Process, advances, and perspectives of graphene oxide-SELEX for the development of aptamer molecular probes: A comprehensive review.

BACKGROUND: Aptamers are screened via the systematic evolution of ligands by exponential enrichment (SELEX) and are widely used in molecular diagnostics and targeted therapies. The development of efficient and convenient SELEX technology has facilitated rapid access to high-performance aptamers, thereby advancing the aptamer industry. Graphene oxide (GO) serves as an immobilization matrix for libraries in GO-SELEX, making it suitable for screening aptamers against diverse targets. RESULTS: This review summarizes the detailed steps involved in GO-SELEX, including monitoring methods, various sublibrary acquisition methods, and practical applications from its inception to the present day. In addition, the potential of GO-SELEX in the development of broad-spectrum aptamers is explored, and its current limitations for future development are emphasized. This review effectively promotes the application of the GO-SELEX technique by providing valuable insights and assisting researchers interested in conducting related studies. SIGNIFICANCE AND NOVELTY: To date, no review on the topic of GO-SELEX has been published, making it challenging for researchers to initiate studies in this area. We believe that this review will broaden the SELEX options available to researchers, ensuring that they can meet the growing demand for molecular probes in the scientific domain.

An integrated network pharmacology and molecular docking approach to reveal the role of Arctigenin against Cutibacterium acnes-induced skin inflammation by targeting the CYP19A1.

Acne caused by inflammation of hair follicles and sebaceous glands is a common chronic skin disease. Arctigenin (ATG) is an extract of Arctium lappa L., which has significant anti-inflammatory effects. However, the effect and mechanism of ATG in cutaneous inflammation mediated by Cutibacterium acnes (C. acnes) has not been fully evaluated. The purpose of this study was to explore the effect and potential mechanism of ATG in the treatment of acne through network pharmacology and experimental confirmation. An acne model was established by injected live C. acnes into living mice and treated with ATG. Our data showed that ATG effectively improved acne induced by live C. acnes, which was confirmed by determining ear swelling rate, estradiol concentration and hematoxylin and eosin (H&E) staining. In addition, ATG inhibited the NLRP3 inflammasome signaling pathway in mice ear tissues and reduced the secretion of pro-inflammatory cytokines IL-1ß to relieve inflammation. The results of network pharmacology and molecular docking confirmed that ATG can regulate 17ß-Estradiol (E2) levels through targeted to CYP19A1, and finally inhibited skin inflammation. Taken together, our results confirmed that ATG regulated E2 secretion by targeting CYP19A1, thereby inhibiting the NLRP3 inflammasome signaling pathway and improving inflammation levels in acne mice. This study provides a basis for the feasibility of ATG in treating acne in clinical practice.

Real-World Effectiveness of Nirmatrelvir in Protecting Long COVID for Outpatient Adult Patients - A Large-Scale Observational Cohort Study from the RECOVER Initiative.

Paxlovid has been approved for use in patients who are at high risk for severe acute COVID-19 illness. Evidence regarding whether Paxlovid protects against Post-Acute Sequelae of SARS-CoV-2 infection (PASC), or Long COVID, is mixed in high-risk patients and lacking in low-risk patients. With a target trial emulation framework, we evaluated the association of Paxlovid treatment within 5 days of SARS-CoV-2 infection with incident Long COVID and hospitalization or death from any cause in the post-acute period (30-180 days after infection) using electronic health records from the Patient-Centered Clinical Research Networks (PCORnet) RECOVER repository. The study population included 497,499 SARS-CoV-2 positive patients between March 1, 2022, to February 1, 2023, and among which 165,256 were treated with Paxlovid within 5 days since infection and 307,922 were not treated with Paxlovid or other COVID-19 treatments. Compared with the non-treated group, Paxlovid treatment was associated with reduced risk of Long COVID with a Hazard Ratio (HR) of 0.88 (95% CI, 0.87 to 0.89) and absolute risk reduction of 2.99 events per 100 persons (95% CI, 2.65 to 3.32). Paxlovid treatment was associated with reduced risk of all-cause death (HR, 0.53, 95% CI 0.46 to 0.60; risk reduction 0.23 events per 100 persons, 95% CI 0.19 to 0.28) and hospitalization (HR, 0.70, 95% CI 0.68 to 0.73; risk reduction 2.37 events per 100 persons, 95% CI 2.19 to 2.56) in the post-acute phase. For those without documented risk factors, the associations (HR, 1.03, 95% CI 0.95 to 1.11; risk increase 0.80 events per 100 persons, 95% CI -0.84 to 2.45) were inconclusive. Overall, high-risk, nonhospitalized adult patients with COVID-19 who were treated with Paxlovid within 5 days of SARS-CoV-2 infection had a lower risk of Long COVID and all-cause hospitalization or death in the post-acute period. However, Long COVID risk reduction with Paxlovid was not observed in low-risk patients.

Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts.

BACKGROUND: SARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae of SARS-CoV-2 infection (PASC, or Long COVID), involve a diverse set of organ systems. Limited studies have investigated the predictability of Long COVID development and its associated risk factors. METHODS: In this retrospective cohort study, we used electronic healthcare records from two large-scale PCORnet clinical research networks, INSIGHT (~1.4 million patients from New York) and OneFlorida+ (~0.7 million patients from Florida), to identify factors associated with having Long COVID, and to develop machine learning-based models for predicting Long COVID development. Both SARS-CoV-2-infected and non-infected adults were analysed during the period of March 2020 to November 2021. Factors associated with Long COVID risk were identified by removing background associations and correcting for multiple tests. RESULTS: We observed complex association patterns between baseline factors and a variety of Long COVID conditions, and we highlight that severe acute SARS-CoV-2 infection, being underweight, and having baseline comorbidities (e.g., cancer and cirrhosis) are likely associated with increased risk of developing Long COVID. Several Long COVID conditions, e.g., dementia, malnutrition, chronic obstructive pulmonary disease, heart failure, PASC diagnosis U099, and acute kidney failure are well predicted (C-index > 0.8). Moderately predictable conditions include atelectasis, pulmonary embolism, diabetes, pulmonary fibrosis, and thromboembolic disease (C-index 0.7-0.8). Less predictable conditions include fatigue, anxiety, sleep disorders, and depression (C-index around 0.6). CONCLUSIONS: This observational study suggests that association patterns between investigated factors and Long COVID are complex, and the predictability of different Long COVID conditions varies. However, machine learning-based predictive models can help in identifying patients who are at risk of developing a variety of Long COVID conditions.

Most people who develop COVID-19 make a full recovery, but some go on to develop post-acute sequelae of SARS-CoV-2 infection, commonly known as Long COVID. Up to now, we did not know why some people are affected by Long COVID whilst others are not. We conducted a study to identify risk factors for Long COVID and developed a mathematical modeling approach to predict those at risk. We find that Long COVID is associated with some factors such as experiencing severe acute COVID-19, being underweight, and having conditions including cancer or cirrhosis. Due to the wide variety of symptoms defined as Long COVID, it may be challenging to come up with a set of risk factors that can predict the whole spectrum of Long COVID. However, our approach could be used to predict a variety of Long COVID conditions.

Electricity generated by upstream proton diffusion in two-dimensional nanochannels.

The movement of ions along the pressure-driven water flow in narrow channels, known as downstream ionic transport, has been observed since 1859 to induce a streaming potential and has enabled the creation of various hydrovoltaic devices. In contrast, here we demonstrate that proton movement opposing the water flow in two-dimensional nanochannels of MXene/poly(vinyl alcohol) films, termed upstream proton diffusion, can also generate electricity. The infiltrated water into the channel causes the dissociation of protons from functional groups on the channel surface, resulting in a high proton concentration inside the channel that drives the upstream proton diffusion. Combined with the particularly sluggish water diffusion in the channels, a small water droplet of 5 µl can generate a voltage of ~400 mV for over 330 min. Benefiting from the ultrathin and flexible nature of the film, a wearable device is built for collecting energy from human skin sweat.

