bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultrahigh‐Temperature Anatexis of Metapelites Generates Near‐Anhydrous Garnet Granitoids
Authors: Wang Bin , Wei Chunjing , Tian Wei , Tang Ming
Published: November 2023

It remains unresolved whether extensive granitoids can originate from ultrahigh‐temperature crustal anatexis beyond the stability of fusible hydrous minerals and, if any, how they are generated and characterized. Here we investigate near‐anhydrous garnet granitoids in the Jining Complex, North China, using bulk‐rock and mineral analyses combined with phase equilibria modeling. The Jining garnet granitoids are parautochthonously emplaced within granulite terranes and diagnostically contain perthite, abundant garnet but minor biotite. The rocks exhibit high maficity (FeOT + MgO) of 4–12 wt.%, minimal H2O contents below ∼0.16 wt.% and limited aluminum saturation indexes within 1.1–1.7. Their magmas are scarcely fractionated and have ultrahigh temperatures of 1000–1100°C as revealed by K‐feldspar rich in anorthite (10–13 mol.%) and Ti (175−276 ppm), and garnet rims depleted in heavy rare‐earth elements that crystallize from melts. Besides, these magmas have deficient H2O contents (<∼0.19 wt.%) and high densities and viscosities. The garnet granitoids are generated by metapelite anatexis at ultrahigh‐temperature conditions likely around ∼1100°C, with selective entrainment of 5–40 vol.% residua, and underwent some melt loss during magma crystallization. The melting temperatures are far beyond biotite stability and close to the crustal dry solidus. Garnet‐involved congruent melting reactions are required to produce the maficity‐rich and H2O‐deficient melts with high capability for entraining residua. The ultrahigh‐temperature garnet granitoids differ from ordinary low‐ and high‐temperature garnetiferous granites in both petrologic features and petrogenesis, and represent a new subcategory of S‐type granitoids. They can indicate mantle‐actuated extreme crustal thermal perturbations.
Exploring the Connection of XVI‐Century Major Historical Earthquakes in the Eastern Betic Cordillera, Spain: Insights From Viscoelastic Relaxation of the Lithosphere
Authors: Yazdi Pouye , García‐Mayordomo Julián , Álvarez‐Gómez José Antonio , Gaspar‐Escribano Jorge Miguel , Masana Eulália
Published: November 2023

Understanding the crustal fault interaction and connection between earthquakes in areas with slow tectonic deformation, such as Betic Cordillera (South Spain), is challenging. When seismic rates are low and large destructive earthquakes happen less frequently, it is necessary to resort to historical or paleoseismic records. This study investigates the postseismic viscoelastic relaxation mechanism as a potential explanation for the occurrence of three historical earthquakes (IEMSVIII‐IX) in the Eastern Betic Shear Zone during the XVI‐century, all of which occurred within a span of 13 years: 1518 Vera Mw6.2, 1522 Alhama de Almeria Mw6.5, and 1531 Baza Mw6.2 associated with the Palomares, Carboneras, and Baza faults, respectively. The results strongly suggest a sequential stress‐triggering connection between the three events. The northern NS‐oriented section of the Baza fault is found to have experienced a larger positive ΔCFS and, indeed, more prone to rupture in 1531. The study also examines whether the cumulative ΔCFS had influenced the occurrence of further significant earthquakes (≥Mw6.0) in the region. A triggering connection between the cascade and the 1658 Almeria Mw6.2 earthquake is suggested, whereas no indications of similar linkage to the 1674 Lorca Mw6.0 or the 1804 Dalias Mw6.4 events are found. The stress triggering impact of the cascade over nearby active faults is noteworthy. It is expected that this analysis could have future applications for studying other important historical events, and improving seismic hazard analysis in complex fault settings of the Betic Cordillera.
An umbrella review of candidate predictors of response, remission, recovery, and relapse across mental disorders
Authors: Solmi Marco , Cortese Samuele , Vita Giovanni , De Prisco Michele , Radua Joaquim , Dragioti Elena , Köhler-Forsberg Ole , Madsen Nanna M. , Rohde Christopher , Eudave Luis , Aymerich Claudia , Pedruzo Borja , Rodriguez Victoria , Rosson Stella , Sabé Michel , Hojlund Mikkel , Catalan Ana , de Luca Beatrice , Fornaro Michele , Ostuzzi Giovanni , Barbui Corrado , Salazar-de-Pablo Gonzalo , Fusar-Poli Paolo , Correll Christoph U.
Published: November 2023

