activity patterns exhibited by astrocytes in the cerebral cortex may provide a means to vary their neuromodulatory influence in response to different behaviors and internal states.
HepG2 cells with knockouts of CYP51A1, DHCR24 or SC5D from cholesterol synthesis accumulate sterols influencing distinct regulatory pathways

Sterol intermediates of cholesterol synthesis are largely dedicated to cholesterol. Here we assess how they influence downstream gene regulatory pathways by developing knockouts (KOs) for consecutive enzymes of cholesterol synthesis in human hepatoma HepG2 cells. The KO of CYP51, DHCR24, and SC5D led to the build-up of specific sterols. The shared differentially expressed genes accounted for only 9% with regards to steroid metabolism and proliferation control, with majority of pathways changed in just one KO. The CYP51 KO cells with highly elevated 24,25-dihydrolanosterol exhibited a significant increase in G2+M phase along with enhanced cancer and cell cycle pathways, likely driven by elevated LEF1 through modulation of WNT/NFKB signalling. In contrast, SC5D and DHCR24 KO cells with elevated lathosterol or desmosterol, slowed cell proliferation and promoted apoptosis with downregulated E2F, mitosis, cell cycle transition, and enriched HNF1A tumor suppressor. These findings demonstrate that sterols from cholesterol synthesis control distinct gene regulatory pathways, while only early sterols can promote cell proliferation.
AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination

An analysis of AlphaFold protein structure predictions shows that while in many cases the predictions are highly accurate, there are also many instances where the predicted structures or parts of predicted structures do not agree with experimentally resolved data. Therefore, care must be taken when using these predictions for informing structural hypotheses. Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.
Assessing the effect of zoo closure on the soundscape using multiple measures

The zoo soundscape has a number of important implications for animal welfare, management, and conservation. However, despite its importance, the zoo soundscape is yet to be examined in depth using multiple measures. Consistent human presence can influence the zoo soundscape. However, it is difficult to determine the specific impact of human presence, as visitors are usually present during the day when animals are active. The COVID-19 lockdown in 2020 provided a unique opportunity to study zoo soundscapes in the absence of visitors. We compared the sound environment during the 2020 closure period to a comparable open period in 2019 across three zoo aviaries, examining broad band frequency measures of sound pressure levels, sound pressure levels in defined frequency bands, and acoustic indices (Acoustic Complexity Index and Normalized Difference Soundscape Index) to describe the zoo soundscape. Acoustic indices have not, to our knowledge, previously been used in the zoo setting, although they may provide a useful metric to assess sound disturbance. Therefore, we also used this natural experiment to explore how successful these measures may be in assessing disturbances in captive environments. We found a significant effect of human presence on the sound environment; aviaries were generally quieter with less low frequency noise and with a greater proportion of biotic sound during the 2020 zoo closure period. We argue that NDSI could be a useful index for determining anthropogenic disturbance in zoos, although further information on how it is influenced by additional factors, such as human speech, would be beneficial. The use of multiple measures to assess the sound environment in zoos can provide additional information beyond ‘loudness’, such as frequencies where sound energy is concentrated and characteristics of the soundscape, which could be used to better target management and mitigation.
Music Affects State Anxiety and Brain Connectivity

Stress, anxiety, and depressive symptoms can be reduced by listening to music, but the underlying mechanisms remain unclear. To address this gap, we measured brain connectivity while participants listened to songs of different genres: ambient, pop, and metal. Additionally, affective ratings were obtained while participants (n = 30) listened to the six different songs, and subjective ratings of state anxiety were solicited at the terminus of each song. Electroencephalography (EEG) connectivity combining weighted Phase Lag Index and graph theory was utilised to document brain activity during listening. Repeated-measures ANOVA indicated that listening to more pleasant and less arousing songs was associated with lower self-reported state anxiety levels than songs rated unpleasant and highly arousing. Of interest, EEG alpha connectivity differed across two ambient songs, particularly in the frontal lobes, despite being from the same genre and rated as highly pleasant and low in arousal. We also observed a sex effect on EEG results, where female participants (n = 18) displayed stronger connectivity than male participants (n = 12). Combined, these results suggest that ambient songs reduce state anxiety but have divergent brain responses, possibly reflecting the complex nature of music listening, including sensory processing, emotion and cognition.
In silico identification of switching nodes in metabolic networks

