Drivers of natural gas use in U.S. residential buildings.

Natural gas is the primary fuel used in U.S. residences, yet little is known about its consumption patterns and drivers. We use daily county-level gas consumption data to assess the spatial patterns of the relationships and the sensitivities of gas consumption to outdoor air temperature across U.S. households. We fitted linear-plus-plateau functions to daily gas consumption data in 1000 counties, and derived two key coefficients: the heating temperature threshold (Tcrit) and the gas consumption rate change per 1°C temperature drop (Slope). We identified the main predictors of Tcrit and Slope (like income, employment rate, and building type) using interpretable machine learning models built on census data. Finally, we estimated a potential 2.47 million MtCO2 annual emission reduction in U.S. residences by gas savings due to household insulation improvements and hypothetical behavioral change toward reduced consumption by adopting a 1°C lower Tcrit than the current value.

Photoinduced Pd-Catalyzed Enantioselective Carboamination of Dienes via Aliphatic C-H Bond Elaboration.

Three-component diene carboaminations offer a potent means to access synthetically valuable allylic amines with rapid molecular complexity escalation. The existing literature primarily discloses racemic examples, necessitating the use of halides/pseudohalides as substrates. This paper introduces a photoinduced Pd-catalyzed enantioselective three-component carboamination of aryl-substituted 1,3-dienes, leveraging aliphatic C-H bonds for rapid synthesis. The reaction employs 10 mol % of chiral palladium catalyst and an excess aryl bromide as the HAT reagent. This approach yields diverse chiral allylamines with moderate to excellent enantioselectivities. Notably, it stands as the first instance of an asymmetric three-component diene carboamination reaction, directly utilizing abundant C(sp3)-H bearing partners, such as toluene-type substrates, ethers, amines, esters, and ketones. The protocol exhibits versatility across amines, encompassing aliphatic, aromatic, primary, and secondary derivatives. This method could serve as a versatile platform for stereoselective incorporation of various nucleophiles, dienes, and C(sp3)-H bearing partners.

Effects of predictive nursing interventions on pressure ulcer in older bedridden patients: A meta-analysis.

To evaluate the effect of predictive nursing interventions on pressure ulcers in elderly bedridden patients by meta-analysis. Applied computer searches of PubMed, Embase, Google Scholar, Cochrane Library, China National Knowledge Infrastructure and Wanfang databases for randomised controlled trials (RCTs) on the effect of predictive nursing in preventing pressure ulcers in elderly bedridden patients from the database inception to November 2023. Two researchers independently screened the literature, extracted data and performed quality assessment based on inclusion and exclusion criteria. Stata 17.0 software was utilised for data analysis. Eighteen RCTs involving 6504 patients were finally included. The analysis revealed the implementation of predictive nursing interventions had a significant advantage in reducing the incidence of pressure ulcers in elderly bedridden patients compared with conventional nursing (odds ratio [OR] = 0.20, 95% confidence interval [CI]: 0.15-0.28, p < 0.001), while the patients' satisfaction with nursing care was higher (OR = 3.70, 95% CI: 2.99-4.57, p < 0.001). This study shows that the implementation of a predictive nursing interventions for elderly bedridden patients can effectively reduce the occurrence of pressure ulcers and significantly improve patients' satisfaction with nursing care, which is worthy of clinical promotion and application.

Effect of quality nursing intervention on wound healing in patients with burns: A meta-analysis.

This meta-analysis aimed to explore the effects of quality nursing intervention on wound healing in patients with burns. A computerised search was conducted for randomised controlled trials (RCTs) on the effect of quality nursing intervention on wound healing in patients with burns in the PubMed, Embase, Google Scholar, Cochrane Library, China National Knowledge Infrastructure and Wanfang databases from the date of database inception to November 2023. Two researchers independently screened the literature, extracted data and performed quality assessment based on the inclusion and exclusion criteria. Stata 17.0 software was used for the data analysis. Twenty-nine RCTs involving 2637 patients with burns were included. The meta-analysis revealed that compared with conventional nursing, the implementation of quality nursing intervention in patients with burns significantly shortened the wound healing time (standardised mean difference [SMD] = -2.93, 95% confidence interval [CI]: -3.44 to -2.42, p < 0.001). The incidence of wound infections (odds ratio [OR] = 0.14, 95% CI: 0.07-0.27, p < 0.001) and complications (OR = 0.16, 95% CI: 0.11-0.23, p < 0.001) was also reduced significantly. This meta-analysis shows that applying quality nursing interventions in patients with burns can significantly shorten the wound healing time and reduce the incidence of wound infection and complications, thus promoting early patient recovery.

