Screen-Printed Electrodes as Low-Cost Sensors for Breast Cancer Biomarker Detection.

This review explores the emerging role of screen-printed electrodes (SPEs) in the detection of breast cancer biomarkers. We discuss the fundamental principles and fabrication techniques of SPEs, highlighting their adaptability and cost-effectiveness. The review examines various modification strategies, including nanomaterial incorporation, polymer coatings, and biomolecule immobilization, which enhance sensor performance. We analyze the application of SPEs in detecting protein, genetic, and metabolite biomarkers associated with breast cancer, presenting recent advancements and innovative approaches. The integration of SPEs with microfluidic systems and their potential in wearable devices for continuous monitoring are explored. While emphasizing the promising aspects of SPE-based biosensors, we also address current challenges in sensitivity, specificity, and real-world applicability. The review concludes by discussing future perspectives, including the potential for early screening and therapy monitoring, and the steps required for clinical implementation. This comprehensive overview aims to stimulate further research and development in SPE-based biosensors for improved breast cancer management.

Global marine microbial diversity and its potential in bioprospecting.

The past two decades has witnessed a remarkable increase in the number of microbial genomes retrieved from marine systems1,2. However, it has remained challenging to translate this marine genomic diversity into biotechnological and biomedical applications3,4. Here we recovered 43,191 bacterial and archaeal genomes from publicly available marine metagenomes, encompassing a wide range of diversity with 138 distinct phyla, redefining the upper limit of marine bacterial genome size and revealing complex trade-offs between the occurrence of CRISPR-Cas systems and antibiotic resistance genes. In silico bioprospecting of these marine genomes led to the discovery of a novel CRISPR-Cas9 system, ten antimicrobial peptides, and three enzymes that degrade polyethylene terephthalate. In vitro experiments confirmed their effectiveness and efficacy. This work provides evidence that global-scale sequencing initiatives advance our understanding of how microbial diversity has evolved in the oceans and is maintained, and demonstrates how such initiatives can be sustainably exploited to advance biotechnology and biomedicine.

Dissolved organic matter (DOM) rather than warming and eutrophication directly affects partial pressure of CO2 (pCO2) in mesocosm systems.

Environmental warming and eutrophication pose significant challenges to shallow lake systems, where dissolved organic matter (DOM) serves as a diverse and intricate mixture of organic macromolecules, playing a pivotal role in aquatic ecosystems. Despite its complexity, comprehending the interplay between environmental changes and DOM composition alterations and their subsequent impacts on aqueous CO2 partial pressure (pCO2) is essential for a better understanding of carbon cycling. Yet, our current understanding in this realm remains limited. To address this gap, mesocosm systems were established to investigate how elevated water temperature and eutrophication, alongside changes in DOM composition, influence pCO2 dynamics. Results indicate that while temperature and nutrient levels do not directly influence pCO2 fluctuations, they indirectly affect aqueous pCO2 through their modulation of DOM composition. Elevated temperature and nutrient concentrations notably enhance both the production and degradation of indigenous protein-like organic matter and increase the accumulation of humic-like organic compounds, with phosphorus released from sediment playing a particularly significant role. Furthermore, the degradation rate of protein-like organic matter significantly exceeds its accumulation rate. On the other hand, the impact of water eutrophication on DOM composition surpasses that of temporal temperature variations, with a 2∼4 °C temperature rise showing minimal effects on DOM composition. Notably, the degradation of protein-like organic matter markedly increases aqueous pCO2, while the rise in humic-like organic matter in water exerts minimal influence on pCO2 concentrations. A comprehensive understanding of carbon cycling processes under environmental changes will facilitate effective management of lake ecosystems and the advancement of carbon mitigation technologies.

Eutrophication constrains driving forces of dissolved organic carbon biodegradation in metropolitan lake systems.

