Estimation of carbon emissions from different industrial categories integrated nighttime light and POI data-A case study in the Yellow River Basin.

Global industrial activities contribute significantly to carbon emissions, impacting climate change and necessitating innovative methods for precise emission monitoring and management at both regional and international levels. Based on nighttime light data, POI data, land use data and energy statistics, this study calculated the carbon emissions of different industrial categories in the Yellow River Basin from 2005 to 2020 and analyzed the temporal and spatial characteristics of their changes to reveal the carbon emission patterns of different industrial categories in the basin. This study analyzes the carbon emissions of various industrial categories from a spatial perspective, addressing the limitations of traditional industrial carbon emission assessments at the spatial scale. The results showed that although the growth rate of industrial carbon emissions in the Yellow River Basin has slowed down significantly, it has not yet reached the peak, with the carbon emissions increasing from 400,0647t in 2005 to 519,216,200t in 2020. The mechanical and electronic manufacturing industry had the largest carbon emissions, which accounting for 37.08% of the total carbon emissions. Medical pharmaceuticals had the fewest, only accounting for 1.16% of the total carbon emissions. The spatial distribution of carbon emissions showed a cluster distribution, and the emissions gradually decrease from the center to the periphery. In addition, the carbon emissions of the construction industry, medical pharmaceutical industry and mechanical and electronic manufacturing industry were concentrated in and around the cites, and were closely related to urban development, infrastructure and technological progress. Furthermore, the study reveals that the relationship between carbon emissions and population structure across different industrial categories is complex. A stable relationship exists between carbon emissions and the population within the mechanical and electronic manufacturing, metallurgy, and chemical industries. However, for the clothing, furniture, and pharmaceutical industries, population is not the sole influencing factor on their carbon emissions. This study provides a new perspective on low-carbon green and sustainable development strategies for industrial carbon emissions in the Yellow River Basin, and emphasizes the importance of constructing detailed, diversified and innovative management strategies in the face of climate change challenges.

Assessing muscle invasion in bladder cancer via virtual biopsy: a study on quantitative parameters and classical radiomics features from dual-energy CT imaging.

OBJECTIVE: To evaluate the prediction value of Dual-energy CT (DECT)-based quantitative parameters and radiomics model in preoperatively predicting muscle invasion in bladder cancer (BCa). MATERIALS AND METHODS: A retrospective study was performed on 126 patients with BCa who underwent DECT urography (DECTU) in our hospital. Patients were randomly divided into training and test cohorts with a ratio of 7:3. Quantitative parameters derived from DECTU were identified through univariate and multivariate logistic regression analysis to construct a DECT model. Radiomics features were extracted from the 40, 70, 100 keV and iodine-based material-decomposition (IMD) images in the venous phase to construct radiomics models from individual and combined images using a support vector machine classifier, and the optimal performing model was chosen as the final radiomics model. Subsequently, a fusion model combining the DECT parameters and the radiomics model was established. The diagnostic performances of all three models were evaluated through receiver operating characteristic (ROC) curves and the clinical usefulness was estimated using decision curve analysis (DCA). RESULTS: The normalized iodine concentration (NIC) in DECT was an independent factor in diagnosing muscle invasion of BCa. The optimal multi-image radiomics model had predictive performance with an area-under-the-curve (AUC) of 0.867 in the test cohort, better than the AUC = 0.704 with NIC. The fusion model showed an increased level of performance, although the difference in AUC (0.893) was not statistically significant. Additionally, it demonstrated superior performance in DCA. For lesions smaller than 3 cm, the fusion model showed a high predictive capability, achieving an AUC value of 0.911. There was a slight improvement in model performance, although the difference was not statistically significant. This improvement was observed when comparing the AUC values of the DECT and radiomics models, which were 0.726 and 0.884, respectively. CONCLUSION: The proposed fusion model combing NIC and the optimal multi-image radiomics model in DECT showed good diagnostic capability in predicting muscle invasiveness of BCa.

