Preprints.org 2023 Most Popular Preprints Award Winner Collection

Preprint ARTICLE | doi:10.20944/preprints202309.0139.v4

A Recombinant Protein XBB.1.5 RBD/Alum/CpG Vaccine Elicits High Neutralizing Antibody Titers against Omicron Subvariants of SARS-CoV-2

Syamala Rani Thimmiraju, Rakesh Adhikari, Maria J Villar, Jungsoon Lee, Zhuyun Liu, Rakhi Kundu, Yi-Lin Chen, Suman Sharma, Karm Ghei, Brian Keegan, Leroy Versteeg, Portia M Gillespie, Allan Ciciriello, Nelufa Yesmin, Cristina Poveda, Nestor Uzcategui, Wen-Hsiang Chen, Jason T Kimata, Bin Zhan, Ulrich Strych, Maria Elena Bottazzi, Peter Hotez, Jeroen Pollet

Subject: Biology And Life Sciences, Immunology And Microbiology Keywords: Immune escape; Vaccine efficacy; COVID-19; SARS-CoV-2

Online: 30 September 2023 (07:44:51 CEST)

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(1) Background: We previously reported the development of a recombinant protein SARS-CoV-2 vaccine, consisting of the Receptor-Binding Domain (RBD) of the SARS-CoV-2 spike protein, adjuvanted with aluminum hydroxide (alum) and CpG oligonucleotides. In mice and non-human primates, our wild-type (WT) RBD vaccine induced high neutralizing antibody titers against the WT isolate of the virus, and, with partners in India and Indonesia it was later developed into two closely resembling human vaccines, Corbevax and Indovac. Here, we describe the development and characterization of a next-generation vaccine adapted to the recently emerging XBB variants of SARS-CoV-2. (2) Methods: We conducted preclinical studies in mice using a novel yeast-produced SARS-CoV-2 XBB.1.5 RBD subunit vaccine candidate formulated with alum and CpG. We examined the neutralization profile of sera obtained from mice vaccinated twice intramuscularly at a 21-day interval with the XBB.1.5-based RBD vaccine, against WT, Beta, Delta, BA.4, BQ.1.1, BA.2.75.2, XBB.1.16, XBB.1.5 and EG.5.1 SARS-CoV-2 pseudoviruses. (3) Results: The XBB.1.5 RBD/CpG/alum vaccine elicited a robust antibody response in mice. Furthermore, serum from vaccinated mice demonstrated potent neutralization against the XBB.1.5 pseudovirus as well as several other Omicron pseudoviruses. However, regardless of high antibody cross-reactivity by ELISA, the anti-XBB.1.5 RBD antigen serum showed low neutralizing titers against the WT and Delta virus variants. (4) Conclusions: Whereas we observed modest cross-neutralization against Omicron subvariants by sera from mice vaccinated with the WT RBD/CpG/Alum vaccine or with the BA.4/5-based vaccine, sera raised against the XBB.1.5 RBD showed robust cross-neutralization. These findings underscore the imminent opportunity for an updated vaccine formulation utilizing the XBB.1.5 RBD antigen.

Preprint ARTICLE | doi:10.20944/preprints202306.0413.v3

Cross-species Transcriptomics Analysis Highlights Conserved Molecular Responses to Per- and Polyfluoroalkyl Substances (PFAS)

Livia Beccacece, Filippo Costa, Jennifer Paola Pascali, Federico Manuel Giorgi

Subject: Biology And Life Sciences, Ecology, Evolution, Behavior And Systematics Keywords: PFAS; metabolism; transcriptomics; transcriptome; cross-species analysis

Online: 28 June 2023 (02:33:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.1846.v1

Metabolome Mining of Curcuma longa L. Using HPLC-MS/MS and Molecular Networking

Rabin Budhathoki, Arjun Prasad Timilsina, Bishnu P. Regmi, Khaga Raj Sharma, Niraj Aryal, Niranjan Parajuli