Dissolved organic carbon (DOC) components can be highly variable in aquatic ecosystems, and play a pivotal role in the global carbon cycles. To comprehend potential effects of nutrient enrichment on portion of DOC biodegradability (%BDOC), we conducted an extensive investigation on 26 urban lakes in a major metropolitan area in subtropical China in a small gradient of trophic levels from mesotrophic to light and middle eutrophic. In addition to field measurements on lake ambient conditions and laboratory analysis of DOC characteristics, we conducted a 28-day temperature-controlled incubation experiment, in which %BDOC of lake waters was determined. In the mesotrophic waters, %BDOC ranged from 0.6 to 41.4 % (11.2 ± 8.9 %). The %BDOC levels spanned from 5.2 to 20.2 % (10.7 ± 4.0 %) in the light eutrophic waters, and the %BDOC ranged from 2.7 to 35.0 % (13.7 ± 8.4 %) in the middle eutrophic waters. We found a significant change in DOC chemical composition across the study lakes characterized by shifting of trophic levels. Although the experiment found significant changes in the factors that can influence %BDOC, a significant difference was not observed in %BDOC among the three trophic levels. The %BDOC was primarily influenced by the inherent DOC concentration and aromaticity, with eutrophication leading to the varied driving factors of %BDOC in lake systems. We show that most of the lake water DOC was stable. The findings indicate the intricate interplay between biological metabolism and nutrient availability governing %BDOC dynamics in urban lake ecosystems.

Multilevel network for large deformation image registration based on feature consistency and flow normalization.

BACKGROUND: Deformable image registration is an essential technique of medical image analysis, which plays important roles in several clinical applications. Existing deep learning-based registration methods have already achieved promising performance for the registrations with small deformations, while it is still challenging to deal with the large deformation registration due to the limits of the image intensity-similarity-based objective function. PURPOSE: To achieve the image registration with large-scale deformations, we proposed a multilevel network architecture FCNet to gradually refine the registration results based on semantic feature consistency constraint and flow normalization (FN) strategy. METHODS: At each level of FCNet, the architecture is mainly composed to a FeaExtractor, a FN module, and a spatial transformation module. FeaExtractor consists of three parallel streams which are used to extract the individual features of fixed and moving images, as well as their joint features, respectively. Using these features, the initial deformation field is estimated, which passes through a FN module to refine the deformation field based on the difference map of deformation filed between two adjacent levels. This allows the FCNet to progressively improve the registration performance. Finally, a spatial transformation module is used to get the warped image based on the deformation field. Moreover, in addition to the image intensity-similarity-based objective function, a semantic-feature consistency constraint is also introduced, which can further promote the alignments by imposing the similarity between the fixed and warped image features. To validate the effectiveness of the proposed method, we compared our method with the state-of-the-art methods on three different datasets. In EMPIRE10 dataset, 20, 3, and 7 fixed and moving 3D computer tomography (CT) image pairs were used for training, validation, and testing respectively; in IXI dataset, atlas to individual image registration task was performed, with 3D MR images of 408, 58, and 115 individuals were used for training, validation, and testing respectively; in the in-house dataset, patient to atlas registration task was implemented, with the 3D MR images of 94, 3, and 15 individuals being training, validation, and testing sets, respectively. RESULTS: The qualitative and quantitative comparison results demonstrated that the proposed method is beneficial for handling large deformation image registration problems, with the DSC and ASSD improved by at least 1.0% and 25.9% on EMPIRE10 dataset. The ablation experiments also verified the effectiveness of the proposed feature combination strategy, feature consistency constraint, and FN module. CONCLUSIONS: Our proposed FCNet enables multiscale registration from coarse to fine, surpassing existing SOTA registration methods and effectively handling long-range spatial relationships.

Comparative Analysis of Gene Expression Profiles in Ovarian Clear Cell Carcinoma and High-Grade Serous Ovarian Cancer.

OBJECTIVE: To evaluate disparities in gene expression profiles between Ovarian Clear Cell Carcinoma (OCCC) and High-Grade Serous Ovarian Carcinoma (HGSOC). STUDY DESIGN: A descriptive study. Place and Duration of the Study: The Second People's Hospital of Jingdezhen, Jiangxi, China, between 31st December 2017 and December 2023. METHODOLOGY: Basic and clinical diagnostic information, along with genetic test reports, were compiled from all patients within the included groups. Differential gene expression between the two cohorts was scrutinised to elucidate its clinical significance. RESULTS: Comparative analysis revealed nine differentially expressed genes in OCCC relative to HGSOC, with six exhibiting significant disparities (p <0.05). These genes are implicated in pivotal cellular processes including the cell cycle, apoptosis, DNA damage repair, and the PI3K pathway. Notably, aberrant expression patterns, such as overexpression of MET and downregulation of PTEN and SMARCA4, correlated with adverse prognosis and survival outcomes in selected patients. CONCLUSION: Distinctive gene expression profiles between OCCC and HGSOC underscore disparate tumorigenic mechanisms, thereby laying a foundation for the tailored therapeutic interventions. Further elucidation of the identified differentially expressed genes is warranted to delineate their role in OCCC pathogenesis and prognostic significance. KEY WORDS: Ovarian clear cell carcinoma, High-grade serous ovarian cancer, Gene expression profiles, Homologous recombination repair.

