Lynch, Ann M

PhD in Agricultural sciences, Professor
Publications
28
Citations
907
h-index
13

About

My research fields are forest entomology, forest disturbance ecology, dendrochronology, and sampling design for forest insects and their damage.  I focus on Southwestern high elevation ecosystems, mixed-conifer forests, spruce-fir forests, Choristoneura sp., Elatobium abietinum, and forest defoliators.  I am affiliated faculty at the Laboratory of Tree-Ring Research at the University of Arizona, and am a retired Research Entomologist with the Rocky Mountain Research Station, U.S. Forest Service.

from chars
Publications found: 16997
Application of Multiple Base‐Editing Mediated by Polycistronic tRNA‐gRNA‐Processing System in Pig Cells
Zhao W., Zhu X., Huang G., Gu H., Bi Y., Tang D., Ren H.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTGene edited pigs have extensive and important application value in the fields of agriculture and biomedicine. With the increasing demand in medical research and agricultural markets, more and more application scenarios require gene edited pigs to possess two or even more advantageous phenotypes simultaneously. The current production of multi gene edited pigs is inefficient, time‐consuming, and costly, and there is an urgent need to develop efficient and accurate multi gene editing application technologies. The polycistronic tRNA‐gRNA‐processing system (PTG), developed based on endogenous tRNA self‐processing systems, has been shown to exhibit efficient multi gene editing in plants. This study aims to combine a PTG strategy with multiple gRNA production functions with an adenine base editor (ABE) to test its feasibility for efficient and precise multi gene base editing in pig cells. The results indicate that the PTG based integrated ABE plasmid can perform efficient base editing at multiple gene loci in pig cells. And while the gene editing efficiency was significantly improved, no indel and sgRNA dependent off target effects caused by DSB were detected. This work permit will provide a solid foundation for the production of multi gene edited pigs with agricultural and medical applications.
A Novel Screening System to Characterize and Engineer Quorum Quenching Lactonases
Sompiyachoke K., Bravo J., Sikdar R., Abdullah J., Elias M.H.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTN‐acyl l‐homoserine lactones are signaling molecules used by numerous bacteria in quorum sensing. Some bacteria encode lactonases, which can inactivate these signals. Lactonases were reported to inhibit quorum sensing‐dependent phenotypes, including virulence and biofilm. As bacterial signaling is dependent on the type of molecule used, lactonases with high substrate specificity are desirable for selectively targeting species in communities. Lactonases characterized from nature show limited diversity in substrate preference, making their engineering appealing but complicated by the lack of convenient assays for evaluating lactonase activity. We present a medium‐throughput lactonase screening system compatible with lysates that couples the ring opening of N‐acyl l‐homocysteine thiolactones with 5,5‐dithio‐bis‐(2‐nitrobenzoic acid) to generate a chromogenic signal. We show that this system is applicable to lactonases from diverse protein families and demonstrate its utility by screening mutant libraries of GcL lactonase from Parageobacillus caldoxylosilyticus. Kinetic characterization corroborated the screening results with thiolactonase and homoserine lactonase activity levels. This system identified GcL variants with altered specificity: up to 1900‐fold lower activity for long‐chain N‐acyl l‐homoserine lactone substrates and ~38‐fold increase in preference for short‐chain substrates. Overall, this new system substantially improves the evaluation of lactonase activity and will facilitate the identification and engineering of quorum quenching enzymes.
