University of South Carolina Sumter

Electrochemical methods for metal nanoparticle (MNP) electrodeposition offer precise control over particle formation without the need for harsh chemicals, extreme reaction conditions, high energy input, or the prolonged synthesis times associated with conventional approaches. Among electrochemical electrodeposition techniques, constant-potential amperometry is widely utilized, employing a single-step potential to reduce metal ions to solid metal at electrode surfaces, thereby producing MNPs. Although single-pulse electrodeposition provides improved control of MNP formation relative to bulk chemical synthesis, it often results in broad particle size distributions and poor spatial dispersion, particularly at longer deposition times. To address these limitations, herein we introduce an alternating potential pulse (APP) method as an approach to enhance particle size distribution, electrode surface coverage, and metal loading on carbon-based electrodes. The APP method was evaluated on two distinct carbon electrode platforms, namely, our nano-sized carbon ultramicroelectrode arrays (CUAs) and planar carbon macroelectrodes, using both gold (AuNPs) and silver nanoparticles (AgNPs). Overall, the APP method yielded higher counts of smaller, more narrowly distributed nanoparticles compared to the single-pulse approach. On CUAs, AuNP coverage increased from 70 ± 20% with the single 300 s pulse to 100% for 300 pulses of 1 s each. Macroelectrodes showed a similar improvement, with particle coverage increasing from 77 ± 7 to 186 ± 3 particles cm–2 under analogous conditions. Gold loading on CUAs likewise increased, rising from 90 ± 10 nmol with the single-pulse method to 310 ± 90 nmol using APP deposition. AgNP electrodeposition exhibited similar trends where Ag amounts on CUAs increased from 90 ± 20 nmol (one 60 s pulse) to 160 ± 10 nmol (six 10 s pulses), while macroelectrode Ag loading increased from 280 ± 30 to 400 ± 50 nmol over the same deposition period. We attribute these improvements to differences in diffusion-layer behavior at the electrode–solution interface induced by the unique APP potential-time waveform, wherein each deposition pulse renews metal-ion availability at the electrode surface and promotes more uniform nucleation. In summary, the APP method produced consistent enhancements across two distinct carbon-based electrode platforms and two different metals, demonstrating improved particle size distributions, surface coverage, and metal loading, and underscoring the versatility of the APP approach for MNP electrodeposition.

Case:Ryan is a 6-year-old boy with a history of eosinophilic esophagitis (EoE) and poor weight gain referred to developmental-behavioral pediatrics (DBP) for attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD). Ryan's mother was concerned about Ryan's defiance and daily emotional outbursts, which could last up to an hour. Ryan's teachers frequently contacted the family due to disruptive behavior, impulsivity, and sneaking food.Ryan was born prematurely at 28 weeks and required nasogastric feeds for 1 month in the NICU. He has a history of reflux requiring proton pump inhibitors and failure to thrive at age 2 (currently at 6% for BMI). At age 4, he was evaluated by pediatric gastroenterology and subsequently diagnosed with EoE. Complete elimination of dairy, wheat, soy, eggs, nuts, and seafood/shellfish was recommended as per standard of care for EoE. The diet was difficult for the family and Ryan to maintain, and Ryan often had tantrums around foods/snacks. He would sneak into the pantry to eat things he was not supposed to, causing significant parent-child conflict. Food restrictions were particularly challenging at school. Ryan would ask classmates for their cheese sticks and cookies; snacks he was not allowed to eat. Despite a 504 plan in place, his teachers were unable to monitor his intake.Parent and teacher behavior rating scales were consistent with ADHD-combined type and ODD. Cognitive and academic testing demonstrated academic underachievement in math and reading; however, these results were thought to be an underrepresentation of his true abilities due to easy distractibility and impulsivity observed during assessments. Behavioral therapy, IEP evaluation, and trial of ADHD medication were recommended.Given his poor weight gain and inability to swallow tablets, a nonstimulant, guanfacine immediate release (IR) was initiated. Guanfacine was helpful, but titration was limited due to daytime sedation. Ryan was placed on homebound services due to frequent EoE flares and concerns that school could not adequately monitor food restrictions.GI recommended elemental formula as his primary source of intake due to nonadherence to diet. Ryan required a gastrostomy tube (g-tube) due to his refusal to drink elemental formula. Although EoE symptoms improved, Ryan had increased oppositional and defiant behaviors with his homebound teacher and parents. An extended-release oral liquid methylphenidate stimulant was started in conjunction with guanfacine and resulted in significant improvement of ADHD symptoms. Ryan experienced weight loss and decreased BMI to 3%. Periactin was initiated to help with appetite and sleep quality.After 3 months, Ryan started feeding therapy and behavioral therapy with a family component. He was also approved for home nursing support and respite hours. Several months later, Ryan endorsed missing his friends and wanting to go back to school. He agreed to sign a behavioral contract stating that if he returned to school, he would not sneak/steal food.What are some recommendations to consider for addressing Ryan's behavioral challenges?

