Tracking cognitive trajectories in older survivors of COVID-19 up to 2.5 years post-infection.

Emerging evidence suggests that neurological and other post-acute sequelae of COVID-19 can persist beyond or develop following SARS-CoV-2 infection. However, the long-term trajectories of cognitive change after a COVID-19 infection remain unclear. Here we investigated cognitive changes over a period of 2.5 years among 1,245 individuals aged 60 years or older who survived infection with the original SARS-CoV-2 strain in Wuhan, China, and 358 uninfected spouses. We show that the overall incidence of cognitive impairment among older COVID-19 survivors was 19.1% at 2.5 years after infection and hospitalization, evaluated using the Telephone Interview for Cognitive Status-40. Cognitive decline primarily manifested in individuals with severe COVID-19 during the initial year of infection, after which the rate of decline decelerated. Severe COVID-19, cognitive impairment at 6 months and hypertension were associated with long-term cognitive decline. These findings reveal the long-term cognitive trajectory of the disease and underscore the importance of post-infection cognitive care for COVID-19 survivors.

Do inexperienced nurses in the lactation period experience workplace violence? A qualitative study.

Introduction: Among clinical healthcare personnel, nurses face the highest proportion of workplace violence, which has a significant impact on their physical and mental well-being as well as their personal and professional lives. However, little is known about the effects of workplace violence on inexperienced breastfeeding nurses and their experiences during and after breastfeeding when they return to work. This study aimed to explore the experiences of inexperienced breastfeeding nurses who encountered workplace violence and its resulting impacts. Methods: This study employed a descriptive qualitative design. Semi-structured in-depth interviews were conducted with 20 nurses working in various positions and departments at three tertiary hospitals. Purposive and maximum variation sampling techniques were employed. The interview data were analyzed using Colaizzi's method, and the research findings were reported according to Consolidated Criteria for Reporting Qualitative Studies (COREQ)standards. Results: Inferences regarding workplace violence and risks for inexperienced breastfeeding nurses included physical labor (such as lifting heavy objects and performing cardiopulmonary resuscitation), conflicts, inadequate job skills, role confusion, occupational exposure risks, patient violence, and pressure from older adults. An inductive thematic investigation revealed the "Challenges faced during breastfeeding," "Conflicting professional and family roles," "Out of balance," and "Coping strategies." Conclusion: Inexperienced breastfeeding nurses experience several negative consequences due to workplace violence. Therefore, it is essential to plan and implement preventive strategies and management programs that specifically target workplace violence among inexperienced breastfeeding nurses.

Gut Subdoligranulum variabile ameliorates rheumatoid arthritis by promoting TSG-6 synthesis from joint cells.

Background: A burgeoning body of evidence has substantiated the association between alterations in the composition of the gut microbiota and rheumatoid arthritis (RA). Nevertheless, our understanding of the intricate mechanisms underpinning this association is limited. Methods: To investigate whether the gut microbiota influences the pathogenesis of RA through metabolism or immunity, we performed rigorous synthesis analyses using aggregated statistics from published genome-wide association studies (GWAS) using two-sample Mendelian randomization (MR) and mediated MR techniques, including two-step MR and multivariate MR analyses. Subsequently, we conducted in vitro cellular validation of the analyzed Microbial-Cytokine-RA pathway. We determined the optimal culture conditions through co-culture experiments involving concentration and time. Cell Counting Kit-8 (CCK-8) assays were employed to assess cellular viability, and enzyme-linked immunosorbent assays (ELISA) were performed to assess tumor necrosis factor-inducible gene 6 protein (TSG-6) and tumor necrosis factor-α (TNF-α) levels. Results: Our univariable MR results confirmed 15 microbial traits, 7 metabolites and 2 cytokines that may be causally associated with RA (P FDR < 0.05). Mediation analysis revealed that microbial traits influence the risk of RA through metabolite or cytokine (proportion mediated: 7.75% - 58.22%). In vitro experiments demonstrated that TSG-6 was highly expressed in the Subdoligranulum variabile treatment group and was correlated with decreased RA severity (reduced TNF-α expression). Silencing the TSG-6 gene significantly increased TNF-α expression, regardless of treatment with S. variabile. Additionally, S. variabile-secreted exosomes exhibited the same effect. Conclusion: The results of this study suggest that S. variabile has the potential to promote TSG-6 secretion, thereby reducing RA inflammation.

