Short- and long-term outcomes of robotic versus open radical antegrade modular pancreatosplenectomy: a retrospective propensity score-matched cohort study.

BACKGROUND: Robotic distal pancreatectomy has increasingly been accepted as it has overcome some of the limitations of open distal pancreatectomy, whilst the outcomes following robotic radical antegrade modular pancreatosplenectomy (RAMPS) in patients with pancreatic ductal adenocarcinoma (PDAC) are still uncertain. This study aimed to evaluate the short and long-term outcomes of robotic RAMPS and open RAMPS for PDAC. METHODS: The patients who underwent robotic RAMPS and open RAMPS for PDAC at our clinical centre between January 2017 and December 2021 were reviewed. After a propensity score matching (PSM) at a 1:1 ratio, the perioperative and pathological outcomes in the both groups were reviewed. Univariable and multivariable Cox regression analyses were used to identify independent prognosis factors for overall survival (OS) and recurrence-free survival (RFS) of these patients. RESULTS: 318 cases were recorded in robotic and open groups. The robotic group showed advantages in operative time [205.00 (166.00, 240.00) min vs 235 (184.75, 270.00) min, P = 0.002], estimated blood loss [100 (50, 100) ml vs 300 (100, 400) ml, P < 0.001], delayed gastric emptying [0 vs 5.03%, P = 0.007] and postoperative hospital stay [7.00 (5.00, 10.00) days vs 11.00 (8.00, 14.00) days, P < 0.001]. There were no significant differences in rate of severe postoperative complications between the robotic group and the open group. Multivariable analysis showed that carbohydrate antigen 19-9, estimated blood loss, N stage, tumour differentiation, chemotherapy and vascular invasion were independent risk factors for OS and RFS of these patients. CONCLUSIONS: Robotic RAMPS was safe and had some advantages over open RAMPS for PDAC. There were no significantly differences in oncological outcomes and long-term survival rates between the robotic and open groups. Robotic RAMPS expanded the indications for minimally invasive surgeries for PDAC to a certain extent.

Association of KMT2C/D loss-of-function variants with response to immune checkpoint blockades in colorectal cancer.

Immune checkpoint inhibitors (ICIs) have become important treatment strategies, yet responses vary among patients and predictive biomarkers are urgently needed. Mutations in KMT2C and KMT2D lead to increased levels of genomic instability. Therefore, we aimed to examine whether KMT2C/D mutations might be a predictor of immunotherapeutic efficacy. Here, we investigated the associations of KMT2C/D loss-of-function (LOF) variants with tumor mutation burden (TMB), MSI-H, PD-L1 expression, the levels of tumor-infiltrating leukocytes (TILs), and clinical response to ICIs. It was found that KMT2C/D LOF variants were associated with higher TMB. Compared with the non-LOF group, the proportion of patients with MSI-H tumors was larger in the LOF group. PD-L1 expression was higher in the LOF group only for colorectal cancer in both the Chinese and The Cancer Genome Atlas cohorts. Importantly, KMT2C/D LOF variants were associated with decreased regulatory T cells and increased levels of CD8+ T cells, activated NK cells, M1 macrophages, and M2 macrophages in colorectal cancer. However, there was no significant association between KMT2C/D LOF and TILs levels in other cancer types. Consistently, the results showed that KMT2C/D LOF variants were associated with prolonged overall survival only in colorectal cancer (p = 0.0485). We also presented that patients with KMT2C/D LOF mutations exhibited a better clinical response to anti-PD-1 therapy in a Chinese colorectal cancer cohort (p = 0.002). Taken together, these results suggested that KMT2C/D LOF variants could be a useful predictor for ICIs efficacy in colorectal cancer. In addition, the predictive value of KMT2C/D LOF variants was consistent with their association with TILs levels.

Nomogram predicts risk of perineural invasion based on serum biomarkers for pancreatic cancer.

