Synthesis of Asp-based lactam cyclic peptides using an amide-bonded diaminodiacid to prevent aspartimide formation.

Asp-based lactam cyclic peptides are considered promising drug candidates. However, using Fmoc solid-phase peptide synthesis (Fmoc-SPPS) for these peptides also causes aspartimide formation, resulting in low yields or even failure to obtain the target peptides. Here, we developed a diaminodiacid containing an amide bond as a ß-carboxyl-protecting group for Asp to avoid aspartimide formation. The practicality of this diaminodiacid has been illustrated by the synthesis of lactam cyclic peptide cyclo[Lys9,Asp13] KIIIA7-14 and 1Y.

Elucidating the enhanced role of carbonate radical in propranolol degradation by UV/peroxymonosulfate system.

Carbonate radical (CO3•-) has been proved to be an important secondary radical in advanced oxidation processes due to various radical reactions involved HCO3-/CO32-. However, the roles and contributions of CO3•- in organic micropollutant degradation have not been explored systematically. Here, we quantified the impact of CO3•- on the degradation kinetics of propranolol, a representative pollutant in the UV/peroxymonosulfate (PMS) system, by constructing a steady-state radical model. Substantially, the measured values were coincident with the predictive values, and the contributions of CO3•- on propranolol degradation were the water matrix-dependent. Propranolol degradation increased by 130% in UV/PMS system containing 10 mM HCO3-, and the contribution of CO3•- was as high as 58%. Relatively high pH values are beneficial for propranolol degradation in pure water containing HCO3-, and the contributions of CO3•- also enhanced, while an inverse phenomenon was shown for the effects of propranolol concentrations. Dissolved organic matter exhibited significant scavenging effects on HO•, SO4•-, and CO3•-, substantially retarding the elimination process. The developed model successfully predicted oxidation degradation kinetics of propranolol in actual sewage, and CO3•- contribution was up to 93%, which in indicative of the important role of CO3•- in organic micropollutant removal via AOPs treatment.

Building adjustment capacity to cope with running water in cultured grass carp through flow stimulation conditions.

The adaptability of cultured fish to complex flow conditions is crucial for their survival after being released into the wild. Running water in natural environments poses significant challenges for the proliferation and release of cultured fish. This study aimed to investigate the effects of flow stimulation on the adjustment capacity of cultured fish to cope with running water. The target fish were cultured grass carp. An annular flume was used to conduct tests on training and control groups. The results demonstrated an enhancement in the adjustment capacity of cultured fish following appropriate flow stimulation training. (1) The trained fish exhibited a heightened preference for low-velocity areas. (2) The trained fish displayed the ability to select a route characterized by low energy consumption, predominantly following the periphery of the low-velocity area. This suggested that an appropriate flow velocity could improve the sensitivity of training fish to water flow information, and their adjustment capacity to cope with running water improved to a certain extent. A higher adjustment capacity allowed them to process flow rate information rapidly and identify a migration strategy with lower energy consumption. This study provides a useful reference for enhancing the survival rate of grass carp through stock enhancement initiatives and contributes to the sustainability of freshwater ecosystems.

[Optimization of prediction model for personalized water pills based on semantic analysis of traditional Chinese medicine materials].

This study aims to optimize the prediction model of personalized water pills that has been established by our research group. Dioscoreae Rhizoma, Leonuri Herba, Codonopsis Radix, Armeniacae Semen Amarum, and calcined Oyster were selected as model medicines of powdery, fibrous, sugary, oily, and brittle materials, respectively. The model prescriptions were obtained by uniform mixing design. With hydroxypropyl methylcellulose E5(HPMC-E5) aqueous solution as the adhesive, personalized water pills were prepared by extrusion and spheronizaition. The evaluation indexes in the pill preparation process and the multi-model statistical analysis were employed to optimize and evaluate the prediction model of personalized water pills. The prediction equation of the adhesive concentration was obtained as follows: Y_1=-4.172+3.63X_A+15.057X_B+1.838X_C-0.997X_D(adhesive concentration of 10% when Y_1<0, and 20% when Y_1>0). The overall accuracy of the prediction model for adhesive concentration was 96.0%. The prediction equation of adhesive dosage was Y_2=6.051+94.944X_A~(1.5)+161.977X_B+70.078X_C~2+12.016X_D~(0.3)+27.493X_E~(0.3)-2.168X_F~(-1)(R~2=0.954, P<0.001). Furthermore, the semantic prediction model for material classification of traditional Chinese medicines was used to classify the materials contained in the prescription, and thus the prediction model of personalized water pills was evaluated. The results showed that the prescriptions for model evaluation can be prepared with one-time molding, and the forming quality was better than that established by the research group earlier. This study has achieved the optimization of the prediction model of personalized water pills.