Predictive Value of Troponin I, Creatinine Kinase Isoenzyme and the New Japanese Severity Score in Severe Acute Pancreatitis.

Purpose: To evaluate troponin I, creatine kinase isoenzyme, and the new Japanese Severity Score(JSS) for predicting Severe Acute Pancreatitis-Associated myocardial Injury(SACI). Patients and Methods: This retrospective study included 136 patients with Severe Acute Pancreatitis, hospitalized in grade-III hospital from June 1, 2015, to October 31, 2022; selected using convenience sampling method and divided into SACI occurrence (n =34) and SACI non-occurrence (n =102) groups. New JSS evaluated predictive value of each SACI index. Binary logistic regression model compared risk factors and constructed a prediction model. Area under receiver operating characteristic curve (AUC) and Hosmer-Lemeshow goodness of fit test evaluated model's prediction efficiency and calibration ability. Results: The incidence of SACI was 25%. Univariate analysis found that troponin I and creatine kinase isoenzyme were significantly different (P < 0.05) and independent risk factors for SACI. The new JSS, troponin I, and creatine kinase isoenzyme were included in the prediction model. The prediction model had a good calibration ability, and its predicted value and the actual observed value were not significantly different (Hosmer-Lemeshow χ2 = 5.408, P = 0.368). AUC of the model was 0.803 (95% CI: 0.689-0.918), and the optimal threshold of the prediction model was 0.318 with the maximum Youden index (0.488). The AUC for internal validation was 0.788 (95% CI: 0.657-0.876), and external validation was 0.761 (95% CI: 0.622-0.832). Conclusion: Troponin I and creatine kinase isoenzymes combined with the new JSS have a high predictive value for SACI, improving the early prediction and treatment of at-risk patients.

A self-immobilizing near-infrared fluorogenic probe for in vivo imaging of fibroblast activation protein-α.

Fibroblast activation protein-α (FAP) plays a crucial role in various physiological and pathological processes, making it a key target for cancer diagnostics and therapeutics. However, in vivo detection of FAP activity with fluorogenic probes remains challenging due to the rapid diffusion and clearance of fluorescent products from the target. Herein, we developed a self-immobilizing near-infrared (NIR) fluorogenic probe, Hcy-CF2H-PG, by introducing a difluoromethyl group to FAP substrate-caged NIR fluorophore. Upon selective activation by FAP, the fluorescence of Hcy-CF2H-PG was triggered, followed by the covalent labelling of FAP. Hcy-CF2H-PG demonstrated significantly improved sensitivity, selectivity, and long-lasting labelling capacity for FAP both in vitro and in vivo, compared to that of non-immobilized probes. This represents a noteworthy advancement in FAP detection and cancer diagnostics within complex physiological systems.

MiR-483-3p promotes dental pulp stem cells osteogenic differentiation via the MAPK signaling pathway by targeting ARRB2.

Human dental pulp stem cells (DPSCs) have become an important component for bone tissue engineering and regenerative medicine due to their ability to differentiate into osteoblast precursors. Two miRNA chip datasets (GSE138180 and E-MTAB-3077) of DPSCs osteogenic differentiation were analyzed respectively to find the expression of miR-483-3p significantly increased in the differentiated groups. We further confirmed that miR-483-3p continued to overexpress during osteogenic differentiation of DPSCs, especially reaching its peak on the 7th day. Moreover, miR-483-3p could significantly promote the expression of osteogenic markers including RUNX2 and OSX, and activate MAPK signaling pathway by inducing phosphorylation of ERK, p38, and JNK. In addition, as a significant gene within the MAPK signaling pathway, ARRB2 was identified as the target gene of miR-483-3p by bioinformatic prediction and experimental verification. In conclusion, we identified miR-483-3p could promote osteogenic differentiation of DPSCs via the MAPK signaling pathway by targeting ARRB2.

Mitochondrial Protein TAMM41 Modulates Depressive-like Behaviors.

