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Wei Liu,1 Jeffrey Hugh Gamble,2 Cui-Hong Cao,3,4 Xiao-Ling Liao,5 I-Hua Chen,1 Gordon L Flett6 1Chinese Academy of Education Big Data, Qufu Normal University, Qufu, People’s Republic of China; 2Department of English, National Changhua University of Education, Changhua, Taiwan; 3Faculty of Education, Qufu Normal University, Qufu, People’s Republic of China; 4School of Foreign Languages, Shandong Women’s University, Jinan, People’s Republic of China; 5Faculty of Education, Jiangxi Science and Technology Normal University, Nanchang, People’s Republic of China; 6Faculty of Health, York University, Toronto, ON, CanadaCorrespondence: I-Hua Chen, Chinese Academy of Education Big Data, Qufu Normal University, 57 Jingxuan West Road, Qufu, Shandong, 273165, People’s Republic of China, Tel/Fax +86 05374450537, Email aholechen@gmail.com Gordon L Flett, Faculty of Health, York University, LaMarsh Centre for Child & Youth Research, 5022K Technology Enhanced Learning – TEL Keele Campus, Toronto, ON, Canada, Tel +1 416 736 2100 Ext. 33727, Email gflett@yorku.caPurpose: Mattering is essential to university students’ mental health. Feeling valued by others or unimportant can affect their overall well-being. However, most measures for assessing mattering have been developed and tested in Western countries, with limited evaluation of the measures when administered to university students in other regions. This study evaluated the reliability and validity of three mattering-related instruments – the General Mattering Scale (GMS), Anti-Mattering Scale (AMS), and Fear of Not Mattering Inventory (FNMI) among Chinese university students using classical test theory and Rasch analysis.Methods: The study comprised 3594 university students from 19 universities across 13 provinces in mainland China, with a balanced gender distribution of 47.2% females and 52.8% males. Participants’ ages ranged from 18 to 37, averaging 20.02 years. Most (78.4%) were in four-year programs, w

Purpose Biallelic variants in TARS2, encoding the mitochondrial threonyl-tRNA-synthetase, have been reported in a small group of individuals displaying a neurodevelopmental phenotype but with limited neuroradiological data and insufficient evidence for causality of the variants. Methods Exome or genome sequencing was carried out in 15 families. Clinical and neuroradiological evaluation was performed for all affected individuals, including review of 10 previously reported individuals. The pathogenicity of TARS2 variants was evaluated using in vitro assays and a zebrafish model. Results We report 18 new individuals harboring biallelic TARS2 variants. Phenotypically, these individuals show developmental delay/intellectual disability, regression, cerebellar and cerebral atrophy, basal ganglia signal alterations, hypotonia, cerebellar signs, and increased blood lactate. In vitro studies showed that variants within the TARS2301-381 region had decreased binding to Rag GTPases, likely impairing mTORC1 activity. The zebrafish model recapitulated key features of the human phenotype and unraveled dysregulation of downstream targets of mTORC1 signaling. Functional testing of the variants confirmed the pathogenicity in a zebrafish model. Conclusion We define the clinico-radiological spectrum of TARS2-related mitochondrial disease, unveil the likely involvement of the mTORC1 signaling pathway as a distinct molecular mechanism, and establish a TARS2 zebrafish model as an important tool to study variant pathogenicity., Purpose: Biallelic variants in TARS2, encoding the mitochondrial threonyl-tRNA-synthetase, have been reported in a small group of individuals displaying a neurodevelopmental phenotype but with limited neuroradiological data and insufficient evidence for causality of the variants. Methods: Exome or genome sequencing was carried out in 15 families. Clinical and neuroradiological evaluation was performed for all affected individuals, including review of 10 previously reported individuals. The pathogenicity of TARS2 variants was evaluated using in vitro assays and a zebrafish model. Results: We report 18 new individuals harboring biallelic TARS2 variants. Phenotypically, these individuals show developmental delay/intellectual disability, regression, cerebellar and cerebral atrophy, basal ganglia signal alterations, hypotonia, cerebellar signs, and increased blood lactate. In vitro studies showed that variants within the TARS2301-381 region had decreased binding to Rag GTPases, likely impairing mTORC1 activity. The zebrafish model recapitulated key features of the human phenotype and unraveled dysregulation of downstream targets of mTORC1 signaling. Functional testing of the variants confirmed the pathogenicity in a zebrafish model. Conclusion: We define the clinico-radiological spectrum of TARS2-related mitochondrial disease, unveil the likely involvement of the mTORC1 signaling pathway as a distinct molecular mechanism, and establish a TARS2 zebrafish model as an important tool to study variant pathogenicity.

Virtual reality (VR) is increasingly being used in training contexts and for understanding cognitive performance. These environments require multi-sensory interactions that can overload cognitive processing and may unintentionally include elements that disrupt attention. Combined with the use of modern EEGs (electroencephalograms), HMDs (head-mounted devices) can be used to understand the thresholds of cognitive load in these multi-sensory virtual environments. Current research in this field suggests cognitive load is affected by the amount of information being processed at a given time and will increase as different types of stimuli are processed simultaneously, like in VR (Albus, Vogt, & Seufert, 2021; Antonenko, et. al, 2010; Baceviciute et. al, 2020; Hebb & Donderi, 2013; Jerald, 2015; Mayer, 2005; Mayer, 2014; Mayer & Fiorella, 2014; Sanei & Chambers, 2013). However, it is still unclear the nuances of cognitive load when distracted by different features of auditory and visual stimuli. The goal of this research is to establish a cognitive-motor dual-task paradigm for understanding cognitive load in VR based on four distractor types: pitch, speed, amplitude, and proximity. These features are analyzed using objective (EEG) and subjective (questionnaires) measures to separate types of cognitive load. The methods employed in this research aim to provide a novel way of analyzing this type of multi-sensory information and inform designers of specific features that may unknowingly increase extraneous cognitive load in virtual training and learning contexts.

Clinical decision-making concerning patients with traumatic brain injuries (TBI) requires accurate projections of both short- and long-term outcomes. However, models based on these data frequently lack transparency, making it difficult for physicians to trust and comprehend the decisions that are made using these models. Explainable Artificial Intelligence (XAI) has gained increasing interest in recent years as a viable method for enhancing the interpretability of these models. One of the reasons for this rise in interest is that XAI is a relatively novel subject.In this dissertation, we provide a comprehensive examination of the application of XAI algorithms to clinical time-series data in order to determine the prognosis of traumatic brain injury. (TBI). In the first study, a predictive model for traumatic brain injury (TBI) is constructed utilizing an attention-based recurrent neural network (RNN) that combines time-series data with other clinical characteristics. The model achieved a superior level of discriminative ability and outperformed other models. The inability of deep learning models to be interpreted by humans, however, poses a significant barrier to the widespread implementation of these techniques in medical settings. In the second study, XAI strategies for TBI prediction models are evaluated critically. This investigation compares the understandability, fidelity, and stability of six alternative methods. We developed two prediction models for the short-term and long-term outcomes of traumatic brain injury, using structured tabular data and time-series physiologic data, respectively. Our study demonstrates that there are numerous XAI techniques, each with its own set of advantages and disadvantages that researchers must consider when evaluating model decisions. In the third study, a novel framework called WindowSHAP is proposed to explain time-series classifiers using Shapley values, which are a well-known method for determining the significance of fe

