Enantioselective formal total synthesis of dihydrospirotryprostatin B.

Spirotryprostatins are representative members of medicinally interesting bioactive molecules of the spirooxindole natural products. In this communication, we present a novel enantioselective total synthesis of the spirooxindole alkaloid dihydrospirotryprostatin B. The synthesis takes advantage of copper-catalyzed tandem reaction of o-iodoanilide chiral sulfinamide derivatives with alkynone to rapidly construct the key quaternary carbon stereocenter of the natural product dihydrospirotryprostatin B.

A red blood cell-derived bionic microrobot capable of hierarchically adapting to five critical stages in systemic drug delivery.

The tumour-targeting efficiency of systemically delivered chemodrugs largely dictates the therapeutic outcome of anticancer treatment. Major challenges lie in the complexity of diverse biological barriers that drug delivery systems must hierarchically overcome to reach their cellular/subcellular targets. Herein, an "all-in-one" red blood cell (RBC)-derived microrobot that can hierarchically adapt to five critical stages during systemic drug delivery, that is, circulation, accumulation, release, extravasation, and penetration, is developed. The microrobots behave like natural RBCs in blood circulation, due to their almost identical surface properties, but can be magnetically manipulated to accumulate at regions of interest such as tumours. Next, the microrobots are "immolated" under laser irradiation to release their therapeutic cargoes and, by generating heat, to enhance drug extravasation through vascular barriers. As a coloaded agent, pirfenidone (PFD) can inhibit the formation of extracellular matrix and increase the penetration depth of chemodrugs in the solid tumour. It is demonstrated that this system effectively suppresses both primary and metastatic tumours in mouse models without evident side effects, and may represent a new class of intelligent biomimicking robots for biomedical applications.

Aromaticity Tuning of Heavy-Atom-Free Photosensitizers for Singlet Fission-Enhanced Immunogenic Photodynamic Oncotherapy.

The quantum yield of reactive oxygen species is of central importance for the development of organic photosensitizers and photodynamic therapy (PDT). A common molecular design approach for optimizing organic photosensitizers involves the incorporation of heavy atoms into their backbones. However, this raises concerns regarding heightened dark cytotoxicity and a shortened triplet-state lifetime. Herein, we demonstrate a heavy-atom-free (HAF) photosensitizer design strategy founded on the singlet fission (SF) mechanism for cancer PDT. Through the "single-atom surgery" approach to deleting oxygen atoms in pyrazino[2,3-g]quinoxaline skeleton photosensitizers, photosensitizers PhPQ and TriPhPQ are produced with Huckel's aromaticity and Baird's aromaticity in the ground state and triplet state, respectively, enabling the generation of two triplet excitons through SF. The SF process endows photosensitizer PhPQ with an ultrahigh triplet-state quantum yield (186%) and an outstanding 1O2 quantum yield (177%). Notably, HAF photosensitizers PhPQ and TriPhPQ enhanced PDT efficacy and potentiated αPD-L1 immune check blockade therapy in vivo, which show their promise for translational oncology treatment.

Iodine/soluble starch cryogel: An iodine-based antiseptic with instant water-solubility, improved stability, and potent bactericidal activity.

Iodine (I2) as a broad-spectrum antiseptic has been widely used for treating bacterial infections. However, I2 has low water-solubility and sublimes under ambient conditions, which limits its practical antibacterial applications. The highly specific and sensitive reaction between I2 and starch discovered 200 years ago has been extensively applied in analytical chemistry, but the antibacterial activity of the I2-starch complex is rarely investigated. Herein, we develop a novel type of iodine-based antiseptics, iodine-soluble starch (I2-SS) cryogel, which can dissolve in water instantly and almost completely kill bacteria in 10 min at 2 µg/mL of I2. Although KI3 and the commercially available povidone­iodine (I2-PVP) solutions show similar antibacterial efficacy, the high affinity of I2 to SS largely enhances the shelf stability of the I2-SS solution with ∼73 % I2 left after one-week storage at room temperature. In sharp contrast, ∼8.5 % and âˆ¼2.5 % I2 are detected in KI3 and I2-PVP solutions, respectively. Mechanistic study reveals that the potent antibacterial effect of I2-SS originates from its attack on multiple bacterial targets. The outstanding antibacterial activity, capability of accelerating wound healing, and good biocompatibility of I2-SS are verified through further in vivo experiments. This work may promote the development of next-generation iodine-based antiseptics for clinical use.

