bluuebunny/crossref_metadata_2025 huggingface dataset:
The elements of resilience in the food system and means to enhance the stability of the food supply
Authors: Rimhanen Karoliina , Aakkula Jyrki , Aro Kalle , Rikkonen Pasi
Published: January 2023

Food systems are increasingly exposed to disruptions and shocks, and they are projected to increase in the future. Most recently, the war in Ukraine and Covid-19 pandemic has increased concerns about the ability to secure the availability of food at stable prices. This article presents a food system resilience framework to promote a national foresight system to better prepare for shocks and disruptions. Our study identified four key elements of resilience: system thinking through science and communication; redundancy of activities and networks; diversity of production and partners; and buffering strategies. Three national means to enhance resilience in the Finnish food system included domestic protein crop production, renewable energy production, and job creation measures. Primary production was perceived as the cornerstone for food system resilience, and the shocks and disruptions that it confronts therefore call for a sufficient and diverse domestic production volume, supported by the available domestic renewable energy. A dialogue between different actors in the food system was highlighted to format a situational picture and enable a rapid response. Our study suggests that to a certain point, concentration and interdependence in the food system increase dialogue and cooperation. For critical resources, sufficient reserve stocks buffer disruptions over a short period in the event of unexpected production or market disruptions. Introducing and strengthening the identified resilience elements and means to the food system call for the preparation of a more holistic and coherent food system policy that acknowledges and emphasises resilience alongside efficiency.
Surface Tension of Ethylene Glycol-Based Nanofluids Containing Three Types of Oxides: Zinc Oxide (ZnO), Magnesium Oxide (MgO) and Indium Oxide (In$$_2$$O$$_3$$)
Authors: Traciak Julian , Żyła Gaweł
Published: January 2023

The paper presents the results of an experimental study of the density and surface tension of ethylene glycol-based nanofluids containing zinc oxide, magnesium oxide and indium oxide. Du Noüy ring method was employed to determine the values of the surface tension of these nanofluids. Samples were prepared in various mass fractions from 0.01 to 0.05 with 0.01 step. Examination was performed in the temperature range from 283.15 K up to 318.15 K. The averaged surface tension values for the studied ZnO14-EG, ZnO25-EG, MgO-EG, In$$_2$$

2

O$$_3$$

3

-EG nanofluids at 298.15 K are 48.685, 48.471, 48.335, and 48.462 mN·m$$^{-1}$$

-
1

, respectively. It was presented that surface tension value could be consider as constant within the examined mass fraction of the particles, and the explanation of such behaviour was provided.
Leveraging an open source serverless framework for high energy physics computing
Authors: Padulano Vincenzo Eduardo , Oliver Cortés Pablo , Alonso-Jordá Pedro , Tejedor Saavedra Enric , Risco Sebastián , Moltó Germán
Published: January 2023

CERN (Centre Europeen pour la Recherce Nucleaire) is the largest research centre for high energy physics (HEP). It offers unique computational challenges as a result of the large amount of data generated by the large hadron collider. CERN has developed and supports a software called ROOT, which is the de facto standard for HEP data analysis. This framework offers a high-level and easy-to-use interface called RDataFrame, which allows managing and processing large data sets. In recent years, its functionality has been extended to take advantage of distributed computing capabilities. Thanks to its declarative programming model, the user-facing API can be decoupled from the actual execution backend. This decoupling allows physical analysis to scale automatically to thousands of computational cores over various types of distributed resources. In fact, the distributed RDataFrame module already supports the use of established general industry engines such as Apache Spark or Dask. Notwithstanding the foregoing, these current solutions will not be sufficient to meet future requirements in terms of the amount of data that the new projected accelerators will generate. It is of interest, for this reason, to investigate a different approach, the one offered by serverless computing. Based on a first prototype using AWS Lambda, this work presents the creation of a new backend for RDataFrame distributed over the OSCAR tool, an open source framework that supports serverless computing. The implementation introduces new ways, relative to the AWS Lambda-based prototype, to synchronize the work of functions.
Evaluation of total protein, peroxidase, and nutrients measured by pXRF for the determination of tissue rejuvenation/reinvigoration of Eucalyptus microcorys
Authors: Faria Júlio Cézar Tannure , Ribeiro-Kumara Caius , Delarmelina William Macedo , Namorato Filipe Aiura , Momolli Dione Richer , José Anderson Cleiton , Konzen Enéas Ricardo , de Carvalho Dulcinéia , Brondani Gilvano Ebling
Published: January 2023