Continuous Production of Influenza VLPs Using IC‐BEVS and Multi‐Stage Bioreactors
Correia R., Zotler T., Ferraz F., Fernandes B., Graça M., Pijlman G.P., Alves P.M., Roldão A.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTThe insect cell‐baculovirus expression vector system (IC‐BEVS) has been an asset to produce biologics for over 30 years. With the current trend in biotechnology shifting toward process intensification and integration, developing intensified processes such as continuous production is crucial to hold this platform as a suitable alternative to others. However, the implementation of continuous production has been hindered by the lytic nature of this expression system and the process‐detrimental virus passage effect. In this study, we implemented a multi‐stage bioreactor setup for continuous production of influenza hemagglutinin‐displaying virus‐like particles (HA‐VLPs) using IC‐BEVS. A setup consisting of one Cell Growth Bioreactor simultaneously feeding non‐infected insect cells to three parallel Production Bioreactors operated at different residence times (RT) (18, 36, and 54 h) was implemented; Production Bioreactors were continuously harvested. Two insect cell lines (neutral pH–adapted High Five and Sf9) and two recombinant baculovirus (rBAC) constructs (one that originates from a bacmid, rBACbacmid, and another of non‐bacteria origin, rBACflashbac) were tested. Combining rBACflashbac with Sf9 cells was the most efficient approach, allowing consistent HA‐VLPs titers (34 ± 14 HA titer/mL) and rBAC titers (108–109 pfu/mL) throughout the period of continuous operation (20 days). Cell growth kinetics and viability varied across RT, and higher RT was associated with increased expression of HA‐VLPs, independent of the cell line and rBAC used; RT of 54 h allowed to maximize titers. The presence of particles resembling HA‐VLPs was confirmed by transmission electron microscopy throughout the continuous operation. This work showcases the implementation of a process for continuous production of a promising class of biotherapeutics (i.e., VLPs), and paves the way for establishing continuous, integrated setups using the IC‐BEVS expression system.
Real‐Time Auto Controlling of Viable Cell Density in Perfusion Cultivation Aided by In‐Line Dielectric Spectroscopy With Segmented Adaptive PLS Model
Sun Y., Zhang Q., He Y., Chen D., Wang Z., Zheng X., Fang M., Zhou H.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTServing as a dedicated process analytical technology (PAT) tool for biomass monitoring and control, the capacitance probe, or dielectric spectroscopy, is showing great potential in robust pharmaceutical manufacturing, especially with the growing interest in integrated continuous bioprocessing. Despite its potential, challenges still exist in terms of its accuracy and applicability, particularly when it is used to monitor cells during stationary and decline phases. In this study, data pre‐processing methods were first evaluated through cross‐validation, where the first‐order derivative emerged as the most effective method to diminish variability in prediction accuracy across different training datasets. Subsequently, a segmented adaptive partial least squares (SA‐PLS) model was developed, and its accuracy and universality were demonstrated through several validation studies using different clones and culture processes. Furthermore, a real‐time viable cell density (VCD) auto‐control system in perfusion culture was established, where the VCD was maintained around the target with notable precision and robustness. This model enhanced the monitoring capabilities of capacitance‐based PAT tools throughout the cultivation, expanded their application in cell‐specific automatic control strategies, and contributed vitally to the advancement of continuous manufacturing paradigms.
Reducing Structural Nonidentifiabilities in Upstream Bioprocess Models Using Profile‐Likelihood
Babel H., Omar O., Paul A., Bär J.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTProcess models are increasingly used to support upstream process development in the biopharmaceutical industry for process optimization, scale‐up and to reduce experimental effort. Parametric unstructured models based on biological mechanisms are highly promising, since they do not require large amounts of data. The critical part in the application is the certainty of the parameter estimates, since uncertainty of the parameter estimates propagates to model predictions and can increase the risk associated with those predictions. Currently Fisher‐Information‐Matrix based approximations or Monte‐Carlo approaches are used to estimate parameter confidence intervals and regularization approaches to decrease parameter uncertainty. Here we apply profile likelihood to determine parameter identifiability of a recent upstream process model. We have investigated the effect of data amount on identifiability and found out that addition of data reduces non‐identifiability. The likelihood profiles of nonidentifiable parameters were then used to uncover structural model changes. These changes effectively alleviate the remaining non‐identifiabilities except for a single parameter out of 21 total parameters. We present the first application of profile likelihood to a complete upstream process model. Profile likelihood is a highly suitable method to determine parameter confidence intervals in upstream process models and provides reliable estimates even with nonlinear models and limited data.