Gut microbiota regulates gut homeostasis, mucosal immunity and influences immune-related diseases.

The intestinal microbiome constitutes a sophisticated and massive ecosystem pivotal for maintaining gastrointestinal equilibrium and mucosal immunity via diverse pathways. The gut microbiota is continuously reshaped by multiple environmental factors, thereby influencing overall wellbeing or predisposing individuals to disease state. Many observations reveal an altered microbiome composition in individuals with autoimmune conditions, coupled with shifts in metabolic profiles, which has spurred ongoing development of therapeutic interventions targeting the microbiome. This review delineates the microbial consortia of the intestine, their role in sustaining gastrointestinal stability, the association between the microbiome and immune-mediated pathologies, and therapeutic modalities focused on microbiome modulation. We emphasize the entire role of the intestinal microbiome in human health and recommend microbiome modulation as a viable strategy for disease prophylaxis and management. However, the application of gut microbiota modification for the treatment of immune-related diseases, such as fecal microbiota transplantation and probiotics, remain quite challenging. Therefore, more research is needed into the role and mechanisms of these therapeutics.

Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER program.

IMPORTANCE: The frequency and characteristics of post-acute sequelae of SARS-CoV-2 infection (PASC) may vary by SARS-CoV-2 variant. OBJECTIVE: To characterize PASC-related conditions among individuals likely infected by the ancestral strain in 2020 and individuals likely infected by the Delta variant in 2021. DESIGN: Retrospective cohort study of electronic medical record data for approximately 27 million patients from March 1, 2020-November 30, 2021. SETTING: Healthcare facilities in New York and Florida. PARTICIPANTS: Patients who were at least 20 years old and had diagnosis codes that included at least one SARS-CoV-2 viral test during the study period. EXPOSURE: Laboratory-confirmed COVID-19 infection, classified by the most common variant prevalent in those regions at the time. MAIN OUTCOME(S) AND MEASURE(S): Relative risk (estimated by adjusted hazard ratio [aHR]) and absolute risk difference (estimated by adjusted excess burden) of new conditions, defined as new documentation of symptoms or diagnoses, in persons between 31-180 days after a positive COVID-19 test compared to persons without a COVID-19 test or diagnosis during the 31-180 days after the last negative test. RESULTS: We analyzed data from 560,752 patients. The median age was 57 years; 60.3% were female, 20.0% non-Hispanic Black, and 19.6% Hispanic. During the study period, 57,616 patients had a positive SARS-CoV-2 test; 503,136 did not. For infections during the ancestral strain period, pulmonary fibrosis, edema (excess fluid), and inflammation had the largest aHR, comparing those with a positive test to those without a COVID-19 test or diagnosis (aHR 2.32 [95% CI 2.09 2.57]), and dyspnea (shortness of breath) carried the largest excess burden (47.6 more cases per 1,000 persons). For infections during the Delta period, pulmonary embolism had the largest aHR comparing those with a positive test to a negative test (aHR 2.18 [95% CI 1.57, 3.01]), and abdominal pain carried the largest excess burden (85.3 more cases per 1,000 persons). CONCLUSIONS AND RELEVANCE: We documented a substantial relative risk of pulmonary embolism and a large absolute risk difference of abdomen-related symptoms after SARS-CoV-2 infection during the Delta variant period. As new SARS-CoV-2 variants emerge, researchers and clinicians should monitor patients for changing symptoms and conditions that develop after infection.

Action and therapeutic targets of myosin light chain kinase, an important cardiovascular signaling mechanism.