Machine-learning model for the prediction of acute orthostatic hypotension after levodopa administration.

BACKGROUND: Levodopa could induce orthostatic hypotension (OH) in Parkinson's disease (PD) patients. Accurate prediction of acute OH post levodopa (AOHPL) is important for rational drug use in PD patients. Here, we develop and validate a prediction model of AOHPL to facilitate physicians in identifying patients at higher probability of developing AOHPL. METHODS: The study involved 497 PD inpatients who underwent a levodopa challenge test (LCT) and the supine-to-standing test (STS) four times during LCT. Patients were divided into two groups based on whether OH occurred during levodopa effectiveness (AOHPL) or not (non-AOHPL). The dataset was randomly split into training (80%) and independent test data (20%). Several models were trained and compared for discrimination between AOHPL and non-AOHPL. Final model was evaluated on independent test data. Shapley additive explanations (SHAP) values were employed to reveal how variables explain specific predictions for given observations in the independent test data. RESULTS: We included 180 PD patients without AOHPL and 194 PD patients with AOHPL to develop and validate predictive models. Random Forest was selected as our final model as its leave-one-out cross validation performance [AUC_ROC 0.776, accuracy 73.6%, sensitivity 71.6%, specificity 75.7%] outperformed other models. The most crucial features in this predictive model were the maximal SBP drop and DBP drop of STS before medication (ΔSBP/ΔDBP). We achieved a prediction accuracy of 72% on independent test data. ΔSBP, ΔDBP, and standing mean artery pressure were the top three variables that contributed most to the predictions across all individual observations in the independent test data. CONCLUSIONS: The validated classifier could serve as a valuable tool for clinicians, offering the probability of a patient developing AOHPL at an early stage. This supports clinical decision-making, potentially enhancing the quality of life for PD patients.

Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents.

Modern food chain supply management necessitates the dire need for mitigating food fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent and systematic review analyses (2018-2023) revealed both destructive and non-destructive methods to demarcate a rational approach for food fraud detection in various countries. These intricate hygiene standards and AI-based technology are also summarized for further prospective research. Chemometrics or AI-based techniques for extensive food fraud detection are demanded. A systematic assessment reveals that various methods to detect food fraud involving multiple substances need to be simple, expeditious, precise, cost-effective, eco-friendly and non-intrusive. The scrutiny resulted in 39 relevant experimental data sets answering key questions. However, additional research is necessitated for an affirmative conclusion in food fraud detection system with modern AI and machine learning approaches.

Role of Type VI secretion system in pathogenic remodeling of host gut microbiota during Aeromonas veronii infection.

Intestinal microbial disturbance is a direct cause of host disease. The bacterial Type VI secretion system (T6SS) often plays a crucial role in the fitness of pathogenic bacteria by delivering toxic effectors into target cells. However, its impact on the gut microbiota and host pathogenesis is poorly understood. To address this question, we characterized a new T6SS in the pathogenic Aeromonas veronii C4. First, we validated the secretion function of the core machinery of A. veronii C4 T6SS. Second, we found that the pathogenesis and colonization of A. veronii C4 is largely dependent on its T6SS. The effector secretion activity of A. veronii C4 T6SS not only provides an advantage in competition among bacteria in vitro, but also contributes to occupation of an ecological niche in the nutritionally deficient and anaerobic environment of the host intestine. Metagenomic analysis showed that the T6SS directly inhibits or eliminates symbiotic strains from the intestine, resulting in dysregulated gut microbiome homeostasis. In addition, we identified three unknown effectors, Tse1, Tse2, and Tse3, in the T6SS, which contribute to T6SS-mediated bacterial competition and pathogenesis by impairing targeted cell integrity. Our findings highlight that T6SS can remodel the host gut microbiota by intricate interplay between T6SS-mediated bacterial competition and altered host immune responses, which synergistically promote pathogenesis of A. veronii C4. Therefore, this newly characterized T6SS could represent a general interaction mechanism between the host and pathogen, and may offer a potential therapeutic target for controlling bacterial pathogens.

