Spectral Background Calibration of Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) Spectrometer Onboard the Perseverance Rover Enables Identification of a Ubiquitous Martian Spectral Component.

The Perseverance rover landed at Jezero crater, Mars, on 18 February 2021, with a payload of scientific instruments to examine Mars' past habitability, look for signs of past life, and process samples for future return to Earth. The instrument payload includes the Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) deep ultraviolet Raman and fluorescence imaging spectrometer designed to detect, characterize, and map the presence of organics and minerals on the Martian surface. Operation and engineering constraints sometimes result in the acquisition of spectra with features near the detection limit. It is therefore important to separate instrumental (background) spectral components and spectral components inherent to Martian surface materials. For SHERLOC, the instrumental background is assessed by collecting spectra in the stowed-arm configuration where the instrument is pointed at the Martian nighttime sky with no surface sample present in its optical path. These measurements reveal weak Raman and fluorescence background spectral signatures as well as charged-coupled device pixels prone to erroneous intensity spikes separate from cosmic rays. We quantitatively describe these features and provide a subtraction procedure to remove the spectral background from surface spectra. By identifying and accounting for the SHERLOC Raman background features within the median Raman spectra of Martian target scans, we find that the undefined silicate spectral feature interpreted to be either amorphous silicate or plagioclase feldspar is ubiquitously found in every Mars target Raman scan collected through Sol 751.

Influence of 1,2,4-Tri-tert-butylcyclopentadienyl Ligand on the Reactivity of the Thorium Bipyridyl Metallocene [η5-1,2,4-(Me3C)3C5H2]2Th(bipy)].

The thorium bipyridyl metallocene (Cp3tBu)2Th(bipy) (1; Cp3tBu = η5-1,2,4-(Me3C)3C5H2) shows a rich reactivity toward a series of small molecules. For example, complex 1 may act as a synthon for the (Cp3tBu)2Th(II) fragment as illustrated by its reactivity toward to CuI, hydrazine derivative (PhNH)2, Ph2E2 (E = S, Se), elemental sulfur (S8) and selenium (Se), organic azides, CS2, and isothiocyanates. Moreover, in the presence of polar multiple bonds, such as those in ketones Ph2CO and (CH2)5CO, aldehydes p-MePhCHO and p-ClPhCHO, seleno-ketone (p-MeOPh)2CSe, nitriles PhCN, Ph2CHCN, C6H11CN, and p-(NC)2Ph, and benzoyl cyanide PhCOCN, C-C coupling occurs to furnish (Cp3tBu)2Th[(bipy)(Ph2CO)] (10), (Cp3tBu)2Th[(bipy)((CH2)5CO)] (11), (Cp3tBu)2Th[(bipy)(p-MePhCHO)] (12), (Cp3tBu)2Th[(bipy)(p-ClPhCHO)] (13), (Cp3tBu)2Th[(bipy){(p-MeOPh)2CSe}] (14), (Cp3tBu)2Th[(bipy)(PhCN)] (16), (Cp3tBu)2Th[(bipy)(Ph2CHCN)] (17), (Cp3tBu)2Th[(bipy)(C6H11CN)] (18), [(Cp3tBu)2Th]2{µ-(bipy)[p-Ph(CN)2](bipy)} (20), and (Cp3tBu)2Th{(bipy)[PhC(CN)O]} (21), respectively. Nevertheless, ketazine (PhCH═N)2 or benzyl nitrile PhCH2CN forms the dimeric complexes [(Cp3tBu)Th]2[µ-NC(Ph)(bipy)]2 (15) and (Cp3tBu)2Th[(bipy){C(═CHPh)NH}] (19), respectively. In contrast, C-N bond cleavage and C-C coupling processes occur upon addition of isonitriles Me3CNC and C6H11NC to 1 to yield the thorium isocyanido amido complexes (Cp3tBu)2Th[4-(Me3C)bipy](NC) (22) and (Cp3tBu)2Th[4-(C6H11)bipy](NC) (23), respectively. Furthermore, a single-electron transfer (SET) process ensues when 1 equiv of CuI is added to 1 to yield the Th(VI) bipyridyl iodide complex (Cp3tBu)2Th(I)(bipy) (3).