IVIM parameters mapping with artificial neural network based on mean deviation prior.

BACKGROUND: The diffusion and perfusion parameters derived from intravoxel incoherent motion (IVIM) imaging provide promising biomarkers for noninvasively quantifying and managing various diseases. Nevertheless, due to the distribution gap between simulated and real datasets, the out-of-distribution (OOD) problem occurred in supervised learning-based methods degrades their performance and hinders their real applications. PURPOSE: To address the OOD problem in supervised methods and to further improve the accuracy and stability of IVIM parameter estimation, this work proposes a novel learning framework called IterANN, based on mean deviation prior (MDP) between training and estimated IVIM parameters on the test set. METHODS: Specifically, MDP indicates that the mean of the estimated IVIM parameters always locates between the mean of IVIM parameters in the test and train sets. In IterANN, we adopt a very simple artificial neural network (ANN) architecture of two hidden layers with 12 neurons per hidden layer, an input layer containing the signals acquired at multiple b-values and an output layer composed of three IVIM parameters ( D $D$ , F $F$ and D S t a r $DStar$ ). Inspired by MDP, the distribution of IVIM parameters in the training set (simulated data) is iteratively updated so that their mean gradually approaches the predicted values of the real data. This aims to achieve a strong correlation between the simulated data and the real data. To validate the effectiveness of IterANN, we compare it with several methods on both simulation and real acquisition datasets, including 21 healthy and 3 tumor subjects, in terms of residual errors of IVIM parameters or DW signals, the coefficients of variation (CV) of IVIM parameters, and the parameter contrast-to-noise ratio (PCNR) between normal and tumor tissues. RESULTS: On two simulation datasets, the proposed IterANN achieves the lowest residual error in IVIM parameters, especially in the case of low signal-to-noise ratio (SNR = 10), the residual error of D $D$ , F $F$ and D S t a r $DStar$ is decreased by 15.82 % / 14.92 % , 81.19 % / 74.04 % , 50.77 % / 1.549 % $15.82\%/14.92\%, 81.19\%/74.04\%, 50.77\%/1.549\%$ (Gaussian distribution /realistic distribution) respectively comparing to the suboptimal method. On real dataset, the IterANN achieves the highest PCNR when comparing the normal and tumor regions. Additionally, the proposed IterANN demonstrated better stability, with its CV being significantly lower than that of other methods in the vast majority of cases ( p < 0.01 $p<0.01$ , paired-sample Student's t-test). CONCLUSIONS: The superior performance of IterANN demonstrates that updating the distribution of the train set based on MDP can effectively solve the OOD problem, which allows us not only to improve the accuracy and stability of the estimated IVIM parameters, but also to increase the potential of IVIM in disease diagnosis.

To explore the postoperative nutritional status and factors influencing prognosis in patients with chronic constipation complicated by malnutrition.