Global research trends on the links between gut microbiota and radiotherapy: a bibliometric analysis (2004-2023).

Background: There is a crosstalk between gut microbiota and radiotherapy. The aim of this study is to use bibliometric analysis to explore the research status and development trends of research on gut microbiota and radiotherapy. Methods: A literature search regarding publications on gut microbiota and radiotherapy from 2004 to 2023 was retrieved. CiteSpace and VOSviewer were used to conduct the bibliometric analysis. The growth rate of publications, leading countries and institutions, preferred journals, top authors and co-cited authors, top co-cited references, keywords and citation were analyzed in this study. Results: A total of 2821 papers were extracted. The number of papers has increased rapidly over the past decade, especially after 2017. The USA and China had the most publications and made great contributions to this field. The Chinese Academy of Sciences stood out as the institution with the highest number of publications, followed by the Chinese Academy of Medical Sciences & Peking Union Medical College. The most influential authors were Fan Saijun and Li Yuan. PLoS One had the most publications and the most total citations. Highly cited papers and high-frequency keywords illustrated the current status and trends. Furthermore, analysis of keyword with burst revealed that immunotherapy, acid, intestinal barrier, therapy, immunotherapy, fecal microbiota transplantation, etc, are at the forefront of research in this area. Conclusion: This study provides an overview of research on gut microbiota and radiotherapy, highlighting influential contributors, impactful publications, and emerging trends. Our finding suggests avenues for further exploration to improve clinical outcomes.

Ultrasensitive Electrochemical Biosensor with Powerful Triple Cascade Signal Amplification for Detection of MicroRNA.

In this work, by ingeniously integrating catalytic hairpin assembly (CHA), double-end Mg2+-dependent DNAzyme, and hybridization chain reaction (HCR) as a triple cascade signal amplifier, an efficient concatenated CHA-DNAzyme-HCR (CDH) system was constructed to develop an ultrasensitive electrochemical biosensor with a low-background signal for the detection of microRNA-221 (miRNA-221). In the presence of the target miRNA-221, the CHA cycle was initiated by reacting with hairpins H1 and H2 to form DNAzyme structure H1-H2, which catalyzed the cleavage of the substrate hairpin H0 to release two output DNAs (output 1 and output 2). Subsequently, the double-loop hairpin H fixed on the electrode plate was opened by the output DNAs, to trigger the HCR with the assistance of hairpins Ha and Hb. Finally, methylene blue was intercalated into the long dsDNA polymer of the HCR product, resulting in a significant electrochemical signal. Surprisingly, the double-loop structure of the hairpin H could prominently reduce the background signal for enhancing the signal-to-noise ratio (S/N). As a proof of concept, an ultrasensitive electrochemical biosensor was developed using the CDH system with a detection limit as low as 9.25 aM, achieving favorable application for the detection of miRNA-221 in various cancer cell lysates. Benefiting from its enzyme-free, label-free, low-background, and highly sensitive characteristics, the CDH system showed widespread application potential for analyzing trace amounts of biomarkers in various clinical research studies.

Unraveling Morphological, Physiological, and Transcriptomic Alterations Underlying the Formation of Little Leaves in Phytoplasma-Infected Sweet Cherry Trees.

