<?xml version="1.0" encoding="utf-8" standalone="yes"?><feed xmlns="http://www.w3.org/2005/Atom"><generator uri="https://gohugo.io" version="0.141.0">Hugo v0.141.0</generator><id>https://millironx.millironx.page/@indiewebpub/academia/</id><link rel="self" type="application/atom+xml" href="https://millironx.millironx.page/@indiewebpub/academia/feed.xml"/><link rel="alternate" type="text/html" href="https://millironx.millironx.page/@indiewebpub/academia/"/><updated>2025-03-31T00:14:19+00:00</updated><title>Academic Publications and Presentations on Milliron X</title><entry><id>https://millironx.millironx.page/@indiewebpub/academia/bpv-genetics/</id><link rel="alternate" href="https://millironx.millironx.page/@indiewebpub/academia/bpv-genetics/"/><title>Genetic analysis of bovine papillomas</title><published>2024-09-19T00:00:00+00:00</published><updated>2024-09-19T00:00:00+00:00</updated><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><author><name>Rachel Palinski</name><uri>https://millironx.millironx.page/@indiewebpub/people/rachel-palinski/</uri></author><author><name>Bob Gentry</name><uri>https://millironx.millironx.page/@indiewebpub/people/bob-gentry/</uri></author><category term="poster"/><summary type="text">
Bovine papillomavirus (BPV) is a major cause of reproductive failure in cattle. In bulls, penile papillomas caused by BPV may cause reluctance to breed, and is always a cause to fail an animal on a breeding soundness exam. Historically, it has been thought that BPV was transmitted via direct contact and could be controlled by managing clinically presenting animals in the herd, but more recent evidence suggests alternative modes of transmission. BPV has been found repeatably in clinically healthy animals, and in non-cutaneous secretions including milk, blood, urine and semen. Currently, no commercially available BPV vaccine uses isolated viral particles and naturally occurring virus does not produce cross-protective immunity. In order to develop a proper vaccine for penile papillomas further studies are required to understand the epidemiology of BPV in herds. While vulvar, cutaneous, and mammary papillomas have been genotyped in recent years, this information is not available for penile papillomas. In this study there were 31 submissions, collected from 7 states, NE, KS, NY, TX, AL, MO and SD (14 different cattle operations) Samples were collected between August of 2022 and April 2024. Twenty-two submissions were penile papillomas and with pooling of samples represented over 50 penile papillomas. Samples were metagenomically sequenced at the Kansas State Veterinary Diagnostic Lab, and the genotype of each sample was determined using the phylogenetic analysis. The clade of each sample was determined by aligning consensus sequences of the L1 gene (used for both for phylogeny and as a vaccine target) using MAFFT and a maximum-likelihood phylogeny generated in Mega X. Analysis found that all penile papilloma submissions were composed of BPV type 2, with one sample showing co-infection with BPV type 1. Conversely, cutaneous and teat papillomas had BPV genotypes that were more variable with genotypes of 1,2,7,12,14,29 and 40. These results indicate that BPV type 2 and type 1 provide a unified target for bovine penile papilloma vaccine development.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Bovine papillomavirus (BPV) is a major cause of reproductive failure in cattle.
In bulls, penile papillomas caused by BPV may cause reluctance to breed, and is
always a cause to fail an animal on a breeding soundness exam. Historically, it
has been thought that BPV was transmitted via direct contact and could be
controlled by managing clinically presenting animals in the herd, but more
recent evidence suggests alternative modes of transmission. BPV has been found
repeatably in clinically healthy animals, and in non-cutaneous secretions
including milk, blood, urine and semen. Currently, no commercially available BPV
vaccine uses isolated viral particles and naturally occurring virus does not
produce cross-protective immunity. In order to develop a proper vaccine for
penile papillomas further studies are required to understand the epidemiology of
BPV in herds. While vulvar, cutaneous, and mammary papillomas have been
genotyped in recent years, this information is not available for penile
papillomas. In this study there were 31 submissions, collected from 7 states,
NE, KS, NY, TX, AL, MO and SD (14 different cattle operations) Samples were
collected between August of 2022 and April 2024. Twenty-two submissions were
penile papillomas and with pooling of samples represented over 50 penile
papillomas. Samples were metagenomically sequenced at the Kansas State
Veterinary Diagnostic Lab, and the genotype of each sample was determined using
the phylogenetic analysis. The clade of each sample was determined by aligning
consensus sequences of the L1 gene (used for both for phylogeny and as a vaccine
target) using MAFFT and a maximum-likelihood phylogeny generated in Mega X.
