Prediction of carbapenem-resistant gram-negative bacterial bloodstream infection in intensive care unit based on machine learning.

BACKGROUND: Predicting whether Carbapenem-Resistant Gram-Negative Bacterial (CRGNB) cause bloodstream infection when giving advice may guide the use of antibiotics because it takes 2-5 days conventionally to return the results from doctor's order. METHODS: It is a regional multi-center retrospective study in which patients with suspected bloodstream infections were divided into a positive and negative culture group. According to the positive results, patients were divided into the CRGNB group and other groups. We used the machine learning algorithm to predict whether the blood culture was positive and whether the pathogen was CRGNB once giving the order of blood culture. RESULTS: There were 952 patients with positive blood cultures, 418 patients in the CRGNB group, 534 in the non-CRGNB group, and 1422 with negative blood cultures. Mechanical ventilation, invasive catheterization, and carbapenem use history were the main high-risk factors for CRGNB bloodstream infection. The random forest model has the best prediction ability, with AUROC being 0.86, followed by the XGBoost prediction model in bloodstream infection prediction. In the CRGNB prediction model analysis, the SVM and random forest model have higher area under the receiver operating characteristic curves, which are 0.88 and 0.87, respectively. CONCLUSIONS: The machine learning algorithm can accurately predict the occurrence of ICU-acquired bloodstream infection and identify whether CRGNB causes it once giving the order of blood culture.

Hemolytic Properties of Fine Particulate Matter (PM2.5) in In Vitro Systems.

Epidemiological studies have suggested that inhalation exposure to particulate matter (PM) air pollution, especially fine particles (i.e., PM2.5 (PM with an aerodynamic diameter of 2.5 microns or less)), is causally associated with cardiovascular health risks. To explore the toxicological mechanisms behind the observed adverse health effects, the hemolytic activity of PM2.5 samples collected during different pollution levels in Beijing was evaluated. The results demonstrated that the hemolysis of PM2.5 ranged from 1.98% to 7.75% and demonstrated a clear dose-response relationship. The exposure toxicity index (TI) is proposed to represent the toxicity potential of PM2.5, which is calculated by the hemolysis percentage of erythrocytes (red blood cells, RBC) multiplied by the mass concentration of PM2.5. In a pollution episode, as the mass concentration increases, TI first increases and then decreases, that is, TI (low pollution levels) < TI (heavy pollution levels) < TI (medium pollution levels). In order to verify the feasibility of the hemolysis method for PM toxicity detection, the hemolytic properties of PM2.5 were compared with the plasmid scission assay (PSA). The hemolysis results had a significant positive correlation with the DNA damage percentages, indicating that the hemolysis assay is feasible for the detection of PM2.5 toxicity, thus providing more corroborating information regarding the risk to human cardiovascular health.

CAV3 alleviates diabetic cardiomyopathy via inhibiting NDUFA10-mediated mitochondrial dysfunction.

BACKGROUND: The progression of diabetic cardiomyopathy (DCM) is noticeably influenced by mitochondrial dysfunction. Variants of caveolin 3 (CAV3) play important roles in cardiovascular diseases. However, the potential roles of CAV3 in mitochondrial function in DCM and the related mechanisms have not yet been elucidated. METHODS: Cardiomyocytes were cultured under high-glucose and high-fat (HGHF) conditions in vitro, and db/db mice were employed as a diabetes model in vivo. To investigate the role of CAV3 in DCM and to elucidate the molecular mechanisms underlying its involvement in mitochondrial function, we conducted Liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis and functional experiments. RESULTS: Our findings demonstrated significant downregulation of CAV3 in the cardiac tissue of db/db mice, which was found to be associated with cardiomyocyte apoptosis in DCM. Importantly, cardiac-specific overexpression of CAV3 effectively inhibited the progression of DCM, as it protected against cardiac dysfunction and cardiac remodeling associated by alleviating cardiomyocyte mitochondrial dysfunction. Furthermore, mass spectrometry analysis and immunoprecipitation assays indicated that CAV3 interacted with NDUFA10, a subunit of mitochondrial complex I. CAV3 overexpression reduced the degradation of lysosomal pathway in NDUFA10, restored the activity of mitochondrial complex I and improved mitochondrial function. Finally, our study demonstrated that CAV3 overexpression restored mitochondrial function and subsequently alleviated DCM partially through NDUFA10. CONCLUSIONS: The current study provides evidence that CAV3 expression is significantly downregulated in DCM. Upregulation of CAV3 interacts with NDUFA10, inhibits the degradation of lysosomal pathway in NDUFA10, a subunit of mitochondrial complex I, restores the activity of mitochondrial complex I, ameliorates mitochondrial dysfunction, and thereby protects against DCM. These findings indicate that targeting CAV3 may be a promising approach for the treatment of DCM.

