搜索结果：Elon

The lambda N protein (λN) is an intrinsically unstructured protein functioning to mediate anti-termination transcription of lambda phage RNA during the infection of Escherichia coli (E. coli) host by interacting with the host's macromolecular transcription machinery. In E. coli host, λN is primarily turned over by the ATP-dependent protease Lon. While it has been demonstrated that Escherichia coli Lon (ELon) readily degrades purified λN in vitro, it is unclear how ELon degrades λN in the RNA anti-termination transcription complex. The N-dependent anti-termination transcription mechanism of Escherichia coli RNA polymerase (ERNAP) and the quality control functions of Lon have been extensively studied and reviewed in literature. By contrast, very little is known about Lon's function as a regulatory protease. Herein, we provide a survey of literature and newfound evidence showing how ELon regulates anti-termination RNA transcription assemblies by using λN as a substrate. Elucidating how a substrate interacts with the various components in the assembly (ERNAP versus ELon) can dictate whether anti-termination transcription or degradation occurs.

Feed algorithms are widely suspected to influence political attitudes. However, previous evidence from switching off the algorithm on Meta platforms found no political effects1. Here we present results from a 2023 field experiment on Elon Musk's platform X shedding light on this puzzle. We assigned active US-based users randomly to either an algorithmic or a chronological feed for 7 weeks, measuring political attitudes and online behaviour. Switching from a chronological to an algorithmic feed increased engagement and shifted political opinion towards more conservative positions, particularly regarding policy priorities, perceptions of criminal investigations into Donald Trump and views on the war in Ukraine. In contrast, switching from the algorithmic to the chronological feed had no comparable effects. Neither switching the algorithm on nor switching it off significantly affected affective polarization or self-reported partisanship. To investigate the mechanism, we analysed users' feed content and behaviour. We found that the algorithm promotes conservative content and demotes posts by traditional media. Exposure to algorithmic content leads users to follow conservative political activist accounts, which they continue to follow even after switching off the algorithm, helping explain the asymmetry in effects. These results suggest that initial exposure to X's algorithm has persistent effects on users' current political attitudes and account-following behaviour, even in the absence of a detectable effect on partisanship.

The aim of the study was to clarify how ethnic identity may impact poor mental health outcomes related to discrimination among Arab American adults in Southeast Michigan, USA. 286 respondents completed a health attitudes and behaviors survey. We used structural equation modeling with path and multi-group analyses to examine moderation effects of ethnic identity on the relationship between discrimination and depression and anxiety, and further moderation based on gender. Ethnic identity positively buffered against depression and anxiety associated with discrimination. In the subgroup analysis, ethnic identity was protective for female participants, though not male participants. These findings provide evidence for ethnic identity as a buffer between discrimination and poor mental health among Arab American adults. Mechanisms may include feelings of belonging and social support. The stronger effects for women may be due to their role of transmitting cultural and religious traditions. Future interventions should incorporate ethnic identity as a protective feature for mental health.

In the digital economy, social media has become a critical channel through which corporate executives communicate with investors, thereby influencing market expectations and price dynamics. This study examines how CEO social media behavior affects stock price volatility from an information-theoretic perspective combined with deep learning methods. Using Lei Jun (Xiaomi) and Elon Musk (Tesla) as contrasting cases, we analyze executive communication under transactional and transformational leadership styles. Emotional tone, thematic alignment, and diffusion intensity are extracted using BERT and LDA, and incorporated into a Long Short-Term Memory (LSTM) model to forecast short-term stock price movements. To interpret the mechanism behind the predictive results, we introduce a novel metric: Semantic Resonance Dissipation Entropy (SRE). Derived from Kullback-Leibler divergence, this indicator measures the informational friction between executive semantic output and market attention. The empirical analysis shows that incorporating these high-dimensional semantic features significantly improves volatility prediction. Moreover, leadership style is closely associated with distinct entropic regimes: Transactional leadership corresponds to relatively stable semantic patterns and low entropy, whereas transformational leadership is associated with higher entropy and greater semantic dispersion. Following Musk's acquisition of Twitter, the previously unstable information environment evolved into a persistent structural factor priced by the market. These findings suggest that the economic impact of digital leadership depends on limiting information dissipation to ensure signal clarity in financial markets.