[Composite excipients for preparing concentrated water pills of personalized traditional Chinese medicine prescriptions by extruding-rounding method].

This study aims to optimize the composite excipients suitable for the preparation of concentrated water pills of personalized traditional Chinese medicine prescriptions by the extruding-rounding method and investigate the roles of each excipient in the preparation process. The fiber materials and powder materials were taken as the standard materials suitable as excipients in the preparation of personalized concentrated water pills without excipient. Water absorption properties and torque rheology were used as indicators for selecting the materials of composite excipients. The ratio of composite excipients was optimized by D-optimal mixture design. Moreover, to demonstrate the universal applicability of the optimal composite excipients, this study selected three traditional Chinese medicine prescriptions with low, medium, and high extraction rates to verify the optimal ratio. Finally, the effects of each selected excipient on the molding of personalized concentrated water pills were investigated with the four parameters of the pill molding quality as indicators. The optimized composite excipients were dextrin∶microcrystalline cellulose(MCC)∶low-substituted hydroxypropyl cellulose(L-HPC) at a ratio of 1∶2∶4. The composite excipients were used for the preparation of personalized concentrated water pills with stable process, good quality, and a wide range of application. Dextrin acted as a diluent and accelerated the speed of extruding. MCC mainly served as an adhesive, increasing the cohesion and viscosity of the pills. L-HPC as a water absorbent and disintegrating agent can absorb and hold the water of the concentrate and has a strong disintegration effect.

[Research practice and development direction of intelligent manufacturing of presonalized traditional Chinese medicine preparations].

In recent years, as people's living standards continue to improve, and the pace of life accelerates dramatically, the demand and quality of traditional Chinese medicine(TCM) services from patients continue to rise. As an essential supplement to the existing forms of TCM application, such as Chinese patent medicine, decoction, and formulated granules, presonalized TCM preparations is facing an increasing market demand. Currently, manual and semi-mechanized production are the primary production ways in presonalized TCM preparations. However, the production process control level is low, and digitalization and informatization need to be improved, which restricts the automated and intelligent development of presonalized TCM preparations. Presonalized TCM preparations faces a significant opportunity and challenge in integrating with intelligent manufacturing through research and development of intelligent equipment and core technology. This paper overviews the connotation and characteristics of intelligent manufacturing and summarizes the application of intelligent manufacturing technologies such as "Internet of things" "big data", and "artificial intelligence" in the TCM industry. Based on the innovative research and development model of "intelligent classification of TCM materials, intelligent decision making of prescription and process, and online control and intelligent production" of presonalized TCM preparations, the research practice and achievements from our research group in the field of intelligent manufacturing of presonalized TCM preparations are introduced. Ultimately, the paper proposes the direction for developing intelligent manufacturing of presonalized TCM preparations, which will provide a reference for the research and application of automation and intelligence of presonalized TCM preparations.

[Molding law of traditional Chinese medicine gel plaster based on physicochemical properties of raw materials and intermediates].