Background: Many patients with constipation also suffer from varying degrees of malnutrition, and the relationship between the two conditions is a vicious cycle. Surgery is the final step in the treatment of constipation, with a success rate of up to 95%. This study aims to investigate the effects of surgical treatment on the nutritional status of patients with chronic constipation and malnutrition. Methods: A total of 60 patients with chronic constipation and various degrees of malnutrition who underwent surgery in our department from January 2020 to March 2023 were included in this study. Biochemical tests including BMI, albumin, total protein, hemoglobin, cholesterol and lymphocyte count were conducted, as well as measurements of inflammatory markers such as Interleukin-6 (IL-6), Interleukin-8 (IL-8), and C-reactive protein (CRP). Additionally, multiple nutritional risk screening scales (NRS2002, MUST, NRI, and MNA) and the prognostic nutritional index (PNI) were used to assess the nutritional status of patients before surgery, as well as at 1 month, 3 months, and 6 months post-surgery. Finally, we analyzed the factors influencing postoperative recovery outcomes in patients. Results: Compared to pre-operation, the BMI of patients significantly increased at 1 month, 3 months, and 6 months after the operation, with statistically significant differences (p < 0.001). Multiple nutritional risk assessment tools (NRS2002, MUST, NRI, and MNA), as well as the prognostic nutritional index (NPI), indicated a reduction in nutritional risk and improvement in nutritional status at 1, 3, and 6 months post-surgery, compared to pre-surgery levels (p < 0.001). The levels of albumin, total protein, and hemoglobin in patients at 1, 3, and 6 months after the surgery were significantly higher than those before the surgery (p < 0.001). However, there was no significant change in the number of lymphocytes. Inflammatory markers such as IL-6, IL-8, and CRP exhibited a significant decrease after the surgery, reaching normal levels at 6 months post-surgery (p < 0.001). Low BMI, low PNI, and low cholesterol levels are independent risk factors for patient prognosis (p < 0.05). Conclusion: Surgical treatment can enhance the nutritional status of constipation patients with malnutrition, which in turn promotes the restoration of intestinal motility. The patient's nutritional status will impact the postoperative recovery outcomes.

Deep learning method with integrated invertible wavelet scattering for improving the quality ofin vivocardiac DTI.

Objective.Respiratory motion, cardiac motion and inherently low signal-to-noise ratio (SNR) are major limitations ofin vivocardiac diffusion tensor imaging (DTI). We propose a novel enhancement method that uses unsupervised learning based invertible wavelet scattering (IWS) to improve the quality ofin vivocardiac DTI.Approach.Our method starts by extracting nearly transformation-invariant features from multiple cardiac diffusion-weighted (DW) image acquisitions using multi-scale wavelet scattering (WS). Then, the relationship between the WS coefficients and DW images is learned through a multi-scale encoder and a decoder network. Using the trained encoder, the deep features of WS coefficients of multiple DW image acquisitions are further extracted and then fused using an average rule. Finally, using the fused WS features and trained decoder, the enhanced DW images are derived.Main result.We evaluate the performance of the proposed method by comparing it with several methods on threein vivocardiac DTI datasets in terms of SNR, contrast to noise ratio (CNR), fractional anisotropy (FA), mean diffusivity (MD) and helix angle (HA). Comparing against the best comparison method, SNR/CNR of diastolic, gastric peristalsis influenced, and end-systolic DW images were improved by 1%/16%, 5%/6%, and 56%/30%, respectively. The approach also yielded consistent FA and MD values and more coherent helical fiber structures than the comparison methods used in this work.Significance.The ablation results verify that using the transformation-invariant and noise-robust wavelet scattering features enables us to effectively explore the useful information from the limited data, providing a potential mean to alleviate the dependence of the fusion results on the number of repeated acquisitions, which is beneficial for dealing with the issues of noise and residual motion simultaneously and therefore improving the quality ofinvivocardiac DTI. Code can be found inhttps://github.com/strawberry1996/WS-MCNN.

Multi-modal evaluation of respiratory diaphragm motion in chronic obstructive pulmonary disease using MRI series and CT images.

PURPOSE: Chronic obstructive pulmonary disease (COPD), characterized by airflow limitation and breathing difficulty, is usually caused by prolonged inhalation of toxic substances or long-term smoking habits. Some abnormal features of COPD can be observed using medical imaging methods, such as magnetic resonance imaging (MRI) and computed tomography (CT). This study aimed to conduct a multi-modal analysis of COPD, focusing on assessing respiratory diaphragm motion using MRI series in conjunction with low attenuation volume (LAV) data derived from CT images. MATERIALS AND METHOD: This study utilized MRI series from 10 normal subjects and 24 COPD patients, along with thoracic CT images from the same patients. Diaphragm profiles in the sagittal thoracic MRI series were extracted using field segmentation, and diaphragm motion trajectories were generated from estimated diaphragm displacements via registration. Re-sliced sagittal CT images were used to calculate regional LAVs for four distinct lung regions. The similarities among diaphragm motion trajectories at various positions were assessed, and their correlations with regional LAVs were analyzed. RESULTS: Compared with the normal subjects, patients with COPD typically exhibited fewer similarities in diaphragm motion, as indicated by the mean normalized correlation coefficient of the vertical motion component (0.96 for normal subjects vs. 0.76 for severity COPD patients). This reduction was significantly correlated with the LAV% in the two lower lung regions with a regression coefficient of 0.81. CONCLUSION: Our proposed evaluation method may assist in the diagnosis and therapy planning for patients with COPD.