Dental Age Estimation in Northern Chinese Han Children and Adolescents Using Demirjian's Method Combined with Machine Learning Algorithms.

OBJECTIVES: To investigate the application value of combining the Demirjian's method with machine learning algorithms for dental age estimation in northern Chinese Han children and adolescents. METHODS: Oral panoramic images of 10 256 Han individuals aged 5 to 24 years in northern China were collected. The development of eight permanent teeth in the left mandibular was classified into different stages using the Demirjian's method. Various machine learning algorithms, including support vector regression (SVR), gradient boosting regression (GBR), linear regression (LR), random forest regression (RFR), and decision tree regression (DTR) were employed. Age estimation models were constructed based on total, female, and male samples respectively using these algorithms. The fitting performance of different machine learning algorithms in these three groups was evaluated. RESULTS: SVR demonstrated superior estimation efficiency among all machine learning models in both total and female samples, while GBR showed the best performance in male samples. The mean absolute error (MAE) of the optimal age estimation model was 1.246 3, 1.281 8 and 1.153 8 years in the total, female and male samples, respectively. The optimal age estimation model exhibited varying levels of accuracy across different age ranges, which provided relatively accurate age estimations in individuals under 18 years old. CONCLUSIONS: The machine learning model developed in this study exhibits good age estimation efficiency in northern Chinese Han children and adolescents. However, its performance is not ideal when applied to adult population. To improve the accuracy in age estimation, the other variables can be considered.

Quercetin regulates dendritic cell activation by targeting STAT4 in the treatment of experimental autoimmune encephalomyelitis.

Multiple sclerosis (MS) is a class of autoimmune diseases mainly caused by the immune system attacking the myelin sheath of the axons in the nervous system. Although the pathogenesis of MS is complex, studies have shown that dendritic cells (DCs) play a vital role in the pathogenesis of MS. Quercetin (QU) has a unique advantage in clinical application, especially for treating autoimmune diseases. However, the mechanism of QU in the treatment of experimental autoimmune encephalomyelitis (EAE) remains unclear. In this study, we explore the potential role of QU in EAE. Finally, we find that QU has anti-inflammatory activities and neural protective effects in EAE. The experimental results suggest that the cellular basis for QU's function is to inhibit the activation of DCs while modulating the Th17 cell differentiation in the co-culture system. Further, QU may target STAT4 to inhibit its activation in DCs. This work will be of great significance for the future development and utilization of QU.

Age and urban-rural disparities in cutaneous melanoma mortality rates in the United States during the COVID-19 pandemic.

Most recent studies on the coronavirus disease 2019 (COVID-19) pandemic and cutaneous melanoma (CM) focused more on delayed diagnosis or advanced presentation. We aimed to ascertain mortality trends of CM between 2012 and 2022, focusing on the effects of the COVID-19 pandemic. In this serial population-based study, the National Vital Statistics System dataset was queried for mortality data. Excess CM-related mortality rates were estimated by calculating the difference between observed and projected mortality rates during the pandemic. Totally there were 108,853 CM-associated deaths in 2012-2022. CM-associated mortality saw a declining trend from 2012 to 2019 overall. However, it increased sharply in 2020 (ASMR 3.73 per 100,000 persons, 5.95% excess mortality), and remained high in 2021 and 2022, with the ASMRs of 3.82 and 3.81, corresponding to 11.17% and 13.20% excess mortality, respectively. The nonmetro areas had the most pronounced rise in mortality with 12.20% excess death in 2020, 15.33% in 2021 and 20.52% in 2022, corresponding to a 4-6 times excess mortality risk compared to large metro areas during the pandemic. The elderly had the most pronounced rise in mortality, but the mortality in the younger population was reduced.

Multi-organ imaging-derived polygenic indexes for brain and body health.