We aimed to identify diagnosis-specific/transdiagnostic/transoutcome multivariable candidate predictors (MCPs) of key outcomes in mental disorders. We conducted an umbrella review (protocol link), searching MEDLINE/Embase (19/07/2022), including systematic reviews of studies reporting on MCPs of response, remission, recovery, or relapse, in DSM/ICD-defined mental disorders. From published predictors, we filtered MCPs, validating MCP criteria. AMSTAR2/PROBAST measured quality/risk of bias of systematic reviews/individual studies. We included 117 systematic reviews, 403 studies, 299,888 individuals with mental disorders, testing 796 prediction models. Only 4.3%/1.2% of the systematic reviews/individual studies were at low risk of bias. The most frequently targeted outcome was remission (36.9%), the least frequent was recovery (2.5%). Studies mainly focused on depressive (39.4%), substance-use (17.9%), and schizophrenia-spectrum (11.9%) disorders. We identified numerous MCPs within disorders for response, remission and relapse, but none for recovery. Transdiagnostic MCPs of remission included lower disease-specific symptoms (disorders = 5), female sex/higher education (disorders = 3), and quality of life/functioning (disorders = 2). Transdiagnostic MCPs of relapse included higher disease-specific symptoms (disorders = 5), higher depressive symptoms (disorders = 3), and younger age/higher anxiety symptoms/global illness severity/ number of previous episodes/negative life events (disorders = 2). Finally, positive trans-outcome MCPs for depression included less negative life events/depressive symptoms (response, remission, less relapse), female sex (response, remission) and better functioning (response, less relapse); for schizophrenia, less positive symptoms/higher depressive symptoms (remission, less relapse); for substance use disorder, marital status/higher education (remission, less relapse). Male sex, younger age, more clinical symptoms and comorbid mental/physical symptoms/disorders were poor prognostic factors, while positive factors included social contacts and employment, absent negative life events, higher education, early access/intervention, lower disease-specific and comorbid mental and physical symptoms/conditions, across mental disorders. Current data limitations include high risk of bias of studies and extraction of single predictors from multivariable models. Identified MCPs can inform future development, validation or refinement of prediction models of key outcomes in mental disorders.
Postpartum and non-postpartum depression: a population-based matched case-control study comparing polygenic risk scores for severe mental disorders
Authors: Munk-Olsen Trine , Di Florio Arianna , Madsen Kathrine B. , Albiñana Clara , Mægbæk Merete L. , Bergink Veerle , Frøkjær Vibe G. , Agerbo Esben , Vilhjálmsson Bjarni J. , Werge Thomas , Nordentoft Merete , Hougaard David M. , Børglum Anders D. , Mors Ole , Mortensen Preben Bo , Liu Xiaoqin
Published: November 2023

It remains inconclusive whether postpartum depression (PPD) and depression with onset outside the postpartum period (MDD) are genetically distinct disorders. We aimed to investigate whether polygenic risk scores (PGSs) for major mental disorders differ between PPD cases and MDD cases in a nested case-control study of 50,057 women born from 1981 to 1997 in the iPSYCH2015 sample in Demark. We identified 333 women with first-onset postpartum depression (PPD group), who were matched with 993 women with first-onset depression diagnosed outside of postpartum (MDD group), and 999 female population controls. Data on genetics and depressive disorders were retrieved from neonatal biobanks and the Psychiatric Central Research Register. PGSs were calculated from both individual-level genetic data and meta-analysis summary statistics from the Psychiatric Genomics Consortium. Conditional logistic regression was used to calculate the odds ratio (OR), accounting for the selection-related reproductive behavior. After adjustment for covariates, higher PGSs for severe mental disorders were associated with increased ORs of both PPD and MDD. Compared with MDD cases, MDD PGS and attention-deficit/hyperactivity disorder PGS were marginally but not statistically higher for PPD cases, with the OR of PPD versus MDD being 1.12 (95% CI: 0 .97–1.29) and 1.11 (0.97–1.27) per-standard deviation increase, respectively. The ORs of PPD versus MDD did not statistically differ by PGSs of bipolar disorder, schizophrenia, or autism spectrum disorder. Our findings suggest that relying on PGS data, there was no clear evidence of distinct genetic make-up of women with depression occurring during or outside postpartum, after taking the selection-related reproductive behavior into account.
Pathological roles of bone marrow adipocyte-derived monocyte chemotactic protein-1 in type 2 diabetic mice
Authors: Wan Shan , Xie Jinwei , Liang Yan , Yu Xijie
Published: November 2023

Type 2 diabetes mellitus (T2DM) has become a prevalent public health concern, with beta-cell dysfunction involved in its pathogenesis. Bone marrow adipose tissue (BMAT) increases in both the quantity and area in individuals with T2DM along with heightened monocyte chemotactic protein-1 (MCP-1) secretion. This study aims to investigate the influence and underlying mechanisms of MCP-1 originating from bone marrow adipocytes (BMAs) on systemic glucose homeostasis in T2DM. Initially, a substantial decrease in the proliferation and glucose-stimulated insulin secretion (GSIS) of islet cells was observed. Moreover, a comparative analysis between the control (Ctrl) group and db/db mice revealed significant alterations in the gene expression profiles of whole bone marrow cells, with a noteworthy upregulation of Mcp-1. And the primary enriched pathways included chemokine signaling pathway and AGE-RAGE signaling pathway in diabetic complications. In addition, the level of MCP-1 was distinctly elevated in BMA-derived conditional media (CM), leading to a substantial inhibition of proliferation, GSIS and the protein level of phosphorylated Akt (p-Akt) in Min6 cells. After blocking MCP-1 pathway, we observed a restoration of p-Akt and the proliferation of islet cells, resulting in a marked improvement in disordered glucose homeostasis. In summary, there is an accumulation of BMAs in T2DM, which secrete excessive MCP-1, exacerbating the abnormal accumulation of BMAs in the bone marrow cavity through paracrine signaling. The upregulated MCP-1, in turn, worsens glucose metabolism disorder by inhibiting the proliferation and insulin secretion of islet cells through an endocrine pathway. Inhibiting MCP-1 signaling can partially restore the proliferation and insulin secretion of islet cells, ultimately ameliorating glucose metabolism disorder. It’s worth noting that to delve deeper into the impact of MCP-1 derived from BMAs on islet cells and its potential mechanisms, it is imperative to develop genetically engineered mice with conditional Mcp-1 knockout from BMAs.
Achieving net-zero in the dry eye disease care pathway
Authors: Latham Samuel G. , Williams Richard L. , Grover Liam M. , Rauz Saaeha
Published: November 2023

