ATGL mediated adipocyte lipolysis exacerbates acute pancreatitis severity in mouse models and patients.

Dyslipolysis of adipocytes has played a critical role in various diseases. Adipose triglyceride lipase (ATGL) is a rate-limiting enzyme in adipocyte autonomous lipolysis. However, whether the degree of adipocyte lipolysis relates to the prognoses in acute pancreatitis (AP) and the role of ATGL mediated lipolysis in the pathogenesis of AP remains elusive. The visceral adipose tissue (VAT) consumption rate (VATR) in the acute stage was measured in both AP patients and mouse models. Lipolysis levels and ATGL expression were detected in caerulein (CER)-induced AP models. CL316,243, a lipolysis stimulator, and adipose tissue-specific ATGL knockout (AAKO) mice were used to further investigate the role of lipolysis in AP. The ATGL-specific inhibitor, Atglistatin, was performed in C57Bl/6N and ob/ob AP models. This study found that increased VATR in the acute phase was independently associated with adverse prognoses in AP patients, which was validated in mice AP models. Lipolysis of adipocytes was elevated in AP mice. Stimulation of lipolysis could aggravate AP. Genetic blockage of ATGL specifically in adipocytes was able to alleviate the damage to AP. The application of Atglistatin could effectively protect against AP in both lean and obese mice. These findings demonstrated that ATGL-mediated adipocyte lipolysis exacerbates AP and highlighted the therapeutic potential of ATGL as a drug target for AP.

Global One Health index for zoonoses: A performance assessment in 160 countries and territories.

The One Health (OH) approach is used to control/prevent zoonotic events. However, there is a lack of tools for systematically assessing OH practices. Here, we applied the Global OH Index (GOHI) to evaluate the global OH performance for zoonoses (GOHI-Zoonoses). The fuzzy analytic hierarchy process algorithm and fuzzy comparison matrix were used to calculate the weights and scores of five key indicators, 16 subindicators, and 31 datasets for 160 countries and territories worldwide. The distribution of GOHI-Zoonoses scores varies significantly across countries and regions, reflecting the strengths and weaknesses in controlling or responding to zoonotic threats. Correlation analyses revealed that the GOHI-Zoonoses score was associated with economic, sociodemographic, environmental, climatic, and zoological factors. Additionally, the Human Development Index had a positive effect on the score. This study provides an evidence-based reference and guidance for global, regional, and country-level efforts to optimize the health of people, animals, and the environment.

Predictive value of the domain specific PLA2R antibodies for clinical remission in patients with primary membranous nephropathy: A retrospective study.

BACKGROUND: M-type phospholipase A2 receptor (PLA2R) is a major auto-antigen of primary membranous nephropathy(PMN). Anti-PLA2R antibody levels are closely associated with disease severity and therapeutic effectiveness. Analysis of PLA2R antigen epitope reactivity may have a greater predictive value for remission compared with total PLA2R-antibody level. This study aims to elucidate the relationship between domain-specific antibody levels and clinical outcomes of PMN. METHODS: This retrospective analysis included 87 patients with PLA2R-associated PMN. Among them, 40 and 47 were treated with rituximab (RTX) and cyclophosphamide (CTX) regimen, respectively. The quantitative detection of -immunoglobulin G (IgG)/-IgG4 targeting PLA2R and its epitope levels in the serum of patients with PMN were obtained through time-resolved fluorescence immunoassays and served as biomarkers in evaluating the treatment effectiveness. A predictive PMN remission possibility nomogram was developed using multivariate logistic regression analysis. Discrimination in the prediction model was assessed using the area under the receiver operating characteristic curve (AUC-ROC).Bootstrap ROC was used to evaluate the performance of the prediction model. RESULTS: After a 6-month treatment period, the remission rates of proteinuria, including complete remission and partial remission in the RTX and CTX groups, were 70% and 70.21% (P = 0.983), respectively. However, there was a significant difference in immunological remission in the PLA2R-IgG4 between the RTX and CTX groups (21.43% vs. 61.90%, P = 0.019). Furthermore, we found differences in PLA2R-CysR-IgG4(P = 0.030), PLA2R-CTLD1-IgG4(P = 0.005), PLA2R-CTLD678-IgG4(P = 0.003), and epitope spreading (P = 0.023) between responders and non-responders in the CTX group. Multivariate logistic analysis showed that higher levels of urinary protein (odds ratio [OR], 0.49; 95% confidence interval [CI], 0.26-0.95; P = 0.035) and higher levels of PLA2R-CTLD1-IgG4 (OR, 0.79; 95%CI,0.62-0.99; P = 0.041) were independent risk factors for early remission. A multivariate model for estimating the possibility of early remission in patients with PMN is presented as a nomogram. The AUC-ROC of our model was 0.721 (95%CI, 0.601-0.840), in consistency with the results obtained with internal validation, for which the AUC-ROC was 0.711 (95%CI, 0.587-0.824), thus, demonstrating robustness. CONCLUSIONS: Cyclophosphamide can induce immunological remission earlier than rituximab at the span of 6 months. The PLA2R-CTLD1-IgG4 has a better predict value than total PLA2R-IgG for remission of proteinuria at the 6th month.

