bluuebunny/crossref_metadata_2025_split huggingface dataset:
Methamphetamine (MA) use and MA-induced psychosis are associated with increasing aberrations in the compensatory immunoregulatory system, interleukin-1α, and CCL5 levels
Authors: Kalayasiri Rasmon , Dadwat Kanokwan , Thika Supaksorn , Sirivichayakul Sunee , Maes Michael 
Published: November 2023

AbstractThere are only a few studies reporting on the immunological profiles of methamphetamine (MA) use, MA dependency, or MA-induced psychosis (MAP). This study measured M1 macrophage, T helper (Th)-1, Th-2, growth factor, and chemokine profiles, as well as the immune inflammatory response system (IRS) and compensatory immunoregulatory system (CIRS) in peripheral blood samples from patients with MA use (n = 51), MA dependence (n = 47), and MAP (n = 43) in comparison with controls (n = 32). We discovered that persistent MA use had a robust immunosuppressive impact on all immunological profiles. The most reliable biomarker profile of MA use is the combination of substantial CIRS suppression and a rise in selected pro-inflammatory cytokines, namely CCL27 (CTACK), CCL11 (eotaxin), and interleukin (IL)-1α. In addition, MA dependency is associated with increased immunosuppression, as demonstrated by lower stem cell factor levels and higher IL-10 levels. MAP is related to a significant decrease in all immunological profiles, particularly CIRS, and an increase in CCL5 (RANTES), IL-1α, and IL-12p70 signaling. In conclusion, long-term MA use and dependency severely undermine immune homeostasis, whereas MAP may be the consequence of increased IL-1α – CCL5 signaling superimposed on strongly depleted CIRS and Th-1 functions. The widespread immunosuppression established in longstanding MA use may increase the likelihood of infectious and immune illness or exacerbate disorders such as hepatitis and AIDS. Furthermore, elevated levels of CCL5, CCL11, CCL27, IL-1α, and/or IL-12p70 may play a role in the peripheral (atherosclerosis, cutaneous inflammation, immune aberrations, hypospermatogenesis) and central (neuroinflammation, neurotoxic, neurodegenerative, depression, anxiety, and psychosis) side effects of MA use.
A reversible state of hypometabolism in a human cellular model of sporadic Parkinson’s disease
Authors: Schmidt Sebastian , Stautner Constantin , Vu Duc Tung , Heinz Alexander , Regensburger Martin , Karayel Ozge , Trümbach Dietrich , Artati Anna , Kaltenhäuser Sabine , Nassef Mohamed Zakaria , Hembach Sina , Steinert Letyfee , Winner Beate , Jürgen Winkler , Jastroch Martin , Luecken Malte D. , Theis Fabian J. , Westmeyer Gil Gregor , Adamski Jerzy , Mann Matthias , Hiller Karsten , Giesert Florian , Vogt Weisenhorn Daniela M. , Wurst Wolfgang 
Published: November 2023

AbstractSporadic Parkinson’s Disease (sPD) is a progressive neurodegenerative disorder caused by multiple genetic and environmental factors. Mitochondrial dysfunction is one contributing factor, but its role at different stages of disease progression is not fully understood. Here, we showed that neural precursor cells and dopaminergic neurons derived from induced pluripotent stem cells (hiPSCs) from sPD patients exhibited a hypometabolism. Further analysis based on transcriptomics, proteomics, and metabolomics identified the citric acid cycle, specifically the α-ketoglutarate dehydrogenase complex (OGDHC), as bottleneck in sPD metabolism. A follow-up study of the patients approximately 10 years after initial biopsy demonstrated a correlation between OGDHC activity in our cellular model and the disease progression. In addition, the alterations in cellular metabolism observed in our cellular model were restored by interfering with the enhanced SHH signal transduction in sPD. Thus, inhibiting overactive SHH signaling may have potential as neuroprotective therapy during early stages of sPD.
The social costs of tropical cyclones
Authors: Krichene Hazem , Vogt Thomas , Piontek Franziska , Geiger Tobias , Schötz Christof , Otto Christian 
Published: November 2023