This paper aims to study the correlation between the physicochemical properties of raw materials and intermediates and the molding quality and law of traditional Chinese medicine(TCM) gel plaster by using TCM slices and powder as raw materials. 48 TCM compounds are selected as model prescriptions to prepare gel plasters. The rotational rheometer is used to determine the rheological parameters of the plaster, including storage modulus(G'), loss modulus(G″), yield stress(τ), and creep compliance [J(t)]. The molding quality of the prepared TCM gel plaster is evaluated by subjective and objective measures. Clustering and principal component analysis are conducted to evaluate the physical properties of the plaster. By measuring the rheological properties of the plaster, the molding quality of the TCM gel plaster can be predicted, with an accuracy of 83.72% after seven days of modeling and 88.37% after 30 days of modeling. When the parameters such as G' and G″ of the plaster are large, and the [J(t)] is small, the molding quality of the plaster is better. When the plaster coating point is no less than 3, it is difficult to be coated. In addition, when the proportion of metal ions in the prescription is higher, the 30-day forming quality of the plaster is mainly affected, and the viscosity of the plaster is poor. If the prescription contains many acidic chemical components, the 7-day forming quality of the plaster is mainly affected, with many residuals. The results suggest that the rheological properties of the plaster can be used to predict the molding quality of TCM slice and powder gel plaster. It can provide a reference for the development of TCM gel plaster prescriptions.

[Intelligent material classification of traditional Chinese medicine based on semantic analysis].

A method for material classification of traditional Chinese medicines based on the physical properties of powder has been established by our research group. This method involves pre-treatment of traditional Chinese medicine decoction pieces, powder preparation, and determination of physical properties, being cumbersome. In this study, the word segmentation logic of semantic analysis was adopted to establish the thesaurus and local standardized semantic word segmentation database with the macroscopic and microscopic characteristics of 36 model traditional Chinese medicines as the basic data. The physical properties of these medicines have been determined and the classification of these medicines is clear in the cluster analysis. A total of 55 keywords for powdery, fibrous, sugary, oily, and brittle materials were screened by association rules and the set inclusion and exclusion criteria, and the weights of the keywords were calculated. Furthermore, the algorithms of the keyword matching scores and the computation rules of the single or multiple material classification were established for building the intelligent model of semantic analysis for the material classification. The semantic classification results of the other 35 TCMs except Pseudostellariae Radix(multi-material medicine) agreed with the clustering results based on the physical properties of the powder, with an agreement rate of 97.22%. In model validation, the prediction results of semantic classification of traditional Chinese medicines were consistent with the clustering results based on the physical properties of powder, with an agreement rate of 83.33%. The results showed that the method of material classification based on semantic analysis was feasible, which laid a foundation for the development of intelligent decision-making technology for personalized traditional Chinese medicine preparations.

[Molding matrix formulation of hot-melt pressure-sensitive adhesive plaster of personalized traditional Chinese medicine preparations].

This study aims to optimize the matrix formulation for the hot-melt pressure-sensitive adhesive plaster of personalized traditional Chinese medicine(TCM) preparations and verify the applicability of the formulation. The central composite design in JMP Pro 16.1.0 was employed to optimize the dosages of styrene-isoprene-styrene triblock copolymer(SIS), hydrogenated petroleum resin, and lightweight liquid paraffin, with the fine powder of Yipifang as the model drug(drug loading of 10%) and the sensory score and objective evaluation as the comprehensive evaluation indicators. The quality evaluation system of hot-melt pressure-sensitive adhesive plaster of personalized TCM preparations was established. The applicability of the optimized matrix formulation of hot-melt pressure-sensitive adhesive plaster was verified with 16 TCM preparations for external application. Furthermore, the applicability of the matrix formulation was investigated with different drug loadings. The general molding matrix formulation was SIS∶hydrogenated petroleum resin∶lightweight liquid paraffin 3∶3∶5. The optimized matrix formulation showed good molding properties and high quality scores for 16 TCM preparations and were suitable for the plastering of finely powdered decoction pieces with a loading capacity of 10% to 30%. The results suggest that the optimized matrix formulation has good applicability and is suitable for TCM preparations. The findings lay a foundation for the application and promotion of the hot-melt pressure-sensitive adhesive plasters of personalized TCM preparations.

[Preparation process selection of presonalized traditional Chinese medicine concentrated watered pills containing heat-unstable components].