BACKGROUND: Pancreatic cancer is a fatal tumor, and the status of perineural invasion (PNI) of pancreatic cancer was positively related to poor prognosis including overall survival and recurrence-free survival. This study aims to develop and validate a predictive model based on serum biomarkers to accurately predict the perineural invasion. MATERIALS AND METHODS: The patients from No.924 Hospital of PLA Joint Logistic Support Force were included. The predictive model was developed in the training cohort using logistic regression analysis, and then tested in the validation cohort. The area under curve (AUC), calibration curves and decision curve analysis were used to validate the predictive accuracy and clinical benefits of nomogram. RESULTS: A nomogram was developed using preoperative total bilirubin, preoperative blood glucose, preoperative CA19-9. It achieved good AUC values of 0.753 and 0.737 in predicting PNI in training and validation cohorts, respectively. Calibration curves showed nomogram had good uniformity of the practical probability of PNI. Decision curve analyses revealed that the nomogram provided higher diagnostic accuracy and superior net benefit compared to single indicators. CONCLUSION: The present study constructed and validate a novel nomogram predicted the PNI of resectable PHAC patients with high stability and accuracy. Besides, it could better screen high-risk probability of PNI in these patients, and optimize treatment decision-making.

Derivation and validation of a preoperative prognostic model for resectable pancreatic ductal adenocarcinoma.

BACKGROUND: The prognosis of patients with pancreatic ductal adenocarcinoma (PDAC) remains poor even after radical pancreaticoduodenectomy (PD). The study aimed to develop and validate a novel preoperative prognostic model to accurately predict the long-term survival of patients with PDAC. METHODS: Patients with PDAC of pancreatic head from Chinese PLA General Hospital were included. The preoperative PDAC model with contour plots was developed using a non-linear model in the training cohort and then tested in the validation cohort. RESULTS: Of 421 patients who met the inclusion criteria, 280 were in the training cohort and 141 in the validation cohort. Contour plots for preoperative PDAC model were established to visually predict the survival probabilities of these patients, based on preoperative carbohydrate antigen 19-9, preoperative fibrinogen to albumin ratio and pain symptoms. This model stratified patients into low- and high-risk groups with distinctly different long-term survival in the training cohort [median overall survival (OS) 32.1 vs. 17.5 months; median recurrence-free survival (RFS) 19.3 vs. 10.0 months, both P < 0.001] and the validation cohort (median OS 28.3 vs. 19.0 months; median RFS 17.5 vs. 11.2 months, both P < 0.001). Time-dependent receiver operating characteristic and decision curve analyses revealed that the model provided higher diagnostic accuracy and superior net benefit compared to other staging systems. CONCLUSIONS: This study constructed and validated a novel preoperative prognostic model that can accurately and conveniently predict the long-term survival of patients with resectable PDAC of pancreatic head. Besides, the model can screen high-risk patients with poor prognosis, which may provide references for personal treatment strategies in the future.

Step-by-step and orderly lowering of the height of inferior vena cava tumor thrombus is the key to robot-assisted thrombectomy for Mayo III/IV tumor thrombus.

BACKGROUND: The surgical management of Mayo III/IV tumor thrombi is difficult and risky, and robotic surgery is even more difficult. The purpose of this study was to introduce the step-by-step and orderly lowering of the height of inferior vena cava tumor thrombus, which was the core technique of robot operation for Mayo III/IV tumor thrombus. METHOD: A total of 18 patients were included in this study. The average tumor thrombus height was 2.4 cm above the level of the second porta hepatis (SPH), and 9 patients were prepared for cardiopulmonary bypass (CPB) before surgery. During the operation, the height of the tumor thrombus was lowered orderly for 2-3 times, and the blood flow blocking method was changed sequentially. The CPB was required when tumor thrombus in the atrium; After the height of the thrombus was lowered to the atrium entrance, CPB was stopped and the blood flow was blocked in the upper- and retro-hepatic inferior vena cava (IVC); After the tumor thrombus continued to descend to the lower part of the SPH, liver blood flow could be restored, and then, the blood flow was simply blocked in the retro-hepatic IVC to complete the removal of the thrombus and the repair or resection of the IVC. Finally, the diseased kidney and renal vein were removed. RESULTS: All operations were successfully completed, and 2 cases were transferred to laparotomy. Seven cases received CPB, while the other 11 did not. 15 patients underwent two times of the lowering of the tumor thrombus, 2 patients underwent one time and 1 patient underwent three times. The mean liver/IVC dissociation and vascular suspension time was 22.0 min. All patients had less than Clavien-Dindo grade III complications, no serious complications occurred during operation, and no patient died within 90 days. CONCLUSIONS: The step-by-step and orderly decline of tumor thrombus height is the key to the success of robot Mayo III / IV tumor thrombus surgery. This method can shorten FPH and CPB time and improve the success rate of surgery.