Anti-seasonal flooding drives substantial alterations in riparian plant diversity and niche characteristics in a unique hydro-fluctuation zone.

Human-induced disturbances such as dam construction and regulation have led to widespread alterations in hydrological processes and thus substantially influence plant characteristics in the hydro-fluctuation zones (HFZs). To reveal utilization of limited resources and mechanisms of inter-specific competition and species co-existence of plant communities based on niche breadth and overlap under the different HFZs of the Three Gorges Reservoir (TGR) in China, we conducted a field investigation with 368 quadrats on the effects of hydrological alterations on plant diversity and niche characteristics. The results showed anti-seasonal flooding precipitated the gradual disappearance of the original diverse niches, resulting in the reduction of plant species richness and functional diversity and more obvious competition among plant species with similar resource requirements. Annuals, perennials and shrubs accounted for 71.23%, 27.39% and 1.37%, respectively, suggesting that annuals and flood-tolerant riparian herbs were favored under such novel flooding conditions. A consistent increase in species number, Shannon-Wiener diversity index and Simpson dominance index with altitude was inconsistent with hump-shaped diversity-disturbance relationship of the intermediate disturbance hypothesis, while the opposite trend was observed for the Pielou evenness index. This species distribution pattern might be caused by several synergetic attributes (e.g., the submergence depth, plant tolerant capacity to flooding, life form, dispersal mode and inter-specific competition). Vegetation types shifted from xerophytes to mesophytes and eventually to hygrophytes with the increasing flooding time in the HFZs. Hydrological alterations proved to be the paramount driver of vegetation distribution in the different HFZs. The niche analysis provided the first insights on the mechanisms of resource utilization and inter-specific competition, of which annuals could germinate quickly after soil drainage to achieve the greatest competitive advantages and occupy a larger niche space than other plants. Vegetation was still in the early stage of primary succession in the novel riparian forests. Therefore, vegetation restoration strategies should be biased towards herbaceous plants, due to annuals with better environmental adaptability, supplemented by shrubs and small trees. To establish a complete reference system for vegetation restoration, natural vegetation monitory plots in the different succession stages should be established in the different HFZs of the TGR, and their environmental conditions, community structures and inter-specific relationships further analyzed.

Facial Symmetry Enhancement and Brain Network Modifications in Surgical Facial Palsy Patients After BoNT-A Treatment on the Unaffected Side.

BACKGROUND: Facial palsy, often resulting from trauma or iatrogenic treatments, leads to significant esthetic and functional impairment. Surgical interventions, such as masseteric-to-facial nerve transfer combined with static suspension, are frequently recommended to restore facial nerve function and symmetry. METHODS: This study examines how Botulinum Toxin A (BoNT-A) treatment on the unaffected side affects facial symmetry and brain connectivity in patients with severe oral commissure droop from facial nerve damage. Patients were divided into two groups: one received BoNT-A injections on the unaffected side, and the other did not. RESULTS: Our findings revealed that BoNT-A treatment not only improved facial symmetry but also induced significant modifications in brain functional network connectivity. These modifications extended beyond the sensorimotor network, involving high-level cognitive processes, and exhibited a significant correlation with the degree of facial asymmetry. CONCLUSIONS: These results provide valuable insights into the mechanisms underlying the positive effects of BoNT-A intervention on motor recovery and brain plasticity in facial palsy patients. Furthermore, the study emphasizes the importance of a multidisciplinary approach to facial palsy rehabilitation. Understanding these intricate interactions between facial symmetry restoration and brain network adaptations may pave the way for more effective treatments and improved quality of life for individuals dealing with facial palsy.

Spin-related excited-state phenomena in photochemistry.

The spin of electrons plays a vital role in chemical reactions and processes, and the excited state generated by the absorption of photons shows abundant spin-related phenomena. However, the importance of electron spin in photochemistry studies has been rarely mentioned or summarized. In this review, we briefly introduce the concept of spin photochemistry based on the spin multiplicity of the excited state, which leads to the observation of various spin-related photophysical properties and photochemical reactivities. Then, we focus on the recent advances in terms of light-induced magnetic properties, excited-state magneto-optical effects and spin-dependent photochemical reactions. The review aims to provide a comprehensive overview to utilize the spin multiplicity of the excited state in manipulating the above photophysical and photochemical processes. Finally, we discuss the existing challenges in the emerging field of spin photochemistry and future opportunities such as smart magnetic materials, optical information technology and spin-enhanced photocatalysis.