A Task-guided, Implicitly-searched and Metainitialized Deep Model for Image Fusion.

Image fusion plays a key role in a variety of multi-sensor-based vision systems, especially for enhancing visual quality and/or extracting aggregated features for perception. However, most existing methods just consider image fusion as an individual task, thus ignoring its underlying relationship with these downstream vision problems. Furthermore, designing proper fusion architectures often requires huge engineering labor. It also lacks mechanisms to improve the flexibility and generalization ability of current fusion approaches. To mitigate these issues, we establish a Task-guided, Implicit-searched and Meta-initialized (TIM) deep model to address the image fusion problem in a challenging real-world scenario. Specifically, we first propose a constrained strategy to incorporate information from downstream tasks to guide the unsupervised learning process of image fusion. Within this framework, we then design an implicit search scheme to automatically discover compact architectures for our fusion model with high efficiency. In addition, a pretext meta initialization technique is introduced to leverage divergence fusion data to support fast adaptation for different kinds of image fusion tasks. Qualitative and quantitative experimental results on different categories of image fusion problems and related downstream tasks (e.g., visual enhancement and semantic understanding) substantiate the flexibility and effectiveness of our TIM.

A comparison of endothelial cell growth on commercial coronary stents with and without laser surface texturing.

Complete endothelialisation of coronary stents is an important determinant of future thrombotic complications following coronary stenting. Stent surface texture is an important factor that influences endothelial cell growth. With the emergence of second and third generation coronary stents, is limited comparative data describing endothelial cell growth in contemporary stent platforms, and limited data available on approaches used to rapidly modify the surfaces of commercial coronary stents to improve endothelialisation. In this study we have determined the in vitro proliferation of the primary human coronary artery endothelial cells on the commonly used 4 types of commercial coronary stents and found that the inner surface of BioMatrix drug-eluting stents (DES), after eliminating of the polymer and drug coating, had significantly higher endothelial cell proliferation compared to that of other bare metal stents (BMS): Multi-Link8, Integrity and Omega. The surfaces of the 3 types of BMS which are smooth, displayed similar endothelial cell proliferation, suggesting the importance of surface features in manipulating endothelial cell growth. Laser surface texturing was used to create micro/nano patterns on the stents. The laser treatment has significantly increased endothelial proliferation on the inner surfaces of all 4 types of stents, and Multi-Link8 stents displayed the highest (>100%) improvement. The laser textured BioMatrix stents had the highest absolute number of endothelial cells growth. Our results provided useful information in the endothelialisation potential for the commonly used commercial coronary stents and suggested a potential future application of laser surface bioengineering to coronary stents for better biocompatibility of the device.

Vonoprazan-amoxicillin dual therapy with different amoxicillin dosages for treatment-naive patients of Helicobacter pylori infection in China: a prospective, randomized controlled study.

BACKGROUND: The vonoprazan (VPZ)-amoxicillin (AMO) dual therapy (VA) demonstrates a satisfactory eradication rate for Helicobacter pylori (H. pylori). However, the optimal dosage of AMO in this regimen remains uncertain. The objective of this study is to investigate the efficacy of different doses of AMO in the VA regimen for first-line treatment of H. pylori infection. METHODS: A total of 192 treatment-naive H. pylori-infected patients were randomly assigned to one of three groups: low-dose VA (LD-VA: VPZ 20 mg b.i.d + AMO 750 mg t.i.d), moderate-dose VA (MD-VA:VPZ 20 mg b.i.d + AMO 1000 mg t.i.d), and high-dose VA (HD-VA: VPZ 20 mg b.i.d + AMO 1250 mg t.i.d). All groups received 14 days of treatment. The study evaluated and compared the eradication rates, adverse events (AEs), and patient compliance among the three groups. RESULTS: Eradication rates for LD-VA, MD-VA, and HD-VA were 76.6% (49/64), 79.7% (51/64), and 84.4% (54/64), respectively, as determined by intention-to-treat analysis; 90.6% (48/53), 94.3% (50/53), and 98.1% (53/54) according to per-protocol analysis; 89.1% (49/55), 94.4% (51/54), and 96.4% (54/56) with modified intention-to-treat analysis (all P > 0.05). Although not statistically significant, numerically higher eradication rates were observed with the higher dose AMO VA regimen. There were no statistically significant differences in the incidence of AEs and compliance among the three VA regimens. CONCLUSION: Fourteen-day VA regimens with AMO doses exceeding 2 g/day demonstrated satisfactory eradication rates. HD-VA therapy is potentially the most effective regimen. Large-sample clinical trials are required to further validate these findings.