Temporal stability of the rumen microbiome and its longitudinal associations with performance traits in beef cattle.

The rumen microbiome is the focus of a growing body of research, mostly based on investigation of rumen fluid samples collected once from each animal. Exploring the temporal stability of rumen microbiome profiles is imperative, as it enables evaluating the reliability of findings obtained through single-timepoint sampling. We explored the temporal stability of rumen microbiomes considering taxonomic and functional aspects across the 7-month growing-finishing phase spanning 6 timepoints. We identified a temporally stable core microbiome, encompassing 515 microbial genera (e.g., Methanobacterium) and 417 microbial KEGG genes (e.g., K00856-adenosine kinase). The temporally stable core microbiome profiles collected from all timepoints were strongly associated with production traits with substantial economic and environmental impact (e.g., average daily gain, daily feed intake, and methane emissions); 515 microbial genera explained 45-83%, and 417 microbial genes explained 44-83% of their phenotypic variation. Microbiome profiles influenced by the bovine genome explained 54-87% of the genetic variation of bovine traits. Overall, our results provide evidence that the temporally stable core microbiome identified can accurately predict host performance traits at phenotypic and genetic level based on a single timepoint sample taken as early as 7 months prior to slaughter.

Tracking dynamic social impressions from multidimensional voice representation.

Recent research by Lavan et al. explores how individuals form complex impressions from voices. Using electroencephalography and behavioral measures, the study identifies distinct time courses for discerning traits, with early acoustic processing preceding higher-order perception. These findings shed light on the temporal dynamics of voice-based person perception and its neural underpinnings.

A 3D micro-computed tomography study comparing embryonic skeletal development in layer versus broiler strains of the domestic chicken.

Our objective was to analyze the effect of selection for divergent traits in the domestic chicken on embryonic skeletal development, which could affect postnatal bird welfare. Development was compared between the Ross 308 broiler line (fast growth and muscle mass accrual) and Novoponte layers (high laying rate and egg quality). In Study 1 (Initial Conditions), we characterized egg composition prior to incubation and identified the onset of embryonic skeletal mineralization in the 2 strains. In Study 2 (Developmental Dynamics), we used 3D X-ray tomographic imaging (µCT) on incubation days ED11, ED13, ED15 and ED17 to track skeletal maturation trajectories as a pseudo-time series. Results showed that Ross 308 embryos, which are heavier than Novoponte embryos, possess higher levels of yolk nutrients including phosphorus and calcium, but lower eggshell mineral content, than Novoponte embryos. Skeletal mineralization started synchronously in both strains, on ED11. The higher mineral ion content in the larger yolk of Ross 308 eggs compared to Novoponte eggs may partly explain why skeletal mineralization in Ross 308 embryos advances faster: using µCT, we show that the mandible and tibiotarsi in Ross 308 embryos are larger at ED11 and ED13 compared with Novoponte embryos. However, Novoponte embryos catch up from this initial lag in mineralization by ED15. The timing of the Novoponte acceleration coincides with the functional activation of the chorioallantoic membrane in releasing calcium from the inner eggshell. This correlates with a decrease in eggshell thickness from ED11 to ED17 in Novoponte eggs, which was not observed during Ross 308 incubation. To conclude, while some temporal discrepancies exist in early skeletal development between the embryos of Ross 308 and Novoponte strains, overall prenatal skeletal maturation seems to be robustly regulated. Despite selection for antagonist production traits, layer and broiler prehatch skeletal morphology ultimately synchronizes. Practically, since the extent of skeletal maturity equalizes between strains towards the end of incubation, refinements of farming practices, postnatal environment, and diet should be considered for improving domestic fowl welfare.

Novel multi-modal methodology to investigate placebo response in major depressive disorder.