Chromophobe renal cell carcinoma (ChRCC) is characterized by the accumulation of abnormal mitochondria, a high rate of mitochondrial DNA (mtDNA) mutations, and altered oxidative metabolism. There are no existing circulating biomarkers to distinguish metastatic ChRCC from clear cell renal cell carcinoma (ccRCC). High-throughput plasma proteomic profiling using the SomaScan platform was performed in 18 ChRCC (including 16 metastatic ChRCC) and 197 metastatic ccRCC patients. Data were harmonized to generate a unified 7K-protein matrix. Differential expression analysis was performed using limma (version 3.62.2). Of 7272 quantified human plasma proteins, 209 were differentially expressed between ChRCC and ccRCC. Upregulated proteins in ChRCC included essential β-oxidation enzymes such as ECH1 (enoyl-CoA hydratase 1) and ECI1 (enoyl-CoA delta-isomerase 1), suggesting increased long-chain fatty acid degradation. Creatine and energy-buffering pathways were also represented, with increased CKMT1A (Creatine Kinase, Mitochondrial 1A) in ChRCC. KIM-1 (Kidney Injury Molecule-1) and leptin were lower in ChRCC, consistent with the known upregulation of these proteins in ccRCC. Pathway enrichment analyses revealed an overrepresentation of mitochondrial protein degradation, fatty acid β-oxidation, and respiratory electron transport in ChRCC, suggesting that ChRCC sheds a unique mitochondrial signature into the peripheral circulation. A bootstrap-based LASSO logistic regression restricted to upregulated mitochondrial proteins in ChRCC vs. ccRCC consistently selected ECI1 and CKMT1A. The LASSO model achieved an AUROC of 0.964. Compared to ccRCC, the plasma proteome of metastatic ChRCC is dominated by mitochondrial metabolic enzymes, revealing a systemic metabolic phenotype strikingly aligned with the known histologic accumulation of abnormal mitochondria in ChRCC cells.

The current study examined suicide and violent crime data for 100 large municipalities in the United States. Suicide occurred more often when high school graduation rates were lower, but paradoxically, better income inequality rates predicted higher suicide, though this is consistent with international economic data. The frequency of mental distress predicted suicide as expected. Communities with higher proportions of black residents were more resilient to suicide, and why this is may be worth exploring in future research.

While data on the factors associated with the sexual and reproductive health of Black women is growing, few studies have applied a reproductive justice framework to their analyses, and few have assessed the role social realities play on reproductive decision-making. We analyzed data collected from a community-based participatory study, conducted between May 2019 and January 2020. The parent study aimed to get an understanding of the reproductive health experiences and concerns of Black women living in two southern states, Georgia and North Carolina. For this paper, we used a thematic analysis to identify themes from codes within the categories: healthcare utilization, pregnancy, and family life. We applied a reproductive justice framework lens to assess pregnancy intentions, pregnancy decision-making, and family planning agency across the full spectrum of family planning. In total, six focus group discussions, with 8-10 participants each, and 25 in-depth interviews were completed. Participants ranged in age, economic, and educational background. We found that social and cultural factors played an important role in pregnancy intentions and decision-making. Community and social norms worked to diminish positive feelings around Black pregnancy and non-childbearing, leading some to feel stigmatized and avoid pregnancy. Factors within the legal, economic, and health systems impacted family planning agency-limiting the ability to access desired family planning services such as abortion and infertility treatments. Participants offered strategies they believed could help counter the impact of these factors. Our findings highlight that Black women's pregnancy intentions, pregnancy decision-making, and family planning agency are influenced by their social realities.

Source apportionment is a method that reconstructs sources of pollution from monitored values. The identification of these sources is important to develop interventions and other strategies to improve environmental quality. This study aimed to identify and quantify potential sources that contribute to fine particulate matter (PM2.5) personal exposures in a cohort of pregnant women participating in a fuel-cooking intervention trial in Guatemala. We estimated the PM2.5 and black carbon (BC) concentrations from 629 polytetrafluoroethylene (PTFE) filter samples using gravimetric and transmittance analyses, and we analyzed inorganic elements using energy dispersive X-ray fluorescence (ED-XRF). The filters correspond to personal exposure samples collected with the Enhanced Children's MicroPEM™ (ECM) from pregnant women who cook using biomass or liquefied petroleum gas (LPG) fuels within the Household Air Pollution Intervention Network (HAPIN) randomized-controlled trial in rural Jalapa, Guatemala. We used the U.S. Environmental Protection Agency's (EPA) Positive Matrix Factorization (PMF) model to identify the potential sources. A four-factor source apportionment model was derived from PMF. The potential sources and their relative contributions to PM2.5 mass were identified as: biomass burning ( ~ 69.6%), fossil fuels (22%), crustal, and other soil ( ~ 4% each). When categorizing our samples by study group, baseline (155 µg/m3; 95% CI: 129.7, 180.2) and post-intervention control (127.2 µg/m3; 95% CI: 114.7, 139.7) samples had the highest amount of PM2.5 mass (49.7% and 40.7%, respectively) compared to 9.6% (29.9 µg/m3; 95% CI: 27.2, 32.7) from intervention samples. We identified biomass burning, fossil fuel burning, crustal and other soil as sources of PM2.5 pollution in rural Jalapa, Guatemala. These findings pave the road for future source apportionment studies in this region and highlight the importance of source characterization to implement interventions to reduce PM2.5 emissions. Sources and average PM2.5 mass contribution in µg/m3 (%) from rural Jalapa, Guatemala. We identified four potential sources of PM2.5 in rural Jalapa, Guatemala, based on personal exposure samples from pregnant women participating in the HAPIN trial. Biomass and fossil fuel burning are the sources with the highest contributions, followed by crustal and other soil. The findings of this study highlight the potential to prioritize emissions reduction efforts in rural Guatemala through the implementation of specific interventions based on the derived sources of pollution.

