bluuebunny/crossref_metadata_2025 huggingface dataset:
Protein structural transitions critically transform the network connectivity and viscoelasticity of RNA-binding protein condensates but RNA can prevent it
Authors: Tejedor Andres R. , Sanchez-Burgos Ignacio , Estevez-Espinosa Maria , Garaizar Adiran , Collepardo-Guevara Rosana , Ramirez Jorge , Espinosa Jorge R.
Published: September 2022

Biomolecular condensates, some of which are liquid-like during health, can age over time becoming gel-like pathological systems. One potential source of loss of liquid-like properties during ageing of RNA-binding protein condensates is the progressive formation of inter-proteinβ-sheets. To bridge microscopic understanding between accumulation of inter-proteinβ-sheets over time and the modulation of FUS and hnRNPA1 condensate viscoelasticity, we develop a multiscale simulation approach. Our method integrates atomistic simulations with sequence-dependent coarse-grained modelling of condensates that exhibit accumulation of inter-proteinβ-sheets over time. We reveal that inter-proteinβ-sheets notably increase condensate viscosity but does not transform the phase diagrams. Strikingly, the network of molecular connections within condensates is drastically altered, culminating in gelation when the network of strongβ-sheets fully percolates. However, high concentrations of RNA decelerate the emergence of inter-proteinβ-sheets. Our study uncovers molecular and kinetic factors explaining how the accumulation of inter-proteinβ-sheets can trigger liquid-to-solid transitions in condensates, and suggests a potential mechanism to slow such transitions down.
Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer
Authors: Stackpole Mary L. , Zeng Weihua , Li Shuo , Liu Chun-Chi , Zhou Yonggang , He Shanshan , Yeh Angela , Wang Ziye , Sun Fengzhu , Li Qingjiao , Yuan Zuyang , Yildirim Asli , Chen Pin-Jung , Winograd Paul , Tran Benjamin , Lee Yi-Te , Li Paul Shize , Noor Zorawar , Yokomizo Megumi , Ahuja Preeti , Zhu Yazhen , Tseng Hsian-Rong , Tomlinson James S. , Garon Edward , French Samuel , Magyar Clara E. , Dry Sarah , Lajonchere Clara , Geschwind Daniel , Choi Gina , Saab Sammy , Alber Frank , Wong Wing Hung , Dubinett Steven M. , Aberle Denise R. , Agopian Vatche , Han Steven-Huy B. , Ni Xiaohui , Li Wenyuan , Zhou Xianghong Jasmine
Published: September 2022

Early cancer detection by cell-free DNA faces multiple challenges: low fraction of tumor cell-free DNA, molecular heterogeneity of cancer, and sample sizes that are not sufficient to reflect diverse patient populations. Here, we develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of the cell-free DNA methylome (with > 12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our approach to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, allowing us to learn new features and expand to other cancer types as training cohorts grow.
Increased household transmission and immune escape of the SARS-CoV-2 Omicron compared to Delta variants
Authors: Jalali Neda , Brustad Hilde K. , Frigessi Arnoldo , MacDonald Emily A. , Meijerink Hinta , Feruglio Siri L. , Nygård Karin M. , Rø Gunnar , Madslien Elisabeth H. , de Blasio Birgitte Freiesleben
Published: September 2022

Understanding the epidemic growth of the novel SARS-CoV-2 Omicron variant is critical for public health. We compared the ten-day secondary attack rate (SAR) of the Omicron and Delta variants in households using Norwegian contact tracing data, December 2021 - January 2022. Omicron SAR was higher than Delta, with a relative risk (RR) of 1.41 (95% CI 1.27-1.56). We observed increased susceptibility to Omicron infection in household contacts compared to Delta, independent of contacts’ vaccination status. Among three-dose vaccinated contacts, the mean SAR was lower for both variants. We found increased Omicron transmissibility from primary cases to contacts in all vaccination groups, except 1-dose vaccinated, compared to Delta. Omicron SAR of three-dose vaccinated primary cases was high, 46% vs 11 % for Delta. In conclusion, three-dose vaccinated primary cases with Omicron infection can efficiently spread in households, while three-dose vaccinated contacts have a lower risk of being infected by Delta and Omicron.
Adversarial attacks and adversarial robustness in computational pathology
Authors: Ghaffari Laleh Narmin , Truhn Daniel , Veldhuizen Gregory Patrick , Han Tianyu , van Treeck Marko , Buelow Roman D. , Langer Rupert , Dislich Bastian , Boor Peter , Schulz Volkmar , Kather Jakob Nikolas
Published: September 2022

Artificial Intelligence (AI) can support diagnostic workflows in oncology by aiding diagnosis and providing biomarkers directly from routine pathology slides. However, AI applications are vulnerable to adversarial attacks. Hence, it is essential to quantify and mitigate this risk before widespread clinical use. Here, we show that convolutional neural networks (CNNs) are highly susceptible to white- and black-box adversarial attacks in clinically relevant weakly-supervised classification tasks. Adversarially robust training and dual batch normalization (DBN) are possible mitigation strategies but require precise knowledge of the type of attack used in the inference. We demonstrate that vision transformers (ViTs) perform equally well compared to CNNs at baseline, but are orders of magnitude more robust to white- and black-box attacks. At a mechanistic level, we show that this is associated with a more robust latent representation of clinically relevant categories in ViTs compared to CNNs. Our results are in line with previous theoretical studies and provide empirical evidence that ViTs are robust learners in computational pathology. This implies that large-scale rollout of AI models in computational pathology should rely on ViTs rather than CNN-based classifiers to provide inherent protection against perturbation of the input data, especially adversarial attacks.
TM9SF4 is an F-actin disassembly factor that promotes tumor progression and metastasis
Authors: Meng Zhaoyue , Li Zhichao , Xie Mingxu , Yu Hongyan , Jiang Liwen , Yao Xiaoqiang
Published: September 2022