Yu-Tong Wu,1,* Dong-Qing Ye,2,* Cui-Hong Lian1 1Department of Dermatology, Shenzhen Second People’s Hospital, Shenzhen, People’s Republic of China; 2Department of Dermatology, The Third People’s Hospital of Longgang District, Shenzhen, People’s Republic of China*These authors contributed equally to this workCorrespondence: Cui-Hong Lian, Department of Dermatology, Shenzhen Second People’s Hospital, 3002 Sungang West Road, Futian District, Shenzhen, People’s Republic of China, Tel +8615814692161, Fax +86 755-83366388, Email liancuihong@email.szu.edu.cnAbstract: Giant condylomata acuminata (a sexually transmitted disease caused by HPV infection) currently is treated in many methods. Surgery, the mainstay treatment of giant condylomata acuminata, may cause a high cost or scar formation. It is important to explore effective and safe treatment options. Although the external treatment of traditional Chinese medicine treatment of condyloma acuminatum has not been widely used, in our case, the use of traditional Chinese medicine successfully treated a perianal giant condyloma acuminatum patient who also suffered from mixed hemorrhoid and IgA nephropathy meanwhile. The treatment process was simple and the effect obvious. There was no recurrence more than 10 months after treatment finished, and the patients felt safe, comfortable and highly coordinated. The outcome of this case suggests that the traditional Chinese medicine might be considered as a mild and effective option for the treatment of giant condyloma acuminatum.Keywords: giant condylomata acuminata, IgA nephropathy, Chinese medicine, HPV infection

Aggregation-induced emission luminogens (AIEgens) are widely used as photosensitizers for image-guided photodynamic therapy (PDT). Due to the limited penetration depth of light in biological tissues, the treatments of deep-seated tumors by visible-light-sensitized aggregation-induced emission (AIE) photosensitizers are severely hampered. Microwave dynamic therapy attracts much attention because microwave irradiation can penetrate very deep tissues and sensitize the photosensitizers to generate reactive oxygen species (ROS). In this work, a mitochondrial-targeting AIEgen (DCPy) is integrated with living mitochondria to form a bioactive AIE nanohybrid. This nanohybrid can not only generate ROS under microwave irradiation to induce apoptosis of deep-seated cancer cells but also reprogram the metabolism pathway of cancer cells through retrieving oxidative phosphorylation (OXPHOS) instead of glycolysis to enhance the efficiency of microwave dynamic therapy. This work demonstrates an effective strategy to integrate synthetic AIEgens and natural living organelles, which would inspire more researchers to develop advanced bioactive nanohybrids for cancer synergistic therapy. © 2023 Wiley-VCH GmbH.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has been responsible for a global pandemic. Monoclonal antibodies (mAbs) have been used as antiviral therapeutics; however, these therapeutics have been limited in efficacy by viral sequence variability in emerging variants of concern (VOCs) and in deployment by the need for high doses. In this study, we leveraged the multi-specific, multi-affinity antibody (Multabody, MB) platform, derived from the human apoferritin protomer, to enable the multimerization of antibody fragments. MBs were shown to be highly potent, neutralizing SARS-CoV-2 at lower concentrations than their corresponding mAb counterparts. In mice infected with SARS-CoV-2, a tri-specific MB targeting three regions within the SARS-CoV-2 receptor binding domain was protective at a 30-fold lower dose than a cocktail of the corresponding mAbs. Furthermore, we showed in vitro that mono-specific MBs potently neutralize SARS-CoV-2 VOCs by leveraging augmented avidity, even when corresponding mAbs lose their ability to neutralize potently, and that tri-specific MBs expanded the neutralization breadth beyond SARS-CoV-2 to other sarbecoviruses. Our work demonstrates how avidity and multi-specificity combined can be leveraged to confer protection and resilience against viral diversity that exceeds that of traditional monoclonal antibody therapies.

The PDF file includes: Supplementary Materials and Methods Figs. S1 to S10 Tables S1 to S3 Legend for data file S1 References (72–92) Other Supplementary Material for this manuscript includes the following: Data file S1 MDAR Reproducibility Checklist

Purpose Biallelic variants in TARS2, encoding the mitochondrial threonyl-tRNA-synthetase, have been reported in a small group of individuals displaying a neurodevelopmental phenotype but with limited neuroradiological data and insufficient evidence for causality of the variants. Methods Exome or genome sequencing was carried out in 15 families. Clinical and neuroradiological evaluation was performed for all affected individuals, including review of 10 previously reported individuals. The pathogenicity of TARS2 variants was evaluated using in vitro assays and a zebrafish model. Results We report 18 new individuals harboring biallelic TARS2 variants. Phenotypically, these individuals show developmental delay/intellectual disability, regression, cerebellar and cerebral atrophy, basal ganglia signal alterations, hypotonia, cerebellar signs, and increased blood lactate. In vitro studies showed that variants within the TARS2301-381 region had decreased binding to Rag GTPases, likely impairing mTORC1 activity. The zebrafish model recapitulated key features of the human phenotype and unraveled dysregulation of downstream targets of mTORC1 signaling. Functional testing of the variants confirmed the pathogenicity in a zebrafish model. Conclusion We define the clinico-radiological spectrum of TARS2-related mitochondrial disease, unveil the likely involvement of the mTORC1 signaling pathway as a distinct molecular mechanism, and establish a TARS2 zebrafish model as an important tool to study variant pathogenicity., Purpose: Biallelic variants in TARS2, encoding the mitochondrial threonyl-tRNA-synthetase, have been reported in a small group of individuals displaying a neurodevelopmental phenotype but with limited neuroradiological data and insufficient evidence for causality of the variants. Methods: Exome or genome sequencing was carried out in 15 families. Clinical and neuroradiological evaluation was performed for all affected individuals, including review of 10 previously reported individuals. The pathogenicity of TARS2 variants was evaluated using in vitro assays and a zebrafish model. Results: We report 18 new individuals harboring biallelic TARS2 variants. Phenotypically, these individuals show developmental delay/intellectual disability, regression, cerebellar and cerebral atrophy, basal ganglia signal alterations, hypotonia, cerebellar signs, and increased blood lactate. In vitro studies showed that variants within the TARS2301-381 region had decreased binding to Rag GTPases, likely impairing mTORC1 activity. The zebrafish model recapitulated key features of the human phenotype and unraveled dysregulation of downstream targets of mTORC1 signaling. Functional testing of the variants confirmed the pathogenicity in a zebrafish model. Conclusion: We define the clinico-radiological spectrum of TARS2-related mitochondrial disease, unveil the likely involvement of the mTORC1 signaling pathway as a distinct molecular mechanism, and establish a TARS2 zebrafish model as an important tool to study variant pathogenicity.

Geoscience foundation models (GFMs) represent a revolutionary approach within Earth sciences to integrate massive cross-disciplinary data for improved simulation and understanding of Earth system dynamics. As a data-centric artificial intelligence paradigm, GFMs extract valuable insights from petabytes of both structured and unstructured data. Their versatility in task specification, diverse inputs and outputs, and multi-modal knowledge representation enable a comprehensive analysis that surpasses the capabilities of individual data sources. Critically, the scalability and generalizability of GFMs empower them to address a wide array of prediction, simulation, and decision tasks related to the intricate interactions among Earth system components. By unraveling the causal mechanisms underlying observed patterns and changes, GFMs contribute to advancing our knowledge of the Earth system and its responses to various drivers and perturbations. Collaboration between domain experts and computer scientists plays a pivotal role in fostering innovations in these invaluable tools for understanding the past, present, and future of our planet. Moreover, we introduce recent advances including key technologies for constructing GFMs, especially remote sensing applications. However, challenges remain in validation and verification, scalability, interpretability, knowledge representation, and addressing social bias. Going forward, the key lies in enhancing model integration, resolution, accuracy, and equity through interdisciplinary teamwork. Despite current limitations, GFMs hold great promise for providing critical insights into pressing issues including climate change, natural hazards, and sustainability through their ability to explore multiple scenarios and quantify uncertainties. Their continued evolution toward integrated, data-driven modeling holds paradigm-shifting potential for Earth science., Comment: the manuscript is under re-writing

Deep mining of B cell repertoires of HIV-1–infected individuals has resulted in the isolation of dozens of HIV-1 broadly neutralizing antibodies (bNAbs). Yet, it remains uncertain whether any such bNAbs alone are sufficiently broad and potent to deploy therapeutically. Here, we engineered HIV-1 bNAbs for their combination on a single multispecific and avid molecule via direct genetic fusion of their Fab fragments to the human apoferritin light chain. The resulting molecule demonstrated a remarkable median IC50 value of 0.0009 µg/mL and 100% neutralization coverage of a broad HIV-1 pseudovirus panel (118 isolates) at a 4 µg/mL cutoff—a 32-fold enhancement in viral neutralization potency compared to a mixture of the corresponding HIV-1 bNAbs. Importantly, Fc incorporation on the molecule and engineering to modulate Fc receptor binding resulted in IgG-like bioavailability in vivo. This robust plug-and-play antibody design is relevant against indications where multispecificity and avidity are leveraged simultaneously to mediate optimal biological activity.