The global incidence of cardiac diseases is increasing, imposing a substantial socioeconomic burden on healthcare systems. The pathogenesis of cardiovascular disease is complex and not fully understood, and the physiological function of the heart is inextricably linked to well-regulated cardiac muscle movement. Myosin light chain kinase (MLCK) is essential for myocardial contraction and diastole, cardiac electrophysiological homeostasis, vasoconstriction of vascular nerves and blood pressure regulation. In this sense, MLCK appears to be an attractive therapeutic target for cardiac diseases. MLCK participates in myocardial cell movement and migration through diverse pathways, including regulation of calcium homeostasis, activation of myosin light chain phosphorylation, and stimulation of vascular smooth muscle cell contraction or relaxation. Recently, phosphorylation of myosin light chains has been shown to be closely associated with the activation of myocardial exercise signaling, and MLCK mediates systolic and diastolic functions of the heart through the interaction of myosin thick filaments and actin thin filaments. It works by upholding the integrity of the cytoskeleton, modifying the conformation of the myosin head, and modulating innervation. MLCK governs vasoconstriction and diastolic function and is associated with the activation of adrenergic and sympathetic nervous systems, extracellular transport, endothelial permeability, and the regulation of nitric oxide and angiotensin II. Additionally, MLCK plays a crucial role in the process of cardiac aging. Multiple natural products/phytochemicals and chemical compounds, such as quercetin, cyclosporin, and ML-7 hydrochloride, have been shown to regulate cardiomyocyte MLCK. The MLCK-modifying capacity of these compounds should be considered in designing novel therapeutic agents. This review summarizes the mechanism of action of MLCK in the cardiovascular system and the therapeutic potential of reported chemical compounds in cardiac diseases by modifying MLCK processes.

Hospice Readmission, Hospitalization, and Hospital Death Among Patients Discharged Alive from Hospice.

Importance: Transitions in care settings following live discharge from hospice care are burdensome for patients and families. Factors contributing to risk of burdensome transitions following hospice discharge are understudied. Objective: To identify factors associated with 2 burdensome transitions following hospice live discharge, as defined by the Centers for Medicare & Medicaid Services. Design, Setting, and Participants: This population-based retrospective cohort study included a 20% random sample of Medicare fee-for-service beneficiaries using 2014 to 2019 Medicare claims data. Data were analyzed from April 22, 2023, to March 4, 2024. Exposure: Live hospice discharge. Main Outcomes and Measures: Multivariable logistic regression examined associations among patient, health care provision, and organizational characteristics with 2 burdensome transitions after live hospice discharge (outcomes): type 1, hospice discharge, hospitalization within 2 days, and hospice readmission within 2 days; and type 2, hospice discharge, hospitalization within 2 days, and hospital death. Results: This study included 115 072 Medicare beneficiaries discharged alive from hospice (mean [SD] age, 84.4 [6.6] years; 71892 [62.5%] female; 5462 [4.8%] Hispanic, 9822 [8.5%] non-Hispanic Black, and 96 115 [83.5%] non-Hispanic White). Overall, 10 381 individuals (9.0%) experienced a type 1 burdensome transition and 3144 individuals (2.7%) experienced a type 2 burdensome transition. In adjusted models, factors associated with higher odds of burdensome transitions included identifying as non-Hispanic Black (type 1: adjusted odds ratio [aOR], 1.47; 95% CI, 1.36-1.58; type 2: aOR, 1.70; 95% CI, 1.51-1.90), hospice stays of 7 days or fewer (type 1: aOR, 1.13; 95% CI, 1.06-1.21; type 2: aOR, 1.71; 95% CI, 1.53-1.90), and care from a for-profit hospice (type 1: aOR, 1.78; 95% CI, 1.62-1.96; type 2: aOR, 1.32; 95% CI, 1.15-1.52). Nursing home residence (type 1: aOR, 0.66; 95% CI, 0.61-0.72; type 2: aOR, 0.47; 95% CI, 0.40-0.54) and hospice stays of 180 days or longer (type 1: aOR, 0.63; 95% CI, 0.59-0.68; type 2: aOR, 0.60; 95% CI, 0.52-0.69) were associated with lower odds of burdensome transitions. Conclusion and Relevance: This retrospective cohort study of burdensome transitions following live hospice discharge found that non-Hispanic Black race, short hospice stays, and care from for-profit hospices were associated with higher odds of experiencing a burdensome transition. These findings suggest that changes to clinical practice and policy may reduce the risk of burdensome transitions, such as hospice discharge planning that is incentivized, systematically applied, and tailored to needs of patients at greater risk for burdensome transitions.