Several lines of evidence have highlighted the crucial role of mitochondria-based therapy in depression. However, there are still less mitochondrial targets for the depression treatment. TAM41 mitochondrial translocator assembly and maintenance homolog (TAMM41) is a mitochondrial inner membrane protein for maintaining mitochondrial function, which is tightly related to many brain diseases including Alzheimer's diseases and epilepsy. Here, we investigated whether TAMM41 would be a potential target to treat depression. We found that the expression of TAMM41 was markedly lower in corticosterone-induced depression, lipopolysaccharide-induced depression, and depressed patients. Meanwhile, loss of TAMM41 resulted in increased immobility in the forced swim test (FST), tail suspension test (TST), and center time in open field test (OFT), suggesting depressive-like behaviors in mice. Moreover, genetic overexpression of TAMM41 obviously exerted antidepressant-like activities. Mechanistically, proteomics revealed that pacsin1 might be the underlying target of TAMM41. Further data supported that TAMM41 regulated the expression of pacsin1, and its antidepressant-like effect at least partially was attributed to pacsin1. In addition, exosomes containing TAMM41 was sufficient to exhibit antidepressant-like effect, suggesting an alternative strategy to exert the effect of TAMM41. Taken together, the present study demonstrates the antidepressant-like effect of TAMM41 and sheds light on its molecular mechanism. These finding provide new insights into a therapeutic strategy targeting mitochondria in the development of novel antidepressants.

Influence of atomic electronegativity on ESIPT behaviour for the BTDI and its derivatives: Theoretical exploration.

In this work, we theoretically explored the influence of atomic electronegativity on excited-state intramolecular proton transfer (ESIPT) behavior among novel fluorescent probes BTDI and its derivatives (BODI and BSeDI). A thorough examination of the optimized structural parameters and infrared vibrational spectra reveals an enhancement in intramolecular hydrogen bonding within BTDI and its derivatives upon light excitation. This finding is further reinforced by topological analysis and interaction region indicator scatter plots, which underscores the sensitivity of atomic electronegativity to variations in hydrogen bonding strength. With regards to absorption and fluorescence spectra, the decrease in atomic electronegativity leads to a pronounced redshift, primarily attributed to the narrowing of the energy gap. Additionally, an analysis of potential energy curves and the exploration of intrinsic reaction coordinate paths based on transition state structures afford a deeper understanding of the mechanism underlying ESIPT and being modulated through the manipulation of atomic electronegativity. We anticipate that this work on atomic electronegativity regulating ESIPT behavior will serve as a catalyst for novel fluorescent probes in the future, offering fresh perspectives and insights.

Theoretical Insights into the Effect of Different Numbers of Thiophene Groups on Hydrogen Bond Interaction and Excited-State Intramolecular Proton-Transfer Process for Flavonoid Derivatives.

In this study, we systematically explored the impact of varying the number of thiophene groups on the hydrogen bond interaction and excited-state intramolecular proton-transfer (ESIPT) processes in flavonoid derivatives (STF, DTF, and TTF) using the density functional theory and time-dependent density functional theory methods. Initially, a thorough analysis of the optimized geometric structures revealed that the intramolecular hydrogen bond in the S1 state is enhanced and gradually weakened as the number of thiophene groups increases. To gain a deeper understanding of the hydrogen bond interaction, topological analysis, interaction region indicator scatter plots, and isosurface plots were employed. These images provide further insights that align with the structural analysis. Additionally, we observed a red-shift in the electronic spectra (absorption and fluorescence spectra), which is primarily attributed to the narrowing of the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, as elucidated by the frontier molecular orbitals. Furthermore, a combined analysis between the hole-electron distribution and the transition density matrix heat map shows that electron excitation involves the unidirectional charge-transfer mechanism. In the end, by conducting relaxed potential energy curve scans, we found that an increase in the number of thiophene groups elevates the energy barrier for ESIPT, making it more challenging for the reaction. In summary, our study underscores the vital effect of thiophene-substituted numbers in modulating the ESIPT process, which is able to provide valuable insights for the design and synthesis of desired organic fluorescent probes in the future.

Lipoproteins and metabolites in diagnosing and predicting Alzheimer's disease using machine learning.