Ontogenetic aging of tissues and the gradual decrease of adventitious rooting are known challenges for the clonal propagation of woody species, hampering clonal forestry programs. This study examined possible signatures of tissue rejuvenation/reinvigoration in different propagated materials of Eucalyptus microcorys by analyzing the total protein profile, peroxidase activity, macro- and micronutrient contents, and adventitious rooting of mini cuttings. The analyses were performed on E. microcorys shoots which were successfully obtained by seminal and grafting propagation, micropropagation with epicormic shoots, and indirect organogenesis. Among four mature trees used in the propagation, tissues from the one with the best propagation results were investigated for signs of tissue rejuvenation and/or reinvigoration. Five individuals from each technique were randomly selected and transferred to a semi-hydroponic “channel” system. After four weeks in the seedbed, the total protein, peroxidase activity, nutrient content and rooting of the mini cuttings were evaluated. SDS-PAGE enabled the differentiation of leaf samples obtained by grafting from the other propagation techniques, as revealed by two distinct bands. Materials obtained by micropropagation with epicormic shoots showed the highest peroxidase activity, while those obtained by seminal propagation and from the selected mature tree showed the lowest peroxidase activity. A portable X-ray fluorescence spectroscope (pXRF) identified adequate nutrient content in most of the nutrients tested in materials obtained by seminal and grafting propagation, and by indirect organogenesis. The analysis of adventitious rooting showed that the highest rooting percentage was observed in mini cuttings from seminal propagation (75%) followed by indirect organogenesis (35%). Based on principal component analysis, it was concluded that rooting of mini cuttings from both seminal propagation and indirect organogenesis was associated with phosphorous, sulphur, and potassium contents, which suggests a higher level of tissue rejuvenation/reinvigoration in these propagated plants. Further studies are recommended to search for other methods that present similarities with the responses to adventitious rooting in forest species and thus optimize the rescue and propagation of plants with distinct ontogenetic stages.
A phase I first-in-man study to investigate the pharmacokinetics and safety of liposomal dexamethasone in patients with progressive multiple myeloma
Authors: Metselaar Josbert , Lammers Twan , Boquoi Amelie , Fenk Roland , Testaquadra Fabio , Schemionek Mirle , Kiessling Fabian , Isfort Susanne , Wilop Stefan , Crysandt Martina
Published: January 2023

Despite the introduction of multiple new drugs and combination therapies, conventional dexamethasone remains a cornerstone in the treatment of multiple myeloma (MM). Its application is, however, limited by frequent adverse effects of which the increased infection rate may have the strongest clinical impact. The efficacy-safety ratio of dexamethasone in MM may be increased by encapsulation in long-circulating PEG-liposomes, thereby both enhancing drug delivery to MM lesions and reducing systemic corticosteroid exposure. We evaluated the preliminary safety and feasibility of a single intravenous (i.v.) infusion of pegylated liposomal dexamethasone phosphate (Dex-PL) in heavily pretreated relapsing or progressive symptomatic MM patients within a phase I open-label non-comparative interventional trial at two dose levels. In the 7 patients that were enrolled (prior to having to close the study prematurely due to slow recruitment), Dex-PL was found to be well tolerated and, as compared to conventional dexamethasone, no new or unexpected adverse events were detected. Pharmacokinetic analysis showed high and persisting concentrations of dexamethasone in the circulation for over a week after i.v. administration, likely caused by the long-circulation half-life of the liposomes that retain dexamethasone as the inactive phosphate prodrug form, something which could significantly limit systemic exposure to the active parent drug. Thus, despite the limitations of this small first-in-man trial, Dex-PL seems safe and well tolerated without severe side effects. Follow-up studies are needed to confirm this in a larger patient cohort and to evaluate if i.v. Dex-PL can provide a safer and more efficacious dexamethasone treatment option for MM.

Graphical Abstract
A bidirectional trajectory contrastive learning model for driving intention prediction
Authors: Zhou Yi , Wang Huxiao , Ning Nianwen , Wang Zhangyun , Zhang Yanyu , Liu Fuqiang
Published: January 2023

Driving intention prediction with trajectory data of surrounding vehicles is critical to advanced driver assistance system for improving the accuracy of decision-making. Previous works mostly focused on trajectory representation based on supervised manners. However, learning generalized and high-quality representations from unlabeled data remains a very challenging task. In this paper, we propose a self-supervised bidirectional trajectory contrastive learning (BTCL) model that learns generalized trajectory representation to improve the performance of the driving intention prediction task. Different trajectory data augmentation strategies and a cross-view trajectory prediction task are constructed jointly as pretext task of contrastive learning. The pretext task can maximize the similarity among different augmentations of the same sample while minimizing similarity among augmentations of different samples. It can not only learn the high-quality representation of trajectory without labeled information but also improve the adversarial attacks on BTCL. Moreover, considering the vehicle trajectory forward and backward follows the same social norms and driving behavior constraints. A bidirectional trajectory contrastive learning module is built to gain more positive samples that further increasing the prediction accuracy in downstream tasks and transfer ability of the model. Experimental results demonstrate that BTCL is competitive with the state-of-the-art, especially for adversarial attack and transfer learning tasks, on real-world HighD and NGSIM datasets.
DAACO: adaptive dynamic quantity of ant ACO algorithm to solve the traveling salesman problem
Authors: Liu Huijun , Lee Ao , Lee Wenshi , Guo Ping
Published: January 2023

The traveling salesman problem (TSP) is an NP-hard problem. Thus far, a large number of researchers have proposed different ant colony optimization (ACO) algorithms to solve the TSP. These algorithms inevitably encounter problems such as long convergence time and the tendency to easily fall into local optima. On the basis of the ACO algorithm, this study proposes a dynamic adaptive ACO algorithm (DAACO). DAACO realizes the diversity of initialization of the ACO algorithm by dynamically determining the number of ants to be prevented from falling into local optimization. DAACO also adopts a hybrid local selection strategy to increase the quality of ant optimization and reduce the optimization time. Among the 20 instances of the TSPLIB dataset, the DAACO algorithm obtains 19 optimal values, and the solutions of 10 instances are better than those of other algorithms. The experimental results on the TSPLIB dataset show that the DAACO algorithm has obvious advantages in terms of convergence time, solution quality, and average value relative to existing state-of-the-art ACO algorithms.
A Communication Efficient ADMM-based Distributed Algorithm Using Two-Dimensional Torus Grouping AllReduce
Authors: Wang Guozheng , Lei Yongmei , Zhang Zeyu , Peng Cunlu
Published: January 2023