The neurobiological mechanisms underlying the placebo phenomenon in patients with major depressive disorder (MDD) remain largely unknown. The progressive rise in rates of placebo responses within clinical trials over the past two decades may impede the detection of a true signal and thus present a major obstacle in new treatment development. Understanding the mechanisms would have several important implications, including (1) identifying biomarkers of placebo responders (thereby identifying those individuals who could benefit therapeutically from such interventions), (2) opening new avenues for manipulating such mechanisms to maximize symptom reduction, and (3) refining treatments with approaches that decrease (in clinical trials) or increase (in clinical practice) the placebo response. Here we investigated the research question: is the dopaminergic system one of the neurobiological underpinnings of the placebo response within MDD? Inspired by preclinical and clinical findings that have implicated dopamine in the occurrence, prediction, and expectation of reward, we hypothesized that dopaminergic activity in the mesolimbic system is a critical mediator of placebo response in MDD. To test this hypothesis, we designed a double-blind, placebo-controlled, sequential parallel comparison design clinical trial aimed at maximizing placebo antidepressant response. We integrated behavioral, imaging, and hemodynamic probes of mesocorticolimbic dopaminergic pathways within the context of manipulations of psychological constructs previously linked to placebo responses (e.g., expectation of improvement). The aim of this manuscript is to present the rationale of the study design and to demonstrate how a cross-modal methodology may be utilized to investigate the role of reward circuitry in placebo response in MDD.

Racial, ethnic, and sex bias in large language model opioid recommendations for pain management.

ABSTRACT: Understanding how large language model (LLM) recommendations vary with patient race/ethnicity provides insight into how LLMs may counter or compound bias in opioid prescription. Forty real-world patient cases were sourced from the MIMIC-IV Note dataset with chief complaints of abdominal pain, back pain, headache, or musculoskeletal pain and amended to include all combinations of race/ethnicity and sex. Large language models were instructed to provide a subjective pain rating and comprehensive pain management recommendation. Univariate analyses were performed to evaluate the association between racial/ethnic group or sex and the specified outcome measures-subjective pain rating, opioid name, order, and dosage recommendations-suggested by 2 LLMs (GPT-4 and Gemini). Four hundred eighty real-world patient cases were provided to each LLM, and responses included pharmacologic and nonpharmacologic interventions. Tramadol was the most recommended weak opioid in 55.4% of cases, while oxycodone was the most frequently recommended strong opioid in 33.2% of cases. Relative to GPT-4, Gemini was more likely to rate a patient's pain as "severe" (OR: 0.57 95% CI: [0.54, 0.60]; P < 0.001), recommend strong opioids (OR: 2.05 95% CI: [1.59, 2.66]; P < 0.001), and recommend opioids later (OR: 1.41 95% CI: [1.22, 1.62]; P < 0.001). Race/ethnicity and sex did not influence LLM recommendations. This study suggests that LLMs do not preferentially recommend opioid treatment for one group over another. Given that prior research shows race-based disparities in pain perception and treatment by healthcare providers, LLMs may offer physicians a helpful tool to guide their pain management and ensure equitable treatment across patient groups.

Diagnostic Accuracy of a Custom Large Language Model on Rare Pediatric Disease Case Reports.

Accurately diagnosing rare pediatric diseases frequently represent a clinical challenge due to their complex and unusual clinical presentations. Here, we explore the capabilities of three large language models (LLMs), GPT-4, Gemini Pro, and a custom-built LLM (GPT-4 integrated with the Human Phenotype Ontology [GPT-4 HPO]), by evaluating their diagnostic performance on 61 rare pediatric disease case reports. The performance of the LLMs were assessed for accuracy in identifying specific diagnoses, listing the correct diagnosis among a differential list, and broad disease categories. In addition, GPT-4 HPO was tested on 100 general pediatrics case reports previously assessed on other LLMs to further validate its performance. The results indicated that GPT-4 was able to predict the correct diagnosis with a diagnostic accuracy of 13.1%, whereas both GPT-4 HPO and Gemini Pro had diagnostic accuracies of 8.2%. Further, GPT-4 HPO showed an improved performance compared with the other two LLMs in identifying the correct diagnosis among its differential list and the broad disease category. Although these findings underscore the potential of LLMs for diagnostic support, particularly when enhanced with domain-specific ontologies, they also stress the need for further improvement prior to integration into clinical practice.