F-actin dynamics is crucial for many fundamental properties of cancer cells, from cell-substrate adhesion to migration, invasion and metastasis. However, the regulatory mechanisms of actin dynamics are still incompletely understood. In this study, we demonstrate the function of a protein named TM9SF4 in regulating actin dynamics and controlling cancer cell motility and metastasis. We show that an N-terminal fragment (NTF) cleaved from TM9SF4 can directly bind to F-actin to induce actin oxidation at Cys374, consequently enhancing cofilin-mediated F-actin disassembly. Knockdown of TM9SF4 reduces cell migration and invasion in ovarian cancer cells A2780, SKOV3 and several high grade serous ovarian cancer lines (HGSOCs). In vivo, knockdown of TM9SF4 completely abolishes the tumor growth and metastasis in athymic nude mice. These data provide mechanistic insights into TM9SF4-mediated regulation of actin dynamics in ovarian cancer cells.
Proteomic characterization of gastric cancer response to chemotherapy and targeted therapy reveals potential therapeutic strategies
Authors: Li Yan , Xu Chen , Wang Bing , Xu Fujiang , Ma Fahan , Qu Yuanyuan , Jiang Dongxian , Li Kai , Feng Jinwen , Tian Sha , Wu Xiaohui , Wang Yunzhi , Liu Yang , Qin Zhaoyu , Liu Yalan , Qin Jing , Song Qi , Zhang Xiaolei , Sujie Akesu , Huang Jie , Liu Tianshu , Shen Kuntang , Zhao Jian-Yuan , Hou Yingyong , Ding Chen
Published: September 2022

Chemotherapy and targeted therapy are the major treatments for gastric cancer (GC), but drug resistance limits its effectiveness. Here, we profile the proteome of 206 tumor tissues from patients with GC undergoing either chemotherapy or anti-HER2-based therapy. Proteome-based classification reveals four subtypes (G-I–G-IV) related to different clinical and molecular features. MSI-sig high GC patients benefit from docetaxel combination treatment, accompanied by anticancer immune response. Further study reveals patients with high T cell receptor signaling respond to anti-HER2-based therapy; while activation of extracellular matrix/PI3K-AKT pathway impair anti-tumor effect of trastuzumab. We observe CTSE functions as a cell intrinsic enhancer of chemosensitivity of docetaxel, whereas TKTL1 functions as an attenuator. Finally, we develop prognostic models with high accuracy to predict therapeutic response, further validated in an independent validation cohort. This study provides a rich resource for investigating the mechanisms and indicators of chemotherapy and targeted therapy in GC.
Bacteriophage-antibiotic combination therapy against extensively drug-resistant Pseudomonas aeruginosa infection to allow liver transplantation in a toddler
Authors: Van Nieuwenhuyse Brieuc , Van der Linden Dimitri , Chatzis Olga , Lood Cédric , Wagemans Jeroen , Lavigne Rob , Schroven Kaat , Paeshuyse Jan , de Magnée Catherine , Sokal Etienne , Stéphenne Xavier , Scheers Isabelle , Rodriguez-Villalobos Hector , Djebara Sarah , Merabishvili Maya , Soentjens Patrick , Pirnay Jean-Paul
Published: September 2022

Post-operative bacterial infections are a leading cause of mortality and morbidity after ongoing liver transplantation. Bacteria causing these infections in the hospital setting can exhibit high degrees of resistance to multiple types of antibiotics, which leads to major therapeutic hurdles. Alternate ways of treating these antibiotic-resistant infections are thus urgently needed. Phage therapy is one of them and consists in using selected bacteriophage viruses – viruses who specifically prey on bacteria, naturally found in various environmental samples – as bactericidal agents in replacement or in combination with antibiotics. The use of phage therapy raises various research questions to further characterize what determines therapeutic success or failure. In this work, we report the story of a toddler who suffered from extensively drug-resistant Pseudomonas aeruginosa sepsis after liver transplantation. He was treated by a bacteriophage-antibiotic intravenous combination therapy for 86 days. This salvage therapy was well tolerated, without antibody-mediated phage neutralization. It was associated with objective clinical and microbiological improvement, eventually allowing for liver retransplantation and complete resolution of all infections. Clear in vitro phage-antibiotic synergies were observed. The occurrence of bacterial phage resistance did not result in therapeutic failure, possibly due to phage-induced virulence tradeoffs, which we investigated in different experimental models.
Genome-wide association study identifies a gene responsible for temperature-dependent rice germination
Authors: Yoshida Hideki , Hirano Ko , Yano Kenji , Wang Fanmiao , Mori Masaki , Kawamura Mayuko , Koketsu Eriko , Hattori Masako , Ordonio Reynante Lacsamana , Huang Peng , Yamamoto Eiji , Matsuoka Makoto
Published: September 2022