BACKGROUND: Alzheimer's disease (AD) is a chronic neurodegenerative disorder that poses a substantial economic burden. The Random forest algorithm is effective in predicting AD; however, the key factors influencing AD onset remain unclear. This study aimed to analyze the key lipoprotein and metabolite factors influencing AD onset using machine-learning methods. It provides new insights for researchers and medical personnel to understand AD and provides a reference for the early diagnosis, treatment, and early prevention of AD. METHODS: A total of 603 participants, including controls and patients with AD with complete lipoprotein and metabolite data from the Alzheimer's disease Neuroimaging Initiative (ADNI) database between 2005 and 2016, were enrolled. Random forest, Lasso regression, and CatBoost algorithms were employed to rank and filter 213 lipoprotein and metabolite variables. Variables with consistently high importance rankings from any two methods were incorporated into the models. Finally, the variables selected from the three methods, with the participants' age, sex, and marital status, were used to construct a random forest predictive model. RESULTS: Fourteen lipoprotein and metabolite variables were screened using the three methods, and 17 variables were included in the AD prediction model based on age, sex, and marital status of the participants. The optimal random forest modeling was constructed with "mtry" set to 3 and "ntree" set to 300. The model exhibited an accuracy of 71.01%, a sensitivity of 79.59%, a specificity of 65.28%, and an AUC (95%CI) of 0.724 (0.645-0.804). When Mean Decrease Accuracy and Gini were used to rank the proteins, age, phospholipids to total lipids ratio in intermediate-density lipoproteins (IDL_PL_PCT), and creatinine were among the top five variables. CONCLUSIONS: Age, IDL_PL_PCT, and creatinine levels play crucial roles in AD onset. Regular monitoring of lipoproteins and their metabolites in older individuals is significant for early AD diagnosis and prevention.

CSF2 Impairs Nrf2 Signaling through the Akt/Mtor Pathway in the Development of Bladder Cancer.

Bladder Cancer (BCa) is one of the most common cancers of the urinary system. Colony-stimulating factor 2 (CSF2) is involved in many cancers, but not BCa. We investigated the effect of CSF2 on BCa in this study and the underlying molecular mechanisms. CSF2 mRNA levels in BCa were analyzed using the Cancer Genome Atlas (TCGA) database. Western blot was conducted to verify CSF2 expression in BCa tissue samples and cell lines. The effect of CSF2 on the growth of BCa cells was assessed by CCK8 and colony formation. To determine the migration and invasion capabilities of BCa cells, transwell analysis and wound healing assays were conducted. Next, western blot was used to explore the underlying mechanism. In the end, a xenografted BCa mouse model was established to examine the effects of CSF2 on tumorigenesis in vivo. Results showed that CSF2 mRNA was upregulated in BCa samples. Knocking down CSF2 significantly inhibited the proliferation and tumorigenesis of BCa cells in vitro and in vivo. Mechanism analysis revealed that CSF2 knockdown inhibited the proliferation and invasion of BCa cells via AKT/mTOR signaling. Based on these results, CSF2 promotes the proliferation and tumorigenesis of BCa.

NRS2002 score as a prognostic factor in solid tumors treated with immune checkpoint inhibitor therapy: a real-world evidence analysis.

To observe the antitumour efficacy of programmed death 1 (PD-1) inhibitors in the real world and explore the relationship between NRS2002 score or other clinical characteristics and immunotherapy efficacy, we retrospectively analyzed 341 tumor patients who received immune checkpoint inhibitor (ICI) treatment at one center. A total of 341 solid tumor patients treated with ICIs from June 2018 to December 2021 were retrospectively included in this study. Patient characteristics, ICI responses, and survival status were documented, and the relationships between clinical factors and survival were analyzed. Among all patients, the median progression-free survival (PFS) was 5.8 months, and the median overall survival (OS) was 12.5 months. The Performance Status (PS), NRS2002 score, The Naples Prognostic Score (NPS), Lymphocyte and C-reactive protein ratio (LCR), line of therapy, and nutritional support were significantly related to PFS or OS according to univariate analysis. The median PFS and OS were significantly better in the group without nutritional risk (NRS2002 0-2) than those with nutritional risk (NRS2002 ≥ 3) (PFS: HR = 1.82, 95% CI 1.30-2.54, p value < .001; OS: HR = 2.49, 95% CI 1.73-3.59, p value < .001). Cox regression analysis revealed that the NRS2002 score was an independent prognostic factor for both PFS and OS. The objective response rate (ORR) in the group at nutritional risk was lower than that in the group without nutritional risk (8.33% and 19.71%, respectively, p value = .037). Patients at nutritional risk according to the NRS2002 score at initial treatment had a poorer prognosis than those without nutritional risk. The NRS2002 could be used as a preliminary index to predict the efficacy of immune checkpoint inhibitor therapy.

