Objective:To analyze the correlation and consistency of urine protein creatinine ratio (UPCR) with 24-hour urine protein quantification (24hUTP) in patients with lupus nephritis (LN).Methods:LN patients were enrolled from the STAR cohort of Peking University First Hospital, The time period is January 1, 2007 to July 31 2024. The correlation and consistency of UPCR with 24hUTP were analyzed in overall patients and various subgroups, such as,the levels of proteinuria and multiple parameters. The correlation was analyzed using Spearman′s method. The consistency was evaluated by using Kappa test, cross tabulation consistency probability, and UPCR/24hUTP ratio.Results:A total of 261 LN patients were included in this study. Overall, UPCR was positively correlated with 24hUTP ( r=0.892, P<0.001), and the consistency between then was good ( Kappa=0.603, P<0.001). Subgroup analysis based on multiple levels including different urine volume, eGFR grading, albumin, urea nitrogen, total cholesterol, low-density lipoprotein cholesterol, SLEDAI-2K, also revealed good correlation ( r=0.747~0.951; P<0.001) and consistency ( Kappa=0.393~0.771; P<0.001). Patients were divided into subgroups according to the 24hUTP (≤ 0.5 g, >0.5 g to ≤1.0 g, >1.0 g to ≤3.5 g, and>3.5 g). The best correlation and consistency were observed in ≤ 0.5g group ( r=0.728, Kappa=0.395, P<0.001), while the correlation was average or poor in other subgroups ( r=0.16~0.46). The consistency evaluated by UPCR/24hUTP ratio showed good consistency (ratios between 0.8~1.2) in 74 patients (28.4%), however, the unsatisfactory consistency in most patients, with 128 patients (68.4%) having ratios < 0.8, indicating a significantly lower UPCR than 24hUTP, and 59 patients (31.6%) having ratios > 1.2, indicating significantly higher UPCR than 24hUTP.The cross tabulation evaluation showed that the probability of consistency was distributed in a gradient, we found the worst consistency (48.9%) in >0.5 g to ≤1.0 g group, moderate consistency (64.0%) in >1.0 g to ≤3.5 g group, and the best consistency (73.3%) in >3.5 g group. Conclusion:In LN patients, the overall correlation and consistency between UPCR and 24hUTP are good, but the degree of correlation and consistency is closely related to the total amount of proteinuria. When 24hUTP ≤ 0.5 g, UPCR can be used to replace 24hUTP, but UPCR cannot be simply equated with 24hUTP at other urinary protein levels. Detecting 24hUTP to accurately reflect the total amount of proteinuria remain necessary.

Objective:To explore the training experiences of palliative care nurses participating in a prognosis disclosure workshop based on Kolb's experiential learning model, and to provide references for future educational programs in palliative care nursing.Methods:Using purposive sampling, 11 nurses were recruited who had participated in the "Palliative Care Competency Training Program for Nurses" in Shanghai between March and May 2025 and selected the Third Affiliated Hospital of Naval Medical University as their clinical training site. Semi-structured interviews were conducted, and data were analyzed using Colaizzi's seven-step method.Results:A total of three major themes emerged: a sense of benefit from enhanced competencies; complex emotional experiences; recommendations for course optimisation.Conclusions:Workshops based on Kolb's experiential learning model offer positive value in palliative care education. They effectively improve core competencies such as communication and empathy. However, the emotional experiences of nurses must also be considered, and multifaceted optimizations to the training design are recommended to further enhance training outcomes.

Advancements in artificial intelligence(AI)and emerging technologies are rapidly expanding the exploration of chemical space,facilitating innovative drug discovery.However,the transformation of novel compounds into safe and effective drugs remains a lengthy,high-risk,and costly process.Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development.Despite this need,no comprehensive tool currently supports systematic evaluation and efficient screening.Here,we present druglikeFilter,a deep learning-based framework designed to assess drug-likeness across four critical dimensions:1)physicochemical rule evaluated by systematic determination,2)toxicity alert investigated from multiple perspectives,3)binding affinity measured by dual-path analysis,and 4)compound synthesizability assessed by retro-route prediction.By enabling automated,multidimensional filtering of compound libraries,druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates,which can be freely accessed at https://idrblab.org/drugfilter/.