An Infant-Type Hemispheric Glioma With SOX5::ALK: A Novel Fusion.

Infant-type hemispheric glioma (IHG) is a rare pediatric brain tumor with variable response to chemotherapy and radiotherapy. Molecular insights into IHG can be useful in identifying potentially active targeted therapy. A male fetus was found to have congenital hydrocephalus at the gestational age of 37 weeks. Fetal MRI showed a 2.6 × 2.0-cm tumor located at the frontal horn of the left lateral ventricle, involving the left basal nuclei and thalamus. Tumor biopsy at the age of 2 days revealed an IHG consisting of spindle tumor cells with strong expression of GFAP and ALK. Targeted RNA sequencing detected a novel fusion gene of SOX5::ALK. After initial chemotherapy with cyclophosphamide, carboplatin, and etoposide for 2 cycles, the tumor size progressed markedly and the patient underwent a subtotal resection of brain tumor followed by treatment with lorlatinib, an ALK tyrosine kinase inhibitor with central nervous system (CNS) activity. After 3 months of treatment, reduction of tumor size was observed. After 14 months of treatment, partial response was achieved, and the infant had normal growth and development. In conclusion, we identified a case of congenital IHG with a novel SOX5::ALK fusion that had progressed after chemotherapy and showed partial response and clinical benefit after treatment with the CNS-active ALK inhibitor lorlatinib.

Crucial computed tomography and magnetic resonance imaging findings of fallopian tubal tuberculosis for diagnosis: a retrospective study of 26 cases.

Background: Fallopian tubal tuberculosis (FTTB), which typically presents with non-specific clinical symptoms and mimics ovarian malignancies clinically and radiologically, often affects young reproductive females and can lead to infertility if not promptly managed. Early diagnosis by imaging modalities is crucial for initiating timely anti-tuberculosis (anti-TB) treatment. Currently, comprehensive radiological descriptions of this relatively rare disease are limited. We aimed to comprehensively investigate the computed tomography (CT) and magnetic resonance imaging (MRI) characteristics of FTTB in patients from the Kashi area, which has the highest incidence of TB in China, to extend radiologists' understanding of this disease. Methods: We conducted a retrospective cross-sectional study of 26 patients diagnosed with FTTB at the First People's Hospital of Kashi Area. All the patients underwent abdominal and pelvic contrast-enhanced CT examinations and/or pelvic contrast-enhanced MRI from January 2017 to June 2022. The imaging findings were evaluated in consensus by two experienced radiologists specialized in abdominal and pelvic imaging. The evaluated sites included the fallopian tubes, ovaries, peritoneum, mesentery, retroperitoneal nodes, and parailiac nodes. The patient characteristics are reported using descriptive statistics. The patient imaging results are presented as percentages. The normally distributed continuous variables are reported as the mean ± standard deviation (SD), and otherwise as the median with the interquartile range (IQR). Results: The median age of the patients was 27 years (IQR: 25-34 years). Bilateral involvement of the fallopian tubes was observed in all patients. The tubal wall appeared coarse with tiny intraductal nodules in 96% (25 of 26) of the patients. The mean CT value of the tubal contents was 34 Hounsfield units (HUs; SD: 3.3 HUs). Ascites was present in 92% (24 of 26) of the patients, with 20 patients showing encapsulated effusion. Among these patients, 20 exhibited the highest CT values of ascites (>20 HUs). Linear enhancement of the parietal peritoneum was observed in 88% (23 of 26) of the patients, of whom 22 had peritoneal nodules measuring a median diameter of 0.4 cm (IQR: 0.3-0.6 cm). Eight patients had retroperitoneal and parailiac nodal enlargement, of whom two showed nodal necrosis, and none displayed nodal calcification. Conclusions: FTTB is consistently accompanied by tuberculous peritonitis. FTTB typically presents with tubal dilation, and coarseness and nodules in the lumen, as well as intraductal caseous material and calcification. Tuberculous peritonitis exhibits high-density ascites, peritoneal adhesion, linear enhancement of the parietal peritoneum, and tiny peritoneal nodules. The co-occurrence of these features strongly suggests a diagnosis of FTTB.

Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning.

BACKGROUND: Predicting the successful weaning of acute kidney injury (AKI) patients from renal replacement therapy (RRT) has emerged as a research focus, and we successfully built predictive models for RRT withdrawal in patients with severe AKI by machine learning. METHODS: This retrospective single-center study utilized data from our general intensive care unit (ICU) Database, focusing on patients diagnosed with severe AKI who underwent RRT. We evaluated RRT weaning success based on patients being free of RRT in the subsequent week and their overall survival. Multiple logistic regression (MLR) and machine learning algorithms were adopted to construct the prediction models. RESULTS: A total of 976 patients were included, with 349 patients successfully weaned off RRT. Longer RRT duration (7.0 vs. 9.6 d, p = 0.002, OR = 0.94), higher serum cystatin C levels (1.2 vs. 3.2 mg/L, p < 0.001, OR = 0.46), and the presence of septic shock (28.1% vs. 41.5%, p < 0.001, OR = 0.63) were associated with reduced likelihood of RRT weaning. Conversely, a positive furosemide stress test (FST) (60.2% vs. 40.7%, p < 0.001, OR = 2.75) and higher total urine volume 3 d before RRT withdrawal (755 vs. 125 mL/d, p < 0.001, OR = 2.12) were associated with an increased likelihood of successful weaning from RRT. Next, we demonstrated that machine learning models, especially Random Forest and XGBoost, achieving an AUROC of 0.95. The XGBoost model exhibited superior accuracy, yielding an AUROC of 0.849. CONCLUSION: High-risk factors for unsuccessful RRT weaning in severe AKI patients include prolonged RRT duration. Machine learning prediction models, when compared to models based on multivariate logistic regression using these indicators, offer distinct advantages in predictive accuracy.

Prevalence and clinical significance of potential drug-drug interactions among lung transplant patients.

Background: Drug-drug interactions (DDIs) are a major but preventable cause of adverse drug reactions. There is insufficient information regarding DDIs in lung transplant recipients. Objective: This study aimed to determine the prevalence of potential DDIs (pDDIs) in intensive care unit (ICU) lung transplant recipients, identify the real DDIs and the most frequently implicated medications in this vulnerable population, and determine the risk factors associated with pDDIs. Methods: This retrospective cross-sectional study included lung transplant recipients from January 2018 to December 2021. Pertinent information was retrieved from medical records. All prescribed medications were screened for pDDIs using the Lexicomp® drug interaction software. According to this interaction software, pDDIs were classified as C, D, or X (C = monitor therapy, D = consider therapy modification, X = avoid combination). The Drug Interaction Probability Scale was used to determine the causation of DDIs. All statistical analysis was performed in SPSS version 26.0. Results: 114 patients were qualified for pDDI analysis, and total pDDIs were 4051. The most common type of pDDIs was category C (3323; 82.0%), followed by D (653; 16.1%) and X (75; 1.9%). Voriconazole and posaconazole were the antifungal medicine with the most genuine DDIs. Mean tacrolimus concentration/dose (Tac C/D) before or after co-therapy was considerably lower than the Tac C/D during voriconazole or posaconazole co-therapy (p < 0.001, p = 0.027). Real DDIs caused adverse drug events (ADEs) in 20 patients. Multivariable logistic regression analyses found the number of drugs per patient (OR, 1.095; 95% CI, 1.048-1.145; p < 0.001) and the Acute Physiology and Chronic Health Evaluation II (APACHE Ⅱ) score (OR, 1.097; 95% CI, 1.021-1.179; p = 0.012) as independent risk factors predicting category X pDDIs. Conclusion: This study revealed a high incidence of both potential and real DDIs in ICU lung transplant recipients. Immunosuppressive drugs administered with azole had a high risk of causing clinically significant interactions. The number of co-administered drugs and APACHE Ⅱ score were associated with an increased risk of category × drug interactions. Close monitoring of clinical and laboratory parameters is essential for ensuring successful lung transplantation and preventing adverse drug events associated with DDIs.

Intensive care unit-acquired weakness: Recent insights.