Analysis found that all penile papilloma submissions were composed of BPV type
2, with one sample showing co-infection with BPV type 1. Conversely, cutaneous
and teat papillomas had BPV genotypes that were more variable with genotypes of
1,2,7,12,14,29 and 40. These results indicate that BPV type 2 and type 1 provide
a unified target for bovine penile papilloma vaccine development.&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/got-warts-naab/</id><link rel="alternate" href="https://millironx.millironx.page/@indiewebpub/academia/got-warts-naab/"/><title>Got Warts? Bovine Papillomavirus Pathogenesis, Transmission, and Vaccination</title><published>2024-09-19T00:00:00+00:00</published><updated>2024-09-19T00:00:00+00:00</updated><author><name>Bob Gentry</name><uri>https://millironx.millironx.page/@indiewebpub/people/bob-gentry/</uri></author><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><category term="presentation"/></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/yavsap/</id><link rel="alternate" href="/academia/yavsap/yavsap.pdf"/><title>YAVSAP: versatile viral quasispecies analysis for veterinary samples</title><published>2024-03-05T00:00:00+00:00</published><updated>2024-03-05T00:00:00+00:00</updated><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><author><name>Steven Stancic</name><uri>https://millironx.millironx.page/@indiewebpub/people/steven-stancic/</uri></author><author><name>Andrea Lu</name><uri>https://millironx.millironx.page/@indiewebpub/people/andrea-lu/</uri></author><author><name>Dana Mitzel</name><uri>https://millironx.millironx.page/@indiewebpub/people/dana-mitzel/</uri></author><author><name>William Wilson</name><uri>https://millironx.millironx.page/@indiewebpub/people/william-wilson/</uri></author><author><name>Rachel Palinski</name><uri>https://millironx.millironx.page/@indiewebpub/people/rachel-palinski/</uri></author><category term="presentation"/><category term="virus"/><category term="quasispecies"/><category term="next-generation sequencing"/><category term="pipeline"/><summary type="text">
Viral populations within an infected host are composed of viral particles with a spectrum of genetic mutations rather than a unified genome. This phenomenon is referred to as viral “quasispecies,” and has been useful for the understanding of viral transmission and early detection of new viral variants. Next generation sequencing (NGS) has enabled the study of these quasispecies for many viral species, notably Influenza A and B, Human Immunodeficiency Virus (HIV), Foot and Mouth Disease Virus (FMDV), and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV2), and established protocols and computer analysis tools have been developed for these species. Some of the most important viruses, such as emerging and exotic disease agents, however, do not have replicatable protocols or software tools capable of producing valid output from their sequence data. Here, we present Yet Another Viral Subspecies Analysis Pipeline (YAVSAP). YAVSAP is a fully automated bioinformatic pipeline built from the ground up to identify and analyze viral quasispecies of any arbitrary virus in human and veterinary samples. YAVSAP provides reference-based genome mapping of both long- and short-read sequencing reads to any reference genome that the user chooses, identifies subconsensus variants and haplotypes, and assesses the phylogenies of all viral sequences found within a sample. YAVSAP is written in Nextflow and conforms to the nf-core initiative’s standards, which allows it to run on low-end computers, high performance computing (HPC) clusters, or anything in between with zero configuration. YAVSAP has been tested on viruses of interest to veterinary medicine and public health, including Japanese Encephalitis Virus (JEV), Influenza D Virus (IDV), Bovine Coronavirus (BCoV), SARS CoV2, and Rift Valley Fever Virus (RVFV), and can correctly identify consensus genomes and quasispecies within samples containing each of these viruses. This tool provides a means for biologists with little bioinformatic experience to analyze deep sequence data while correcting for many of the pitfalls associated with previous and current analysis platforms. YAVSAP is open source software and is publicly available at https://github.com/ksumngs/yavsap.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Viral populations within an infected host are composed of viral particles with a
spectrum of genetic mutations rather than a unified genome. This phenomenon is
referred to as viral &amp;ldquo;quasispecies,&amp;rdquo; and has been useful for the understanding
of viral transmission and early detection of new viral variants. Next generation
sequencing (NGS) has enabled the study of these quasispecies for many viral
species, notably Influenza A and B, Human Immunodeficiency Virus (HIV), Foot and
Mouth Disease Virus (FMDV), and Severe Acute Respiratory Syndrome Coronavirus 2
(SARS CoV2), and established protocols and computer analysis tools have been
developed for these species. Some of the most important viruses, such as
emerging and exotic disease agents, however, do not have replicatable protocols
or software tools capable of producing valid output from their sequence data.