Application of a data continuity prediction algorithm to an electronic health record-based pharmacoepidemiology study.

BACKGROUND AND OBJECTIVES: Use of algorithms to identify patients with high data-continuity in electronic health records (EHRs) may increase study validity. Practical experience with this approach remains limited. METHODS: We developed and validated four algorithms to identify patients with high data continuity in an EHR-based data source. Selected algorithms were then applied to a pharmacoepidemiologic study comparing rates of COVID-19 hospitalization in patients exposed to insulin versus noninsulin antidiabetic drugs. RESULTS: A model using a short list of five EHR-derived variables performed as well as more complex models to distinguish high- from low-data continuity patients. Higher data continuity was associated with more accurate ascertainment of key variables. In the pharmacoepidemiologic study, patients with higher data continuity had higher observed rates of the COVID-19 outcome and a large unadjusted association between insulin use and the outcome, but no association after propensity score adjustment. DISCUSSION: We found that a simple, portable algorithm to predict data continuity gave comparable performance to more complex methods. Use of the algorithm significantly impacted the results of an empirical study, with evidence of more valid results at higher levels of data continuity.

A comprehensive review of aptamer screening and application for lateral flow strip: Current status and future perspectives.

The detection of biomarkers is of great significance for medical diagnosis, food safety, environmental monitoring, and agriculture. However, bio-detection technology at present often necessitates complex instruments, expensive reagents, specialized expertise, and prolonged procedures, making it challenging to fulfill the demand for rapid, sensitive, user-friendly, and economical testing. In contrast, lateral flow strip (LFS) technology offers simple, fast, and visually accessible detection modality, allowing real-time analysis of clinical specimens, thus finding widespread utility across various domains. Within the realm of LFS, the application of aptamers as molecular recognition probes presents distinct advantages over antibodies, including cost-effectiveness, smaller size, ease of synthesis, and chemical stability. In recent years, aptamer-based LFS has found extensive application in qualitative, semi-quantitative, and quantitative detection across food safety, environmental surveillance, clinical diagnostics, and other domains. This review provided a concise overview of different aptamer screening methodologies, selection strategies, underlying principles, and procedural, elucidating their respective advantages, limitations, and applications. Additionally, we summarized recent strategies and mechanisms for aptamer-based LFS, such as the sandwich and competitive methods. Furthermore, we classified LFSs constructed based on aptamers, considering the rapid advancements in this area, and discussed their applications in biological and chemical detection. Finally, we delved into the current challenges and future directions in the development of aptamer and aptamer-based LFS. Although this review was not thoroughly, it would serve as a valuable reference for understanding the research progress of aptamer-based LFS and aid in the development of new types of aptasensors.

A capillary-aided microfiber Bragg grating pH sensor for hydrovoltaic technology.