Environment is an important determinant of agricultural productivity; therefore, crops have been bred with traits adapted to their environment. It is assumed that the physiology of seed germination is optimised for various climatic conditions. Here, to understand the genetic basis underlying seed germination, we conduct a genome-wide association study considering genotype-by-environment interactions on the germination rate of Japanese rice cultivars under different temperature conditions. We find that a 4 bp InDel in one of the 14-3-3 family genes, GF14h, preferentially changes the germination rate of rice under optimum temperature conditions. The GF14h protein constitutes a transcriptional regulatory module with a bZIP-type transcription factor, OREB1, and a florigen-like protein, MOTHER OF FT AND TFL 2, to control the germination rate by regulating abscisic acid (ABA)-responsive genes. The GF14h loss-of-function allele enhances ABA signalling and reduces the germination rate. This allele is found in rice varieties grown in the northern area and in modern cultivars of Japan and China, suggesting that it contributes to the geographical adaptation of rice. This study demonstrates the complicated molecular system involved in the regulation of seed germination in response to temperature, which has allowed rice to be grown in various geographical locations.
Regain flood adaptation in rice through a 14-3-3 protein OsGF14h
Authors: Sun Jian , Zhang Guangchen , Cui Zhibo , Kong Ximan , Yu Xiaoyu , Gui Rui , Han Yuqing , Li Zhuan , Lang Hong , Hua Yuchen , Zhang Xuemin , Xu Quan , Tang Liang , Xu Zhengjin , Ma Dianrong , Chen Wenfu
Published: September 2022

Contemporary climatic stress seriously affects rice production. Unfortunately, long-term domestication and improvement modified the phytohormones network to achieve the production needs of cultivated rice, thus leading to a decrease in adaptation. Here, we identify a 14-3-3 protein-coding gene OsGF14h in weedy rice that confers anaerobic germination and anaerobic seedling development tolerance. OsGF14h acts as a signal switch to balance ABA signaling and GA biosynthesis by interacting with the transcription factors OsHOX3 and OsVP1, thereby boosting the seeding rate from 13.5% to 60.5% for anaerobic sensitive variety under flooded direct-seeded conditions. Meanwhile, OsGF14h co-inheritance with the Rc (red pericarp gene) promotes divergence between temperate japonica cultivated rice and temperate japonica weedy rice through artificial and natural selection. Our study retrieves a superior allele that has been lost during modern japonica rice improvement and provides a fine-tuning tool to improve flood adaptation for elite rice varieties.
MicroRNA-7 regulates melanocortin circuits involved in mammalian energy homeostasis
Authors: LaPierre Mary P. , Lawler Katherine , Godbersen Svenja , Farooqi I. Sadaf , Stoffel Markus
Published: September 2022

MicroRNAs (miRNAs) modulate physiological responses by repressing the expression of gene networks. We found that global deletion of microRNA-7 (miR-7), the most enriched miRNA in the hypothalamus, causes obesity in mice. Targeted deletion of miR-7 in Single-minded homolog 1 (Sim1) neurons, a critical component of the hypothalamic melanocortin pathway, causes hyperphagia, obesity and increased linear growth, mirroring Sim1 and Melanocortin-4 receptor (MC4R) haplo-insufficiency in mice and humans. We identified Snca (α-Synuclein) and Igsf8 (Immunoglobulin Superfamily Member 8) as miR-7 target genes that act in Sim1 neurons to regulate body weight and endocrine axes. In humans, MIR-7-1 is located in the last intron of HNRNPK, whose promoter drives the expression of both genes. Genetic variants at the HNRNPK locus that reduce its expression are associated with increased height and truncal fat mass. These findings demonstrate that miR-7 suppresses gene networks involved in the hypothalamic melanocortin pathway to regulate mammalian energy homeostasis.
Deciphering microbial gene function using natural language processing
Authors: Miller Danielle , Stern Adi , Burstein David
Published: September 2022

Revealing the function of uncharacterized genes is a fundamental challenge in an era of ever-increasing volumes of sequencing data. Here, we present a concept for tackling this challenge using deep learning methodologies adopted from natural language processing (NLP). We repurpose NLP algorithms to model “gene semantics” based on a biological corpus of more than 360 million microbial genes within their genomic context. We use the language models to predict functional categories for 56,617 genes and find that out of 1369 genes associated with recently discovered defense systems, 98% are inferred correctly. We then systematically evaluate the “discovery potential” of different functional categories, pinpointing those with the most genes yet to be characterized. Finally, we demonstrate our method’s ability to discover systems associated with microbial interaction and defense. Our results highlight that combining microbial genomics and language models is a promising avenue for revealing gene functions in microbes.
Coherent dynamics of multi-spin V$${}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ center in hexagonal boron nitride
Authors: Liu Wei , Ivády Viktor , Li Zhi-Peng , Yang Yuan-Ze , Yu Shang , Meng Yu , Wang Zhao-An , Guo Nai-Jie , Yan Fei-Fei , Li Qiang , Wang Jun-Feng , Xu Jin-Shi , Liu Xiao , Zhou Zong-Quan , Dong Yang , Chen Xiang-Dong , Sun Fang-Wen , Wang Yi-Tao , Tang Jian-Shun , Gali Adam , Li Chuan-Feng , Guo Guang-Can
Published: September 2022

Hexagonal boron nitride (hBN) has recently been demonstrated to contain optically polarized and detected electron spins that can be utilized for implementing qubits and quantum sensors in nanolayered-devices. Understanding the coherent dynamics of microwave driven spins in hBN is of crucial importance for advancing these emerging new technologies. Here, we demonstrate and study the Rabi oscillation and related phenomena of a negatively charged boron vacancy (V$${}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$

B

−

) spin ensemble in hBN. We report on different dynamics of the V$${}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$

B

−

spins at weak and strong magnetic fields. In the former case the defect behaves like a single electron spin system, while in the latter case it behaves like a multi-spin system exhibiting multiple-frequency dynamical oscillation as beat in the Ramsey fringes. We also carry out theoretical simulations for the spin dynamics of V$${}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$

