Supramolecular Chiral Aggregation of Porphyrin Induced by Photo-Generated Triphenylamines Radical Cations.

Here, it is shown that photoirradiation triggered chiral J-aggregates formation of an achiral anionic porphyrin, TPPS (tetrakis(4-sulfonatophenyl) porphyrin), in the presence of chiral triphenylamine (TPA) derivatives. A series of chiral triarylamines linked with aromatic rings is designed through urea or amide bonds. UV-irradiation of self-assembled urea-linked triphenylamine derivatives causes the formation of persistent radical cations in the chlorinated solvents, which subsequently induces the aggregation of TPPS. Transferring chirality of TPA derivatives to achiral TPPS J-aggregates leads to the chiral assemblies with remarkable chiroptical signals. The experimental results demonstrate that, TPA derivatives linked by the urea bond can effectively promote the aggregation of TPPS rather than those with the amide bond although the photo-generated radical cations are both produced. It is suggested that the urea-linked TPA derivatives are more favorable to stable radical cations and thus cause the formation of TPPS chiral J-aggregation. This work may open up an avenue for designing photo-modulated chiral supramolecular assemblies.

Development of a nomogram for predicting malnutrition in elderly hospitalized cancer patients: a cross-sectional study in China.

Objectives: The Patient-Generated Subjective Global Assessment (PG-SGA) serves as a specialized nutritional assessment instrument designed for cancer patients. Despite its specificity, the complexity and time requirements of this tool, along with the necessity for administration by trained professionals, limit its practicality in clinical settings. Our objective is to identify a straightforward, efficient, and dependable nutritional assessment tool to promote broader adoption in clinical practice. Methods: This study encompassed a total of 450 patients diagnosed with cancer. Of these, 315 individuals constituted the training set, and the remaining 135 were allocated to the external validation set. The model variables were identified through the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. Binary logistic regression outcomes facilitated the development of a nomogram, offering a visual depiction of the predicted probabilities. The predictive accuracy of the nomogram model was evaluated by calculating the area under the Receiver Operating Characteristic (ROC) curve. Results: The LASSO method detected four variables that were included in the final prediction model: age, serum albumin levels (ALB), body mass index (BMI), and activities of daily living (ADL). The area under the curve (AUC) for this prediction model was 0.905. Both the internal and external calibration curves for malnutrition showed that the predictive nomogram model was highly accurate. Conclusion: The study has developed a prediction model that demonstrates remarkable accuracy in forecasting malnutrition. Furthermore, it presents a streamlined nutritional assessment tool aimed at swiftly identifying cancer patients at nutritional risk, thereby facilitating oncologists in delivering targeted nutritional support to these individuals.

Symbiosis of a lytic bacteriophage and Yersinia pestis and characteristics of plague in Marmota himalayana.

Surveillance for animal plague was conducted in the Marmota himalayana plague focus of the Qinghai-Tibet Plateau from 2020 to 2023. A 22.89% positive rate of serum F1 antibody was detected in live-caught marmots, alongside a 43.40% incidence of Yersinia pestis isolation from marmot carcasses. Marmot carcasses infected with plague exhibited a significantly higher spleen-somatic index (P < 0.05). Twenty-one Y. pestis-specific phages were isolated, among which one Y. pestis lytic phage (AKS2022HT87GU_phi) was isolated from the bone marrow of a marmot carcass (no. AKS2022HT87) and was found to be symbiotic with Y. pestis. Microscopy revealed the coexistence of lysed and non-lysed colonies of Y. pestis AKS2022HT87. Genome-wide analysis showed that certain strains of the Y. pestis AKS2022HT87 carried phage DNA fragments consistent with phage AKS2022HT87GU_phi. The rare symbiotic relationship between a lytic phage and Y. pestis observed in vitro was highlighted in this study, laying the basis for further exploring the relationship between Y. pestis and its bacteriophages.IMPORTANCEBacteriophages and host bacteria commonly coexist in vivo or in soil environments through complex and interdependent microbial interactions. However, recapitulating this symbiotic state remains challenging in vitro due to limited medium nutrients. In this work, the natural symbiosis between Yersinia pestis and specific phages has been discovered in a Marmota himalayana specimen. Epidemiological analysis presented the characteristics of the Y. pestis and specific phages in the area with a strong plague epidemic. Crucially, comparative genomics has been conducted to analyze the genetic changes in both the Y. pestis and phages over different periods, revealing the dynamic and evolving nature of their symbiosis. These are the critical steps to study the mechanism of the symbiosis.