A novel online calculator to predict recurrence risk in patients with distal cholangiocarcinoma after radical pancreaticoduodenectomy.

BACKGROUND: Patients with distal cholangiocarcinoma (DCC) are prone to relapse even after radical pancreaticoduodenectomy. In this study, we sought to create an online nomogram calculator to accurately predict the recurrence risk of DCC. METHODS: A total of 184 patients were included. Multivariate Cox regression analysis was used to identify independent prognosis factors for recurrence-free survival and overall survival. A nomogram was constructed according to the prognostic factors in the training cohort and then tested in the validation cohort. RESULTS: Multivariate Cox analysis showed preoperative carbohydrate antigen 19-9 (p < 0.001), maximum tumor size (p = 0.076), perineural invasion (p = 0.044), and N stage (p = 0.076) were independent prognostic factors for DCC relapse. We then constructed a nomogram with these four factors. The consistency index (C-index) of the nomogram in the training and validation cohorts were 0.703 and 0.665, respectively. Time-dependent receiver operating characteristic and decision curve analyses revealed that the nomogram provided higher diagnostic power and net benefit compared with other staging systems. CONCLUSION: In this study, we developed an online nomogram calculator that can accurately predict the recurrence risk of DCC and identify patients with a high risk of recurrence in a simple and convenient manner.

Molecular subtyping based on TRP family and prognostic assessment for TRP-associated lncRNAs in pancreatic adenocarcinoma.

BACKGROUND: Transient receptor potential (TRP) channels have high permeability to Ca2+ ions because they are non-selective ion channels. TRP channels have been implicated in tumor onset and progression, proliferation, and migration in recent years. However, the prognostic value of genes related to TRP and their specific mechanism in pancreatic adenocarcinoma (PAAD) are yet to be understood. METHODS: Public databases such as TCGA and GEO were used to retrieve data on gene expression and clinical information of patients with pancreatic adenocarcinoma for our study. ConsensusClusterPlus package was used for unsupervised clustering analysis. The microenvironment cell population (MCP)-counter approach was employed to measure the immune cells infiltration status. The Pearson correlation was performed to identify TRP-associated lncRNAs. RESULTS: Initially, we separated PAAD patients into three clusters depending on TRP-related genes, and of the three clusters, cluster B showed the least immune cell infiltration, which was correlated with poor prognosis. Moreover, GSVA enrichment analysis further revealed that cluster A was subjected to a considerable enrichment in carcinogenic signaling pathways, whereas cluster C was enriched in immune-related pathways. Then, using TRP-associated lncRNAs as a starting point, we constructed a prognostic risk model for PAAD patients that could efficiently predict their prognosis. Further, GSEA revealed that cancer-related pathways, for instance, the cell cycle, p53 signaling pathway, etc. were considerably enriched in the high-risk group. In addition, we looked into the link between the prognostic model and the immunological microenvironment. Lower cytotoxic lymphocytes, NK cells, CD8 T cells, and endothelial cells infiltration were found to be associated with high risk using the MCP-counter algorithm. The expression of CD274, POLE2, MCM6, and LOXL2 was also found to be higher in the high-risk group. TMB was also considerably greater in high-risk individuals, indicating that immune checkpoint inhibitors (ICIs) therapy may benefit them more. Lastly, qRT-PCR further confirmed the differential expression of these prognostic TRP-associated lncRNAs, indicating that these lncRNAs play an imperative role in PAAD tumorigenesis. CONCLUSION: TRP family genes may represent a new class of candidate molecular markers of the occurrence and progression of PAAD. Risk models based on TRP-associated lncRNAs could provide important new references for immunotargeted therapy of pancreatic adenocarcinoma.

Robotic versus open pancreaticoduodenectomy for distal cholangiocarcinoma: a multicenter propensity score-matched study.