PremiseSpatial and temporal variations in climate and ecological interactions may underlie the origin and maintenance of floral color polymorphisms across a species range. Betalains are nitrogen‐containing, phylogenetically restricted pigments that, like the widespread and well‐studied anthocyanins and carotenoids, may attract pollinators, deter herbivores, and protect against abiotic stress.MethodsWe investigated which selection pressures underlie betalain pigmentation variation in Abronia fragrans, a wildflower polymorphic in floral color across its range.ResultsWhile most populations produced white flowers, some in the south‐central United States bore pink flowers with reduced floral display, suggesting a trade‐off between pigment production and reproductive investment. A greenhouse experiment confirmed that floral pigmentation was heritable, though it was not correlated with other inflorescence traits across the species range, nor with pigmentation of most other flower or vegetative tissues. However, floral betalain concentration was positively correlated with hotter, wetter summers and milder winters across populations. Transplant experiments across this floral‐color transition zone also revealed marked ecological differences: The pink‐flowered site had higher seed set and leaf herbivory, while the white‐flowered site experienced greater florivory. Leaf herbivore damage was highest on transplants that differed in floral color from the local morph at each site.ConclusionsAlthough less‐pigmented plants produced more flowers, this relationship did not translate to higher reproductive success, suggesting an ecological trade‐off of pigmentation may drive the observed floral color pattern. Our findings underscore how complex ecological interactions may shape floral trait divergence and highlight the importance of integrating biotic and abiotic factors to understand the evolution of phenotypic variation.

With the rising prevalence of metabolic diseases, infections, and mental health disorders, there is a growing demand for noninvasive diagnostic tools that enable early detection and continuous health monitoring. In this context, exhaled breath biomarkers provide insight into physiological and pathological processes. Electrochemical breath sensors (EBSs) have emerged as a promising platform for rapid, real‐time, and cost‐effective disease tracking via the detection of volatile breath biomarkers, such as NH 3 , NO, and CO 2 . Recent advancements in electrode materials, biological recognition elements, and sensor architectures—spanning nanomaterials, enzymes, aptamers, and molecularly imprinted polymers—have enhanced the analytical performance of EBSs. Nonetheless, challenges remain in achieving biologically relevant detection ranges, selectivity in complex breath matrices, and long‐term environmental stability. This perspective article provides a critical overview of recent innovations and enduring limitations in EBS development. Beyond their role in monitoring physiological diseases, we highlight the emerging potential of EBSs for mental health assessment through the detection of gut‐derived metabolites in exhaled breath, such as short‐chain fatty acids, H 2 S, and ammonia, as indicators of gut–brain axis activity. The EBS‐based, noninvasive, real‐time measurement of these metabolites represents a transformative and underexplored approach for the diagnosis and treatment of psychiatric disorders.