The UK Biobank (UKB) imaging project is a crucial resource for biomedical research, but is limited to 100,000 participants due to cost and accessibility barriers. Here we used genetic data to predict heritable imaging-derived phenotypes (IDPs) for a larger cohort. We developed and evaluated 4,375 IDP genetic scores (IGS) derived from UKB brain and body images. When applied to UKB participants who were not imaged, IGS revealed links to numerous phenotypes and stratified participants at increased risk for both brain and somatic diseases. For example, IGS identified individuals at higher risk for Alzheimer's disease and multiple sclerosis, offering additional insights beyond traditional polygenic risk scores of these diseases. When applied to independent external cohorts, IGS also stratified those at high disease risk in the All of Us Research Program and the Alzheimer's Disease Neuroimaging Initiative study. Our results demonstrate that, while the UKB imaging cohort is largely healthy and may not be the most enriched for disease risk management, it holds immense potential for stratifying the risk of various brain and body diseases in broader external genetic cohorts.

Dual-mode nanoprobe strategy integrating ultrasound and near-infrared light for targeted and synergistic arterial thrombolysis.

Efficient thrombolysis in time is crucial for prognostic improvement of patients with acute arterial thromboembolic disease, while limitations and complications still exist in conventional thrombolytic treatment methods. Herein, our study sought to investigate a novel dual-mode strategy that integrated ultrasound (US) and near-infrared light (NIR) with establishment of hollow mesoporous silica nanoprobe (HMSN) which contains Arginine-glycine-aspartate (RGD) peptide (thrombus targeting), perfluoropentane (PFP) (thrombolysis with phase-change and stable cavitation) and indocyanine green (ICG) (thrombolysis with photothermal conversion). HMSN is used as the carrier, the surface is coupled with targeted RGD to achieve high targeting and permeability of thrombus, PFP and ICG are loaded to achieve the collaborative diagnosis and treatment of thrombus by US and NIR, so as to provide a new strategy for the integration of diagnosis and treatment of arterial thrombus. From the in vitro and in vivo evaluation, RGD/ICG/PFP@HMSN can aggregate and penetrate at the site of thrombus, and finally establish the dual-mode directional development and thrombolytic treatment under the synergistic effect of US and NIR, providing strong technical support for the accurate diagnosis and treatment of arterial thrombosis.

Hyperbaric oxygen enhances tumor penetration and accumulation of engineered bacteria for synergistic photothermal immunotherapy.

Bacteria-mediated cancer therapeutic strategies have attracted increasing interest due to their intrinsic tumor tropism. However, bacteria-based drugs face several challenges including the large size of bacteria and dense extracellular matrix, limiting their intratumoral delivery efficiency. In this study, we find that hyperbaric oxygen (HBO), a noninvasive therapeutic method, can effectively deplete the dense extracellular matrix and thus enhance the bacterial accumulation within tumors. Inspired by this finding, we modify Escherichia coli Nissle 1917 (EcN) with cypate molecules to yield EcN-cypate for photothermal therapy, which can subsequently induce immunogenic cell death (ICD). Importantly, HBO treatment significantly increases the intratumoral accumulation of EcN-cypate and facilitates the intratumoral infiltration of immune cells to realize desirable tumor eradication through photothermal therapy and ICD-induced immunotherapy. Our work provides a facile and noninvasive strategy to enhance the intratumoral delivery efficiency of natural/engineered bacteria, and may promote the clinical translation of bacteria-mediated synergistic cancer therapy.

Deciphering the environmental chemical basis of muscle quality decline by interpretable machine learning models.

BACKGROUND: Sarcopenia is known as a decline in skeletal muscle quality and function that is associated with age. Sarcopenia is linked to diverse health problems, including endocrine-related diseases. Environmental chemicals (ECs), a broad class of chemicals released from industry, may influence muscle quality decline. OBJECTIVES: In this work, we aimed to simultaneously elucidate the associations between muscle quality decline and diverse EC exposures based on the data from the 2011-2012 and 2013-2014 survey cycles in the National Health and Nutrition Examination Survey (NHANES) project using machine learning models. METHODS: Six machine learning models were trained based on the EC and non-EC exposures from NHANES to distinguish low from normal muscle quality index status. Different machine learning metrics were evaluated for these models. The Shapley additive explanations (SHAP) approach was used to provide explainability for machine learning models. RESULTS: Random forest (RF) performed best on the independent testing data set. Based on the testing data set, ECs can independently predict the binary muscle quality status with good performance by RF (area under the receiver operating characteristic curve = 0.793; area under the precision-recall curve = 0.808). The SHAP ranked the importance of ECs for the RF model. As a result, several metals and chemicals in urine, including 3-phenoxybenzoic acid and cobalt, were more associated with the muscle quality decline. CONCLUSIONS: Altogether, our analyses suggest that ECs can independently predict muscle quality decline with a good performance by RF, and the SHAP-identified ECs can be closely related to muscle quality decline and sarcopenia. Our analyses may provide valuable insights into ECs that may be the important basis of sarcopenia and endocrine-related diseases in United States populations.