Large-scale distributed training mainly consists of sub-model parallel training and parameter synchronization. With the expansion of training workers, the efficiency of parameter synchronization will be affected. To tackle this problem, we first propose 2D-TGA, a grouping AllReduce method based on the two-dimensional torus topology. This method synchronizes the model parameters by grouping and makes full use of bandwidth. Secondly, we propose a distributed algorithm, 2D-TGA-ADMM, which combines the 2D-TGA with the alternating direction method of multipliers (ADMM). It focuses on sub-model training and reduces the wait time among workers in the synchronization process. Finally, experimental results on the Tianhe-2 supercomputing platform show that compared with the $${\mathtt {MPI\_Allreduce}}$$

MPI
_
Allreduce

, the 2D-TGA could shorten the synchronization wait time by $$33\%$$

33
%

.
Multi-Model Fusion-Based Hierarchical Extraction for Chinese Epidemic Event
Authors: Liao Zenghua , Yang Zongqiang , Huang Peixin , Pang Ning , Zhao Xiang
Published: January 2023

In recent years, Coronavirus disease 2019 (COVID-19) has become a global epidemic, and some efforts have been devoted to tracking and controlling its spread. Extracting structured knowledge from involved epidemic case reports can inform the surveillance system, which is important for controlling the spread of outbreaks. Therefore, in this paper, we focus on the task of Chinese epidemic event extraction (EE), which is defined as the detection of epidemic-related events and corresponding arguments in the texts of epidemic case reports. To facilitate the research of this task, we first define the epidemic-related event types and argument roles. Then we manually annotate a Chinese COVID-19 epidemic dataset, named COVID-19 Case Report (CCR). We also propose a novel hierarchical EE architecture, named multi-model fusion-based hierarchical event extraction (MFHEE). In MFHEE, we introduce a multi-model fusion strategy to tackle the issue of recognition bias of previous EE models. The experimental results on CCR dataset show that our method can effectively extract epidemic events and outperforms other baselines on this dataset. The comparative experiments results on other generic datasets show that our method has good scalability and portability. The ablation studies also show that the proposed hierarchical structure and multi-model fusion strategy contribute to the precision of our model.
Quantized fields induced topological features in Harper-Hofstadter model
Authors: Han Xue , Li Fude , Qiu De-Xiu , Xue Kang , Yi X. X.
Published: January 2023

Classical magnetic fields might change the properties of topological insulators such as the time reversal symmetry protected topological edge states. This poses a question that whether quantized fields would change differently the feature of topological materials with respect to the classical one. In this paper, we propose a model to describe topological insulators (ultracold atoms in square optical lattices with magnetic field) coupled to a tunable single-mode quantized field, and discuss the topological features of the system. We find that the quantized field can induce topological quantum phase transitions in a different way. To be specific, for fixed gauge magnetic flux ratio, we calculate the energy bands for different coupling constants between the systems and the fields in both open and periodic boundary conditions. We find that the Hofstadter butterfly graph is divided into a pair for continuous gauge magnetic flux ratio, which is different from the one without single-mode quantized field. In addition, we plot topological phase diagrams characterized by Chern number as a function of the momentum of the single-mode quantized field and obtain a quantized structure with non-zero filling factor.
Underestimated Passive Volcanic Sulfur Degassing Implies Overestimated Anthropogenic Aerosol Forcing
Authors: Jongebloed U. A. , Schauer A. J. , Cole‐Dai J. , Larrick C. G. , Wood R. , Fischer T. P. , Carn S. A. , Salimi S. , Edouard S. R. , Zhai S. , Geng L. , Alexander B.
Published: January 2023

The Arctic is warming at almost four times the global rate. An estimated sixty percent of greenhouse‐gas‐induced Arctic warming has been offset by anthropogenic aerosols, but the contribution of aerosols to radiative forcing (RF) represents the largest uncertainty in estimating total RF, largely due to unknown preindustrial aerosol abundance. Here, sulfur isotope measurements in a Greenland ice core show that passive volcanic degassing contributes up to 66 ± 10% of preindustrial ice core sulfate in years without major eruptions. A state‐of‐the‐art model indicates passive volcanic sulfur emissions influencing the Arctic are underestimated by up to a factor of three, possibly because many volcanic inventories do not include hydrogen sulfide emissions. Higher preindustrial volcanic sulfur emissions reduce modeled anthropogenic Arctic aerosol cooling by up to a factor of two (+0.11 to +0.29 W m−2), suggesting that underestimating passive volcanic sulfur emissions has significant implications for anthropogenic‐induced Arctic climate change.
SCGN deficiency is a risk factor for autism spectrum disorder
Authors: Liu Zhe , Tan Shuai , Zhou Lianyu , Chen Li , Liu Mingfeng , Wang Wang , Tang Yingying , Yang Qin , Chi Sensen , Jiang Peiyan , Zhang Yue , Cui Yonghua , Qin Junhong , Hu Xiao , Li Shenglong , Liu Qi , Chen Lu , Li Song , Burstein Ezra , Li Wei , Zhang Xiaohu , Mo Xianming , Jia Da
Published: January 2023