<strong class="journal-contentHeaderColor">Abstract.</strong> Atmospheric sulfate formation influences climate and air quality, yet its chemical pathways remain difficult to constrain. This study utilizes the oxygen isotope anomaly (&Delta;¹⁷O) of sulfate aerosol (ASO₄) as a tracer to distinguish formation processes. We modeled &Delta;¹⁷O(ASO₄) using the Community Multiscale Air Quality Model (CMAQ), focusing on 2006 and 2019 to quantify key ASO₄ formation pathways and their response to U.S. emission changes. In 2006, &Delta;¹⁷O(ASO₄) values were predicted to be below 1 &permil; in the Gulf Coast indicated acidic, ASO₄-rich conditions dominated by S(IV) + H₂O₂ oxidation, while values above 1 &permil; in the West suggested less acidic conditions, leading to enhanced ASO₄ production via S(IV) + O₃ oxidation. Peak &Delta;¹⁷O(ASO₄) values of ~5 &permil; in April across the Western U.S. reflected O₃-driven ASO₄ formation during high ammonia (NH₃) emissions from fertilization. Between 2006 and 2019, mean &Delta;¹⁷O(ASO₄) increased by up to 2 &permil;, driven by declining sulfur dioxide (SO₂) emissions from regulatory measures. Model comparisons with historical measurements show reasonable agreement in the acidic southeastern U.S. (RMSE = 0.3 &permil;, Baton Rouge, LA). However, the model overpredicts &Delta;¹⁷O(ASO₄) in the West (RMSE = 0.5 &permil;, La Jolla, CA; RMSE = 2.1 &permil;, White Mountain Research Center, CA), particularly during periods of high NH₃ emissions. This overestimation suggests an excessive model response to aqueous S(IV) + O₃ reactions. These results emphasize the need for expanded &Delta;¹⁷O(ASO₄) measurements and improved model constraints to better capture evolving emission trends and regulatory impacts on sulfate formation.

Stress granule formation is a type of liquid-liquid phase separation in the cytoplasm, leading to RNA-protein condensates that are associated with various cellular stress responses and implicated in numerous pathologies, including cancer, neurodegeneration, inflammation, and cellular senescence. One of the key components of mammalian stress granules is the DEAD-box RNA helicase DDX3, which unwinds RNA in an ATP-dependent manner. DDX3 is involved in multiple steps of RNA metabolism, facilitating gene transcription, splicing, and nuclear export and regulating cytoplasmic translation. In this study, we investigate the role of the RNA helicase DDX3's enzymatic activity in shaping the RNA content of ribonucleoprotein (RNP) condensates formed during arsenite-induced stress by inhibiting DDX3 activity with RK-33, a small molecule previously shown to be effective in cancer clinical studies. Using the human osteosarcoma U2OS cell line, we purified the RNP granule fraction and performed RNA sequencing to assess changes in the RNA pool. Our results reveal that RK-33 treatment alters the composition of non-coding RNAs within the RNP granule fraction. We observed a DDX3-dependent increase in circular RNA (circRNA) content and alterations in the granule-associated intronic RNAs, suggesting a novel role for DDX3 in regulating the cytoplasmic redistribution of non-coding RNAs.

Abstract. Regional inverse analyses of atmospheric trace gas observations quantify gridded two-dimensional surface fluxes by fitting the observations to simulated concentrations from a chemical transport model (CTM), usually by Bayesian optimization regularized by a gridded prior flux estimates. Regional inversions rely on the specification of background concentrations given by the boundary conditions (BCs) at the edges of the inversion domain, but biases in the BCs propagate to biases in the optimized fluxes. We develop a theoretical framework to explain how errors in the BCs influence the optimized fluxes as a function of the prior and observing system error statistics and of CTM transport. We derive a preview metric to estimate the BC-induced errors before conducting an inversion to support domain specification and a diagnostic metric to accurately quantify these errors after solving the inversion. We compare two methods to correct BC biases as part of an inversion, either directly by optimizing BC concentrations (boundary method) or indirectly by correcting grid cell fluxes outside the domain of interest (buffer method). We demonstrate that the boundary method is generally more accurate, physically grounded, and computationally tractable.

