Clinical outcomes of repetitive transcranial magnetic stimulation (rTMS) for treatment of treatment-resistant depression (TRD) vary widely and there is no mood rating scale that is standard for assessing rTMS outcome. It remains unclear whether TMS is as efficacious in older adults with late-life depression (LLD) compared to younger adults with major depressive disorder (MDD). This study examined the effect of age on outcomes of rTMS treatment of adults with TRD. Self-report and observer mood ratings were measured weekly in 687 subjects ages 16–100 years undergoing rTMS treatment using the Inventory of Depressive Symptomatology 30-item Self-Report (IDS-SR), Patient Health Questionnaire 9-item (PHQ), Profile of Mood States 30-item, and Hamilton Depression Rating Scale 17-item (HDRS). All rating scales detected significant improvement with treatment; response and remission rates varied by scale but not by age (response/remission ≥ 60: 38%–57%/25%–33%; <60: 32%–49%/18%–25%). Proportional hazards models showed early improvement predicted later improvement across ages, though early improvements in PHQ and HDRS were more predictive of remission in those < 60 years (relative to those ≥ 60) and greater baseline IDS burden was more predictive of non-remission in those ≥ 60 years (relative to those < 60). These results indicate there is no significant effect of age on treatment outcomes in rTMS for TRD, though rating instruments may differ in assessment of symptom burden between younger and older adults during treatment.

Bulk and size-fractionated kaolinites from seven localities in Australia as well as the Clay Minerals Society Source Clays Georgia KGa-1 and KGa-2 have been studied by X-ray diffraction (XRD), laser scattering, and electron microscopy in order to understand the variation of particle characteristics across a range of environments and to correlate specific particle characteristics with intercalation behavior. All kaolinites have been intercalated with N-methyl (NMF) after pretreatment with hydrazine hydrate, and the relative efficiency of intercalation has been determined using XRD. Intercalate yields of kaolinite: NMF are consistently low for bulk samples that have a high proportion of small-sized particles (i.e., <0.5 µm) and for biphased kaolinites with a high percentage (>60%) of low-defect phase. In general, particle size appears to be a more significant controlling factor than defect distribution in determining the relative yield of kaolinite: NMF intercalate.

Kaolinite:NaCl intercalates with basal layer dimensions of 0.95 and 1.25 nm have been prepared by direct reaction of saturated aqueous NaCl solution with well-crystallized source clay KGa-1. The intercalates and their thermal decomposition products have been studied by XRD, solid-state 23Na, 27Al, and 29Si MAS NMR, and FTIR. Intercalate yield is enhanced by dry grinding of kaolinite with NaCl prior to intercalation. The layered structure survives dehydroxylation of the kaolinite at 500°–600°C and persists to above 800°C with a resultant tetrahedral aluminosilicate framework. Excess NaCl can be readily removed by rinsing with water, producing an XRD “amorphous” material. Upon heating at 900°C this material converts to a well-crystallized framework aluminosilicate closely related to low-carnegieite, NaAlSiO4, some 350°C below its stability field. Reaction mechanisms are discussed and structural models proposed for each of these novel materials.

Simple extended constant capacitance surface complexation models have been developed to represent the adsorption of polyaromatic dyes (9-aminoacridine, 3,6-diaminoacridine, azure A and safranin O) to kaolinite, and the competitive adsorption of the dyes with Cd. The formulation of the models was based on data from recent publications, including quantitative adsorption measurements over a range of conditions (varying pH and concentration), acid-base titrations and attenuated total reflectance-Fourier transform infrared spectroscopic data. In the models the dye molecules adsorb as aggregates of three or four, forming outer-sphere complexes with sites on the silica face of kaolinite. Both electrostatic and hydrophobic interactions are implicated in the adsorption processes. Despite their simplicity, the models fit a wide range of experimental data, thereby supporting the underlying hypothesis that the flat, hydrophobic, but slightly charged silica faces of kaolinite facilitate the aggregation and adsorption of the flat, aromatic, cationic dye molecules.

The strong adsorption to kaolinite of four polyaromatic, cationic dyes (9-aminoacridine, 3,6-diaminoacridine, azure A and safranin O), which adsorb much less to alumina or silica, was investigated by means of acid-base titrations, measurements of adsorption at varying pH and dye concentration, and by ATR-FTIR spectroscopy. The four dyes adsorb to kaolinite to similar extents, with little change over the pH range 3–10, but at higher pH (above the pKas of the dyes) the adsorption of 9-aminoacridine and 3,6-diaminoacridine decreases, that of azure A increases, and that of safranin O stays approximately constant. Although the dyes adsorb to kaolinite much more strongly than metal ions do, titration and spectroscopic data show that there is only limited chemical interaction between the adsorbed dyes and the kaolinite surface. The results indicate that electrostatic interaction between the dye molecules and the kaolinite surface is necessary for adsorption, but that hydrophobic interactions also contribute. It is proposed that the relatively hydrophobic silica faces of kaolinite, which carry low-density permanent negative charge, facilitate aggregation and adsorption of the positively charged, flat, aromatic dye molecules.