Autism spectrum disorder (ASD) affects 1–2% of all children and poses a great social and economic challenge for the globe. As a highly heterogeneous neurodevelopmental disorder, the development of its treatment is extremely challenging. Multiple pathways have been linked to the pathogenesis of ASD, including signaling involved in synaptic function, oxytocinergic activities, immune homeostasis, chromatin modifications, and mitochondrial functions. Here, we identify secretagogin (SCGN), a regulator of synaptic transmission, as a new risk gene for ASD. Two heterozygous loss-of-function mutations in SCGN are presented in ASD probands. Deletion of Scgn in zebrafish or mice leads to autism-like behaviors and impairs brain development. Mechanistically, Scgn deficiency disrupts the oxytocin signaling and abnormally activates inflammation in both animal models. Both ASD probands carrying Scgn mutations also show reduced oxytocin levels. Importantly, we demonstrate that the administration of oxytocin and anti-inflammatory drugs can attenuate ASD-associated defects caused by SCGN deficiency. Altogether, we identify a convergence between a potential autism genetic risk factor SCGN, and the pathological deregulation in oxytocinergic signaling and immune responses, providing potential treatment for ASD patients suffering from SCGN deficiency. Our study also indicates that it is critical to identify and stratify ASD patient populations based on their disease mechanisms, which could greatly enhance therapeutic success.
Targeting integrin pathways: mechanisms and advances in therapy
Authors: Pang Xiaocong , He Xu , Qiu Zhiwei , Zhang Hanxu , Xie Ran , Liu Zhiyan , Gu Yanlun , Zhao Nan , Xiang Qian , Cui Yimin
Published: January 2023

Integrins are considered the main cell-adhesion transmembrane receptors that play multifaceted roles as extracellular matrix (ECM)-cytoskeletal linkers and transducers in biochemical and mechanical signals between cells and their environment in a wide range of states in health and diseases. Integrin functions are dependable on a delicate balance between active and inactive status via multiple mechanisms, including protein-protein interactions, conformational changes, and trafficking. Due to their exposure on the cell surface and sensitivity to the molecular blockade, integrins have been investigated as pharmacological targets for nearly 40 years, but given the complexity of integrins and sometimes opposite characteristics, targeting integrin therapeutics has been a challenge. To date, only seven drugs targeting integrins have been successfully marketed, including abciximab, eptifibatide, tirofiban, natalizumab, vedolizumab, lifitegrast, and carotegrast. Currently, there are approximately 90 kinds of integrin-based therapeutic drugs or imaging agents in clinical studies, including small molecules, antibodies, synthetic mimic peptides, antibody–drug conjugates (ADCs), chimeric antigen receptor (CAR) T-cell therapy, imaging agents, etc. A serious lesson from past integrin drug discovery and research efforts is that successes rely on both a deep understanding of integrin-regulatory mechanisms and unmet clinical needs. Herein, we provide a systematic and complete review of all integrin family members and integrin-mediated downstream signal transduction to highlight ongoing efforts to develop new therapies/diagnoses from bench to clinic. In addition, we further discuss the trend of drug development, how to improve the success rate of clinical trials targeting integrin therapies, and the key points for clinical research, basic research, and translational research.
Sulfoquinovose is a widespread organosulfur substrate for Roseobacter clade bacteria in the ocean
Authors: Liu Le , Chen Xiaofeng , Ye Jianing , Ma Xiaoyi , Han Yu , He Yajie , Tang Kai
Published: January 2023

Sulfoquinovose (SQ) is one of the most abundant organosulfur compounds in the biosphere, and its biosynthesis and degradation can represent an important contribution to the sulfur cycle. To data, in marine environments, the microorganisms capable of metabolising SQ have remained unidentified and the sources of SQ are still uncertain. Herein, the marine Roseobacter clade bacteria (RCB) Dinoroseobacter shibae DFL 12 and Roseobacter denitrificans OCh 114 were found to grow using SQ as the sole source of carbon and energy. In the presence of SQ, we identified a set of highly up-regulated proteins encoded by gene clusters in these two organisms, of which four homologues to proteins in the SQ monooxygenase pathway of Agrobacterium fabrum C58 may confer the ability to metabolise SQ to these marine bacteria. The sulfite released from SQ desulfonation by FMN-dependent SQ monooxygenase (SmoC) may provide bacteria with reduced sulfur for assimilation, while proteins associated with sulfite production via assimilatory sulfate reduction were significantly down-regulated. Such SQ catabolic genes are restricted to a limited number of phylogenetically diverse bacterial taxa with the predominate genera belonging to the Roseobacter clade (Roseobacteraceae). Moreover, transcript analysis of Tara Oceans project and coastal Bohai Sea samples provided additional evidence for SQ metabolism by RCB. SQ was found to be widely distributed in marine phytoplankton and cyanobacteria with variable intracellular concentrations ranging from micromolar to millimolar levels, and the amounts of SQ on particulate organic matter in field samples were, on average, lower than that of dimethylsulfoniopropionate (DMSP) by one order of magnitude. Together, the phototroph-derived SQ actively metabolised by RCB represents a previously unidentified link in the marine sulfur cycle.
The role of TGF-beta3 in cartilage development and osteoarthritis
Authors: Du Xinmei , Cai Linyi , Xie Jing , Zhou Xuedong
Published: January 2023