Creating a Halotolerant Degrader for Efficient Mineralization of p‐Nitrophenol‐Substituted Organophosphorus Pesticides in High‐Saline Wastewater
Liu Y., Xiong W., Jiang Y., Meng Y., Zhao W., Yang C., Liu R.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTThe bioaugmentation performance is severely reduced in the treatment of high‐saline pesticide wastewater because the growth and degradation activity of pesticide degraders are significantly inhibited by high salt concentrations. In this study, a heterologous biodegradation pathway comprising the seven genes mpd/pnpABCDEF responsible for the bioconversion of p‐nitrophenol (PNP)‐substituted organophosphorus pesticides (OPs) into β‐oxoadipate and the genes encoding Vitreoscilla hemoglobin (VHb) and green fluorescent protein (GFP) were integrated into the genome of a salt‐tolerant chassis Halomonas cupida J9, to generate a genetically engineered halotolerant degrader J9U‐MP. RT‐PCR assays demonstrated that the nine exogenous genes are successfully transcribed to mRNA in J9U‐MP. Gas chromatography analysis of methyl parathion (MP) and its intermediates demonstrated that the expressed MP hydrolase and PNP‐degrading enzymes PnpABCD show obvious degradation activity toward the specific substrates in J9U‐MP. Stable isotope analysis showed that J9U‐MP is able to efficiently convert 13C6‐PNP into 13CO2, demonstrating the complete mineralization of MP in high‐salt media. J9U‐MP is genetically stable during passage culture, and genomic integration of exogenous genes does not negatively influence the growth of J9U‐MP. Under oxygen‐limited conditions, VHb‐expressing J9U‐MP does not show obvious growth inhibition and a significant reduction in the MP degradation rate. A real‐time monitoring system with enhanced GFP is used to track the motion and activity of J9U‐MP during bioremediation. Moreover, 50 mg/L MP and its intermediates (i.e., PNP and HQ) were completely degraded by J9U‐MP within 12 h in wastewater supplemented with 60 g/L NaCl. After 3 days of incubation, 25 mg/L 13C6‐PNP was converted into 13CO2 by J9U‐MP in wastewater supplemented with 60 g/L NaCl. Our results highlight the power of synthetic biology for creating new halotolerant pollutant‐mineralizing strains. The strong competitive advantages of J9U‐MP in high‐salinity and low‐oxygen environments make this degrader suitable for in situ bioaugmentation of OP wastewater.
A Paradigm of Computer Vision and Deep Learning Empowers the Strain Screening and Bioprocess Detection
Xu F., Su L., Wang Y., Hu K., Liu L., Ben R., Gao H., Mohsin A., Chu J., Tian X.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTHigh‐performance strain and corresponding fermentation process are essential for achieving efficient biomanufacturing. However, conventional offline detection methods for products are cumbersome and less stable, hindering the “Test” module in the operation of “Design‐Build‐Test‐Learn” cycle for strain screening and fermentation process optimization. This study proposed and validated an innovative research paradigm combining computer vision with deep learning to facilitate efficient strain selection and effective fermentation process optimization. A practical framework was developed for gentamicin C1a titer as a proof‐of‐concept, using computer vision to extract different color space components across various cultivation systems. Subsequently, by integrating data preprocessing with algorithm design, a prediction model was developed using 1D‐CNN model with Z‐score preprocessing, achieving a correlation coefficient (R2) of 0.9862 for gentamicin C1a. Furthermore, this model was successfully applied for high‐yield strain screening and real‐time monitoring of the fermentation process and extended to rapid detection of fluorescent protein expression in promoter library construction. The visual sensing research paradigm proposed in this study provides a theoretical framework and data support for the standardization and digital monitoring of color‐changing bioprocesses.