Here, we present Yet Another Viral Subspecies Analysis Pipeline (YAVSAP). YAVSAP
is a fully automated bioinformatic pipeline built from the ground up to identify
and analyze viral quasispecies of any arbitrary virus in human and veterinary
samples. YAVSAP provides reference-based genome mapping of both long- and
short-read sequencing reads to any reference genome that the user chooses,
identifies subconsensus variants and haplotypes, and assesses the phylogenies of
all viral sequences found within a sample. YAVSAP is written in Nextflow and
conforms to the nf-core initiative&amp;rsquo;s standards, which allows it to run on
low-end computers, high performance computing (HPC) clusters, or anything in
between with zero configuration. YAVSAP has been tested on viruses of interest
to veterinary medicine and public health, including Japanese Encephalitis Virus
(JEV), Influenza D Virus (IDV), Bovine Coronavirus (BCoV), SARS CoV2, and Rift
Valley Fever Virus (RVFV), and can correctly identify consensus genomes and
quasispecies within samples containing each of these viruses. This tool provides
a means for biologists with little bioinformatic experience to analyze deep
sequence data while correcting for many of the pitfalls associated with previous
and current analysis platforms. YAVSAP is open source software and is publicly
available at &lt;a
 href="https://github.com/ksumngs/yavsap">https://github.com/ksumngs/yavsap&lt;/a>.&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/taxprofiler/</id><link rel="alternate" href="https://doi.org/10.1101/2023.10.20.563221"/><title>nf-core/taxprofiler: highly parallelised and flexible pipeline for metagenomic taxonomic classification and profiling</title><published>2023-10-23T00:00:00+00:00</published><updated>2023-10-23T00:00:00+00:00</updated><author><name>Sofia Stamouli</name><uri>https://millironx.millironx.page/@indiewebpub/people/sofia-stamouli/</uri></author><author><name>Moritz E. Beber</name><uri>https://millironx.millironx.page/@indiewebpub/people/moritz-e.-beber/</uri></author><author><name>Tanja Normark</name><uri>https://millironx.millironx.page/@indiewebpub/people/tanja-normark/</uri></author><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><author><name>Lili Andersson-Li</name><uri>https://millironx.millironx.page/@indiewebpub/people/lili-andersson-li/</uri></author><author><name>Maxime Borry</name><uri>https://millironx.millironx.page/@indiewebpub/people/maxime-borry/</uri></author><author><name>Mahwash Jamy</name><uri>https://millironx.millironx.page/@indiewebpub/people/mahwash-jamy/</uri></author><author><name>Nf-Core Community</name><uri>https://millironx.millironx.page/@indiewebpub/people/nf-core-community/</uri></author><author><name>James A. Fellows Yates</name><uri>https://millironx.millironx.page/@indiewebpub/people/james-a.-fellows-yates/</uri></author><category term="paper"/><category term="genomics"/><summary type="text">
Metagenomic classification tackles the problem of characterising the taxonomic source of all DNA sequencing reads in a sample. A common approach to address the differences and biases between the many different taxonomic classification tools is to run metagenomic data through multiple classification tools and databases. This, however, is a very time-consuming task when performed manually - particularly when combined with the appropriate preprocessing of sequencing reads before the classification. Here we present nf-core/taxprofiler, a highly parallelised read-processing and taxonomic classification pipeline. It is designed for the automated and simultaneous classification and/or profiling of both short- and long-read metagenomic sequencing libraries against a 11 taxonomic classifiers and profilers as well as databases within a single pipeline run. Implemented in Nextflow and as part of the nf-core initiative, the pipeline benefits from high levels of scalability and portability, accommodating from small to extremely large projects on a wide range of computing infrastructure. It has been developed following best-practise software development practises and community support to ensure longevity and adaptability of the pipeline, to help keep it up to date with the field of metagenomics.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Metagenomic classification tackles the problem of characterising the taxonomic
source of all DNA sequencing reads in a sample. A common approach to address the
differences and biases between the many different taxonomic classification tools
is to run metagenomic data through multiple classification tools and databases.
This, however, is a very time-consuming task when performed manually -
particularly when combined with the appropriate preprocessing of sequencing
reads before the classification. Here we present nf-core/taxprofiler, a highly
parallelised read-processing and taxonomic classification pipeline. It is
designed for the automated and simultaneous classification and/or profiling of
both short- and long-read metagenomic sequencing libraries against a 11
taxonomic classifiers and profilers as well as databases within a single
pipeline run. Implemented in Nextflow and as part of the nf-core initiative, the
pipeline benefits from high levels of scalability and portability, accommodating
from small to extremely large projects on a wide range of computing
infrastructure. It has been developed following best-practise software
development practises and community support to ensure longevity and adaptability
of the pipeline, to help keep it up to date with the field of metagenomics.&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/hydronium-pva/</id><link rel="alternate" href="https://doi.org/10.1021/acsestengg.2c00107"/><title>Investigation of Hydronium Diffusion in Poly(vinyl alcohol) Hydrogels: A Critical First Step to Describe Acid Transport for Encapsulated Bioremediation</title><published>2022-09-02T00:00:00+00:00</published><updated>2022-09-02T00:00:00+00:00</updated><author><name>Carson J. Silsby</name><uri>https://millironx.millironx.page/@indiewebpub/people/carson-j.-silsby/</uri></author><author><name>Jonathan R. Counts</name><uri>https://millironx.millironx.page/@indiewebpub/people/jonathan-r.-counts/</uri></author><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><author><name>Mark F. Roll</name><uri>https://millironx.millironx.page/@indiewebpub/people/mark-f.-roll/</uri></author><author><name>Kristopher v. Waynant</name><uri>https://millironx.millironx.page/@indiewebpub/people/kristopher-v.-waynant/</uri></author><author><name>James G. Moberly</name><uri>https://millironx.millironx.page/@indiewebpub/people/james-g.-moberly/</uri></author><category term="paper"/><category term="diffusion"/><category term="hydrogels"/><category term="ionic strength"/><category term="polymers"/><category term="transport properties"/><summary type="text">