Zhao-Yin Ma,1,* Yong-Ya Wu,2,* Hong-Yin-Long Cui,3 Guang-Yan Yao,3 Hong Bian3,4 1Department of Diagnostic, Medical Integration and Practice Center, Shandong University, Jinan, Shandong, People’s Republic of China; 2Department of Emergency Critical Care Medicine, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, People’s Republic of China; 3Department of Neurology, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People’s Republic of China; 4Department of Neurology, Jinan Central Hospital, Shandong University, Jinan, Shandong, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hong Bian, Department of Neurology, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People’s Republic of China, Tel +86-15318816109, Fax +86-053188382085, Email jnbianh@163.comObjective: Type 2 diabetes mellitus (T2DM) and ischemic stroke, which are common diseases among older people, are closely related to cognitive impairment. This study aims to investigate the influencing factors of post-stroke cognitive impairment (PSCI) in patients with T2DM.Methods: We enrolled 161 patients with T2DM who experienced acute ischemic stroke and were hospitalized in the Department of Neurology, Jinan Central Hospital, Shandong, China. Cognitive function was evaluated with the Montreal Cognitive Assessment scale. According to the results, patients were divided into three groups—the cognitively normal group, mild cognitive impairment group, and severe cognitive impairment group. We analyzed general demographic data, laboratory information, imaging data, the results of neuropsychological evaluation, and clinical features as well as influencing factors of PSCI in these patients and established a prediction model.Results: The three groups of patients were significantly different in terms of age, education level, course of diabe

Ever-increasing quantities of sequencing data have enabled novel insights into the structure, dynamics, and function of microbial communities in the oceans; however, data management efforts are outpaced by the volumes of new data generated. Life-science ontologies representing information about genes, species taxonomy, and environmental parameters hold the promise of improving the digital data ecosystem by making these high-value datasets Findable, Accessible, Reusable, and Interoperable (FAIR). However, efforts using these ontologies to harmonize, integrate, and analyze marine metagenomic data have been limited thus far. In this dissertation, we present three studies demonstrating the relevance of using life-science ontologies to get more out of existing metagenomic datasets by using ontologies to harmonize, integrate, and analyze state-of-the-art marine metagenomic data.In the first study, we present Planet Microbe a cyberinfrastructure system for marine microbiome and physiochemical datasets. This novel web-based platform re-integrates multi- component marine microbiome datasets published in various data repositories into a single harmonized and manually curated resource. Planet Microbe enables the discovery of sequencing data and its accompanying environmental and physiochemical context based on terminology from life- science ontologies. Additionally, Planet Microbe addresses the challenges of creating a cyberinfrastructure platform enabling the open sharing and discovery of historical and ongoing oceanographic marine metagenomic sequencing efforts. The second study created a technical specification by which Planet Microbe's multifaceted marine metagenomic data could be encapsulated within a machine-readable framework to comprehensively represent the physicochemical data accompanying sequencing data using life- science ontologies. The new technical specification leverages Frictionless Data Packages and ontologies from the Open Biological and Biomedical Ontology

Xiaowei Sun,1 Fenqin Xue,2 Jialin Wen,1 Limin Gao,1 Yang Li,1 Lijun Yang,1 Hong Cui1 1Department of Pediatrics, Beijing Friendship Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Department of Core Facility Center, Capital Medical University, Beijing, People’s Republic of ChinaCorrespondence: Lijun Yang; Hong Cui, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, Xicheng District, Beijing, 100050 People’s Republic of China, Email yanglijun1979@ccmu.edu.cn; cuihong100@ccmu.edu.cnObjective: Sleep is necessary for brain maturation in infants. Perinatal hypoxic-ischemic encephalopathy (HIE) is a major cause of chronic neurological disease in infants. Although the developmental changes of electroencephalogram (EEG) in human newborns have been described, little is known about the EEG normal maturation characteristics in rodents and the changes in sleep-awake states caused by hypoxia-ischemia (HI). This study aimed to investigate the pathological response of sleep-wake states in neonatal rats with HIE.Methods: We constructed HIE and sham models on postnatal day (P) 3 rats and continuously monitored them using electroencephalography and electromyography for up to P12. The distribution of sleep-wake states was analyzed to estimate the effects of HIE.Results: Compared with the sham group, the HI group showed lower rapid eye movement (REM) sleep percentage, but wake percentage and frequency was higher during P4-P12. The frequency of REM and non-rapid eye movement (NREM) sleep increased and the duration of REM and NREM sleep decreased after HI induction. However, it gradually returned to the normal level with an increase in daytime.Conclusion: HI damage alters the sleep-wake patterns during early neural development. The findings provide a comprehensive assessment of serial sleep-wake state recordings in neonatal rats from P4-P12.Keywords: electroencephalography, EEG, hypoxia-ischemia, rapid eye movement, premature

Broadly neutralizing antibodies (bnAbs) against HIV-1 are frequently associated with the presence of autoreactivity/polyreactivity, a property that can limit their use as therapeutic agents. The bnAb 4E10, targeting the conserved Membrane proximal external region (MPER) of HIV-1, displays almost pan-neutralizing activity across globally circulating HIV-1 strains but exhibits nonspecific off-target interactions with lipid membranes. The hydrophobic apex of the third complementarity-determining region of the heavy chain (CDRH3) loop, which is essential for viral neutralization, critically contributes to this detrimental effect. Here, we have replaced the aromatic/hydrophobic residues from the apex of the CDRH3 of 4E10 with a single aromatic molecule through chemical modification to generate a variant that preserves the neutralization potency and breadth of 4E10 but with reduced autoreactivity. Collectively, our study suggests that the localized accumulation of aromaticity by chemical modification provides a pathway to ameliorate the adverse effects triggered by the CDRH3 of anti-HIV-1 MPER bnAbs.

SARS-CoV-2, the virus responsible for COVID-19, has caused a global pandemic. Antibodies can be powerful biotherapeutics to fight viral infections. Here, we use the human apoferritin protomer as a modular subunit to drive oligomerization of antibody fragments and transform antibodies targeting SARS-CoV-2 into exceptionally potent neutralizers. Using this platform, half-maximal inhibitory concentration (IC50) values as low as 9 × 10−14 M are achieved as a result of up to 10,000-fold potency enhancements compared to corresponding IgGs. Combination of three different antibody specificities and the fragment crystallizable (Fc) domain on a single multivalent molecule conferred the ability to overcome viral sequence variability together with outstanding potency and IgG-like bioavailability. The MULTi-specific, multiAffinity antiBODY (Multabody or MB) platform thus uniquely leverages binding avidity together with multi-specificity to deliver ultrapotent and broad neutralizers against SARSCoV-2. The modularity of the platform also makes it relevant for rapid evaluation against other infectious diseases of global health importance. Neutralizing antibodies are a promising therapeutic for SARS-CoV-2.

Broadly neutralizing antibodies (bnAbs) against HIV-1 are frequently associated with the presence of autoreactivity/polyreactivity, a property that can limit their use as therapeutic agents. The bnAb 4E10, targeting the conserved Membrane proximal external region (MPER) of HIV-1, displays almost pan-neutralizing activity across globally circulating HIV-1 strains but exhibits nonspecific off-target interactions with lipid membranes. The hydrophobic apex of the third complementarity-determining region of the heavy chain (CDRH3) loop, which is essential for viral neutralization, critically contributes to this detrimental effect. Here, we have replaced the aromatic/hydrophobic residues from the apex of the CDRH3 of 4E10 with a single aromatic molecule through chemical modification to generate a variant that preserves the neutralization potency and breadth of 4E10 but with reduced autoreactivity. Collectively, our study suggests that the localized accumulation of aromaticity by chemical modification provides a pathway to ameliorate the adverse effects triggered by the CDRH3 of anti-HIV-1 MPER bnAbs.

