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Background In 2018, the National Centralized Drug Procurement (NCDP) policy has been implemented in 11 provinces, and promoted across the country in 2019. The main feature of the policy is “volume for price”, therefore, it is necessary to measure the price relationship, not only to reduce the price of drugs, reduce the burden of patients' medical costs, but also facilitate pharmaceutical companies to access enough innovation incentives. The aim of this study was to assess the vacated space effect of the drug centralized procurement by national organizations in exchange of price for quantity. Methods A difference-in-differences (DID) model was employed to analyze the effect of the 4 + 7 pilot drugs centralized purchasing policy on drug sales volume and selected versus clinically substitutable unselected varieties, using observational data from 2018 to 2019. We compared drug procurement data between secondary and above public hospitals in pilot and non-pilot cities throughout China. Results The study showed that the average treatment effect (ATE) of sales in the in-hospital market for the selected supply varieties in centralized purchasing is -0.42, and with a sales volume of 0.49. This indicates a volume-price vacated space of 1.16 ~ 1.17 DDD (defined daily dose)/Yuan, implying that for every 1 defined daily dose (DDD) increase in reported volume, the standardized price decreased by 1.16–1.17 Yuan. The ATE of in-hospital market sales for drugs not selected in centralized procurement shows a decrease of 0.13. This finding highlights the presence of the price linkage effect. The ATE of sales volume is 0.57, indicating a volume-price space of 4.38 ~ 4.39 DDD/Yuan for unselected drugs, approximately 3.75 higher relative to that of the selected ones. Conclusions The ratio of the volume-price space of clinically substitutable unselected and selected drugs may serve as direct evidence for evaluating the shift from centralized purchasing of drug varieties to clinically substitutable other ones. To strengthen the volume-based negotiation approach and maximize the effectiveness of centralized purchasing policies, we recommend the strategic implementation of a three-tiered centralized purchasing system, the expansion of drug coverage, and the introduction of relevant constraints and incentives.

The aim of this study was to investigate whether serum zinc levels correlate with the response to immune checkpoint inhibitors (ICIs) and whether they can be used as a useful prognostic biomarker in patients with advanced or metastatic cancer. We divided 98 patients with advanced or metastatic lung, esophageal, gastric, and colorectal cancer into two groups based on enrollment date: the training group (n = 68) and the validation group (n = 30). And these patients were from Shandong Provincial Hospital and had received immunotherapy. We then used the solid tumor response Evaluation Criteria (RECIST v1.1) to determine whether the patient's condition was evaluated for clinical benefit response (CBR) or non-clinical benefit (NCB). Subsequently, serum zinc levels were assessed using ICP-MS. We have identified for the first time that elevated levels of serum zinc (>14.2μg/L) in cancer patients undergoing immunotherapy can serve as a novel biomarker for improved overall survival (20.0m vs 10.0m; p < 0.0001), as determined by continuous serum zinc data using ROC curve analysis (sensitivity: 100.00%, specificity: 41.86%, p = 0.0009) in both CBR (n = 43) and NCB patients (n = 25) within the training group. Bioinformatics analysis has revealed that serum zinc may modulate cellular DNA replication through the MAPK and NF-kB pathways, with proteomic analysis confirming enrichment of these pathways based on KEGG and GO analyses. Consequently, a nomogram incorporating multiple clinical and independent factors has been developed to provide enhanced predictive capability. Serum zinc levels are positively associated with the effectiveness of ICIs in patients with advanced or metastatic cancer, potentially through their modulation of NF-κB and MAPK pathways. These findings highlight serum zinc as a valuable biomarker for predicting responses to ICI treatment.

The pyrolysis of pine sawdust was carried out in a fixed bed reactor heated from 30 °C to a maximum of 700 °C in atmospheric nitrogen and pressurized hydrogen (5 MPa). The yield, elemental composition, thermal stability, and composition of the two pyrolysis bio-oils were analyzed and compared. The result shows that the oxygen content of the bio-oil (17.16%) obtained under the hydrogen atmosphere was lower while the heating value (31.40 MJ/kg) was higher than those of bio-oil produced under nitrogen atmosphere. Compounds with a boiling point of less than 200 °C account for 63.21% in the bio-oil at pressurized hydrogen atmosphere, with a proportion 14.69% higher than that of bio-oil at nitrogen atmosphere. Furthermore, the hydrogenation promoted the formation of ethyl hexadecanoate (peak area percentage 19.1%) and ethyl octadecanoate (peak area percentage 15.42%) in the bio-oil. Overall, high pressure of hydrogen improved the bio-oil quality derived from the pyrolysis of pine biomass.