Enhanced Electrochemical Sensing of Oxalic Acid Based on VS2 Nanoflower-Decorated Glassy Carbon Electrode Prepared by Hydrothermal Method.

Oxalic acid (OA) is a predominant constituent in kidney stones, contributing to 70-80% of all cases. Rapid detection of OA is vital for the early diagnosis and treatment of kidney stone conditions. This work introduces a novel electrochemical sensing approach for OA, leveraging vanadium disulfide (VS2) nanoflowers synthesized via hydrothermal synthesis. These VS2 nanoflowers, known for their excellent electrocatalytic properties and large surface area, are used to modify glassy carbon electrodes for enhanced OA sensing. The proposed OA sensor exhibits high sensitivity and selectivity across a wide linear detection range of 0.2-20 µM, with an impressively low detection limit of 0.188 µM. The practicality of this sensor was validated through interference studies, offering a promising tool for the early diagnosis and monitoring of kidney stone diseases.

FoxO transcription factors regulate urea cycle through Ass1.

When amino acids are plentiful in the diet, the liver upregulates most enzymes responsible for amino acid degradation. In particular, the activity of urea cycle enzymes increases in response to high-protein diets to facilitate the excretion of excess nitrogen. KLF15 has been established as a critical regulator of amino acid catabolism including ureagenesis and we have recently identified FoxO transcription factors as an important upstream regulator of KLF15 in the liver. Therefore, we explored the role of FoxOs in amino acid metabolism under high-protein diet. Our findings revealed that the concentrations of two urea cycle-related amino acids, arginine and ornithine, were significantly altered by FoxOs knockdown. Additionally, using KLF15 knockout mice and an in vivo Ad-luc analytical system, we confirmed that FoxOs directly regulate hepatic Ass1 expression under high-protein intake independently from KLF15. Moreover, ChIP analysis showed that the high-protein diet increased FoxOs DNA binding without altering the nuclear protein amount. Therefore, FoxOs play a direct role in regulating ureagenesis via a KLF15-independent pathway in response to high-protein intake.

The impact of small intestinal bacterial overgrowth on the efficacy of fecal microbiota transplantation in patients with chronic constipation.

To investigate the impact of Small Intestinal Bacterial Overgrowth (SIBO) on the efficacy of Fecal Microbiota Transplantation (FMT) in patients with chronic constipation, our research team included 218 patients with chronic constipation treated with FMT. Based on the results of the SIBO breath test, the patients were divided into two groups: the constipation with SIBO group (SIBO) and the constipation without SIBO group (non-SIBO). The efficacy of the two groups was evaluated using constipation-related scoring scales. At the same time, feces and small intestinal fluid samples were collected from both groups before and after FMT to compare the changes in the intestinal microbiota through 16S rRNA sequencing. In this study, it was found that the clinical efficacy of FMT in the SIBO group was superior to that in the non-SIBO group. After FMT treatment, both groups showed a significant increase in bowel frequency and improvement in stool characteristics. Abdominal symptoms, rectal symptoms, and defecation symptoms were significantly alleviated (P < 0.05), and patients' quality of life was significantly enhanced (P < 0.05). After FMT, except for the Constipation Assessment Scale scores, other scale scores showed significant differences between the two groups, the SIBO group scoring significantly better than the non-SIBO group (P < 0.05). After FMT, there were minor changes in the colonic microbiota but more substantial changes in the small intestinal microbiota. At baseline, the SIBO group had a higher abundance of Veillonella, and lower abundances of Escherichia-Shigella and Acinetobacter compared to the non-SIBO group. Chronic constipation patients with SIBO have a better response to FMT than those without SIBO. IMPORTANCE: Existing studies have rarely considered the impact of the small intestine's microbial state on the efficacy of fecal microbiota transplantation (FMT), nor have they extensively explored the effect of the small intestine's microbial state on the recovery of colonic motility. Therefore, this study investigates the influence of small intestinal bacterial overgrowth (SIBO) on the efficacy of FMT in treating constipation, specifically the impact of the microbial state of the small intestine on the restoration of colonic homeostasis, and consequently on the recovery of colonic motility.