BACKGROUND: Pancreatoduodenectomy is the only potentially curative treatment for distal cholangiocarcinoma (DCC). In this study, we sought to compare the perioperative and oncological outcomes of robotic pancreaticoduodenectomy (RPD) and open pancreaticoduodenectomy (OPD) based on a multicenter propensity score-matched study. METHODS: Consecutive patients with DCC who underwent RPD or OPD from five centers in China between January 2014 and June 2019 were included. A 1:1 propensity score matching (PSM) was performed. Univariable and multivariable Cox regression analyses were used to identify independent prognosis factors for overall survival (OS) and recurrence-free survival (RFS) of these patients. RESULTS: A total of 217 patients and 228 patients underwent RPD and OPD, respectively. After PSM, 180 patients in each group were enrolled. There were no significant differences in operative time, lymph node harvest, intraoperative transfusion, vascular resection, R0 resection, postoperative major morbidity, reoperation, 90-day mortality, and long-term survival between the two groups before and after PSM. Whereas, compared with the OPD group, the RPD group had significantly lower estimated blood loss (150.0 ml vs. 250.0 ml; P < 0.001), and a shorter postoperative length of stay (LOS) (12.0 days vs. 15.0 days; P < 0.001). Multivariable analysis showed carbohydrate antigen 19-9 (CA19-9), R0 resection, N stage, perineural invasion, and tumor differentiation significantly associated with OS and RFS of these patients. CONCLUSIONS: RPD was comparable to OPD in feasibility and safety. For patients with DCC, RPD resulted in similar oncologic and survival outcomes as OPD.

PIWIL4 and SUPT5H combine to predict prognosis and immune landscape in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a fatal primary liver cancer, and its long-term survival rate remains poor. RNA-binding proteins (RBPs) play an important role in critical cellular processes, failure of any one or more processes can lead to the development of multiple cancers. This study aimed to explore pivotal biomarkers and corresponding mechanisms to predict the prognosis of patients with ICC. METHODS: The transcriptomic and clinical information of patients were collected from The Cancer Genome Atlas and Gene Expression Omnibus databases. Bioinformatic methods were used to identify survival-related and differentially-expressed biomarkers. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry were used to detect the expression levels of key biomarkers in independent real-world cohorts. Subsequently, a prognostic signature was constructed that effectively distinguished patients in the high- and low-risk groups. Independent prognosis analysis was used to verify the signature's independent predictive capabilities, and two nomograms were developed to predict survival. RESULTS: PIWIL4 and SUPT5H were identified and considered as pivotal biomarkers, and the same expression trends of upregulation in ICC were also validated via qRT-PCR and immunohistochemistry in the separate real-world sample cohorts. The prognostic signature showed good predictive capabilities according to the area under the curve. The correlation of the biomarkers with the tumour microenvironment suggested that the high riskScore was positively related to the enrichment of resting natural killer cells and activated memory CD4 + T cells. CONCLUSION: In the present study, we demonstrated that PIWIL4 and SUPT5H could be used as novel prognostic biomarkers to develop a prognostic signature. This study provides potential biomarkers of prognostic value for patients with intrahepatic cholangiocarcinoma.

A nomogram predicting overall survival in patients with non-metastatic pancreatic head adenocarcinoma after surgery: a population-based study.

BACKGROUND: Pancreatic head adenocarcinoma (PHAC), a malignant tumour, has a very poor prognosis, and the existing prognostic tools lack good predictive power. This study aimed to develop a better nomogram to predict overall survival after resection of non-metastatic PHAC. METHODS: Patients with non-metastatic PHAC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and divided randomly into training and validation cohorts at a ratio of 7:3. Cox regression analysis was used to screen prognostic factors and construct the nomogram. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the performance of the model. The predictive accuracy and clinical benefits of the nomogram were validated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). RESULTS: From 2010 to 2016, 6419 patients with non-metastatic PHAC who underwent surgery were collected from the SEER database. A model including T stage, N stage, grade, radiotherapy, and chemotherapy was constructed. The concordance index of the nomogram was 0.676, and the AUCs of the model assessing survival at multiple timepoints within 60 months were significantly higher than those of the American Joint Committee on Cancer (AJCC) 8th staging system in the training cohort. Calibration curves showed that the nomogram had ability to predict the actual survival. The NRI, IDI, and DCA curves also indicated that our nomogram had higher predictive capability and clinical utility than the AJCC staging system. CONCLUSIONS: Our nomogram has an ability to predict overall survival after resection of non-metastatic PHAC and includes prognostic factors that are easy to obtain in clinical practice. It would help assist clinicians to conduct personalized medicine.

A metabolism-related 4-lncRNA prognostic signature and corresponding mechanisms in intrahepatic cholangiocarcinoma.