In the process of preparing presonalized concentrated watered pills, the decoction needs to be concentrated by heat and mixed with medicinal slices or powder to prepare a wet mass. However, some of the traditional Chinese medicine(TCM) components are easily decomposed or transformed by heat. In order to optimize the preparation process of presonalized TCM concentrated watered pills and reduce the loss of heat-unstable components in prescriptions, this study uses five compound TCM prescriptions containing heat-unstable components as model prescriptions, namely the Linggui Zhugan Formula, Xiaochengqi Formula, Sanpian Formula, Xiaoer Qixing Formula, and Xiaoyao Formula. Based on the two kinds of preparation process of presonalized concentrated watered pills previously established by our research group, whole extract concentrated watered pills and concentrated watered pills without excipients are prepared, respectively. Characteristic maps are measured and compared with those of the corresponding decoction. The results show that the characteristic maps of the concentrated watered pills without excipients of the five model prescriptions are very close to those of the decoction, and the number of characteristic peaks and peak areas are higher than those of whole extract concentrated watered pills. In addition, the peak area of some peaks is higher than that of the corresponding decoction. Thus, it is recommended to select the preparation process of prescription-based concentrated watered pills without excipients based on the "unification of medicines and excipients" to preserve those heat-unstable components more effectively when the prescription contains a heat-unstable component of TCM. This study provides a basis for the subsequent reasonable development and application of presonalized TCM pills.

The change of intimate relationship between people with Alzheimer's disease and their adult child caregivers: An interpretative phenomenological analysis.

This study aims to explore the change of intimate relationship between people with Alzheimer's disease and their adult child caregivers as the disease progresses. Twelve adult child caregivers were recruited through purposive sampling. Explanatory phenomenological analysis was conducted to analyse data collected by semi-structured in-depth interviews. This study found a dynamically changing relationship between adult child caregivers and their parents with Alzheimer's disease during care giving that evolved with the progress of the disease. The relationship was the most intimate in the middle stage of the disease for most caregivers and a new reciprocal relationship developed due to caregiving. Caregivers experienced different degrees of self-growth when providing care, though caregiver burdens were common. The positive experience and perception of caregivers were important for improving the quality of life for adult child caregivers of people with Alzheimer's disease.

Vitamin D inhibits ferroptosis and mitigates the kidney injury of prediabetic mice by activating the Klotho/p53 signaling pathway.

Diabetic nephropathy (DN) is a serious public health problem worldwide, and ferroptosis is deeply involved in the pathogenesis of DN. Prediabetes is a critical period in the prevention and control of diabetes and its complications, in which kidney injury occurs. This study aimed to explore whether ferroptosis would induce kidney injury in prediabetic mice, and whether vitamin D (VD) supplementation is capable of preventing kidney injury by inhibiting ferroptosis, while discussing the potential mechanisms. High-fat diet (HFD) fed KKAy mice and high glucose (HG) treated HK-2 cells were used as experimental subjects in the current study. Our results revealed that serious injury and ferroptosis take place in the kidney tissue of prediabetic mice; furthermore, VD intervention significantly improved the kidney structure and function in prediabetic mice and inhibited ferroptosis, showing ameliorated iron deposition, enhanced antioxidant capability, reduced reactive oxygen species (ROS) and lipid peroxidation accumulation. Meanwhile, VD up-regulated Klotho, solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4) expression, and down-regulated p53, transferrin receptor 1 (TFR1) and Acyl-Coenzyme A synthetase long-chain family member 4 (ACSL4) expression. Moreover, we demonstrated that HG-induced ferroptosis is antagonized by treatment of VD and knockdown of Klotho attenuates the protective effect of VD on ferroptosis in vitro. In conclusion, ferroptosis occurs in the kidney of prediabetic mice and VD owns a protective effect on prediabetic kidney injury, possibly by via the Klotho/p53 pathway, thus inhibiting hyperglycemia-induced ferroptosis.

Focus on pemphigus treatment publications: A bibliometric and visual analysis (1992-2022).