SARS-CoV-2, the virus responsible for COVID-19, has caused a global pandemic. Antibodies can be powerful biotherapeutics to fight viral infections. Here, we use the human apoferritin protomer as a modular subunit to drive oligomerization of antibody fragments and transform antibodies targeting SARS-CoV-2 into exceptionally potent neutralizers. Using this platform, half-maximal inhibitory concentration (IC50) values as low as 9 × 10−14 M are achieved as a result of up to 10,000-fold potency enhancements compared to corresponding IgGs. Combination of three different antibody specificities and the fragment crystallizable (Fc) domain on a single multivalent molecule conferred the ability to overcome viral sequence variability together with outstanding potency and IgG-like bioavailability. The MULTi-specific, multiAffinity antiBODY (Multabody or MB) platform thus uniquely leverages binding avidity together with multi-specificity to deliver ultrapotent and broad neutralizers against SARSCoV-2. The modularity of the platform also makes it relevant for rapid evaluation against other infectious diseases of global health importance. Neutralizing antibodies are a promising therapeutic for SARS-CoV-2.

The BCAP31 gene, located at Xq28, encodes BAP31, which plays a role in ER-to-Golgi anterograde transport. To date, BCAP31 pathogenic variants have been reported in 12 male cases from seven families (six loss of function (LoF) and one missense). Patients had severe intellectual disability (ID), dystonia, deafness, and central hypomyelination, delineating a so-called deafness, dystonia and cerebral hypomyelination syndrome (DDCH). Female carriers are mostly asymptomatic but may present with deafness. BCAP31 is flanked by the SLC6A8 and ABCD1 genes. Contiguous deletions of BCAP31 and ABCD1 and/or SLC6A8 have been described in 12 patients. Patients with deletions including BCAP31 and SLC6A8 have the same phenotype as BCAP31 patients. Patients with deletions of BCAP31 and ABCD1 have contiguous ABCD1 and DXS1375E/BCAP31 deletion syndrome (CADDS), and demonstrate a more severe neurological phenotype with cholestatic liver disease and early death. We report 17 novel families, 14 with intragenic BCAP31 variants (LoF and missense) and three with a deletion of BCAP31 and adjacent genes (comprising two CADDS patients, one male and one symptomatic female). Our study confirms the phenotype reported in males with intragenic LoF variants and shows that males with missense variants exhibit a milder phenotype. Most patients with a LoF pathogenic BCAP31 variant have permanent or transient liver enzyme elevation. We further demonstrate that carrier females (n = 10) may have a phenotype comprising LD, ID, and/or deafness. The male with CADDS had a severe neurological phenotype, but no cholestatic liver disease, and the symptomatic female had moderate ID and cholestatic liver disease.

Broadly neutralizing antibodies (bnAbs) against HIV-1 are frequently associated with the presence of autoreactivity/polyreactivity, a property that can limit their use as therapeutic agents. The bnAb 4E10, targeting the conserved Membrane proximal external region (MPER) of HIV-1, displays almost pan-neutralizing activity across globally circulating HIV-1 strains but exhibits nonspecific off-target interactions with lipid membranes. The hydrophobic apex of the third complementarity-determining region of the heavy chain (CDRH3) loop, which is essential for viral neutralization, critically contributes to this detrimental effect. Here, we have replaced the aromatic/hydrophobic residues from the apex of the CDRH3 of 4E10 with a single aromatic molecule through chemical modification to generate a variant that preserves the neutralization potency and breadth of 4E10 but with reduced autoreactivity. Collectively, our study suggests that the localized accumulation of aromaticity by chemical modification provides a pathway to ameliorate the adverse effects triggered by the CDRH3 of anti-HIV-1 MPER bnAbs.

Broadly neutralizing antibodies (bnAbs) against HIV-1 are frequently associated with the presence of autoreactivity/polyreactivity, a property that can limit their use as therapeutic agents. The bnAb 4E10, targeting the conserved Membrane proximal external region (MPER) of HIV-1, displays almost pan-neutralizing activity across globally circulating HIV-1 strains but exhibits nonspecific off-target interactions with lipid membranes. The hydrophobic apex of the third complementarity-determining region of the heavy chain (CDRH3) loop, which is essential for viral neutralization, critically contributes to this detrimental effect. Here, we have replaced the aromatic/hydrophobic residues from the apex of the CDRH3 of 4E10 with a single aromatic molecule through chemical modification to generate a variant that preserves the neutralization potency and breadth of 4E10 but with reduced autoreactivity. Collectively, our study suggests that the localized accumulation of aromaticity by chemical modification provides a pathway to ameliorate the adverse effects triggered by the CDRH3 of anti-HIV-1 MPER bnAbs.

SARS-CoV-2, the virus responsible for COVID-19, has caused a global pandemic. Antibodies can be powerful biotherapeutics to fight viral infections. Here, we use the human apoferritin protomer as a modular subunit to drive oligomerization of antibody fragments and transform antibodies targeting SARS-CoV-2 into exceptionally potent neutralizers. Using this platform, half-maximal inhibitory concentration (IC50) values as low as 9 × 10−14 M are achieved as a result of up to 10,000-fold potency enhancements compared to corresponding IgGs. Combination of three different antibody specificities and the fragment crystallizable (Fc) domain on a single multivalent molecule conferred the ability to overcome viral sequence variability together with outstanding potency and IgG-like bioavailability. The MULTi-specific, multiAffinity antiBODY (Multabody or MB) platform thus uniquely leverages binding avidity together with multi-specificity to deliver ultrapotent and broad neutralizers against SARSCoV-2. The modularity of the platform also makes it relevant for rapid evaluation against other infectious diseases of global health importance. Neutralizing antibodies are a promising therapeutic for SARS-CoV-2.

SARS-CoV-2, the virus responsible for COVID-19, has caused a global pandemic. Antibodies can be powerful biotherapeutics to fight viral infections. Here, we use the human apoferritin protomer as a modular subunit to drive oligomerization of antibody fragments and transform antibodies targeting SARS-CoV-2 into exceptionally potent neutralizers. Using this platform, half-maximal inhibitory concentration (IC50) values as low as 9 × 10−14 M are achieved as a result of up to 10,000-fold potency enhancements compared to corresponding IgGs. Combination of three different antibody specificities and the fragment crystallizable (Fc) domain on a single multivalent molecule conferred the ability to overcome viral sequence variability together with outstanding potency and IgG-like bioavailability. The MULTi-specific, multi-Affinity antiBODY (Multabody or MB) platform thus uniquely leverages binding avidity together with multi-specificity to deliver ultrapotent and broad neutralizers against SARS-CoV-2. The modularity of the platform also makes it relevant for rapid evaluation against other infectious diseases of global health importance. Neutralizing antibodies are a promising therapeutic for SARS-CoV-2.

Power systems have become more vulnerable to cascading failures and blackouts with the growth of transmission and generation networks. Critical loads and power blackouts can threaten with massive economic damage to the society The situation worsens due to the added complexity of their intermittent behavior of the growing penetration of renewable energy sources. Thus, the importance to achieve a reliable power system, i.e., a system able to meet the end-users' electricity needs when considering unexpected contingencies or any other factor that may reduce the electricity availability. In the first part of this dissertation, stochastic and robust optimization approaches are applied for large-scale modeling of reliable expansion and operations of power systems under consecutive contingencies. In the two-stage stochastic optimization model, the expansion planning and operational variables under normal conditions are the "here and now" decisions. The operational variables under contingency are the "wait and see" decisions with a respective contingency probability assigned. First, a study for reliable power grid expansion considering N-1-1 contingencies is presented. The N-1-1 contingency consists of the consecutive loss of two components in a power system with intervening time for system adjustments between failures. Second, a two-stage stochastic power grid expansion considering multiple N-1-1 contingencies is studied. A reliable power system expansion planning may be achieved by placing new transmission lines and generation units while checking the grid's survivability under different contingency scenarios with defined probabilities. Finally, a study of N-1-1 contingency-constrained unit commitment with renewable integration and corrective actions is presented. Meeting the end-use customers' demands is crucial for energy companies, even when unexpected and consecutive failures are present. This task has increased its complexity considerably due to the high integration o

