The m6A reader SlYTH2 negatively regulates tomato fruit aroma by impeding the translation process.

N6-methyladenosine (m6A) is a fundamentally important RNA modification for gene regulation, whose function is achieved through m6A readers. However, whether and how m6A readers play regulatory roles during fruit ripening and quality formation remains unclear. Here, we characterized SlYTH2 as a tomato m6A reader protein and profiled the binding sites of SlYTH2 at the transcriptome-wide level. SlYTH2 undergoes liquid-liquid phase separation and promotes RNA-protein condensate formation. The target mRNAs of SlYTH2, namely m6A-modified SlHPL and SlCCD1B associated with volatile synthesis, are enriched in SlYTH2-induced condensates. Through polysome profiling assays and proteomic analysis, we demonstrate that knockout of SlYTH2 expedites the translation process of SlHPL and SlCCD1B, resulting in augmented production of aroma-associated volatiles. This aroma enrichment significantly increased consumer preferences for CRISPR-edited fruit over wild type. These findings shed light on the underlying mechanisms of m6A in plant RNA metabolism and provided a promising strategy to generate fruits that are more attractive to consumers.

Impact of dietary inflammatory index on gestational diabetes mellitus in normal and overweight women: a systematic review and meta-analysis of observational studies.

BACKGROUND AND OBJECTIVES: To systematically investigate the association between the dietary inflammatory index (DII) and gestational diabetes mellitus (GDM), with a focus on the role of BMI in this relationship. METHODS AND STUDY DESIGN: A comprehensive search was conducted in PubMed, Embase, Web of Science, The Cochrane Library, Medline, CINAHL Complete, Chinese Periodical Full-text Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, and China Wanfang Database for rele-vant observational studies published up to August 2023. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. The pooled effect size was calculated using a random-effects model. Sub-group and meta-regression analyses were performed to explore potential sources of heterogeneity. RESULTS: The study included 54,058 participants from 10 studies. Pregnant women with a higher DII, indicating a pro-inflammatory diet, had a significantly increased risk of GDM compared to those with a lower DII, indicating an anti-inflammatory diet (pooled OR: 1.17, 95% CI: 1.01-1.36; I²=70%, p <0.001). Subgroup analyses revealed a stronger association in normal weight stratification (OR: 1.25, 95%CI: 1.04-1.51), case-control studies (OR: 1.45, 95%CI: 1.03-2.05), Asia (OR: 1.26, 95%CI: 1.10-1.43), Europe (OR: 1.27, 95%CI: 1.09-1.48), 3-day dietary record as a dietary assessment tool (OR: 1.30, 95%CI: 1.16-1.46), physical activity adjustment (OR: 1.28, 95%CI: 1.13-1.46), and energy intake adjustment (OR: 1.33, 95%CI: 1.19-1.48). Meta-regression analysis confirmed that geographical region significantly influenced heterogeneity between studies (p <0.05). CONCLUSIONS: An elevated DII is independently linked to a higher risk of GDM, especially in women of normal weight.

Evaluation on photocatalytic activity of bismuth nitrate derived materials at different calcination temperatures using paper microzones method.

Our work reveals for the first time that directly calcined bismuth nitrate derivatives (BNDs) possess significant photocatalytic activity towards rhodamine B (RhB). As the calcination temperature increased, the Bi(NO3)3·5H2O powder gradually ruptured and transformed into different bismuth nitrate products and their mixtures, finally into stable α-Bi2O3 at 500 °C. Among them, BNDs-100 could achieve 100 % photocatalytic degradation of 10 mg/L RhB solution under UV irradiation for 6 min. The ImageJ-led paper microzones (PMZs) method is introduced for the first time into the performance evaluation process of photocatalysts, which can achieve the green chemistry pathway and the rapid evaluation of different catalysts. The accuracy of the results of the PMZs method relative to the spectrophotometric method was up to 91.14 %, which has a better reliability and is suitable for qualitative analysis, and a certain ability when used for quantitative analysis. The results showed that the PMZs method was used to assess the photocatalytic degradation of rhodamine B by bismuth nitrate-derived materials at different calcination temperatures with well reliability, and the preparation of BNDs by direct calcination was a simple and effective strategy.