Dynamic Culture of Bioprinted Liver Tumor Spheroids in a Pillar/Perfusion Plate for Predictive Screening of Anticancer Drugs
Joshi P., Nascimento H.S., Kang S., Lee M., Vanga M.G., Lee S., Ku B., Miranda M.D., Lee M.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTRecent advancements in three‐dimensional (3D) cell culture technologies, such as cell spheroids, organoids, and 3D bioprinted tissue constructs, have significantly improved the physiological relevance of in vitro models. These models better mimic tissue structure and function, closely emulating in vivo characteristics and enhancing phenotypic analysis, critical for basic research and drug screening in personalized cancer therapy. Despite their potential, current 3D cell culture platforms face technical challenges, which include user‐unfriendliness in long‐term dynamic cell culture, incompatibility with rapid cell encapsulation in biomimetic hydrogels, and low throughput for compound screening. To address these issues, we developed a 144‐pillar plate with sidewalls and slits (144PillarPlate) and a complementary 144‐perfusion plate with perfusion wells and reservoirs (144PerfusionPlate) for dynamic 3D cell culture and predictive compound screening. To accelerate biomimetic tissue formation, small Hep3B liver tumor spheroids suspended in alginate were printed and encapsulated on the 144PillarPlate rapidly by using microsolenoid valve‐driven 3D bioprinting technology. The microarray bioprinting technology enabled precise and rapid loading of small spheroids in alginate on the pillar plate, facilitating reproducible and scalable formation of large tumor spheroids with minimal manual intervention. The bioprinted Hep3B spheroids on the 144PillarPlate were dynamically cultured in the 144PerfusionPlate and tested with anticancer drugs to measure drug effectiveness and determine the concentration required to inhibit 50% of the cell viability (IC50 value). The perfusion plate enabled the convenient dynamic culture of tumor spheroids and facilitated the dynamic testing of anticancer drugs with increased sensitivity. It is envisioned that the integration of microarray bioprinting of tumor spheroids onto the pillar plate, along with dynamic 3D cell culture in the perfusion plate, could more accurately replicate tumor microenvironments. This advancement has the potential to enhance the predictive drug screening process in personalized cancer therapy significantly.
Manganese Peroxidase Participates in the Liquid–Solid–Gas Triphase Regulation on Microbial Degradation of Lignocellulose in Solid‐State Fermentation
Zhu L., Ding J., Xue W., Zhou S., Wang L., Jiang A., Zhao M., He Q., Ren A.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTThe three‐phase structure of solid‐state fermentation (SSF) directly affects substrate degradation and fermentation efficiency. However, the mechanism of three‐phase regulation on lignocellulose utilization and microbial metabolism is still unclear. Based on comparative transcriptome analysis, a lignocellulose degrading enzyme, manganese peroxidase (GlMnP), which was significantly affected by water stress meanwhile related to triphase utilization, was screened to reveal the mechanism using Ganoderma lucidum as the reference strain. The results showed that GlMnP directly participates in lignocellulose degradation by positively regulating the activity of carboxymethylcellulase (CMCase), filter paper (FPAse), and laccase (LACase) enzymes, and indirectly participates in lignocellulose degradation by negatively regulating the redox levels in microorganisms. In addition, GlMnP can also control microbial glycolysis rate to enhance lignocellulose utilization. The results indicated that GlMnP participates in the liquid–solid–gas triphase regulation on lignocellulose degradation by G. lucidum in SSF.