Microarray Chip-Based High-Throughput Screening of Neurofilament Light Chain Self-Assembling Peptide for Noninvasive Monitoring of Alzheimer's Disease.

Alzheimer's disease (AD) starts decades before cognitive symptoms develop. Easily accessible and cost-effective biomarkers that accurately reflect AD pathology are essential for both monitoring and therapeutics of AD. Neurofilament light chain (NfL) levels in blood and cerebrospinal fluid are increased in AD more than a decade before the expected onset, thus providing one of the most promising blood biomarkers for monitoring of AD. The clinical practice of employing single-molecule array (Simoa) technology for routine use in patient care is limited by the high costs. Herein, we developed a microarray chip-based high-throughput screening method and screened an attractive self-assembling peptide targeting NfL. Through directly "imprinting" and further analyzing the sequences, morphology, and affinity of the identified self-assembling peptides, the Pep-NfL peptide nanosheet with high binding affinity toward NfL (KD = 1.39 × 10-9 mol/L), high specificity, and low cost was characterized. The superior binding ability of Pep-NfL was confirmed in AD mouse models and cell lines. In the clinical setting, the Pep-NfL peptide nanosheets hold great potential for discriminating between patients with AD (P < 0.001, n = 37), mild cognitive impairment (P < 0.05, n = 26), and control groups (n = 30). This work provides a high-throughput, high-sensitivity, and economical system for noninvasive tracking of AD to monitor neurodegeneration at different stages of disease. The obtained Pep-NfL peptide nanosheet may be useful for assessing dynamic changes in plasma NfL concentrations to evaluate disease-modifying therapies as a surrogate end point of neurodegeneration in clinical trials.

Study on multiscale structures and digestibility of cassava starch and medium-chain fatty acids complexes using molecular simulation techniques.

Effect of complexation of three medium-chain fatty acids (octanoic, decylic and lauric acid, OA, DA and LA, respectively) on structural characteristics, physicochemical properties and digestion behaviors of cassava starch (CS) was investigated. Current study indicated that LA was more easily to combine with CS (complex index 88.9%), followed by DA (80.9%), which was also consistent with their corresponding complexed lipids content. Following the investigation of morphology, short-range ordered structure, helical structure, crystalline/amorphous region and fractal dimension of the various complexes, all cassava starch-fatty acids complexes (CS-FAs) were characterized with a flaked morphology rather than a round morphology in native starch (control CS). X-ray diffraction demonstrated that all CS-FAs had a V-type crystalline structure, and nuclear magnetic resonance spectroscopy confirmed that the complexes made from different fatty acids displayed similar V6 or V7 type polymorphs. Interestingly, small-angle X-ray scattering analysis revealed that α value became greater following increased carbon chain length of fatty acids, indicating the formation of a more ordered fractal structure in the aggregates. Changes in rheological parameters G' and G'' indicated that starch complexed with fatty acids was more likely to form a gel network, but difference among three CS-FAs complexes was significant, which might be contributed to their corresponding hydrophobicity and hydrophilicity raised from individual fatty acids. Importantly, digestion indicated that CS-LA complexes had the lowest hydrolysis degree, followed by the greatest RS content, indicating the importance of chain length of fatty acids for manipulating the fine structure and functionality of the complexes.

Different machine learning methods based on maxillary sinus in sex estimation for northwestern Chinese Han population.