Intensive care unit-acquired weakness (ICU-AW) is a common complication in critically ill patients and is associated with a variety of adverse outcomes. These include the need for prolonged mechanical ventilation and ICU stay; higher ICU, in-hospital, and 1-year mortality; and increased in-hospital costs. ICU-AW is associated with multiple risk factors including age, underlying disease, severity of illness, organ failure, sepsis, immobilization, receipt of mechanical ventilation, and other factors related to critical care. The pathological mechanism of ICU-AW remains unclear and may be considerably varied. This review aimed to evaluate recent insights into ICU-AW from several aspects including risk factors, pathophysiology, diagnosis, and treatment strategies; this provides new perspectives for future research.

A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study.

Background: Septic shock is a severe life-threatening disease, and the mortality of septic shock in China was approximately 37.3% that lacks prognostic prediction model. This study aimed to develop and validate a prediction model to predict 28-day mortality for Chinese patients with septic shock. Methods: This retrospective cohort study enrolled patients from Intensive Care Unit (ICU) of the Second Affiliated Hospital, School of Medicine, Zhejiang University between December 2020 and September 2021. We collected patients' clinical data: demographic data and physical condition data on admission, laboratory data on admission and treatment method. Patients were randomly divided into training and testing sets in a ratio of 7:3. Univariate logistic regression was adopted to screen for potential predictors, and stepwise regression was further used to screen for predictors in the training set. Prediction model was constructed based on these predictors. A dynamic nomogram was performed based on the results of prediction model. Using receiver operator characteristic (ROC) curve to assess predicting performance of dynamic nomogram, which were compared with Sepsis Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) systems. Results: A total of 304 patients with septic shock were included, with a 28-day mortality of 25.66%. Systolic blood pressure, cerebrovascular disease, Na, oxygenation index (PaO2/FiO2), prothrombin time, glucocorticoids, and hemodialysis were identified as predictors for 28-day mortality in septic shock patients, which were combined to construct the predictive model. A dynamic nomogram (https://zhijunxu.shinyapps.io/DynNomapp/) was developed. The dynamic nomogram model showed a good discrimination with area under the ROC curve of 0.829 in the training set and 0.825 in the testing set. Additionally, the study suggested that the dynamic nomogram has a good predictive value than SOFA and APACHE II. Conclusion: The dynamic nomogram for predicting 28-day mortality in Chinese patients with septic shock may help physicians to assess patient survival and optimize personalized treatment strategies for septic shock.

Complete pathway elucidation and heterologous reconstitution of (+)-nootkatone biosynthesis from Alpinia oxyphylla.

(+)-Nootkatone is a natural sesquiterpene ketone widely used in food, cosmetics, pharmaceuticals, and agriculture. It is also regarded as one of the most valuable terpenes used commercially. However, plants contain trace amounts of (+)-nootkatone, and extraction from plants is insufficient to meet market demand. Alpinia oxyphylla is a well-known medicinal plant in China, and (+)-nootkatone is one of the main components within the fruits. By transcriptome mining and functional screening using a precursor-providing yeast chassis, the complete (+)-nootkatone biosynthetic pathway in Alpinia oxyphylla was identified. A (+)-valencene synthase (AoVS) was identified as a novel monocot-derived valencene synthase; three (+)-valencene oxidases AoCYP6 (CYP71BB2), AoCYP9 (CYP71CX8), and AoCYP18 (CYP701A170) were identified by constructing a valencene-providing yeast strain. With further characterisation of a cytochrome P450 reductase (AoCPR1) and three dehydrogenases (AoSDR1/2/3), we successfully reconstructed the (+)-nootkatone biosynthetic pathway in Saccharomyces cerevisiae, representing a basis for its biotechnological production. Identifying the biosynthetic pathway of (+)-nootkatone in A. oxyphylla unravelled the molecular mechanism underlying its formation in planta and also supported the bioengineering production of (+)-nootkatone. The highly efficient yeast chassis screening method could be used to elucidate the complete biosynthetic pathway of other valuable plant natural products in future.

Laser Synthesis of PtMo Single-Atom Alloy Electrode for Ultralow Voltage Hydrogen Generation.

Maximizing atom-utilization efficiency and high current stability are crucial for the platinum (Pt)-based electrocatalysts for hydrogen evolution reaction (HER). Herein, the Pt single-atom anchored molybdenum (Mo) foil (Pt-SA/Mo-L) as a single-atom alloy electrode is synthesized by the laser ablation strategy. The local thermal effect with fast rising-cooling rate of laser can achieve the single-atom distribution of the precious metals (e.g., Pt, Rh, Ir, and Ru) onto the Mo foil. The synthesized self-standing Pt-SA/Mo-L electrode exhibits splendid catalytic activity (31 mV at 10 mA cm-2 ) and high-current-density stability (≈850 mA cm-2 for 50 h) for HER in acidic media. The strong coordination of Pt-Mo bonding in Pt-SA/Mo-L is critical for the efficient and stable HER. In addition, the ultralow electrolytic voltage of 0.598 V to afford the current density of 50 mA cm-2 is realized by utilization of the anodic molybdenum oxidation instead of the oxygen evolution reaction (OER). Here a universal synthetic strategy of single-atom alloys (PtMo, RhMo, IrMo, and RuMo) as self-standing electrodes is provided for ultralow voltage and membrane-free hydrogen production.