Sex differences in the association between sleep duration and muscle quality index in adults: A cross-sectional study from NHANES 2011-2014.

OBJECTIVE: The aim of this study was to investigate the association between sleep duration and muscle quality index (MQI) in middle-aged and older age groups, as limited evidence exists on this topic. METHODS: In order to assess the relationship between sleep duration and MQI, a cross-sectional study was undertaken, utilizing data from the National Health and Nutrition Examination Survey (NHANES) acquired during the period from 2011 to 2014. The study comprised a total of 4598 participants aged 20 years and above. To examine the association between sleep duration and MQI, sophisticated weighted multivariate linear regression models were employed. Additionally, smooth curve fitting techniques were applied to examine the possibility of any non-linear relationship between the two variables. RESULTS: The average age of the adults who were enrolled in the study was 38.48±11.69 years, and 46.75% of them were female. The results of the multivariable linear regression models showed that sleep duration had a positive correlation with MQI. However, when subgroup analysis was conducted, it was found that this positive correlation only existed among women (ß = 0.09, 95% CI: 0.014 to 0.167). To further confirm the differences between sexes in the relationship between sleep duration and MQI, a weighted generalized additive model (GAM) was used. CONCLUSIONS: This research study provides evidence that there is a positive correlation between the duration of sleep and MQI specifically in females, while no such association was observed in males. These findings shed light on the existence of gender disparities in the connection between sleep duration and MQI.

Computational Docking as a Tool in Guiding the Drug Design of Rutaecarpine Derivatives as Potential SARS-CoV-2 Inhibitors.

COVID-19 continues to spread around the world. This is mainly because new variants of the SARS-CoV-2 virus emerge due to genomic mutations, evade the immune system and result in the effectiveness of current therapeutics being reduced. We previously established a series of detection platforms, comprising computational docking analysis, S-protein-based ELISA, pseudovirus entry, and 3CL protease activity assays, which allow us to screen a large library of phytochemicals from natural products and to determine their potential in blocking the entry of SARS-CoV-2. In this new screen, rutaecarpine (an alkaloid from Evodia rutaecarpa) was identified as exhibiting anti-SARS-CoV-2 activity. Therefore, we conducted multiple rounds of structure-activity-relationship (SAR) studies around this phytochemical and generated several rutaecarpine analogs that were subjected to in vitro evaluations. Among these derivatives, RU-75 and RU-184 displayed remarkable inhibitory activity when tested in the 3CL protease assay, S-protein-based ELISA, and pseudovirus entry assay (for both wild-type and omicron variants), and they attenuated the inflammatory response induced by SARS-CoV-2. Interestingly, RU-75 and RU-184 both appeared to be more potent than rutaecarpine itself, and this suggests that they might be considered as lead candidates for future pharmacological elaboration.

Glucose-6-phosphate dehydrogenase alleviates epileptic seizures by repressing reactive oxygen species production to promote signal transducer and activator of transcription 1-mediated N-methyl-d-aspartic acid receptors inhibition.

The pathogenesis of epilepsy remains unclear; however, a prevailing hypothesis suggests that the primary underlying cause is an imbalance between neuronal excitability and inhibition. Glucose-6-phosphate dehydrogenase (G6PD) is a key enzyme in the pentose phosphate pathway, which is primarily involved in deoxynucleic acid synthesis and antioxidant defense mechanisms and exhibits increased expression during the chronic phase of epilepsy, predominantly colocalizing with neurons. G6PD overexpression significantly reduces the frequency and duration of spontaneous recurrent seizures. Furthermore, G6PD overexpression enhances signal transducer and activator of transcription 1 (STAT1) expression, thus influencing N-methyl-d-aspartic acid receptors expression, and subsequently affecting seizure activity. Importantly, the regulation of STAT1 by G6PD appears to be mediated primarily through reactive oxygen species signaling pathways. Collectively, our findings highlight the pivotal role of G6PD in modulating epileptogenesis, and suggest its potential as a therapeutic target for epilepsy.