B

−

and reveal that the nuclear spins can be driven via the strong electron nuclear coupling existing in V$${}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$

B

−

center, which can be modulated by the magnetic field and microwave field.
Spatiotemporal organisation of protein processing in the kidney
Authors: Polesel Marcello , Kaminska Monika , Haenni Dominik , Bugarski Milica , Schuh Claus , Jankovic Nevena , Kaech Andres , Mateos Jose M. , Berquez Marine , Hall Andrew M.
Published: September 2022

The kidney regulates plasma protein levels by eliminating them from the circulation. Proteins filtered by glomeruli are endocytosed and degraded in the proximal tubule and defects in this process result in tubular proteinuria, an important clinical biomarker. However, the spatiotemporal organization of renal protein metabolism in vivo was previously unclear. Here, using functional probes and intravital microscopy, we track the fate of filtered proteins in real time in living mice, and map specialized processing to tubular structures with singular value decomposition analysis and three-dimensional electron microscopy. We reveal that degradation of proteins requires sequential, coordinated activity of distinct tubular sub-segments, each adapted to specific tasks. Moreover, we leverage this approach to pinpoint the nature of endo-lysosomal disorders in disease models, and show that compensatory uptake in later regions of the proximal tubule limits urinary protein loss. This means that measurement of proteinuria likely underestimates severity of endocytotic defects in patients.
Association between formal thought disorder and cannabis use: a systematic review and meta-analysis
Authors: Argote Mathilde , Sescousse Guillaume , Brunelin Jérôme , Fakra Eric , Nourredine Mikail , Rolland Benjamin
Published: September 2022

Formal thought disorder (FTD) is a multidimensional syndrome mainly occurring along the psychosis continuum. Cannabis use is known to increase symptoms of psychosis, particularly positive symptoms. However, the impact of cannabis use on FTD in individuals presenting symptoms along the psychosis continuum remains unclear. To address this knowledge gap, we conducted a meta-analysis examining the association between cannabis use and FTD in those individuals. We hypothesized that cannabis would worsen FTD. We conducted a systematic search of the PubMed, ScienceDirect, PsycINFO, Web of Science, Embase and Google Scholar databases up to July 2022. The results were collated through a random-effects model using the statistical software R. Reference lists of included studies were searched for additional relevant publications. Nineteen studies were included, totalling 1840 cannabis users and 3351 non-cannabis users. The severity of FTD was found to be higher in cannabis users (SMD = 0.21, 95%CI [0.12–0.29], p = 0.00009). Subgroup analyses revealed that FTD severity was increased among cannabis users, regardless of the disorder severity: healthy individuals (SMD = 0.19, 95%CI [0.05–0.33], p = 0.02); patients with first-episode psychosis (SMD = 0.21, 95%CI [0.01–0.41], p = 0.04); patients with schizophrenia (SMD = 0.25, 95%CI [0.11–0.38], p = 0.005). Between-group differences were not significant. In line with its already known effect on positive symptoms in psychosis, cannabis use appears to be associated with increased FTD severity all along the psychosis continuum. Future research should consider potential confounding variables such as other substance use disorders and explore how FTD dimensions are impacted by cannabis use.
Analysis of the Human Protein Atlas Weakly Supervised Single-Cell Classification competition
Authors: Le Trang , Winsnes Casper F. , Axelsson Ulrika , Xu Hao , Mohanakrishnan Kaimal Jayasankar , Mahdessian Diana , Dai Shubin , Makarov Ilya S. , Ostankovich Vladislav , Xu Yang , Benhamou Eric , Henkel Christof , Solovyev Roman A. , Banić Nikola , Bošnjak Vito , Bošnjak Ana , Miličević Andrija , Ouyang Wei , Lundberg Emma
Published: September 2022

While spatial proteomics by fluorescence imaging has quickly become an essential discovery tool for researchers, fast and scalable methods to classify and embed single-cell protein distributions in such images are lacking. Here, we present the design and analysis of the results from the competition Human Protein Atlas – Single-Cell Classification hosted on the Kaggle platform. This represents a crowd-sourced competition to develop machine learning models trained on limited annotations to label single-cell protein patterns in fluorescent images. The particular challenges of this competition include class imbalance, weak labels and multi-label classification, prompting competitors to apply a wide range of approaches in their solutions. The winning models serve as the first subcellular omics tools that can annotate single-cell locations, extract single-cell features and capture cellular dynamics.
Economic estimation of Bitcoin mining’s climate damages demonstrates closer resemblance to digital crude than digital gold
Authors: Jones Benjamin A. , Goodkind Andrew L. , Berrens Robert P.
Published: September 2022

This paper provides economic estimates of the energy-related climate damages of mining Bitcoin (BTC), the dominant proof-of-work cryptocurrency. We provide three sustainability criteria for signaling when the climate damages may be unsustainable. BTC mining fails all three. We find that for 2016–2021: (i) per coin climate damages from BTC were increasing, rather than decreasing with industry maturation; (ii) during certain time periods, BTC climate damages exceed the price of each coin created; (iii) on average, each $1 in BTC market value created was responsible for $0.35 in global climate damages, which as a share of market value is in the range between beef production and crude oil burned as gasoline, and an order-of-magnitude higher than wind and solar power. Taken together, these results represent a set of sustainability red flags. While proponents have offered BTC as representing “digital gold,” from a climate damages perspective it operates more like “digital crude”.
Identification of novel differentially expressed genes in type 1 diabetes mellitus complications using transcriptomic profiling of UAE patients: a multicenter study
Authors: Mussa Bashair M. , Venkatachalam Thenmozhi , Srivastava Ankita , Al-Habshi Abeer , Abdelgadir Elamin , Bashier Alaaeldin , Al Awadi Fatheya , Hafidh Khadija , Hamoudi Rifat , Abusnana Salah
Published: September 2022