Mammalian reoviruses are promising oncolytic agents, but most preclinical and clinical work has focused on the type 3 Dearing (T3D) prototype, potentially underestimating the therapeutic relevance of broader reovirus genetic diversity. Because reoviruses possess a segmented double-stranded RNA genome, reassortment can generate progeny with novel combinations of traits influencing infectivity, replication, and cytotoxicity. Here, we evaluated a panel of previously generated T1L × T3D reassortants and recombinant reoviruses across three epithelial tumor models: A549 lung adenocarcinoma and the oral squamous carcinoma cell lines OECM-1 and CAL-27. Across all three models, the tested viruses displayed marked cell line-dependent heterogeneity in both cytotoxicity and infectivity. Several reassortants reduced viability more effectively than the parental T1L and T3D strains in one or more cell lines, and DB62 emerged as the most broadly active candidate across the panel. Infectivity and cytotoxicity overlapped only partially, indicating that efficient infection alone does not fully predict oncolytic potency. Together, these findings show that reassortment can generate reoviruses with enhanced or selective activity across epithelial tumor contexts and support future studies examining how segment-dependent differences in interferon antagonism, entry, and cell death shape oncolytic potency.

Obeticholic acid (OCA) has been evaluated in patients with primary biliary cholangitis (PBC) with inadequate response or intolerance to ursodeoxycholic acid (UDCA) in the 12-month, double-blind, phase 3 POISE trial. A 3-year interim analysis of the open-label extension (OLE) demonstrated a favourable safety profile with sustained improvements in liver biochemistries. To present the final long-term safety and efficacy data from the 5-year POISE OLE. All patients who entered the OLE (N = 193) were started on OCA 5 mg daily for a minimum of 3 months, after which the dose could be increased. Safety and efficacy were evaluated in the overall OLE population. Additional analyses censored data points following OCA titration > 10 mg to align with the prescribing label. POISE was terminated after it was determined that the OLE had achieved its study objectives of sustained efficacy with no unexpected safety findings. With censoring of data points following OCA titration to > 10 mg, the most common treatment-emergent adverse event (TEAE) was pruritus (70%); serious hepatic-related TEAEs were reported in five patients (3%). The serious hepatic-related TEAEs and deaths (n = 2, 1%) were assessed by the Investigators as unrelated to OCA. Liver biochemistries improved throughout the OLE; the response rate for the POISE primary endpoint was 63% at Month 72. Liver stiffness, as measured by transient elastography, was stable over the study duration. Findings from the POISE OLE support the safety and efficacy profile of long-term OCA treatment for patients with PBC with inadequate response or intolerance to UDCA (NCT01473524). Phase 3 study of obeticholic acid in patients with primary biliary cirrhosis (POISE) ClinicalTrials.gov identifier: NCT01473524.

BACKGROUND: Recurrent weight gain (RWG) and Suboptimal Clinical Response (SCR) after primary metabolic and bariatric surgery (MBS) are common, often necessitating revisional procedures. Single-anastomosis duodeno-ileal bypass with sleeve gastrectomy (SADI-S) has emerged as a promising conversion option. METHODS: We retrospectively reviewed patients who underwent laparoscopic conversion to SADI-S for RWG/SCR between 2018 and 2024. Eligible patients had prior MBS after meeting national guidelines. Data included demographics, weight-loss outcomes, complications and nutritional/metabolic markers. The primary outcomes were percent of total weight loss (%TWL) and excess weight loss (%EWL). Long-term complications and need for revisional surgery were also assessed. RESULTS: Sixty-nine patients (mean age 42.7 ± 9.8 years; 66.7% female) were included. Most (65.2%) were converted from sleeve gastrectomy. Mean follow-up was 2.2 ± 1.4 years. Mean %TWL was 36.4%, 37.8%, and 34.5% at 1, 3, and 5 years, respectively, and %EWL exceeded 90% at all time points. Major complications (Clavien-Dindo ≥ 3b) occurred in 5.8% within 90 days, with 4 reoperations in the perioperative period. No conversional surgeries were required during the follow-up period. CONCLUSIONS: Conversion to SADI-S is a safe and effective option for RWG/SCR following primary MBS, yielding durable weight loss and metabolic improvement with low complication rates. These findings support its use as a conversion strategy, warranting further prospective validation.