Assessment of Pelvic Tilt in Anteroposterior Radiographs by Area Ratio Based on Deep Learning.

STUDY DESIGN: Diagnostics. OBJECTIVES: Based on deep learning semantic segmentation model, we sought to assess pelvic tilt by area ratio of the lesser pelvic and the obturator foramen in anteroposterior (AP) radiographs. BACKGROUND: Pelvic tilt is a critical factor in hip and spinal surgery, commonly evaluated by medical professionals through sagittal pelvic radiographs. The inherent pelvic asymmetry, as well as potential obstructions from clothing and musculature in roentgenography, may result in ghosting and blurring artifacts, thereby complicating precise measurement. METHODS: PT directly affects the area ratio of the lesser pelvis to the obturator foramen in AP radiographs. An exponential regression analysis of simulated radiographs from ten male and ten female pelvises in specific tilt positions derived a formula correlating this area ratio with PT. Two blinded investigators evaluated this formula using 161 simulated AP pelvic radiographs. A deep learning semantic segmentation model was then fine-tuned to automatically calculate the area ratio, enabling intelligent PT evaluation. This model and the regression function were integrated for automated PT measurement and tested on a dataset of 231 clinical cases. RESULTS: We observed no disparity between males and females in the aforementioned area ratio. The test results from two blinded investigators analyzing 161 simulated radiographs revealed a mean absolute error of 0.19° (SD±4.71°), with a correlation coefficient between them reaching 0.96. Additionally, the mean absolute error obtained from testing 231 clinical AP radiographs using the fine-tuned semantic segmentation model mentioned earlier is -0.58° (SD±5.97°). CONCLUSION: We found that using deep learning neural networks enabled a more accurate and robust automatic measurement of PT through the area ratio of the lesser pelvis and obturator foramen.

Temporal Dynamics and Physical Priori Multimodal Network for Rehabilitation Physical Training Evaluation.

Sensor-based rehabilitation physical training assessment methods have attracted significant attention in refined evaluation scenarios. A refined rehabilitation evaluation method combines the expertise of clinicians with advanced sensor-based technology to capture and analyze subtle movement variations often unobserved by traditional subjective methods. Current approaches center on either body postures or muscle strength, which lack more sophisticated analysis features of muscle activation and coordination, thereby hindering analysis efficacy in deep rehabilitation feature exploration. To address this issue, we present a multimodal network algorithm that integrates surface electromyography (sEMG) and stress distribution signals. The algorithm considers the physical knowledge a priori to interpret the current rehabilitation stage and efficiently handles temporal dynamics arising from diverse user profiles in an online setting. Besides, we verified the performance of this model using a learned-nonuse phenomenon assessment task in 24 subjects, achieving an accuracy of 94.7%. Our results surpass those of conventional feature-based, distance-based, and ensemble baseline models, highlighting the advantages of incorporating multimodal information rather than relying solely on unimodal data. Moreover, the proposed model presents a network design solution for rehabilitation physical training that requires deep bioinformatic features and can potentially assist real-time and home-based physical training work.

Anesthetic Effect on the Subthalamic Nucleus in Microelectrode Recording and Local Field Potential of Parkinson's Disease.