Cell-specific localization of ß-synuclein in the mouse retina.

ß-synuclein, a member of the synuclein family, is frequently co-expressed with α-synuclein in the neural system, where it serves to inhibit abnormal aggregation of α-synuclein in neurodegenerative diseases. Beyond its role in pathological conditions, ß-synuclein plays various functions independently of α-synuclein. In our investigation, we discovered a broader expression of ß-synuclein in the mouse retina compared to α-synuclein. This widespread pattern implies its potential significance in the retina. Through detailed examination via light- and electron-microscopic immunocytochemistry, we identified ß-synuclein expression from the inner segment (IS) and outer segment (OS) of photoreceptor cells to the ganglion cell layer (GCL). Our findings unveiled unique features, including ß-synuclein immunoreactive IS and OS of cones, higher expression in cone pedicles than in rod spherules, absence in horizontal cells, limited expression in cone bipolar dendrites and somas, higher expression in cone bipolar terminals, presence in most amacrine cells, and expression in almost majority of somas in GCL with an absence in intrinsically photosensitive retinal ganglion cell (ipRGCs) processes. Notably, all cholinergic amacrine cells express high ß- but not α-synuclein, while dopaminergic amacrine cells express α-synuclein exclusively. These distinctive expression patterns offer valuable insights for further exploration into the functions of ß-synuclein and its potential role in synuclein pathology within the retina.

Deciphering the pancreatic cancer microbiome in Mainland China: Impact of Exiguobacterium/Bacillus ratio on tumor progression and prognostic significance.

The existing body of research underscores the critical impact of intratumoral microbiomes on the progression of pancreatic ductal adenocarcinoma (PDAC), particularly in reshaping the tumor microenvironment and influencing gemcitabine resistance. However, peritumoral tissues' microbiome, distinct from PDAC tumors, remain understudied, and Western-centric analyses overlooking potential variations in dietary-influenced microbiomes. Our study addresses this gap by 16 S rRNA sequencing of PDAC tumors and matched peritumoral tissues from Chinese Mainland patients. Our research has uncovered that the microbiome composition within tumors and paired peritumoral tissues exhibits a high degree of similarity, albeit with certain discrepancies. Notably, Exiguobacterium is found to be more abundant within the tumor tissues. Further investigations have revealed that a lower Exiguobacterium/Bacillus ratio in both the tumor and peritumoral tissues of PDAC patients is indicative of a more favorable prognosis. Further exploration utilizing an orthotopic tumor model demonstrates that the probiotic Bacillus Coagulans impedes PDAC progression, accompanied by an increased infiltration of inflammatory neutrophils in tumors. Additionally, in the subgroup with a low Exiguobacterium/Bacillus ratio, whole-exome sequencing reveals elevated missense mutations in ABL2 and MSH2. The elevated expression of ABL2 and MSH2 has been correlated with poorer prognostic outcomes in PDAC patients. Together, these insights shed light on risk factors influencing PDAC progression and unveil potential therapeutic targets, alongside probiotic intervention strategies.

Great genetic diversity of vector-borne bacteria and protozoan in wild rodents from Guangxi, China.

