Negative Effects Research Articles

Inflation’s Reduction of the Real Minimum Wage and Unemployment in the USA: 1987 to 2021

<p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">Hundreds of articles have been written that include empirical estimates of the dis-employment effects of minimum wages; however, many of these articles find statistically insignificant effects, some find significant negative effects, and a few find significant positive effects. Most of these studies use multivariate analyses which can be criticized for omitting key variables. The omitted variables problem ruins all statistics and estimates. This paper uses reiterative truncated projected least squares (RTPLS), a solution to the omitted variables problem, to estimate the percentage increase in unemployment due to a one percent increase in the real minimum wage using monthly data for the 50 states of the USA from 1987 to 2021. RTPLS produces a separate elasticity for every observation where differences in these estimates are due to omitted variables. We argue that RTPLS solves most of the econometric problems that David Neumark identified in his keynote address at a minimum wage conference in Berlin in 2018. We find that the percentage change in the unemployment rate due to a one percent change in the minimum wage ranges between 1.156 and 3.389, that the elasticities for different states tend to move together over time, and that all these elasticities are statistically significant at a 95 percent confidence level.</span></p>

Exploring Attention Bias Mechanisms in Sub-Threshold Depression: ERP Insights into Biased Orientation and Disengagement.

Individuals with depression may have alterations in attention that begin at the sub-threshold stage. This study explored attention bias from the perspectives of early attention orientation and late attention disengagement in individuals with sub-threshold depression (SD) and healthy control (HC) individuals using a cue-target paradigm and event-related potentials (ERPs). The study enrolled 46 participants, comprising 23 males and 23 females, with 25 individuals in the SD group and 21 in the HC group, exceeding the calculated sample size requirement. The data were analyzed from two aspects. Behavioral data showed that SD individuals had difficulty in attention disengagement and that the time of attention transfer was delayed. Analysis of ERP data revealed that, regardless of the attributes of the emotional stimulus, the cue information promoted participants' response to the target stimulus. While SD individuals did show directional acceleration of attention to the emotional stimulus, no significant negative attention bias was observed. Taken together, these findings suggest that SD individuals do not show specific directional acceleration of attention to negative stimuli in the early stage of attention processing, although there may be attention avoidance.

An Evaluation of Cloud‐Precipitation Structures in Mixed‐Phase Stratocumuli Over the Southern Ocean in Kilometer‐Scale ICON Simulations During CAPRICORN

AbstractA persistent shortwave radiative bias of Southern Ocean (SO) clouds in climate models is strongly associated with incorrect cloud phase representation, which impacts precipitation. Measurements characterizing precipitation in low‐level mixed‐phase clouds, which frequently form over the SO, are rare, and our understanding of precipitation efficacy within these clouds remains limited. The simulated surface precipitation bias has an indirect effect on determining global climate sensitivity and a direct impact on the hydrological cycle. This study investigates the representation of low clouds, cloud variability, and precipitation statistics over the SO in real‐case Icosahedral Nonhydrostatic (ICON) simulations at the kilometer scale. The simulations are contrasted with 48 hr of continuous shipborne observations of open and closed‐cell stratocumuli, south of Tasmania. Our simulations show the significance of heavily rimed particle formation, their in‐cloud growth, and subcloud melting to capture the observed cloud‐precipitation vertical structure. In addition, supercooled drizzle formation impacts the vertical structure and precipitation statistics. ICON captures the observed intermittency of precipitation even at a standard vertical resolution of 200 m in the boundary layer but only captures the observed sparse distribution of intense precipitation (>1 mm hr−1) when the maximum vertical resolution is reduced to 100 m. However, the simulations of the 2‐day accumulated precipitation and the radiative effect are largely insensitive to the vertical resolution. The cloud reflectivity of the broken cloud deck is underestimated due to negative biases in cloud optical depth.

Coupled Thermal and Power Transport of Optical Waveguide Arrays: Photonic Wiedemann-Franz Law and Rectification Effect.