OBJECTIVES: Anesthetic agents used during deep brain stimulation (DBS) surgery might interfere with microelectrode recording (MER) and local field potential (LFP) and thus affect the accuracy of surgical target localization. This review aimed to identify the effects of different anesthetic agents on neuronal activity of the subthalamic nucleus (STN) during the MER procedure. MATERIALS AND METHODS: We used Medical Subject Heading terms to search the PubMed, EMBASE, EBSCO, and ScienceDirect data bases. MER characteristics were sorted into quantitative and qualitative data types. Quantitative data included the burst index, pause index, firing rate (FR), and interspike interval. Qualitative data included background activity, burst discharge (BD), and anesthetic agent effect. We also categorized the reviewed manuscripts into those describing local anesthesia with sedation (LAWS) and those describing general anesthesia (GA) and compiled the effects of anesthetic agents on MER and LFP characteristics. RESULTS: In total, 26 studies on MER were identified, of which 12 used LAWS and 14 used GA. Three studies on LFP also were identified. We found that the FR was preserved under LAWS but tended to be lower under GA, and BD was reduced in both groups. Individually, propofol enhanced BD but was better used for sedation, or the dosage should be minimized in GA. Similarly, low-dose dexmedetomidine sedation did not disturb MER. Opioids could be used as adjunctive anesthetic agents. Volatile anesthesia had the least adverse effect on MER under GA, with minimal alveolar concentration at 0.5. Dexmedetomidine anesthesia did not affect LFP, whereas propofol interfered with the power of LFP. CONCLUSIONS: The effects of the tested anesthetics on the STN in MER and LFP of Parkinson's disease varied; however, identifying the STN and achieving a good clinical outcome are possible under controlled anesthetic conditions. For patient comfort, anesthesia should be considered in STN-DBS.

A Hydrophilic Polyethylene Glycol-Blended Anion Exchange Membrane to Facilitate the Migration of Hydroxide Ions.

As one of the most important sources for green hydrogen, anion exchange membrane water electrolyzers (AEMWEs) have been developing rapidly in recent decades. Among these components, anion exchange membranes (AEMs) with high ionic conductivity and good stability play an important role in the performance of AEMWEs. In this study, we have developed a simple blending method to fabricate the blended membrane ImPSF-PEGx via the introduction of a hydrophilic PEG into the PSF-based ionic polymer. Given their hydrophilicity and coordination properties, the introduced PEGs are beneficial in assembling the ionic groups to form the ion-conducting channels. Moreover, an asymmetric structure is observed in ImPSF-PEGx membranes with a layer of finger-like cracks at the upper surface because PEGs can act as pore-forming agents. During the study, the ImPSF-PEGx membranes exhibited higher water uptake and ionic conductivity with lower swelling ratios and much better mechanical properties in comparison to the pristine ImPSF membrane. The ImPSF-PEG1000 membrane showed the best overall performance among the membranes with higher ionic conductivity (82.6 mS cm-1 at 80 °C), which was approximately two times higher than the conductivity of ImPSF, and demonstrated better mechanical and alkaline stability. The alkaline water electrolyzer assembled by ImPSF-PEG1000 achieved a current density of 606 mA cm-2 at 80 °C under conditions of 1 M KOH and 2.06 V, and maintained an essentially unchanged performance after 48 h running.

Application of Medical Statistical and Machine Learning Methods in the Age Estimation of Living Individuals.

In the study of age estimation in living individuals, a lot of data needs to be analyzed by mathematical statistics, and reasonable medical statistical methods play an important role in data design and analysis. The selection of accurate and appropriate statistical methods is one of the key factors affecting the quality of research results. This paper reviews the principles and applicable principles of the commonly used medical statistical methods such as descriptive statistics, difference analysis, consistency test and multivariate statistical analysis, as well as machine learning methods such as shallow learning and deep learning in the age estimation research of living individuals, and summarizes the relevance and application prospects between medical statistical methods and machine learning methods. This paper aims to provide technical guidance for the age estimation research of living individuals to obtain more scientific and accurate results.

Diet and the risk of inflammatory bowel disease: A retrospective cohort study in Taiwan.

