耶鲁大学医学院

Within cells, across diverse organisms, macromolecular condensation enables spatial and temporal organization of biochemical reactions by organizing proteins and nucleic acids into compositionally distinct membraneless biomolecular condensates. In the gut bacterium Bacteroides thetaiotaomicron, condensate formation by the transcription termination factor Rho (BtRho) increases its termination activity and promotes B. thetaiotaomicron fitness in the mammalian gut. Here, we elucidate the molecular mechanism governing carbon starvation-induced BtRho phase separation. We establish that short, specific amino acid sequences within BtRho's intrinsically disordered region (IDR) control BtRho condensation via complex coacervation. The identified sequences participate in RNA and intra-IDR regulatory interactions that drive condensate formation in vitro and in vivo. We also report that the signaling molecule ppGpp is essential for BtRho phase separation in vivo, binds to purified BtRho in an IDR-dependent manner, and promotes RNA-dependent BtRho condensation in vitro. Our findings demonstrate how specific short sequences within an IDR dictate phase separation in response to nutritional cues.

Cocaine use disorder (CUD) remains a major public health problem, particularly among individuals receiving medications for opioid use disorder (mOUD), where ongoing cocaine use is associated with poorer treatment outcomes and elevated overdose risk. N-acetylcysteine (NAC) is a promising adjunctive candidate that reduces cocaine-seeking in preclinical models and shows mixed efficacy in humans, but its functional neural mechanisms in individuals with CUD—especially within mOUD settings—remain poorly understood. The present study uses functional magnetic resonance imaging (fMRI) to determine whether short-term NAC administration modulates brain activity in regions associated with inhibitory control and affective processing in people with CUD receiving medications for opioid use disorder (mOUD). In this double-blind, placebo-controlled, crossover study, 21 individuals with CUD enrolled in an mOUD program were randomized to receive NAC or placebo for 7 days and participated in fMRI scanning on the 7th day of this period. Following a fourteen-day washout period, participants were crossed over to receive the other condition for another 7-day period. Participants received a second fMRI scan on the 7th day of this period. Participants completed a go/no-go (GNG) and emotion-regulation task (ERT) during each scan. Compared to placebo, active NAC did not significantly affect brain activity during either the GNG task or the ERT. Overall, short-term NAC did not robustly modulate neural circuits supporting inhibitory control or emotion regulation in individuals with comorbid CUD and OUD receiving mOUD, consistent with prior trials reporting limited efficacy of NAC for CUD. These findings underscore the value of incorporating neuroimaging into early-phase treatment trials to evaluate target engagement in humans. ClinicalTrials.gov identifier: NCT02994875, registered 2016–12-16.

The high prevalence of depression and limitations of current antidepressants necessitate alternative therapies. Electroacupuncture (EA) shows promise, but its mechanisms remain unclear. Hippocampal impairment in depression involves neuroinflammation linked to defective autophagy. This study investigated whether EA alleviates depressive-like behaviors by enhancing autophagy via the VEGF/AKT1/ERK pathway to attenuate hippocampal neuroinflammation. Bioinformatic analysis of the GEO dataset GSE53987 was performed to identify autophagy- and neuroinflammation-related differentially expressed genes in depression. A chronic unpredictable mild stress (CUMS) rat model was used for validation. Rats were divided into control, CUMS, EA, EA + VEGFR2 inhibitor (SU5416) (EA+SU5416), EA + 3-methyladenine (3-MA), and FXL (fluoxetine) groups. Comprehensive assessments included behavioral tests, Nissl staining for histomorphology, transmission electron microscopy (TEM) for neuronal ultrastructure, immunofluorescence(IF), immunohistochemistry (IHC), Western blot (WB), enzyme-linked immunosorbent assay (ELISA), and reverse transcription quantitative polymerase chain reaction (RT-qPCR) to evaluate therapeutic effects and hippocampal alterations, focusing on VEGF/AKT1/ERK pathway expression and phosphorylation. AKT1 was identified as a key gene linking autophagy and inflammation. CUMS rats exhibited upregulation of hippocampal AKT1 transcription but decreased phosphorylation, along with enrichment of the VEGF pathway. EA at LI4/LR3 significantly ameliorated depressive-like behaviors and hippocampal damage in CUMS rats. Mechanistically, EA upregulated hippocampal VEGF expression and promoted synergistic phosphorylation of AKT1 and ERK. This was accompanied by enhanced autophagic activity (increased LC3-II/I ratio, decreased p62) and attenuated neuroinflammation (reduced IL-1β, TNF-α). Co-administration of the VEGFR2 inhibitor SU5416 largely abolished these therapeutic effects, including behavioral improvement, AKT1/ERK phosphorylation, autophagy enhancement, and anti-neuroinflammation. Furthermore, the autophagy inhibitor 3-MA also blocked EA’s benefits, indicating autophagy as the essential downstream executor. EA ameliorated depressive-like behaviors in CUMS rats, suggesting that the mechanism may involve the activation of the VEGF/AKT1/ERK pathway, leading to enhanced autophagy and attenuated hippocampal neuroinflammation.

This review summarizes considerations within the existing recent literature that guide the practice of interval appendectomy (IA) after initial non-operative management (NOM) of complicated appendicitis (CA) in children. A systematic review of English language articles published from 2000 to 2025 was conducted in Medline, Embase, and Cochrane Central Register of Controlled Trials to address four elements which could impact the decision for IA after NOM of CA: (1) the incidence of recurrent appendicitis; (2) the time period in which recurrence occurs; (3) the patient or disease-related risk factors which increase recurrence; and (4) the incidence of appendiceal neoplasms identified by IA. Of the 3,022 articles initially reviewed, 46 met inclusion criteria. Recurrence was reported in 2–50

This review highlights recent advances in the use of artificial intelligence (AI) for lung cancer screening, risk stratification, prognosis, and treatment selection, with a focus on emerging multimodal machine learning approaches. AI models, particularly deep learning algorithms, have exhibited high accuracy in interpreting imaging and liquid biopsy data for the early detection of lung cancer. Multimodal approaches integrating imaging, clinical, and molecular features have improved lung nodule classification and treatment response prediction. In retrospective studies, AI can outperform subjective decision-making thresholds and aid in providing patient-centered care. However, real-world deployment remains limited, and early clinical evaluations show performance degradation outside of retrospective settings. AI is poised to improve lung cancer care through enhanced detection, individualized prognostication, and personalized treatment. Multimodal models are especially promising but face challenges in generalizability, interpretability, and implementation. Clinical decision support systems that incorporate provider input may offer a feasible path to clinical integration. Prospective validation studies, system integration, and equitable data access are necessary to ensure AI can safely and effectively enhance lung cancer care.