Phytoplasmas are minute phytopathogenic bacteria that induce excessive vegetative growth, known as witches'-broom (WB), in many infected plant species during the later stages of infection. The WB structure is characterized by densely clustered little (small) leaves, which are frequently accompanied by chlorosis (yellowing). The mechanisms behind the formation of little leaves within WB structures (LL-WB) are poorly understood. To address this gap, the LL-WB formation was extensively studied using sweet cherry virescence (SCV) phytoplasma-infected sweet cherry plants. Based on morphological examinations, signs of premature leaf senescence were observed in LL-WB samples, including reduced leaf size, chlorosis, and alterations in shape. Subsequent physiological analyses indicated decreased sucrose and glucose levels and changes in hormone concentrations in LL-WB samples. Additionally, the transcriptomic analysis revealed impaired ribosome biogenesis and DNA replication. As an essential process in protein production, the compromised ribosome biogenesis and the inhibited DNA replication led to cell cycle arrest, thus affecting leaf morphogenesis and further plant development. Moreover, the expression of marker genes involved in premature leaf senescence was significantly altered. These results indicate a complicated interplay between the development of leaves, premature leaf senescence, and the pathogen-induced stress responses in SCV phytoplasma-infected sweet cherry trees. The results of this study provide insight into understanding the underlying molecular mechanisms driving the formation of little leaves and interactions between plants and pathogens. The findings might help control phytoplasma diseases in sweet cherry cultivation.

Association between plant and animal protein and biological aging: findings from the UK Biobank.

PURPOSE: This study aimed to evaluate the relationship between plant protein, animal protein and biological aging through different dimensions of biological aging indices. Then explore the effects of substitution of plant protein, animal protein, and their food sources on biological aging. METHODS: The data came from 79,294 participants in the UK Biobank who completed at least two 24-h dietary assessments. Higher Klemera-Doubal Method Biological Age (HKDM-BA), higher PhenoAge (HPA), higher allostatic load (HAL), and longer telomere length (LTL) were estimated to assess biological aging. Logistic regression was used to estimate protein-biological aging associations. Substitution model was performed to assess the effect of dietary protein substitutions. RESULTS: Plant protein intake was inversely associated with HKDM-BA, HPA, HAL, and positively associated with LTL (odds ratios after fully adjusting and comparing the highest to the lowest quartile: 0.83 (0.79-0.88) for HKDM-BA, 0.86 (0.72-0.94) for HPA, 0.90 (0.85-0.95) for HAL, 1.06 (1.01-1.12) for LTL), while animal protein was not correlated with the four indices. Substituting 5% of energy intake from animal protein with plant protein, replacing red meat or poultry with whole grains, and replacing red or processed meat with nuts, were negatively associated with HKDM-BA, HPA, HAL and positively associated with LTL. However, an inverse association was found when legumes were substituted for yogurt. Gamma glutamyltransferase, alanine aminotransferase, and aspartate aminotransferase mediated the relationship between plant protein and HKDM-BA, HPA, HAL, and LTL (mediation proportion 11.5-24.5%; 1.9-6.7%; 2.8-4.5%, respectively). CONCLUSION: Higher plant protein intake is inversely associated with biological aging. Although there is no association with animal protein, food with animal proteins displayed a varied correlation.

The longitudinal study of the relationship between social participation pattern and depression symptoms in frail older adults.

Background: Mental health challenges are encountered by frail older adults as the population ages. The extant literature is scant regarding the correlation between depressive symptoms and social participation among frail older adults. Methods: This study is based on an analysis of data from China Health and Retirement Longitudinal Study (CHARLS) participants aged 60 and older who are frail. A frailty index (FI) was developed for the purpose of assessing the frailty level of the participants. Additionally, latent class analysis (LCA) was employed to classify the participants' social engagement patterns in 2015 and 2018. The study used ordered logistic regression to examine the relationship between social participation type and depressive symptoms. We also used Latent Transition Analysis (LTA) methods to explore the impact of changes in social activity types on depressive symptoms after three years of follow-up in 2018. In addition, the response surface analysis (RSM) investigation explored the relationship among FI, depression, and social participation. Results: A total of 4,384 participants completed the baseline survey; three years later, 3,483 were included in the follow-up cohort. The baseline survey indicates that female older adults in rural areas who are single, have lower incomes, shorter sleep durations, and lighter weights exhibited more severe depressive symptoms. Social participation patterns were categorized into five subgroups by LCA. The findings indicate that individuals classified as "board game enthusiasts" (OR, 0.62; 95% CI, 0.47-0.82) and those as "extensive social interaction" (OR,0.67; 95% CI, 0.49-0.90) have a significantly lower likelihood of developing depressive symptoms compared to the "socially isolated" group. We also discovered that "socially isolated" baseline participants who transitioned to the "helpful individual" group after three years had significantly greater depressed symptoms (OR, 1.56; 95% CI, 1.00-2.44). More social activity types and less FI are linked to lower depression in our study. Conclusion: The results of the study emphasize the importance of social participation patterns and the number of social participation types in relation to the severity of depression among frail older adults individuals. This study's findings may provide important insights for addressing depressive symptoms in frail older adults person.