Climate change is a threat to human health and wellbeing across the world. In recent years, there has been a surge in awareness of this crisis, leading to many countries and organisations setting “net-zero” targets. This entails minimising carbon emissions and neutralising remaining emissions by removing carbon from the atmosphere. At the 2022 United Nations Climate Change Conference (COP27), commitments to transition away from fossil fuels and augment climate targets were underwhelming. It is therefore imperative for public and private sector organisations to demonstrate successful implementation of net-zero and set a precedent for the global political consensus. As a top 10 world employer, the United Kingdom National Health Service (NHS) has pledged to reach net-zero by 2045. The NHS has already taken positive steps forward, but its scale and complexity as a health system means stakeholders in each of its services must highlight the specifications for further progress. Dry eye disease is a chronic illness with an estimated global prevalence of 29.5% and an environmentally damaging care pathway. Moreover, environmental damage is a known aggravator of dry eye disease. Worldwide management of this illness generates copious amounts of non-recyclable waste, utilises inefficient supply chains and involves recurrent follow-up appointments and prescriptions. By mapping the dry eye disease care pathway to environmental impact, in this review we will highlight seven key areas in which reduced emissions and pollution could be targeted. Examining these approaches for improved environmental sustainability is critical in driving the transformation needed to preserve our health and wellbeing.
Integrating human activity into food environments can better predict cardiometabolic diseases in the United States
Authors: Xu Ran , Huang Xiao , Zhang Kai , Lyu Weixuan , Ghosh Debarchana , Li Zhenlong , Chen Xiang
Published: November 2023

The prevalence of cardiometabolic diseases in the United States is presumably linked to an obesogenic retail food environment that promotes unhealthy dietary habits. Past studies, however, have reported inconsistent findings about the relationship between the two. One underexplored area is how humans interact with food environments and how to integrate human activity into scalable measures. In this paper, we develop the retail food activity index (RFAI) at the census tract level by utilizing Global Positioning System tracking data covering over 94 million aggregated visit records to approximately 359,000 food retailers across the United States over two years. Here we show that the RFAI has significant associations with the prevalence of multiple cardiometabolic diseases. Our study indicates that the RFAI is a promising index with the potential for guiding the development of policies and health interventions aimed at curtailing the burden of cardiometabolic diseases, especially in communities characterized by obesogenic dietary behaviors.
Intra- and inter-molecular regulation by intrinsically-disordered regions governs PUF protein RNA binding
Authors: Qiu Chen , Zhang Zihan , Wine Robert N. , Campbell Zachary T. , Zhang Jun , Hall Traci M. Tanaka
Published: November 2023

PUF proteins are characterized by globular RNA-binding domains. They also interact with partner proteins that modulate their RNA-binding activities. Caenorhabditis elegans PUF protein fem-3 binding factor-2 (FBF-2) partners with intrinsically disordered Lateral Signaling Target-1 (LST-1) to regulate target mRNAs in germline stem cells. Here, we report that an intrinsically disordered region (IDR) at the C-terminus of FBF-2 autoinhibits its RNA-binding affinity by increasing the off rate for RNA binding. Moreover, the FBF-2 C-terminal region interacts with its globular RNA-binding domain at the same site where LST-1 binds. This intramolecular interaction restrains an electronegative cluster of amino acid residues near the 5′ end of the bound RNA to inhibit RNA binding. LST-1 binding in place of the FBF-2 C-terminus therefore releases autoinhibition and increases RNA-binding affinity. This regulatory mechanism, driven by IDRs, provides a biochemical and biophysical explanation for the interdependence of FBF-2 and LST-1 in germline stem cell self-renewal.
PI3K/AKT signaling activates HIF1α to modulate the biological effects of invasive breast cancer with microcalcification
Authors: Tian Yao , Zhao Lu , Gui Zhengwei , Liu Shiyang , Liu Chenguang , Yu Tianyao , Zhang Lin
Published: November 2023

Microcalcification (MC) is a valuable diagnostic indicator of breast cancer, and it is reported to be associated with increased tumor aggressiveness and poor prognosis. Nevertheless, the exact potential molecular mechanism is not completely understood. Here, we find that the mineralized invasive breast cancer (IBC) cells not only increased their proliferation and migration, but also showed the characteristic of doxorubicin resistance. The PI3K/AKT signaling pathway is associated with the generation of calcification in IBC, and it activates the transcription and translation of its downstream hypoxia-inducible factor 1α (HIF1α). Knockdown of HIF1α protein significantly downregulated cell proliferation and migration while calcification persists. Meanwhile, calcified breast cancer cells restored sensitivity to doxorubicin because of suppressed HIF1α expression. In addition, we provide initial data on the underlying value of HIF1α as a biomarker of doxorubicin resistance. These findings provide a new direction for exploring microcalcifications in IBC.
Laser pulse compression by a density gradient plasma for exawatt to zettawatt lasers
Authors: Hur Min Sup , Ersfeld Bernhard , Lee Hyojeong , Kim Hyunsuk , Roh Kyungmin , Lee Yunkyu , Song Hyung Seon , Kumar Manoj , Yoffe Samuel , Jaroszynski Dino A. , Suk Hyyong
Published: November 2023

