James T.

Abstract Phragmites australis is exhibiting extensive dieback in the Lower Mississippi River Delta (MRD). We explored the potential for

Over the past century, antibiotic usage has skyrocketed in the treatment of critically ill patients. There have been increasing calls to establish guidelines for appropriate treatment and durations of antibiosis. Antibiotic treatment, even when appropriately tailored to the patient and infection, is not without cost. Short term risks—hepatic/renal dysfunction, intermediate effects—concomitant superinfections, and long-term risks—potentiating antimicrobial resistance (AMR), are all possible consequences of antimicrobial administration. These risks are increased by longer periods of treatment and unnecessarily broad treatment courses. Recently, the literature has focused on multiple strategies to determine the appropriate duration of antimicrobial therapy. Further, there is a clinical shift to multi-modal approaches to determine the most suitable timepoint at which to end an antibiotic course. An approach utilising biomarker assays and an inter-disciplinary team of pharmacists, nurses, physicians, and microbiologists appears to be the way forward to develop sound clinical decision-making surrounding antibiotic treatment.

Advanced instruments and methods need to be developed now to create a technical basis to support the negotiation of future nuclear arms control treaties. One new capability that is anticipated is the ability to confirm either the declared presence or declared absence of high explosive (HE) material in the presence of special nuclear material (SNM). Towards this goal, Passive HE Neutron Inspection (PHENIX) has been developed and demonstrated as a method for confirming the presence or absence of HE in the presence of plutonium. The method exploits the inherent presence of neutrons associated with the decay of plutonium as an internal probe source for performing prompt gamma-ray neutron activation analysis (PGNAA), searching for the presence of HE as revealed by the emission of characteristic gamma rays following neutron absorption in hydrogen and nitrogen which are building blocks of present-day, military-grade HE. Tests using stoichiometrically-correct hemishells of mock HE with plutonium show that a system can be expected to positively confirm the presence or absence of these signatures, supporting determination of HE presence or absence with Pu, in a few hours. To protect other potentially sensitive gamma-ray signatures from a treaty accountable item, an analog information barrier has been conceptualized and tested which physically prevents the collection of gamma-ray spectral data outside of user selected energy windows strategically chosen to view only narrow spectral regions corresponding to the hydrogen (2223.2 keV) and nitrogen (9807.2 keV, 10,318.2 keV, and 10,829.2 keV) PGNAA signatures.

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Fear conditioning evokes a physiologic release of glucocorticoids that assists learning. As a cochaperone in the glucocorticoid receptor complex, FKBP51 modulates stress-induced glucocorticoid signaling and may influence conditioned fear responses. This study combines molecular and behavioral approaches to examine whether locally reducing FKBP51 expression in the ventral hippocampus is sufficient to affect fear-related behaviors. We hypothesized that reducing FKBP51 expression in the VH would increase glucocorticoid signaling to alter auditory fear conditioning. Adult male rats were injected with an adeno-associated virus (AAV) vector expressing short hairpin – RNAs (shRNA) targeting FKBP5 into the ventral hippocampus to reduce FKBP5 levels or a control AAV. Infusion of FKBP5-shRNA into the ventral hippocampus decreased auditory fear acquisition and recall. Although animals injected with FKBP5-shRNA showed less freezing during extinction recall, the difference was due to a reduced fear recall rather than improved extinction. Reducing ventral hippocampus FKBP51 did not affect exploratory behavior in either the open field test or the elevated zero maze test but did increase passive behavior in the forced swim test, suggesting that the reduction in auditory fear recall was not due to more active responses to acute stress. Furthermore, lower ventral hippocampus FKBP51 levels did not alter corticosterone release in response to restraint stress, suggesting that the reduced fear recall was not due to lower corticosterone release. Our findings suggest FKBP51 in the ventral hippocampus plays a selective role in modulating fear-learning processes and passive behavioral responses to acute stress rather than hypothalamic-pituitary-adrenal axis reactivity or exploratory responses.

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease which can present with mixed organ involvement. Kidney involvement in lupus nephritis (LN) is a severe complication and major cause of mortality in SLE patients, second only to cardiovascular disease. While mouse models have helped uncover some molecular pathways involved in SLE/LN, we need a better understanding of the connection of these pathways and the immune cells involved in disease pathogenesis to develop new and effective therapies. Furthermore, models used for studying SLE/LN in mice have a heterogeneous immune response and may not always represent disease manifestations observed in patients. Identifying models that have shared pathways with human disease would allow for better translation for developing effective SLE/LN therapies. The molecular pathways of five different SLE/LN models (MRL/lpr, poly (I:C)-induced, interferon-α-induced, bm12 GvHD, and spontaneous NZB/W F1) were compared to characterize the immune response in mouse kidneys. These models demonstrated varied magnitudes in immune responses and proportions of innate vs. adaptive cell involvement. These findings were compared to human molecular pathways and cell types from public databases, including the Accelerating Medicine Partnership–Systemic Lupus Erythematosus Program (AMP-SLE), to help corelate mechanisms involved in mouse models to human disease.

Background/Objective: SeptiCyte RAPID is a transcriptional host response assay that discriminates between sepsis and non-infectious systemic inflammation (SIRS) with a one-hour turnaround time. The overall performance of this test in a cohort of 419 patients has recently been described [Balk et al., J Clin Med 2024, 13, 1194]. In this study, we present the results from a detailed stratification analysis in which SeptiCyte RAPID performance was evaluated in the same cohort across patient groups and subgroups encompassing different demographics, comorbidities and disease, sources and types of pathogens, interventional treatments, and clinically defined phenotypes. The aims were to identify variables that might affect the ability of SeptiCyte RAPID to discriminate between sepsis and SIRS and to determine if any patient subgroups appeared to present a diagnostic challenge for the test. Methods: (1) Subgroup analysis, with subgroups defined by individual demographic or clinical variables, using conventional statistical comparison tests. (2) Principal component analysis and k-means clustering analysis to investigate phenotypic subgroups defined by unique combinations of demographic and clinical variables. Results: No significant differences in SeptiCyte RAPID performance were observed between most groups and subgroups. One notable exception involved an enhanced SeptiCyte RAPID performance for a phenotypic subgroup defined by a combination of clinical variables suggesting a septic shock response. Conclusions: We conclude that for this patient cohort, SeptiCyte RAPID performance was largely unaffected by key variables associated with heterogeneity in patients suspected of sepsis.

In the future, large language models (LLMs) may enhance the delivery of healthcare, but there are risks of misuse. These methods may be trained to allocate resources via unjust criteria involving multimodal data - financial transactions, internet activity, social behaviors, and healthcare information. This study shows that LLMs may be biased in favor of collective/systemic benefit over the protection of individual rights and could facilitate AI-driven social credit systems.

Abstract Ecological character displacement, whereby shifts in resource use in the presence of competing species leads to adaptive evolutionary

Rich evidence of the potential co-benefits and trade-offs of natural climate solutions is available but remains poorly understood. Assessing the literature with machine learning methods, this study maps and analyses the growing evidence of trade-offs in natural climate solutions globally.