Subject: Chemistry And Materials Science, Analytical Chemistry Keywords: Untargeted metabolomics; HPLC-ESI-MS/MS; Curcuma longa; GNPS; Diarylheptanoids

Online: 27 June 2023 (04:47:44 CEST)

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Preprint REVIEW | doi:10.20944/preprints202308.1912.v1

Polymers in 3D Printing of External Maxillofacial Prostheses and Their Retention Systems

Samvel V. Apresyan, Alexandr G. Stepanov, Alexander A. Vikhrov, Maxim S. Myasoedov, Anna I. Prostyakova, Alla N. Generalova

Subject: Chemistry And Materials Science, Medicinal Chemistry Keywords: 3D printing; polymers for maxillofacial prostheses; adhesives; osseointegrated implants; nasal; auricle and ocular prostheses

Online: 29 August 2023 (03:30:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0146.v27

A Proof of the Riemann Hypothesis Based on a New Expression of the Completed Zeta Function

Weicun Zhang

Subject: Computer Science And Mathematics, Algebra And Number Theory Keywords: Riemann Hypothesis (RH); proof; completed zeta function

Online: 30 October 2023 (10:34:15 CET)

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Preprint ARTICLE | doi:10.20944/preprints202308.0148.v2

GPT-4 Can't Reason

Konstantine Arkoudas

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: GPT-4; LLM; AI; reasoning; inference

Online: 7 August 2023 (07:13:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.1106.v1

An Explainable Vision Transformer Model Based White Blood Cells Classification and Localization

Oguzhan Katar, Ozal Yildirim

Subject: Engineering, Other Keywords: Vision Transformers; white blood cells; explainable AI models; deep learning; Score-CAM

Online: 15 June 2023 (08:42:51 CEST)

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Preprint REVIEW | doi:10.20944/preprints202303.0072.v1

Glycosylation Shapes the Efficacy and Safety of Diverse Protein, Gene and Cell Therapies

Frances Rocamora, Angelo G Peralta, Seunghyeon Shin, James Sorrentino, Mina Wu, Eric A Toth, Thomas R Fuerst, Nathan E Lewis

Subject: Engineering, Bioengineering Keywords: glycosylation, glycoengineering, biologic, therapeutic protein, gene therapy, cell-based therapy, monoclonal antibody

Online: 3 March 2023 (10:43:51 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0390.v1

Understanding Landslide Expression in SAR Backscatter Data: A Global Study

Erin Lindsay, Alexandra Jarna Ganerød, Graziella Devoli, Johannes Reiche, Steinar Nordal, Regula Frauenfelder, Lars-Christian Tokle

Subject: Environmental And Earth Sciences, Geophysics And Geology Keywords: change detection; time-series; landslide detection; land cover; Sentinel-1; backscatter; Google Earth Engine;

Online: 22 February 2023 (15:33:14 CET)

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During disaster response, clouds or darkness can prevent the use of optical images for detecting consequences of natural disasters, including landslides. In these situations, radar images can be used to detect changes more rapidly. However, Synthetic Aperture Radar (SAR) backscatter intensity images are underutilized for landslide detection. Unfortunately, there remains a lack of understanding about how to interpret landslide signatures in SAR imagery. In this study, we investigate how the morphometric features and material properties of landslides, and preexisting land cover, control their expression in SAR backscatter intensity change images. Trends in the spatial and temporal signatures of over 1000 landslides in 30 diverse case studies are investigated, using multi-temporal composites and dense time-series of Sentinel-1 C-band SAR backscatter intensity data. The results show that the orientation of landslide surfaces relative to the sensor, pre-existing land cover, and the roughness of the landslide surface, determine whether landslides will produce an increase or decrease in backscatter intensity values. In certain cases, we can identify morphometric features of landslides (e.g. scarps, transit zone, deposits, ponding) and material properties. Generally, we see that landslides appear most clearly with a strong increase in intensity when they occur in herbaceous vegetation or non-vegetated ground surfaces, due to an increase in surface roughness. While in forested or densely vegetated areas, landslides produce a more complex signature with both decreases due to radar shadow and vegetation removal, and an adjacent edge of increased intensity due to double bounce and direct return from vertical tree trunks and convex edges. In most cases, rough deposits produce an increase in intensity, while smooth deposits (e.g. from mudslides) exhibit specular reflection, and thus show decreased values. Landslides are less visible in cases with pre-event very rough ground, or mixed vegetation conditions. The conceptual model developed can aid interpretation of landslides in SAR imagery, and provide domain knowledge needed to train models for automatic landslide detection.