We propose a new method of compressing laser pulses to ultrahigh powers based on spatially varying dispersion of an inhomogeneous plasma. Here, compression is achieved when a long, negatively frequency-chirped laser pulse reflects off the density ramp of an over-dense plasma slab. As the density increases longitudinally, high-frequency photons at the leading part of the laser pulse penetrate more deeply into the plasma region than lower-frequency photons, resulting in pulse compression in a similar way to that by a chirped mirror. Proof-of-principle simulations performed using particle-in-cell simulation codes predict compression of a 2.35 ps laser pulse to 10.3 fs—a ratio of 225. As plasma is robust and resistant to damage at high intensities—unlike solid-state gratings commonly used in chirped-pulse amplification—the method could be used as a compressor to reach exawatt or zettawatt peak powers.
Predicting multiple conformations via sequence clustering and AlphaFold2
Authors: Wayment-Steele Hannah K. , Ojoawo Adedolapo , Otten Renee , Apitz Julia M. , Pitsawong Warintra , Hömberger Marc , Ovchinnikov Sergey , Colwell Lucy , Kern Dorothee
Published: November 2023

AlphaFold2 (ref. 1) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein’s biological function often depends on multiple conformational substates2, and disease-causing point mutations often cause population changes within these substates3,4. We demonstrate that clustering a multiple-sequence alignment by sequence similarity enables AlphaFold2 to sample alternative states of known metamorphic proteins with high confidence. Using this method, named AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protein KaiB5 and found that predictions of both conformations were distributed in clusters across the KaiB family. We used nuclear magnetic resonance spectroscopy to confirm an AF-Cluster prediction: a cyanobacteria KaiB variant is stabilized in the opposite state compared with the more widely studied variant. To test AF-Cluster’s sensitivity to point mutations, we designed and experimentally verified a set of three mutations predicted to flip KaiB from Rhodobacter sphaeroides from the ground to the fold-switched state. Finally, screening for alternative states in protein families without known fold switching identified a putative alternative state for the oxidoreductase Mpt53 in Mycobacterium tuberculosis. Further development of such bioinformatic methods in tandem with experiments will probably have a considerable impact on predicting protein energy landscapes, essential for illuminating biological function.
Protein-based bandpass filters for controlling cellular signaling with chemical inputs
Authors: Shui Sailan , Scheller Leo , Correia Bruno E.
Published: November 2023

Biological signal processing is vital for cellular function. Similar to electronic circuits, cells process signals via integrated mechanisms. In electronics, bandpass filters transmit frequencies with defined ranges, but protein-based counterparts for controlled responses are lacking in engineered biological systems. Here, we rationally design protein-based, chemically responsive bandpass filters (CBPs) showing OFF-ON-OFF patterns that respond to chemical concentrations within a specific range and reject concentrations outside that range. Employing structure-based strategies, we designed a heterodimeric construct that dimerizes in response to low concentrations of a small molecule (ON), and dissociates at high concentrations of the same molecule (OFF). The CBPs have a multidomain architecture in which we used known drug receptors, a computationally designed protein binder and small-molecule inhibitors. This modular system allows fine-tuning for optimal performance in terms of bandwidth, response, cutoff and fold changes. The CBPs were used to regulate cell surface receptor signaling pathways to control cellular activities in engineered cells.
Model-based predictions of protective HIV pre-exposure prophylaxis adherence levels in cisgender women
Authors: Zhang Lanxin , Iannuzzi Sara , Chaturvedula Ayyappa , Irungu Elizabeth , Haberer Jessica E. , Hendrix Craig W. , von Kleist Max
Published: November 2023

Most human immunodeficiency virus (HIV) infections occur in cisgender women in resource-limited settings. In women, self-protection with emtricitabine/tenofovir disoproxil fumarate pre-exposure prophylaxis (FTC/TDF-PrEP) constitutes a major pillar of HIV prevention. However, clinical trials in women had inconsistent outcomes, sparking uncertainty about adherence requirements and reluctance in evaluating on-demand regimens. We analyzed data from published FTC/TDF-PrEP trials to establish efficacy ranges in cisgender women. In a ‘bottom-up’ approach, we modeled hypotheses in the context of risk-group-specific, adherence–efficacy profiles and challenged those hypotheses with clinical data. We found that different clinical outcomes were related to the proportion of women taking the product, allowing coherent interpretation of the data. Our analysis showed that 90% protection was achieved when women took some product. We found that hypotheses of putative male/female differences were either not impactful or statistically inconsistent with clinical data. We propose that differing clinical outcomes could arise from pill-taking behavior rather than biological factors driving specific adherence requirements in cisgender women.
Meta-reinforcement learning via orbitofrontal cortex
Authors: Hattori Ryoma , Hedrick Nathan G. , Jain Anant , Chen Shuqi , You Hanjia , Hattori Mariko , Choi Jun-Hyeok , Lim Byung Kook , Yasuda Ryohei , Komiyama Takaki
Published: November 2023