Cells modulate their metabolism according to environmental conditions. A major challenge to better understand metabolic regulation is to identify, from the hundreds or thousands of molecules, the key metabolites where the re-orientation of fluxes occurs. Here, a method called ISIS (for In Silico Identification of Switches) is proposed to locate these nodes in a metabolic network, based on the analysis of a set of flux vectors (obtained e.g. by parsimonious flux balance analysis with different inputs). A metabolite is considered as a switch if the fluxes at this point are redirected in a different way when conditions change. The soundness of ISIS is shown with four case studies, using both core and genome-scale metabolic networks of Escherichia coli, Saccharomyces cerevisiae and the diatom Phaeodactylum tricornutum. Through these examples, we show that ISIS can identify hot-spots where fluxes are reoriented, some of these nodes corresponding to reporter metabolites identified with transcriptomic data. Additionally, switch metabolites are deeply involved in post-translational modification of proteins, showing their key role in cellular regulation. Finally, we show that Erythrose 4-phosphate is an important switch metabolite for mixotrophy in P. tricornutum, highlighting the (somehow overlooked) importance of this metabolite in the non-oxidative pentose phosphate pathway to orchestrate the flux variations between glycolysis, the Calvin cycle and the oxidative pentose phosphate pathway when the trophic mode changes. Overall, ISIS opens up new possibilities for studying cellular metabolism and regulation, as well as potentially for developing metabolic engineering.
Explanatory model of the psychosocial variables related to the social acceptance of a uranium mine project in northwest Spain

Introduction The demographic growth and the development of the welfare system have been accompanied by an important social dilemma between preserving nature or promoting energy development by assuming the benefits and risks of both proposals. This research attempts to address this social dilemma by analyzing the psychosocial factors that influence the acceptance or rejection of a new uranium mining development and exploitation project. The main objective was to test an explanatory theoretical model of uranium mining project acceptance, based on the interrelation of sociodemographic variables (e.g., age, gender, economic and educational situation, and level of knowledge about uranium energy) and cognitive variables (e.g., environmental beliefs, risk, and benefit perceptions), along with the activation of an emotional balance in response to the proposal of constructing a uranium mine. Method Three hundred seventy-one individuals responded to the questionnaire about the variables included in the model. Results The results showed that older participants showed lower levels of agreement with the mining proposal people, while women and those with greater knowledge of nuclear energy perceived greater risks and had a more negative emotional balance. The proposed explanatory model based on sociodemographic, cognitive, and affective variables showed good fit indices for explaining the assessment of the uranium mine. Thus, age, level of knowledge, risks and benefits, and emotional balance had a direct effect on the acceptance of the mine. Likewise, emotional balance showed a partial mediation effect between the relationships existing between the perception of benefits and risks and the acceptance of the mining proposal. Discussion The results are discussed based on the consideration of analyzing sociodemographic, cognitive, and affective variables to understand potential conflicts in communities affected by energy projects.
Composition of subgingival microbiota associated with periodontitis and diagnosis of malignancy—a cross-sectional study

Periodontitis is one of the world’s most prevalent infectious conditions, affecting between 25 and 40% of the adult population. It is a consequence of the complex interactions between periodontal pathogens and their products, which trigger the host inflammatory response, chronic inflammation, and tissue destruction. Chronic systemic low-grade inflammation is involved in numerous diseases, and it is also known that long-lasting inflammation and chronic infections predispose one to cancer. Here, we characterized and compared the subgingival microbiota associated with periodontitis and diagnosis of malignancy in a longitudinal 10-year follow-up study. The study was conducted on 50 patients with periodontitis and 40 periodontally healthy individuals. The recorded clinical oral health parameters were periodontal attachment loss (AL), bleeding on probing (BOP), gingival index (GI), probing depth (PD), and plaque index (PI). Subgingival plaque was collected from each participant, from which DNA was extracted, and 16S rRNA gene amplicon sequencing performed. Cancer diagnoses data were collected between the years 2008–2018 from the Swedish Cancer Registry. The participants were categorized based on having cancer at the time of sample collection (CSC), having developed cancer later (DCL), and controls without any cancer. The most abundant phyla across all 90 samples were Actinobacteria, Proteobacteria, Firmicutes, Bacteroidetes, and Fusobacteria. At the genus level, Treponema, Fretibacterium, and Prevotella were significantly more abundant in samples of periodontitis patients compared to non-periodontitis individuals. With regard to samples of cancer patients, Corynebacterium and Streptococcus were more abundant in the CSC group; Prevotella were more abundant in the DCL group; and Rothia, Neisseria, and Capnocytophaga were more abundant in the control group. In the CSC group, we also found that the presence of periodontal inflammation, in terms of BOP, GI, and PLI, significantly correlated with species belonging to the genera Prevotella, Treponema, and Mycoplasma. Our results revealed that several subgingival genera were differentially enriched among the studied groups. These findings underscore the need for further research to fully understand the role that oral pathogens may play in the development of cancer.
Simultaneous co-infection with swine influenza A and porcine reproductive and respiratory syndrome viruses potentiates adaptive immune responses