AbstractTropical cyclones (TCs) can adversely affect economic development for more than a decade. Yet, these long-term effects are not accounted for in current estimates of the social cost of carbon (SCC), a key metric informing climate policy on the societal costs of greenhouse gas emissions. We here derive temperature-dependent damage functions for 41 TC-affected countries to quantify the country-level SCC induced by the persistent growth effects of damaging TCs. We find that accounting for TC impacts substantially increases the global SCC by more than 20%; median global SCC increases from US$ 173 to US$ 212 per tonne of CO2 under a middle-of-the-road future emission and socioeconomic development scenario. This increase is mainly driven by the strongly TC-affected major greenhouse gas emitting countries India, USA, China, Taiwan, and Japan. This suggests that the benefits of climate policies could currently be substantially underestimated. Adequately accounting for the damages of extreme weather events in policy evaluation may therefore help to prevent a critical lack of climate action.
A synaptic corollary discharge signal suppresses midbrain visual processing during saccade-like locomotion
Authors: Ali Mir Ahsan , Lischka Katharina , Preuss Stephanie J. , Trivedi Chintan A. , Bollmann Johann H. 
Published: November 2023

AbstractIn motor control, the brain not only sends motor commands to the periphery, but also generates concurrent internal signals known as corollary discharge (CD) that influence sensory information processing around the time of movement. CD signals are important for identifying sensory input arising from self-motion and to compensate for it, but the underlying mechanisms remain unclear. Using whole-cell patch clamp recordings from neurons in the zebrafish optic tectum, we discovered an inhibitory synaptic signal, temporally locked to spontaneous and visually driven locomotion. This motor-related inhibition was appropriately timed to counteract visually driven excitatory input arising from the fish’s own motion, and transiently suppressed tectal spiking activity. High-resolution calcium imaging revealed localized motor-related signals in the tectal neuropil and the upstream torus longitudinalis, suggesting that CD enters the tectum via this pathway. Together, our results show how visual processing is suppressed during self-motion by motor-related phasic inhibition. This may help explain perceptual saccadic suppression observed in many species.
An ultrasmall organic synapse for neuromorphic computing
Authors: Liu Shuzhi , Zeng Jianmin , Wu Zhixin , Hu Han , Xu Ao , Huang Xiaohe , Chen Weilin , Chen Qilai , Yu Zhe , Zhao Yinyu , Wang Rong , Han Tingting , Li Chao , Gao Pingqi , Kim Hyunwoo , Baik Seung Jae , Zhang Ruoyu , Zhang Zhang , Zhou Peng , Liu Gang 
Published: November 2023

AbstractHigh‐performance organic neuromorphic devices with miniaturized device size and computing capability are essential elements for developing brain‐inspired humanoid intelligence technique. However, due to the structural inhomogeneity of most organic materials, downscaling of such devices to nanoscale and their high‐density integration into compact matrices with reliable device performance remain challenging at the moment. Herein, based on the design of a semicrystalline polymer PBFCL10 with ordered structure to regulate dense and uniform formation of conductive nanofilaments, we realize an organic synapse with the smallest device dimension of 50 nm and highest integration size of 1 Kb reported thus far. The as‐fabricated PBFCL10 synapses can switch between 32 conductance states linearly with a high cycle‐to‐cycle uniformity of 98.89% and device‐to‐device uniformity of 99.71%, which are the best results of organic devices. A mixed-signal neuromorphic hardware system based on the organic neuromatrix and FPGA controller is implemented to execute spiking‐plasticity‐related algorithm for decision-making tasks.
ID1 expressing macrophages support cancer cell stemness and limit CD8+ T cell infiltration in colorectal cancer
Authors: Shang Shuang , Yang Chen , Chen Fei , Xiang Ren-shen , Zhang Huan , Dai Shu-yuan , Liu Jing , Lv Xiao-xi , Zhang Cheng , Liu Xiao-tong , Zhang Qi , Lu Shuai-bing , Song Jia-wei , Yu Jiao-jiao , Zhou Ji-chao , Zhang Xiao-wei , Cui Bing , Li Ping-ping , Zhu Sheng-tao , Zhang Hai-zeng , Hua Fang 
Published: November 2023

AbstractElimination of cancer stem cells (CSCs) and reinvigoration of antitumor immunity remain unmet challenges for cancer therapy. Tumor-associated macrophages (TAMs) constitute the prominant population of immune cells in tumor tissues, contributing to the formation of CSC niches and a suppressive immune microenvironment. Here, we report that high expression of inhibitor of differentiation 1 (ID1) in TAMs correlates with poor outcome in patients with colorectal cancer (CRC). ID1 expressing macrophages maintain cancer stemness and impede CD8+ T cell infiltration. Mechanistically, ID1 interacts with STAT1 to induce its cytoplasmic distribution and inhibits STAT1-mediated SerpinB2 and CCL4 transcription, two secretory factors responsible for cancer stemness inhibition and CD8+ T cell recruitment. Reducing ID1 expression ameliorates CRC progression and enhances tumor sensitivity to immunotherapy and chemotherapy. Collectively, our study highlights the pivotal role of ID1 in controlling the protumor phenotype of TAMs and paves the way for therapeutic targeting of ID1 in CRC.
Modular access to alkylgermanes via reductive germylative alkylation of activated olefins under nickel catalysis
Authors: Gu Rui , Feng Xiujuan , Bao Ming , Zhang Xuan 
Published: November 2023