DOTA-Based Plectin-1 Targeted Contrast Agent Enables Detection of Pancreatic Cancer in Human Tissue.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive and lethal malignancy with extremely poor patient survival rates. A key reason for the poor prognosis is the lack of effective diagnostic tools to detect the disease at curable, premetastatic stages. Tumor surgical resection is PDAC's first-line treatment, however distinguishing between cancerous and healthy tissue with current imaging tools remains a challenge. In this work, we report a DOTA-based fluorescent probe targeting plectin-1 for imaging PDAC with high specificity. To enable heterogeneous functionalization of the DOTA-core with multiple targeting peptide units and the fluorophore, a novel, fully clickable synthetic route that proceeds in one pot was developed. Extensive validation of the probe set the stage for PDAC detection in mice and human tissue. Altogether, these findings may pave the way for improved clinical understanding and early detection of PDAC progression as well as more accurate resection criteria.

Brusatol hinders the progression of bladder cancer by Chac1/Nrf2/SLC7A11 pathway.

Bladder cancer is a common tumor that impacts the urinary system and marked by a significant fatality rate and an unfavorable prognosis. Promising antineoplastic properties are exhibited by brusatol, which is obtained from the dried ripe fruit of Brucea javanica. The present study aimed to evaluate the influence of brusatol on the progression of bladder cancer and uncover the molecular mechanism involved. We used Cell Counting Kit-8, colony formation and EdU assays to detect cell numbers, viability and proliferation. We used transwell migration assay to detect cell migration ability. The mechanism of brusatol inhibition of bladder cancer proliferation was studied by flow cytometry and western blotting. It was revealed that brusatol could reduce the viability and proliferation of T24 and 5637 cells. The transwell migration assay revealed that brusatol was able to attenuate the migration of T24 and 5637 cells. We found that treatment with brusatol increased the levels of reactive oxygen species, malondialdehyde and Fe2+, thereby further promoting ferroptosis in T24 and 5637 cells. In addition, treatment with RSL3 (an agonistor of ferroptosis) ferrostatin-1 (a selective inhibitor of ferroptosis) enhanced or reversed the brusatol-induced inhibition. In vivo, treatment with brusatol significantly suppressed the tumor growth in nude mice. Mechanistically, brusatol induced ferroptosis by upregulating the expression of ChaC glutathione-specific gamma-glutamylcyclotransferase (Chac1) and decreasing the expression of SLC7A11 and Nrf2 in T24 and 5637 cells. To summarize, the findings of this research demonstrated that brusatol hindered the growth of bladder cancer and triggered ferroptosis via the Chac1/Nrf2/SLC7A11 pathway.

OPUS-Rota5: A highly accurate protein side-chain modeling method with 3D-Unet and RotaFormer.

Accurate protein side-chain modeling is crucial for protein folding and design. This is particularly true for molecular docking as ligands primarily interact with side chains. In this study, we introduce a two-stage side-chain modeling approach called OPUS-Rota5. It leverages a modified 3D-Unet to capture the local environmental features, including ligand information of each residue, and then employs the RotaFormer module to aggregate various types of features. Evaluation on three test sets, including recently released targets from CAMEO and CASP15, shows that OPUS-Rota5 significantly outperforms some other leading side-chain modeling methods. We also employ OPUS-Rota5 to refine the side chains of 25 G protein-coupled receptor targets predicted by AlphaFold2 and achieve a significantly improved success rate in a subsequent "back" docking of their natural ligands. Therefore, OPUS-Rota5 is a useful and effective tool for molecular docking, particularly for targets with relatively accurate predicted backbones but not side chains such as high-homology targets.

WormBase 2024: status and transitioning to Alliance infrastructure.