Engineering Gene and Protein Switches for Regulation of Lineage‐Specifying Transcription Factors
Teixeira A.P., Franko N., Fussenegger M.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTHuman pluripotent stem cells (hPSCs) can be differentiated in vitro to an increasing number of mature cell types, presenting significant promise for addressing a wide range of diseases and studying human development. One approach to further enhance stem cell differentiation methods would be to coordinate multiple inducible gene or protein switches to operate simultaneously within the same cell, with minimal cross‐interference, to precisely regulate a network of lineage‐specifying transcription factors (TFs) to guide cell fate decisions. Therefore, in this study, we designed and tested various mammalian gene and protein switches responsive to clinically safe small‐molecule inhibitors of viral proteases. First, we leveraged hepatitis C virus and human rhinovirus proteases to control the activity of chimeric transcription factors, enabling gene expression activation exclusively in the presence of protease inhibitors and achieving high fold‐inductions in hPSC lines. Second, we built single‐chain protein switches regulating the activity of three differentiation‐related pancreatic TFs, MafA, Pdx1, and Ngn3, each engineered with a protease cleavage site within its structure and having the corresponding protease fused at one terminus. While variants lacking the protease retained most of the unmodified TF activity, the attachment of the protease significantly decreased the activity, which could be rescued upon addition of the corresponding protease inhibitor. We confirmed the functionality of these protein switches for simultaneously controlling the activity of three TFs with a common input molecule, as well as the orthogonality of each protease‐based system to independently regulate two TFs. Finally, we validated these very compact systems for precisely controlling TF activity in hPSCs. Our results suggest that they will be valuable tools for research in both developmental biology and regenerative medicine.
Heterologous Expression and Optimization of Fermentation Conditions for Recombinant Ikarugamycin Production
Evers J.K., Glöckle A., Wiegand M., Schuler S., Einsiedler M., Gulder T.A.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTIkarugamycin is a member of the natural product family of the polycyclic tetramate macrolactams (PoTeMs). The compound exhibits a diverse range of biological activities, including antimicrobial, antiprotozoal, anti‐leukemic, and anti‐inflammatory properties. In addition, it interferes with several crucial cellular functions, such as oxidized low‐density lipoprotein uptake in macrophages, Nef‐induced CD4 cell surface downregulation, and mechanisms of endocytosis. It is, therefore, used as a tool compound to study diverse biological processes. However, ikarugamycin commercial prices are very high, with up to 1300 € per 1 mg, thus limiting its application. We, therefore, set out to develop a high‐yielding recombinant production platform of ikarugamycin by screening different expression vectors, recombinant host strains, and cultivation conditions. Overall, this has led to overproduction levels of more than 100 mg/L, which, together with a straightforward purification protocol, establishes biotechnological access to affordable ikarugamycin enabling its increased use in biomedical research in the future.
Biotechnology and Bioengineering: Volume 122, Number 2, February 2025
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0
The Effect of Accessibility of Insoluble Substrate on the Overall Kinetics of Enzymatic Degradation
Petrášek Z., Nidetzky B.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTThe enzymatic reaction kinetics on cellulose and other solid substrates is limited by the access of the enzyme to the reactive substrate sites. We introduce a general model in which the reaction rate is determined by the active surface area, and the resulting kinetics consequently reflects the evolving relationship between the exposed substrate surface and the remaining substrate volume. Two factors influencing the overall surface‐to‐volume ratio are considered: the shape of the substrate particles, characterized by a single numerical parameter related to its dimensionality, and the distribution of the particle sizes. The model is formulated in a form of simple analytical equations, enabling fast and efficient application to experimental data, and facilitating its incorporation into more detailed and complex models. The application of the introduced formalism exploring its potential to account for the observed reaction rate is demonstrated on two examples: the derivation of particle size distribution from experimentally determined reaction kinetics, and the prediction of reaction slowdown from experimental particle size distribution.
Genome‐Scale Community Model‐Guided Development of Bacterial Coculture for Lignocellulose Bioconversion
Kundu P., Ghosh A.