Bioremediation of chlorinated aliphatic hydrocarbon-contaminated aquifers can be hindered by high contaminant concentrations and acids generated during remediation. Encapsulating microbes in hydrogels may provide a protective, tunable environment from inhibiting compounds; however, current approaches to formulate successful encapsulated systems rely on trial and error rather than engineering approaches because fundamental information on mass-transfer coefficients is lacking. To address this knowledge gap, hydronium ion mass-transfer rates through two commonly used hydrogel materials, poly(vinyl alcohol) and alginic acid, under two solidification methods (chemical and cryogenic) were measured. Variations in hydrogel crosslinking conditions, polymer composition, and solvent ionic strength were investigated to understand how each influenced hydronium ion diffusivity. A three-way ANOVA indicated that the ionic strength, membrane type, and crosslinking method significantly (p &lt; 0.001) contributed to changes in hydronium ion mass transfer. Hydronium ion diffusion increased with ionic strength, counter to what is observed in aqueous-only (no polymer) solutions. Co-occurring mechanisms correlated to increased hydronium ion diffusion with ionic strength included an increased water fraction within hydrogel matrices and hydrogel contraction. Measured diffusion rates determined in this study provide first principal design information to further optimize encapsulating hydrogels for bioremediation.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Bioremediation of chlorinated aliphatic hydrocarbon-contaminated aquifers can be
hindered by high contaminant concentrations and acids generated during
remediation. Encapsulating microbes in hydrogels may provide a protective,
tunable environment from inhibiting compounds; however, current approaches to
formulate successful encapsulated systems rely on trial and error rather than
engineering approaches because fundamental information on mass-transfer
coefficients is lacking. To address this knowledge gap, hydronium ion
mass-transfer rates through two commonly used hydrogel materials, poly(vinyl
alcohol) and alginic acid, under two solidification methods (chemical and
cryogenic) were measured. Variations in hydrogel crosslinking conditions,
polymer composition, and solvent ionic strength were investigated to understand
how each influenced hydronium ion diffusivity. A three-way ANOVA indicated that
the ionic strength, membrane type, and crosslinking method significantly (&lt;em>p&lt;/em> &amp;lt;
0.001) contributed to changes in hydronium ion mass transfer. Hydronium ion
diffusion increased with ionic strength, counter to what is observed in
aqueous-only (no polymer) solutions. Co-occurring mechanisms correlated to
increased hydronium ion diffusion with ionic strength included an increased
water fraction within hydrogel matrices and hydrogel contraction. Measured
diffusion rates determined in this study provide first principal design
information to further optimize encapsulating hydrogels for bioremediation.&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/rotavirus-virome/</id><link rel="alternate" href="https://doi.org/10.1016/j.vetmic.2022.109447"/><title>Assessment of Porcine Rotavirus-associated virome variations in pigs with enteric disease</title><published>2022-04-27T00:00:00+00:00</published><updated>2022-04-27T00:00:00+00:00</updated><author><name>Tyler Doerksen</name><uri>https://millironx.millironx.page/@indiewebpub/people/tyler-doerksen/</uri></author><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><author><name>Andrea Lu</name><uri>https://millironx.millironx.page/@indiewebpub/people/andrea-lu/</uri></author><author><name>Lance Noll</name><uri>https://millironx.millironx.page/@indiewebpub/people/lance-noll/</uri></author><author><name>Jianfa Bai</name><uri>https://millironx.millironx.page/@indiewebpub/people/jianfa-bai/</uri></author><author><name>Jamie Henningson</name><uri>https://millironx.millironx.page/@indiewebpub/people/jamie-henningson/</uri></author><author><name>Rachel Palinski</name><uri>https://millironx.millironx.page/@indiewebpub/people/rachel-palinski/</uri></author><category term="paper"/><category term="porcine rotavirus"/><category term="porcine enteric disease"/><category term="virome"/><category term="rotavirus"/><summary type="text">
Enteric disease is the predominant cause of morbidity and mortality in young mammals including pigs. Viral species involved in porcine enteric disease complex (PEDC) include rotaviruses, coronaviruses, picornaviruses, astroviruses and pestiviruses among others. The virome of three groups of swine samples submitted to the Kansas State University Veterinary Diagnostic Laboratory for routine testing were assessed, namely, a Rotavirus A positive (RVA) group, a Rotavirus co-infection (RV) group and a Rotavirus Negative (RV Neg) group. All groups were designated by qRT-PCR results testing for Porcine Rotavirus A, B, C and H such that samples positive for RVA only went in the RVA group, samples positive for >1 rotavirus went in the RV group and samples negative for all were grouped in the RVNeg group. All of the animals had clinical enteric disease resulting in scours and swollen joints/lameness, enlarged heart and/or a cough. All samples were metagenomic sequenced and analyzed for viral species composition that identified 14 viral species and eight bacterial viruses/phages. Sapovirus and Escherichia coli phages were found at a high prevalence in RVA and RV samples but were found at low or no prevalence in the RV Neg samples. Picobirnavirus was identified at a high proportion and prevalence in RV Neg and RV samples but at a low prevalence in the RVA group. A sequence analysis of the possible host of Picobirnaviruses revealed fungi as the most likely host. Non-rotaviral diversity was highest in RVA samples followed by RV then RV Neg samples. Various sequences were extracted from the sample reads and a phylogenetic update was provided showing a high prevalence of G9 and P[23] RVA genotypes. These data are important for pathogen surveillance and control measures</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Enteric disease is the predominant cause of morbidity and mortality in young
mammals including pigs. Viral species involved in porcine enteric disease
complex (PEDC) include rotaviruses, coronaviruses, picornaviruses, astroviruses
and pestiviruses among others. The virome of three groups of swine samples
submitted to the Kansas State University Veterinary Diagnostic Laboratory for
routine testing were assessed, namely, a Rotavirus A positive (RVA) group, a
Rotavirus co-infection (RV) group and a Rotavirus Negative (RV Neg) group. All
groups were designated by qRT-PCR results testing for Porcine Rotavirus A, B, C
and H such that samples positive for RVA only went in the RVA group, samples
positive for &amp;gt;1 rotavirus went in the RV group and samples negative for all were
grouped in the RVNeg group. All of the animals had clinical enteric disease
resulting in scours and swollen joints/lameness, enlarged heart and/or a cough.