Articular cartilage serves as a low-friction, load-bearing tissue without the support with blood vessels, lymphatics and nerves, making its repair a big challenge. Transforming growth factor-beta 3 (TGF-β3), a vital member of the highly conserved TGF-β superfamily, plays a versatile role in cartilage physiology and pathology. TGF-β3 influences the whole life cycle of chondrocytes and mediates a series of cellular responses, including cell survival, proliferation, migration, and differentiation. Since TGF-β3 is involved in maintaining the balance between chondrogenic differentiation and chondrocyte hypertrophy, its regulatory role is especially important to cartilage development. Increased TGF-β3 plays a dual role: in healthy tissues, it can facilitate chondrocyte viability, but in osteoarthritic chondrocytes, it can accelerate the progression of disease. Recently, TGF-β3 has been recognized as a potential therapeutic target for osteoarthritis (OA) owing to its protective effect, which it confers by enhancing the recruitment of autologous mesenchymal stem cells (MSCs) to damaged cartilage. However, the biological mechanism of TGF-β3 action in cartilage development and OA is not well understood. In this review, we systematically summarize recent progress in the research on TGF-β3 in cartilage physiology and pathology, providing up-to-date strategies for cartilage repair and preventive treatment.
Inhibition of fibroblast activation protein ameliorates cartilage matrix degradation and osteoarthritis progression
Authors: Fan Aoyuan , Wu Genbin , Wang Jianfang , Lu Laiya , Wang Jingyi , Wei Hanjing , Sun Yuxi , Xu Yanhua , Mo Chunyang , Zhang Xiaoying , Pang Zhiying , Pan Zhangyi , Wang Yiming , Lu Liangyu , Fu Guojian , Ma Mengqiu , Zhu Qiaoling , Cao Dandan , Qin Jiachen , Yin Feng , Yue Rui
Published: January 2023

Fibroblast activation protein (Fap) is a serine protease that degrades denatured type I collagen, α2-antiplasmin and FGF21. Fap is highly expressed in bone marrow stromal cells and functions as an osteogenic suppressor and can be inhibited by the bone growth factor Osteolectin (Oln). Fap is also expressed in synovial fibroblasts and positively correlated with the severity of rheumatoid arthritis (RA). However, whether Fap plays a critical role in osteoarthritis (OA) remains poorly understood. Here, we found that Fap is significantly elevated in osteoarthritic synovium, while the genetic deletion or pharmacological inhibition of Fap significantly ameliorated posttraumatic OA in mice. Mechanistically, we found that Fap degrades denatured type II collagen (Col II) and Mmp13-cleaved native Col II. Intra-articular injection of rFap significantly accelerated Col II degradation and OA progression. In contrast, Oln is expressed in the superficial layer of articular cartilage and is significantly downregulated in OA. Genetic deletion of Oln significantly exacerbated OA progression, which was partially rescued by Fap deletion or inhibition. Intra-articular injection of rOln significantly ameliorated OA progression. Taken together, these findings identify Fap as a critical pathogenic factor in OA that could be targeted by both synthetic and endogenous inhibitors to ameliorate articular cartilage degradation.
Co-targeting BCL-XL and MCL-1 with DT2216 and AZD8055 synergistically inhibit small-cell lung cancer growth without causing on-target toxicities in mice
Authors: Khan Sajid , Kellish Patrick , Connis Nick , Thummuri Dinesh , Wiegand Janet , Zhang Peiyi , Zhang Xuan , Budamagunta Vivekananda , Hua Nan , Yang Yang , De Umasankar , Jin Lingtao , Zhang Weizhou , Zheng Guangrong , Hromas Robert , Hann Christine , Zajac-Kaye Maria , Kaye Frederic J. , Zhou Daohong
Published: January 2023

Small-cell lung cancer (SCLC) is an aggressive malignancy with limited therapeutic options. The dismal prognosis in SCLC is in part associated with an upregulation of BCL-2 family anti-apoptotic proteins, including BCL-XL and MCL-1. Unfortunately, the currently available inhibitors of BCL-2 family anti-apoptotic proteins, except BCL-2 inhibitors, are not clinically relevant because of various on-target toxicities. We, therefore, aimed to develop an effective and safe strategy targeting these anti-apoptotic proteins with DT2216 (our platelet-sparing BCL-XL degrader) and AZD8055 (an mTOR inhibitor) to avoid associated on-target toxicities while synergistically optimizing tumor response. Through BH3 mimetic screening, we identified a subset of SCLC cell lines that is co-dependent on BCL-XL and MCL-1. After screening inhibitors of selected tumorigenic pathways, we found that AZD8055 selectively downregulates MCL-1 in SCLC cells and its combination with DT2216 synergistically killed BCL-XL/MCL-1 co-dependent SCLC cells, but not normal cells. Mechanistically, the combination caused BCL-XL degradation and suppression of MCL-1 expression, and thus disrupted MCL-1 interaction with BIM leading to an enhanced apoptotic induction. In vivo, the DT2216 + AZD8055 combination significantly inhibited the growth of cell line-derived and patient-derived xenografts and reduced tumor burden accompanied by increased survival in a genetically engineered mouse model of SCLC without causing appreciable thrombocytopenia or other normal tissue injuries. Thus, these preclinical findings lay a strong foundation for future clinical studies to test DT2216 + mTOR inhibitor combinations in a subset of SCLC patients whose tumors are co-driven by BCL-XL and MCL-1.
RALF signaling pathway activates MLO calcium channels to maintain pollen tube integrity
Authors: Gao Qifei , Wang Chao , Xi Yasheng , Shao Qiaolin , Hou Congcong , Li Legong , Luan Sheng
Published: January 2023