The meta-reinforcement learning (meta-RL) framework, which involves RL over multiple timescales, has been successful in training deep RL models that generalize to new environments. It has been hypothesized that the prefrontal cortex may mediate meta-RL in the brain, but the evidence is scarce. Here we show that the orbitofrontal cortex (OFC) mediates meta-RL. We trained mice and deep RL models on a probabilistic reversal learning task across sessions during which they improved their trial-by-trial RL policy through meta-learning. Ca2+/calmodulin-dependent protein kinase II-dependent synaptic plasticity in OFC was necessary for this meta-learning but not for the within-session trial-by-trial RL in experts. After meta-learning, OFC activity robustly encoded value signals, and OFC inactivation impaired the RL behaviors. Longitudinal tracking of OFC activity revealed that meta-learning gradually shapes population value coding to guide the ongoing behavioral policy. Our results indicate that two distinct RL algorithms with distinct neural mechanisms and timescales coexist in OFC to support adaptive decision-making.
Soil organic carbon stocks increased across the tide-induced salinity transect in restored mangrove region
Authors: Zou Huimin , Li Xianglan , Li Sen , Xu Zhe , Yu Zhitong , Cai Houcai , Chen Wandong , Ni Xiaopin , Wu Erwei , Zeng Guihou
Published: November 2023

Blue carbon in mangrove ecosystems contributes significantly to the global carbon cycle. However, large uncertainties maintain in the soil organic carbon (SOC) storage throughout the tide-induced salinity and alkalinity transect in the mangrove restoration region in Southern China. Total 125 soil samples were obtained to detect the SOC content and physicochemical properties. The mean SOC content of each layer ranged from 6.82 to 7.86 g kg−1, while the SOC density ranged from 2.99 to 11.41 kg m−2, increasing with soil depths. From different land covers in the study region, the SOC content varied from 4.63 to 9.71 g kg−1, increasing across the salinity and alkalinity transect, while the SOC density fluctuated from 3.01 kg m−2 in mudflats to 10.05 kg m−2 in mangrove forests. SOC concentration was favorably linked with total nitrogen (r = 0.95), and total phosphorus (r = 0.74), and negatively correlated with Cl− (r = − 0.95), electrical conductivity (r = − 0.24), and total dissolved solids (r = − 0.08). There were significant logarithmic relationships between SOC content and the concentrations of clay (r = 0.76), fine silt (r = 0.81), medium silt (r = − 0.82), and coarse silt (r = − 0.78). The spatial patterns of SOC concentration were notably affected by soil texture, physicochemical properties, and land-cover type, providing essential reference for future investigations of blue carbon budget in restored mangrove forests.
Influence of the pesticide flupyradifurone on mobility and physical condition of larval green lacewings
Authors: Scheibli Leonie , Elsenhans Tabita , Wolf Harald , Stemme Torben , Pfeffer Sarah Elisabeth
Published: November 2023

Global pesticide use in agriculture is one reason for the rapid insect decline in recent years. The relatively new pesticide flupyradifurone is neurotoxic to pest insects but considered harmless to bees according to previous risk assessments. With this study, we aim to investigate lethal and sublethal effects of flupyradifurone on larvae of the beneficial arthropod Chrysoperla carnea. We treated the animals orally with field-realistic concentrations of flupyradifurone and examined lethality as well as effects on condition, mobility and locomotion. For the lethal dose 50, we determined a value of > 120–200 ng/mg (corresponding to a mean amount of 219 ng/larva) after 168 h. Abnormal behaviors such as trembling and comatose larvae were observed even at the lowest concentration applied (> 0–20 ng/mg, 59 ng/larva). Mobility analysis showed impaired activity patterns, resulting in acute hypoactivity at all pesticide concentrations and time-delayed hyperactivity in larvae treated with > 40–60 ng/mg (100 ng/larva) and > 80–100 ng/mg (120 ng/larva), respectively. Even locomotion as a fundamental behavioral task was negatively influenced throughout larval development. In conclusion, our results demonstrate that flupyradifurone impacts life and survival of lacewing larvae and may pose—despite its status as bee-friendly—a major threat to insect fauna and environment.
Detecting continuous structural heterogeneity in single-molecule localization microscopy data
Authors: Haghparast Sobhan , Stallinga Sjoerd , Rieger Bernd
Published: November 2023

Fusion of multiple chemically identical complexes, so-called particles, in localization microscopy, can improve the signal-to-noise ratio and overcome under-labeling. To this end, structural homogeneity of the data must be assumed. Biological heterogeneity, however, could be present in the data originating from distinct conformational variations or (continuous) variations in particle shapes. We present a prior-knowledge-free method for detecting continuous structural variations with localization microscopy. Detecting this heterogeneity leads to more faithful fusions and reconstructions of the localization microscopy data as their heterogeneity is taken into account. In experimental datasets, we show the continuous variation of the height of DNA origami tetrahedrons imaged with 3D PAINT and of the radius of Nuclear Pore Complexes imaged in 2D with STORM. In simulation, we study the impact on the heterogeneity detection pipeline of Degree Of Labeling and of structural variations in the form of two independent modes.
Occurrence of tardigrades and morphometric and chemical conditions in rock pools by the Baltic Sea
Authors: Troell Sofia , Jönsson K. Ingemar
Published: November 2023