AbstractCarbon-introducing difunctionalization of C-C double bonds enabled by transition-metal catalysis is one of most straightforward and efficient strategies to construct C-C and C-X bonds concurrently from readily available feedstocks towards structurally diverse molecules in one step; however, analogous difunctionalization for introducing germanium group and other functionalities remains elusive. Herein, we describe a nickel-catalyzed germylative alkylation of activated olefins with easily accessible primary, secondary and tertiary alkyl bromides and chlorogermanes as the electrophiles to form C-Ge and C-Calkyl bonds simultaneously. This method provides a modular and facile approach for the synthesis of a broad range of alkylgermanes with good functional group compatibility, and can be further applied to the late-stage modification of natural products and pharmaceuticals, as well as ligation of drug fragments. More importantly, this platform enables the expedient synthesis of germanium substituted ospemifene-Ge-OH, which shows improved properties compared to ospemifene in the treatment of breast cancer cells, demonstrating high potential of our protocol in drug development.
Immune-privileged tissues formed from immunologically cloaked mouse embryonic stem cells survive long term in allogeneic hosts
Authors: Harding Jeffrey , Vintersten-Nagy Kristina , Yang Huijuan , Tang Jean Kit , Shutova Maria , Jong Eric D. , Lee Ju Hee , Massumi Mohammad , Oussenko Tatiana , Izadifar Zohreh , Zhang Puzheng , Rogers Ian M. , Wheeler Michael B. , Lye Stephen J. , Sung Hoon-Ki , Li ChengJin , Izadifar Mohammad , Nagy Andras 
Published: November 2023

AbstractThe immunogenicity of transplanted allogeneic cells and tissues is a major hurdle to the advancement of cell therapies. Here we show that the overexpression of eight immunomodulatory transgenes (Pdl1, Cd200, Cd47, H2-M3, Fasl, Serpinb9, Ccl21 and Mfge8) in mouse embryonic stem cells (mESCs) is sufficient to immunologically ‘cloak’ the cells as well as tissues derived from them, allowing their survival for months in outbred and allogeneic inbred recipients. Overexpression of the human orthologues of these genes in human ESCs abolished the activation of allogeneic human peripheral blood mononuclear cells and their inflammatory responses. Moreover, by using the previously reported FailSafe transgene system, which transcriptionally links a gene essential for cell division with an inducible and cell-proliferation-dependent kill switch, we generated cloaked tissues from mESCs that served as immune-privileged subcutaneous sites that protected uncloaked allogeneic and xenogeneic cells from rejection in immune-competent hosts. The combination of cloaking and FailSafe technologies may allow for the generation of safe and allogeneically accepted cell lines and off-the-shelf cell products.
Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning
Authors: Nippa David F. , Atz Kenneth , Hohler Remo , Müller Alex T. , Marx Andreas , Bartelmus Christian , Wuitschik Georg , Marzuoli Irene , Jost Vera , Wolfard Jens , Binder Martin , Stepan Antonia F. , Konrad David B. , Grether Uwe , Martin Rainer E. , Schneider Gisbert 
Published: November 2023

AbstractLate-stage functionalization is an economical approach to optimize the properties of drug candidates. However, the chemical complexity of drug molecules often makes late-stage diversification challenging. To address this problem, a late-stage functionalization platform based on geometric deep learning and high-throughput reaction screening was developed. Considering borylation as a critical step in late-stage functionalization, the computational model predicted reaction yields for diverse reaction conditions with a mean absolute error margin of 4–5%, while the reactivity of novel reactions with known and unknown substrates was classified with a balanced accuracy of 92% and 67%, respectively. The regioselectivity of the major products was accurately captured with a classifier F-score of 67%. When applied to 23 diverse commercial drug molecules, the platform successfully identified numerous opportunities for structural diversification. The influence of steric and electronic information on model performance was quantified, and a comprehensive simple user-friendly reaction format was introduced that proved to be a key enabler for seamlessly integrating deep learning and high-throughput experimentation for late-stage functionalization.
Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA
Authors: Baek Minkyung , McHugh Ryan , Anishchenko Ivan , Jiang Hanlun , Baker David , DiMaio Frank 
Published: November 2023

