Prognostic value of inflammatory nutritional scores in locally advanced esophageal squamous cell carcinoma patients undergoing neoadjuvant chemoimmunotherapy: a multicenter study in China

ObjectiveThis study investigates the prognostic significance of inflammatory nutritional scores in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC) undergoing neoadjuvant chemoimmunotherapy.MethodsA total of 190 LA-ESCC patients were recruited from three medical centers across China. Pre-treatment laboratory tests were utilized to calculate inflammatory nutritional scores. LASSO regression and multivariate logistic regression analyses were conducted to pinpoint predictors of pathological response. Kaplan-Meier and Cox regression analyses were employed to assess disease-free survival (DFS) prognostic factors.ResultsThe cohort comprised 154 males (81.05%) and 36 females (18.95%), with a median age of 61.4 years. Pathological complete response (pCR) was achieved in 17.38% of patients, while 44.78% attained major pathological response (MPR). LASSO and multivariate logistic regression analyses identified that hemoglobin, albumin, lymphocyte, and platelet (HALP) (P=0.02) as an independent predictors of MPR in LA-ESCC patients receiving neoadjuvant chemoimmunotherapy. Kaplan-Meier and log-rank tests indicated that patients with low HALP, MPR, ypT1-2, ypN0 and, ypTNM I stages had prolonged DFS (P < 0.05). Furthermore, univariate and multivariate Cox regression analyses underscored HALP (P = 0.019) and ypT (P = 0.029) as independent predictive factors for DFS in ESCC.ConclusionOur study suggests that LA-ESCC patients with lower pre-treatment HALP scores exhibit improved pathological response and reduced recurrence rate. As a comprehensive index of inflammatory nutritional status, pre-treatment HALP may be a reliable prognostic marker in ESCC patients undergoing neoadjuvant chemoimmunotherapy

Optimization Method for Low Tilt Sensitivity of Secondary Mirror Based on the Nodal Aberration Theory

The optical system that combines imaging and image motion compensation is conducive to the miniaturization of aerial mapping cameras, but the movement of optical element for image motion compensation will cause a decrease in image quality. To solve this problem, reducing the sensitivity of moving optical element is one of the effective ways to ensure the imaging quality of aerial mapping cameras. Therefore, this paper proposes an optimization method for the low tilt sensitivity of the secondary mirror based on the Nodal aberration theory. In this method, the analytical expressions of the tilt sensitivity of the secondary mirror in different tilt directions are given in the form of zernike polynomial coefficients, and the influence of the field of view on the sensitivity is expressed in the mathematical model. The desensitization optimization function and desensitization optimization method are proposed. The catadioptric optical system with a focal length of 350 mm is used for desensitization optimization. The results show that the desensitization function proposed in this paper is linearly related to the decrease of sensitivity within a certain range, and the standard deviation of the system after desensitization is 0.020, which is 59% of the system without desensitization. Compared with the traditional method, the method in this paper widens the range of angle reduction sensitivity and has a better desensitization effect. The research results show that the optimization method for low tilt sensitivity of the secondary mirror based on the Nodal aberration theory proposed in this paper reduces the tilt sensitivity of the secondary mirror, revealing that the reduction of the sensitivity depends on the reduction of the aberration coefficient related to the misalignment in the field of view, which is critical for the development of an optical system for aerial mapping cameras that combines imaging and image motion compensation

Evaluation and advancement of the integrated circular economy model of farming and stock raising

The integrated circular economy model of farming and stock raising (ICEMFSR) has attracted increased attention as an effective model for solving the current irrational allocation of agricultural resources and realizing the agricultural value-added industrial chain. This study uses emergy analysis to comprehensively examine and evaluate the economic benefits, environmental pressures, and sustainable development levels of ICEMFSR in Shucheng County, China. The results show that the ICEMFSR possesses the value of popularization with optimally allocated resources in the studied region, in which the emergy yield ratio (EYR), emergy loading ratio (ELR), and emergy sustainable index (ESI) in this model accounted for 3.59, 1.25, and 2.89, respectively. This result indicates a leading position in the national agricultural system. Hence, this study constructs a new model based on the coupling of emergy evaluation and multi-objective linear programming to study ICEMFSR. Consequently, the EYR, ELR, and ESI respectively varied by +24.23%, −10.40%, and +38.06% after replanning of ICEMFSR. This variation implies a significant improvement in the sustainable development level of the model. In addition, the optimized scenario design for key substances is proposed based on traceability and the reduce-reuse-recycle principle, including biogasification of crop straw and enhancement of crop scientific planting capacity