Martensitic/bainitic wear-resistant steels are widely used in civilian industry, where a good combination of strength and toughness is required. In the present study, a double-quenching process was applied and compared to the conventional single-quenching process. The microhardness and ductile–brittle transition temperature were measured, and the microstructure was characterized with scanning electron microscopy and electron backscatter diffraction (EBSD) technique. It was found that the double-quenching process refined the prior austenite grain size by 43% and simultaneously improved the toughness and hardness. The ductile-to-brittle transition temperature was decreased from −77 °C to −90 °C, and the hardness was increased by 8%. Based on the EBSD data, a detailed analysis of the grain boundary distribution was performed using a recently developed machine learning model. Unlike what was found in previous studies, for the studied wear-resistant steel, the refinement of the prior austenite grain did not increase the block boundary density while increasing the high-angle packet boundary density. As a result, the total density of the high-angle grain boundaries in the double-quenched specimen was not improved compared to the single-quenched specimen. Further inspection suggested that it is the prior austenite grain boundaries and high-angle packet boundaries that contribute to the hardness and toughness, and the key factors that determine their effectiveness are the high misorientation angle between the 110 slip planes and the high slip transmission factor.

Purpose The KRAS mutation is highly prevalent in NSCLC and is associated with poor efficacy of immunotherapy. Nevertheless, the impact of KRAS mutation, mutation subtypes, and co-mutations on the effectiveness of immunotherapy remains uncertain. This study aimed to assess the influence of the KRAS mutation on the effectiveness of immunotherapy in NSCLC, specifically examining different subtypes of KRAS mutations and co-mutations. Methods We performed an extensive search of multiple databases, covering the period from January 1, 2000, to December 5, 2023. A total of 24 articles met our inclusion criteria and were included in this study. A comparative analysis assessed the influence of different subgroups, including KRAS mutation, KRAS wild-type, KRAS G12C mutation, KRAS G12D mutation, and KRAS with co-mutations in NSCLC with immunotherapy. The study outcomes include HR, with corresponding 95% CI and P-values for OS and PFS using Review Manager 5.4 software for the meta-analysis. Result The KRAS mutation appears to have a more beneficial impact on OS (HR 0.54 [95% CI: 0.41–0.71]; P  < 0.00001) and PFS (HR 0.63 [95% CI: 0.53–0.76]; P  < 0.00001) in NSCLC patients receiving immunotherapy compared to those without immunotherapy. The presence of KRASG12C mutation has been found to have a positive impact on PFS (HR 0.39 [95% CI: 0.25–0.62]; P  < 0.0001) in NSCLC patients who undergo immunotherapy, compared to those who did not receive immunotherapy. KRAS non-G12D mutation is considerably associated with longer OS (HR 1.52 [95% CI: 1.10–2.10]; P  = 0.01). The clinical benefit in OS between patients without STK11 co-mutation and those who have KRAS mutation with STK11 is significant (HR 1.46 [95% CI: 1.10–1.93]; P  = 0.008). Comparing the impact of OS patients without KEAP1/NFE2L2 mutation to those with KRAS and KEAP1/NFE2L2 co-mutations showed a significant impact (HR 1.89 [95% CI: 1.33–2.68]; P  = 0.0004). Conclusion The KRAS mutation and KRAS G12C mutation confer benefits that impact OS and PFS in NSCLC patients treated with immunotherapy. However, the KRAS G12D mutation negatively impacts OS compared to the KRAS non-G12D mutation. Furthermore, KRAS co-mutations involving STK11 and KEAP1/NFE2L2 are associated with a negative impact on the efficacy of immunotherapy in NSCLC patients.

For engineering structures, strain flexibility-based approaches have been widely used for structural health monitoring purposes with prominent advantages. However, the applicability and robustness of the method need to be further improved. In this paper, a novel damage index based on differences in uniform load strain field (ULSF) is developed for plate-like structures. When estimating ULSF, the strain flexibility matrix (SFM) based on mass-normalized strain mode shapes (SMSs) is needed. However, the mass-normalized strain mode shapes (SMSs) are complicated and difficult to obtain when the input, i.e., the excitation, is unknown. To address this issue, the proportional strain flexibility matrix (PSFM) and its simplified construction procedure are proposed and integrated into the frames of ULSF, which can be easily obtained when the input is unknown. The identification accuracy of the method under the damage with different locations and degrees is validated by the numerical examples and experimental examples. Both the numerical and experimental results demonstrate that the proposed method provides a reliable tool for output-only damage detection of plate-like structures without estimating the mass-normalized strain mode shapes (SMSs).