Type 1 diabetes mellitus (T1DM) is a chronic metabolic disorder that mainly affects children and young adults. It is associated with debilitating and long-life complications. Therefore, understanding the factors that lead to the onset and development of these complications is crucial. To our knowledge this is the first study that attempts to identify the common differentially expressed genes (DEGs) in T1DM complications using whole transcriptomic profiling in United Arab Emirates (UAE) patients. The present multicenter study was conducted in different hospitals in UAE including University Hospital Sharjah, Dubai Hospital and Rashid Hospital. A total of fifty-eight Emirati participants aged above 18 years and with a BMI < 25 kg/m2 were recruited and forty-five of these participants had a confirmed diagnosis of T1DM. Five groups of complications associated with the latter were identified including hyperlipidemia, neuropathy, ketoacidosis, hypothyroidism and polycystic ovary syndrome (PCOS). A comprehensive whole transcriptomic analysis using NGS was conducted. The outcomes of the study revealed the common DEGs between T1DM without complications and T1DM with different complications. The results revealed seven common candidate DEGs, SPINK9, TRDN, PVRL4, MYO3A, PDLIM1, KIAA1614 and GRP were upregulated in T1DM complications with significant increase in expression of SPINK9 (Fold change: 5.28, 3.79, 5.20, 3.79, 5.20) and MYO3A (Fold change: 4.14, 6.11, 2.60, 4.33, 4.49) in hyperlipidemia, neuropathy, ketoacidosis, hypothyroidism and PCOS, respectively. In addition, functional pathways of ion transport, mineral absorption and cytosolic calcium concentration were involved in regulation of candidate upregulated genes related to neuropathy, ketoacidosis and PCOS, respectively. The findings of this study represent a novel reference warranting further studies to shed light on the causative genetic factors that are involved in the onset and development of T1DM complications.
Weak-keys and key-recovery attack for $$\text{ TinyJAMBU }$$
Authors: Dutta Pranjal , Rajasree Mahesh Sreekumar , Sarkar Santanu
Published: September 2022

In this paper, we study NIST lightweight 3rd round candidate $$\text{ TinyJAMBU }$$

TinyJAMBU

. The core component of $$\text{ TinyJAMBU }$$

TinyJAMBU

is the keyed permutation $$\mathcal {P}_n$$

P
n

, which is based on a non-linear feedback shift register. By analysing this permutation carefully, we are able to find good cubes that are used to build distinguishers in the weak-key setting. In particular, we show that there are at least $$2^{108}$$

2
108

keys for which TinyJAMBU can be distinguished from a random source for up to 476 rounds. These distinguishers outperform the best-known distinguishers, which were proposed in ‘Scientific Reports - Nature’ by Teng et al. We are the first to study the exact degree of the feedback polynomial $$\mathcal {P}_n$$

P
n

in the nonce variables. This helped us in concluding that $$\text{ TinyJAMBU }$$

TinyJAMBU

with more than 445 rounds is secure against distinguishers using 32 sized cubes in the normal setting. Finally, we give new key-recovery attacks against $$\text{ TinyJAMBU }$$

TinyJAMBU

using the concepts of monomial trail presented by Hu et al. at ASIACRYPT 2020. Our attacks are unlikely to jeopardise the security of the entire 640 rounds $$\text{ TinyJAMBU }$$

TinyJAMBU

, but we strongly anticipate that they will shed new lights on the cipher’s security.
Selection of a stealthy and harmful attack function in discrete event systems
Authors: Zhang Qi , Seatzu Carla , Li Zhiwu , Giua Alessandro
Published: September 2022

In this paper we consider the problem of joint state estimation under attack in partially-observed discrete event systems. An operator observes the evolution of the plant to evaluate its current states. The attacker may tamper with the sensor readings received by the operator inserting dummy events or erasing real events that have occurred in the plant with the goal of preventing the operator from computing the correct state estimation. An attack function is said to be harmful if the state estimation consistent with the correct observation and the state estimation consistent with the corrupted observation satisfy a given misleading relation. On the basis of an automaton called joint estimator, we show how to compute a supremal stealthy joint subestimator that allows the attacker to remain stealthy, no matter what the future evolution of the plant is. Finally, we show how to select a stealthy and harmful attack function based on such a subestimator.
Fuzzy-clustering and fuzzy network based interpretable fuzzy model for prediction
Authors: Wang Xiaowei , Chen Yanqiao , Jin Jiashan , Zhang Baohua
Published: September 2022

Interpretability is the dominant feature of a fuzzy model in security-oriented fields. Traditionally fuzzy models based on expert knowledge have obtained well interpretation innately but imprecisely. Numerical data based fuzzy models perform well in precision but not necessarily in interpretation. To utilize the expert knowledge and numerical data in a fuzzy model synchronously, this paper proposed a hybrid fuzzy c-means (FCM) clustering algorithm and Fuzzy Network (FN) method-based model for prediction. The Mamdani rule-based structure of the proposed model is identified based on FCM algorithm from data and by expert-system method from expert knowledge, both of which are combined by FN method. Particle swarm optimization (PSO) algorithm is utilized to optimize the fuzzy set parameters. We tested the proposed model on 6 real datasets comparing the results with the ones obtained by using FCM algorithm. The results showed that our model performed best in interpretability, transparency, and accuracy.
Changes in preterm birth and birthweight during the SARS-CoV-2 pandemic: a nationwide study in South Korea
Authors: Hwang Jeongeun , Moon Seokjoo , Cho Kyu-Dong , Oh Min-Jeong , Hong Su Jung , Cho Geum Joon
Published: September 2022