Fluorescent probes for glucolipid metabolism of bacterial cell wall

Cell wall is a basic component of bacteria that promotes bacteria to adapt the complicated environment as well as play an essential role in antimicrobial resistance. The structure of bacterial cell wall is remarkably rich, and some complex components, such as peptidoglycan, lipopolysaccharide, and peptidoglycan-arabinogalactan et al., can only be found in bacteria. Furthermore, the biosynthesis and transfer of these glycolipids are indispensable for bacteria during cell elongation. And the process of biosynthesis and transfer are generally associated with metabolism and sophisticated enzyme mechanisms. However, how the metabolic process takes place, what role enzymes play in this process and how they function have been major concerns for scientists in this field. Numerous significant progresses on fluorescent probes and biological imaging bring opportunity for the studying of metabolism and enzyme mechanisms recently due to its non-invasive and high sensitivity. In this review, we focused on metabolic fluorescent probes for the detection of glycolipids in bacterial cell wall and highlighted the involving mechanisms and biological application

A Diabetes Prediction System Based on Incomplete Fused Data Sources

In recent years, the diabetes population has grown younger. Therefore, it has become a key problem to make a timely and effective prediction of diabetes, especially given a single data source. Meanwhile, there are many data sources of diabetes patients collected around the world, and it is extremely important to integrate these heterogeneous data sources to accurately predict diabetes. For the different data sources used to predict diabetes, the predictors may be different. In other words, some special features exist only in certain data sources, which leads to the problem of missing values. Considering the uncertainty of the missing values within the fused dataset, multiple imputation and a method based on graph representation is used to impute the missing values within the fused dataset. The logistic regression model and stacking strategy are applied for diabetes training and prediction on the fused dataset. It is proved that the idea of combining heterogeneous datasets and imputing the missing values produced in the fusion process can effectively improve the performance of diabetes prediction. In addition, the proposed diabetes prediction method can be further extended to any scenarios where heterogeneous datasets with the same label types and different feature attributes exist

Molecular mechanism by which spider-driving peptide potentiates coagulation factors

Hemostasis is a crucial process that quickly forms clots at injury sites to prevent bleeding and infections. Dysfunctions in this process can lead to hemorrhagic disorders, such as hemophilia and thrombocytopenia purpura. While hemostatic agents are used in clinical treatments, there is still limited knowledge about potentiators targeting coagulation factors. Recently, LCTx-F2, a procoagulant spider-derived peptide, was discovered. This study employed various methods, including chromogenic substrate analysis and dynamic simulation, to investigate how LCTx-F2 enhances the activity of thrombin and FXIIa. Our findings revealed that LCTx-F2 binds to thrombin and FXIIa in a similar manner, with the N-terminal penetrating the active-site cleft of the enzymes and the intermediate section reinforcing the peptide-enzyme connection. Interestingly, the C-terminal remained at a considerable distance from the enzymes, as evidenced by the retention of affinity for both enzymes using truncated peptide T-F2. Furthermore, results indicated differences in the bonding relationship of critical residues between thrombin and FXIIa, with His13 facilitating binding to thrombin and Arg7 being required for binding to FXIIa. Overall, our study sheds light on the molecular mechanism by which LCTx-F2 potentiates coagulation factors, providing valuable insights that may assist in designing drugs targeting procoagulation factors

A Flexible Solid Composite Electrolyte with Vertically Aligned and Connected Ion-Conducting Nanoparticles for Lithium Batteries

Replacing flammable organic liquid electrolytes with solid Li-ion conductors is a promising approach to realize safe rechargeable batteries with high energy density. Composite solid electrolytes, which are comprised of a polymer matrix with ceramic Li-ion conductors dispersed inside, are attractive, since they combine the flexibility of polymer electrolytes and high ionic conductivities of ceramic electrolytes. However, the high conductivity of ceramic fillers is largely compromised by the low conductivity of the matrix, especially when nanoparticles (NPs) are used. Therefore, optimizations of the geometry of ceramic fillers are critical to further enhance the conductivity of composite electrolytes. Here we report the vertically aligned and connected Li_1+<i>x</i>Al_<i>x</i>Ti_2–<i>x</i>(PO₄)₃ (LATP) NPs in the poly­(ethylene oxide) (PEO) matrix to maximize the ionic conduction, while maintaining the flexibility of the composite. This vertically aligned structure can be fabricated by an ice-templating-based method, and its conductivity reaches 0.52 × 10^–4 S/cm, which is 3.6 times that of the composite electrolyte with randomly dispersed LATP NPs. The composite electrolyte also shows enhanced thermal and electrochemical stability compared to the pure PEO electrolyte. This method opens a new approach to optimize ion conduction in composite solid electrolytes for next-generation rechargeable batteries