Rock pools are eroded depressions in bedrock providing temporary aquatic habitats with varying morphometric and chemical conditions. Tardigrades have adapted to many habitats with varying and extreme abiotic conditions, including desiccation, but their occurrence in rock pools have rarely been investigated. This study investigated the occurrence of tardigrades and the morphometric and chemical conditions in rock pools by the Baltic Sea in southeast Sweden. Samples of benthic material were collected from rock pools at three sites near the town Karlshamn together with measurements of pool size, pH, temperature, salinity, and dissolved oxygen of the water. Tardigrades occurred in about one fifth of the rock pools and included five eutardigrade genera. Also rotifers and nematodes were observed in the samples. The morphometric and chemical variables varied both within and among the three sites but with few differences between rock pools with or without tardigrades. However, rock pools with tardigrades tended to be overall shallower than pools without tardigrades, indicating that more desiccating-prone rock pools may be more favourable habitats for tardigrades. The study shows that tardigrades are part of the micro-invertebrate fauna in rock pools and this habitat deserves more investigations into the occurrence of this animal group.
Biostimulation of green microalgae Chlorella sorokiniana using nanoparticles of MgO, Ca10(PO4)6(OH)2, and ZnO for increasing biodiesel production
Authors: Faried Maryam , Khalifa Amany , Samer Mohamed , Attia Yasser A. , Moselhy Mohamed A. , El-Hussein Ahmed , Yousef Rania S. , Abdelbary Khaled , Abdelsalam Essam M.
Published: November 2023

Microalgae have the potential to become the primary source of biodiesel, catering to a wide range of essential applications such as transportation. This would allow for a significant reduction in dependence on conventional petroleum diesel. This study investigates the effect of biostimulation techniques utilizing nanoparticles of Magnesium oxide MgO, Calcium hydroxyapatite Ca10(PO4)6(OH)2, and Zinc oxide ZnO to enhance the biodiesel production of Chlorella sorokiniana. By enhancing cell activity, these nanoparticles have demonstrated the ability to improve oil production and subsequently increase biodiesel production. Experimentally, each nanomaterial was introduced at a concentration of 15 mg L−1. The results have shown that MgO nanoparticles yielded the highest biodiesel production, with a recorded yield of 61.5 mg L−1. Hydroxyapatite nanoparticles, on the other hand, facilitated lipid accumulation. ZnO nanoparticles showcased a multifaceted advantage by enhancing both growth and lipid content. Thus, it is suggested that these nanoparticles can be used effectively to increase the lipid content of microalgae. These findings highlight the potential of biostimulation strategies utilizing MgO, hydroxyapatite, and zinc oxide nanoparticles to bolster biodiesel production.
Targeting the Schistosoma mansoni nutritional mechanisms to design new antischistosomal compounds
Authors: Pavani Thaís F. A. , Cirino Maria E. , Teixeira Thainá R. , de Moraes Josué , Rando Daniela G. G.
Published: November 2023

The chemical classes of semicarbazones, thiosemicarbazones, and hydrazones are present in various compounds, each demonstrating diverse biological activities. Extensive studies have revealed their potential as schistosomicidal agents. Thiosemicarbazones, in particular, have shown inhibitory effects on Schistosoma mansoni's cathepsin B1 enzyme (SmCB1), which plays a crucial role in hemoglobin degradation within the worm's gut and its nutrition processes. Consequently, SmCB1 has emerged as a promising target for novel schistosomiasis therapies. Moreover, chloroquinoline exhibits characteristics in its aromatic structure that hold promise for developing SmCB1 inhibitors, along with its interaction with hemoglobin's heme group, potentially synergizing against the parasite's gut. In this context, we report the synthesis of 22 hybrid analogs combining hydrazones and quinolines, evaluated against S. mansoni. Five of these hybrids demonstrated schistosomicidal activity in vitro, with GPQF-8Q10 being the most effective, causing worm mortality within 24 h at a concentration of 25 µM. GPQF-8Q8 proved to be the most promising in vivo, significantly reducing egg presence in feces (by 52.8%) and immature eggs in intestines (by 45.8%). These compounds exhibited low cytotoxicity in Vero cells and an in in vivo animal model (Caenorhabditis elegans), indicating a favorable selectivity index. This suggests their potential for the development of new schistosomiasis therapies. Further studies are needed to uncover specific target mechanisms, but these findings offer a promising starting point.
Adaptive walking control for quadruped robot by using oscillation patterns
Authors: Zhang Yong , Qian Yijia , Ding Yi , Hou Beiping , Wang Rongyang
Published: November 2023

To improve the adaptability of quadruped robot in multiple scenarios, an adaptive locomotive system based on the double-layered central pattern generator (CPG) is proposed. The novel CPG network consists of double master units and subsets of slave units based on gyroscope signals including yaw and pitch angle. The response of master units provides the ability to control the 1st joins of quadruped robot, while slave units can generate the symmetry signals to control the 2nd and 3rd joints. The CPG network enables the seamless switching of locomotion gaits to stops and starts by using an ultrasonic sensor. Through adjusting the mutually dependent parameters, joints can generate the joint angles to achieve steering behavior. For adaptive movement on an irregular surface, stable ranges of the robot body yaw and pitch angles are proposed by using gyroscope signals. The experimental results verify that the quadruped robot with the proposed double-layered CPG network can perform stable trot pattern in a complex environment.
A computational approach to investigating facial attractiveness factors using geometric morphometric analysis and deep learning
Authors: Sano Takanori , Kawabata Hideaki
Published: November 2023