Birthweight is a strong determinant of a neonate’s health. The SARS-CoV-2 pandemic’s impact on birthweight has not been investigated in-depth, with inconsistent conclusions from initial studies. To assess changes in preterm birth and inappropriate birthweight between the SARS-CoV-2 pandemic and pre-pandemic periods. A nationwide birth micro-data consisted with exhaustive census of all births in 2011–2020 in South Korea was accessed to examine whether the mean birthweight and rates of under/overweight births changed significantly during the SARS-CoV-2 pandemic year (2020) compared to those of the pre-pandemic period (2011–2019). A total of 3,736,447 singleton births were analyzed. Preterm birth was defined as < 37 weeks of gestation. Low birthweight (LBW) and macrosomia were defined as birthweights < 2.5 kg and ≥ 4.0 kg, respectively. Small for gestational age (SGA) and large for gestational age (LGA) were defined as birthweights below the 10th and above 90th percentiles for sex and gestational age, respectively. Inappropriate birthweight was defined as one or more LBW, macrosomia, SGA, or LGA. Generalized linear models predicted birth outcomes and were adjusted for parental age and education level, marital status, parity, gestational age, and months from January 2011. There were 3,481,423 and 255,024 singleton births during the pre-pandemic and pandemic periods, respectively. Multivariable generalized linear models estimated negative associations between the pandemic and preterm birth (odds ratio [OR], 0.968; 95% confidence interval [CI] 0.958–0.978), LBW (OR: 0.967, 95% CI 0.956–0.979), macrosomia (OR: 0.899, 95% CI 0.886–0.912), SGA (OR: 0.974, 95% CI 0.964–0.983), LGA (OR: 0.952, 95% CI 0.945–0.959), and inappropriate birthweight (OR: 0.958, 95% CI 0.952–0.963), indicating a decline during the pandemic compared to pre-pandemic period. An 8.98 g decrease in birthweight (95% CI 7.98–9.99) was estimated during the pandemic. This is the largest and comprehensive nationwide study to date on the impact of the SARS-CoV-2 pandemic on preterm birth and inappropriate birthweight. Birth during the pandemic was associated with lower odds of being preterm, underweight, and overweight. Further studies are required to understand the dynamics underlying this phenomenon.
The compliance of head-mounted industrial PPE by using deep learning object detectors
Authors: Isailovic Velibor , Peulic Aleksandar , Djapan Marko , Savkovic Marija , Vukicevic Arso M.
Published: September 2022

The compliance of industrial personal protective equipment (PPE) still represents a challenging problem considering size of industrial halls and number of employees that operate within them. Since there is a high variability of PPE types/designs that could be used for protecting various body parts and physiological functions, this study was focused on assessing the use of computer vision algorithms to automate the compliance of head-mounted PPE. As a solution, we propose a pipeline that couples the head ROI estimation with the PPE detection. Compared to alternative approaches, it excludes false positive cases while it largely speeds up data collection and labeling. A comprehensive dataset was created by merging public datasets PictorPPE and Roboflow with author’s collected images, containing twelve different types of PPE was used for the development and assessment of three deep learning architectures (Faster R-CNN, MobileNetV2-SSD and YOLOv5)—which in literature were studied only separately. The obtained results indicated that various deep learning architectures reached different performances for the compliance of various PPE types—while the YOLOv5 slightly outperformed considered alternatives (precision 0.920 ± 0.147, and recall 0.611 ± 0.287). It is concluded that further studies on the topic should invest more effort into assessing various deep learning architectures in order to objectively find the optimal ones for the compliance of a particular PPE type. Considering the present technological and data privacy barriers, the proposed solution may be applicable for the PPE compliance at certain checkpoints where employees can confirm their identity.
Ultra-fast green microwave assisted synthesis of NaFePO4-C nanocomposites for sodium ion batteries and supercapacitors
Authors: Wazeer Wael , Nabil Marwa M. , Feteha Mohamed , Soliman Moataz B. , Kashyout Abd El-Hady B.
Published: September 2022

Sodium ion batteries are favored in stationary and large scale power storage due to their low cost and nontoxicity. As the lithium is replaced with sodium due to the cost motive, a cheap processing method is needed to maintain the cell price as low as possible. We report an ultra-fast synthesis method that utilizes the high microwave absorbance of silicon carbide content in rice straw ash. Amorphous/maricite mixtures of sodium iron phosphates-carbon composites (NaFePO4-C) are synthesized, crystallized, and carbon coated using one-step microwave heating. The sodium ion electroactive composites are prepared using different microwave heating durations ranging from 30 to 100 s. High purity inert gases are not needed during synthesis, processing, and even at cell assembly. The materials are characterized by elemental analysis techniques, X-ray diffraction (XRD), scanning/transmission electron microscope (SEM/TEM), and Raman spectroscopy. The electrochemical performance of the synthesized nanocomposites is examined as sodium ion battery cathode and as symmetric supercapacitors. The optimum synthesis time is 60 s for the application as sodium ion batteries and as a supercapacitor. The maximum specific capacity is 108.4 mA h g−1 at 0.2 C in the case of using it as a battery cathode. While the capacitance is 86 F g−1 at 0.5 A g−1 as a supercapacitor. The capacity retention is 92.85% after 40 cycles at 0.2 C as sodium ion battery electrode. For supercapacitor, the capacity retention is 81.7% after 1000 cycles.
Extraction of sensing data for desired scent impressions using mass spectra of odorant molecules
Authors: Debnath Tanoy , Nakamoto Takamichi
Published: September 2022