BACKGROUND & OBJECTIVE: Sex estimation is a critical aspect of forensic expertise. Some special anatomical structures, such as the maxillary sinus, can still maintain integrity in harsh environmental conditions and may be served as a basis for sex estimation. Due to the complex nature of sex estimation, several studies have been conducted using different machine learning algorithms to improve the accuracy of sex prediction from anatomical measurements. MATERIAL & METHODS: In this study, linear data of the maxillary sinus in the population of northwest China by using Cone-Beam Computed Tomography (CBCT) were collected and utilized to develop logistic, K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and random forest (RF) models for sex estimation with R 4.3.1. CBCT images from 477 samples of Han population (75 males and 81 females, aged 5-17 years; 162 males and 159 females, aged 18-72) were used to establish and verify the model. Length (MSL), width (MSW), height (MSH) of both the left and right maxillary sinuses and distance of lateral wall between two maxillary sinuses (distance) were measured. 80% of the data were randomly picked as the training set and others were testing set. Besides, these samples were grouped by age bracket and fitted models as an attempt. RESULTS: Overall, the accuracy of the sex estimation for individuals over 18 years old on the testing set was 77.78%, with a slightly higher accuracy rate for males at 78.12% compared to females at 77.42%. However, accuracy of sex estimation for individuals under 18 was challenging. In comparison to logistic, KNN and SVM, RF exhibited higher accuracy rates. Moreover, incorporating age as a variable improved the accuracy of sex estimation, particularly in the 18-27 age group, where the accuracy rate increased to 88.46%. Meanwhile, all variables showed a linear correlation with age. CONCLUSION: The linear measurements of the maxillary sinus could be a valuable tool for sex estimation in individuals aged 18 and over. A robust RF model has been developed for sex estimation within the Han population residing in the northwestern region of China. The accuracy of sex estimation could be higher when age is used as a predictive variable.

ZmASR1 negatively regulates drought stress tolerance in maize.

Abscisic acid-, stress-, and ripening-induced (ASR) proteins in plants play a significant role in plant response to diverse abiotic stresses. However, the functions of ASR genes in maize remain unclear. In the present study, we identified a novel drought-induced ASR gene in maize (ZmASR1) and functionally characterized its role in mediating drought tolerance. The transcription of ZmASR1 was upregulated under drought stress and abscisic acid (ABA) treatment, and the ZmASR1 protein was observed to exhibit nuclear and cytoplasmic localization. Moreover, ZmASR1 knockout lines generated with the CRISPR-Cas9 system showed lower ROS accumulation, higher ABA content, and a higher degree of stomatal closure than wild-type plants, leading to higher drought tolerance. Transcriptome sequencing data indicated that the significantly differentially expressed genes in the drought treatment group were mainly enriched in ABA signal transduction, antioxidant defense, and photosynthetic pathway. Taken together, the findings suggest that ZmASR1 negatively regulates drought tolerance and represents a candidate gene for genetic manipulation of drought resistance in maize.

Hypervirulent Klebsiella pneumoniae Mediated Hepatic Infarction Septic Shock After Rectal Cancer Surgery: A Case Report.

The liver receives blood from both the hepatic artery and portal vein. Hepatic infarction is rare in clinical practice as both the hepatic artery and portal vein can supply blood to the liver. Here, we reported a case of a 75-year-old man who underwent radical laparoscopic surgery for rectal cancer and subsequently developed hepatic infarction. The patient experienced severe infection, as well as circulatory and respiratory failure on the third day after surgery. The patient presented with high fever, chest tightness, shortness of breath, decreased blood oxygen saturation and blood pressure. The leukocyte count decreased from 8.10 × 10^9/L to 1.75 × 10^9/L. Procalcitonin (PCT) levels increased from 1.02 ng/mL to 67.14 ng/mL, and eventually reaching levels over 200 ng/mL. Enhanced abdominal computed tomography (CT) confirmed the presence of hepatic infarction, but no thrombosis was observed in the hepatic artery or portal vein. Metagenomic next-generation sequencing (mNGS) identified hypervirulent Klebsiella pneumoniae (hvKp) in the patient's blood and ascites, one day earlier than the detection results using traditional culture methods. The patient was diagnosed with hepatic infarction combined with septic shock caused by hvKp. This case emphasizes that in the high-risk group of thrombosis, infection can trigger exacerbated hepatic infarction events, particularly in cases after surgical procedures. For severely ill patients with infectious diseases who are admitted to the ICU with worsening symptoms, it is important to collect appropriate samples and send them for pathogen detection using mNGS in a timely manner. This may aid in early intervention and improve clinical outcomes.

Positive profile of natural small molecule organic matters on emerging antivirus pharmaceutical elimination in advance reduction process: A deep dive into the photosensitive mechanism of triplet excited state compounds.