Pollen tube tip growth requires intricate Ca2+ signaling. Recent studies have also identified rapid alkalization factor (RALF)-family peptides and their receptors as critical components for pollen tube tip growth and integrity. The functional relationship of RALF and calcium signaling modules remains largely unclear. Here we report that disruption of RALF signaling pathway abolished the cytosolic Ca2+ gradient in the pollen tube, indicating that Ca2+ signaling is downstream of the RALF signaling pathway. We identified MILDEW RESISTANCE LOCUS O (MLO) family proteins MLO1, 5, 9, 15, as Ca2+ channels required for Ca2+ influx and pollen tube integrity. We further reconstituted the biochemical pathway in which signaling via RALF and RALF receptors activated MLO1/5/9/15 calcium channels. Together, we conclude that RALF peptides derived from pollen tube bind to their receptors to establish pollen tube Ca2+ gradient through activation of the MLO channels. Our finding has thus provided a mechanistic link between the RALF signaling pathway and Ca2+ signaling in controlling pollen tube integrity and growth.
De novo genes with an lncRNA origin encode unique human brain developmental functionality
Authors: An Ni A. , Zhang Jie , Mo Fan , Luan Xuke , Tian Lu , Shen Qing Sunny , Li Xiangshang , Li Chunqiong , Zhou Fanqi , Zhang Boya , Ji Mingjun , Qi Jianhuan , Zhou Wei-Zhen , Ding Wanqiu , Chen Jia-Yu , Yu Jia , Zhang Li , Shu Shaokun , Hu Baoyang , Li Chuan-Yun
Published: January 2023

Human de novo genes can originate from neutral long non-coding RNA (lncRNA) loci and are evolutionarily significant in general, yet how and why this all-or-nothing transition to functionality happens remains unclear. Here, in 74 human/hominoid-specific de novo genes, we identified distinctive U1 elements and RNA splice-related sequences accounting for RNA nuclear export, differentiating mRNAs from lncRNAs, and driving the origin of de novo genes from lncRNA loci. The polymorphic sites facilitating the lncRNA–mRNA conversion through regulating nuclear export are selectively constrained, maintaining a boundary that differentiates mRNAs from lncRNAs. The functional new genes actively passing through it thus showed a mode of pre-adaptive origin, in that they acquire functions along with the achievement of their coding potential. As a proof of concept, we verified the regulations of splicing and U1 recognition on the nuclear export efficiency of one of these genes, the ENSG00000205704, in human neural progenitor cells. Notably, knock-out or over-expression of this gene in human embryonic stem cells accelerates or delays the neuronal maturation of cortical organoids, respectively. The transgenic mice with ectopically expressed ENSG00000205704 showed enlarged brains with cortical expansion. We thus demonstrate the key roles of nuclear export in de novo gene origin. These newly originated genes should reflect the novel uniqueness of human brain development.
Protection of cell therapeutics from antibody-mediated killing by CD64 overexpression
Authors: Gravina Alessia , Tediashvili Grigol , Rajalingam Raja , Quandt Zoe , Deisenroth Chad , Schrepfer Sonja , Deuse Tobias
Published: January 2023

Allogeneic cell therapeutics for cancer therapy or regenerative medicine are susceptible to antibody-mediated killing, which diminishes their efficacy. Here we report a strategy to protect cells from antibody-mediated killing that relies on engineered overexpression of the IgG receptor CD64. We show that human and mouse iPSC-derived endothelial cells (iECs) overexpressing CD64 escape antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity from IgG antibodies in vitro and in ADCC-enabled mice. When CD64 expression was combined with hypoimmune genetic modifications known to protect against cellular immunity, B2M−/−CIITA−/− CD47/CD64-transgenic iECs were resistant to both IgG antibody-mediated and cellular immune killing in vitro and in humanized mice. Mechanistic studies demonstrated that CD64 or its intracellularly truncated analog CD64t effectively capture monomeric IgG and occupy their Fc, and the IgG bind and occupy their target antigens. In three applications of the approach, human CD64t-engineered thyroid epithelial cells, pancreatic beta cells and CAR T cells withstood clinically relevant levels of graft-directed antibodies and fully evaded antibody-mediated killing.
Identification of patient-specific CD4+ and CD8+ T cell neoantigens through HLA-unbiased genetic screens
Authors: Cattaneo Chiara M. , Battaglia Thomas , Urbanus Jos , Moravec Ziva , Voogd Rhianne , de Groot Rosa , Hartemink Koen J. , Haanen John B. A. G. , Voest Emile E. , Schumacher Ton N. , Scheper Wouter
Published: January 2023

Cancer neoantigens that arise from tumor mutations are drivers of tumor-specific T cell responses, but identification of T cell-recognized neoantigens in individual patients is challenging. Previous methods have restricted antigen discovery to selected HLA alleles, thereby limiting the breadth of neoantigen repertoires that can be uncovered. Here, we develop a genetic neoantigen screening system that allows sensitive identification of CD4+ and CD8+ T cell-recognized neoantigens across patients’ complete HLA genotypes.
Accurate isoform discovery with IsoQuant using long reads
Authors: Prjibelski Andrey D. , Mikheenko Alla , Joglekar Anoushka , Smetanin Alexander , Jarroux Julien , Lapidus Alla L. , Tilgner Hagen U.
Published: January 2023