Pharmacokinetics, Mass Balance, Safety, and Tolerability of Obeldesivir in Healthy Participants.

There is an unmet need for safe and efficacious oral therapies for COVID-19 with low potential for drug-drug interactions. Obeldesivir is an orally administered nucleoside prodrug that has shown antiviral potency in nonclinical studies against SARS-CoV-2 and its circulating variants. Obeldesivir is metabolized to the active nucleoside triphosphate (GS-443902), which acts as an inhibitor of the SARS-CoV-2 RNA-dependent RNA polymerase, thereby inhibiting viral RNA synthesis. Here, we report the safety, tolerability, and pharmacokinetics from a first-in-human, randomized, placebo-controlled, phase I study following oral administration of obeldesivir and a phase I, open-label absorption, distribution, metabolism, and excretion study following oral administration of [14C]-obeldesivir. Overall, obeldesivir was safe and well tolerated at single and multiple doses between 100 and 1,600 mg, with low potential for QT prolongation as assessed by QT-concentration analysis. The exposures to GS-441524 increased dose proportionally in the 100-900-mg dose range. GS-441524 accumulated by 35% after twice-daily and 12% after once-daily dosing for 5 days. Dose-proportional increases in the intracellular concentration of GS-443902 were also observed in peripheral blood mononuclar cells. Plasma exposure of GS-441524 was not significantly altered by food intake. Following oral administration of [14C]-obeldesivir (500 mg; 100 µCi), the mean cumulative [14C]-dose recovery was 90.7% with 58.5% in urine and 32.2% in feces. GS-441524 was the predominant plasma component (90% of 14C-area under the concentration-time curve) and was primarily eliminated via renal excretion. Collectively, data from these studies support selection of the obeldesivir 350 mg twice-daily dosing regimen for further evaluation in phase III studies for COVID-19.

Predictive model for assessing malnutrition in elderly hospitalized cancer patients: A machine learning approach.

BACKGROUND: Malnutrition is prevalent among elderly cancer patients. This study aims to develop a predictive model for malnutrition in hospitalized elderly cancer patients. METHODS: Data from January 2022 to January 2023 on cancer patients aged 60+ were collected, involving 22 variables. Key variables were identified using the LASSO (Least Absolute Shrinkage and Selection Operator) method, and nine machine learning models were tested. SHAP was used to interpret the XGBoost model. Malnutrition prevalence was assessed. RESULTS: Among 450 participants, 46.4 % were malnourished. Key predictors identified were ADL (Activities of Daily Living), ALB (Albumin), BMI (Body Mass Index) and age. XGBoost had the highest AUC of 0.945, accuracy of 0.872, and sensitivity of 0.968. Higher ADL and age increased malnutrition risk, while lower ALB and BMI reduced it. CONCLUSIONS: The XGBoost model is highly effective in detecting malnutrition in elderly cancer patients, enabling early and rapid nutritional assessments.

Cobalt(II)-Substituted Cysteamine Dioxygenase Oxygenation Proceeds through a Cobalt(III)-Superoxo Complex.

We investigated the metal-substituted catalytic activity of human cysteamine dioxygenase (ADO), an enzyme pivotal in regulating thiol metabolism and contributing to oxygen homeostasis. Our findings demonstrate the catalytic competence of cobalt(II)- and nickel(II)-substituted ADO in cysteamine oxygenation. Notably, Co(II)-ADO exhibited superiority over Ni(II)-ADO despite remaining significantly less active than the natural enzyme. Structural analyses through X-ray crystallography and cobalt K-edge excitation confirmed successful metal substitution with minimal structural perturbations. This provided a robust structural basis, supporting a conserved catalytic mechanism tailored to distinct metal centers. This finding challenges the proposed high-valent ferryl-based mechanism for thiol dioxygenases, suggesting a non-high-valent catalytic pathway in the native enzyme. Further investigation of the cysteamine-bound or a peptide mimic of N-terminus RGS5 bound Co(II)-ADO binary complex revealed the metal center's high-spin (S = 3/2) state. Upon reaction with O2, a kinetically and spectroscopically detectable intermediate emerged with a ground spin state of S = 1/2. This intermediate exhibits a characteristic 59Co hyperfine splitting (A = 67 MHz) structure in the EPR spectrum alongside UV-vis features, consistent with known low-spin Co(III)-superoxo complexes. This observation, unique for protein-bound thiolate-ligated cobalt centers in a protein, unveils the capacities for O2 activation in such metal environments. These findings provide valuable insights into the non-heme iron-dependent thiol dioxygenase mechanistic landscape, furthering our understanding of thiol metabolism regulation. The exploration of metal-substituted ADO sheds light on the intricate interplay between metal and catalytic activity in this essential enzyme.