Preprint ARTICLE | doi:10.20944/preprints202310.2060.v1

Production of High-Resolution Map of Biomass Carbon over Forests in Malaysia Estimated using Aboveground Carbon Density Indicator (ACDI) and a Collection of 12 Years Inventory Data

Hamdan Omar, Muhamad Afizzul Misman, Valeria Linggok, Suhaini Haron, Ahmad Ashrin Mohd Bohari, Mohammad Nor Firdaus Haji Sariee

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Aboveground carbon stock; tropical forest; Landsat; Malaysia ecosystem; spectral indicators

Online: 31 October 2023 (09:56:37 CET)

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The accurate estimation of biomass carbon in forests is of paramount importance for effective forest management and mitigating climate change. This study presents a novel approach to produce a high-resolution map of biomass carbon over forests in Malaysia using the Aboveground Carbon Density Indicator (ACDI) and a comprehensive collection of 12 years of inventory data, i.e., from 2012 to 2023. The ACDI was derived based on several vegetation indices (VIs) that were produced from the original Landsat images to indicate the level of aboveground biomass carbon (AGC) stock in the forested areas. The VIs includes Normalised Difference Vegetation Index (NDVI), Normalised Burn Ratio (NBR), Shadow Index (SI), Soil-Adjusted Vegetation Index (SAVI), Iron Oxide Index (IO), Modified Normalised Difference Water Index (NDWI), and Enhanced Vegetation Index (EVI). The ACDI was then integrated with ground-based measurements, and serves as a robust indicator for estimating AGC. This calculation was conducted on Google Earth Engine (GEE) platform to match the date of field observation with the satellite imagery datasets. The production of seamless mosaic of the latest date of Landsat imagery and the forest type classification were also performed on GEE. The forested areas were classified into three major types, which are dry inland forest, mangrove forest, and peat swamp forest. Results indicated significant spatial variations in AGC across Malaysia's forests. The derived AGC prediction models based on the ACDI varied among the forest types. Based on the estimates, a 30-metre resolution, wall-to-wall map of AGC across the entire forested region of Malaysia has been created. The ACDI was calibrated and validated using a separate validation plots dataset to ensure the accuracy of the AGC estimates. The total AGC in all types of forests in Malaysia was estimated at 3.0 billion Mg C with an attainable accuracy of about 80%. These estimates were also divided into categories and reported to the AGC at the state level. This high-resolution map provides essential information for various stakeholders, with critical implications for carbon sequestration efforts, conservation priorities, and sustainable forest management. The presented methodology not only showcases the value of combining advanced remote sensing techniques with long-term inventory data but also underscores the potential for similar approaches in other tropical forest regions globally. Ultimately, this study contributes to the understanding of carbon dynamics in Malaysian forests and promotes effective strategies for mitigating climate change through better-informed forest conservation and management practices.

Preprint ARTICLE | doi:10.20944/preprints202207.0399.v44

Euclidean Relativity Solves 15 Mysteries of Physics

Markolf H. Niemz

Subject: Physical Sciences, Theoretical Physics Keywords: spacetime; cosmology; Hubble constant; Hubble diagram; quantum mechanics

Online: 29 November 2023 (11:08:20 CET)

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Preprint ARTICLE | doi:10.20944/preprints201711.0022.v7