Metal-Organic Framework Nanofluidic Synapse.

Chemical synapse completes the signaling through neurotransmitter-mediated ion flux, the emulation of which has been a long-standing obstacle in neuromorphic exploration. Here, we report metal-organic framework (MOF) nanofluidic synapses in which conjugated MOFs with abundant ionic storage sites underlie the ionic hysteresis and simultaneously serve as catalase mimetics that sensitively respond to neurotransmitter glutamate (Glu). Various neurosynaptic patterns with adaptable weights are realized via Glu-mediated chemical/ionic coupling. In particular, nonlinear Hebbian and anti-Hebbian learning in millisecond time ranges are achieved, akin to those of chemical synapses. Reversible biochemical in-memory encoding via enzymatic Glu clearance is also accomplished. Such results are prerequisites for highly bionic electrolytic computers.

Synthesis of a Sodium-Ion Cathode Material Na3Fe2(SO4)3F with the Help of Fluorine Element.

The development of cathode materials has always been one of the most crucial areas of research in the field of sodium-ion batteries. Sulfate-based polyanionic materials, known for their high working voltage characteristics, have received widespread attention. In this work, a fluoro-sulfate sodium-ion battery cathode material, Na3Fe2(SO4)3F modified with carbon nanotubes, was developed using a low-temperature solid-state annealing method. This Na3Fe2(SO4)3F cathode exhibits an exceptionally high voltage of 3.77 V, excellent discharge capacity (102 mAh/g at 0.1C), and good rate capability. This material broadens the research directions for cathode materials and holds promise as a foundation for the further development of high-performance sodium-ion batteries.

Plasmapheresis, immunosuppressive therapy and anti-GBM disease prognosis: a cohort study of 107 patients.

BACKGROUND: Anti-glomerular basement membrane (anti-GBM) disease presents with rapidly progressive glomerulonephritis and alveolar hemorrhage, requiring urgent management. In this study, we analyzed the relationship between plasmapheresis strategy, immunosuppressive therapy and the prognosis of anti-GBM disease patients. METHOD: We screened newly diagnosed anti-GBM disease patients at West China Hospital of Sichuan University from 2010 to 2021. The primary outcome was a composite endpoint of in-hospital death or dialysis dependency upon discharge. RESULTS: This study enrolled 107 anti-GBM disease patients. The use of plasmapheresis was independently associated with a reduced risk of primary outcome (OR: 0.179, 95% Cl: 0.051-0.630, p = 0.007), better 2-year (HR: 0.146; 95% CI: 0.038-0.553; p = 0.005) and 8-year patient survival (HR: 0.309; 95% CI: 0.112-0.850; p = 0.023). Restricted cubic spline regression suggested that patients with 5-10 sessions of plasmapheresis had already achieved maximum risk reduction in the primary outcome. Patients who started plasmapheresis at lower serum creatinine (42.9% vs. 96.2%, p < 0.001) or lower anti-GBM antibody levels (44.4% vs. 93.3%, p = 0.030) had lower risk of primary outcome than those at higher levels. Use of high-dose methylprednisolone (p = 0.505), pulsed cyclophosphamide (p = 0.343) or ANCA positivity (p = 0.115) were not related to primary outcome in anti-GBM disease. CONCLUSION: Plasmapheresis was protective for both in-hospital outcome and long-term survival in anti-GBM disease. Patients who initiated plasmapheresis early had a better prognosis and might only need 5-10 plasmapheresis sessions to achieve maximal risk reduction. Use of high-dose methylprednisolone or cyclophosphamide pulses was not related to improved short- or long-term outcomes in anti-GBM disease.