Numerous studies discuss the features that constitute facial attractiveness. In recent years, computational research has received attention because it can examine facial features without relying on prior research hypotheses. This approach uses many face stimuli and models the relationship between physical facial features and attractiveness using methods such as geometric morphometrics and deep learning. However, studies using each method have been conducted independently and have technical and data-related limitations. It is also difficult to identify the factors of actual attractiveness perception using only computational methods. In this study, we examined morphometric features important for attractiveness perception through geometric morphometrics and impression evaluation. Furthermore, we used deep learning to analyze important facial features comprehensively. The results showed that eye-related areas are essential in determining attractiveness and that different racial groups contribute differently to the impact of shape and skin information on attractiveness. The approach used in this study will contribute toward understanding facial attractiveness features that are universal and diverse, extending psychological findings and engineering applications.
Tests and deflection calculation method for circular concrete-filled steel tubular columns under very low-elevation lateral impact loads
Authors: Liang Jiayu , Liu Yanhui , Zhao Yichao , Xu Nan
Published: November 2023

An experimental investigation of circular concrete-filled steel tubular (CFST) columns subjected to very low-elevation lateral impacts was performed. Six circular CFST members were prepared for lateral impact tests according to the typical CFST columns in high-speed railway stations in China, and the impact location was at the height of the 2/9 column. The tests had three variables: the thickness of the steel tube, the impact velocity, and the axial load. The failure modes were determined in the tests, along with the time histories of the impact force and the deflection at the impact location. A finite-element analysis was performed to examine the effects of the axial load and scaling on the maximum deflection. The results show that with the increase of axial compression ratio, the impact resistance of the member first increases and then weakens. According to the travelling plastic hinge theory, a three-stage rigid plastic mechanical model was employed to describe the impact process, in which the impact location was at the non-mid-span, and a deflection calculation method for CFST applicable to any impact position was developed. A comparison with the test results indicated that deflections can be calculated with reasonable accuracy using the proposed method.
Utilizing deep learning via the 3D U-net neural network for the delineation of brain stroke lesions in MRI image
Authors: Soleimani Parisa , Farezi Navid
Published: November 2023

The segmentation of acute stroke lesions plays a vital role in healthcare by assisting doctors in making prompt and well-informed treatment choices. Although Magnetic Resonance Imaging (MRI) is a time-intensive procedure, it produces high-fidelity images widely regarded as the most reliable diagnostic tool available. Employing deep learning techniques for automated stroke lesion segmentation can offer valuable insights into the precise location and extent of affected tissue, enabling medical professionals to effectively evaluate treatment risks and make informed assessments. In this research, a deep learning approach is introduced for segmenting acute and sub-acute stroke lesions from MRI images. To enhance feature learning through brain hemisphere symmetry, pre-processing techniques are applied to the data. To tackle the class imbalance challenge, we employed a strategy of using small patches with balanced sampling during training, along with a dynamically weighted loss function that incorporates f1-score and IOU-score (Intersection over Union). Furthermore, the 3D U-Net architecture is used to generate predictions for complete patches, employing a high degree of overlap between patches to minimize the requirement for subsequent post-processing steps. The 3D U-Net model, utilizing ResnetV2 as the pre-trained encoder for IOU-score and Seresnext101 for f1-score, stands as the leading state-of-the-art (SOTA) model for segmentation tasks. However, recent research has introduced a novel model that surpasses these metrics and demonstrates superior performance compared to other backbone architectures. The f1-score and IOU-score were computed for various backbones, with Seresnext101 achieving the highest f1-score and ResnetV2 performing the highest IOU-score. These calculations were conducted using a threshold value of 0.5. This research proposes a valuable model based on transfer learning for the classification of brain diseases in MRI scans. The achieved f1-score using the recommended classifiers demonstrates the effectiveness of the approach employed in this study. The findings indicate that Seresnext101 attains the highest f1-score of 0.94226, while ResnetV2 achieves the best IOU-score of 0.88342, making it the preferred architecture for segmentation methods. Furthermore, the study presents experimental results of the 3D U-Net model applied to brain stroke lesion segmentation, suggesting prospects for researchers interested in segmenting brain strokes and enhancing 3D U-Net models.
Dual-color space network with global priors for photo retouching
Authors: Park Pilseo , Oh Heungmin , Kim Hyuncheol
Published: November 2023

There have been growing trends using deep learning-based approaches for photo retouching which aims to enhance unattractive images and make them visually appealing. However, the existing methods only considered the RGB color space, which limited the available color information for editing. To address this issue, we propose a dual-color space network that extracts color representations from multiple color spaces to provide more robust color information. Our approach is based on the observation that converting an image to a different color space generates a new image that can be further processed by a neural network. Hence, we utilize two separate networks: a transitional network and a base network, each operating in a different color space. Specifically, the input RGB image is converted to another color space (e.g., YCbCr) using color space converter (CSC). The resulting image is then passed through the transitional network to extract color representations from the corresponding color space using color prediction module (CPM). The output of the transitional network is converted back to the RGB space and fed into the base network, which operates in RGB space. By utilizing global priors from each representation in different color spaces, we guide the retouching process to produce natural and realistic results. Experimental results demonstrate that our proposed method outperforms state-of-the-art methods on the MIT-Adobe FiveK dataset, and an in-depth analysis and ablation study highlight the advantages of our approach.
Evaluation of cortical and trabecular bone structure of the mandible in patients with ankylosing spondylitis
Authors: Gulec Melike , Erturk Mediha , Tassoker Melek , Basdemirci Muserref
Published: November 2023