BACKGROUND: Rodents are recognized as the hosts of many vector-borne bacteria and protozoan parasites and play an important role in their transmission and maintenance. Intensive studies have focused on their infections in vectors, especially in ticks, however, vector-borne bacterial and protozoan infections in rodents are poorly understood although human cases presenting with fever may due to their infection have been found. METHODS: From May to October 2019, 192 wild rodents were trapped in wild environment of Guangxi Province, and the spleen samples were collected to reveal the presence of vector-borne bacterial and protozoan infections in them. The microorganisms in rodents were identified by detecting their DNA using (semi-)nested PCR. All the PCR products of the expected size were subjected to sequencing, and then analyzed by BLASTn. Furthermore, all the recovered sequences were subjected to nucleotide identity and phylogenetic analyses. RESULTS: As a result, 192 rodents representing seven species were captured, and Bandicota indica were the dominant species, followed by Rattus andamanensis. Based on the (semi-)nested PCR, our results suggested that Anaplasma bovis, Anaplasma capra, Anaplasma ovis, Anaplasma phagocytophilum, "Candidatus Neoehrlichia mikurensis", "Candidatus E. hainanensis", "Candidatus E. zunyiensis", three uncultured Ehrlichia spp., Bartonella coopersplainsensis, Bartonella tribocorum, Bartonella rattimassiliensis, Bartonella silvatica, two uncultured Bartonella spp., Babesia microti and diverse Hepatozoon were identified in six rodent species. More importantly, six species (including two Anaplasma, two Bartonella, "Ca. N. mikurensis" and Bab. microti) are zoonotic pathogens except Anaplasma bovis and Anaplasma ovis with zoonotic potential. Furthermore, dual infection was observed between different microorganisms, and the most common type of co-infection is between "Ca. N. mikurensis" and other microorganisms. Additionally, potential novel Bartonella species and Hepatozoon species demonstrated the presence of more diverse rodent-associated Bartonella and Hepatozoon. CONCLUSIONS: The results in this work indicated great genetic diversity of vector-borne infections in wild rodents, and highlighted the potential risk of human pathogens transmitted from rodents to humans through vectors.

DCES-PA: Deformation-controllable elastic shape model for 3D bone proliferation analysis using hand HR-pQCT images.

Bone proliferation is an important pathological feature of inflammatory rheumatic diseases. Although recent advance in high-resolution peripheral quantitative computed tomography (HR-pQCT) enables physicians to study microarchitectures, physicians' annotation of proliferation suffers from slice inconsistency and subjective variations. Also, there are only few effective automatic or semi-automatic tools for proliferation detection. In this study, by integrating pathological knowledge of proliferation formation with the advancement of statistical shape analysis theory, we present an unsupervised method, named Deformation-Controllable Elastic Shape model, for 3D bone Proliferation Analysis (DCES-PA). Unlike previous shape analysis methods that directly regularize the smoothness of the displacement field, DCES-PA regularizes the first and second-order derivative of the displacement field and decomposes these vector fields according to different deformations. For the first-order elastic metric, DCES-PA orthogonally decomposes the first-order derivative of the displacement field by shearing, scaling and bending deformation, and then penalize deformations triggering proliferation formation. For the second-order elastic metric, DCES-PA encodes both intrinsic and extrinsic surface curvatures into the second-order derivative of the displacement field to control the generation of high-curvature regions. By integrating the elastic shape metric with the varifold distances, DCES-PA achieves correspondence-free shape analysis. Extensive experiments on both simulated and real clinical datasets demonstrate that DCES-PA not only shows an improved accuracy than other state-of-the-art shape-based methods applied to proliferation analysis but also produces highly sensitive proliferation annotations to assist physicians in proliferation analysis.

The complete chloroplast genome of Pandanus amaryllifolius Roxb. ex Lindl. (Pandanaceae) and its phylogenetic relationship.

Pandanus amaryllifolius of Pandanaceae, a plant native to Southeast Asia, has been domesticated for its health benefits and aromatic leaves. It is also used for phytoremediation and soil rehabilitation. However, genetic studies of this species are limited. This study aims to expand its genomic information by assembling and characterizing the complete chloroplast genome of P. amaryllifolius. The chloroplast genome, which was 157,839 bp long, contains a total of 133 genes, including 87 protein-coding (CDS), 38 tRNA, and eight rRNA genes. The overall G/C content was 37.7%. A phylogenetic analysis using 79 shared unique CDS revealed a monophyletic relationship in Pandanales. Based on the limited sampling size, Pandanus amaryllifolius was the first to diverge in Pandanaceae. The genomic data will be useful for future phylogenetic and evolutionary studies of Pandanaceae.