Annotating newly sequenced genomes and determining alternative isoforms from long-read RNA data are complex and incompletely solved problems. Here we present IsoQuant—a computational tool using intron graphs that accurately reconstructs transcripts both with and without reference genome annotation. For novel transcript discovery, IsoQuant reduces the false-positive rate fivefold and 2.5-fold for Oxford Nanopore reference-based or reference-free mode, respectively. IsoQuant also improves performance for Pacific Biosciences data.
Real-time, volumetric imaging of radiation dose delivery deep into the liver during cancer treatment
Authors: Zhang Wei , Oraiqat Ibrahim , Litzenberg Dale , Chang Kai-Wei , Hadley Scott , Sunbul Noora Ba , Matuszak Martha M. , Tichacek Christopher J. , Moros Eduardo G. , Carson Paul L. , Cuneo Kyle C. , Wang Xueding , El Naqa Issam
Published: January 2023

Ionizing radiation acoustic imaging (iRAI) allows online monitoring of radiation’s interactions with tissues during radiation therapy, providing real-time, adaptive feedback for cancer treatments. We describe an iRAI volumetric imaging system that enables mapping of the three-dimensional (3D) radiation dose distribution in a complex clinical radiotherapy treatment. The method relies on a two-dimensional matrix array transducer and a matching multi-channel preamplifier board. The feasibility of imaging temporal 3D dose accumulation was first validated in a tissue-mimicking phantom. Next, semiquantitative iRAI relative dose measurements were verified in vivo in a rabbit model. Finally, real-time visualization of the 3D radiation dose delivered to a patient with liver metastases was accomplished with a clinical linear accelerator. These studies demonstrate the potential of iRAI to monitor and quantify the 3D radiation dose deposition during treatment, potentially improving radiotherapy treatment efficacy using real-time adaptive treatment.
In situ cryo-electron tomography reveals the asymmetric architecture of mammalian sperm axonemes
Authors: Chen Zhen , Greenan Garrett A. , Shiozaki Momoko , Liu Yanxin , Skinner Will M. , Zhao Xiaowei , Zhao Shumei , Yan Rui , Yu Zhiheng , Lishko Polina V. , Agard David A. , Vale Ronald D.
Published: January 2023

The flagella of mammalian sperm display non-planar, asymmetric beating, in contrast to the planar, symmetric beating of flagella from sea urchin sperm and unicellular organisms. The molecular basis of this difference is unclear. Here, we perform in situ cryo-electron tomography of mouse and human sperm, providing the highest-resolution structural information to date. Our subtomogram averages reveal mammalian sperm-specific protein complexes within the microtubules, the radial spokes and nexin–dynein regulatory complexes. The locations and structures of these complexes suggest potential roles in enhancing the mechanical strength of mammalian sperm axonemes and regulating dynein-based axonemal bending. Intriguingly, we find that each of the nine outer microtubule doublets is decorated with a distinct combination of sperm-specific complexes. We propose that this asymmetric distribution of proteins differentially regulates the sliding of each microtubule doublet and may underlie the asymmetric beating of mammalian sperm.
Development of Kovacs model for electrical conductivity of carbon nanofiber–polymer systems
Authors: Arjmandi Sajad Khalil , Khademzadeh Yeganeh Jafar , Zare Yasser , Rhee Kyong Yop
Published: January 2023

This study develops a model for electrical conductivity of polymer carbon nanofiber (CNF) nanocomposites (PCNFs), which includes two steps. In the first step, Kovacs model is developed to consider the CNF, interphase and tunneling regions as dissimilar zones in the system. In the second step, simple equations are expressed to estimate the resistances of interphase and tunnels, the volume fraction of CNF and percolation onset. Although some earlier models were proposed to predict the electrical conductivity of PCNFs, developing of Kovacs model causes a better understanding of the effects of main factors on the nanocomposite conductivity. The developed model is supported by logical influences of all factors on the conductivity and by experimented conductivity of several samples. The calculations show good accordance to the experimented data and all factors rationally manage the conductivity of PCNFs. The highest conductivity of PCNF is gained as 0.019 S/m at the lowest ranges of polymer tunnel resistivity (ρ = 500 Ω m) and tunneling distance (d = 2 nm), whereas the highest levels of these factors (ρ > 3000 Ω m and d > 6 nm) cannot cause a conductive sample. Also, high CNF volume fraction, poor waviness, long and thin CNF, low “k”, thick interphase, high CNF conduction, high percentage of percolated CNFs, low percolation onset and high interphase conductivity cause an outstanding conductivity in PCNF.
The clinical significance of radiological changes associated with gliadel implantation in patients with recurrent high grade glioma
Authors: Haim Oz , Agur Ariel , Efrat Or-Tal , Valdes Pablo , Ram Zvi , Grossman Rachel
Published: January 2023

Gliadel occasionally induces edema following its implantation. We aimed to correlate such post-surgical radiological changes to its efficacy and subsequent survival. Fifty-six patients with recurrent high grade glioma were treated between 2005 and 2016 with Gliadel implantation. Volumetric measurements of MRI features, including FLAIR abnormalities, tumor bulk (volume of gadolinium enhancement on T1) and resection cavity volumes over time were conducted. To assess dynamics over time, linear regression trendlines for each of these were calculated and examined to correlate with survival. Median follow-up after resection was 21.5 months. Median survival post-Gliadel implantation and overall survival since diagnosis were 12 months and 22 months, respectively. A subgroup of patients (n = 6) with a transient increase in FLAIR changes volume over time survived significantly longer post-Gliadel compared to those who did not demonstrate such change (36 vs 12 months, p = .03). Positive trends, representing overall growth in volume over time, of tumor bulk and resection cavity predicted survival in multivariate analyses (hazard ratios 7.9 and 84, p = .003 and .002, respectively). Increase in tumor bulk and resection cavity over time were associated with decreased survival, while transient FLAIR increase was a favorable prognostic factor. This may represent a transient inflammatory process in the tumor, possibly stemming from a presumed immune-mediated anti-tumor response.
Cyst identification in retinal optical coherence tomography images using hidden Markov model
Authors: Mousavi Niloofarsadat , Monemian Maryam , Ghaderi Daneshmand Parisa , Mirmohammadsadeghi Mohammad , Zekri Maryam , Rabbani Hossein
Published: January 2023