Elucidation of the molecular mechanism of type 2 diabetes mellitus affecting the progression of nonalcoholic steatohepatitis using bioinformatics and network pharmacology: A review.

Increasing evidence suggests that patients with diabetes are at increased risk of developing nonalcoholic steatohepatitis (NASH), but the underlying mechanisms that affect the progression of NASH remain unclear. In this study, we used bioinformatics and network pharmacology methods to explore the differentially expressed genes of NASH and the related genes of type 2 diabetes mellitus, and a total of 46 common targets were obtained. Gene ontology showed that the common targets were mainly involved in biological processes such as glucocorticoid, hormone, and bacterium responses. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis signal pathways were mainly in colorectal cancer, amphetamine addition, the peroxisome proliferator-activated receptor signaling pathway, and the toll-like receptor signaling pathway. The protein-protein interaction network identified 8 hub genes, and the co-expression network was analyzed to obtain 7 related functions and mutual proportions of hub genes. A total of 120 transcription factors were predicted for hub genes. Hub genes were closely related to immune cells, including neutropils and eosinophils. In addition, we identified 15 potential candidate drugs based on hub genes that are promising for the treatment of NASH. Type 2 diabetes mellitus can affect the progression of NASH by changing hormone levels and inflammatory responses through multiple targets and signaling pathways. Eight hub genes are expected to be potential targets for subsequent treatment.

IMAGING PREDICTORS OF FUNCTIONAL OUTCOMES AFTER RHEGMATOGENOUS RETINAL DETACHMENT REPAIR.

PURPOSE: To evaluate the microstructural optical coherence tomography and fundus autofluorescence imaging predictors of visual acuity, metamorphopsia, and aniseikonia following rhegmatogenous retinal detachment repair. METHODS: This is a multicenter retrospective study of patients with primary rhegmatogenous retinal detachment who underwent repair. Best-corrected visual acuity, metamorphopsia, and aniseikonia were formally tested at 3 months postoperatively. Metamorphopsia and aniseikonia were quantitatively assessed with M-CHARTS and the New Aniseikonia Test, respectively. High-resolution spectral-domain optical coherence tomography and fundus autofluorescence images were obtained at 3 months postoperatively. Images were assessed for discontinuity of the outer retinal bands on optical coherence tomography and retinal displacement detected by retinal vessel printings on fundus autofluorescence by two masked graders with disagreements adjudicated by a third senior masked grader. Multiple linear regression models were used to determine the predictors of postoperative visual acuity, metamorphopsia, and aniseikonia. RESULTS: Six hundred fourteen eyes of 614 patients were included in this study. Regression analysis indicated that significant early postoperative (at 3 months) imaging predictors of visual acuity were discontinuity of the external limiting membrane (P = 0.001) and the presence of retinal vessel printings on fundus autofluorescence (P = 0.033). Discontinuity of interdigitation zone was a significant predictor of metamorphopsia [horizontal metamorphopsia (P =0.004); vertical metamorphopsia (P = 0.056); average of horizontal metamorphopsia + vertical metamorphopsia (P = 0.008)], and presence of retinal vessel printings was a significant predictor of aniseikonia (P = 0.04). CONCLUSION: Discontinuity of the external limiting membrane and retinal displacement were significant predictors of postoperative visual acuity following rhegmatogenous retinal detachment repair. Discontinuity of the interdigitation zone and retinal displacement were significant predictors of metamorphopsia and aniseikonia, respectively.

Efficient PPCPs removal from wastewaters via a novel A/O-MBBR system: Transition towards circular economy in the water sector.