Pemphigus is a chronic recurrent disease in dermatology. Although it is not very common, its treatment has been an increasing concern in recent years because it is difficult and long-lasting. At present, there are many papers on pemphigus treatment, and to better understand the research trends and research frontiers of pemphigus treatment, it is necessary to conduct a comprehensive systematic review and analysis. We combined bibliometric and visualization methods to analyze 1365 papers published in the Web of Science database from 1992 to 2022, including basic information about countries, institutions and authors, to gain a general understanding of the treatment of pemphigus. Among them, the United States is the country with the most output, Iran's Tehran University of Medical Sciences is the institution with the most published works, and Ahmed, A. Razzaque of Tufts University is the most influential scholar. In addition, we also learned about the research hotspots and frontiers of pemphigus treatment through a series of analyses on the frequency, clustering, keywords bursts and cited literature, and we briefly reviewed the highly cited literature. We found that the current research focuses in the study of pemphigus treatment are the types, pathogenesis, and treatment of pemphigus, including glucocorticoids, immunosuppressants and many other major treatment methods. Hailey-Hailey disease, genetic susceptibility, and traditional Chinese medicine are potential research hotspots. Rituximab is a research frontier. In conclusion, we hope to provide new research ideas for promoting the development of pemphigus treatment.

Enhancing Narrative Commonsense Reasoning With Multilevel Causal Knowledge.

Narratives is an account of the unfolding of events, along with explanations of how and why these processes and events came to be. To understand narratives, causality has been proven to be especially useful. Causality manifests itself primarily at both the event and sentence levels, offering essential insights into understanding narratives. However, previous works utilize either sentence-level or event-level causalities. In this article, we devise a two-stage approach to fully exploit both levels of causal relationships. In the first stage, by devising posttraining tasks, we inject sentence-level causalities into pretrained language models (PLMs). The causal-enhanced PLMs, which carry sentence-level causalities, can be transferred to downstream tasks. In the second stage, we utilize event causalities to further refine narrative commonsense reasoning. But, the event sparsity problem brings about the difficulty to learn event representations and capture useful causal semantics. To alleviate this problem, we break down events into multiple word components, enabling the retrieval of word-word relations between these components. And it is possible to alleviate the event sparsity problem since word-word relations capture the interplays between event components. Based on the event-level causalities and the word-level relations, we construct the hierarchical knowledge graph (KG) as knowledge ground. A KG-based reasoning process is then employed for narrative commonsense reasoning. Experimental results affirm the effectiveness of our framework.

Self-supervised contrastive learning for EEG-based cross-subject motor imagery recognition.

Objective. The extensive application of electroencephalography (EEG) in brain-computer interfaces (BCIs) can be attributed to its non-invasive nature and capability to offer high-resolution data. The acquisition of EEG signals is a straightforward process, but the datasets associated with these signals frequently exhibit data scarcity and require substantial resources for proper labeling. Furthermore, there is a significant limitation in the generalization performance of EEG models due to the substantial inter-individual variability observed in EEG signals.Approach. To address these issues, we propose a novel self-supervised contrastive learning framework for decoding motor imagery (MI) signals in cross-subject scenarios. Specifically, we design an encoder combining convolutional neural network and attention mechanism. In the contrastive learning training stage, the network undergoes training with the pretext task of data augmentation to minimize the distance between pairs of homologous transformations while simultaneously maximizing the distance between pairs of heterologous transformations. It enhances the amount of data utilized for training and improves the network's ability to extract deep features from original signals without relying on the true labels of the data.Main results. To evaluate our framework's efficacy, we conduct extensive experiments on three public MI datasets: BCI IV IIa, BCI IV IIb, and HGD datasets. The proposed method achieves cross-subject classification accuracies of 67.32%, 82.34%, and 81.13%on the three datasets, demonstrating superior performance compared to existing methods.Significance. Therefore, this method has great promise for improving the performance of cross-subject transfer learning in MI-based BCI systems.

The correlation of obesity status with serum 25-hydroxyvitamin D in US Asian adults: NHANES 2011-2018.