All samples were metagenomic sequenced and analyzed for viral species
composition that identified 14 viral species and eight bacterial viruses/phages.
Sapovirus and Escherichia coli phages were found at a high prevalence in RVA and
RV samples but were found at low or no prevalence in the RV Neg samples.
Picobirnavirus was identified at a high proportion and prevalence in RV Neg and
RV samples but at a low prevalence in the RVA group. A sequence analysis of the
possible host of Picobirnaviruses revealed fungi as the most likely host.
Non-rotaviral diversity was highest in RVA samples followed by RV then RV Neg
samples. Various sequences were extracted from the sample reads and a
phylogenetic update was provided showing a high prevalence of G9 and P[23] RVA
genotypes. These data are important for pathogen surveillance and control
measures&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/thesis/</id><link rel="alternate" href="https://www.proquest.com/dissertations-theses/polyoxometalate-incorporation-effects-on-proton/docview/2502214356/se-2"/><title>Polyoxometalate Incorporation and Effects on Proton Transport in Hydrogel Polymers</title><published>2020-08-07T00:00:00+00:00</published><updated>2020-08-07T00:00:00+00:00</updated><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><category term="thesis"/><category term="bioremediation"/><category term="polyoxometalate"/><category term="hydrogel polymers"/><category term="proton transport"/><category term="chemical engineering"/><summary type="text">
Polyoxometalate clusters embedded into hydrogel biobeads may be able to solve the challenges posed by free proton generation during remediation of trichloroethylene by acting as buffers and reducing protons to hydrogen gas. In this thesis, the challenges posed by systems that contain both diffusion and reaction processes for protons are considered mathematically, and a computer simulation to was developed to prove the relationship between diaphragm cell lag period and reactive capabilities of membranes. Two polyoxometalate compounds, sodium decavanadate and alumina sulfate, were successfully incorporated into a poly(vinyl alcohol) hydrogel membrane, and the diffusivity changes associated with each compound was determined. It was found that the diffusivity of protons through an unmodified 10% w/v poly(vinyl alcohol) membrane was 1.76 × 10-5 cm2 s-1 , the diffusivity through a 10%/2% w/w/v poly(vinyl alcohol)/sodium decavanadate membrane was 3.10 × 10-6 cm2 s-1 , and the diffusivity through a 10%/2% w/w/v poly(vinyl alcohol)/alumina sulfate membrane was 3.32 × 10-7 cm2 s-1 . Through analysis of the diaphragm cell lag period, it was found the incorporation of sodium decavanadate did not increase the reactivity of a poly(vinyl alcohol) hydrogel, and incorporation of alumina sulfate lowered the reactivity. These results indicate that polyoxometalate integration into hydrogel membranes is feasible, but does not provide any advantage to a bioremediation scenario.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Polyoxometalate clusters embedded into hydrogel biobeads may be able to solve
the challenges posed by free proton generation during remediation of
trichloroethylene by acting as buffers and reducing protons to hydrogen gas. In
this thesis, the challenges posed by systems that contain both diffusion and
reaction processes for protons are considered mathematically, and a computer
simulation to was developed to prove the relationship between diaphragm cell lag
period and reactive capabilities of membranes. Two polyoxometalate compounds,
sodium decavanadate and alumina sulfate, were successfully incorporated into a
poly(vinyl alcohol) hydrogel membrane, and the diffusivity changes associated
with each compound was determined. It was found that the diffusivity of protons
through an unmodified 10% w/v poly(vinyl alcohol) membrane was 1.76 ×
10&lt;sup>-5&lt;/sup>
 cm&lt;sup>2&lt;/sup>
 s&lt;sup>-1&lt;/sup>
, the diffusivity through a
10%/2% w/w/v poly(vinyl alcohol)/sodium decavanadate membrane was 3.10 ×
10&lt;sup>-6&lt;/sup>
 cm&lt;sup>2&lt;/sup>
 s&lt;sup>-1&lt;/sup>
, and the diffusivity through a
10%/2% w/w/v poly(vinyl alcohol)/alumina sulfate membrane was 3.32 ×
10&lt;sup>-7&lt;/sup>
 cm&lt;sup>2&lt;/sup>
 s&lt;sup>-1&lt;/sup>
. Through analysis of the
diaphragm cell lag period, it was found the incorporation of sodium decavanadate
did not increase the reactivity of a poly(vinyl alcohol) hydrogel, and
incorporation of alumina sulfate lowered the reactivity. These results indicate
that polyoxometalate integration into hydrogel membranes is feasible, but does