As industrial and agricultural production depends on water supply, it is crucial for economic development. The available freshwater reserves on Earth are insufficient to meet humanity's growing demands. This study establishes a three-stage anoxic/oxic (A/O)-moving bed biofilm reactor (MBBR) system. The study evaluated the wastewater purification capacity of the system in summer and winter, examined the system's removal efficiency of 10 pharmaceuticals and personal care products (PPCPs) from the water, and analyzed the composition of microbial communities. Results indicate that the system effectively removes pollutants and PPCPs, with the aerobic tanks in the first two A/O stages playing a significant role in PPCP removal. The system is effective in removing four kinds of pollutants: AMP, IBU, CLR, and CAF, and the removal efficiency of CAF is up to 99.2%. Seasonal variations significantly affect the removal of PPCPs and bacterial growth, leading to changes in bacterial species. At the genus level, 41 bacterial types presented different effects in response to temperature changes, with Trichoderma and c_OM190_unclassified being the most affected. This study provides essential theoretical support for reducing pollutant levels and improving water recycling and economic efficiency.

Barriers and facilitators of the nurse providing evidence-based preoperative visit-care for transcatheter aortic valve replacement: a mixed-methods study based on an evidence application setting.

BACKGROUND: Preoperative visit-care for transcatheter aortic valve replacement (TAVR) plays a crucial role in improving the quality of care and patient safety. However, preoperative care for TAVR patients is still in its early stages in China, with the care often being experience-based. The application of relevant evidence in nursing practice is necessary. Little is known regarding the facilitators and barriers to apply and compliance to the evidences about preoperative visit-care for TAVR in nursing. METHODS: The Nurse's Compliance Checklist was used to investigate the evidence-based compliance of nurses (n = 21) who worked in the TAVR team in the evidence-based implementation setting. Meanwhile, an Evidence-Based Practice Beliefs Scale, and Influencing Factors Checklist were used to investigate all nurses (n = 66) who work in the same setting. Stakeholders (Middle and senior-level nursing administrators, frontline clinical nurses, and patients) interview was carried out to further disclose the barriers and facilitators in the process of evidence-based practice. RESULTS: The results of this study showed that only 1 evidence implemented fully (100%) by nurses, 3 evidences with 0% implementation rate, and implementation rate of the other evidences were 9.5∼71.4%. The overall score of nurses' evidence-based nursing belief level was (3.52 ± 0.82). Three domains of barriers were identified: the Context Domain included lack of nursing procedures, inadequate health education materials, insufficient training; the Practitioner Domain included insufficient attention, lack of relevant knowledge, high work pressure and uncertainty of expected results, and Patient Domain included lack of relational knowledge. Facilitating factors included leadership support, nurse' high evidence-based nursing belief, high executive ability and enthusiasm for learning. CONCLUSION: The study indicated that the nurses' compliance of evidence-based practice in preoperative visit-care for TAVR was in lower level. There were some factors influencing the application of the evidences. The study revealed potential modifiable barriers to the successful implementation of evidence-based preoperative visit-care, including a lack of preoperative visit- care routine, related knowledge and training. Leadership support and nurse training should be considered to improve nurses' compliance with evidence-based practice.

Developing and Validating of the Family Coping Scale for Patients with Chronic Heart Failure.