Transplantation of olfactory mucosa mesenchymal stromal cells repairs spinal cord injury by inducing microglial polarization.

STUDY DESIGN: Animal studies OBJECTIVES: To evaluate the therapeutic effect of olfactory mucosa mesenchymal stem cell (OM-MSCs) transplantation in mice with spinal cord injury (SCI) and to explore the mechanism by which OM-MSCs inhibit neuroinflammation and improve SCI. SETTING: Xiangya Hospital, Central South University; Affiliated Hospital of Guangdong Medical University. METHODS: Mice (C57BL/6, female, 6-week-old) were randomly divided into sham, SCI, and SCI + OM-MSC groups. The SCI mouse model was generated using Allen's method. OM-MSCs were immediately delivered to the lateral ventricle after SCI using stereotaxic brain injections. One day prior to injury and on days 1, 5, 7, 14, 21, and 28 post-injury, the Basso Mouse Scale and Rivlin inclined plate tests were performed. Inflammation and microglial polarization were evaluated using histological staining, immunofluorescence, and qRT-PCR. RESULTS: OM-MSCs originating from the neuroectoderm have great potential in the management of SCI owing to their immunomodulatory effects. OM-MSCs administration improved motor function, alleviated inflammation, promoted the transformation of the M1 phenotype of microglia into the M2 phenotype, facilitated axonal regeneration, and relieved spinal cord injury in SCI mice. CONCLUSIONS: OM-MSCs reduced the level of inflammation in the spinal cord tissue, protected neurons, and repaired spinal cord injury by regulating the M1/M2 polarization of microglia.

Synergistic Effects of Boron and Rare Earth Elements on the Microstructure and Stress Rupture Properties in a Ni-Based Superalloy.

The synergistic effects of boron (B) and rare earth (RE) elements on the microstructure and stress rupture properties were investigated in a Ni-based superalloy. The stress rupture lifetime at 650 °C/873 MPa significantly increased with the addition of B as a single element. Furthermore, the stress rupture lifetime reached its peak (303 h), with a certain amount of B and RE added together in test alloys. Although the grain size and morphology of the γ' phase varied a little with the change in B and RE addition, they were not considered to be the main reasons for stress rupture performance. The enhancement in stress rupture lifetime was mostly attributed to the segregation of the B and RE elements, which increased the binding force of the grain boundary and improved its strength and plasticity. In addition, the enrichment of B and RE inhabited the precipitation of carbides along grain boundaries. Furthermore, nano-scale RE precipitates containing sulfur (S) and phosphorus (P) were observed to be distributed along the grain boundaries. The purification of grain boundaries by B and RE elements was favorable to further improve the stress rupture properties.

Beaconet: A Reference-Free Method for Integrating Multiple Batches of Single-Cell Transcriptomic Data in Original Molecular Space.

Integrating multiple single-cell datasets is essential for the comprehensive understanding of cell heterogeneity. Batch effect is the undesired systematic variations among technologies or experimental laboratories that distort biological signals and hinder the integration of single-cell datasets. However, existing methods typically rely on a selected dataset as a reference, leading to inconsistent integration performance using different references, or embed cells into uninterpretable low-dimensional feature space. To overcome these limitations, a reference-free method, Beaconet, for integrating multiple single-cell transcriptomic datasets in original molecular space by aligning the global distribution of each batch using an adversarial correction network is presented. Through extensive comparisons with 13 state-of-the-art methods, it is demonstrated that Beaconet can effectively remove batch effect while preserving biological variations and is superior to existing unsupervised methods using all possible references in overall performance. Furthermore, Beaconet performs integration in the original molecular feature space, enabling the characterization of cell types and downstream differential expression analysis directly using integrated data with gene-expression features. Additionally, when applying to large-scale atlas data integration, Beaconet shows notable advantages in both time- and space-efficiencies. In summary, Beaconet serves as an effective and efficient batch effect removal tool that can facilitate the integration of single-cell datasets in a reference-free and molecular feature-preserved mode.