Precision Prediction for Dengue Fever in Singapore: A Machine Learning Approach Incorporating Meteorological Data.

OBJECTIVE: This study aimed to improve dengue fever predictions in Singapore using a machine learning model that incorporates meteorological data, addressing the current methodological limitations by examining the intricate relationships between weather changes and dengue transmission. METHOD: Using weekly dengue case and meteorological data from 2012 to 2022, the data was preprocessed and analyzed using various machine learning algorithms, including General Linear Model (GLM), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Decision Tree (DT), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Performance metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2) were employed. RESULTS: From 2012 to 2022, there was a total of 164,333 cases of dengue fever. Singapore witnessed a fluctuating number of dengue cases, peaking notably in 2020 and revealing a strong seasonality between March and July. An analysis of meteorological data points highlighted connections between certain climate variables and dengue fever outbreaks. The correlation analyses suggested significant associations between dengue cases and specific weather factors such as solar radiation, solar energy, and UV index. For disease predictions, the XGBoost model showed the best performance with an MAE = 89.12, RMSE = 156.07, and R2 = 0.83, identifying time as the primary factor, while 19 key predictors showed non-linear associations with dengue transmission. This underscores the significant role of environmental conditions, including cloud cover and rainfall, in dengue propagation. CONCLUSION: In the last decade, meteorological factors have significantly influenced dengue transmission in Singapore. This research, using the XGBoost model, highlights the key predictors like time and cloud cover in understanding dengue's complex dynamics. By employing advanced algorithms, our study offers insights into dengue predictive models and the importance of careful model selection. These results can inform public health strategies, aiming to improve dengue control in Singapore and comparable regions.

Tumor cell-intrinsic epigenetic dysregulation shapes cancer-associated fibroblasts heterogeneity to metabolically support pancreatic cancer.

The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) involves a significant accumulation of cancer-associated fibroblasts (CAFs) as part of the host response to tumor cells. The origins and functions of transcriptionally diverse CAF populations in PDAC remain poorly understood. Tumor cell-intrinsic genetic mutations and epigenetic dysregulation may reshape the TME; however, their impacts on CAF heterogeneity remain elusive. SETD2, a histone H3K36 trimethyl-transferase, functions as a tumor suppressor. Through single-cell RNA sequencing, we identify a lipid-laden CAF subpopulation marked by ABCA8a in Setd2-deficient pancreatic tumors. Our findings reveal that tumor-intrinsic SETD2 loss unleashes BMP2 signaling via ectopic gain of H3K27Ac, leading to CAFs differentiation toward lipid-rich phenotype. Lipid-laden CAFs then enhance tumor progression by providing lipids for mitochondrial oxidative phosphorylation via ABCA8a transporter. Together, our study links CAF heterogeneity to epigenetic dysregulation in tumor cells, highlighting a previously unappreciated metabolic interaction between CAFs and pancreatic tumor cells.

Bias distribution and regulation in photoelectrochemical overall water-splitting cells.

The water oxidation half-reaction at anodes is always considered the rate-limiting step of overall water splitting (OWS), but the actual bias distribution between photoanodes and cathodes of photoelectrochemical (PEC) OWS cells has not been investigated systematically. In this work, we find that, for PEC cells consisting of photoanodes (nickel-modified n-Si [Ni/n-Si] and α-Fe2O3) with low photovoltage (Vph < 1 V), a large portion of applied bias is exerted on the Pt cathode for satisfying the hydrogen evolution thermodynamics, showing a thermodynamics-controlled characteristic. In contrast, for photoanodes (TiO2 and BiVO4) with Vph > 1 V, the bias required for cathode activation can be significantly reduced, exhibiting a kinetics-controlled characteristic. Further investigations show that the bias distribution can be regulated by tuning the electrolyte pH and using alternative half-reaction couplings. Accordingly, a volcano plot is presented for the rational design of the overall reactions and unbiased PEC cells. Motivated by this, an unbiased PEC cell consisting of a simple Ni/n-Si photoanode and Pt cathode is assembled, delivering a photocurrent density of 5.3 ± 0.2 mA cm-2.

Construction of novel Ag(0)-containing silver nanoclusters by regulating auxiliary phosphine ligands.