Background: : Family coping, as an essential part of family management of patients with chronic heart failure (CHF), is an important component of CHF interventions, affecting the health of patients, family members, and the whole family. It is necessary to understand the current situation of family coping in patients with CHF to facilitate the development of family interventions for patients with CHF. This study aims to develop and validate a tool for assessing the family coping scale for patients with CHF. Methods: The semi-structured interviews, expert consensus meetings, expert consultations, and item analysis were used to develop the initial scale. We employed classical test theory and exploratory factor analysis to scrutinize and refine the items in the scale. To validate the scale, we used confirmatory factor analysis to assess structural validity. We assessed internal consistency, and split-half reliability to ensure the scale's robustness and accuracy. Results: The FCS-CHF consisted of 24 items, including six dimensions: strategies for better management of CHF, psychological coping, substantial support by family members, emergency coping, overall heart failure awareness, and patients' health behavior. The results of confirmatory factor analysis showed that the scale fitted the data with well construct validity. The results of the confirmatory factor analysis for the overall goodness of fit indices for the fitted model were found to be acceptable for the scale. The scale demonstrates good reliability and validity, meeting the requirements of psychometrics. Conclusions: The FCS-CHF developed in this study is considered reliable and valid, which can measure family coping in patients with CHF and provide a basis for developing family coping enhancement strategies.

Clinical study on improving the diagnostic accuracy of adult elbow joint cartilage injury by multisequence magnetic resonance imaging.

BACKGROUND: Due to frequent and high-risk sports activities, the elbow joint is susceptible to injury, especially to cartilage tissue, which can cause pain, limited movement and even loss of joint function. AIM: To evaluate magnetic resonance imaging (MRI) multisequence imaging for improving the diagnostic accuracy of adult elbow cartilage injury. METHODS: A total of 60 patients diagnosed with elbow cartilage injury in our hospital from January 2020 to December 2021 were enrolled in this retrospective study. We analyzed the accuracy of conventional MRI sequences (T1-weighted imaging, T2-weighted imaging, proton density weighted imaging, and T2 star weighted image) and Three-Dimensional Coronary Imaging by Spiral Scanning (3D-CISS) in the diagnosis of elbow cartilage injury. Arthroscopy was used as the gold standard to evaluate the diagnostic effect of single and combination sequences in different injury degrees and the consistency with arthroscopy. RESULTS: The diagnostic accuracy of 3D-CISS sequence was 89.34% ± 4.98%, the sensitivity was 90%, and the specificity was 88.33%, which showed the best performance among all sequences (P < 0.05). The combined application of the whole sequence had the highest accuracy in all sequence combinations, the accuracy of mild injury was 91.30%, the accuracy of moderate injury was 96.15%, and the accuracy of severe injury was 93.33% (P < 0.05). Compared with arthroscopy, the combination of all MRI sequences had the highest consistency of 91.67%, and the kappa value reached 0.890 (P < 0.001). CONCLUSION: Combination of 3D-CISS and each sequence had significant advantages in improving MRI diagnostic accuracy of elbow cartilage injuries in adults. Multisequence MRI is recommended to ensure the best diagnosis and treatment.

Optimizing the dosing regimen of roxadustat in kidney transplant recipients with early post-transplant anemia.

INTRODUCTION: Roxadustat, an oral inhibitor of hypoxia-inducible factor prolyl hydroxylase domain enzymes, has been approved for the treatment of renal anemia. However, there is a lack of study on its pharmacokinetics in kidney transplant recipients (KTRs) with early posttransplant anemia (PTA). Therefore, the aim of this study is to elucidate the pharmacokinetic characteristics of roxadustat in KTRs with early PTA and optimize the dosing regimen. METHODS: A population pharmacokinetic (PopPK) analysis was performed based on 72-hour full concentration-time profiles collected from 52 Chinese KTRs. Covariates influencing exposure were assessed using stepwise covariate modelling. Monte Carlo simulations were conducted to recommend the dosing regimen for patients with different levels of covariates. RESULTS: PopPK analysis showed that the concentration-time data can be fully described by a two-compartment model. Body weight (BW) and direct bilirubin (DBIL) levels significant affected the apparent clearance of roxadustat. Based on the established model and the estimated exposures of roxadustat by Monte Carlo simulations, a recommended dosing regimen for KTRs with early PTA at varying BW and DBIL levels were developed. Roxadustat at 100 mg three times weekly were suitable for the majority of KTRs with a DBIL level around 3 µmol/L and BW between 50 and 75 kg. The required dose may need to be increased with higher BW and lower DBIL levels, while decreased with lower BW and higher DBIL levels. CONCLUSIONS: It was the first PopPK analysis of roxadustat in KTRs with early PTA, which provide a research basis for optimizing the dosing regimen.