Hydrovoltaic is an emerging technology that aims to harvest energy from water flow and evaporation, in which the plasmonic hydrogen ions are generated by the interaction between water and hydrovoltaic device. However, the volume of the water sample for the interaction is usually ultra-small due to the compact size of hydrovoltaic device, making the quantification and characterization of the hydrogen ions in such water sample an elusive goal. To address this issue, a miniature fiber-optic pH probe is proposed using a unilaterally tapered-microfiber Bragg grating. The microfiber Bragg grating has an intrinsic Bragg reflection signal with a narrow linewidth. The fiber probe is functionalized by coating the sodium alginate, which can respond to the variation of pH mediated by the alteration of the hydrophilicity. The rigidity and robustness of microfiber Bragg grating facilitates the encapsulation of the sensor into a sampling capillary, allowing for the detection of trace aqueous sample less than 2 µL. The pH sensitivity of the tapered-µFBG-based sensor is 62.8 p.m./pH (R2 = 0.995) with a limit resolution of 0.096 pH. The sensor performed a practical application in the monitoring and characterization of the hydrovoltaic microdevice, which can generate microcurrent as soaked in the water. This work demonstrates a promising technology in the fields of materials, energy, biology and medicine, in which the detection of the microsamples is inevitable.

Dual-Targeted Novel Temozolomide Nanocapsules Encapsulating siPKM2 Inhibit Aerobic Glycolysis to Sensitize Glioblastoma to Chemotherapy.

Chemotherapy of glioblastoma (GBM) has not yielded success due to inefficient blood-brain barrier (BBB) penetration and poor glioma tissue accumulation. Aerobic glycolysis, as the main mode of energy supply for GBM, safeguards the rapid growth of GBM while affecting the efficacy of radiotherapy and chemotherapy. Therefore, to effectively inhibit aerobic glycolysis, increase drug delivery efficiency and sensitivity, a novel temozolomide (TMZ) nanocapsule (ApoE-MT/siPKM2 NC) is successfully designed and prepared for the combined delivery of pyruvate kinase M2 siRNA (siPKM2) and TMZ. This drug delivery platform uses siPKM2 as the inner core and methacrylate-TMZ (MT) as the shell component to achieve inhibition of glioma energy metabolism while enhancing the killing effect of TMZ. By modifying apolipoprotein E (ApoE), dual targeting of the BBB and GBM is achieved in a "two birds with one stone" style. The glutathione (GSH) responsive crosslinker containing disulfide bonds ensures "directional blasting" cleavage of the nanocapsules to release MT and siPKM2 in the high GSH environment of glioma cells. In addition, in vivo experiments verify that ApoE-MT/siPKM2 NC has good targeting ability and prolongs the survival of tumor-bearing nude mice. In summary, this drug delivery system provides a new strategy for metabolic therapy sensitization chemotherapy.

Mononuclear Iron Pyridinethiolate Complex Promoted CO2 Photoreduction via Rapid Intramolecular Electron Transfer.

Designing earth-abundant metal complexes as efficient molecular photocatalysts for visible light-driven CO2 reduction is a key challenge in artificial photosynthesis. Here, we demonstrated the first example of a mononuclear iron pyridine-thiolate complex that functions both as a photosensitizer and catalyst for CO2 reduction. This single-component bifunctional molecular photocatalyst efficiently reduced CO2 to formate and CO with a total turnover number (TON) of 46 and turnover frequency (TOF) of 11.5 h-1 in 4 h under visible light irradiation. Notably, the quantum yield was determined to be 8.4 % for the generation of formate and CO at 400 nm. Quenching experiments indicate that high photocatalytic activity is mainly attributed to the rapid intramolecular quenching protocol. The mechanism investigation by DFT calculation and electrochemical studies revealed that the protonation of Febpy(pyS)2 is indispensable step for photocatalytic CO2 reduction.

Prediction model of land surface settlement deformation based on improved LSTM method: CEEMDAN-ICA-AM-LSTM (CIAL) prediction model.