Controlled synthesis of metal clusters through minor changes in surface ligands holds significant interest because the corresponding entities serve as ideal models for investigating the ligand environment's stereochemical and electronic contributions that impact the corresponding structures and properties of metal clusters. In this work, we obtained two Ag(0)-containing nanoclusters (Ag17 and Ag32) with near-infrared emissions by regulating phosphine auxiliary ligands. Ag17 and Ag32 bear similar shells wherein Ag17 features a trigonal bipyramid Ag5 kernel while Ag32 has a bi-icosahedral interpenetrating an Ag20 kernel. Ag17 and Ag32 showed a near-infrared emission (NIR) of around 830 nm. Benefiting from the rigid structure, Ag17 displayed a more intense near-infrared emission than Ag32. This work provides new insight into the construction of novel superatomic silver nanoclusters by regulating phosphine ligands.

Enzymatic Preparation, In-Depth Molecular Analysis, and In Vitro Digestion Simulation of Palmitoleic Acid (ω-7)-Enriched Fish Oil Triacylglycerols.

In this study, an enzymatic reaction was developed for synthesizing pure triacylglycerols (TAG) with a high content of palmitoleic acid (POA) using fish byproduct oil. The characteristics of synthesized structural TAGs rich in POA (POA-TAG) were analyzed in detail through ultrahigh-performance liquid chromatography Q Exactive orbitrap mass spectrometry. Optimal conditions were thoroughly investigated and determined for reaction systems, including the use of Lipozyme TL IM and Novozym 435, 15 wt % lipase loading, substrate mass ratio of 1:3, and water content of 2.5 and 0.5 wt %, respectively, resulting in yields of 67.50 and 67.45% for POA-TAG, respectively. Multivariate statistical analysis revealed that TAG 16:1/16:1/20:4, TAG 16:1/16:1/16:1, TAG 16:1/16:1/18:1, and TAG 16:0/16:1/18:1 were the main variables in Lipozyme TL IM and Novozym 435 enzyme-catalyzed products under different water content conditions. Finally, the fate of POA-TAG across the gastrointestinal tract was simulated using an in vitro digestion model. The results showed that the maximum release of free fatty acids and apparent rate constants were 71.44% and 0.0347 s-1, respectively, for POA-TAG lipids, and the physical and structural characteristics during digestion depended on their microenvironments. These findings provide a theoretical basis for studying the rational design of POA-structural lipids and exploring the nutritional and functional benefits of POA products.

A pollen selection system links self and interspecific incompatibility in the Brassicaceae.

Self-incompatibility and recurrent transitions to self-compatibility have shaped the extant mating systems underlying the nonrandom mating critical for speciation in angiosperms. Linkage between self-incompatibility and speciation is illustrated by the shared pollen rejection pathway between self-incompatibility and interspecific unilateral incompatibility (UI) in the Brassicaceae. However, the pollen discrimination system that activates this shared pathway for heterospecific pollen rejection remains unknown. Here we show that Stigma UI3.1, the genetically identified stigma determinant of UI in Arabidopsis lyrata × Arabidopsis arenosa crosses, encodes the S-locus-related glycoprotein 1 (SLR1). Heterologous expression of A. lyrata or Capsella grandiflora SLR1 confers on some Arabidopsis thaliana accessions the ability to discriminate against heterospecific pollen. Acquisition of this ability also requires a functional S-locus receptor kinase (SRK), whose ligand-induced dimerization activates the self-pollen rejection pathway in the stigma. SLR1 interacts with SRK and interferes with SRK homomer formation. We propose a pollen discrimination system based on competition between basal or ligand-induced SLR1-SRK and SRK-SRK complex formation. The resulting SRK homomer levels would be sensed by the common pollen rejection pathway, allowing discrimination among conspecific self- and cross-pollen as well as heterospecific pollen. Our results establish a mechanistic link at the pollen recognition phase between self-incompatibility and interspecific incompatibility.

Prognostic predictive value of urothelial carcinoma of the bladder after TURBT based on multiphase CT radiomics.