Dynamic Brain Lipid Profiles Modulate Microglial Lipid Droplet Accumulation and Inflammation Under Ischemic Conditions in Mice.

Microglia are critically involved in post-stroke inflammation affecting neurological outcomes. Lipid droplet (LD) accumulation in microglia results in a dysfunctional and pro-inflammatory state in the aged brain and worsens the outcome of neuroinflammatory and neurodegenerative diseases. However, the role of LD-rich microglia (LDRM) under stroke conditions is unknown. Using in vitro and in vivo stroke models, herein accumulation patterns of microglial LD and their corresponding microglial inflammatory signaling cascades are studied. Interactions between temporal and spatial dynamics of lipid profiles and microglial phenotypes in different post-stroke brain regions are found. Hence, microglia display enhanced levels of LD accumulation and elevated perilipin 2 (PLIN2) expression patterns when exposed to hypoxia or stroke. Such LDRM exhibit high levels of TNF-α, IL-6, and IL-1ß as well as a pro-inflammatory phenotype and differentially expressed lipid metabolism-related genes. These post-ischemic alterations result in distinct lipid profiles with spatial and temporal dynamics, especially with regard to cholesteryl ester and triacylglycerol levels, further exacerbating post-ischemic inflammation. The present study sheds new light on the dynamic changes of brain lipid profiles and aggregation patterns of LD in microglia exposed to ischemia, demonstrating a mutual mechanism between microglial phenotype and function, which contributes to progression of brain injury.

Bombyx mori serpin 3 is involved in innate immunity by interacting with serine protease 7 to regulate prophenoloxidase activation.

A subfamily of conserved proteins called serpins plays crucial roles in various physiological functions, particularly in the activation pathway of the serine protease cascade, an essential component of insect innate immunity. Here, we found Bombyx mori serpin 3 (BmSerpin3) was most highly expressed in the fat body, and was up-regulated after exposure to bacteria, fungus and virus. Further, the expression of BmSerpin3 in the hemocytes, fat body, midgut of silkworm larvae, and BmN cells was up-regulated upon Bombyx mori nucleopolyhedrovirus (BmNPV) infection. Through Bac-to-Bac expression system, we obtained the active protein of BmSerpin3, and the enzyme activity assay showed that BmSerpin3 significantly inhibited the activity of both subtilisin and trypsin. In addition, BmSerpin3 could inhibit the activation of prophenoloxidase (PPO) in larvae. The knockdown of BmSerpin3 showed increased phenoloxidase (PO) activity compared to control after BmNPV infection. Ultimately, we confirmed that BmSerpin3 interacts with B. mori Serine Protease 7 (BmSP7). Hence, we hypothesize that BmSerpin3 is involved in innate immunity by interacting with BmSP7 to regulate the PPO activation cascade. Taken together, these results showed that BmSerpin3 play a role in silkworm innate immunity and lay a foundation for studying its functions.

AI approaches for the discovery and validation of drug targets.

Artificial intelligence (AI) holds immense promise for accelerating and improving all aspects of drug discovery, not least target discovery and validation. By integrating a diverse range of biological data modalities, AI enables the accurate prediction of drug target properties, ultimately illuminating biological mechanisms of disease and guiding drug discovery strategies. Despite the indisputable potential of AI in drug target discovery, there are many challenges and obstacles yet to be overcome, including dealing with data biases, model interpretability and generalisability, and the validation of predicted drug targets, to name a few. By exploring recent advancements in AI, this review showcases current applications of AI for drug target discovery and offers perspectives on the future of AI for the discovery and validation of drug targets, paving the way for the generation of novel and safer pharmaceuticals.