BACKGROUND: There is a correlation between obesity and 25-hydroxyvitamin D (25OHD) that tends to be negative. However, this relationship varies among different races. In this study, Asian adults with and without obesity were compared in terms of their levels of 25OHD. METHODS: We carried out a cross-sectional analysis on 2664 non-Hispanic Asian adults who participated in the National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2018. To examine the connection between obese status, body mass index (BMI), waist circumference (WC) and weight, and 25OHD, we ran multivariate linear regression models and multivariate logistic regression models. RESULTS: After adjusting for all confounding factors, obesity status shows a significant positive correlation with vitamin D deficiency (model 3: OR = 2.318, 95% CI:1.317, 4.082). This positive correlation remains significant in males (males: OR = 2.713, 95% CI: -13.398, 5.217). In all three models, a negative association was observed between obesity status and 25OHD (model 1: ß = -4.535, 95% CI: -6.987, -2.083; model 2 ß = -4.249, 95% CI: -6.549, -2.039; model 3 ß = -1.734, 95% CI: -7.285, 3.816). After controlling for covariates, there was a significant negative correlation between WC and 25OHD when stratified by gender and obesity status in both males with and without obesity (males with obesity: ß = -1.461, 95% CI: -2.485, -0.436; males without obesity: ß = -0.855. 95% CI: -1.499, -0.210). In males with obesity, there was a very strong positive connection between body weight and 25OHD (ß = 0.912, 95% CI: 0.227, 1.597). In addition, neither gender's obese individuals showed a significant link between BMI and 25OHD. CONCLUSION: This study demonstrated a positive correlation between obesity and vitamin D deficiency and a negative correlation between obesity and 25OHD in Asian American adults. Additionally, among male obese individuals, there was a significant negative correlation between WC and 25OHD, an observation that needs to be validated in further prospective studies.

Identification of autism spectrum disorder using multiple functional connectivity-based graph convolutional network.

Presently, the combination of graph convolutional networks (GCN) with resting-state functional magnetic resonance imaging (rs-fMRI) data is a promising approach for early diagnosis of autism spectrum disorder (ASD). However, the prevalent approach involves exclusively full-brain functional connectivity data for disease classification using GCN, while overlooking the prior information related to the functional connectivity of brain subnetworks associated with ASD. Therefore, in this study, the multiple functional connectivity-based graph convolutional network (MFC-GCN) framework is proposed, using not only full brain functional connectivity data but also the established functional connectivity data from networks of key brain subnetworks associated with ASD, and the GCN is adopted to acquire complementary feature information for the final classification task. Given the heterogeneity within the Autism Brain Imaging Data Exchange (ABIDE) dataset, a novel External Attention Network Readout (EANReadout) is introduced. This design enables the exploration of potential subject associations, effectively addressing the dataset's heterogeneity. Experiments were conducted on the ABIDE dataset using the proposed framework, involving 714 subjects, and the average accuracy of the framework was 70.31%. The experimental results show that the proposed EANReadout outperforms the best traditional readout layer and improves the average accuracy of the framework by 4.32%.

Difference in mortality risk predicted by leukocyte and lymphocyte levels in COVID-19 patients infected with the Wild-type, Delta, and Omicron strains.

This study aimed to investigate the changing trends, level differences, and prognostic performance of the leukocyte and lymphocyte levels of patients infected with the Wild strains, Delta strains and Omicron strains to provide a reference for prognostic assessment. In the current study, we conducted a retrospective cross-sectional study to evaluate the changing trends, level differences, and prognostic performance of leukocyte and lymphocyte of different strains at admission and discharge may already exist in patients with coronavirus disease-2019 (COVID-19) infected with the Wild type, Delta, and Omicron strains. A retrospective cross-sectional study was conducted. We recruited and screened the 243 cases infected with the Wild-type strains in Wuhan, the 629 cases infected with the Delta and 116 cases infected strains with the Omicron strains in Xi'an. The leukocyte and lymphocyte levels were compared the cohort of Wild-type infection with the cohort of Delta and the Omicron. The changes in the levels of leukocytes and lymphocytes exhibit a completely opposite trend in patients with COVID-19 infected with the different strains. The lymphocyte level at admission and discharge in patients with COVID-19 infected with Omicron strains (area under curve [AUC] receiver operating characteristic curve [ROC] 72.8-90.2%, 82.8-97.2%) presented better performance compared patients with COVID-19 infected with Wild type strains (AUC ROC 60.9-80.7%, 82.3-97.2%) and Delta strains (AUC ROC 56.1-84.7%, 40.3-93.3%). Kaplan-Meier curves showed that the leukocyte levels above newly established cutoff values and the lymphocyte levels below newly established cutoff values had a significantly higher risk of in-hospital mortality in COVID-19 patients with Wild-type and Omicron strains (P < .01). The levels of leukocyte and lymphocyte at admission and discharge in patients with COVID-19 infected with the Wild type, Delta, and Omicron strains may be differences among strains, which indicates different death risks. Our research may help clinicians identify patients with a poor prognosis for severe acute respiratory syndrome coronavirus 2 infection.