BACKGROUND: Long non-coding RNA (lncRNA) plays a critical role in the malignant progression of intrahepatic cholangiocarcinoma (iCCA). This study aimed to establish a 4-lncRNA prognostic signature and explore corresponding potential mechanisms in patients with iCCA. METHODS: The original lncRNA-seq and clinical data were collected from the TCGA and GEO databases. Overlapping and differentially expressed lncRNAs (DE-lncRNAs) were further identified from transcriptome data. Univariate regression analysis was performed to screen survival-related DE-lncRNAs, which were further selected to develop an optimal signature to predict prognosis using multivariate regression analysis. The Kaplan-Meier survival curve visualized the discrimination of the signature on overall survival (OS). The area under the curve (AUC) and C-index were used to verify the predictive accuracy of the signature. Combined with clinical data, multivariate survival analysis was used to reveal the independent predictive capability of the signature. In addition, a prognostic nomogram was constructed. Finally, the common target genes of 4 lncRNAs were predicted by the co-expression method, and the corresponding functions were annotated by GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was also performed to explore the potential mechanism of the signature. Quantitative real-time PCR was used to evaluated the expression of 4 lncRNAs in an independent cohort. RESULTS: We identified and constructed a 4-lncRNA (AC138430.1, AGAP2-AS1, AP001783.1, and AP005233.2) prognostic signature using regression analysis, and it had the capability to independently predict prognosis. The AUCs were 0.952, 0.909, and 0.882 at 1, 2, and 3 years, respectively, and the C-index was 0.808, which showed good predictive capability. Subsequently, combined with clinical data, we constructed a nomogram with good clinical application. Finally, 252 target genes of all four lncRNAs were identified by the co-expression method, and functional enrichment analysis showed that the signature was strongly correlated with metabolism-related mechanisms in tumourigenesis. The same results were also validated via GSEA. CONCLUSION: We demonstrated that a metabolism-related 4-lncRNA prognostic signature could be a novel biomarker and deeply explored the target genes and potential mechanism. This study will provide a promising therapeutic strategy for patients with intrahepatic cholangiocarcinoma.

Identification of the immune cell infiltration landscape in pancreatic cancer to assist immunotherapy.

Background: A malignant tumor's immune environment, including infiltrating immune cell status, can be critical to patient outcomes. Recent studies have shown that immune cell infiltration (ICI) in pancreatic cancer (PC) is highly correlated with the response to immunotherapy and patient prognosis. Therefore, we aimed to create an ICI score that accurately predicts patient outcomes and immunotherapeutic efficacy. Methods: The ICI statuses of patients with PC were estimated from the publicly available The Cancer Genome Atlas (TCGA) pancreatic ductal adenocarcinoma and GSE57495 gene expression datasets using two computational algorithms (CIBERSORT and ESTIMATE). ICI and transcriptome subsets were defined using a clustering algorithm, and survival analysis was also performed. Principal component analysis was used to calculate the novel ICI score, and gene set enrichment analysis was performed to identify the pathways underlying the defined clusters. The tumor mutational burden (TMB) was further explored in TCGA cohort, and survival analysis was used to assess the capability of the ICI and TMB scores to predict overall survival. Additionally, common driver gene mutations and their differential expression in the different ICI score group were investigated. Results: The ICI landscapes of 240 patients were generated using the devised algorithm, revealing three ICI and three gene clusters whose use improved the prediction of overall survival (p = 0.019 and p < 0.001, respectively). Crucial immune checkpoint genes were differentially expressed among these subtypes; the RIG-I-LIKE and NOD-LIKE receptor signaling pathways were enriched in samples with low ICI scores (p < 0.05). We also found that the TMB scores could predict survival outcomes, whereas the ICI scores also could predict prognoses independent of TMB. Notably, ICI scores could effectively predict responses to immunotherapy. KRAS, TP53, CDKN2A, SMAD4 and TTN remained the most commonly mutated genes in PC; moreover, KRAS and TP53 mutation rates were significantly different between the two ICI score groups. Conclusions: We developed a novel ICI score that could independently predict the response to immunotherapy and survival of patients with PC. Evaluation of the ICI landscape in a larger cohort could clarify the interactions between these infiltrating cells, the tumor microenvironment and response to immunotherapy.