In isolated nonlinear optical waveguide arrays, simultaneous conservation of longitudinal momentum flow ("internal energy") and optical power ("particle number") of the optical modes enables study of coupled thermal and particle transport in the negative temperature regime. Based on exact numerical simulation and rationale from Landauer formalism, we predict generic photonic version of the Wiedemann-Franz law in such systems, with the Lorenz number L∝|T|^{-2}. This is rooted in the spectral decoupling of thermal and particle current, and their different temperature dependence. In addition, in asymmetric junctions, relaxation of the system toward equilibrium shows apparent asymmetry for positive and negative biases, indicating rectification behavior. This Letter illustrates the possibility of simulate nonequilibrium transport processes using optical networks, in parameter regimes difficult to reach in natural condensed matter or atomic gas systems. It also provides new insights in manipulating power and momentum flow of optical waves in artificial waveguide arrays.

High-density integration of uniform sub-22 nm silicon nanowires for transparent thin film transistors on glass

Ultrathin catalytical silicon nanowires (SiNWs), grown as orderly arrays upon glass substrates, are ideal 1D channels for the construction of high-performance field effect transistors for low-power and high aperture/transparency electronics. In this work, a rather uniform growth integration of high-density ultrathin SiNWs has been accomplished directly on glass substrate at 290 °C, via an in-plane solid–liquid-solid mechanism. The indium (In) catalyst thickness deposited on the dense guiding terrace steps was identified as a key parameter to suppress the size dispersion of the In droplets, and thus enable a uniform growth of ultrathin SiNWs with diameters down to DNW=21.8 ± 1.8 nm, a close-to-unity guided growth rate and an excellent transparency > 90 % in spectrum ranging from 350 nm to 950 nm. Based on a convenient dry plasma etching and low-temperature passivation procedure, high-performance SiNW transistors have been successfully fabricated upon a dense array of parallel SiNWs as channels with a narrow NW-to-NW spacing of 100 nm. A high current ratio Ion/Ioff > 107, a low off-state current down to 0.1 pA, a steep subthreshold swing of SS∼120 mV dec-1 and excellent positive and negative bias stabilities have been demonstrated, as well as SiNW-based inverter logics that achieve a gain of 14.6 V/V under a drive voltage of 2.25 V. These results highlight the potential of catalytic SiNWs to serve as advantageous 1D channels for large-area display or transparent electronics.

Do people recover from the impact of COVID-19 social isolation? Social connectivity and negative affective bias.

Do people recover from the impact of COVID-19 social isolation? Social connectivity and negative affective bias.

Significant systematic bias of alpha angles measured on MRI compared to various radiographic views in patients with femoroacetabular impingement syndrome.

The aim of this study was to assess the inter-rater reproducibility and inter-method comparability of hip alpha angle measurements on magnetic resonance imaging (MRI)/magnetic resonance arthrography (MRA) and plain radiographs in patients with femoroacetabular impingement syndrome (FAIS). A cross-sectional study of patients who were diagnosed with symptomatic FAIS underwent preoperative MRI/MRA with axial oblique and/or radial plane imagingand had preoperative radiographs with anterior-posterior (AP), 45° Dunnand 90° Dunn views. Alpha angle measurements were performed independently by two musculoskeletal radiologists. Inter-rater reproducibility and inter-method comparability between MRI/MRA images and radiographic views were assessed using the intraclass correlation coefficient (ICC) with 95% confidence interval (CI). Ninety-seven patients were included of whom 93 (95.8%) received axial oblique plane images and 54 (55.6%) had radial plane MRI/MRA images. Inter-rater reproducibility was excellent (ICC > 0.9) for all planes on MRI/MRA and radiographs. MRI/MRA axial oblique images had poor (ICC 0.39, 95% CI [0.09, 0.59]), moderate (ICC 0.57, 95% CI [0.18, 0.75])and moderate (ICC 0.64, 95% CI [0.20, 0.81]) comparability with AP, 45° Dunnand 90° Dunn, respectively. MRI/MRA radial plane images had equivocal (0 included in all CIs) comparability with AP (ICC 0.66), 45° Dunn (ICC 0.35)and 90° Dunn (ICC 0.14) radiographs. On average, alpha angle measurements were significantly higher with radial images and lower with axial oblique images, when compared to all radiographic views (p < 0.05), except axial oblique versus 45° Dunn views, where angles measured on axial oblique were significantly larger. Alpha angle measurements taken on axial oblique MRI/MRA images show moderate comparability to radiographic 45° Dunnand 90° Dunn views despite negative bias to measurements taken on radiographic AP and 45° Dunn view. Larger alpha angles were appreciated on MRI/MRA radial and axial oblique views compared to radiographic views supporting the inclusion of MRI/MRA alpha angle measurements to properly identify deformity. Level II.