Objective:To analyze the serological and molecular characteristics of rare A el and B el subtypes in the ABO blood group system, and to explore their genotype-phenotype correlation and the potential clinical significance. Methods:From January 1st, 2021, to January 1st, 2025, 289, 815 samples subjected to ABO blood grouping in Henan Provincial People′s Hospital were selected. Samples demonstrating discrepancies between forward and reverse typing, or consistent typing but with abnormal agglutination degree were included. Those affected by underlying diseases, transplantation, age-related and other interferences were excluded. A total of 169 suspected ABO subgroup samples were identified. Sanger sequencing of exons 1-7 and relevant regulatory regions of the ABO gene was performed. Protein structure modeling and mutation effect analysis for two'el′ subtype glycosyltransferases (GTs) were conducted using SWISS-MODEL and PyMOL.Results:A total of 12 Ael, 6 B el, and 2 AB el subtypes were identified. Serological analysis revealed that all 18 A el/B el samples exhibited O phenotype in forward typing. Among them, A el subtypes showed weaker agglutination in reverse typing with A 1c than with Bc (>2+), while the opposite pattern was observed in B el subtypes. The two AB el samples were typed as A in forward typing, with agglutination ranging from 0-1+with Bc in reverse typing. Genetic analysis indicated that AEL.02 (c.646T>A, p.Phe216Ile) was the predominant allele in A el samples accounting for 7 cases. Also, we found an AEL.02-like variant (lacking c.681G>A), AEL.10 (c.963insC), and carrying a compound variant of c.322C>T (p.Gln108Ter) and c.296C>T (p.Thr99Ile). Among B el samples, BEL.03 (c.502C>T, p.Arg168Trp) accounted for 4 cases, one of which lacked the c.297A>G mutation, and novel mutations such as c.145_146dupCG were detected. Structural simulation demonstrated that AEL.02 and BEL.03 disrupted the hydrogen-bonding network within the active centers of GTA and GTB, respectively, and these mutations probably significantly impaired the structural stability of the corresponding GTs. Additionally, the c.296C>T mutation also markedly affected GTA structural stability. Conclusion:A el/B el subtypes are prone to mis-identify routine blood types. Their molecular mechanisms involved a variety of functional variantions, and integrating molecular detection is crucial for achieving accurate sub-typing and transfusion safety.

Drug development encompasses multiple processes,wherein protein subcellular localization is essential.It promotes target identification,treatment development,and the design of drug delivery systems.In this research,a deep learning framework called LocPro is presented for predicting protein subcellular localization.Specifically,LocPro is unique in(a)combining protein representations from the pre-trained large language model(LLM)ESM2 and the expert-driven tool PROFEAT,(b)implementing a hybrid deep neural network architecture that integrates convolutional neural network(CNN),fully connected(FC)layer,and bidirectional long short-term memory(BiLSTM)blocks,and(c)developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels.Additionally,a dataset was curated and divided using a homology-based strategy for training and validation.Compar-ative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction.The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization.All in all,LocPro serves as a valuable complement to existing protein localization prediction tools.The web server is freely accessible at https://idrblab.org/LocPro/.

Objective: To investigate the trends in incidence and mortality of esophageal cancer in cancer registration areas of Anhui Province from 2014 to 2020, so as to provide the basis for formulating prevention and control measures. Methods: The incidence and mortality data of esophageal cancer in Anhui Province from 2014 to 2020 was collected through the Cancer Registry in Anhui Province. The crude incidence and crude mortality were calculated. The Chinese population-standardized rate was standardized using the age structure of the standard population from the Fifth National Population Census in 2000. The trends in incidence and mortality of esophageal cancer were analyzed using the average annual percent change (APPC), stratified by genders, urban/rural areas, and ages. Results: In Anhui Province, the rank of esophageal cancer incidence dropped from the third in 2014 to the sixth in 2020. Concurrently, the crude incidence and Chinese population-standardized incidence declined from 28.74/100 000 and 20.74/100 000 to 19.23/100 000 and 10.59/100 000, respectively (AAPC=-5.846%, -9.658%, both P<0.05). The mortality rank remained stable at the fourth in 2014 and 2020, while the crude mortality and Chinese population-standardized mortality decreased from 19.96/100 000 and 14.09/100 000 to 16.00/100 000 and 8.41/100 000, respectively (AAPC=-3.542%, -7.784%, both P<0.05). The Chinese population-standardized incidence (AAPC=-9.682%, -9.188%, -6.175% and -12.575%, all P<0.05) and Chinese population-standardized mortality (AAPC=-7.734%. -7.447%. -5.366% and -10.209%, all P<0.05) showed declining trends in males, females, urban, and rural areas, respectively. From 2014 to 2020 in Anhui Province, the crude incidence and mortality of esophageal cancer generally increased with age. However, significant declining trends were observed in crude incidence (AAPC=-12.779%, -11.701%, -11.955% and -5.751%, all P<0.05) and crude mortality (AAPC=-12.255%, -11.120%, -10.985% and -5.751%, all P<0.05) for the age groups of 40-<50, 50-<60, 60-<70, 70-<80 years. A significant declining trend in crude incidence was also seen in the ≥80 years group (APPC=-6.334%, P<0.05), but the trend in crude mortality was no statistically significant (P>0.05). Conclusion In registration areas of Anhui Province, the incidence and mortality of esophageal cancer exhibited a declining trend from 2014 to 2020, calling for focused attention on the middle-aged and elderly population and enhanced health behaviors such as tobacco and alcohol control.