BACKGROUND/PURPOSE: The incidence of inflammatory bowel disease (IBD) rapidly increases in Asia, and western dietary pattern is suspected to be the major risk factor. Despite this, there has been a lack of studies analyzing the relationship between dietary patterns and IBD in Taiwan. This study examines the dietary habits of Taiwanese individuals with and without IBD to inform clinical dietary recommendations for IBD patients. METHODS: We collected baseline characteristics and dietary habits from both IBD patients and healthy controls from February and August 2022 in Chang Gung memorial hospital using a structured and validated food frequency questionnaire. The dietary habits of IBD patients in this study were focused on the six months leading up to their IBD diagnosis. RESULTS: Our study recruited 98 IBD patients and 184 healthy controls. In demographic characteristics, cigarette smoking is more common in IBD group. Besides, distinct dietary patterns were observed between groups. The healthy controls demonstrated a higher consumption of whole foods and antioxidants. By contrast, the IBD group consumed more western-style foods but the difference didn't reach statistical significance. CONCLUSION: Our study found that healthy controls in Taiwan embraced a dietary pattern rich in whole foods that may prevent IBD or reduce IBD disease activity. Nonetheless, a larger sample size is needed to further provide valuable dietary guidance for general population in Taiwan for IBD prevention or for patients with IBD for disease activity control.

Classification of field wheat varieties based on a lightweight G-PPW-VGG11 model.

Introduction: In agriculture, especially wheat cultivation, farmers often use multi-variety planting strategies to reduce monoculture-related harvest risks. However, the subtle morphological differences among wheat varieties make accurate discrimination technically challenging. Traditional variety classification methods, reliant on expert knowledge, are inefficient for modern intelligent agricultural management. Numerous existing classification models are computationally complex, memory-intensive, and difficult to deploy on mobile devices effectively. This study introduces G-PPW-VGG11, an innovative lightweight convolutional neural network model, to address these issues. Methods: G-PPW-VGG11 ingeniously combines partial convolution (PConv) and partially mixed depthwise separable convolution (PMConv), reducing computational complexity and feature redundancy. Simultaneously, incorporating ECANet, an efficient channel attention mechanism, enables precise leaf information capture and effective background noise suppression. Additionally, G-PPW-VGG11 replaces traditional VGG11's fully connected layers with two pointwise convolutional layers and a global average pooling layer, significantly reducing memory footprint and enhancing nonlinear expressiveness and training efficiency. Results: Rigorous testing showed G-PPW-VGG11's superior performance, with an impressive 93.52% classification accuracy and only 1.79MB memory usage. Compared to VGG11, G-PPW-VGG11 showed a 5.89% increase in accuracy, 35.44% faster inference, and a 99.64% reduction in memory usage. G-PPW-VGG11 also surpasses traditional lightweight networks in classification accuracy and inference speed. Notably, G-PPW-VGG11 was successfully deployed on Android and its performance evaluated in real-world settings. The results showed an 84.67% classification accuracy with an average time of 291.04ms per image. Discussion: This validates the model's feasibility for practical agricultural wheat variety classification, establishing a foundation for intelligent management. For future research, the trained model and complete dataset are made publicly available.

Acyloxyacyl Hydrolase Protects against Kidney Injury via Inhibition of Tubular CD74-Macrophage Crosstalk.

Renal fibrosis is the common pathway in the progression of chronic kidney disease (CKD). Acyloxyacyl hydrolase (AOAH) is expressed in various phagocytes and is highly expressed in proximal tubular epithelial cells (PTECs). Research shows that AOAH plays a critical role in infections and chronic inflammatory diseases, although its role in kidney injury is unknown. Here, we found that AOAH deletion led to exacerbated kidney injury and fibrosis after folic acid (FA) administration, which was reversed by overexpression of Aoah in kidneys. ScRNA-seq revealed that Aoah-/- mice exhibited increased subpopulation of CD74+ PTECs, though the percentage of total PTECs were decreased compared to WT mice after FA treatment. Additionally, exacerbated kidney injury and fibrosis seen in Aoah-/- mice was attenuated via administration of methyl ester of (S, R)-3-(4-hydroxyphenyl)-4,5-dihydro-5-isoxazole acetic acid (ISO-1), an inhibitor of macrophage inhibition factor (MIF) and CD74 binding. Finally, AOAH expression was found positively correlated with estimated glomerular filtration rate while negatively correlated with the degree of renal fibrosis in kidneys of CKD patients. Thus, our work indicates that AOAH protects against kidney injury and fibrosis by inhibiting renal tubular epithelial cells CD74 signaling pathways. Targeting kidney AOAH represents a promising strategy to prevent renal fibrosis progression.