The Regulatory Impact of CFLAR Methylation Modification on Liver Lipid Metabolism.

Non-alcoholic fatty liver disease (NAFLD) has emerged as the leading cause of chronic liver disease worldwide. Caspase 8 and FADD-like apoptosis regulator (CFLAR) has been identified as a potent factor in mitigating non-alcoholic steatohepatitis (NASH) by inhibiting the N-terminal dimerization of apoptosis signal-regulating kinase 1 (ASK1). While arginine methyltransferase 1 (PRMT1) was previously reported to be associated with increased hepatic glucose production, its involvement in hepatic lipid metabolism remains largely unexplored. The interaction between PRMT1 and CFLAR and the methylation of CFLAR were verified by Co-IP and immunoblotting assays. Recombinant adenoviruses were generated for overexpression or knockdown of PRMT1 in hepatocytes. The role of PRMT1 in NAFLD was investigated in normal and high-fat diet-induced obese mice. In this study, we found a significant upregulation of PRMT1 and downregulation of CFLAR after 48h of fasting, while the latter significantly rebounded after 12h of refeeding. The expression of PRMT1 increased in the livers of mice fed a methionine choline-deficient (MCD) diet and in hepatocytes challenged with oleic acid (OA)/palmitic acid (PA). Overexpression of PRMT1 not only inhibited the expression of genes involved in fatty acid oxidation (FAO) and promoted the expression of genes involved in fatty acid synthesis (FAS), resulting in increased triglyceride accumulation in primary hepatocytes, but also enhanced the gluconeogenesis of primary hepatocytes. Conversely, knockdown of hepatic PRMT1 significantly alleviated MCD diet-induced hepatic lipid metabolism abnormalities and liver injury in vivo, possibly through the upregulation of CFLAR protein levels. Knockdown of PRMT1 suppressed the expression of genes related to FAS and enhanced the expression of genes involved in FAO, causing decreased triglyceride accumulation in OA/PA-treated primary hepatocytes in vitro. Although short-term overexpression of PRMT1 had no significant effect on hepatic triglyceride levels under physiological conditions, it resulted in increased serum triglyceride and fasting blood glucose levels in normal C57BL/6J mice. More importantly, PRMT1 was observed to interact with and methylate CFLAR, ultimately leading to its ubiquitination-mediated protein degradation. This process subsequently triggered the activation of c-Jun N-terminal kinase 1 (JNK1) and lipid deposition in primary hepatocytes. Together, these results suggested that PRMT1-mediated methylation of CFLAR plays a critical role in hepatic lipid metabolism. Targeting PRMT1 for drug design may represent a promising strategy for the treatment of NAFLD.

Bacterial exonuclease III expands its enzymatic activities on single-stranded DNA.

Bacterial exonuclease III (ExoIII), widely acknowledged for specifically targeting double-stranded DNA (dsDNA), has been documented as a DNA repair-associated nuclease with apurinic/apyrimidinic (AP)-endonuclease and 3'→5' exonuclease activities. Due to these enzymatic properties, ExoIII has been broadly applied in molecular biosensors. Here, we demonstrate that ExoIII (Escherichia coli) possesses highly active enzymatic activities on ssDNA. By using a range of ssDNA fluorescence-quenching reporters and fluorophore-labeled probes coupled with mass spectrometry analysis, we found ExoIII cleaved the ssDNA at 5'-bond of phosphodiester from 3' to 5' end by both exonuclease and endonuclease activities. Additional point mutation analysis identified the critical residues for the ssDNase action of ExoIII and suggested the activity shared the same active center with the dsDNA-targeted activities of ExoIII. Notably, ExoIII could also digest the dsDNA structures containing 3'-end ssDNA. Considering most ExoIII-assisted molecular biosensors require the involvement of single-stranded DNA (ssDNA) or nucleic acid aptamer containing ssDNA, the activity will lead to low efficiency or false positive outcome. Our study revealed the multi-enzymatic activity and the underlying molecular mechanism of ExoIII on ssDNA, illuminating novel insights for understanding its biological roles in DNA repair and the rational design of ExoIII-ssDNA involved diagnostics.