AbstractProtein–RNA and protein–DNA complexes play critical roles in biology. Despite considerable recent advances in protein structure prediction, the prediction of the structures of protein–nucleic acid complexes without homology to known complexes is a largely unsolved problem. Here we extend the RoseTTAFold machine learning protein-structure-prediction approach to additionally predict nucleic acid and protein–nucleic acid complexes. We develop a single trained network, RoseTTAFoldNA, that rapidly produces three-dimensional structure models with confidence estimates for protein–DNA and protein–RNA complexes. Here we show that confident predictions have considerably higher accuracy than current state-of-the-art methods. RoseTTAFoldNA should be broadly useful for modeling the structure of naturally occurring protein–nucleic acid complexes, and for designing sequence-specific RNA and DNA-binding proteins.
Exploring the neural basis and modulating factors of implicit altercentric spatial perspective-taking with fNIRS
Authors: Ang Natania , Brucker Birgit , Rosenbaum David , Lachmair Martin , Dresler Thomas , Ehlis Ann-Christine , Gerjets Peter 
Published: November 2023

AbstractHumans spontaneously take the perspective of others when encoding spatial information in a scene, especially with agentive action cues present. This functional near-infrared spectroscopy (fNIRS) study explored how action observation influences implicit spatial perspective-taking (SPT) by adapting a left–right spatial judgment task to investigate whether transformation strategies underlying altercentric SPT can be predicted on the basis of cortical activation. Strategies associated with two opposing neurocognitive accounts (embodied versus disembodied) and their proposed neural correlates (human mirror neuron system; hMNS versus cognitive control network; CCN) are hypothesized. Exploratory analyses with 117 subjects uncover an interplay between perspective-taking and post-hoc factor, consistency of selection, in regions alluding to involvement of the CCN. Descriptively, inconsistent altercentric SPT elicited greater activation than consistent altercentric SPT and/or inconsistent egocentric SPT in the left inferior frontal gyrus (IFG), left dorsolateral prefrontal cortex (DLPFC) and left motor cortex (MC), but not the inferior parietal lobules (IPL). Despite the presence of grasping cues, spontaneous embodied strategies were not evident during implicit altercentric SPT. Instead, neural trends in the inconsistent subgroups (22 subjects; 13 altercentric; 9 egocentric) suggest that inconsistency in selection modulates the decision-making process and plausibly taps on deliberate and effortful disembodied strategies driven by the CCN. Implications for future research are discussed.
Traffic prediction in SDN for explainable QoS using deep learning approach
Authors: Wassie Getahun , Ding Jianguo , Wondie Yihenew 
Published: November 2023

AbstractThe radical increase of multimedia applications such as voice over Internet protocol (VOIP), image processing, and video-based applications require better quality of service (QoS). Therefore, traffic Predicting and explaining the prediction models is essential. However, elephant flows from those applications still needs to be improved to satisfy Internet users. Elephant flows lead to network congestion, resulting in packet loss, delay and inadequate QoS delivery. Recently, deep learning models become a good alternative for real-time traffic management. This research aims to design a traffic predicting model that can identify elephant flows to prevent network congestion in advance. Thus, we are motivated to develop elephant flow prediction models and explain those models explicitly for network administrators’ use in the SDN network. H2O, Deep Autoencoder, and autoML predicting algorithms, including XGBoost, GBM and GDF, were employed to develop the proposed model. The performance of Elephant flow prediction models scored 99.97%, 99.99%, and 100% in validation accuracy of under construction error of 0.0003952, 0.001697, and 0.00000408 using XGBoost, GBM, and GDF algorithms respectively. The models were also explicitly explained using Explainable Artificial Intelligence. Accordingly, packet size and byte size attributes need much attention to detect elephant flows.
New cytotoxic dammarane type saponins from Ziziphus spina-christi
Authors: Elmaidomy Abeer H. , El Zawily Amr , Salem Aliasger K. , Altemani Faisal H. , Algehainy Naseh A. , Altemani Abdullah H. , Rateb Mostafa E. , Abdelmohsen Usama Ramadan , Shady Nourhan Hisham 
Published: November 2023