Association Between Peritoneal Carcinomatosis Index (PCI) Assessed by CT and Pathological Parameters and Short-Term Prognosis of Rectal Cancer.

Objective: The study aimed at explore the correlation between the CT-based Peritoneal Carcinomatosis Index (PCI) and pathological parameters of rectal cancer, as well as the correlation with short-term postoperative prognosis. Methods: A retrospective analysis was performed on 198 rectal cancer patients treated in our institution from January 2017 to December 2022. Based on preoperative CT-PCI, patients were classified into a normal and low CT-PCI groups. Baseline characteristics and short-term postoperative outcomes were compared between the two groups. Univariate and Multivariable logistic regression analyses were conducted to ascertain the independent risk factors for postoperative complications (Clavien-Dindo classification ≥ Grade II) following neoadjuvant treatment and radical rectal cancer surgery. Results: There were significant statistical differences between the two groups regarding age, ASA score, and surgical method (P < .05). Variations in overall postoperative complications and complications of Grade II or higher among patients with differing preoperative CT-PCI were statistically significant (P < .05). No significant statistical difference was found in the time to first liquid intake post-surgery between the preoperative low CT-PCI group and the normal CT-PCI group (P > .05); however, differences in the time to first flatus, duration of postoperative hospital stay, and total hospital expenditure were statistically meaningful (P < .05). Multivariate logistic regression revealed that CT-PCI (OR=2.254) was an influential factor for postoperative complications (Clavien-Dindo classification ≥ Grade II) (P < .05). The ROC curve demonstrated an AUC of 0.854 for CT-PCI in predicting postoperative complications (Clavien-Dindo classification ≥ Grade II). Conclusion: Preoperative CT-PCI may be utilized to evaluate the short-term prognosis of patients who undergo radical surgery for rectal cancer after neoadjuvant therapy. This evaluation assists in guiding clinical diagnostic and therapeutic decision-making, allowing for prompt interventions and enhancing short-term patient outcomes.

The receptor binding domain of SARS-CoV-2 Omicron subvariants targets Siglec-9 to decrease its immunogenicity by preventing macrophage phagocytosis.

The development of a vaccine specific to severe acute respiratory syndrome coronavirus 2 Omicron has been hampered due to its low immunogenicity. Here, using reverse mutagenesis, we found that a phenylalanine-to-serine mutation at position 375 (F375S) in the spike protein of Omicron to revert it to the sequence found in Delta and other ancestral strains significantly enhanced the immunogenicity of Omicron vaccines. Sequence FAPFFAF at position 371-377 in Omicron spike had a potent inhibitory effect on macrophage uptake of receptor-binding domain (RBD) nanoparticles or spike-pseudovirus particles containing this sequence. Omicron RBD enhanced binding to Siglec-9 on macrophages to impair phagocytosis and antigen presentation and promote immune evasion, which could be abrogated by the F375S mutation. A bivalent F375S Omicron RBD and Delta-RBD nanoparticle vaccine elicited potent and broad nAbs in mice, rabbits and rhesus macaques. Our research suggested that manipulation of the Siglec-9 pathway could be a promising approach to enhance vaccine response.