Lay abstract Pancreatic cancer (PC) is a lethal malignancy with a higher mortality rate. Currently, immunotherapy is increasingly interesting to clinical researchers and considered a novel and efficient treatment. However, in clinical practice, immunotherapy has not demonstrated consistent therapeutic responses across all patients. Thus, to identify the immunotherapy-sensitive subgroup of advanced PC patients is important based on immune cell infiltration. In this study, we downloaded and processed transcriptomic data from TCGA-PAAD and GEO databases and used CIBERSORT and ESTIMATE algorithms to reveal the immune cell infiltration landscape of pancreatic cancer. According to consensus clustering results, we identified three ICI and gene clusters for guiding the identification of immune-subtype in future clinical treatments. Finally, we calculated an ICI score for each subject to describe their tumor immune landscape and performed the risk grouping for all patients and multiomics analysis. In sum, the ICI score and clusters could be used in the future to assist clinicians in identifying patients with the greatest chance of responding to immunotherapy.

Natural Disasters, Social Protection, and Risk Perceptions.

Natural disasters give rise to loss and damage and may affect subjective expectations about the prevalence and severity of future disasters. These expectations might then in turn shape individuals' investment behaviors, potentially affecting their incomes in subsequent years. As part of an emerging literature on endogenous preferences, economists have begun studying the consequences that exposure to natural disasters have on risk attitudes, perceptions, and behavior. We add to this field by studying the impact of being struck by the December 2012 Cyclone Evan on Fijian households' risk attitudes and subjective expectations about the likelihood and severity of natural disasters over the next 20 years. The randomness of the cyclone's path allows us to estimate the causal effects of exposure on both risk attitudes and risk perceptions. Our results show that being struck by an extreme event substantially changes individuals' risk perceptions as well as their beliefs about the frequency and magnitude of future shocks. However, we find sharply distinct results for the two ethnicities in our sample, indigenous Fijians and Indo-Fijians; the impact of the natural disaster aligns with previous results in the literature on risk attitudes and risk perceptions for Indo-Fijians, whereas they have little to no impact on those same measures for indigenous Fijians. To provide welfare implications for our results, we compare households' risk perceptions to climate and hydrological models of future disaster risk, and find that both ethnic groups over-infer the risk of future disasters relative to the model predictions. If such distorted beliefs encourage over-investment in preventative measures at the cost of other productive investments, these biases could have negative welfare impacts. Understanding belief biases and how they vary across social contexts may thus help decision makers design policy instruments to reduce such inefficiencies, particularly in the face of climate change.

Rapid Analysis of the Quality of Amoxicillin and Clavulanate Potassium Tablets Using Diffuse Reflectance Near-Infrared Spectroscopy.

The cycle-closed dimer of amoxicillin influences its critical quality and is an important impurity in amoxicillin and clavulanate potassium tablets. The quality of the tablets could be rapidly evaluated using the impurity as an indicator. Here, we report a quantitative model to determine the cycle-closed dimer in samples from different manufacturers using diffuse reflectance near-infrared (NIR) spectroscopy by partial least squares regression for one y variable (PLS1) and hierarchical cluster analysis. Because the contents of the (active pharmaceutical ingredients) APIs (amoxicillin and clavulanate potassium) and water are also the important indexes of the tablet quality, three other quantitative models were used to confirm the API data and water content. All of the four models facilitate rapid and complete control of the tablet quality. In addition, quantitative models were validated in terms of specificity, linearity, accuracy, repeatability, and intermediate precision according to the International Conference on Harmonisation guidelines by evaluating the characteristics of the NIR spectra. These results confirmed that the models were satisfactory.

[Update of near-infrared models for testing ceftazidime, water and arginine in ceftazidime for injection].