The uneven settlement of the surrounding ground surface caused by subway construction is not only complicated but also liable to cause casualties and property damage, so a timely understanding of the ground settlement deformation in the subway excavation and its prediction in real time is of practical significance. Due to the complex nonlinear relationship between subway settlement deformation and numerous influencing factors, as well as the existence of a time lag effect and the influence of various factors in the process, the prediction performance and accuracy of traditional prediction methods can no longer meet industry demands. Therefore, this paper proposes a surface settlement deformation prediction model by combining noise reduction and attention mechanism (AM) with the long short-term memory (LSTM). The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and independent component analysis (ICA) methods are used to denoise the input original data and then combined with AM and LSTM for prediction to obtain the CEEMDAN-ICA-AM-LSTM (CIAL) prediction model. Taking the settlement monitoring data of the construction site of Urumqi Rail Transit Line 1 as an example for analysis reveals that the model in this paper has better effectiveness and applicability in the prediction of surface settlement deformation than multiple prediction models. The RMSE, MAE, and MAPE values of the CIAL model are 0.041, 0.033 and 0.384%; R2 is the largest; the prediction effect is the best; the prediction accuracy is the highest; and its reliability is good. The new method is effective for monitoring the safety of surface settlement deformation.

Deciphering the Roles of Interfacial Amino Acids in Inter-Protein Charge Transport.

Elucidating charge transport (CT) through proteins is critical for gaining insights into ubiquitous CT chain reactions in biological systems and developing high-performance bioelectronic devices. While intra-protein CT has been extensively studied, crucial knowledge about inter-protein CT via interfacial amino acids is still absent due to the structural complexity. Herein, by loading cytochrome c (Cyt c) on well-defined peptide self-assembled monolayers to mimic the protein-protein interface, we provide a precisely controlled platform for identifying the roles of interfacial amino acids in solid-state CT via peptide-Cyt c junctions. The terminal amino acid of peptides serves as a fine-tuning factor for both the interfacial interaction between peptides and Cyt c and the immobilized Cyt c orientation, resulting in a nearly 10-fold difference in current through peptide-Cyt c junctions with varied asymmetry. This work provides a valuable platform for studying CT across proteins and contributes to the understanding of fundamental principles governing inter-protein CT.

Lipid Metabolic Disorders Induced by Organophosphate Esters in Silver Carp from the Middle Reaches of the Yangtze River.

The Yangtze River fishery resources have declined strongly over the past few decades. One suspected reason for the decline in fishery productivity, including silver carp (Hypophthalmichthys molitrix), has been linked to organophosphate esters (OPEs) contaminant exposure. In this study, the adverse effect of OPEs on lipid metabolism in silver carp captured from the Yangtze River was examined, and our results indicated that muscle concentrations of the OPEs were positively associated with serum cholesterol and total lipid levels. In vivo laboratory results revealed that exposure to environmental concentrations of OPEs significantly increased the concentrations of triglyceride, cholesterol, and total lipid levels. Lipidome analysis further confirmed the lipid metabolism dysfunction induced by OPEs, and glycerophospholipids and sphingolipids were the most affected lipids. Hepatic transcriptomic analysis found that OPEs caused significant alterations in the transcription of genes involved in lipid metabolism. Pathways associated with lipid homeostasis, including the peroxisome proliferator-activated receptor (PPAR) signal pathway, cholesterol metabolism, fatty acid biosynthesis, and steroid biosynthesis, were significantly changed. Furthermore, the affinities of OPEs were different, but the 11 OPEs tested could bind with PPARγ, suggesting that OPEs could disrupt lipid metabolism by interacting with PPARγ. Overall, this study highlighted the harmful effects of OPEs on wild fish and provided mechanistic insights into OPE-induced metabolic disorders.

Modulation of Performance, Plasma Constituents, Small Intestinal Morphology, and Cecum Microbiota in Growing Geese by Dietary Citric Acid Supplementation.