Ji-sheng Wang,1,2,* Xue-feng Gong,3,4,* Jun-long Feng,1,2,* Hai-song Li,2 Xiao Li,5 Sheng Deng,1,2 Pei-zhong Ren,3,4 Jia-mei Wang,3,4 Ming-sheng Lv,3,4 Rui-feng Jin,3,4 Qiu-yi Chen,3,4 Bin Wang,2 Hong-sheng Cui4 1First Clinical Medical College, Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China; 2Andrology Department, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, People’s Republic of China; 3The Third Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China; 4Pneumology Department, The Third Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China; 5Department of Andrology, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450046, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bin WangAndrology Department, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, People’s Republic of ChinaEmail dayiwangbln@sina.comHong-sheng CuiPneumology Department, The Third Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of ChinaEmail Hshcui@sina.comBackground: Jiawei Shengjiang Powder (JWSJP) is a classical Chinese medicinal formula, which has been widely applied in the treatment of asthma and complications for many years due to its curative effect.Aim: To verify the effect of JWSJP in improving abnormal sperm motility caused by asthma and to explore its potential mechanism.Materials and Methods: The active compounds of JWSJP were obtained from high performance liquid chromatography tandem mass spectrometry and the Traditional Chinese Medicine System Pharmacology. The key active components and targets of JWSJP were predicted based on network pharmacological analysis and bioinformatics research. Rats were ra

Yu Liu,1 Wen-Li Zhang,1 Ji-Qiang Bu,1 Jian-Jun Gu,1 Yong-Quan Sun,1 Hong-Zhan Cui,1 Da-Wei Wang,2 Zi-Ying Chen1 1Department of Cardiac Surgery, Second Hospital of Hebei Medical University, Shi Jiazhuang, 050000, People’s Republic of China; 2Department of Cardiac Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, 075000, People’s Republic of ChinaCorrespondence: Zi-Ying ChenDepartment of Cardiac Surgery, Second Hospital of Hebei Medical University, No. 215 of Heping West Road, XinHua District, Shijiazhuang, 050000, People’s Republic of ChinaTel +86 15803210520Fax +86 311 6600 2995Email chenziying258@163.comObjective: This study aims to investigate the value of thromboelastography (TEG) in predicting blood loss, and its relationship with blood transfusion demand, during the perioperative period in off-pump coronary artery bypass grafting (OPCABG).Methods: The data of 398 patients undergoing OPCABG were retrospectively analyzed. Blood was drawn before anesthesia induction (T1) and at 10 minutes after heparin neutralization (T2) for further TEG detection. The patients were divided into two groups based on the results at T2: a TEG normal group and a TEG abnormal group. Logistic regression analysis was used to predict the related factors contributing to the significant increase in perioperative blood loss (more than 20% of the estimated blood volume).Results: There were 277 (69.6%) patients in the TEG normal group and 121 (30.4%) in the TEG abnormal group. Compared with the TEG normal group, the volume of blood loss, red blood cell count, and volume of plasma transfusion in the TEG abnormal group significantly increased within 24 hours after surgery. The results of the logistic regression analysis identified the use of clopidogrel, platelet count at T2, fibrinogen level at T2, and abnormality in TEG value as independent predictors for the significant increase in perioperative blood loss (P < 0.001).Conclusio

Ontology, as a formal and explicit specification of a shared conceptualization for a particular domain, is useful in information extraction. On the one hand, since information extraction is concerned with retrieving information for a particular domain, formally and explicitly specifying the concepts of that domain through an ontology defines the boundary of what information needs to be extracted. On the other hand, an ontology, typically consisting of classes (or concepts), attributes (or properties), and relationships (or relations among class members), contains the structured information that information extraction systems aim to extract. In this thesis, we are interested in how using an ontology can improve the information extraction process. We explore two research directions that both employ ontologies in the information extraction process, temporal normalization and biomedical concept normalization. In both research directions, we show that leveraging resources in ontologies helps to build high-performance information extraction systems, and presenting the extracted output using such ontologies makes the structured information concise and interchangeable.

The inducible co-stimulator (ICOS) is a member of the CD28/B7 superfamily, and delivers a positive co-stimulatory signal to activated T cells upon binding to its ligand (ICOS-L). Dysregulation of this pathway has been implicated in autoimmune diseases and cancer, and is currently under clinical investigation as an immune checkpoint blockade. Here, we describe the molecular interactions of the ICOS/ICOS-L immune complex at 3.3 Ao resolution. A central FDPPPF motif and residues within the CC' loop of ICOS are responsible for the specificity of the interaction with ICOS-L, with a distinct receptor binding orientation in comparison to other family members. Furthermore, our structure and binding data reveal that the ICOS N110 N-linked glycan participates in ICOS-L binding. In addition, we report crystal structures of ICOS and ICOS-L in complex with monoclonal antibodies under clinical evaluation in immunotherapy. Strikingly, antibody paratopes closely mimic receptor-ligand binding core interactions, in addition to contacting peripheral residues to confer high binding affinities. Our results uncover key molecular interactions of an immune complex central to human adaptive immunity and have direct implications for the ongoing development of therapeutic interventions targeting immune checkpoint receptors. The inducible co-stimulator (ICOS) is a member of the CD28/B7 superfamily, binding its ligand (ICOS-L) on activated T cells. The structure of the ICOS/ICOS-L complex reveals a distinct receptor binding orientation. The structures of ICOS and ICOS-L in complex with potentially therapeutic antibodies suggest the structural basis of such antibodies' efficacies and high binding affinities.

The inducible co-stimulator (ICOS) is a member of the CD28/B7 superfamily, and delivers a positive co-stimulatory signal to activated T cells upon binding to its ligand (ICOS-L). Dysregulation of this pathway has been implicated in autoimmune diseases and cancer, and is currently under clinical investigation as an immune checkpoint blockade. Here, we describe the molecular interactions of the ICOS/ICOS-L immune complex at 3.3 Ao resolution. A central FDPPPF motif and residues within the CC' loop of ICOS are responsible for the specificity of the interaction with ICOS-L, with a distinct receptor binding orientation in comparison to other family members. Furthermore, our structure and binding data reveal that the ICOS N110 N-linked glycan participates in ICOS-L binding. In addition, we report crystal structures of ICOS and ICOS-L in complex with monoclonal antibodies under clinical evaluation in immunotherapy. Strikingly, antibody paratopes closely mimic receptor-ligand binding core interactions, in addition to contacting peripheral residues to confer high binding affinities. Our results uncover key molecular interactions of an immune complex central to human adaptive immunity and have direct implications for the ongoing development of therapeutic interventions targeting immune checkpoint receptors. The inducible co-stimulator (ICOS) is a member of the CD28/B7 superfamily, binding its ligand (ICOS-L) on activated T cells. The structure of the ICOS/ICOS-L complex reveals a distinct receptor binding orientation. The structures of ICOS and ICOS-L in complex with potentially therapeutic antibodies suggest the structural basis of such antibodies' efficacies and high binding affinities.

The inducible co-stimulator (ICOS) is a member of the CD28/B7 superfamily, and delivers a positive co-stimulatory signal to activated T cells upon binding to its ligand (ICOS-L). Dysregulation of this pathway has been implicated in autoimmune diseases and cancer, and is currently under clinical investigation as an immune checkpoint blockade. Here, we describe the molecular interactions of the ICOS/ICOS-L immune complex at 3.3 Å resolution. A central FDPPPF motif and residues within the CC' loop of ICOS are responsible for the specificity of the interaction with ICOS-L, with a distinct receptor binding orientation in comparison to other family members. Furthermore, our structure and binding data reveal that the ICOS N110 N-linked glycan participates in ICOS-L binding. In addition, we report crystal structures of ICOS and ICOS-L in complex with monoclonal antibodies under clinical evaluation in immunotherapy. Strikingly, antibody paratopes closely mimic receptor-ligand binding core interactions, in addition to contacting peripheral residues to confer high binding affinities. Our results uncover key molecular interactions of an immune complex central to human adaptive immunity and have direct implications for the ongoing development of therapeutic interventions targeting immune checkpoint receptors.