Chasing the landscape for intrahospital transmission and evolution of hypervirulent carbapenem-resistant Klebsiella pneumoniae.

The spread of hypervirulent carbapenem-resistant Klebsiella pneumoniae (Hv-CRKP) is a global health concern. Here, we report the intrahospital colonization and spread of Hv-CRKP isolates in a tertiary hospital from 2017 to 2022. Analyses of 90 nonredundant CRKP isolates from 72 patients indicated that Hv-CRKP transferability relies on the dominant ST11-K64 clone. Whole-genome sequencing of 11 representative isolates gave 31 complete plasmid sequences, including 12 KPC-2 resistance carriers and 10 RmpA virulence vehicles. Apart from the binary vehicles, we detected two types of fusion plasmids, favoring the cotransfer of RmpA virulence and KPC-2 resistance. The detection of ancestry/relic plasmids enabled us to establish genetic mechanisms by which rare fusion plasmids form. Unexpectedly, we found a total of five rmpA promoter variants (P9T-P13T) exhibiting distinct activities and varying markedly in their geographic distributions. CRISPR/Cas9 manipulation confirmed that an active PT11-rmpA regulator is a biomarker for the "high-risk" ST11-K64/CRKP clone. These findings suggest clonal spread and clinical evolution of the prevalent ST11-K64/Hv-CRKP clones. Apart from improved public awareness of Hv-CRKP convergence, our findings might benefit the development of surveillance (and/or intervention) strategies for the dominant ST11-K64 lineage of the Hv-CRKP population in healthcare sectors.

Electroencephalogram pattern predicting neurological outcomes of children with seizures secondary to abusive head trauma.

BACKGROUND: The clinical presentations of abusive head trauma can abruptly worsen, so the occurrence of seizures and changes of EEG can be variable according to patients' conditions. Since the changes of EEG background waves reflect the cortical function of children, we aimed to find out whether the timing of EEG background, epileptiform discharges and seizure patterns were associated with the outcomes of patients with AHT. MATERIAL AND METHODS: Using seizure type and acute stage electroencephalographic (EEG) characteristics to assess adverse neurological outcomes in children with seizures secondary to abusive head trauma (AHT). Children who were hospitalized with AHT at a tertiary referral hospital from October 2000 to April 2010 were evaluated retrospectively. A total of 50 children below 6 years of age admitted due to AHT were included. KOSCHI outcome scale was used to evaluate the primary outcome and neurological impairment was used as secondary outcome after 6 months discharge. RESULTS: Children with apnea, cardiac arrest, reverse blood flow and skull fracture in clinic had a higher mortality rate even in the no-seizure group (3/5 [60%] vs. 3/45 [6.7%], odds ratio [OR] = 11; 95% CI = 2.3-52; p = 0.025). Seizure occurrence reduced mostly at the second day after admission in seizure groups; but children with persistent seizures for 1 week showed poor neurological outcomes. The occurrence of initial seizure was frequency associated with younger age; focal seizure, diffuse cortical dysfunction in acute-stage EEG, and low Glasgow Coma Scale (GCS) score were significantly related to poor outcomes after 6 months. Diffuse cortical dysfunction was also associated with motor, speech, and cognitive dysfunction. CONCLUSIONS: Diffuse cortical dysfunction in acute-stage EEG combined with low GCS score and focal seizure may related to poor outcomes and neurological dysfunctions in children with AHT.

Sensitive detection of microRNA by dynamic light scattering based on DNAzyme walker-mediated AuNPs self-assembly.