The competitive adsorption to kaolinite between Cd(II) and four polyaromatic dyes (9-aminoacridine, 3,6-diaminoacridine, azure A and safranin O) was studied in 5 mM KNO3 at 25°C. Under these conditions, Cd adsorbs to the silica face of kaolinite between about pH 4 and 6.5, but at higher pH, adsorbed Cd is progressively relocated to the crystal edges. In the presence of dye, less Cd adsorbed to kaolinite below pH 7. If sufficient dye was added to saturate the kaolinite surface, Cd adsorption was totally suppressed up to ∼pH 6. At higher pH, Cd followed the characteristic pattern for edge adsorption. In separate experiments 9-aminoacridine and azure A displaced pre-adsorbed Cd from kaolinite. The displacement curves were initially linear, with one Cd ion being displaced for every 13 dye molecules adsorbed at pH 5.5, and one Cd ion for every 35 dye molecules at pH 7.5. The interpretation of these results is that the dyes bind to kaolinite much more strongly than Cd(II) does, but only to the silica face.

The social cost of greenhouse gases is important in many regulatory impact analyses. However, calculations of the social cost of greenhouse gases are highly complex and periodically revisited. We offer seven recommendations to improve current estimates. These include recommendations to use both country-level and global measures of the social cost of greenhouse gases, to use country-specific values for monetizing climate damages, to represent uncertainties by reporting distributions instead of using only central values, and to conduct a temporal distributional analysis that shows the magnitudes of climate damages across generations. We also provide recommendations for the discount rates that should be used when estimating the social cost of greenhouse gases, and the appropriate discount rates for regulatory impact analyses that include the social cost of greenhouse gases.

We recently reported on the radio-frequency attenuation length of cold polar ice at Summit Station, Greenland, based on bi-static radar measurements of radio-frequency bedrock echo strengths taken during the summer of 2021. Those data also allow studies of (a) the relative contributions of coherent (such as discrete internal conducting layers with sub-centimeter transverse scale) vs incoherent (e.g. bulk volumetric) scattering, (b) the magnitude of internal layer reflection coefficients, (c) limits on signal propagation velocity asymmetries (‘birefringence’) and (d) limits on signal dispersion in-ice over a bandwidth of ~100 MHz. We find that (1) attenuation lengths approach 1 km in our band, (2) after averaging 10 000 echo triggers, reflected signals observable over the thermal floor (to depths of ~1500 m) are consistent with being entirely coherent, (3) internal layer reflectivities are ≈–60$\to$–70 dB, (4) birefringent effects for vertically propagating signals are smaller by an order of magnitude relative to South Pole and (5) within our experimental limits, glacial ice is non-dispersive over the frequency band relevant for neutrino detection experiments.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

OBJECTIVES/GOALS: Glioblastomas (GBMs) are heterogeneous, treatment-resistant tumors that are driven by populations of cancer stem cells (CSCs). In this study, we perform an epigenetic-focused functional genomics screen in GBM organoids and identify WDR5 as an essential epigenetic regulator in the SOX2-enriched, therapy resistant cancer stem cell niche. METHODS/STUDY POPULATION: Despite their importance for tumor growth, few molecular mechanisms critical for CSC population maintenance have been exploited for therapeutic development. We developed a spatially resolved loss-of-function screen in GBM patient-derived organoids to identify essential epigenetic regulators in the SOX2-enriched, therapy resistant niche. Our niche-specific screens identified WDR5, an H3K4 histone methyltransferase responsible for activating specific gene expression, as indispensable for GBM CSC growth and survival. RESULTS/ANTICIPATED RESULTS: In GBM CSC models, WDR5 inhibitors blocked WRAD complex assembly and reduced H3K4 trimethylation and expression of genes involved in CSC-relevant oncogenic pathways. H3K4me3 peaks lost with WDR5 inhibitor treatment occurred disproportionally on POU transcription factor motifs, required for stem cell maintenance and including the POU5F1(OCT4)::SOX2 motif. We incorporated a SOX2/OCT4 motif driven GFP reporter system into our CSC cell models and found that WDR5 inhibitor treatment resulted in dose-dependent silencing of stem cell reporter activity. Further, WDR5 inhibitor treatment altered the stem cell state, disrupting CSC in vitro growth and self-renewal as well as in vivo tumor growth. DISCUSSION/SIGNIFICANCE: Our results unveiled the role of WDR5 in maintaining the CSC state in GBM and provide a rationale for therapeutic development of WDR5 inhibitors for GBM and other advanced cancers. This conceptual and experimental framework can be applied to many cancers, and can unmask unique microenvironmental biology and rationally designed combination therapies.

When one or several classes are much less prevalent than another class (unbalanced data), class error rates and variable importances of the machine learning algorithm random forest can be biased, particularly when sample sizes are smaller, imbalance levels higher, and effect sizes of important variables smaller. Using simulated data varying in size, imbalance level, number of true variables, their effect sizes, and the strength of multicollinearity between covariates, we evaluated how eight versions of random forest ranked and selected true variables out of a large number of covariates despite class imbalance. The version that calculated variable importance based on the area under the curve (AUC) was least adversely affected by class imbalance. For the same number of true variables, effect sizes, and multicollinearity between covariates, the AUC variable importance ranked true variables still highly at the lower sample sizes and higher imbalance levels at which the other seven versions no longer achieved high ranks for true variables. Conversely, using the Hellinger distance to split trees or downsampling the majority class already ranked true variables lower and more variably at the larger sample sizes and lower imbalance levels at which the other algorithms still ranked true variables highly. In variable selection, a higher proportion of true variables were identified when covariates were ranked by AUC importances and the proportion increased further when the AUC was used as the criterion in forward variable selection. In three case studies, known species–habitat relationships and their spatial scales were identified despite unbalanced data.