Inpatient Management of Pain Episodes in Children with Sickle Cell Disease: A Review.

Sickle cell disease (SCD) is the most common hemoglobinopathy in the world. Sickle cell vaso-occlusive episodes (VOEs) are very painful acute events and the most common complication as well as reason for hospitalization. SCD pain is best evaluated holistically with a pain functional assessment to aid in focusing pain management on reducing pain in addition to improving function. Patients with SCD have long endured structural racism and negative implicit bias surrounding the management of pain. Thus, it is important to approach the management of inpatient pain systematically with the use of multi-modal medications and nonpharmacologic treatments. Furthermore, equitable pain management care can be better achieved with standardized pain plans for an entire system and individualized pain plans for patients who fall outside the scope of the standardized pain plans. In this article, we discuss the best practices to manage SCD VOEs during an inpatient hospitalization.

The impact of coupling a dynamic ocean in the Hurricane Analysis and Forecast System

Coupling a three-dimensional ocean circulation model to an atmospheric model can significantly improve forecasting of tropical cyclones (TCs). This is particularly true of forecasts for TC intensity (maximum sustained surface wind and minimum central pressure), but also for structure (e.g., surface wind-field sizes). This study seeks to explore the physical mechanisms by which a dynamic ocean influences TC evolution, using an operational TC model. The authors evaluated impacts of ocean-coupling on TC intensity and structure forecasts from NOAA’s Hurricane Analysis and Forecast System v1.0 B (HFSB), which became operational at the NOAA National Weather Service in 2023. The study compared existing HFSB coupled simulations with simulations using an identical model configuration in which the dynamic ocean coupling was replaced by a simple diurnally varying sea surface temperature model. The authors analyzed TCs of interest from the 2020–2022 Atlantic hurricane seasons, selecting forecast cycles with small coupled track-forecast errors for detailed analysis. The results show the link between the dynamic, coupled ocean response to TCs and coincident TC structural changes directly related to changing intensity and surface wind-field size. These results show the importance of coupling in forecasting slower-moving TCs and those with larger surface wind fields. However, there are unexpected instances where coupling impacts the near-TC atmospheric environment (e.g., mid-level moisture intrusion), ultimately affecting intensity forecasts. These results suggest that, even for more rapidly moving and smaller TCs, the influence of the ocean response to the wind field in the near-TC atmospheric environment is important for TC forecasting. The authors also examined cases where coupling degrades forecast performance. Statistical comparisons of coupled versus uncoupled HFSB further show an interesting tendency: high biases in peak surface winds for the uncoupled forecasts contrast with corresponding low biases, contrary to expectations, in coupled forecasts; the coupled forecasts also show a significant negative bias in the radii of 34 kt winds relative to National Hurricane Center best track estimates. By contrast, coupled forecasts show very small bias in minimum central pressure compared with a strong negative bias in uncoupled. Possible explanations for these discrepancies are discussed. The ultimate goal of this work will be to enable better evaluation and forecast improvement of TC models in future work.

Do consumers care about organic when consuming speciality bakery products or is it all about indulgence?