The Geometrization of Maxwell’s Equations and the Emergence of Gravity

Raymond Beach

Subject: Physical Sciences, Theoretical Physics Keywords: Maxwell’s equations; General Relativity; unification of electromagnetism and gravity; dark matter and dark energy; electromagnetic and gravitational radiation; antimatter; antigravity; quantization; superluminal transport

Online: 15 May 2023 (14:37:07 CEST)

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Preprint REVIEW | doi:10.20944/preprints202307.1198.v1

Autopsy Proven Fatal COVID-19 Vaccine-Induced Myocarditis

Nicolas Hulscher, Roger Hodkinson, William Makis, Peter McCullough

Subject: Medicine And Pharmacology, Cardiac And Cardiovascular Systems Keywords: myocarditis; sudden death; chest pain; autopsy; necropsy; COVID-19; COVID-19 vaccines; mRNA; SARS-CoV-2 vaccination; death; excess mortality; spike protein; organ system

Online: 18 July 2023 (09:34:51 CEST)

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Background: COVID-19 vaccines have been linked to myocarditis which in some circumstances can be fatal. This systematic review aims to investigate potential causal links between COVID-19 vaccines and death from myocarditis using post-mortem analysis. Methods: We performed a systematic review of all published autopsy reports involving COVID-19 vaccination-related myocarditis through July 3^rd, 2023. All autopsy studies that include COVID-19 vaccine-induced myocarditis as a possible cause of death were included, without imposing any additional restrictions. Causality in each case was determined by three independent reviewers with cardiac pathology experience and expertise. Results: We initially identified 1,691 studies and, after screening for our inclusion criteria, included 14 papers that contained 28 autopsy cases. The cardiovascular system was the only organ system affected in 26 cases. In 2 cases, myocarditis was characterized as a consequence from multisystem inflammatory syndrome (MIS). The mean and median number of days from last COVID-19 vaccination until death was 6.2 and 3 days, respectively. Most of the deaths occurred within a week from the last injection. We established that all 28 deaths were causally linked to COVID-19 vaccination by independent adjudication. Conclusions: The temporal relationship, internal and external consistency seen among cases in this review with known COVID-19 vaccine-induced myocarditis, its pathobiological mechanisms and related excess death, complemented with autopsy confirmation, independent adjudication, and application of the Bradford Hill criteria to the overall epidemiology of vaccine myocarditis, suggests there is a high likelihood of a causal link between COVID-19 vaccines and death from suspected myocarditis in cases where sudden, unexpected death has occurred in a vaccinated person. Urgent investigation is required for the purpose of risk stratification and mitigation in order to reduce the population occurrence of fatal COVID-19 vaccine-induced myocarditis.

Preprint ARTICLE | doi:10.20944/preprints202108.0327.v3

Logic-Based Modeling and Drug Repurposing for the Prediction of Novel Therapeutic Targets and Combination Regimens against E2F1-Driven Melanoma Progression

Nivedita Singh, Faiz M. Khan, Lakshmi Bala, Julio Vera, Olaf Wolkenhauer, Brigitte Pützer, Stella Logotheti, Shailendra K. Gupta

Subject: Medicine And Pharmacology, Oncology And Oncogenics Keywords: Melanoma; Core regulatory network; in silico perturbationSystems pharmacology; Boolean model; Small molecule inhibitors; Virtual screening; ADME; E2F1

Online: 12 June 2023 (10:22:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202312.0564.v1

Bridging Digital Competence and Sustainability: Unveiling the Synergistic Potential of Design and Maker Education

Noble Po-kan Lo

Subject: Social Sciences, Education Keywords: maker education; green digital skills; problem-solving; innovation; creativity; engagement; sustainable education

Online: 8 December 2023 (08:31:01 CET)

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Preprint ARTICLE | doi:10.20944/preprints202305.0523.v1

Lightning Network’s Evolution: Unraveling Its Present State and the Emergence of Disruptive Digital Business Models

Thomas Dasaklis, Vangelis Malamas

Subject: Business, Economics And Management, Business And Management Keywords: Lightning Network; Business models; Narrative review

Online: 8 May 2023 (10:54:36 CEST)

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