The inducible co-stimulator (ICOS) is a member of the CD28/B7 superfamily, and delivers a positive co-stimulatory signal to activated T cells upon binding to its ligand (ICOS-L). Dysregulation of this pathway has been implicated in autoimmune diseases and cancer, and is currently under clinical investigation as an immune checkpoint blockade. Here, we describe the molecular interactions of the ICOS/ICOS-L immune complex at 3.3 Ao resolution. A central FDPPPF motif and residues within the CC' loop of ICOS are responsible for the specificity of the interaction with ICOS-L, with a distinct receptor binding orientation in comparison to other family members. Furthermore, our structure and binding data reveal that the ICOS N110 N-linked glycan participates in ICOS-L binding. In addition, we report crystal structures of ICOS and ICOS-L in complex with monoclonal antibodies under clinical evaluation in immunotherapy. Strikingly, antibody paratopes closely mimic receptor-ligand binding core interactions, in addition to contacting peripheral residues to confer high binding affinities. Our results uncover key molecular interactions of an immune complex central to human adaptive immunity and have direct implications for the ongoing development of therapeutic interventions targeting immune checkpoint receptors. The inducible co-stimulator (ICOS) is a member of the CD28/B7 superfamily, binding its ligand (ICOS-L) on activated T cells. The structure of the ICOS/ICOS-L complex reveals a distinct receptor binding orientation. The structures of ICOS and ICOS-L in complex with potentially therapeutic antibodies suggest the structural basis of such antibodies' efficacies and high binding affinities.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes Coronavirus Disease 2019 (COVID-19), has caused a global pandemic. Antibodies are powerful biotherapeutics to fight viral infections; however, discovery of the most potent and broadly acting clones can be lengthy. Here, we used the human apoferritin protomer as a modular subunit to drive oligomerization of antibody fragments and transform antibodies targeting SARS-CoV-2 into exceptionally potent neutralizers. Using this platform, half-maximal inhibitory concentration (IC50) values as low as 9 × 10−14 M were achieved as a result of up to 10,000-fold potency enhancements. Combination of three different antibody specificities and the fragment crystallizable (Fc) domain on a single multivalent molecule conferred the ability to overcome viral sequence variability together with outstanding potency and Ig-like in vivo bioavailability. This MULTi-specific, multi-Affinity antiBODY (Multabody; or MB) platform contributes a new class of medical countermeasures against COVID-19 and an efficient approach to rapidly deploy potent and broadly-acting therapeutics against infectious diseases of global health importance.

In order to reduce the weight and improve aerodynamic characteristics, the new aircraft generally adopts lightweight composite materials and high-aspect-ratio layout. Such the structural layout aircraft will produce large nonlinear aeroelastic deformation under the action of aerodynamic loads. Due to the anisotropy of the composite, the composite ply angle of wing skin has a great influence on the elastic deformation of the high-aspect-ratio wing. In order to study the influence of the ply angle on the nonlinear static aeroelastic wing deformation, based on CFD/CSD unidirectional fluid-solid coupling, the structural deformation and stress of high-aspect-ratio composite wing were numerically solved. The wing deformation along the lift direction was taken as the optimization target. The structure strength was taken as the constraint. The ply angle for the composite skin of the high-aspect-ratio composite wing was optimized by the Screening method. The optimization results show the nonlinear static aeroelastic deformation of the wing in the lift direction is reduced by 39.1 %. The maximum stress of the wing beam and rib is reduced by 39.0 %. The maximum Tsai-Wu failure factor of the wing skin is reduced by 47.1 %.

Explainability in machine learning remains a critical unsolved challenge that slows the adoption of machine learning systems in real-world applications. Machine learning approaches are widely applied to complex natural language processing tasks such as question answering (QA) where explainability directly impacts end users understanding and trust. This thesis is particularly focused on improving the explainability of question answering systems via textual evidence retrieval and explaining learned representations within QA systems. Evidence retrieval in question answering (QA) is necessary not only to explain the decisions but also improve QA performance. We present 3 simple but effective unsupervised techniques for retrieving evidence texts necessary for explaining the QA inference process : Relevance-Overlap-Coverage Retriever (ROCC), Alignment Retriever and Alignment based Iterative Retriever ({\bf AIR}). ROCC (a) maximizes the relevance of the selected sentences, (b) minimizes the overlap between the selected facts, and (c) maximizes the coverage of both question and answer. Alignment retriever computes similarity between query and evidence facts by computing cosine similarity of individual tokens in embedding space. AIR extends the alignment retriever by combining two techniques: (a) adding an iterative process that reformulates queries focusing on terms that are not covered by existing justifications, which (b) stops when the terms in the given question and candidate answers are covered by the retrieved justifications. We show that, when evidence retrieved by ROCC, Alignment retriever and {\bf AIR} are fed to state-of-the-art transformer based QA methods, we substantially improve the state-of-the-art QA performance on multiple QA datasets. We further improve the state-of-the-art performance by adding supervision for evidence retrieval and show several representational analyses of the supervised retrieval based QA model.

Zhao-Hua Wang,1,* Chang Shu,2,* Xiao Ran,1 Cui-Hong Xie,1 Lei Zhang2 1Department of Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, People’s Republic of China; 2Department of Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lei ZhangDepartment of Surgery, Tongji Hospital, 1095 Jiefang Avenue, Wuhan 430030, People’s Republic of ChinaTel +86-27-83665312Email zhangl@tjh.tjmu.edu.cnBackground: Coronavirus disease 2019 (COVID-19) is a worldwide pandemic outbreak with a high mortality. Prognostic factors of critically ill patients with COVID-19 have not been fully elucidated yet.Methods: In the present study, 59 patients with COVID-19 from the intensive care unit of the Caidian Branch of Tongji Hospital were enrolled. Epidemiological, demographic, clinical, laboratory, radiological, treatment data, and clinical outcomes were collected. Prognostic factors were statistically defined.Results: Of the 59 patients studied (67.4± 11.3 years), 38 patients were male, 51 had underlying diseases, and 41 patients died during admission. Compared with the survivors, the deceased patients were of older age, had more smoking history, severer fatigue, and diarrhea, a higher incidence of multiple organ injuries, more deteriorative lymphopenia and thrombocytopenia, remarkably impaired cellular immune response, and strengthened cytokine release. Age higher than 70 (OR=2.76, 95% CI=1.45– 5.23), arrhythmia (OR=4.76, 95% CI=1.59– 14.25), and a Sequential Organ Failure Assessment (SOFA) score above 4 (OR=5.16, 95% CI=1.29– 20.55) were identified as risk factors for mortality of patients.Conclusion: Critically ill COVID-19 patients aged higher than 70, arrhythmia, or a SOFA score above 4 have a high ri

COX20/FAM36A encodes a mitochondrial complex IV assembly factor important for COX2 activation. Only one homozygous COX20 missense mutation has been previously described in two separate consanguineous families. We report four subjects with features that include childhood hypotonia, areflexia, ataxia, dysarthria, dystonia, and sensory neuropathy. Exome sequencing in all four subjects identified the same novel COX20 variants. One variant affected the splice donor site of intron-one (c.41A>G), while the other variant (c.157+3G>C) affected the splice donor site of intron-two. cDNA and protein analysis indicated that no full-length cDNA or protein was generated. These subjects expand the phenotype associated with COX20 deficiency.

COX20/FAM36A encodes a mitochondrial complex IV assembly factor important for COX2 activation. Only one homozygous COX20 missense mutation has been previously described in two separate consanguineous families. We report four subjects with features that include childhood hypotonia, areflexia, ataxia, dysarthria, dystonia, and sensory neuropathy. Exome sequencing in all four subjects identified the same novel COX20 variants. One variant affected the splice donor site of intron-one (c.41A>G), while the other variant (c.157+3G>C) affected the splice donor site of intron-two. cDNA and protein analysis indicated that no full-length cDNA or protein was generated. These subjects expand the phenotype associated with COX20 deficiency.