This study aimed to examine the difference between the fractal dimension (FD) values of the mandibular trabecular bone and the panoramic mandibular index (PMI), mandibular cortical index (MCI) and mandibular cortical thickness (MCW) of patients with ankylosing spondylitis (AS) and healthy control group. A total of 184 individuals (92 cases, 92 controls), were examined in our study. PMI, MCI, and MCW values were calculated on panoramic images of all individuals. For FD values, the region of interest (ROI) was selected with the size of 100 × 100 pixels from the right-left gonial and interdental regions and 50 × 50 pixels from the condylar region. Degenerative changes in the temporomandibular joint (TMJ) region were recorded. PMI, MCI, and MCW values showed statistically significant differences between the groups (p = 0.000, p < 0.001). The radiological signs of mandibular cortical resorption were more severe in the case group than in the control group. PMI and MCW values were found to be lower in the case group than in the control group. It was determined that the number of C3 and C2 values, among the MCI values, was higher in the case group. Only the FD values of the ROI selected from the condyle region were found to be statistically significant and were lower in the case group (p = 0.026, p < 0.05). Degenerative changes in the TMJ region were significantly more frequent in the case groups (p = 0.000, p < 0.001). The fact that the mandibular cortex shows more resorptive features in individuals with AS may require further evaluation in terms of osteoporosis. Because of the low FD values of the condylar regions of these patients and the more frequent degenerative changes, the TMJ region should be followed carefully. Detailed examination of the mandibular cortex and condylar region is beneficial in patients with AS for screening and following osteoporotic changes in these individuals, which is essential for the patient’s life quality.
Ensembles of climate simulations to anticipate worst case heatwaves during the Paris 2024 Olympics
Authors: Yiou Pascal , Cadiou Camille , Faranda Davide , Jézéquel Aglaé , Malhomme Nemo , Miloshevich George , Noyelle Robin , Pons Flavio , Robin Yoann , Vrac Mathieu
Published: November 2023

The Summer Olympic Games in 2024 will take place during the apex of the temperature seasonal cycle in the Paris Area. The mid-latitudes of the Northern hemisphere have witnessed a few intense heatwaves since the 2003 event. Those heatwaves have had environmental and health impacts, which often came as surprises. In this paper, we search for the most extreme heatwaves in Ile-de-France that are physically plausible, under climate change scenarios, for the decades around 2024. We circumvent the sampling limitation by applying a rare event algorithm on CMIP6 data to evaluate the range of such extremes. We find that the 2003 record can be exceeded by more than 4 °C in Ile-de-France before 2050, with a combination of prevailing anticyclonic conditions and cut-off lows. This study intends to raise awareness of those unprecedented events, against which our societies are ill-prepared, in spite of adaptation measures designed from previous events. Those results could be extended to other areas of the world.
A Cre-dependent massively parallel reporter assay allows for cell-type specific assessment of the functional effects of non-coding elements in vivo
Authors: Lagunas Tomas , Plassmeyer Stephen P. , Fischer Anthony D. , Friedman Ryan Z. , Rieger Michael A. , Selmanovic Din , Sarafinovska Simona , Sol Yvette K. , Kasper Michael J. , Fass Stuart B. , Aguilar Lucero Alessandra F. , An Joon-Yong , Sanders Stephan J. , Cohen Barak A. , Dougherty Joseph D.
Published: November 2023

The function of regulatory elements is highly dependent on the cellular context, and thus for understanding the function of elements associated with psychiatric diseases these would ideally be studied in neurons in a living brain. Massively Parallel Reporter Assays (MPRAs) are molecular genetic tools that enable functional screening of hundreds of predefined sequences in a single experiment. These assays have not yet been adapted to query specific cell types in vivo in a complex tissue like the mouse brain. Here, using a test-case 3′UTR MPRA library with genomic elements containing variants from autism patients, we developed a method to achieve reproducible measurements of element effects in vivo in a cell type-specific manner, using excitatory cortical neurons and striatal medium spiny neurons as test cases. This targeted technique should enable robust, functional annotation of genetic elements in the cellular contexts most relevant to psychiatric disease.
A fully 3D-printed versatile tumor-on-a-chip allows multi-drug screening and correlation with clinical outcomes for personalized medicine
Authors: Steinberg Eliana , Friedman Roy , Goldstein Yoel , Friedman Nethanel , Beharier Ofer , Demma Jonathan Abraham , Zamir Gideon , Hubert Ayala , Benny Ofra
Published: November 2023

Optimal clinical outcomes in cancer treatments could be achieved through the development of reliable, precise ex vivo tumor models that function as drug screening platforms for patient-targeted therapies. Microfluidic tumor-on-chip technology is emerging as a preferred tool since it enables the complex set-ups and recapitulation of the physiologically relevant physical microenvironment of tumors. In order to overcome the common hindrances encountered while using this technology, a fully 3D-printed device was developed that sustains patient-derived multicellular spheroids long enough to conduct multiple drug screening tests. This tool is both cost effective and possesses four necessary characteristics of effective microfluidic devices: transparency, biocompatibility, versatility, and sample accessibility. Compelling correlations which demonstrate a clinical proof of concept were found after testing and comparing different chemotherapies on tumor spheroids, derived from ten patients, to their clinical outcomes. This platform offers a potential solution for personalized medicine by functioning as a predictive drug-performance tool.