PurposeThis study explores the viability of incorporating more expensive organic wheat flour into speciality bakery products, which are of superior quality, thus justifying the higher cost. As consumers may be reluctant to purchase organic speciality baked goods due to unfavorable taste associations with organic foods, particularly those consumed as a treat or for pleasure, this study investigates the impact of providing taste assurances and origin information on consumer acceptance and WTP for organic speciality bakery products.Design/methodology/approachUsing data from an online survey of US consumers, random parameter logit models were estimated and willingness-to-pay (WTP) values were calculated.FindingsStudy results show that the use of more expensive organic flour is justified for speciality bakery products when favorable taste assurances are provided or for consumers who value organic foods. Freshness indictors were only important in the case of speciality breads, but not for other products. Finally, improving consumer awareness of organic labeling standards does not significantly impact their organic product preferences or taste perceptions.Practical implicationsThis analysis aims to identify the product information likely to increase the consumption of organic speciality bakery/pastry products and thus support the incorporation of organic wheat flour into these higher-value products.Originality/valueWhile previous choice experiment studies have extensively examined consumer preferences for organic products, few have evaluated the impact of providing taste and freshness indicators, particularly in the context of vice goods. This study examines the impact of providing taste and freshness indicators on consumer acceptance and WTP for various organic speciality bakery/pastry products in stated choice experiments, where consumers to not have the option to taste the product. Specifically, we examine if taste and freshness assurances reduce potential negative organic product taste biases.

Multi-View Graph Learning for Path-Level Aging-Aware Timing Prediction

As CMOS technology continues to scale down, the aging effect—known as negative bias temperature instability (NBTI)—has become increasingly prominent, gradually emerging as a key factor affecting device reliability. Accurate aging-aware static timing analysis (STA) at the early design phase is critical for establishing appropriate timing margins to ensure circuit reliability throughout the chip lifecycle. However, traditional aging-aware timing analysis methods, typically based on Simulation Program with Integrated Circuit Emphasis (SPICE) simulations or aging-aware timing libraries, struggle to balance prediction accuracy with computational cost. In this paper, we propose a multi-view graph learning framework for path-level aging-aware timing prediction, which combines the strengths of the spatial–temporal Transformer network (STTN) and graph attention network (GAT) models to extract the aging timing features of paths from both timing-sensitive and workload-sensitive perspectives. Experimental results demonstrate that our proposed framework achieves an average MAPE score of 3.96% and reduces the average MAPE by 5.8 times compared to FFNN and 2.2 times compared to PNA, while maintaining acceptable increases in processing time.

Bipolar topological spin diode and topological spin transistor in finite size quantum spin Hall insulators

Abstract The miniaturization and stability of electronic devices are becoming increasingly important today. We attempt to provide the theoretical support for designing spintronic devices by numerically investigating spin transport in finite size quantum spin Hall insulators (QSHI) under a perpendicular weak magnetic field. By modifying magnetic field strength, we find the gapped spin up and spin down bands are split to realize a half-metal phase which is a promising candidate for designing an efficient spin filter. Moreover, one of the two energy gaps becomes larger and the other smaller due to the weakened or enhanced coupling between two edge states. Here we propose and demonstrate the spin filter based on a finite size QSHI junction under a magnetic field and the polarity can be inverted by a bias voltage or magnetic field. Interestingly, we find a bipolar spin diode effect that only one spin channel is opened and the other spin channel is closed at positive bias, and the opposite spin electron can be transmitted with negative bias. Two spin filters in series can be a spin transistor, the on and off states can be controlled by spin polarization of one spin filter. We show that the topological spin transistor can be controlled by the gate voltage, and it survives in moderate disorder.

Prior Negative Experience Biases Activity of Medial Amygdala during Interstrain Social Engagement in Male Rats.