BackgroundTaxonomic descriptions are traditionally composed in natural language and published in a format that cannot be directly used by computers. The Exploring Taxon Concepts (ETC) project has been developing a set of web-based software tools that convert morphological descriptions published in telegraphic style to character data that can be reused and repurposed. This paper introduces the first semi-automated pipeline, to our knowledge, that converts morphological descriptions into taxon-character matrices to support systematics and evolutionary biology research. We then demonstrate and evaluate the use of the ETC Input Creation - Text Capture - Matrix Generation pipeline to generate body part measurement matrices from a set of 188 spider morphological descriptions and report the findings.ResultsFrom the given set of spider taxonomic publications, two versions of input (original and normalized) were generated and used by the ETC Text Capture and ETC Matrix Generation tools. The tools produced two corresponding spider body part measurement matrices, and the matrix from the normalized input was found to be much more similar to a gold standard matrix hand-curated by the scientist co-authors. Special conventions utilized in the original descriptions (e.g., the omission of measurement units) were attributed to the lower performance of using the original input. The results show that simple normalization of the description text greatly increased the quality of the machine-generated matrix and reduced edit effort. The machine-generated matrix also helped identify issues in the gold standard matrix.ConclusionsETC Text Capture and ETC Matrix Generation are low-barrier and effective tools for extracting measurement values from spider taxonomic descriptions and are more effective when the descriptions are self-contained. Special conventions that make the description text less self-contained challenge automated extraction of data from biodiversity descriptions and hinder the

BackgroundTaxonomic descriptions are traditionally composed in natural language and published in a format that cannot be directly used by computers. The Exploring Taxon Concepts (ETC) project has been developing a set of web-based software tools that convert morphological descriptions published in telegraphic style to character data that can be reused and repurposed. This paper introduces the first semi-automated pipeline, to our knowledge, that converts morphological descriptions into taxon-character matrices to support systematics and evolutionary biology research. We then demonstrate and evaluate the use of the ETC Input Creation - Text Capture - Matrix Generation pipeline to generate body part measurement matrices from a set of 188 spider morphological descriptions and report the findings.ResultsFrom the given set of spider taxonomic publications, two versions of input (original and normalized) were generated and used by the ETC Text Capture and ETC Matrix Generation tools. The tools produced two corresponding spider body part measurement matrices, and the matrix from the normalized input was found to be much more similar to a gold standard matrix hand-curated by the scientist co-authors. Special conventions utilized in the original descriptions (e.g., the omission of measurement units) were attributed to the lower performance of using the original input. The results show that simple normalization of the description text greatly increased the quality of the machine-generated matrix and reduced edit effort. The machine-generated matrix also helped identify issues in the gold standard matrix.ConclusionsETC Text Capture and ETC Matrix Generation are low-barrier and effective tools for extracting measurement values from spider taxonomic descriptions and are more effective when the descriptions are self-contained. Special conventions that make the description text less self-contained challenge automated extraction of data from biodiversity descriptions and hinder the

Natural language descriptions of organismal phenotypes, a principal object of study in biology, are abundant in the biological literature. Expressing these phenotypes as logical statements using ontologies would enable large-scale analysis on phenotypic information from diverse systems. However, considerable human effort is required to make these phenotype descriptions amenable to machine reasoning. Natural language processing tools have been developed to facilitate this task, and the training and evaluation of these tools depend on the availability of high quality, manually annotated gold standard data sets. We describe the development of an expert-curated gold standard data set of annotated phenotypes for evolutionary biology. The gold standard was developed for the curation of complex comparative phenotypes for the Phenoscape project. It was created by consensus among three curators and consists of entity-quality expressions of varying complexity. We use the gold standard to evaluate annotations created by human curators and those generated by the Semantic CharaParser tool. Using four annotation accuracy metrics that can account for any level of relationship between terms from two phenotype annotations, we found that machine-human consistency, or similarity, was significantly lower than inter-curator (human-human) consistency. Surprisingly, allowing curatorsaccess to external information did not significantly increase the similarity of their annotations to the gold standard or have a significant effect on inter-curator consistency. We found that the similarity of machine annotations to the gold standard increased after new relevant ontology terms had been added. Evaluation by the original authors of the character descriptions indicated that the gold standard annotations came closer to representing their intended meaning than did either the curator or machine annotations. These findings point toward ways to better design software to augment human curators and the

Background: When phenotypic characters are described in the literature, they may be constrained or clarified with additional information such as the location or degree of expression, these terms are called "modifiers". With effort underway to convert narrative character descriptions to computable data, ontologies for such modifiers are needed. Such ontologies can also be used to guide term usage in future publications. Spatial and method modifiers are the subjects of ontologies that already have been developed or are under development. In this work, frequency (e.g., rarely, usually), certainty (e.g., probably, definitely), degree (e.g., slightly, extremely), and coverage modifiers (e.g., sparsely, entirely) are collected, reviewed, and used to create two modifier ontologies with different design considerations. The basic goal is to express the sequential relationships within a type of modifiers, for example, usually is more frequent than rarely, in order to allow data annotated with ontology terms to be classified accordingly. Method: Two designs are proposed for the ontology, both using the list pattern: a closed ordered list (i.e., five-bin design) and an open ordered list design. The five-bin design puts the modifier terms into a set of 5 fixed bins with interval object properties, for example, one_level_more/less_frequently_than, where new terms can only be added as synonyms to existing classes. The open list approach starts with 5 bins, but supports the extensibility of the list via ordinal properties, for example, more/less_frequently_than, allowing new terms to be inserted as a new class anywhere in the list. The consequences of the different design decisions are discussed in the paper. CharaParser was used to extract modifiers from plant, ant, and other taxonomic descriptions. After a manual screening, 130 modifier words were selected as the candidate terms for the modifier ontologies. Four curators/experts (three biologists and one information scientist spe

Scholarly publications of biodiversity literature contain a vast amount of information in human readable format. The detailed morphological descriptions in these publications contain rich information that can be extracted to facilitate analysis and computational biology research. However, the idiosyncrasies of morphological descriptions still pose a number of challenges to machines. In this work, we demonstrate the use of two different approaches to resolve meronym (i.e. part-of) relations between anatomical parts and their anchor organs, including a syntactic rule-based approach and a SVM-based (support vector machine) method. Both methods made use of domain ontologies. We compared the two approaches with two other baseline methods and the evaluation results show the syntactic methods (92.1% F1 score) outperformed the SVM methods (80.7% F1 score) and the part-of ontologies were valuable knowledge sources for the task. It is notable that the mistakes made by the two approaches rarely overlapped. Additional tests will be conducted on the development version of the Explorer of Taxon Concepts toolkit before we make the functionality publicly available. Meanwhile, we will further investigate and leverage the complementary nature of the two approaches to further drive down the error rate, as in practical application, even a 1% error rate could lead to hundreds of errors.

Scholarly publications of biodiversity literature contain a vast amount of information in human readable format. The detailed morphological descriptions in these publications contain rich information that can be extracted to facilitate analysis and computational biology research. However, the idiosyncrasies of morphological descriptions still pose a number of challenges to machines. In this work, we demonstrate the use of two different approaches to resolve meronym (i.e. part-of) relations between anatomical parts and their anchor organs, including a syntactic rule-based approach and a SVM-based (support vector machine) method. Both methods made use of domain ontologies. We compared the two approaches with two other baseline methods and the evaluation results show the syntactic methods (92.1% F1 score) outperformed the SVM methods (80.7% F1 score) and the part-of ontologies were valuable knowledge sources for the task. It is notable that the mistakes made by the two approaches rarely overlapped. Additional tests will be conducted on the development version of the Explorer of Taxon Concepts toolkit before we make the functionality publicly available. Meanwhile, we will further investigate and leverage the complementary nature of the two approaches to further drive down the error rate, as in practical application, even a 1% error rate could lead to hundreds of errors.