WormBase has been the major repository and knowledgebase of information about the genome and genetics of Caenorhabditis elegans and other nematodes of experimental interest for over 2 decades. We have 3 goals: to keep current with the fast-paced C. elegans research, to provide better integration with other resources, and to be sustainable. Here, we discuss the current state of WormBase as well as progress and plans for moving core WormBase infrastructure to the Alliance of Genome Resources (the Alliance). As an Alliance member, WormBase will continue to interact with the C. elegans community, develop new features as needed, and curate key information from the literature and large-scale projects.

MRI-based clinical-radiomics nomogram model for predicting microvascular invasion in hepatocellular carcinoma.

BACKGROUND: Preoperative microvascular invasion (MVI) of liver cancer is an effective method to reduce the recurrence rate of liver cancer. Hepatectomy with extended resection and additional adjuvant or targeted therapy can significantly improve the survival rate of MVI+ patients by eradicating micrometastasis. Preoperative prediction of MVI status is of great clinical significance for surgical decision-making and the selection of other adjuvant therapy strategies to improve the prognosis of patients. PURPOSE: Established a radiomics machine learning model based on multimodal MRI and clinical data, and analyzed the preoperative prediction value of this model for microvascular invasion (MVI) of hepatocellular carcinoma (HCC). METHOD: The preoperative liver MRI data and clinical information of 130 HCC patients who were pathologically confirmed to be pathologically confirmed were retrospectively studied. These patients were divided into MVI-positive group (MVI+) and MVI-negative group (MVI-) based on postoperative pathology. After a series of dimensionality reduction analysis, six radiomic features were finally selected. Then, linear support vector machine (linear SVM), support vector machine with rbf kernel function (rbf-SVM), logistic regression (LR), Random forest (RF) and XGBoost (XGB) algorithms were used to establish the MVI prediction model for preoperative HCC patients. Then, rbf-SVM with the best predictive performance was selected to construct the radiomics score (R-score). Finally, we combined R-score and clinical-pathology-image independent predictors to establish a combined nomogram model and corresponding individual models. The predictive performance of individual models and combined nomogram was evaluated and compared by receiver operating characteristic curve (ROC). RESULT: Alpha-fetoprotein concentration, peritumor enhancement, maximum tumor diameter, smooth tumor margins, tumor growth pattern, presence of intratumor hemorrhage, and RVI were independent predictors of MVI. Compared with individual models, the final combined nomogram model (AUC: 0.968, 95% CI: 0.920-1.000) constructed by radiometry score (R-score) combined with clinicopathological parameters and apparent imaging features showed the optimal predictive performance. CONCLUSION: This multi-parameter combined nomogram model had a good performance in predicting MVI of HCC, and had certain auxiliary value for the formulation of surgical plan and evaluation of prognosis.

Dynamically changed HSP70 after reperfusion following cerebral infarction in human and rats: correlation with p38 MAPK.

We aimed to clarify the correlation between dynamic change of blood HSP70 and the prognosis of thrombolysis in human and rats, so as to explain the neuroprotection and early warning role of HSP70 in cerebral ischemia-reperfusion. Forty-two patients with acute ischemic stroke were divided into two groups according to the time from onset to thrombolytic therapy: 0 h-3 h (27 patients) and 3-4.5 h group (15 patients). The level of HSP70 in serum before and after thrombolysis was detected by ELISA. Furthermore, a rat model was also used to mimic the ischemic stroke and reperfusion. Peripheral blood of rat samples was collected to detect the level of HSP70 using Elisa. Several signal proteins from MAPK signaling pathway including JNK, p38, ERK (p42/44) were detected at different time points by Western blot of brain tissue. Patients who underwent thrombolytic therapy within 0-3 h had the highest HSP70 level at 1 h after thrombolysis. The higher HSP70 after thrombolysis, the better the patient prognosis. NIHSS scores showed HSP70 was positively correlated with cerebral ischemia. The levels of ERK family (p42/44 MAPK) and p-JNK were decreased gradually along with the time suffering cerebral ischemia. P-ERK, JNK, p-p38 had dynamic changes with increased ischemic time in the middle cerebral artery occlusion model. Dynamic change of HSP70 level in blood may be a biological index that reflects the functional condition of cell survival for cerebral ischemia and estimating the prognostic conditions. Importantly, HSP70 levels in blood were positively correlated with the p38 MAPK pathway in brain tissue.