<strong class="journal-contentHeaderColor">Abstract.</strong> Atmospheric sulfate formation influences climate and air quality, yet its chemical pathways remain difficult to constrain. This study utilizes the oxygen isotope anomaly (&Delta;¹⁷O) of sulfate aerosol (ASO₄) as a tracer to distinguish formation processes. We modeled &Delta;¹⁷O(ASO₄) using the Community Multiscale Air Quality Model (CMAQ), focusing on 2006 and 2019 to quantify key ASO₄ formation pathways and their response to U.S. emission changes. In 2006, &Delta;¹⁷O(ASO₄) values were predicted to be below 1 &permil; in the Gulf Coast indicated acidic, ASO₄-rich conditions dominated by S(IV) + H₂O₂ oxidation, while values above 1 &permil; in the West suggested less acidic conditions, leading to enhanced ASO₄ production via S(IV) + O₃ oxidation. Peak &Delta;¹⁷O(ASO₄) values of ~5 &permil; in April across the Western U.S. reflected O₃-driven ASO₄ formation during high ammonia (NH₃) emissions from fertilization. Between 2006 and 2019, mean &Delta;¹⁷O(ASO₄) increased by up to 2 &permil;, driven by declining sulfur dioxide (SO₂) emissions from regulatory measures. Model comparisons with historical measurements show reasonable agreement in the acidic southeastern U.S. (RMSE = 0.3 &permil;, Baton Rouge, LA). However, the model overpredicts &Delta;¹⁷O(ASO₄) in the West (RMSE = 0.5 &permil;, La Jolla, CA; RMSE = 2.1 &permil;, White Mountain Research Center, CA), particularly during periods of high NH₃ emissions. This overestimation suggests an excessive model response to aqueous S(IV) + O₃ reactions. These results emphasize the need for expanded &Delta;¹⁷O(ASO₄) measurements and improved model constraints to better capture evolving emission trends and regulatory impacts on sulfate formation.

<strong class="journal-contentHeaderColor">Abstract.</strong> Atmospheric sulfate formation influences climate and air quality, yet its chemical pathways remain difficult to constrain. This study utilizes the oxygen isotope anomaly (&Delta;¹⁷O) of sulfate aerosol (ASO₄) as a tracer to distinguish formation processes. We modeled &Delta;¹⁷O(ASO₄) using the Community Multiscale Air Quality Model (CMAQ), focusing on 2006 and 2019 to quantify key ASO₄ formation pathways and their response to U.S. emission changes. In 2006, &Delta;¹⁷O(ASO₄) values were predicted to be below 1 &permil; in the Gulf Coast indicated acidic, ASO₄-rich conditions dominated by S(IV) + H₂O₂ oxidation, while values above 1 &permil; in the West suggested less acidic conditions, leading to enhanced ASO₄ production via S(IV) + O₃ oxidation. Peak &Delta;¹⁷O(ASO₄) values of ~5 &permil; in April across the Western U.S. reflected O₃-driven ASO₄ formation during high ammonia (NH₃) emissions from fertilization. Between 2006 and 2019, mean &Delta;¹⁷O(ASO₄) increased by up to 2 &permil;, driven by declining sulfur dioxide (SO₂) emissions from regulatory measures. Model comparisons with historical measurements show reasonable agreement in the acidic southeastern U.S. (RMSE = 0.3 &permil;, Baton Rouge, LA). However, the model overpredicts &Delta;¹⁷O(ASO₄) in the West (RMSE = 0.5 &permil;, La Jolla, CA; RMSE = 2.1 &permil;, White Mountain Research Center, CA), particularly during periods of high NH₃ emissions. This overestimation suggests an excessive model response to aqueous S(IV) + O₃ reactions. These results emphasize the need for expanded &Delta;¹⁷O(ASO₄) measurements and improved model constraints to better capture evolving emission trends and regulatory impacts on sulfate formation.