Background: The intestinal mucus layer is comprised of heavily glycosylated mucins, including mucin 2 (MUC2), that serve as a nutrient source for certain bacterial members of the gut microbiota. Only a subset of gut commensals encode the glycoside hydrolases required to degrade mucin glycans. However, mucin-degrading microbes can release glycans and generate compounds that can cross-fed non-mucin degrading microbes, creating complex microbial networks. While pairwise studies have shown that mucin degradation drives cross-feeding and metabolite exchange, the broader impact of mucins on community structure and metabolic output remains poorly understood. Objective: In this study, we sought to identify how a defined microbial consortium of human commensals with varied mucin-degrading capacities responds to MUC2 to shape community composition and metabolic output. Methods: A defined consortium of human gut commensals with varied mucin-degrading capacities was cultivated in anaerobic bioreactors in the presence or absence of porcine MUC2. Community composition was assessed, and extracellular metabolites were quantified using targeted and untargeted metabolomic profiling. Results: MUC2 supplementation significantly altered community structure, promoting the expansion of Akkermansia muciniphila while reducing Prevotella. MUC2 also reshaped microbial metabolism, decreasing acetate levels while increasing propionate, butyrate, and formate. In addition, MUC2 supplementation altered amino acid utilization and vitamin metabolism and reduced several neuroactive compounds, including glutamate, γ-aminobutyric acid (GABA), and anthranilic acid, while increasing tryptamine levels. Conclusion: These findings demonstrate that mucins exert broad effects on microbial community structure and metabolic output. Collectively, this work highlights the central role of bacterial cross-feeding in shaping gut ecosystem function.

Ashwagandha (Withania somnifera L.Dunal) is an adaptogenic herb known to reduce stress and enhance well-being in adults. This randomized, double-blind, placebo controlled, parallel-group trial evaluated the efficacy and safety of standardized Ashwagandha root extract (ARE) in children with parent-reported concerns related to attention, concentration, or memory. Eight-five healthy children aged 6-12 years were randomized to receive ARE gummies (n = 42; 150 mg twice daily) or identical placebo gummies (n = 43) for 8 weeks. Primary outcomes included attention, memory, and executive function assessed using the Computerized Mental Performance Assessment System (COMPASS). Secondary outcomes included overall functioning and well-being assessed using the Strengths and Difficulties Questionnaire (SDQ), Behavior Rating Inventory of Executive Function, Second Edition (BRIEF2 Parent version), Sleep Disturbance Scale for Children (SDSC), and Patient-Reported Outcomes Measurement Information System - Fatigue Scale. Safety was evaluated based on self-reported adverse events. Among 73 participants who completed the study (ARE, n = 39; placebo, n = 34), ARE supplementation significantly improved speed of information processing (p = 0.040). Improvements were also observed in delayed word recall (p = 0.038, d = 0.59), Stroop task accuracy (p = 0.021, d = 0.61), Corsi block span (p = 0.013, d = 0.66), and choice reaction time accuracy (p = 0.005, d = 0.75). Additionally, SDSC scores improved, indicating better parent-reported sleep quality (p = 0.035). No significant adverse events were reported. These findings suggest that an eight-week supplementation with ARE is well tolerated and may enhance cognitive performance and sleep quality in children. The trial was prospectively registered with the Clinical Trials Registry of India (CTRI/2021/10/037126; dated 06/10/2021; CTRI) and the Australian and New Zealand Clinical Trials Registry (Reg. No.: ACTRN12621000656831; ANZCTR-Registration).