Most of the olfactory perception works focused on forward prediction of odor impression, for example, given an odorant’s molecular structure parameters or the sensing data predict its odor impression. So far, mapping of mass spectrum of odorant molecules into the odor perception space (binary or continuous sensory space) has been successfully performed. However, it is difficult to predict odorant’s sensing data associated with binary odor descriptors (e.g., minty, peach, vanilla etc.). In this study, we have proposed a method to extract the corresponding sensing data (mass spectrum as sensing data) for a desired scent impression although one-to-one relationships are not usually guaranteed. Our target is to extract the sensing data for a given odor descriptor that will help perfumers to create scent. This study is first report for predicting sensing data for a given binary odor descriptor.
Variability of coil inductance measurements inside an interleaving structure
Authors: Mocholí Antonio , Mocholí Ferran , Milián-Sánchez Víctor , Guerra-Carmenate José , Iglesias-Martínez Miguel E. , Fernández de Córdoba Pedro , Castro-Palacio Juan C. , Sahu Sarira , Monsoriu Juan A. , Lorduy María , Gallardo Sergio , Verdú Gumersindo , Kolombet Valeriy A. , Panchelyuga Victor A.
Published: September 2022

The present article is a continuation of our previous works on the anomalies in the decay rates and the capacitance measurements inside a modified Faraday cage. Here we present the anomalous variations in the measurements of inductance when a coil is placed inside an interleaving structure of metal and organic material. The fluctuation in the inductance values was found to be in the range − 0.007 to 0.018 mH. Additionally, it was observed that the temperature coefficient which was 0.0062 mH/°C initially jumped to two distinct levels, 0.0095 mH/°C and 0.0145 mH/°C, respectively. A multiple factor analysis of our results revealed a very strong correlation (R2 = 95.2%) between the inductance and the combination of the temperature and the relative humidity both measured inside the cage, next to the inductor.
Deep language algorithms predict semantic comprehension from brain activity
Authors: Caucheteux Charlotte , Gramfort Alexandre , King Jean-Rémi
Published: September 2022

Deep language algorithms, like GPT-2, have demonstrated remarkable abilities to process text, and now constitute the backbone of automatic translation, summarization and dialogue. However, whether these models encode information that relates to human comprehension still remains controversial. Here, we show that the representations of GPT-2 not only map onto the brain responses to spoken stories, but they also predict the extent to which subjects understand the corresponding narratives. To this end, we analyze 101 subjects recorded with functional Magnetic Resonance Imaging while listening to 70 min of short stories. We then fit a linear mapping model to predict brain activity from GPT-2’s activations. Finally, we show that this mapping reliably correlates ($$\mathcal {R}=0.50, p<10^{-15}$$R=0.50,p<10-15) with subjects’ comprehension scores as assessed for each story. This effect peaks in the angular, medial temporal and supra-marginal gyri, and is best accounted for by the long-distance dependencies generated in the deep layers of GPT-2. Overall, this study shows how deep language models help clarify the brain computations underlying language comprehension.
Safety and outcomes of short-term use of peripheral vasoactive infusions in critically ill paediatric population in the emergency department
Authors: Yeong Y. Q. , Chan J. M. F. , Chan J. K. Y. , Huang H. L. , Ong G. Y.
Published: September 2022

Early restoration of oxygen delivery to end organs in paediatric patients experiencing shock states is critical to optimizing outcomes. However, obtaining central access in paediatric patients may be challenging in non-intensive care settings. There is limited literature on the use of peripheral vasoactive infusions in the initial resuscitation of paediatric patients in the emergency department. The aims of this study were to report the associated complications of peripheral vasoactive infusions and describe our local experience on its use. This was a single-centre, retrospective study on all paediatric patients who received peripheral vasoactive infusions at our paediatric emergency department from 2009 to 2016. 65 patients were included in this study. No patients had any local or regional complications. The mean patient age was 8.29 years old (± 5.99). The most frequent diagnosis was septic shock (45, 69.2%). Dopamine was the most used peripheral vasoactive agent (71.2%). The median time to central agents was 2 h (IQR 1–4). 16(24.2%) received multiple peripheral infusions. We reported no complications of peripheral vasoactive infusions. Its use could serve as a bridge till central access is obtained. Considerations on the use of multiple peripheral vasoactive infusions in the emergency department setting needs further research.
Assessing momentary relaxation using the Relaxation State Questionnaire (RSQ)
Authors: Steghaus Sarah , Poth Christian H.
Published: September 2022

Stress is ubiquitous in everyday life and hazardous for mental and physical health. To prevent or ameliorate stress-related disease, relaxation exercises aim to counteract stress by inducing short-lasting states of relaxation on a regular basis. Critically, current assessments capture the mid- and long-term consequences of relaxation, however, cannot measure its short-term effects on an individual’s momentary psychological state. To address this problem, we developed the Relaxation State Questionnaire (RSQ). We assessed the psychometric quality of the questionnaire by investigating its item properties, reliability, and validity in an online study with 92 participants. Construct validity was examined through correlations with the Perceived Stress Questionnaire (PSQ; Fliege in https://doi.org/10.23668/PSYCHARCHIVES.2889, 2009). An exploratory factor analysis revealed four factors capturing the momentary state of muscle tension, sleepiness, cardiovascular activity, and general relaxation. In a second online study with 99 participants, we conducted a confirmatory factor analysis. Results revealed high item loadings (0.70–0.91), excellent reliability (α = 0.86) and excellent fit indices, and a good construct validity of the RSQ. These findings establish the RSQ as a tool to measure momentary states of relaxation. As such, the RSQ opens up research of the immediate subjective effects and the effectiveness of relaxation exercises.
Varactor-tuned wideband band-pass filter for 5G NR frequency bands n77, n79 and 5G Wi-Fi
Authors: Golestanifar Alireza , Karimi Gholamreza , Lalbakhsh Ali
Published: September 2022