Social recognition is an essential part of social function and often promotes specific social behaviors based on prior experience. Social and defensive behaviors in particular often emerge with prior experiences of familiarity or novelty/stress, respectively. This is also commonly seen in rodents toward same-strain and interstrain conspecifics. Medial amygdala (MeA) activity guides social choice based on age and sex recognition and is sensitive to social experiences. However, little is known about whether the MeA exhibits differential responses based on strain or how this is impacted by experience. Social stress impacts posterior MeA (MeAp) function and can shift measures of social engagement. However, it is unclear how stress impacts MeAp activity and contributes to altered social behavior. The primary goal of this study in adult male Sprague Dawley rats was to determine whether prior stress experience with a different-strain (Long-Evans) rat impacts MeAp responses to same-strain and different-strain conspecifics in parallel with a change in behavior using in vivo fiber photometry. We found that MeAp activity was uniformly activated during social contact with a novel same-strain rat during a three-chamber social preference test following control handling but became biased toward a novel different-strain rat following social stress. Socially stressed rats also showed initially heightened social interaction with novel same-strain rats but showed social avoidance and fragmented social behavior with novel different-strain rats relative to controls. These results indicate that heightened MeAp activity may guide social responses to novel, threatening, rather than non-threatening, social stimuli after stress.

Validation of Cool-Season Snowfall Forecasts at a High-Elevation Site in Utah’s Little Cottonwood Canyon

Abstract Producing a quantitative snowfall forecast (QSF) typically requires a model quantitative precipitation forecast (QPF) and snow-to-liquid ratio (SLR) estimate. QPF and SLR can vary significantly in space and time over complex terrain, necessitating fine-scale or point-specific forecasts of each component. Little Cottonwood Canyon (LCC) in Utah’s Wasatch Range frequently experiences high-impact winter storms and avalanche closures that result in substantial transportation and economic disruptions, making it an excellent testbed for evaluating snowfall forecasts. In this study, we validate QPFs, SLR forecasts, and QSFs produced by or derived from the Global Forecast System (GFS) and High-Resolution Rapid Refresh (HRRR) using liquid precipitation equivalent (LPE) and snowfall observations collected during the 2019/20–2022/23 cool seasons at the Alta–Collins snow-study site (2945 m MSL) in upper LCC. The 12-h QPFs produced by the GFS and HRRR underpredict the total LPE during the four cool seasons by 33% and 29%, respectively, and underpredict 50th, 75th, and 90th percentile event frequencies. Current operational SLR methods exhibit mean absolute errors of 4.5–7.7. In contrast, a locally trained random forest algorithm reduces SLR mean absolute errors to 3.7. Despite the random forest producing more accurate SLR forecasts, QSFs derived from operational SLR methods produce higher critical success indices since they exhibit positive SLR biases that offset negative QPF biases. These results indicate an overall underprediction of LPE by operational models in upper LCC and illustrate the need to identify sources of QSF bias to enhance QSF performance. Significance Statement Winter storms in mountainous terrain can disrupt transportation and threaten life and property due to road snow and avalanche hazards. Snow-to-liquid ratio (SLR) is an important variable for snowfall and avalanche forecasts. Using high-quality historical snowfall observations and atmospheric analyses, we developed a machine learning technique for predicting SLR at a high mountain site in Utah’s Little Cottonwood Canyon that is prone to closure due to winter storms. This technique produces improved SLR forecasts for use by weather forecasters and snow-safety personnel. We also show that current operational models and SLR techniques underforecast liquid precipitation amounts and overforecast SLRs, respectively, which has implications for future model development.

Interplay among attention, appraisal, and memory bias in provisional posttraumatic stress disorder: Exploring the combined cognitive biases hypothesis.