Optical Coherence Tomography (OCT) is a useful imaging modality facilitating the capturing process from retinal layers. In the salient diseases of retina, cysts are formed in retinal layers. Therefore, the identification of cysts in the retinal layers is of great importance. In this paper, a new method is proposed for the rapid detection of cystic OCT B-scans. In the proposed method, a Hidden Markov Model (HMM) is used for mathematically modelling the existence of cyst. In fact, the existence of cyst in the image can be considered as a hidden state. Since the existence of cyst in an OCT B-scan depends on the existence of cyst in the previous B-scans, HMM is an appropriate tool for modelling this process. In the first phase, a number of features are extracted which are Harris, KAZE, HOG, SURF, FAST, Min-Eigen and feature extracted by deep AlexNet. It is shown that the feature with the best discriminating power is the feature extracted by AlexNet. The features extracted in the first phase are used as observation vectors to estimate the HMM parameters. The evaluation results show the improved performance of HMM in terms of accuracy.
Correlations between linear sprint with the ball, linear sprint without the ball, and change-of-direction without the ball in professional female soccer players
Authors: Preissler Artur Avelino Birk , Schons Pedro , Clemente Filipe Manuel , de Vargas Guilherme Droescher , Klein Lucas Moraes , Silva Ana Filipa , Nobari Hadi , Kruel Luiz Fernando Martins
Published: January 2023

The evolution of female soccer is related to the increase in high-intensity actions and choosing the abilities that best characterize the players' performance. Determining the capabilities that best describe the players' performance becomes essential for coaches and technical staff to obtain the results more efficiently within the competitive calendar. Thus, the study aimed to analyze the correlations between performance in the 20-m sprint tests with and without the ball and the Zigzag 20-m change-of-direction (COD) test without the ball in professional female soccer players. Thirty-three high-level professional female soccer players performed the 20-m sprint tests without a ball, 20-m sprint tests with the ball, and the Zigzag 20-m COD test without the ball. The shortest time obtained in the three trials was used for each test. The fastest time in the three trials was used for each test to calculate the average test speed. The Pearson product–moment correlation test was applied to analyze the correlation between the performance in the tests. Pearson's product–moment correlation test was used to analyze the correlation between the performance in the trials, with a significance level of α < 0.05. The average speed in the 20-m sprint tests with ball showed very large and significant correlations with the speed in the Zigzag 20-m COD test (r = 0.822; p < 0.001; 95% CI = 0.666 to 0.909). The 20-m sprint tests with ball and 20-m sprint tests without ball showed moderate, positive and significant correlation (r = 0.363; p = 0.038; 95% CI = 0.023–0.628). The tests of 20-m sprint tests without ball and Zigzag 20-m COD test also showed moderate, positive and significant correlation (r = 0.415; p = 0.016; 95% CI = 0.084–0.664). The female–female soccer players with a better ability to change direction may also have a better technical ability to drive the ball at high speed. However, they will not necessarily be the fastest in the linear sprint without the ball. Coaches and technical staff may choose to perform tests seeking efficiency and practicality, especially in a congested competitive period.
A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population
Authors: Chowdhury Mohammad Ziaul Islam , Leung Alexander A. , Walker Robin L. , Sikdar Khokan C. , O’Beirne Maeve , Quan Hude , Turin Tanvir C.
Published: January 2023

Risk prediction models are frequently used to identify individuals at risk of developing hypertension. This study evaluates different machine learning algorithms and compares their predictive performance with the conventional Cox proportional hazards (PH) model to predict hypertension incidence using survival data. This study analyzed 18,322 participants on 24 candidate features from the large Alberta’s Tomorrow Project (ATP) to develop different prediction models. To select the top features, we applied five feature selection methods, including two filter-based: a univariate Cox p-value and C-index; two embedded-based: random survival forest and least absolute shrinkage and selection operator (Lasso); and one constraint-based: the statistically equivalent signature (SES). Five machine learning algorithms were developed to predict hypertension incidence: penalized regression Ridge, Lasso, Elastic Net (EN), random survival forest (RSF), and gradient boosting (GB), along with the conventional Cox PH model. The predictive performance of the models was assessed using C-index. The performance of machine learning algorithms was observed, similar to the conventional Cox PH model. Average C-indexes were 0.78, 0.78, 0.78, 0.76, 0.76, and 0.77 for Ridge, Lasso, EN, RSF, GB and Cox PH, respectively. Important features associated with each model were also presented. Our study findings demonstrate little predictive performance difference between machine learning algorithms and the conventional Cox PH regression model in predicting hypertension incidence. In a moderate dataset with a reasonable number of features, conventional regression-based models perform similar to machine learning algorithms with good predictive accuracy.