PTEN status determines therapeutic vulnerability to celastrol in cholangiocarcinoma.

BACKGROUND: A balanced protein homeostasis network helps cholangiocarcinoma (CCA) maintain their oncogenic growth, and disrupting proteostasis therapeutically will induce proteotoxic stress. Phosphatase and tensin homolog (PTEN) have been reported to be involved in proteostasis, and PTEN-associated pathways are commonly altered in CCA. Celastrol, a triterpene from plants, exhibits cytotoxic effects in various types of cancer. However, the underlying mechanisms remain unclear. PURPOSE: We investigated the therapeutic effect of celastrol in CCA and identified the molecular characteristics of tumors that were sensitive to celastrol. The target of celastrol was explored. We then evaluated the candidate combination therapeutic strategy to increase the effectiveness of celastrol in celastrol-insensitive CCA tumors. METHODS: Various CCA cells were categorized as either celastrol-sensitive or celastrol-insensitive based on their response to celastrol. The molecular characteristics of cells from different groups were determined by RNA-seq. PTEN status and its role in proteasome activity in CCA cells were investigated. The CMAP analysis, molecular docking, and functional assay were performed to explore the effect of celastrol on proteasome activities. The correlation between PTEN status and clinical outcomes, as well as proteasomal activity, were measured in CCA patients. The synergistic therapeutic effect of autophagy inhibitors on celastrol-insensitive CCA cells were measured. RESULTS: Diverse responses to celastrol were observed in CCA cells. PTEN expression varied among different CCA cells, and its status could impact cell sensitivity to celastrol: PTENhigh tumor cells were resistant to celastrol, while PTENlow cells were more sensitive. Celastrol induced proteasomal dysregulation in CCA cells by directly targeting PSMB5. Cells with low PTEN status transcriptionally promoted proteasome subunit expression in an AKT-dependent manner, making these cells more reliant on proteasomal activities to maintain proteostasis. This caused the PTENlow CCA cells sensitive to celastrol. A negative correlation was found between PTEN levels and the proteasome signature in CCA patients. Moreover, celastrol treatment could induce autophagy in PTENhigh CCA cells. Disrupting the autophagic pathway in PTENhigh CCA cells enhanced the cytotoxic effect of celastrol. CONCLUSION: PTEN status in CCA cells determines their sensitivity to celastrol, and autophagy inhibitors could enhance the anti-tumor effect in PTENhigh CCA.

Altered nucleocytoplasmic export of adenosine-rich circRNAs by PABPC1 contributes to neuronal function.

Circular RNAs (circRNAs) are upregulated during neurogenesis. Where and how circRNAs are localized and what roles they play during this process have remained elusive. Comparing the nuclear and cytoplasmic circRNAs between H9 cells and H9-derived forebrain (FB) neurons, we identify that a subset of adenosine (A)-rich circRNAs are restricted in H9 nuclei but exported to cytosols upon differentiation. Such a subcellular relocation of circRNAs is modulated by the poly(A)-binding protein PABPC1. In the H9 nucleus, newly produced (A)-rich circRNAs are bound by PABPC1 and trapped by the nuclear basket protein TPR to prevent their export. Modulating (A)-rich motifs in circRNAs alters their subcellular localization, and introducing (A)-rich circRNAs in H9 cytosols results in mRNA translation suppression. Moreover, decreased nuclear PABPC1 upon neuronal differentiation enables the export of (A)-rich circRNAs, including circRTN4(2,3), which is required for neurite outgrowth. These findings uncover subcellular localization features of circRNAs, linking their processing and function during neurogenesis.

Identification of southern Taiwan genetic variants in thyroid dyshormonogenesis through whole-exome sequencing.