not provide any advantage to a bioremediation scenario.&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/metagenomics/</id><link rel="alternate" href="/academia/metagenomics/metagenomics_analysis_of_rumen_populations.pdf"/><title>Metagenomic analysis of rumen populations in week-old calves as altered by maternal late gestational nutrition and mode of delivery</title><published>2019-06-12T00:00:00+00:00</published><updated>2019-06-12T00:00:00+00:00</updated><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><author><name>Kathy J. Austin</name><uri>https://millironx.millironx.page/@indiewebpub/people/kathy-j.-austin/</uri></author><author><name>Kristi M. Cammack</name><uri>https://millironx.millironx.page/@indiewebpub/people/kristi-m.-cammack/</uri></author><author><name>Hannah C. Cunningham-Hollinger</name><uri>https://millironx.millironx.page/@indiewebpub/people/hannah-c.-cunningham-hollinger/</uri></author><category term="poster"/><category term="gestation"/><category term="metagenomics"/><category term="microbiome"/><category term="rumen"/><summary type="text">
Early colonization of the rumen microbiome is critical to host health and long term performance. Factors that influence early colonization include maternal factors such as gestational nutrition and mode of delivery. Therefore, we hypothesized that late gestational nutrition and mode of delivery would influence the calf rumen microbiome. Our objectives were to determine if nutrient restriction during late gestation alters the calf rumen microbiome and determine if ruminal microbiome composition differs in calves born vaginally versus caesarean. Late gestating Angus cows were randomly allocated to one of three treatment groups: control (CON; n = 6), caesarean section (CS; n = 4), and nutrient restricted (NR; n = 5), where CON were fed DDGS and hay to meet NRC requirements and calved naturally; CS were fed similarly to CON and calves were born via caesarean section; and NR were fed at a level to reduce BCS by 1.5-2.0 points over the last trimester compared to CON and calved naturally. Rumen fluid was collected via oral lavage prior to partition from cows and at d 7 from calves. Microbial DNA was isolated from the rumen fluid and metagenomic shotgun sequencing was performed using the Illumina HiSeq 2500 platform. Sequence data were analyzed using Metaxa2 for taxonomic assignment followed by QIIME1 and QIIME2 to determine differential abundance and alpha- and beta-diversity differences. There were no significant differences in alpha-diversity as measured by shannon index across treatment groups for cows (P = 0.239), but there were significant differences for calves (P = 0.015). Similarly, there were no significant differences in beta-diversity as measured by the bray-curtis dissimilarity matrix for cows (P = 0.059), but there were significant differences for calves (P = 0.007). Alpha-diversity differed (P &lt; 0.001) between cows and calves, with cows having increased species richness compared to calves. Beta-diversity also differed (P = 0.001) between cows and calves. At total of 410 taxa were differentially abundant (P &lt; 0.01) between cows and calves. These results suggest that the mature rumen microbiome of cows is able to withstand changes in feed intake, however the calf microbiome is susceptible to alteration by maternal factors. These data also suggest that there may be opportunities to develop management strategies during late gestation that influence calf health and performance long-term.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Early colonization of the rumen microbiome is critical to host health and long
term performance. Factors that influence early colonization include maternal
factors such as gestational nutrition and mode of delivery. Therefore, we
hypothesized that late gestational nutrition and mode of delivery would
influence the calf rumen microbiome. Our objectives were to determine if
nutrient restriction during late gestation alters the calf rumen microbiome and
determine if ruminal microbiome composition differs in calves born vaginally
versus caesarean. Late gestating Angus cows were randomly allocated to one of
three treatment groups: control (&lt;strong>CON&lt;/strong>; n = 6), caesarean section (&lt;strong>CS&lt;/strong>; n =
4), and nutrient restricted (&lt;strong>NR&lt;/strong>; n = 5), where CON were fed DDGS and hay to
meet NRC requirements and calved naturally; CS were fed similarly to CON and
calves were born via caesarean section; and NR were fed at a level to reduce BCS
by 1.5-2.0 points over the last trimester compared to CON and calved naturally.
Rumen fluid was collected via oral lavage prior to partition from cows and at d
7 from calves. Microbial DNA was isolated from the rumen fluid and metagenomic
shotgun sequencing was performed using the Illumina HiSeq 2500 platform.
Sequence data were analyzed using Metaxa2 for taxonomic assignment followed by
QIIME1 and QIIME2 to determine differential abundance and alpha- and
beta-diversity differences. There were no significant differences in
alpha-diversity as measured by shannon index across treatment groups for cows
(&lt;em>P&lt;/em> = 0.239), but there were significant differences for calves (&lt;em>P&lt;/em> = 0.015).