Background Shenling Baizhu Powder (SBP) is a traditional Chinese medicine (TCM) prescription, which has the good efficacy on gastrointestinal toxicity. In this study, we used gut microbiota analysis, metabonomics and network pharmacology to investigate the therapeutic effect of SBP on pyrotinib-induced diarrhea. Methods 24 Rats were randomly divided into 4 groups: control group, SBP group (3.6 g/kg /bid SBP for 10 days), pyrotinib model group (80 mg/kg/qd pyrotinib) and pyrotinib + SBP treatment group. A 16S rRNA sequencing was used to detect the microbiome of rat fecal bowel. Metabolic profiles were collected by non-targeted metabolomics and key metabolic pathways were identified using MetaboAnalyst 5.0. The antitumor effect of SBP on cells treated with pyrotinib was measured using a CCK-8 assay. Network pharmacology was used to predict the target and action pathway of SBP in treating pyrotinib-related diarrhea. Results In vivo study indicated that SBP could significantly alleviate pyrotinib-induced diarrhea, reaching a therapeutic effect of 66.7%. SBP could regulate pyrotinib-induced microbiota disorder. LEfSe research revealed that the SBP could potentially decrease the relative abundance of Escherichia, Helicobacter and Enterobacteriaceae and increase the relative abundance of Lachnospiraceae, Bacilli, Lactobacillales etc. In addition, 25-Hydroxycholesterol, Guanidinosuccinic acid, 5-Hydroxyindolepyruvate and cAMP were selected as potential biomarkers of SBP for pyrotinib-induced diarrhea. Moreover, Spearman's analysis showed a correlation between gut microbiota and metabolite: the decreased 25-hydroxycholesterol in the pyrotinib + SBP treatment group was negatively correlated with Lachnospiraceae while positively correlated with Escherichia and Helicobacter . Meanwhile, SBP did not affect the inhibitory effect of pyrotinib on BT-474 cells and Calu-3 cells in vitro. Also, the network analysis further revealed that SBP treated pyrotinib-induced diarrhea through multiple pathways, including inflammatory bowel disease, IL-17 signaling pathway, pathogenic Escherichia coli infection and cAMP signaling pathway. Conclusions SBP could effectively relieve pyrotinib-induced diarrhea, revealing that intestinal flora and its metabolites may be involved in this process.

Identifying prognostic factors for severe COVID-19 pneumonia during the Omicron wave remains crucial for early risk stratification and improving patient outcomes. This study aimed to identify and analyze key clinical and CT imaging features associated with survival in patients with severe pneumonia caused by the SARS-CoV-2 Omicron variant. This retrospective study included patients presenting to the emergency department of Shandong Provincial Hospital (December 2022-January 2023) with confirmed SARS-CoV-2 Omicron infection and severe pneumonia. Clinical/laboratory data and CT imaging features were systematically collected and evaluated. Patients were randomly divided into training (70%) and validation (30%) cohorts. Univariate and multivariate analyses were rigorously applied to identify significant baseline clinical and CT imaging features associated with survival. A predictive nomogram was constructed based on the selected feature combination. Among 1,739 COVID-19 patients, 151 (8.68%) had severe pneumonia (median age 75, 70.1% male). Multivariate logistic regression analysis identified a critical combination of features independently associated with survival: CT findings of pleural effusion ( = 0.008) and cardiac enlargement ( = 0.008), along with clinical/laboratory factors including reduced baseline pulse oxygen saturation ( = 0.034), elevated SAA ( = 0.020), elevated GLU ( = 0.022), and reduced Ca concentration ( = 0.029). The nomogram integrating these combined features demonstrated good predictive performance for in-hospital mortality (AUC: training cohort 0.914, validation cohort 0.802). This study identifies a distinct combination of clinical and CT imaging features (pleural effusion, cardiac enlargement, low SpO2, elevated SAA, elevated GLU, low Ca) as key independent prognostic factors for survival in severe Omicron pneumonia. The predictive tool based on this feature combination shows significant clinical utility. These preliminary findings provide critical insights for early risk assessment and targeted management, facilitating improved patient prognosis.

A novel YOLOv5 network is presented in this paper to quantify the degree of defects in continuously cast billets. The proposed network addresses the challenges posed by noise or dirty spots and different defect sizes in the images of these billets. The CBAM-YOLOv5 network integrates the channel and spatial attention of the Convolutional Block Attention Module (CBAM) with the C3 layer of the YOLOv5 network structure to better fuse channel and spatial information, with focus on the defect target, and improve the network’s detection capability, particularly for different levels of segregation. As a result, the feature pyramid is improved. The feature map obtained after the fourth down-sampling of the backbone network is fed into the feature pyramid through CBAM to improve the perceptual field of the target and reduce information loss during the fusion process. Finally, a self-built dataset of continuously cast billets collected from different sources is used, and several experiments are conducted using this database. The experimental results show that the average accuracy (mAP) of the network is 93.7%, which can achieve intelligent rating.

Addition of B is beneficial for the hardenability of low-alloy steels and the effect is further improved when combined with the addition of Mo. While experiments demonstrated that Mo reduces the M23(C,B)6 precipitation and indicated an interaction between the alloying elements at the grain boundary, the underlying mechanism remains unclear. In the present study, the segregation behavior of B and its interaction with C and Mo at an austenite grain boundary were investigated using first-principles calculations. It was demonstrated that B has a strong tendency to segregate to the grain boundary and leads to a remarkable reduction in grain boundary energy, which is considered to be responsible for the improvement in hardenability. A strong attractive interaction between B and Mo was revealed, consistent with the experimentally observed co-segregation. The partitioning energies of Mo and B from grain boundary into borocarbide were calculated, and it was found that Mo can suppress the precipitation by increasing the partitioning energy of B and destabilizing the M23(C,B)6 phase.