Thyroid dyshormonogenesis (TDH) is responsible for 15%-25% of congenital hypothyroidism (CH) cases. Pathogenetic variants of this common inherited endocrine disorders vary geographically. Unraveling the genetic underpinnings of TDH is essential for genetic counseling and precise therapeutic strategies. This study aims to identify genetic variants associated with TDH in Southern Taiwan using whole exome sequencing (WES). We included CH patients diagnosed through newborn screening at a tertiary medical center from 2011 to 2022. Permanent TDH was determined based on imaging evidence of bilateral thyroid structure and the requirement for continuous medication beyond 3 years of age. Genomic DNA extracted from blood was used for exome library construction, and pathogenic variants were detected using an in-house algorithm. Of the 876 CH patients reviewed, 121 were classified as permanent, with 47 (40%) confirmed as TDH. WES was conducted for 45 patients, and causative variants were identified in 32 patients (71.1%), including DUOX2 (15 cases), TG (8 cases), TSHR (7 cases), TPO (5 cases), and DUOXA2 (1 case). Recurrent variants included DUOX2 c.3329G>A, TSHR c.1349G>A, TG c.1348delT, and TPO c.2268dupT. We identified four novel variants based on genotype, including TSHR c.1135C>T, TSHR c.1349G>C, TG c.2461delA, and TG c.2459T>A. This study underscores the efficacy of WES in providing definitive molecular diagnoses for TDH. Molecular diagnoses are instrumental in genetic counseling, formulating treatment, and developing management strategies. Future research integrating larger population cohorts is vital to further elucidate the genetic landscape of TDH.

Effective Connectivity of Default Mode Network Subsystems in Parkinson's Disease with Mild Cognitive Impairment Based on Spectral Dynamic Causal Modeling.

OBJECTIVE: The objective of this study is to compare the differences in effective connectivity within the default mode network (DMN) subsystems between patients with Parkinson's disease with mild cognitive impairment (PD-MCI) and patients with Parkinson's disease with normal cognition (PD-CN). The mechanisms underlying DMN dysfunction in PD-MCI patients and its association with clinical cognitive function in PD-MCI are aimed to be investigated. METHODS: The spectral dynamic causal model (spDCM) was employed to analyze the effective connectivity of functional magnetic resonance imaging (fMRI) data in the resting state for the DMN subsystems, which include the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), left and right angular gyrus (LAG, RAG) in 23 PD-MCI and 22 PD-CN patients, respectively. The effective connectivity values of DMN subsystems in the two groups were statistically analyzed using a two-sample t-test. The Spearman correlation analysis was used to test the correlation between the effective connectivity values of the subsystems with significant differences between the two groups and the clinical cognitive function (as measured by Montreal Cognitive Assessment Scale (MoCA) score). RESULTS: Statistical analysis revealed significant differences in the effective connections of MPFC-LAG and LAG-PCC between the two patient groups (MPFC-LAG: t = -2.993, p < 0.05; LAG-PCC: t = 2.174, p < 0.05). CONCLUSIONS: The study findings suggest that abnormal strength and direction of effective connections between DMN subsystems are found in PD-MCI patients.

Calixarene-Based Supramolecular Sensor Array for Pesticide Discrimination.

The identification and detection of pesticides is crucial to protecting both the environment and human health. However, it can be challenging to conveniently and rapidly differentiate between different types of pesticides. We developed a supramolecular fluorescent sensor array, in which calixarenes with broad-spectrum encapsulation capacity served as recognition receptors. The sensor array exhibits distinct fluorescence change patterns for seven tested pesticides, encompassing herbicides, insecticides, and fungicides. With a reaction time of just three minutes, the sensor array proves to be a rapid and efficient tool for the discrimination of pesticides. Furthermore, this supramolecular sensing approach can be easily extended to enable real-time and on-site visual detection of varying concentrations of imazalil using a smartphone with a color scanning application. This work not only provides a simple and effective method for pesticide identification and quantification, but also offers a versatile and advantageous platform for the recognition of other analytes in relevant fields.

Porcine cis-acting lnc-CAST positively regulates CXCL8 expression through histone H3K27ac.