As an important biomarker, microRNAs (miRNAs) play an important role in gene expression, and their detection has attracted increasing attention. In this study, a DNAzyme walker that could provide power to perform autonomous movement was designed. Based on the continuous mechanical motion characteristics of DNAzyme walker, a miRNA detection strategy for the self-assembly of AuNPs induced by the hairpin probe-guided DNAzyme walker "enzyme cleavage and walk" was established. In this strategy, DNAzyme walker continuously cleaved and walked on the hairpin probe on the surface of AuNPs to induce the continuous shedding of some segments of the hairpin probe. The remaining hairpin sequences on the surface of the AuNP pair with each other, causing the nanoparticles to self-assemble. This strategy uses the autonomous movement mechanism of DNAzyme walker to improve reaction efficiency and avoid the problem of using expensive and easily degradable proteases. Secondly, using dynamic light scattering technology as the signal output system, ultra-sensitive detection with a detection limit of 3.6 fM is achieved. In addition, this strategy has been successfully used to analyze target miRNAs in cancer cell samples.

Lentinan alleviates diabetic cardiomyopathy by suppressing CAV1/SDHA-regulated mitochondrial dysfunction.

Diabetic cardiomyopathy (DCM), characterized by mitochondrial dysfunction and impaired energetics as contributing factors, significantly contributes to high mortality in patients with diabetes. Targeting key proteins involved in mitochondrial dysfunction might offer new therapeutic possibilities for DCM. Lentinan (LNT), a ß-(1,3)-glucan polysaccharide obtained from lentinus edodes, has demonstrated biological activity in modulating metabolic syndrome. In this study, the authors investigate LNT's pharmacological effects on and mechanisms against DCM. The results demonstrate that administering LNT to db/db mice reduces cardiomyocyte apoptosis and mitochondrial dysfunction, thereby preventing DCM. Notably, these effects are fully negated by Caveolin-1 (CAV1) overexpression both in vivo and in vitro. Further studies and bioinformatics analysis uncovered that CAV1 bound with Succinate dehydrogenase subunit A (SDHA), triggering the following ubiquitination and degradation of SDHA, which leads to mitochondrial dysfunction and mitochondria-derived apoptosis under PA condition. Silencing CAV1 leads to reduced apoptosis and improved mitochondrial function, which is blocked by SDHA knockdown. In conclusion, CAV1 directly interacts with SDHA to promote ubiquitination and proteasomal degradation, resulting in mitochondrial dysfunction and mitochondria-derived apoptosis, which was depressed by LNT administration. Therefore, LNT may be a potential pharmacological agent in preventing DCM, and targeting the CAV1/SDHA pathway may be a promising therapeutic approach for DCM.

Expression and functional study of cholecystokinin-A receptors on the interstitial Cajal-like cells of the guinea pig common bile duct.

BACKGROUND: Many studies have shown that interstitial Cajal-like cell (ICLC) abnormalities are closely related to a variety of dynamic gastrointestinal disorders. ICLCs are pacemaker cells for gastrointestinal movement and are involved in the transmission of nerve impulses. AIM: To elucidate the expression profile and significance of cholecystokinin-A (CCK-A) receptors in ICLCs in the common bile duct (CBD), as well as the role of CCK in regulating CBD motility through CCK-A receptors on CBD ICLCs. METHODS: The levels of tyrosine kinase receptor (c-kit) and CCK-A receptors in CBD tissues and isolated CBD cells were quantified using the double immunofluorescence labeling technique. The CCK-mediated enhancement of the movement of CBD muscle strips through CBD ICLCs was observed by a muscle strip contraction test. RESULTS: Immunofluorescence showed co-expression of c-kit and CCK-A receptors in the CBD muscularis layer. Observations of isolated CBD cells showed that c-kit was expressed on the surface of ICLCs, the cell body and synapse were colored and polygonal, and some cells presented protrusions and formed networks adjacent to the CBD while others formed filaments at the synaptic terminals of local cells. CCK-A receptors were also expressed on CBD ICLCs. At concentrations ranging from 10-6 mol/L to 10-10 mol/L, CCK promoted CBD smooth muscle contractility in a dose-dependent manner. In contrast, after ICLC removal, the contractility mediated by CCK in CBD smooth muscle decreased. CONCLUSION: CCK-A receptors are highly expressed on CBD ICLCs, and CCK may regulate CBD motility through the CCK-A receptors on ICLCs.

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures.

Background: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented. Methods: After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism. Results: The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a "Walktrap" algorithm, the community map indicated that the "apoptosis, metabolism, chemotherapy" (Centrality = 12, Density = 6), "lymphoma, pet/ct, prognosis" (Centrality = 11, Density = 1), and "genotoxicity, mutagenicity" (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism. Conclusion: This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.