暂无摘要（点击查看详情）

Adopted adults may be at a higher risk of developing complex trauma symptoms due to early attachment ruptures caused by separating from caregivers and other potential early adverse childhood experiences. Critical consciousness, or interrogating systems of oppression, may mitigate trauma symptoms of powerlessness for marginalized groups by inspiring purposeful collective action. This study explored the association between critical consciousness (critical reflection, motivation, and action) and complex trauma symptoms from a national cross-sectional online survey of a racially diverse sample (N = 464) of adopted adults in the United States. The final regression model, which included demographic variables, adoption characteristics, traumatic experiences, and critical consciousness, explained 34.9% of complex trauma symptoms among adult adoptees in the sample, R&#xb2; = .349, F(3, 355) = 5.630, p < .001, and critical consciousness accounted for 3.1% of the unique variance. Critical motivation, or a belief in one's ability to contribute to social change, was the only variable associated with lower complex trauma symptoms (&#x3b2; = -0.15, p = .019). Critical reflection, or a realization of societal inequality (&#x3b2; = .13, p = .037) and critical action, or political activism (&#x3b2; = .14, p = .004), were associated with higher trauma symptoms. Exploratory findings suggest critical consciousness of systemic oppression may be an important and complex factor to consider when addressing complex trauma symptoms among racially diverse clients who grew up outside of the "traditional" standard North American family (i.e., heterosexual, legally married couple with biological children). Findings suggest that aspects of critical consciousness may cause distress, but other aspects, such as critical motivation, may address feelings of powerlessness and be associated with lower complex trauma symptoms. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Pregnancy and postpartum represent identity-salient biopsychosocial transitions for athlete-mothers navigating return-to-activity within digitally mediated performance environments. Wearable technologies are increasingly embedded in training and recovery decision-making; however, these systems are typically calibrated on non-pregnant populations and may assign deficit-based meaning to normative perinatal physiological adaptation. This clinical commentary highlights the potential for wearable devices to function not merely as measurement tools but as interpretive systems that shape identity appraisal and mental health during the perinatal transition. We propose a recalibrated framework for wearable design that integrates perinatal-specific physiological reference ranges, contextual caregiving inputs, validated mental health screening tools, and psychologically informed feedback framing. We emphasize the need for longitudinal research to establish normative physiological trajectories across pregnancy and postpartum, particularly among athlete-mothers. By aligning algorithmic interpretation with contemporary biopsychosocial science, wearable technologies can evolve from performance-optimization tools to identity-sensitive, clinically informed adjuncts that support adaptive recovery among athlete-mothers.

Serum and plasma are widely used in proteomic biomarker discovery, but differences between their proteomes have hindered the integration of data from the two specimen types. Here, we describe a computational approach for bridging between serum and plasma proteomic measurements derived from the aptamer-based SomaScan assay. We aimed to enable cross-specimen data utilization in the context of the PROphet model designed to predict immunotherapy outcomes based on 388 plasma proteomic biomarkers. Proteomic profiling of 7289 proteins was performed on 177 matched serum-plasma sample pairs from cancer patients across three distinct cohorts. Remarkably, 91.6% of the proteins showed correlation (p-value < 0.05) between serum and plasma protein levels, highlighting the feasibility of serum-plasma bridging. Linear scaling factors derived from matched serum-plasma sample pairs were consistent across the three cohorts, suggesting that the scaling factors are generalizable. Notably, the PROphet model maintained its predictive power when applied to scaled serum proteomic measurements. Specifically, clinical benefit predictions and survival stratification based on scaled serum proteomic measurements were similar to those based on plasma proteomic measurements. Our study demonstrates the feasibility of generalizing plasma-based predictors to serum samples through appropriate bridging strategies, paving the way for integrating serum and plasma datasets.

This research addresses an often-overlooked opportunity for police reform: the predictive value of prehire misbehavior data for reducing posthire police misconduct. While most reform efforts focus on officers' actions after they are hired, our findings highlight the impact of rigorous screening before hire. We examined how specific prior employment and nonwork misbehaviors related to general occupational instability, trouble in previous law enforcement roles, prior temper problems and violence, and irresponsible behaviors predicted future misconduct among 6,075 police officers tracked over 5 years. Notably, some prehire behaviors significantly elevated risks of citizen complaints and misconduct-related lawsuits, with hazard ratios up to 14.59. Contrary to common assumptions, candidates with prior law enforcement experience showed increased liability, including excessive use of force, suggesting that this background does not inherently reduce misconduct risk. After identifying the strongest predictors of police misconduct, we also examined their relation to termination for cause and assessed how agency decision makers respond differently to prehire versus posthire misbehaviors. By integrating findings on the predictive value of specific prehire misbehaviors, we offer targeted, evidence-based guidance and actionable recommendations for police agencies and policymakers. This work provides a scientifically grounded foundation for effective and consistent police screening decisions, offering a framework for establishing long-overdue national police hiring standards. (PsycInfo Database Record (c) 2026 APA, all rights reserved).