The chemokine CXCL8, also known as the neutrophil chemotactic factor, plays a crucial role in mediating inflammatory responses and managing cellular immune reactions during viral infections. Porcine reproductive and respiratory syndrome virus (PRRSV) primarily infects pulmonary alveolar macrophages (PAMs), leading to acute pulmonary infections. In this study, we explored a novel long non-coding RNA (lncRNA), termed lnc-CAST, situated within the Cxcl8 gene locus. This lncRNA was found to be highly expressed in porcine macrophages. We observed that both lnc-CAST and CXCL8 were significantly upregulated in PAMs following PRRSV infection, and after treatments with lipopolysaccharide (LPS) or lipoteichoic acid (LTA). Furthermore, we noticed a concurrent upregulation of lnc-CAST and CXCL8 expression in lungs of PRRSV-infected pigs. We then determined that lnc-CAST positively influenced CXCL8 expression in PAMs. Overexpression of lnc-CAST led to an increase in CXCL8 production, which in turn enhanced the migration of epithelial cells and the recruitment of neutrophils. Conversely, inhibiting lnc-CAST expression resulted in reduced CXCL8 production in PAMs, leading to decreased migration levels of epithelial cells and neutrophils. From a mechanistic perspective, we found that lnc-CAST, localized in the nucleus, facilitated the enrichment of histone H3K27ac in CXCL8 promoter region, thereby stimulating CXCL8 transcription in a cis-regulatory manner. In conclusion, our study underscores the pivotal critical role of lnc-CAST in regulating CXCL8 production, offering valuable insights into chemokine regulation and lung damage during PRRSV infection.

Outcome prediction of SSTR-RADS-3A and SSTR-RADS-3B lesions in patients with neuroendocrine tumors based on 68Ga-DOTATATE PET/MR.

PURPOSE: Somatostatin receptor (SSTR)-targeted PET imaging has emerged as a common approach to evaluating those patients with well-differentiated neuroendocrine tumors (NETs). The SSTR reporting and data system (SSTR-RADS) version 1.0 provides a means of categorizing lesions from 1 to 5 according to the likelihood of NET involvement, with SSTR-RADS-3A (soft-tissue) and SSTR-RADS-3B (bone) lesions being those suggestive of but without definitive NET involvement. The goal of the present study was to assess the ability of 68Ga-DOTATATE PET/MR imaging data to predict outcomes for indeterminate SSTR-RADS-3A and 3B lesions. METHODS: NET patients with indeterminate SSTR-RADS-3A or SSTR-RADS-3B lesions who underwent 68Ga-DOTATATE PET/MR imaging from April 2020 through August 2023 were retrospectively evaluated. All patients underwent follow-up through December 2023 (median, 17 months; (3-31 months)), with imaging follow-up or biopsy findings ultimately being used to classify lesions as malignant or benign. Lesion maximum standardized uptake value (SUVmax) along with minimum and mean apparent diffusion coefficient (ADCmin and ADCmean) values were measured and assessed for correlations with outcomes on follow-up. RESULTS: In total, 33 indeterminate SSTR-RADS-3 lesions from 22 patients (19 SSTR-RADS-3A and 14 SSTR-RADS-3B) were identified based upon baseline 68Ga-DOTATATE PET/MR findings. Over the course of follow-up, 16 of these lesions (48.5%) were found to exhibit true NET positivity, including 9 SSTR-RADS-3A and 7 SSTR-RADS-3B lesions. For SSTR-RADS-3A lymph nodes, a diameter larger than 0.7 cm and an ADCmin of 779 × 10-6mm2/s or lower were identified as being more likely to be associated with metastatic lesions. Significant differences in ADCmin and ADCmean were identified when comparing metastatic and non-metastatic SSTR-RADS-3B bone lesions (P < 0.05), with these parameters offering a high predictive ability (AUC = 0.94, AUC = 0.86). CONCLUSION: Both diameter and ADCmin can aid in the accurate identification of the nature of lesions associated with SSTR-RADS-3A lymph nodes, whereas ADCmin and ADCmean values can inform the accurate interpretation of SSTR-RADS-3B bone lesions.

Restoring colistin sensitivity in colistin-resistant Salmonella and Escherichia coli: combinatorial use of berberine and EDTA with colistin.