A wide-band band-pass filter (BPF) using coupled lines, rectangular stubs and Stepped-Impedance Resonators (SIRs) is presented in this paper. The proposed BPF operates over a large pass-band from 3.15 to 6.05 GHz covering 5G New Radio (NR) frequency Bands n77, n79 and 5G Wi-Fi, which includes the G band of US (3.3 to 4.2 GHz), 5G band of Japan (4.4 to 5 GHz) and 5G Wi-Fi (5.15 to 5.85 GHz). The presented filter has a maximum pass-band Insertion-Loss (IL) of 2 dB, a sharp roll-off rate and suppresses all the unwanted harmonics from 4.2 GHz up to 12 GHz with a 15 dB attenuation level. The performance of each section can be analyzed based on lumped-element circuit models. The electrical size of the BPF is 0.258 λg × 0.255 λg, where λgis the guided wavelength at the central frequency. The design accuracy is verified through implementing and testing the final BPF. The pass-band band-width can be controlled by adding the varactor diodes. A good relationship between the band-width and the varactor diodes are extracted by the curve fitting technique.
Synthesis, characterization and application of high adsorption performance of novel 1,4-polyketone
Authors: Sayed Marwa M. , Abd El-Hamid Islam S. , M. El-Bery Haitham , Farrag Mostafa , Abdelhakiem Alaa K. , Aly Kamal I.
Published: September 2022

This study aims to develop an alternating polyketone containing cationic groups in one and four alternating positions for increased functionality. A novel polyarylidene ketone was synthesized using simple condensation polymerization of terephthaldehyde and 2,5-hexane dione (PAK) The physicochemical properties of the resulting polymer were evaluated using Fourier-transform infrared spectroscopy, thermogravimetric analysis, X-ray diffraction, UV-Visible absorbance, fluorescence, and SEM investigations. The findings show that the polymer is amorphous, has good thermal stability, and emits red light. It can also be used as a dye adsorbent in aqueous solutions, with high selectivity for the cationic dye methylene blue (MB). The adsorbent efficiency of PAK was measured as a function of pH, dosage, and initial dye concentration; the greatest dye removal of 96 % was obtained at pH 10, 50 mg dosage, and initial dye concentration of 20 ppm. Kinetics and isotherms were studied, showing that the pseudo-second-order model described kinetic data better than Freundlich and Langmuir and revealed a satisfactory chemisorption process. This study suggests that PAK can purify MB dyeing wastewater, remove Zn2+, Cu2+, Ni2+, Co2+, Cd2+, Fe3+ metal ions well, and is selective for Fe3+ and Cu2+; ion adsorption is chelating-based.
Prevalence of cardiovascular risk factors in active tuberculosis in Africa: a systematic review and meta-analysis
Authors: Baluku Joseph Baruch , Ronald Olum , Bagasha Peace , Okello Emmy , Bongomin Felix
Published: September 2022

People with tuberculosis (TB) are at risk of major adverse cardiovascular events. We estimated the prevalence of cardiovascular risk (CVR) factors among people with active TB in Africa. This was a systematic review and meta-analysis of studies from Africa. We searched EMBASE, MEDLINE through PubMed, Web of Science, the Cochrane Central Register of Controlled Trials, mRCTs, Clinical trials.gov, and International Clinical Trials Registry Platform from inception to 31st December 2021. Among 110 eligible studies, 79 (238,316 participants) were included in the meta-analysis for smoking, 67 (52,793 participants) for current alcohol use, 30 (31,450 participants) for hazardous alcohol use, 51 (37,879 participants) for diabetes mellitus (DM), 19 (18,211 participants) for hypertension and 18 (13,910 participants) for obesity. The pooled prevalence was 26.0% (95% confidence interval 22.0–29.0) for smoking, 30.0% (25.0–35.0) for any current alcohol use, 21.0% (17.0–26.0) for hazardous alcohol use, 14.0% (9.0–18.0) for hypertension, 7.0% (6.0–9.0) for DM, and 4.0% (2.0–5.0) for obesity. Cost-effective strategies are needed to screen for CVR factors among people with active TB in Africa.
Ring contraction in synthesis of functionalized carbocycles
Authors: Hui Chunngai , Craggs Luke , Antonchick Andrey P.
Published: September 2022

This review summarizes the contractive synthesis of carbocycles, highlighting synthetic methods in organic synthesis and natural product synthesis.
Photochemically engineered ultra-stable 1T MoS2 by flow synthesis
Authors: Chen Wanqing , Panda Manas Ranjan , Mirsherkaloo Meysam Sharifzadeh , Kalantar-Zadeh Kourosh , Majumder Mainak
Published: September 2022

A novel photochemical (batch/flow) process for synthesis of ultra-stable 1T MoS2.
A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing
Authors: Winter Benedikt , Winter Clemens , Schilling Johannes , Bardow André
Published: September 2022

SPT is a natural language processing model that predicts limiting activity coefficients from SMILES. High accuracy is achieved by pre-training the model on millions of synthetic data points and fine-tuning the model on limited experimental data.