AbstractCancer is the world's second-leading cause of death. Drug development efforts frequently focus on medicinal plants since they are a valuable source of anticancer medications. A phytochemical investigation of the edible Ziziphus spina-christi (F. Rhamnaceae) leaf extract afforded two new dammarane type saponins identified as christinin E and F (1, 2), along with the known compound christinin A (3). Different cancer cell lines, such as lung cancer (A549), glioblastoma (U87), breast cancer (MDA-MB-231), and colorectal carcinoma (CT-26) cell lines, were used to investigate the extracted compounds' cytotoxic properties. Our findings showed significant effects on all the tested cell lines at varying concentrations (1, 5, 10, and 20 µg/mL). The three compounds exhibited potent activity at low concentrations (< 10 μg/mL), as evidenced by their low IC50 values. To further investigate the complex relationships between these identified cancer-relevant biological targets and to identify critical targets in the pathogenesis of the disease, we turned to network pharmacology and in silico-based investigations. Following this, in silico-based analysis (e.g., inverse docking, ΔG calculation, and molecular dynamics simulation) was performed on the structures of the isolated compounds to identify additional potential targets for these compounds and their likely interactions with various signalling pathways relevant to this disease. Based on our findings, Z. spina-christi's compounds showed promise as potential anti-cancer therapeutic leads in the future.
Saliency of breast lesions in breast cancer detection using artificial intelligence
Authors: Pertuz Said , Ortega David , Suarez Érika , Cancino William , Africano Gerson , Rinta-Kiikka Irina , Arponen Otso , Paris Sara , Lozano Alfonso 
Published: November 2023

AbstractThe analysis of mammograms using artificial intelligence (AI) has shown great potential for assisting breast cancer screening. We use saliency maps to study the role of breast lesions in the decision-making process of AI systems for breast cancer detection in screening mammograms. We retrospectively collected mammograms from 191 women with screen-detected breast cancer and 191 healthy controls matched by age and mammographic system. Two radiologists manually segmented the breast lesions in the mammograms from CC and MLO views. We estimated the detection performance of four deep learning-based AI systems using the area under the ROC curve (AUC) with a 95% confidence interval (CI). We used automatic thresholding on saliency maps from the AI systems to identify the areas of interest on the mammograms. Finally, we measured the overlap between these areas of interest and the segmented breast lesions using Dice’s similarity coefficient (DSC). The detection performance of the AI systems ranged from low to moderate (AUCs from 0.525 to 0.694). The overlap between the areas of interest and the breast lesions was low for all the studied methods (median DSC from 4.2% to 38.0%). The AI system with the highest cancer detection performance (AUC = 0.694, CI 0.662–0.726) showed the lowest overlap (DSC = 4.2%) with breast lesions. The areas of interest found by saliency analysis of the AI systems showed poor overlap with breast lesions. These results suggest that AI systems with the highest performance do not solely rely on localized breast lesions for their decision-making in cancer detection; rather, they incorporate information from large image regions. This work contributes to the understanding of the role of breast lesions in cancer detection using AI.
COVID-19 vaccine uptake among people with HIV: identifying characteristics associated with vaccine hesitancy
Authors: Boschung Karol , Gill M. John , Krentz Hartmut B. , Dalere Jessica , Beckthold Brenda , Fonseca Kevin , Bakal Jeffrey A. , McMillan Jacqueline M. , Kanji Jamil , Lang Raynell 
Published: November 2023

AbstractPeople with HIV (PWH) are at increased risk of COVID-19 infection. Both Canadian (NACI) and US (CDC) guidelines recommend that all PWH receive at least 2 doses of COVID-19 vaccine, and a booster. We examined vaccination uptake among PWH in Southern Alberta, Canada. Among adult PWH, we evaluated COVID-19 vaccination uptake between December 2020 and August 2022. Poisson regression models with robust variance (approximating log binomial models) estimated crude and adjusted prevalence ratios (aPR) and 95% confidence intervals (CI) for receiving (1) any vs. no vaccine, and (2) primary series with booster (≥ 3 vaccines) versus primary series without booster. Among 1885 PWH, 10% received no COVID-19 vaccinations, 37% < 3 vaccines and 54% received ≥ 3 vaccines. Females (vs. males) were less likely to receive a vaccine booster. Receiving no COVID-19 vaccines was associated with White ethnicity, unsuppressed HIV viral load (> 200 copies/mL), and using illegal substances. Factors associated with decreased booster uptake included being younger, Black (vs. White) ethnicity, substance use, lower educational attainment, and having an unsuppressed HIV viral load. COVID-19 booster uptake among PWH does not meet vaccine guidelines, and receipt of vaccines is unevenly distributed. Booster uptake is lowest among young females and marginalized individuals. Focused outreach is necessary to close this gap.