UNLABELLED: To find a more reasonable index to decide whether the universal quantitative NIR model needs to be updated and to develop a general method to update universal quantitative NIR models, the quantitative models for testing ceftazidime, water and arginine contents in ceftazidime for injection were taken as example. The study was performed by analyzing the similarity between new sample spectra and the training set spectra of the original models. At first, new samples of ceftazidime for injection were divided into five groups by cluster analysis. Then representative samples of each group were selected by sample selection strategy. Spectra of those samples were used to update the original quantitative models. The prediction deviation of the new ceftazidime powder injection samples by the models before and after updating was calculated. Decreasing the prediction deviation was regarded as the standard to decide if the updating was effective. At the same time, the correlation coefficient of new sample spectra and reference sample spectra was defined as the index to study the general method for model updating. (Reference sample refers to training set sample) Finally, the proposed method was validated by updating universal models for testing ceftazidime, water and arginine contents in ceftazidime powder injections. Results show that the correlation coefficient of new sample spectra and training set sample spectra of the original model was calculated within modeling wavelength range. It was proved that when correlation coefficient rT < 96.5%, the model needs to be updated. Accordingly, rT = 96.5% was set as the threshold. The quantitative models were updated by the method mentioned above. As a result, when testing ceftazidime for injection containing sodium carbonate using newly updated models, the average predicting deviation of ceftazidime contents decreased from 8.1% to 2.3%. And the average predicting deviation of water contents decreased from 2.2% to 0.3%. Meanwhile, with regard to samples containing arginine using the updated models, the average predicting deviation of ceftazidime contents decreased from 7.0% to 1.9%. The average predicting deviation of water contents decreased from 0.6% to 0.3%. And that of arginine contents de- creased from 2.3% to 0.4%. CONCLUSION: The newly updated models can be used for testing ceftazidime, water and arginine contens in ceftazidime for injection samples of domestic market. It is reasonable to set rT as the index to decide whether the model needs updating. Moreover, it is necessary to take PCA scores graph of new sample spectra and training set spectra of the original model into account. The proposed method for updating models can be used as a usual approach. And rT = 96.5% can be set as the threshold to determine whether the model needs to be updated.

Ultrasound-guided percutaneous high-frequency irreversible electroporation in porcine livers using four electrode needles: A feasibility and safety study.

BACKGROUND: Malignant liver tumors seriously endanger human health. Among different therapeutic approaches, high-frequency irreversible electroporation (H-FIRE) is a recently emerging tumor ablation technique. The objective of this study was to evaluate the feasibility and safety of ultrasound-guided percutaneous H-FIRE using four electrode needles in porcine livers. METHODS: Twelve experimental pigs underwent percutaneous H-FIRE ablation using a compound steep-pulse therapeutic device. Liver tissues adjacent to the gallbladder, blood vessels, and bile ducts were selected as the ablation targets. Pigs were randomly divided into three groups: (1) immediately after ablation (N = 4), (2) 2 days after ablation (N = 4), and (3) 7 days after ablation (N = 4). Blood routine, liver and kidney function, and myocardial enzyme levels were measured before and after ablation. Ultrasound, contrast-enhanced ultrasound (CEUS), contrast-enhanced magnetic resonance imaging (MRI), and hematoxylin-eosin staining were performed to evaluate the ablation performance. RESULTS: Ultrasound-guided percutaneous H-FIRE ablations using four electrode needles were successfully performed in all 12 experimental pigs. The general conditions of the pigs, including postoperative activities and feeding behaviors, were normal, with no significant changes compared with the preoperative conditions. The imaging features of ultrasound, CEUS, and MRI demonstrated no significant changes in the gallbladder walls, bile ducts, or blood vessels close to the ablation areas. Laboratory tests showed that liver function indices and myocardial enzymes increased temporarily after H-FIRE ablation, but decreased to normal levels at 7 days after ablation. Histopathological examinations of porcine liver specimens showed that this technique could effectively ablate the target areas without damaging the surrounding or internal vascular systems and gallbladder. CONCLUSIONS: This study demonstrated the feasibility and safety of ultrasound-guided percutaneous H-FIRE ablation in porcine livers in vivo, and proposed a four-needle method to optimize its clinical application.

Homocysteine levels are associated with diabetes mellitus in Chinese with H-type hypertension.

BACKGROUND/OBJECTIVES: The study examined the association between homocysteine and diabetes mellitus in patients with H-type hypertension and assessed the possible effect modifiers. SUBJECTS/METHODS: This cross-sectional study included 1,255 eligible participants in the 'H-type Hypertension Management and Stroke Prevention Strategic International Science and Technology Innovation Cooperation Project' among rural Chinese people with H-type hypertension. A multivariate logistic regression model was used to evaluate the relationship between homocysteine and diabetes mellitus. RESULTS: The mean level of total homocysteine (tHcy) in the diabetes mellitus population was 19.37 µmol/L, which was significantly higher than the non-diabetic patients (18.18 µmol/L). When tHcy was analyzed as a continuous variable, the odds ratio (OR) of diabetes was 1.17 (95% confidence interval [CI], 1.01-1.35; per interquartile range). When tHcy was stratified according to the quintile, the ORs for diabetes were 2.86 (95% CI, 1.22-6.69) in the highest quintile (tHcy ≥ 20.60 µmol/L) compared to the reference group (tHcy < 12.04 µmol/L). When tHcy was grouped by 15 µmol/L and 20 µmol/L, patients with tHcy ≥ 20 µmol/L had a significantly (P = 0.037) higher risk of diabetes (OR, 2.03; 95% CI, 1.04-3.96) than in those with tHcy < 15 µmol/L. Subgroup analysis showed that the tHcy-diabetes association was unaffected by other variables. CONCLUSION: In this study of rural Chinese people with H-type hypertension, the tHcy levels showed a positive association with diabetes mellitus. This independent association is unaffected by other potential risk factors.