Both theoretical and empirical studies suggest that negative cognitive biases significantly influence the onset and persistence of posttraumatic stress disorder (PTSD) symptoms. However, the interplay among these cognitive biases and their conjoint contribution to the long-term trajectory of posttraumatic stress symptoms remains underexplored. This study delves into the interplay among attention, appraisal, and memory biases within a provisional PTSD population and evaluates the predictive effects of two integrative models (weakest link, additive approach) on posttraumatic stress symptoms reported 2 months later. Sixty Chinese participants (Mage = 20.17, SDage = 2.11) with provisional PTSD undertook the scrambled sentences test (appraisal bias) with their eye movements recorded (attention bias) and then the free recall task (memory bias). Posttraumatic stress symptom was assessed at baseline and 2-month follow-up. Selective attention bias toward negative words was positively associated with the negative appraisal of scrambled sentences, which subsequently showed a strong association with negative memory bias. Regarding the progression of posttraumatic stress symptoms, the additive approach was found to be a more reliable predictor of self-reported posttraumatic stress symptoms at 2 months than the weak link approach. This study provides initial evidence supporting the combined cognitive biases hypothesis in provisional PTSD. It also underscores potential avenues to enhance cognitive bias modification techniques. Replication of these findings in broader clinical samples is essential. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A Novel Scalable and Reliable Control for DC Microgrids With Varying Number of Agents.

Existing scalable control methods mainly rely on a fixed block-diagonal structure for the Lyapunov matrix, potentially resulting in numerical infeasibility issues. To overcome this limitation, this article proposes a novel scalable and reliable control scheme for dc microgrids. Initially, a general model for dc microgrids is established to enhance reliability, considering scenarios involving loss of control effectiveness (LoCE) and offset faults. Subsequently, a structured free-weight matrix technique is introduced to mitigate negative coupling effects of power lines, and to address numerical infeasibility by avoiding the assumption about the Lyapunov matrix. Furthermore, the stability of the entire dc microgrid is guaranteed by checking local agent conditions, independently of power line couplings. Therefore, the proposed control scheme ensures plug-and-play scalability with varying number of agents. Finally, theoretical results are validated through numerical simulations using the MATLAB/SimPowerSystems toolbox.

Comparison of temperature, pressure and specific humidity derived from Sentinel-6 with ERA5 and radiosonde

The temperature, pressure and specific humidity data of Sentinel-6 (S6) products are compared with the ECMWF Reanalysis v5 (ERA5) and radio sounding in 2022. The overall STD of temperature, pressure and specific humidity for S6-ERA5 and S6-Radiosonde are 0.74 ℃, 0.45 hPa, 0.3 g/kg, 1.33 ℃, 0.51 hPa, 0.34 g/kg respectively. The study found that the consistency of these three atmospheric parameters between S6 and ERA5 is better than that between S6 and radiosonde. In the aspect of temporal characteristics, the specific humidity STD of S6-ERA5 decrease successively in summer, autumn, spring and winter. In the aspect of spatial characteristics, S6 has better retrieval ability of temperature values in the troposphere, but the maximum negative bias value of temperature between S6 and ERA5 is −1.57 ℃ at 41.7 km. The pressure bias values of S6 and ERA5 fluctuate greatly below the troposphere. In addition, the STD values of S6-ERA5 and S6-Radiosonde specific humidity data both show the decreasing characteristics in sequence from low to high latitudes.

Pivotal-Aware Principal Component Analysis.

A conventional principal component analysis (PCA) frequently suffers from the disturbance of outliers, and thus, spectra of extensions and variations of PCA have been developed. However, all the existing extensions of PCA derive from the same motivation, which aims to alleviate the negative effect of the occlusion. In this article, we design a novel collaborative-enhanced learning framework that aims to highlight the pivotal data points in contrast. As for the proposed framework, only a part of well-fitting samples are adaptively highlighted, which indicates more significance during training. Meanwhile, the framework can collaboratively reduce the disturbance of the polluted samples as well. In other words, two contrary mechanisms could work cooperatively under the proposed framework. Based on the proposed framework, we further develop a pivotal-aware PCA (PAPCA), which utilizes the framework to simultaneously augment positive samples and constrain negative ones by retaining the rotational invariance property. Accordingly, extensive experiments demonstrate that our model has superior performance compared with the existing methods that only focus on the negative samples.