Similarly, there were no significant differences in beta-diversity as measured
by the bray-curtis dissimilarity matrix for cows (&lt;em>P&lt;/em> = 0.059), but there were
significant differences for calves (&lt;em>P&lt;/em> = 0.007). Alpha-diversity differed (&lt;em>P&lt;/em>
&amp;lt; 0.001) between cows and calves, with cows having increased species richness
compared to calves. Beta-diversity also differed (&lt;em>P&lt;/em> = 0.001) between cows and
calves. At total of 410 taxa were differentially abundant (&lt;em>P&lt;/em> &amp;lt; 0.01) between
cows and calves. These results suggest that the mature rumen microbiome of cows
is able to withstand changes in feed intake, however the calf microbiome is
susceptible to alteration by maternal factors. These data also suggest that
there may be opportunities to develop management strategies during late
gestation that influence calf health and performance long-term.&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/cheme-car/</id><link rel="alternate" href="https://doi.org/10.15786/13700938.v1"/><title>The ChemE Car that Cud: AIChE ChemE Car Engineering Design Proposal</title><published>2019-05-14T00:00:00+00:00</published><updated>2019-05-14T00:00:00+00:00</updated><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><category term="thesis"/><category term="chemical engineering"/><category term="aiche"/><category term="radiation"/><category term="rumen"/><category term="microbial electrolysis cells"/><summary type="text">
The ChemE Car That Cud showcases Wyoming’s dominant industries of agriculture and mining by utilizing rumen fluid from a cannulated beef cow to generate hydrogen to be used in a hydrogen fuel cell and radioactive cesium, a byproduct of uranium that is often obtained from Wyoming’s mines, to time the car’s stop. The concentration of cesium-137 source is measured using the radioactive decay of cesium shielded by aluminum. The painted aluminum chassis was obtained from a previous team at UW, and modified using plastic k’nex toys to adapt to the current power source and stopping mechanism.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>The ChemE Car That Cud showcases Wyoming&amp;rsquo;s dominant industries of agriculture
and mining by utilizing rumen fluid from a cannulated beef cow to generate
hydrogen to be used in a hydrogen fuel cell and radioactive cesium, a byproduct
of uranium that is often obtained from Wyoming&amp;rsquo;s mines, to time the car&amp;rsquo;s stop.
The concentration of cesium-137 source is measured using the radioactive decay
of cesium shielded by aluminum. The painted aluminum chassis was obtained from a
previous team at UW, and modified using plastic k&amp;rsquo;nex toys to adapt to the
current power source and stopping mechanism.&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/pva-aiche/</id><link rel="alternate" href="/academia/pva-aiche/measuring_diffusion_of_trichloroethylene.pdf"/><title>Measuring Diffusion of Trichlorethylene Breakdown Products in Polyvinylalginate</title><published>2018-10-29T00:00:00+00:00</published><updated>2018-10-29T00:00:00+00:00</updated><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><author><name>Samuel R. Wolfe</name><uri>https://millironx.millironx.page/@indiewebpub/people/samuel-r.-wolfe/</uri></author><author><name>Jonathan Counts</name><uri>https://millironx.millironx.page/@indiewebpub/people/jonathan-counts/</uri></author><author><name>Mark F. Roll</name><uri>https://millironx.millironx.page/@indiewebpub/people/mark-f.-roll/</uri></author><author><name>Kristopher v. Waynant</name><uri>https://millironx.millironx.page/@indiewebpub/people/kristopher-v.-waynant/</uri></author><author><name>James G. Moberly</name><uri>https://millironx.millironx.page/@indiewebpub/people/james-g.-moberly/</uri></author><category term="poster"/><category term="bioremediation"/><category term="polyoxometalate"/><category term="hydrogel polymers"/><category term="proton transport"/><category term="chemical engineering"/><summary type="text">
Trichloroethylene (TCE), a toxic and carcinogenic contaminant, presents unique challenges for cleanup because of its water solubility, density, and volatility. Bioremediation of TCE is a promising cleanup method; however, metabolism of TCE results in acid generation that inhibits remediating microorganisms. Calcium alginate(CA)-polyvinylalcohol (PVA) hydrogels show promise for protecting remediating microbes, however diffusion of TCE or its byproducts through these polymers is unknown. To measure the effective diffusion coefficient of TCE and byproducts through hydrogel membranes, we used a modified diaphragm cell. Measured effective diffusion coefficient of each species was (cm 2 /s × 106 ): 14.0 ± 1.91 for H+ ions, 12.4 ± 1.64 for TCE, 7.83 ± 0.54 for cis-1,2-dichloroethylene (DCE), and 4.68 ± 4.14 for vinyl chloride. These results aid in engineering biobeads and suggest that CA-PVA hydrogel blends are effective in slowing diffusion of protons, buffering acids produced by trichloroethylene metabolism, and remains suitable for encapsulation of microorganisms involved in bioremediation.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Trichloroethylene (TCE), a toxic and carcinogenic contaminant, presents unique
challenges for cleanup because of its water solubility, density, and volatility.