Integrated Assessment of OCT, Multimodal Imaging, and Cytokine Markers for Predicting Treatment Responses in Retinal Vein Occlusion Associated Macular Edema: A Comparative Review of Anti-VEGF and Steroid Therapies.

Retinal vein occlusion (RVO) is a significant cause of vision loss, characterized by the occlusion of retinal veins, leading to conditions such as central retinal vein occlusion (CRVO) and branch retinal vein occlusion (BRVO). Macular edema (ME), a prevalent consequence of RVO, is the primary cause of vision impairment in affected patients. Anti-VEGF agents have become the standard treatment, showing efficacy in improving visual acuity (VA) and reducing ME. However, a subset of patients exhibit a suboptimal response to anti-VEGF therapy, necessitating alternative treatments. Corticosteroids, which address inflammatory pathways implicated in ME, have shown promise, particularly in cases resistant to anti-VEGF. This review aims to identify biomarkers that predict treatment response to corticosteroids in RVO-associated ME, utilizing multimodal imaging and cytokine assessments. Baseline imaging, including SD-OCT and OCT-A, is essential for evaluating biomarkers like hyperreflective foci (HRF), serous retinal detachment (SRF), and central retinal thickness (CRT). Elevated cytokine levels, such as IL-6 and MCP-1, correlate with ME severity and poor anti-VEGF response. Early identification of these biomarkers can guide timely transitions to corticosteroid therapy, potentially enhancing treatment outcomes. The practical conclusion of this review is that integrating biomarker assessment into clinical practice enables personalized treatment decisions, allowing for earlier and more effective management of RVO-associated ME by transitioning patients to corticosteroid therapy when anti-VEGF agents are insufficient. Advanced diagnostics and machine learning may further refine personalized treatment strategies, improving the management of RVO-associated ME.

Free-breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model.

$\textbf{Purpose:}$ To develop a new method for free-breathing 3D extracellular volume (ECV) mapping of the whole heart at 3T. $\textbf{Methods:}$ A free-breathing 3D cardiac ECV mapping method was developed at 3T. T1 mapping was performed before and after contrast agent injection using a free-breathing ECG-gated inversion-recovery sequence with spoiled gradient echo readout. A linear tangent space alignment (LTSA) model-based method was used to reconstruct high-frame-rate dynamic images from (k,t)-space data sparsely sampled along a random stack-of-stars trajectory. Joint T1 and transmit B1 estimation was performed voxel-by-voxel for pre- and post-contrast T1 mapping. To account for the time-varying T1 after contrast agent injection, a linearly time-varying T1 model was introduced for post-contrast T1 mapping. ECV maps were generated by aligning pre- and post-contrast T1 maps through affine transformation. $\textbf{Results:}$ The feasibility of the proposed method was demonstrated using in vivo studies with six healthy volunteers at 3T. We obtained 3D ECV maps at a spatial resolution of 1.9$\times$1.9$\times$4.5 $mm^{3}$ and a FOV of 308$\times$308$\times$144 $mm^{3}$, with a scan time of 10.1$\pm$1.4 and 10.6$\pm$1.6 min before and after contrast agent injection, respectively. The ECV maps and the pre- and post-contrast T1 maps obtained by the proposed method were in good agreement with the 2D MOLLI method both qualitatively and quantitatively. $\textbf{Conclusion:}$ The proposed method allows for free-breathing 3D ECV mapping of the whole heart within a practically feasible imaging time. The estimated ECV values from the proposed method were comparable to those from the existing method. $\textbf{Keywords:}$ cardiac extracellular volume (ECV) mapping, cardiac T1 mapping, linear tangent space alignment (LTSA), manifold learning.