Natural language descriptions of organismal phenotypes, a principal object of study in biology, are abundant in the biological literature. Expressing these phenotypes as logical statements using ontologies would enable large-scale analysis on phenotypic information from diverse systems. However, considerable human effort is required to make these phenotype descriptions amenable to machine reasoning. Natural language processing tools have been developed to facilitate this task, and the training and evaluation of these tools depend on the availability of high quality, manually annotated gold standard data sets. We describe the development of an expert-curated gold standard data set of annotated phenotypes for evolutionary biology. The gold standard was developed for the curation of complex comparative phenotypes for the Phenoscape project. It was created by consensus among three curators and consists of entity-quality expressions of varying complexity. We use the gold standard to evaluate annotations created by human curators and those generated by the Semantic CharaParser tool. Using four annotation accuracy metrics that can account for any level of relationship between terms from two phenotype annotations, we found that machine-human consistency, or similarity, was significantly lower than inter-curator (human-human) consistency. Surprisingly, allowing curatorsaccess to external information did not significantly increase the similarity of their annotations to the gold standard or have a significant effect on inter-curator consistency. We found that the similarity of machine annotations to the gold standard increased after new relevant ontology terms had been added. Evaluation by the original authors of the character descriptions indicated that the gold standard annotations came closer to representing their intended meaning than did either the curator or machine annotations. These findings point toward ways to better design software to augment human curators and the

Background: When phenotypic characters are described in the literature, they may be constrained or clarified with additional information such as the location or degree of expression, these terms are called "modifiers". With effort underway to convert narrative character descriptions to computable data, ontologies for such modifiers are needed. Such ontologies can also be used to guide term usage in future publications. Spatial and method modifiers are the subjects of ontologies that already have been developed or are under development. In this work, frequency (e.g., rarely, usually), certainty (e.g., probably, definitely), degree (e.g., slightly, extremely), and coverage modifiers (e.g., sparsely, entirely) are collected, reviewed, and used to create two modifier ontologies with different design considerations. The basic goal is to express the sequential relationships within a type of modifiers, for example, usually is more frequent than rarely, in order to allow data annotated with ontology terms to be classified accordingly. Method: Two designs are proposed for the ontology, both using the list pattern: a closed ordered list (i.e., five-bin design) and an open ordered list design. The five-bin design puts the modifier terms into a set of 5 fixed bins with interval object properties, for example, one_level_more/less_frequently_than, where new terms can only be added as synonyms to existing classes. The open list approach starts with 5 bins, but supports the extensibility of the list via ordinal properties, for example, more/less_frequently_than, allowing new terms to be inserted as a new class anywhere in the list. The consequences of the different design decisions are discussed in the paper. CharaParser was used to extract modifiers from plant, ant, and other taxonomic descriptions. After a manual screening, 130 modifier words were selected as the candidate terms for the modifier ontologies. Four curators/experts (three biologists and one information scientist spe

Hong Cui,1 Feng Han,1 Ling Zhang,1 Li Wang,1 Mukesh Kumar2 1Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Tumor Hospital of Zhengzhou University, Zhengzhou City, Henan Province 450008, China; 2Chandra Shekhar Singh College of Pharmacy, Allahabad, India Introduction: Hepatocellular carcinoma (HCC) is one of the known major health problems across the globe, and is sixth ranked among all cancer, due to its high mortality rate. Polyunsaturated fatty acids (PUFAs) play an important role in the formation of a cell membrane, along with the fluidity of the membrane and proteins. Gamma linolenic acid (GLA) is member of the ω-6 family of PUFAs and converts into the arachidonic acid via a series of elongation and desaturation reactions. The aim of the current investigation was to scrutinize the effect of GLA on mitochondrial mediated apoptosis and anti-inflammatory pathway against diethylnitrosamine (DEN) induced HCC.Materials and methods: Chemical carcinogenesis in Wistar rats was introduced by an intraperitoneal dose of DEN (200 mg/kg). The rats received the various doses of GLA for 22 weeks. The progressions of serum biomarkers and histopathology components of hepatic tissue were used to access the prophylactic effects. The antioxidant parameters, cancer preventive agent status, and apoptosis mechanism were reviewed to scrutinize the possible mechanism.Results: Dose-dependent treatment of GLA significantly (P<-0.001) modulated the hepatic nodules, hepatic, body weight, antioxidant, and non-hepatic parameters. Curiously, the Real-time polymerase chain reaction (RT-PCR) and immunoblotting showed the GLA altered reduced the hypoxic microenvironment, mitochondrial mediated death apoptosis, and anti-inflammsatory pathways.Conclusion: On the basis of the above results, we can conclude that the GLA exhibited a chemoprotective effect against DEN induced HCC that might be due to the altered hypoxic microenvironment, mitochondrial mediated death

Geographic information systems (GIS) are tools used to facilitate locational decision making in interactive, graphic-based environments. GIS and interactive maps allow users to customize displays and manipulate data for accomplishing a variety of tasks, ranging from map interpretation to wayfinding and land use planning. Although originally adopted for professional use, GIS software is increasingly utilized by both expert and non-expert users. Despite the improved availability, training in cartographic design has not followed suit and studies claim that users often employ inefficient displays for task completion. Research on naïve realism indicates that people exhibit a bias for realistic depictions containing irrelevant, extraneous details, leading to increased cognitive load and decreased task performance. This dissertation explores how display realism affects decision making task performance when using a GIS. Prior studies examining naïve realism have primarily had users perform map reading and inference tasks with static displays. Natural resource management was selected as a test case because it often involves the use of geospatial tools and data and people with varying levels of GIS expertise. This research had expert and novice users utilize a GIS to perform site selection tasks for a natural resource management decision making scenario. The results indicate that increased display realism has a negative impact on task performance, especially with regards to task completion time. Individuals in both the expert and novice groups were influenced by naïve realism. It was observed that expert and novice users employed different strategies for task completion and the implications on task performance are discussed. Ultimately, the study results contribute to the theory of naïve realism and make recommendations that inform the use of task-appropriate graphic displays in an interactive mapping environment.

Esterases receive special attention because of their wide distribution in biological systems and environments and their importance for physiology and chemical synthesis. The prediction of esterases’ substrate promiscuity level from sequence data and the molecular reasons why certain such enzymes are more promiscuous than others remain to be elucidated. This limits the surveillance of the sequence space for esterases potentially leading to new versatile biocatalysts and new insights into their role in cellular function. Here, we performed an extensive analysis of the substrate spectra of 145 phylogenetically and environmentally diverse microbial esterases, when tested with 96 diverse esters. We determined the primary factors shaping their substrate range by analyzing substrate range patterns in combination with structural analysis and protein–ligand simulations. We found a structural parameter that helps rank (classify) the promiscuity level of esterases from sequence data at 94% accuracy. This parameter, the active site effective volume, exemplifies the topology of the catalytic environment by measuring the active site cavity volume corrected by the relative solvent accessible surface area (SASA) of the catalytic triad. Sequences encoding esterases with active site effective volumes (cavity volume/SASA) above a threshold show greater substrate spectra, which can be further extended in combination with phylogenetic data. This measure provides also a valuable tool for interrogating substrates capable of being converted. This measure, found to be transferred to phosphatases of the haloalkanoic acid dehalogenase superfamily and possibly other enzymatic systems, represents a powerful tool for low-cost bioprospecting for esterases with broad substrate ranges, in large scale sequence data sets.

DUF89 family proteins occur widely in both prokaryotes and eukaryotes, but their functions are unknown. Here we define three DUF89 subfamilies (I, II, and III), with subfamily II being split into stand-alone proteins and proteins fused to pantothenate kinase (PanK). We demonstrated that DUF89 proteins have metal-dependent phosphatase activity against reactive phosphoesters or their damaged forms, notably sugar phosphates (subfamilies II and III), phosphopantetheine and its S-sulfonate or sulfonate (subfamily II-PanK fusions), and nucleotides (subfamily I). Genetic and comparative genomic data strongly associated DUF89 genes with phosphoester metabolism. The crystal structure of the yeast (Saccharomyces cerevisiae) subfamily III protein YMR027W revealed a novel phosphatase active site with fructose 6-phosphate and Mg(2+) bound near conserved signature residues Asp254 and Asn255 that are critical for activity. These findings indicate that DUF89 proteins are previously unrecognized hydrolases whose characteristic in vivo function is to limit potentially harmful buildups of normal or damaged phosphometabolites.