Bioremediation of TCE is a promising cleanup method; however, metabolism of TCE
results in acid generation that inhibits remediating microorganisms. Calcium
alginate(CA)-polyvinylalcohol (PVA) hydrogels show promise for protecting
remediating microbes, however diffusion of TCE or its byproducts through these
polymers is unknown. To measure the effective diffusion coefficient of TCE and
byproducts through hydrogel membranes, we used a modified diaphragm cell.
Measured effective diffusion coefficient of each species was (cm &lt;sup>2&lt;/sup>
/s
× 10&lt;sup>6&lt;/sup>
): 14.0 ± 1.91 for H&lt;sup>&amp;#43;&lt;/sup>
 ions, 12.4 ± 1.64 for TCE,
7.83 ± 0.54 for cis-1,2-dichloroethylene (DCE), and 4.68 ± 4.14 for vinyl
chloride. These results aid in engineering biobeads and suggest that CA-PVA
hydrogel blends are effective in slowing diffusion of protons, buffering acids
produced by trichloroethylene metabolism, and remains suitable for encapsulation
of microorganisms involved in bioremediation.&lt;/p>
</content></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/how-to-build-a-cow-cud-fuel-cell/</id><link rel="alternate" href="https://millironx.millironx.page/@indiewebpub/academia/how-to-build-a-cow-cud-fuel-cell/"/><title>How to Build a Cow-Cud Fuel Cell</title><published>2018-08-01T00:00:00+00:00</published><updated>2018-08-01T00:00:00+00:00</updated><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><category term="presentation"/></entry><entry><id>https://millironx.millironx.page/@indiewebpub/academia/pva-inbre/</id><link rel="alternate" href="https://millironx.millironx.page/@indiewebpub/academia/pva-inbre/"/><title>Measuring diffusion of protons in polyvinyalginate</title><published>2018-07-31T00:00:00+00:00</published><updated>2018-07-31T00:00:00+00:00</updated><author><name>Thomas A. Christensen II</name><uri>https://millironx.millironx.page/@indiewebpub/people/thomas-a.-christensen-ii/</uri></author><author><name>Jonathan Counts</name><uri>https://millironx.millironx.page/@indiewebpub/people/jonathan-counts/</uri></author><author><name>James G. Moberly</name><uri>https://millironx.millironx.page/@indiewebpub/people/james-g.-moberly/</uri></author><category term="poster"/><summary type="text">
Trichloroethylene (TCE) is a toxic and carcinogenic contaminant that presents unique challenges for cleanup because of its density and volatility. Use of microorganisms may be a promising remediation method, however metabolism of TCE results in acid buildup, which consequently impedes the ability of microorganisms to perform this remediation. Polyvinylalginate (PVA) shows promise as a useful shield for microorganisms carrying out bioremediation of TCE by surrounding them in a protective biofilm-like layer, however, key information is missing which relates diffusion of TCE or its metabolic products through PVA. To measure the effective diffusion coefficient of H+ ions through a PVA membrane cross-linked with boric acid and calcium ions, we used a modified diaphragm cell. We found the effective diffusion coefficient to be 1.40 × 10-5 ± 1.91 × 10-6 cm2 s, a nearly seven-fold decrease in diffusivity compared to protons in water, with an unexpected significant but as of yet unquantified adsorption capacity. These results suggest that polyvinylalginate is effective in slowing diffusion of protons and buffering these acids produced by trichloroethylene metabolism, and remains suitable for encapsulation of microorganisms involved in bioremediation.</summary><content type="html" xml:lang="en" xml:base="https://millironx.millironx.page/@indiewebpub/">
&lt;p>Trichloroethylene (TCE) is a toxic and carcinogenic contaminant that presents
unique challenges for cleanup because of its density and volatility. Use of
microorganisms may be a promising remediation method, however metabolism of TCE
results in acid buildup, which consequently impedes the ability of
microorganisms to perform this remediation. Polyvinylalginate (PVA) shows
promise as a useful shield for microorganisms carrying out bioremediation of TCE
by surrounding them in a protective biofilm-like layer, however, key information
is missing which relates diffusion of TCE or its metabolic products through PVA.
To measure the effective diffusion coefficient of H&lt;sup>&amp;#43;&lt;/sup>
 ions through
a PVA membrane cross-linked with boric acid and calcium ions, we used a modified
diaphragm cell. We found the effective diffusion coefficient to be 1.40 ×
10&lt;sup>-5&lt;/sup>
 ± 1.91 × 10&lt;sup>-6&lt;/sup>
 cm&lt;sup>2&lt;/sup>
s, a nearly
seven-fold decrease in diffusivity compared to protons in water, with an
unexpected significant but as of yet unquantified adsorption capacity. These
results suggest that polyvinylalginate is effective in slowing diffusion of
protons and buffering these acids produced by trichloroethylene metabolism, and
remains suitable for encapsulation of microorganisms involved in bioremediation.&lt;/p>
</content></entry></feed>