Natural small molecular organic matter (NSOM), ubiquitous in natural waters and distinct from humic acid or fulvic acid, is a special type of dissolved organic matter (DOM) which is characterized as strong photosensitivity and simple molecular structure. However, little study had been directed on the role of NSOM in eliminating emerging contaminants in advanced reduction process (ARP). This study took three small molecular isomeric organic acids (p-hydroxybenzoic acid, pHBA; salicylic acid, SA; m-hydroxybenzoic acid, mHBA) as the representative substances of NSOM to explore these mechanisms on promoting Ribavirin (RBV, an anti COVID-19 medicine) degradation in ultraviolet activated sulfite (UV/Sulfite) process. The results demonstrated that the observed degradation rate constant of RBV (kobs-RBV) was 7.56 × 10-6 s-1 in UV/Sulfite process, indicating that hydrated electron (eaq-) from UV/Sulfite process could not effectively degrade RBV, while it increased by 178 and 38 times when pHBA and SA were introduced into UV/Sulfite process respectively, suggesting that pHBA and SA strongly promoted RBV degradation while mHBA had no promotion on RBV abatement in UV/Sulfite process. Transient absorption spectra and reactive intermediates scavenging experiment indicated that the triplet excited state pHBA and SA (3pHBA* and 3SA*) contributed to the degradation of RBV through non-radical process. Notably, eaq- played the role of key initiator in transforming pHBA and SA into their triplet states. The difference of kobs-RBV in UV/Sulfite/pHBA and UV/Sulfite/SA process was attributed to different generation pathways of 3pHBA* and 3SA* (high molar absorptivity at the wavelength of 254 nm and photosensitive cycle, respectively) and their second order rate constants towards RBV (kRBV-3pHBA* = 8.60 × 108 M-1 s-1 and kRBV-3SA* = 6.81 × 107 M-1 s-1). mHBA could not degrade RBV for its lack of intramolecular hydrogen bond and low molar absorptivity at 254 nm to abundantly transform into its triplet state. kobs-RBV increased as pH increased from 5.0 to 11.0 in UV/Sulfite/SA process, due to the high yield of eaq- in alkaline condition which promoted the generation of 3SA* and the stable of the absorbance of SA at 254 nm. By contrast, kobs-RBV underwent a process of first increasing and then decreasing in UV/Sulfite/pHBA process as the increase of pH, and its highest value achieved in a neutral condition. This lied in the exposure of eaq- increased as the increase of pH which promoted the generation of 3pHBA*, while the molar absorptivity of pHBA at 254 nm decreased as the increase of pH in an alkaline condition which inhibited the yield of 3pHBA*. The RBV degradation pathways and products toxicity assessment indicated that UV/Sulfite/pHBA had better detoxification performance on RBV than UV/Sulfite/SA process. This study disclosed a novel mechanism of emerging contaminants abatement through non-radical process in NSOM mediated ARP, and provide a wide insight into positive profile of DOM in water treatment process, instead of only taking DOM as a quencher of reactive intermediates.

BAG6 inhibits influenza A virus replication by inducing viral polymerase subunit PB2 degradation and perturbing RdRp complex assembly.

The interaction between influenza A virus (IAV) and host proteins is an important process that greatly influences viral replication and pathogenicity. PB2 protein is a subunit of viral ribonucleoprotein (vRNP) complex playing distinct roles in viral transcription and replication. BAG6 (BCL2-associated athanogene 6) as a multifunctional host protein participates in physiological and pathological processes. Here, we identify BAG6 as a new restriction factor for IAV replication through targeting PB2. For both avian and human influenza viruses, overexpression of BAG6 reduced viral protein expression and virus titers, whereas deletion of BAG6 significantly enhanced virus replication. Moreover, BAG6-knockdown mice developed more severe clinical symptoms and higher viral loads upon IAV infection. Mechanistically, BAG6 restricted IAV transcription and replication by inhibiting the activity of viral RNA-dependent RNA polymerase (RdRp). The co-immunoprecipitation assays showed BAG6 specifically interacted with the N-terminus of PB2 and competed with PB1 for RdRp complex assembly. The ubiquitination assay indicated that BAG6 promoted PB2 ubiquitination at K189 residue and targeted PB2 for K48-linked ubiquitination degradation. The antiviral effect of BAG6 necessitated its N-terminal region containing a ubiquitin-like (UBL) domain (17-92aa) and a PB2-binding domain (124-186aa), which are synergistically responsible for viral polymerase subunit PB2 degradation and perturbing RdRp complex assembly. These findings unravel a novel antiviral mechanism via the interaction of viral PB2 and host protein BAG6 during avian or human influenza virus infection and highlight a potential application of BAG6 for antiviral drug development.