OBJECTIVE: To investigate multiphase computed tomography (CT) radiomics-based combined with clinical factors to predict overall survival (OS) in patients with bladder urothelial carcinoma (BLCA) who underwent transurethral resection of bladder tumor (TURBT). METHODS: Data were retrospectively collected from 114 patients with primary BLCA from February 2016 to February 2018. The regions of interest (ROIs) of the plain, arterial, and venous phase images were manually segmented. The Cox regression algorithm was used to establish 3 basic models for the plain phase (PP), arterial phase (AP), and venous phase (VP) and 2 combination models (AP + VP and PP + AP + VP). The highest-performing radiomics model was selected to calculate the radiomics score (Rad-score), and independent risk factors affecting patients' OS were analyzed using Cox regression. The Rad-score and clinical risk factors were combined to construct a joint model and draw a visualized nomogram. RESULTS: The combined model of PP + AP + VP showed the best performance with the Akaike Information Criterion (AIC) and Consistency Index (C-index) in the test group of 130.48 and 0.779, respectively. A combined model constructed with two independent risk factors (age and Ki-67 expression status) in combination with the Rad-score outperformed the radiomics model alone; AIC and C-index in the test group were 115.74 and 0.840, respectively. The calibration curves showed good agreement between the predicted probabilities of the joint model and the actual (p < 0.05). The decision curve showed that the joint model had good clinical application value within a large range of threshold probabilities. CONCLUSION: This new model can be used to predict the OS of patients with BLCA who underwent TURBT.

Injectable Dynamic ROS-Responsive COF-Modified Microalgae Gels for In Vivo bFGF Delivery to Treat Diabetic Wounds.

Hypoxia, chronic inflammation, and elevated reactive oxygen species (ROS) production induced by hyperglycemia pose formidable challenges to the healing of diabetic chronic wounds, often resulting in impaired recovery. Currently, sustainable and eco-friendly therapeutic approaches targeting this multifaceted problem remain uncharted. Herein, we develop a unique three-functional covalent organic framework (COF)-modified microalgae gel designed for the preparation and treatment of chronic diabetic wounds. The gel comprises an oxygen-releasing basic fibroblast growth factor (bFGF) microalgae matrix, augmented by an ROS-responsive COF. Although two of these components have been reported to be used in wound healing, the combination of all three functions represents an innovative approach to synergize the treatment of chronic diabetic wounds. Therefore, we propose a new concept of "ligand interlocking" with three functional synergistic effects. Specifically, the COF has a similar effect to the "double Excalibur", which binds bFGF to promote angiogenesis and proliferation and inhibit the inflammatory response of chronic wounds and binds live microalgae to eliminate ROS and release dissolved oxygen to alleviate the hypoxia of wounds. Moreover, in vivo experiments and RNA sequencing analyses similarly demonstrated that the COF-modified microalgae gel reduced the inflammatory cascade cycle in the wound site and promoted vascular and tissue regeneration. We posit that the COF-modified microalgae gel represents a promising strategy for the active in vivo delivery of therapeutics to the wound body in intensive care unit settings.

Unveiling the Dynamic Electrocatalytic Activity of Online Synthesized Bimetallic Nanocatalysts via Electrochemiluminescence Microscopy.

Effective bimetallic nanoelectrocatalysis demands precise control of composition, structure, and understanding catalytic mechanisms. To address these challenges, we employ a two-in-one approach, integrating online synthesis with real-time imaging of bimetallic Au@Metal core-shell nanoparticles (Au@M NPs) via electrochemiluminescence microscopy (ECLM). Within 120 s, online electrodeposition and in situ catalytic activity screening alternate. ECLM captures transient faradaic processes during potential switches, visualizes electrochemical processes in real-time, and tracks catalytic activity dynamics at the single-particle level. Analysis using ECL photon flux density eliminates size effects and yields quantitative electrocatalytic activity results. Notably, a nonlinear activity trend corresponding to the shell metal to Au surface atomic ratio is discerned, quantifying the optimal surface component ratio of Au@M NPs. This approach offers a comprehensive understanding of catalytic behavior during the deposition process with high spatiotemporal resolution, which is crucial for tailoring efficient bimetallic nanocatalysts for diverse applications.

SIRT1 as a potential therapeutic target in pelvic organ prolapse due to protective effects against oxidative stress and cellular senescence in human uterosacral ligament fibroblasts.