Porcine respiratory disease is multifactorial and most commonly involves pathogen co-infections. Major contributors include swine influenza A (swIAV) and porcine reproductive and respiratory syndrome (PRRSV) viruses. Experimental co-infection studies with these two viruses have shown that clinical outcomes can be exacerbated, but how innate and adaptive immune responses contribute to pathogenesis and pathogen control has not been thoroughly evaluated. We investigated immune responses following experimental simultaneous co-infection of pigs with swIAV H3N2 and PRRSV-2. Our results indicated that clinical disease was not significantly exacerbated, and swIAV H3N2 viral load was reduced in the lung of the co-infected animals. PRRSV-2/swIAV H3N2 co-infection did not impair the development of virus-specific adaptive immune responses. swIAV H3N2-specific IgG serum titers and PRRSV-2-specific CD8β+ T-cell responses in blood were enhanced. Higher proportions of polyfunctional CD8β+ T-cell subset in both blood and lung washes were found in PRRSV-2/swIAV H3N2 co-infected animals compared to the single-infected groups. Our findings provide evidence that systemic and local host immune responses are not negatively affected by simultaneous swIAV H3N2/PRRSV-2 co-infection, raising questions as to the mechanisms involved in disease modulation.
Classification and neuroimaging of ependymal tumors

Ependymal tumors arise from the ependymal cell remnants of the cerebral ventricles, the central canal of the spinal cord, or the filum terminale or conus medullaris, although most pediatric supratentorial ependymomas do not exhibit clear communication or abutment of the ventricles. In this article, we discuss the classification, imaging characteristics, and clinical settings of these tumors. The WHO 2021 classification system has categorized ependymal tumors based on histopathologic and molecular features and location, in which they are grouped as supratentorial, posterior fossa (PF), and spinal. The supratentorial tumors are defined by either the ZFTA (formerly RELA) fusion or the YAP1 fusion. Posterior fossa tumors are divided into group A and group B based on methylation. On imaging, supratentorial and infratentorial ependymomas may arise from the ventricles and commonly contain calcifications and cystic components, with variable hemorrhage and heterogeneous enhancement. Spinal ependymomas are defined by MYCN amplification. These tumors are less commonly calcified and may present with the “cap sign,” with T2 hypointensity due to hemosiderin deposition. Myxopapillary ependymoma and subependymoma remain tumor subtypes, with no change related to molecular classification as this does not provide additional clinical utility. Myxopapillary ependymomas are intradural and extramedullary tumors at the filum terminale and/or conus medullaris and may also present the cap sign. Subependymomas are homogeneous when small and may be heterogeneous and contain calcifications when larger. These tumors typically do not demonstrate enhancement. Clinical presentation and prognosis vary depending on tumor location and type. Knowledge of the updated WHO classification of the central nervous system in conjunction with imaging features is critical for accurate diagnosis and treatment.
Overweight/obesity and socio-demographic disparities in children’s motor and cognitive function

Fundamental motor skills (FMS) and cognitive function are important indicators of development in early childhood. Using a cross-sectional design, the purpose of this study was to investigate obesity (healthy weight vs. overweight/obese) and socio-demographic (i.e., gender, SES) disparities in FMS (locomotor and ball skills) and cognitive function (reaction time [RT] and movement time [MT]), in preschoolers. There were 74 preschoolers (girl = 38; Mage = 4.02 ± 0.73) recruited from two childcare centers and were categorized into healthy weight (n = 58, BMI percentile < 85%) and overweight/obese (n = 16, BMI percentile ≥ 85%) categories. Children’s FMS were assessed using the TGMD-3; cognitive function was assessed by the iPad-based CANTAB™ software using the Reaction Time Task (RTI), including reaction time (RT; Simple RT [SRT], choice RT [CRT]) and movement time (MT; simple MT [SMT], choice MT [CMT]). Children presented less FMS proficiency compared to recent data. Both weight groups performed comparably in FMS (ps > 0.05; ball skill Cohen’s d = 0.40; locomotor Cohen’s d = 0.02). Children in the overweight/obese group performed significantly worse on all cognitive tests compared to healthy weight peers (ps < 0.05; Cohen’s d range from −0.93 to −1.43). No significant gender or SES disparities were observed. Maintaining healthy weight status is critical for cognitive development among preschoolers, which may influence their developmental trajectory and school readiness.