Synthesis of n-Propanol from CO2 Electroreduction on Bicontinuous Cu2O/Cu Nanodomains.

n-propanol is an important pharmaceutical and pesticide intermediate. To produce n-propanol by electrochemical reduction of CO2 is a promising way, but is largely restricted by the very low selectivity and activity. How to promote the coupling of *C1 and *C2 intermediates to form the *C3 intermediate for n-propanol formation is challenging. Here, we propose the construction of bicontinuous structure of Cu2O/Cu electrocatalyst, which consists of ultra-small Cu2O nanodomains, Cu nanodomains and large amounts of grain boundaries between Cu2O and Cu nanodomains. The n-propanol current density is as high as 101.6 mA cm-2 at the applied potential of -1.1 V vs. reversible hydrogen electrode in flow cell, with the Faradaic efficiency up to 12.1 %. Moreover, the catalyst keeps relatively stable during electrochemical CO2 reduction process. Experimental studies and theoretical calculations reveal that the bicontinuous structure of Cu2O/Cu can facilitate the *CO formation, *CO-*CO coupling and *CO-*OCCO coupling for the final generation of n-propanol.

Sustained remission of Cronkhite-Canada syndrome after corticosteroid and mesalazine treatment: A case report.

BACKGROUND: Cronkhite-Canada syndrome (CCS) is a rare disease of unknown etiology. The optimal treatment for CCS remains unknown. Treatment with corticosteroids is considered the mainstay treatment because of its high efficacy, but the therapeutic strategy for steroid-resistant CCS is not yet established. CASE SUMMARY: This is the case of an 81-year-old woman who was diagnosed with CCS. Given her severe diarrhea, nausea, vomiting, and hypoproteinemia, hormone therapy (40 mg/d) was administered, and the symptoms improved within 1 wk. After 3 mo, the patient had no obvious symptoms. The polyps were significantly reduced on review gastroscopy and colonoscopy, thus hormone reduction gradually began. The hormone level was maintained at 10 mg/d after 6 mo. Despite the age of the patient and the side effects of hormones, the patient had no obvious discomfort. However, hormone drugs were discontinued, and mesalazine was administered orally at 3 g/d. The patient's symptoms continued to improve after a follow-up of 5 years. CONCLUSION: Corticosteroids and mesalazine are potential treatment options for CCS.

Glucose uptake in trophoblasts of GDM mice is regulated by the AMPK-CLUT3 signaling pathway.

GDM, as a metabolic disease during pregnancy, regulates GLUT3 translocation by AMPK, thereby affecting glucose uptake in trophoblasts. It provides a new research idea and therapeutic target for alleviating intrauterine hyperglycemia in GDM. STZ was used to construct GDM mice, inject AICAR into pregnant mice, and observe fetal and placental weight; flow cytometry was employed for the detection of glucose uptake by primary trophoblast cells; immunofluorescence was applied to detect the localization of GLUT3 and AMPK in placental tissue; Cocofal microscope was used to detect the localization of GLUT3 in trophoblast cells;qRT-PCR and Western blot experiments were carried out to detect the expression levels of GLUT3 and AMPK in placental tissue; CO-IP was utilized to detect the interaction of GLUT3 and AMPK. Compared with the normal pregnancy group, the weight of the fetus and placenta of GDM mice increased (P < 0.001), and the ability of trophoblasts to take up glucose decreased (P < 0.001). In addition, AMPK activity in trophoblasts and membrane localization of GLUT3 in GDM mice were down-regulated compared with normal pregnant mice (P < 0.05). There is an interaction between GLUT3 and AMPK. Activating AMPK in trophoblasts can up-regulate the expression of GLUT3 membrane protein in trophoblasts of mice (P < 0.05) and increase the glucose uptake of trophoblasts (P < 0.05). We speculate that inhibition of AMPK activity in GDM mice results in aberrant localization of GLUT3, which in turn attenuates glucose uptake by placental trophoblast cells. AICAR activates AMPK to increase the membrane localization of GLUT3 and improve the glucose uptake capacity of trophoblasts.