INTRODUCTION: The pathogenesis of pelvic organ prolapse (POP), an age-related disease, has not been fully elucidated. Therapeutic targets of POP are limited. Silencing information regulator 2 related enzyme 1 (SIRT1), a gene considered capable of regulating oxidative stress and cellular senescence, has been widely demonstrated involved in aging and age-related diseases. The present study aimed to explore the role of SIRT1 in POP in vivo and in vitro. METHODS: Expression levels of SIRT1 in uterosacral ligament (USL) tissues from patients with or without POP were measured using immunohistochemical assays. SRT1720, a SIRT1 agonist, was used to upregulate SIRT1, and hydrogen peroxide (H2O2) was used to establish an oxidative stress model in human uterosacral ligament fibroblasts (hUSLFs). The effects of SIRT1 on cell viability, apoptosis, senescence, and reactive oxygen species (ROS) levels were detected, respectively. Western blot assays were used to examine expression levels of apoptosis- and senescence-associated biomarkers. Unpaired Student's t test, Mann-Whitney U test, χ2 test, and one-way ANOVA were performed for determining statistically significant differences. RESULTS: Compared to the control group, expression levels of SIRT1 were downregulated in USL tissues and hUSLFs from patients with POP, and associated with stage (p < 0.05). hUSLFs of patients with POP had lower growth rates (p < 0.0001) than those of the control group, which were improved by upregulating SIRT1 (p < 0.05). The senescent proportion was higher in the POP group than the control group (43.63 ± 10.62% vs. 4.84 ± 5.32%, p < 0.0001), which could be reduced by upregulating SIRT1 (p < 0.0001). High ROS levels in the POP group were also alleviated by SRT1720. H2O2 exposure increased ROS levels, inhibited proliferation, and triggered apoptosis and senescence in hUSLFs of patients without POP in a concentration-dependent manner. Further, these damages were alleviated by pretreatment with SRT1720. CONCLUSIONS: SIRT1 is downregulated in patients with POP, and the development of SIRT1 activators or agonists may have applications in the treatment and prevention of POP through antioxidative stress and antisenescence effects.

Anaplasma, Bartonella, and Rickettsia infections in Daurian ground squirrels (Spermophilus dauricus), Hebei, China.

Rodents have been confirmed as hosts of various vector-borne zoonotic pathogens and are important for the maintenance of these microbes in nature. However, surveillance for zoonotic pathogens is limited for many wild rodent species in China, so our knowledge of pathogen ecology, genetic diversity, and the risk of cross-species transmission to humans is limited. In this study, 165 spleen samples of Daurian ground squirrels (Spermophilus dauricus) were collected from Weichang Manchu and the Mongolian Autonomous County of Hebei Province, China, and Rickettsia, Bartonella, and Anaplasma were identified by DNA detection using polymerase chain reaction (PCR). Sequence analysis identified eight bacterial pathogens: R. raoultii, R. sibirica, Candidatus R. longicornii, B. washoensis, B. grahamii, B. jaculi, A. capra, and Candidatus Anaplasma cinensis. Co-infection of B. grahamii and R. raoultii in one sample was observed. Our results demonstrated the genetic diversity of bacteria in Daurian ground squirrels and contributed to the distribution of these pathogens. Six species, A. capra, R. raoultii, R. sibirica, Candidatus R. longicornii, B. washoensis, and B. grahamii, are known to be pathogenic to humans, indicating a potential public health risk to the local human population, especially to herders who frequently have close contact with Daurian ground squirrels and are thus exposed to their ectoparasites.

Relationship-Guided Knowledge Transfer for Class-Incremental Facial Expression Recognition.

Human emotions contain both basic and compound facial expressions. In many practical scenarios, it is difficult to access all the compound expression categories at one time. In this paper, we investigate comprehensive facial expression recognition (FER) in the class-incremental learning paradigm, where we define well-studied and easily-accessible basic expressions as initial classes and learn new compound expressions incrementally. To alleviate the stability-plasticity dilemma in our incremental task, we propose a novel Relationship-Guided Knowledge Transfer (RGKT) method for class-incremental FER. Specifically, we develop a multi-region feature learning (MFL) module to extract fine-grained features for capturing subtle differences in expressions. Based on the MFL module, we further design a basic expression-oriented knowledge transfer (BET) module and a compound expression-oriented knowledge transfer (CET) module, by effectively exploiting the relationship across expressions. The BET module initializes the new compound expression classifiers based on expression relevance between basic and compound expressions, improving the plasticity of our model to learn new classes. The CET module transfers expression-generic knowledge learned from new compound expressions to enrich the feature set of old expressions, facilitating the stability of our model against forgetting old classes. Extensive experiments on three facial expression databases show that our method achieves superior performance in comparison with several state-of-the-art methods.