Comparison of vonoprazan-based dual therapy with vonoprazan-based bismuth quadruple therapy for treatment-naive patients with Helicobacter pylori infection: A propensity score matching analysis.

Vonoprazan, a novel acid suppressant and the first potassium-competitive acid blocker, has the potential to enhance the eradication rate of Helicobacter pylori due to its robust acid-suppressing capacity. This study aimed to compare the efficacy of vonoprazan-based dual therapy (vonoprazan-amoxicillin, VA) with vonoprazan-based bismuth quadruple therapy (VBQT) as a first-line treatment for H pylori infection. This retrospective single-center non-inferiority study was conducted in China. Treatment-naive H pylori-positive patients aged 18 to 80 received one of the 2 treatment regimens at our center. The VA group received vonoprazan 20 mg twice daily and amoxicillin 1000 mg 3 times daily for 14 days, whereas the VBQT group received vonoprazan 20 mg, amoxicillin 1000 mg, clarithromycin 500 mg, and bismuth potassium citrate 220 mg twice daily for 14 days. The eradication rate was evaluated 4 to 6 weeks after treatment using the carbon-13/14 urea breath test. Propensity score matching was used to analyze eradication rates, adverse events (AEs), and patient compliance between the 2 groups. Initially, 501 patients were included, and after propensity score analysis, 156 patients were selected for the study. Intention-to-treat analysis showed eradication rates of 87.2% (95% CI, 79.8-94.6%) for the VA group and 79.5% (95% CI, 70.5-88.4%) for the VBQT group (P = .195). Per-protocol analysis demonstrated rates of 94.4% (95% CI, 89.2-99.7%) for the VA group and 96.8% (95% CI, 92.4-100%) for the VBQT group (P = .507). Non-inferiority was confirmed between the 2 groups, with P values < .025. The VA group showed a lower rate of AEs (10.3% vs 17.9%, P = .250) compared to the VBQT group. There were no significant differences in patient compliance between the 2 groups. In treatment-naive patients with H pylori infection, both the 14-day VA and VBQT regimens demonstrated comparable efficacy, with excellent eradication rates. Moreover, due to reduced antibiotic usage, lower rate of AEs, and lower costs, VA dual therapy should be prioritized.

Development of PEG-mediated genetic transformation and gene editing system of Bryum argenteum as an abiotic stress tolerance model plant.

KEY MESSAGE: To establish a sterile culture system and protoplast regeneration system for Bryum argenteum, and to establish and apply CRISPR/Cas9 system in Bryum argenteum. Bryum argenteum is a fascinating, cosmopolitan, and versatile moss species that thrives in various disturbed environments. Because of its comprehensive tolerance to the desiccation, high UV and extreme temperatures, it is emerging as a model moss for studying the molecular mechanisms underlying plant responses to abiotic stresses. However, the lack of basic tools such as gene transformation and targeted genome modification has hindered the understanding of the molecular mechanisms underlying the survival of B. argenteum in different environments. Here, we reported the protonema of B. argenteum can survive up to 95.4% water loss. In addition, the genome size of B. argenteum is approximately 313 Mb by kmer analysis, which is smaller than the previously reported 700 Mb. We also developed a simple method for protonema induction and an efficient protoplast isolation and regeneration protocol for B. argenteum. Furthermore, we established a PEG-mediated protoplast transient transfection and stable transformation system for B. argenteum. Two homologues of ABI3(ABA-INSENSITIVE 3) gene were successfully cloned from B. argenteum. To further investigate the function of the ABI3 gene in B. argenteum, we used the CRISPR/Cas9 genetic editing system to target the BaABI3A and BaABI3B gene in B. argenteum protoplasts. This resulted in mutagenesis at the target in about 2-5% of the regenerated plants. The isolated abi3a and abi3b mutants exhibited increased sensitivity to desiccation, suggesting that BaABI3A and BaABI3B play redundant roles in desiccation stress. Overall, our results provide a rapid and simple approach for molecular genetics in B. argenteum. This study contributes to a better understanding of the molecular mechanisms of plant adaptation to extreme environmental.