A Review of Femtosecond Laser Processing of Silicon Carbide.

Silicon carbide (SiC) is a promising semiconductor material as well as a challenging material to machine, owing to its unique characteristics including high hardness, superior thermal conductivity, and chemical inertness. The ultrafast nature of femtosecond lasers enables precise and controlled material removal and modification, making them ideal for SiC processing. In this review, we aim to provide an overview of the process properties, progress, and applications by discussing the various methodologies involved in femtosecond laser processing of SiC. These methodologies encompass direct processing, composite processing, modification of the processing environment, beam shaping, etc. In addition, we have explored the myriad applications that arise from applying femtosecond laser processing to SiC. Furthermore, we highlight recent advancements, challenges, and future prospects in the field. This review provides as an important direction for exploring the progress of femtosecond laser micro/nano processing, in order to discuss the diversity of processes used for manufacturing SiC devices.

Spontaneous delayed migration or shortening after pipeline embolization device treatment of intracranial aneurysm: incidence, management, and risk factors.

BACKGROUND: Studies reporting spontaneous delayed migration or shortening (SDMS) after treatment with the Pipeline Embolization Device (PED) are limited. This study aimed to evaluate the incidence of SDMS after PED treatment, propose management strategies, and identify the risk factors contributing to its occurrence. METHODS: We retrospectively reviewed consecutive patients with an intracranial aneurysm (IA) treated with PEDs at three institutions. SDMS was classified as type I or II based on whether the PED covered the aneurysm neck. RESULTS: The total cohort comprised 790 patients. SDMS was identified in 24 (3.04%) patients. Eighteen of the 24 patients had type I SDMS and did not require retreatment, while the remaining six patients had type II SDMS and all received retreatment. Multivariate logistic regression showed that the difference between the proximal and distal parent artery diameters (DPAD) (adjusted OR 2.977; 95% CI 1.054 to 8.405; P=0.039) and device tortuosity index (DTI) (adjusted OR 8.059; 95% CI 2.867 to 23.428; P<0.001) were independent predictors of SDMS after PED treatment, while the difference in length (DL) (adjusted OR 0.841; 95% CI 0.738 to 0.958; P=0.009) and PED plus coiling (adjusted OR 0.288; 95% CI 0.106 to 0.785; P=0.015) were protective factors. CONCLUSION: The incidence of SDMS after PED treatment of IA was 3.04%. For patients with type I SDMS with incomplete aneurysm occlusion we recommend continuous imaging follow-up while, for patients with type II SDMS, we recommend aggressive retreatment. The DPAD and DTI were independent risk predictors of SDMS after PED treatment, while the DL and PED plus coiling were protective factors.

The relationship between heavy metals and metabolic syndrome using machine learning.

Background: Exposure to high levels of heavy metals has been widely recognized as an important risk factor for metabolic syndrome (MetS). The main purpose of this study is to assess the associations between the level of heavy metal exposure and Mets using machine learning (ML) method. Methods: The data used in this study are from the national health and nutrition examination survey 2003-2018. According to the demographic information and heavy metal exposure level of participants, a total of 22 variables were included. Lasso was used to screen out the key variables, and 9 commonly used ML models were selected to establish the associations with the 5-fold cross validation method. Finally, we choose the SHapley Additive exPlanations (SHAP) method to explain the prediction results of Adaboost model. Results: 11,667 eligible individuals were randomly divided into two groups to train and verify the prediction model. Through lasso, characteristic variables were selected from 24 variables as predictors. The AUC (area under curve) of the models selected in this study were all greater than 0.7, and AdaBoost was the best model. The AUC value of AdaBoost was 0.807, the accuracy was 0.720, and the sensitivity was 0.792. It is noteworthy that higher levels of cadmium, body mass index, cesium, being female, and increasing age were associated with an increased probability of MetS. Conversely, lower levels of cobalt and molybdenum were linked to a decrease in the estimated probability of MetS. Conclusion: Our study highlights the AdaBoost model proved to be highly effective, precise, and resilient in detecting a correlation between exposure to heavy metals and MetS. Through the use of interpretable methods, we identified cadmium, molybdenum, cobalt, cesium, uranium, and barium as prominent contributors within the predictive model.