Evaluation of Hydrazide-hydrazone and 4-thiazolidinone Derivatives of Etodolac as Potential Anticancer Agents in Leukemia Cells

Background: Nonsteroidal anti-inflammatory drugs (NSAIDs), which are commonly used for their anti-inflammatory and analgesic properties, have also been found to prevent cancer. (±)(R,S) Etodolac is an NSAID that belongs to the class of cyclooxygenase-2 inhibitors. Various derivatives of etodolac are synthesized to boost its anti-proliferative action and lessen its potential negative effects. In our earlier studies, some novel derivatives of etodolac exhibited stronger cytotoxic effects on prostate cell lines and had similar effects on leukemia cells in pre-screening experiments. Objective: Using the K562 leukemia cell line as a model, we sought to investigate the anti-cancer properties of a hydrazide-hydrozone derivative (SGK-205) and a 4-thiazolidinone derivative of etodolac (SGK-216). Materials and Methods: In the current investigation, SGK-205 and SGK-216 compounds were administered to K562 cells for 24 and 48 hours at concentrations of 10, 25, 50, 75 and 100 μM. Cell viability was assessed using the MTT test, and apoptosis by Annexin V-PI staining and mitochondrial membrane potential assays, together with mRNA expressions of apoptotic proteins. The levels of the proteins, HER2 and COX2, were also examined to evaluate COX2 inhibitory capacity. Results: In K562 cells, there was a definite dose-dependent response to SGK-205 and SGK-216 compounds. Results from MTT viability tests, together with mitochondrial membrane potential measurements and Annexin V-PI staining, revealed that SGK-216 and SGK-205 significantly outperformed etodolac in terms of their apoptotic and anti-proliferative activities. The concentration range of 10-20 M for both chemicals was sufficient to start biological responses. Apoptosis was also investigated through the expressions of pro- and anti-apoptotic proteins. Additionally, gene expression research demonstrated SGK-205 to be a beneficial substitute to etodolac in lowering COX-2 and human epidermal growth factor receptor-2 (HER2) expression. Conclusion: Our data indicated both derivatives to have higher anti-proliferative and apoptotic effects compared to etodolac. An overall assessment highlighting apoptotic induction potential, acceptable toxicity levels, a consistent dose-response relationship, and COX2 inhibitory actions, in particular, indicated SGK-205 as a viable novel therapeutic.

Negative global metacognitive biases are associated with depressive and posttraumatic stress disorder symptoms and improve with targeted or game-based cognitive training.

Metacognition is disrupted in several clinical populations. One aspect of metacognition, global metacognitive bias (difference between objective and self-reported abilities), has shown to be particularly relevant to clinical functioning. However, previous studies of global metacognitive biases in populations with elevated depressive/posttraumatic stress disorder (PTSD) symptoms have not measured objective and self-reported abilities relative to normative samples, limiting the quantification of biases. Additionally, few studies have examined whether cognitive interventions can improve metacognitive biases or how this relates to depressive/PTSD symptom severity. A total of 84 participants with mild traumatic brain injury (77% veterans) performed PTSD and depression assessments along with self-reported and objective measures of global cognition. Age-adjusted norm-based z scores were used for self-reported and objective cognition, and bias was calculated by subtracting objective minus self-report scores. Participants then received 13 weeks of targeted cognitive training or entertainment games training (both providing performance feedback). Participants were assessed at baseline, immediately posttraining, and 3 months posttraining. We found large negative metacognitive biases in those with clinically significant severity of depressive symptoms (z score difference = -1.77), PTSD symptoms (-1.47), and depressive + PTSD symptoms (-2.29). Metacognitive biases improved after both targeted and entertainment training and was associated with reductions in depressive/PTSD symptom severity (r = -.41/-.42, respectively), led by the entertainment training group (r = -.54/-.46, respectively). These findings show that clinically significant severity of depressive/PTSD symptoms is associated with substantial negative global metacognitive biases and preliminarily suggests that cognitive training may improve these biases and depressive/PTSD symptom severity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).