Q2
Wiley
Biotechnology and Bioengineering 2025 citations by CoLab: 0  |  Abstract
ABSTRACTMicrobial communities have shown promising potential in degrading complex biopolymers, producing value‐added products through collaborative metabolic functionality. Hence, developing synthetic microbial consortia has become a predominant technique for various biotechnological applications. However, diverse microbial entities in a consortium can engage in distinct biochemical interactions that pose challenges in developing mutualistic communities. Therefore, a systems‐level understanding of the inter‐microbial metabolic interactions, growth compatibility, and metabolic synergisms is essential for developing effective synthetic consortia. This study demonstrated a genome‐scale community modeling approach to assess the inter‐microbial interaction pattern and screen metabolically compatible bacterial pairs for designing the lignocellulolytic coculture system. Here, we have investigated the pairwise growth and biochemical synergisms among six termite gut bacterial isolates by implementing flux‐based parameters, i.e., pairwise growth support index (PGSI) and metabolic assistance (PMA). Assessment of the PGSI and PMA helps screen nine beneficial bacterial pairs that were validated by designing a coculture experiment with lignocellulosic substrates. For the cocultured bacterial pairs, the experimentally measured enzymatic synergisms (DES) showed good coherence with model‐derived biochemical compatibility (PMA), which explains the fidelity of the in silico predictions. The highest degree of enzymatic synergisms has been observed in C. denverensis P3 and Brevibacterium sp P5 coculture, where the total cellulase activity has been increased by 53%. Hence, the flux‐based assessment of inter‐microbial interactions and metabolic compatibility helps select the best bacterial coculture system with enhanced lignocellulolytic functionality. The flux‐based parameters (PGSI and PMA) in the proposed community modeling strategy will help optimize the composition of microbial consortia for developing synthetic microcosms for bioremediation, bioengineering, and biomedical applications.
A Novel, Site‐Specific N‐Linked Glycosylation Model Provides Mechanistic Insights Into the Process‐Condition Dependent Distinct Fab and Fc Glycosylation of an IgG1 Monoclonal Antibody Produced by CHO VRC01 Cells
Reddy J.V., Leibiger T., Singh S.K., Lee K.H., Papoutsakis E., Ierapetritou M.
Q2
Wiley
Biotechnology and Bioengineering 2024 citations by CoLab: 0  |  Abstract
ABSTRACTThe CHO VRC01 cell line produces an anti‐HIV IgG1 monoclonal antibody containing N‐linked glycans on both the Fab (variable) and Fc (constant) regions. Site‐specific glycan analysis was used to measure the complex effects of cell culture process conditions on Fab and Fc glycosylation. Experimental data revealed major differences in glycan fractions across the two sites. Bioreactor pH was found to influence fucosylation, galactosylation, and sialylation in the Fab region and galactosylation in the Fc region. To understand the complex effects of process conditions on site‐specific N‐linked glycosylation, a kinetic model of site‐specific N‐linked glycosylation was developed. The model parameters provided mechanistic insights into the differences in glycan fractions observed in the Fc and Fab regions. Enzyme activities calculated from the model provided insights into the effect of bioreactor pH on site‐specific N‐linked glycosylation. Model predictions were experimentally tested by measuring glycosyltransferase‐enzyme mRNA‐levels and intracellular nucleotide sugar concentrations. The model was used to demonstrate the effect of increasing galactosyltransferase activity on site‐specific N‐linked glycan fractions. Experiments involving galactose and MnCl2 supplementation were used to test model predictions. The model is capable of providing insights into experimentally measured data and also of making predictions that can be used to design media supplementation strategies.