Uncertainty-based saltwater intrusion prediction using integrated Bayesian machine learning modeling (IBMLM) in a deep aquifer.

Data-driven machine learning approaches are promising to substitute physically based groundwater numerical models and capture input-output relationships for reducing computational burden. But the performance and reliability are strongly influenced by different sources of uncertainty. Conventional researches generally rely on a stand-alone machine learning surrogate approach and fail to account for errors in model outputs resulting from structural deficiencies. To overcome this issue, this study proposes a flexible integrated Bayesian machine learning modeling (IBMLM) method to explicitly quantify uncertainties originating from structures and parameters of machine learning surrogate models. An Expectation-Maximization (EM) algorithm is combined with Bayesian model averaging (BMA) to find out maximum likelihood and construct posterior predictive distribution. Three machine learning approaches representing different model complexity are incorporated in the framework, including artificial neural network (ANN), support vector machine (SVM) and random forest (RF). The proposed IBMLM method is demonstrated in a field-scale real-world "1500-foot" sand aquifer, Baton Rouge, USA, where overexploitation caused serious saltwater intrusion (SWI) issues. This study adds to the understanding of how chloride concentration transport responds to multi-dimensional extraction-injection remediation strategies in a sophisticated saltwater intrusion model. Results show that most IBMLM exhibit r values above 0.98 and NSE values above 0.93, both slightly higher than individual machine learning, confirming that the IBMLM is well established to provide better model predictions than individual machine learning models, while maintaining the advantage of high computing efficiency. The IBMLM is found useful to predict saltwater intrusion without running the physically based numerical simulation model. We conclude that an explicit consideration of machine learning model structure uncertainty along with parameters improves accuracy and reliability of predictions, and also corrects uncertainty bounds. The applicability of the IBMLM framework can be extended in regions where a physical hydrogeologic model is difficult to build due to lack of subsurface information.

Health-environment efficiency of diets shows nonlinear trends over 1990-2011.

Understanding the impacts of diets on health and the environment, as well as their association with socio-economic development, is key to operationalize and monitor food systems shifts. Here we propose a health-environment efficiency indicator defined as a ratio of health benefits and four key food-related environmental impacts (greenhouse gas emissions, scarcity-weighted water withdrawal, acidifying and eutrophying emissions) to assess how diets have performed in supporting healthy lives in relation to environmental pollution and resource consumption across 195 countries from 1990 to 2011. We find that the health-environment efficiency of each environmental input follows a nonlinear path along the Socio-Demographic Index gradient representing different development levels. Health-environment efficiency first increases thanks to the elimination of child and maternal malnutrition through greater food supply, then decreases driven by additional environmental impacts from a shift to animal products, and finally shows a slow growth in some developed countries again as they shift towards healthier diets.

Peanut-based intercropping systems altered soil bacterial communities, potential functions, and crop yield.

Intercropping is an efficient land use and sustainable agricultural practice widely adopted worldwide. However, how intercropping influences the structure and function of soil bacterial communities is not fully understood. Here, the effects of five cropping systems (sole sorghum, sole millet, sole peanut, sorghum/peanut intercropping, and millet/peanut intercropping) on soil bacterial community structure and function were investigated using Illumina MiSeq sequencing. The results showed that integrating peanut into intercropping systems increased soil available nitrogen (AN) and total nitrogen (TN) content. The alpha diversity index, including Shannon and Chao1 indices, did not differ between the five cropping systems. Non-metric multidimensional scaling (NMDS) and analysis of similarities (ANOSIM) illustrated a distinct separation in soil microbial communities among five cropping systems. Bacterial phyla, including Actinobacteria, Proteobacteria, Acidobacteria, and Chloroflexi, were dominant across all cropping systems. Sorghum/peanut intercropping enhanced the relative abundance of phyla Actinobacteriota and Chloroflexi compared to the corresponding monocultures. Millet/peanut intercropping increased the relative abundance of Proteobacteria, Acidobacteriota, and Nitrospirota. The redundancy analysis (RDA) indicated that bacterial community structures were primarily shaped by soil organic carbon (SOC). The land equivalent ratio (LER) values for the two intercropping systems were all greater than one. Partial least squares path modeling analysis (PLS-PM) showed that soil bacterial community had a direct effect on yield and indirectly affected yield by altering soil properties. Our findings demonstrated that different intercropping systems formed different bacterial community structures despite sharing the same climate, reflecting changes in soil ecosystems caused by interspecific interactions. These results will provide a theoretical basis for understanding the microbial communities of peanut-based intercropping and guide agricultural practice.