The appearance and prevalence of multidrug-resistance (MDR) Gram-negative bacteria (GNB) have limited our antibiotic capacity to control bacterial infections. The clinical efficacy of colistin (COL), considered as the "last resort" for treating GNB infections, has been severely hindered by its increased use as well as the emergence and prevalence of mobile colistin resistance (MCR)-mediated acquired drug resistance. Identifying promising compounds to restore antibiotic activity is becoming an effective strategy to alleviate the crisis of increasing MDR. We first demonstrated that the combination of berberine (BBR) and EDTA substantially restored COL sensitivity against COL-resistant Salmonella and Escherichia coli. Molecular docking indicated that BBR can interact with MCR-1 and the efflux pump system AcrAB-TolC, and BBR combined with EDTA downregulated the expression level of mcr-1 and tolC. Mechanically, BBR combined with EDTA could increase bacterial membrane damage, inhibit the function of multidrug efflux pump, and promote oxidative damage, thereby boosting the action of COL. In addition, transcriptome analysis found that the combination of BBR and EDTA can accelerate the tricarboxylic acid cycle, inhibit cationic antimicrobial peptide (CAMP) resistance, and attenuate Salmonella virulence. Notably, the combination of BBR and EDTA with COL significantly reduced the bacterial load in the liver and spleen of a mice model infected with Salmonella. Our findings revealed that BBR and EDTA can be used as adjuvants collectively with COL to synergistically reverse the COL resistance of bacteria. IMPORTANCE: Colistin is last-resort antibiotic used to treat serious clinical infections caused by MDR bacterial pathogens. The recent emergence of transferable plasmid-mediated COL resistance gene mcr-1 has raised the specter of a rapid worldwide spread of COL resistance. Coupled with the fact of barren antibiotic development pipeline nowadays, a critical approach is to revitalize existing antibiotics using antibiotic adjuvants. Our research showed that berberine combined with EDTA effectively reversed COL resistance both in vivo and in vitro through multiple modes of action. The discovery of berberine in combination with EDTA as a new and safe COL adjuvant provides a therapeutic regimen for combating Gram-negative bacteria infections. Our findings provide a potential therapeutic option using existing antibiotics in combination with antibiotic adjuvants and address the prevalent infections caused by MDR Gram-negative pathogens worldwide.

Prevalence and bidirectional association of sleep quality and gut health among Chinese midwives: a large population, multi-center cross-sectional study.

Background: Shift work can disrupt sleep quality and gut health. Nurses and midwives constitute approximately half of the global healthcare shift-working workforce. Our previous study revealed that most midwives were experiencing suboptimal health conditions, characterized by poor sleep quality and a high prevalence of gastrointestinal diseases. The gut-brain axis theory highlights the potential interplay between sleep quality and gut health. However, limited research focuses on this relationship among midwives. Methods: A cross-sectional survey included 2041 midwives from 87 Chinese hospitals between March and October 2023. Participants completed standardized questionnaires assessing sleep quality, gut health, depression, anxiety, and work stress. Binary logistic regression analyzed factors associated with poor sleep, and multiple linear regression examined the influence of sleep quality on gut health. Results: Over 60% of midwives reported poor sleep, with many experiencing gastrointestinal disorders. We observed a bidirectional relationship between sleep quality and gut health among midwives. After multivariable adjustments, midwives with higher gut health scores were more likely to experience poor sleep quality (odds ratio = 1.042, 95% confidence interval = 1.03-1.054). Conversely, midwives with higher sleep quality scores were also more likely to have poor gut health (ß = 0.222, 95% confidence interval = 0.529-0.797). These associations remained robust across sensitivity analyses. Furthermore, depression, anxiety, and work stress significantly affected both sleep quality and gut health among midwives. Conclusion: This study enhances our understanding of the intricate relationship between sleep quality and gut health among midwives. Poor gut health was associated with a higher risk of poor sleep, and vice versa. To improve the overall wellbeing of midwives, the findings emphasize the importance of addressing poor sleep quality and promoting gut health through maintaining a healthy diet, lifestyle, and good mental health. Further studies are needed to confirm our findings and clarify the underlying mechanisms.