The heterogeneity of cellular metabolism in the tumour microenvironment of hepatocellular carcinoma with portal vein tumour thrombus.

Given the growing interest in the metabolic heterogeneity of hepatocellular carcinoma (HCC) and portal vein tumour thrombus (PVTT). This study comprehensively analysed the metabolic heterogeneity of HCC, PVTT, and normal liver samples using multi-omics combinations. A single-cell RNA sequencing dataset encompassing six major cell types was obtained for integrated analysis. The optimal subtypes were identified using cluster stratification and validated using spatial transcriptomics and fluorescent multiplex immunohistochemistry. Then, a combined index based meta-cluster was calculated to verify its prognostic significance using multi-omics data from public cohorts. Our study first depicted the metabolic heterogeneity landscape of non-malignant cells in HCC and PVTT at multiomics levels. The optimal subtypes interpret the metabolic characteristics of PVTT formation and development. The combined index provided effective predictions of prognosis and immunotherapy responses. Patients with a higher combined index had a relatively poor prognosis (p <0.001). We also found metabolism of polyamines was a key metabolic pathway involved in conversion of metabolic heterogeneity in HCC and PVTT, and identified ODC1 was significantly higher expressed in PVTT compared to normal tissue (p =0.03). Our findings revealed both consistency and heterogeneity in the metabolism of non-malignant cells in HCC and PVTT. The risk stratification based on cancer-associated fibroblasts and myeloid cells conduce to predict prognosis and guide treatment. This offers new directions for understanding disease development and immunotherapy responses.

Ingroup bias in a social learning experiment.

Does social learning and subsequent private information processing differ depending on whether the observer shares the same group identity as the predecessor whose action is observed? In this paper, we conduct a lab experiment to answer this question, in which subjects first observe a social signal and then receive a private signal. We find that subjects put greater weights on the social signal if they share with the predecessor the same group identity that is induced in the experimental environment. We also provide suggestive evidence that such an ingroup-outgroup difference cannot be explained by individuals' beliefs of the predecessor's rationality. Moreover, heterogeneous effects of group identity exist in weights given to the subsequent private signal: Compared to when the predecessor is an outgroup, those who have learned from an ingroup predecessor put a greater (smaller) weight on the private signal if it contradicts (confirms) the social signal. We conjecture that such group effects are consistent with the perspective that group identity works as a framing device and brings about certain decision heuristics in the social signal phase, which no longer exist in the private signal phase. Supplementary Information: The online version contains supplementary material available at 10.1007/s10683-022-09788-1.

Characterization of enteric-coated erythromycin tablets by Raman mapping and its pharmaceutical evaluation.

Enteric tablet coating thickness is a critical quality attribute of the coating process that can affect dissolution behavior in vitro as well as release in vivo. Raman mapping offers unique advantages in analyzing the distribution of active pharmaceutical ingredients and excipients in formulations. In this study, Raman mapping was used to characterize the coating of enteric-coated erythromycin tablets coated by two different processes and compare the differences in their coating formulation, thickness, and uniformity. Furthermore, we aimed to select the appropriate pH of the dissolution medium at which the coating slowly cracks to release the drug and determine the dissolution profile. The differences in the coating thickness and uniformity of the two products resulted in differences in dissolution behavior. Although there are differences in the coating processes for the two types of enteric-coated erythromycin tablets, the thickness of the outer coating on the side is a critical quality attribute in both processes. The outer coating of product A is relatively thick, and the thickness of the outer coating on the side affects the dissolution amount. The outer coating of product B is relatively thin, resulting in a short cracking time and large variation and a significant difference in the initial dissolution amounts between tablets. Raman mapping can be used to analyze the differences in coating formulations and for process evaluation.