Addressing the enduring challenge of evaluating traditional Chinese medicines (TCMs), the integrated evidence chain-based effectiveness evaluation of TCMs (Eff-iEC) has emerged. This paper explored its capacity through a demonstration study that evaluated the effectiveness evidence of six commonly used anti-hepatic fibrosis Chinese patent medicines (CPMs), including Biejiajian Pill (BP), Dahuang Zhechong Pill (DZP), Biejia Ruangan Compound (BRC), Fuzheng Huayu Capsule (FHC), Anluo Huaxian Pill (AHP), and Heluo Shugan Capsule (HSC), using both Eff-iEC and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The recognition of these CPMs within the TCM academic community was also assessed through their inclusion in relevant medical documents. Results showed that the evidence of BRC and FHC received higher assessments in both Eff-iEC and GRADE system, while the assessments for others varied. Analysis of community recognition revealed that Eff-iEC more accurately reflects the clinical value of these CPMs, exhibiting superior evaluative capabilities. By breaking through the conventional pattern of TCMs effectiveness evaluation, Eff-iEC offers a novel epistemology that better aligns with the clinical realities and reasoning of TCMs, providing a coherent methodology for clinical decision-making, new drug evaluations, and health policy formulation.

The translocator protein (TSPO) positron emission tomography (PET) can noninvasively detect neuroinflammation associated with epileptogenesis and epilepsy. This study explored the role of the TSPO-targeting radioligand [¹⁸F]F-TFQC, an m-trifluoromethyl ER176 analog, in the PET neuroimaging of epileptic rats. Initially, [¹⁸F]F-TFQC was synthesized with a radiochemical yield of 8%-10% (EOS), a radiochemical purity of over 99%, and a specific activity of 38.21 ± 1.73 MBq/nmol (EOS). After determining that [¹⁸F]F-TFQC exhibited good biochemical properties, [¹⁸F]F-TFQC PET neuroimaging was performed in epileptic rats at multiple time points in various stages of disease progression. PET imaging showed specific [¹⁸F]F-TFQC uptake in the right hippocampus (KA-injected site, i.e., epileptogenic zone), which was most pronounced at 1 week (T/NT 1.63 ± 0.21) and 1 month (T/NT 1.66 ± 0.20). The PET results were further validated using autoradiography and pathological analysis. Thus, [¹⁸F]F-TFQC can reflect the TSPO levels and localize the epileptogenic zone, thereby offering the potential for monitoring neuroinflammation and guiding anti-inflammatory treatment in patients with epilepsy.

Vascular damage plays a significant role in the onset and progression of Alzheimer's disease (AD). However, the precise molecular mechanisms underlying the induction of neuronal injury by vascular damage remain unclear. The present study aimed to examine the impact of fibrinogen (Fg) on tau pathology. The results showed that Fg deposits in the brains of tau P301S transgenic mice interact with tau, enhancing the cytotoxicity of pathological tau aggregates and promoting tau phosphorylation and aggregation. Notably, Fg-modified tau fibrils caused enhanced neuronal apoptosis and synaptic damage compared to unmodified fibrils. Furthermore, intrahippocampal injection of Fg-modified tau fibrils worsened the tau pathology, neuroinflammation, synaptic damage, neuronal apoptosis, and cognitive dysfunction in tau P301S mice compared to controls. The present study provides compelling evidence linking Fg and tau, thereby connecting cerebrovascular damage to tau pathology in AD. Consequently, inhibiting Fg-mediated tau pathology could potentially impede the progression of AD.
Animals ; tau Proteins/metabolism* ; Alzheimer Disease/metabolism* ; Fibrinogen/metabolism* ; Mice, Transgenic ; Mice ; Disease Models, Animal ; Memory Disorders/metabolism* ; Male ; Mice, Inbred C57BL ; Brain/metabolism* ; Hippocampus/metabolism* ; Protein Aggregation, Pathological/metabolism* ; Apoptosis ; Phosphorylation

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.