Genome-wide DNA N6-methyladenosine in Aeromonas veronii and Helicobacter pylori.

BACKGROUND: DNA N6-methyladenosine (6mA), as an important epigenetic modification, widely exists in bacterial genomes and participates in the regulation of toxicity, antibiotic resistance, and antioxidant. With the continuous development of sequencing technology, more 6mA sites have been identified in bacterial genomes, but few studies have focused on the distribution characteristics of 6mA at the whole-genome level and its association with gene expression and function. RESULTS: This study conducted an in-depth analysis of the 6mA in the genomes of two pathogenic bacteria, Aeromonas veronii and Helicobacter pylori. The results showed that the 6mA was widely distributed in both strains. In A. veronii, 6mA sites were enriched at 3' end of protein-coding genes, exhibiting a certain inhibitory effect on gene expression. Genes with low 6mA density were associated with cell motility. While in H. pylori, 6mA sites were enriched at 5' end of protein-coding genes, potentially enhancing gene expression. Genes with low 6mA density were closely related to defense mechanism. CONCLUSIONS: This study elucidated the distribution characteristics of 6mA in A. veronii and H. pylori, highlighting the effects of 6mA on gene expression and function. These findings provide valuable insights into the epigenetic regulation and functional characteristics of A. veronii and H. pylori.

Rhodium and Isothiourea Dual Catalysis: Enantiodivergent Transformation of Terminal Alkynes.

A dual rhodium/isothiourea catalytic system was developed for the enantiodivergent transformation of terminal alkynes. Under synergistic rhodium/isothiourea dual catalysis, terminal alkynes can be creatively utilized as precursors for C1-ammonium enolate species, which subsequently participate in [4 + 2] and [2 + 2] annulation reactions with α,ß-unsaturated ketimines or ketones, respectively. A wide range of chiral lactams and lactones were obtained in excellent yields and stereoselectivities (up to >20:1 dr, 98% ee).

The effects of pks+ Escherichia coli and bile acid in colorectal tumorigenesis among people with cholelithiasis or cholecystectomy.

BACKGROUND AND AIM: Patients with cholelithiasis (CL) or cholecystectomy (CE) would have more chances of getting colorectal adenoma (CRA) or cancer (CRC). We aimed to figure out the effects of gut microbiota and bile acid on colorectal neoplasm in CL and CE patients. METHODS: This was a retrospective observational study that recruited 514 volunteers, including 199 people with normal gallbladders (normal), 152 CL, and 163 CE patients. Discovery cohort was established to explore the difference in gut microbiota through 16S rRNA and metagenomics sequencing. Validation cohort aimed to verify the results through quantitative polymerase chain reaction (qPCR). RESULTS: Significant enrichment of Escherichia coli was found in patients with cholelithiasis or cholecystectomy both in the discovery cohort (16S rRNA sequencing, PNormal-CL  = 0.013, PNormal-CE  = 0.042; metagenomics sequencing, PNormal-CE  = 0.026) and validation cohort (PNormal-CL  < 0.0001, PNormal-CE  < 0.0001). Pks+ E. coli was found enriched in CL and CE patients through qPCR (in discovery cohort: PNormal-CE  = 0.018; in validation cohort: PNormal-CL  < 0.0001, PNormal-CE  < 0.0001). The differences in bile acid metabolism were found both through Tax4Fun analysis of 16S rRNA sequencing (Ko00120, primary bile acid biosynthesis, PNormal-CE  = 0.014; Ko00121, secondary bile acid biosynthesis, PNormal-CE  = 0.010) and through metagenomics sequencing (map 00121, PNormal-CE  = 0.026). The elevation of serum total bile acid of CE patients was also found in validation cohort (PNormal-CE  < 0.0001). The level of serum total bile acid was associated with the relative abundance of pks+ E. coli (r = 0.1895, P = 0.0012). CONCLUSIONS: E. coli, especially pks+ species, was enriched in CL and CE patients. Pks+ E. coli and bile acid metabolism were found associated with CRA and CRC in people after cholecystectomy.