Neurological manifestations and risk factors associated with poor prognosis in hospitalized children with Omicron variant infection.

There are increasing reports of neurological manifestation in children with coronavirus disease 2019 (COVID-19). However, the frequency and clinical outcomes of in hospitalized children infected with the Omicron variant are unknown. The aim of this study was to describe the clinical characteristics, neurological manifestations, and risk factor associated with poor prognosis of hospitalized children suffering from COVID-19 due to the Omicron variant. Participants included children older than 28 days and younger than 18 years. Patients were recruited from December 10, 2022 through January 5, 2023. They were followed up for 30 days. A total of 509 pediatric patients hospitalized with the Omicron variant infection were recruited into the study. Among them, 167 (32.81%) patients had neurological manifestations. The most common manifestations were febrile convulsions (n = 90, 53.89%), viral encephalitis (n = 34, 20.36%), epilepsy (n = 23, 13.77%), hypoxic-ischemic encephalopathy (n = 9, 5.39%), and acute necrotizing encephalopathy (n = 6, 3.59%). At discharge, 92.81% of patients had a good prognosis according to the Glasgow Outcome Scale (scores ≥ 4). However, 7.19% had a poor prognosis. Eight patients died during the follow-up period with a cumulative 30-day mortality rate of 4.8% (95% confidence interval (CI) 1.5-8.1). Multivariate analysis revealed that albumin (odds ratio 0.711, 95% CI 0.556-0.910) and creatine kinase MB (CK-MB) levels (odds ratio 1.033, 95% CI 1.004-1.063) were independent risk factors of poor prognosis due to neurological manifestations. The area under the curve for the prediction of poor prognosis with albumin and CK-MB was 0.915 (95%CI 0.799-1.000), indicating that these factors can accurately predict a poor prognosis.          Conclusion: In this study, 32.8% of hospitalized children suffering from COVID-19 due to the Omicron variant infection experienced neurological manifestations. Baseline albumin and CK-MB levels could accurately predict poor prognosis in this patient population. What is Known: • Neurological injury has been reported in SARS-CoV-2 infection; compared with other strains, the Omicron strain is more likely to cause neurological manifestations in adults. • Neurologic injury in adults such as cerebral hemorrhage and epilepsy has been reported in patients with Omicron variant infection. What is New: • One-third hospitalized children with Omicron infection experience neurological manifestations, including central nervous system manifestations and peripheral nervous system manifestations. • Albumin and CK-MB combined can accurately predict poor prognosis (AUC 0.915), and the 30-day mortality rate of children with Omicron variant infection and neurological manifestations was 4.8%.

Advances in traditional Chinese herbal medicine and their pharmacodynamic mechanisms in cancer immunoregulation: a narrative review.

Background and Objective: The cancer-immunity cycle (CIC) is defined as a series of progressive events that cause an anticancer immune response leading to the killing of the cancer cell. The concept of CIC has important guiding significance for the clinical and basic tumor immunotherapy research. As one of the methods of traditional Chinese medicine (TCM), Chinese herbal medicine (CHM) has shown unique advantages in multitarget and multipathway immune regulation. However, the tumor immune circulation targeted by CHM is generally unclear at present. To provide reference for future clinical and basic research, we systematically reviewed the existing literature on CHM (including CHM monomers, CHM compounds, and CHM patent medicines) and the mechanisms related to its efficacy. Methods: We searched the PubMed and China National Knowledge Infrastructure (CNKI) databases for relevant Chinese-language and English-language literature published from January 1988 to October 2022. The literature was screened manually at three levels: title, abstract, and full text, to identify articles related to CHM and their mechanism of regulating tumor immunity. Key Content and Findings: By further classifying the CIC, it was confirmed that CHM can regulate the activation of dendritic cells (DCs) and macrophages and promote the presentation of tumor antigens. Meanwhile, CHM can also reverse tumor-immune escape by enhancing T-cell proliferation and infiltration. In addition, CHM can also enhance the antitumor ability of the body by regulating the killing process of tumor cells. Conclusions: The theory of a CIC is of guiding significance to regulating tumor immunity via CHM.