Found 
See full statistics
Total publications
28
Total citations
907
Citations per publication
32.39
Average publications per year
0.68
Average coauthors
4.29
Publications years
1984-2024 (41 years)
h-index
13
i10-index
18
m-index
0.32
o-index
57
g-index
28
w-index
5
Metrics description

Fields of science

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Forestry, 14, 50%
Ecology, 9, 32.14%
Nature and Landscape Conservation, 7, 25%
Management, Monitoring, Policy and Law, 6, 21.43%
Plant Science, 4, 14.29%
Ecology, Evolution, Behavior and Systematics, 4, 14.29%
Global and Planetary Change, 4, 14.29%
General Chemistry, 1, 3.57%
General Biochemistry, Genetics and Molecular Biology, 1, 3.57%
General Medicine, 1, 3.57%
Multidisciplinary, 1, 3.57%
General Physics and Astronomy, 1, 3.57%
Environmental Chemistry, 1, 3.57%
General Environmental Science, 1, 3.57%
Physiology, 1, 3.57%
Insect Science, 1, 3.57%
Radiology, Nuclear Medicine and imaging, 1, 3.57%
Environmental Science (miscellaneous), 1, 3.57%
Urban Studies, 1, 3.57%
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Citing journals

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Organizations from articles

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Organization not defined, 10, 35.71%
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Countries from articles

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USA, 22, 78.57%
Country not defined, 7, 25%
Kazakhstan, 2, 7.14%
Spain, 1, 3.57%
Canada, 1, 3.57%
Mexico, 1, 3.57%
Poland, 1, 3.57%
Switzerland, 1, 3.57%
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Organization not defined, 281, 30.98%
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Citing countries

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USA, 410, 45.2%
Country not defined, 165, 18.19%
Canada, 140, 15.44%
Germany, 64, 7.06%
China, 55, 6.06%
Switzerland, 48, 5.29%
United Kingdom, 43, 4.74%
Spain, 30, 3.31%
Czech Republic, 29, 3.2%
Italy, 27, 2.98%
France, 22, 2.43%
Russia, 17, 1.87%
Mexico, 17, 1.87%
Poland, 16, 1.76%
Austria, 14, 1.54%
Sweden, 13, 1.43%
Netherlands, 12, 1.32%
Norway, 12, 1.32%
Belgium, 11, 1.21%
Finland, 11, 1.21%
Japan, 11, 1.21%
Australia, 9, 0.99%
Argentina, 9, 0.99%
Brazil, 9, 0.99%
Romania, 9, 0.99%
Slovenia, 7, 0.77%
Denmark, 6, 0.66%
Chile, 6, 0.66%
South Africa, 6, 0.66%
Bangladesh, 5, 0.55%
Lithuania, 5, 0.55%
Serbia, 5, 0.55%
Kazakhstan, 4, 0.44%
India, 4, 0.44%
Latvia, 4, 0.44%
Thailand, 4, 0.44%
Turkey, 4, 0.44%
Albania, 3, 0.33%
Bulgaria, 3, 0.33%
Greece, 3, 0.33%
New Zealand, 3, 0.33%
Panama, 3, 0.33%
Slovakia, 3, 0.33%
Croatia, 3, 0.33%
Estonia, 2, 0.22%
Portugal, 2, 0.22%
Afghanistan, 2, 0.22%
Hungary, 2, 0.22%
Colombia, 2, 0.22%
Pakistan, 2, 0.22%
Republic of Korea, 2, 0.22%
Ukraine, 1, 0.11%
Gabon, 1, 0.11%
Honduras, 1, 0.11%
Georgia, 1, 0.11%
Zambia, 1, 0.11%
Iran, 1, 0.11%
Iceland, 1, 0.11%
Cameroon, 1, 0.11%
Kenya, 1, 0.11%
Cyprus, 1, 0.11%
Kyrgyzstan, 1, 0.11%
Costa Rica, 1, 0.11%
Malaysia, 1, 0.11%
Morocco, 1, 0.11%
Nigeria, 1, 0.11%
Peru, 1, 0.11%
Saudi Arabia, 1, 0.11%
North Macedonia, 1, 0.11%
Tajikistan, 1, 0.11%
Uruguay, 1, 0.11%
Ecuador, 1, 0.11%
Ethiopia, 1, 0.11%
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  • We do not take into account publications without a DOI.
  • Statistics recalculated daily.