To investigate the efficiency and optimum inclusion level of CA in growing geese diets on performance, plasma constituents, and intestinal health, 240 healthy female geese at the age of 28d were randomly allotted six treatment diets incorporated with 0, 0.8, 1.6, 2.4, 3.2, and 4% CA. Each treatment group consisted of five replicates and eight birds per replicate. The findings demonstrated that 3.2% CA supplementation resulted in improved growth performance (ADG, ADFI, and FBW) (p = 0.001), and geese who received CA also showed lower body fat contents (p < 0.05) than the control group. Moreover, geese from the 2.4% and 3.2% CA group had the highest plasma glutathione peroxidase and insulin-like growth factor 1 levels compared to the other groups (p < 0.05). A microbial diversity analysis of the cecum conducted by 16S rDNA sequencing revealed that 3.2% CA supplementation showed a significantly higher abundance of beneficial bacteria (Muribaculaceae, CHKCI001, Erysipelotricha-ceae_UCG_003, and UCG_009) (p < 0.05) and a lower abundance of harmful bacteria (Atopobiaceae, Streptococcus, Acinetobacter, Pseudomonas, and Alistipes) (p < 0.10). Collectively, our results revealed that dietary supplementation with 3.2% CA had several benefits on the performance and physiological health of growing geese by promoting nutrients metabolism, improving antioxidant capacity, and modulating cecum microbiota.

Process Study of Selective Laser Sintering of PS/GF/HGM Composites.

To address the issues of insufficient strength and poor precision in polystyrene forming parts during the selective laser sintering process, a ternary composite of polystyrene/glass fiber/hollow glass microbeads was prepared through co-modification by incorporating glass fiber and hollow glass microbeads into polystyrene using a mechanical mixing method. The bending strength and dimensional accuracy of the sintered composites were investigated by conducting an orthogonal test and analysis of variance to study the effects of laser power, scanning speed, scanning spacing, and delamination thickness. The process parameters were optimized and selected to determine the optimal combination. The results demonstrated that when considering bending strength and Z-dimensional accuracy as evaluation criteria for terpolymer sintered parts, the optimum process parameters are as follows: laser power of 24 W, scanning speed of 1600 mm/s, scanning spacing of 0.24 mm, and delamination thickness of 0.22 mm. Under these optimal process parameters, the bending strength of sintered parts reaches 6.12 MPa with a relative error in the Z-dimension of only 0.87%. The bending strength of pure polystyrene sintered parts is enhanced by 15.69% under the same conditions, while the relative error in the Z-dimension is reduced by 63.45%. It improves the forming strength and precision of polystyrene in the selective laser sintering process and achieves the effect of enhancement and modification, which provides a reference and a new direction for exploring polystyrene-based high-performance composites and expands the application scope of selective laser sintering technology.

Parametric Design of Porous Structure and Optimal Porosity Gradient Distribution Based on Root-Shaped Implants.

Porous structures can reduce the elastic modulus of implants, decrease stress shielding, and avoid bone loss in the alveolar bone and aseptic loosening of implants; however, there is a mismatch between yield strength and elastic modulus as well as biocompatibility problems. This study aimed to investigate the parametric design method of porous root-shaped implants to reduce the stress-shielding effect and improve the biocompatibility and long-term stability and effectiveness of the implants. Firstly, the porous structure part was parametrically designed, and the control of porosity gradient distribution was achieved by using the fitting relationship between porosity and bias and the position function of bias. In addition, the optimal distribution law of the porous structure was explored through mechanical and hydrodynamic analyses of the porous structure. Finally, the biomechanical properties were verified using simulated implant-bone tissue interface micromotion values. The results showed that the effects of marginal and central porosity on yield strength were linear, with the elastic modulus decreasing from 18.9 to 10.1 GPa in the range of 20-35% for marginal porosity, with a maximum decrease of 46.6%; the changes in the central porosity had a more consistent effect on the elastic modulus, ranging from 18.9 to 15.3 GPa in the range of 50-90%, with a maximum downward shift of 19%. The central porosity had a more significant effect on permeability, ranging from 1.9 × 10-7 m2 to 4.9 × 10-7 m2 with a maximum enhancement of 61.2%. The analysis showed that the edge structure had a more substantial impact on the mechanical properties. The central structure could increase the permeability more effectively. Hence, the porous structure with reasonable gradient distribution had a better match between mechanical properties and flow properties. The simulated implantation results showed that the porous implant with proper porosity gradient distribution had better biomechanical properties.