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Abstract To assess the relationship between acute kidney injury (AKI) with outcomes among patients requiring extracorporeal membrane oxygenation (ECMO). This is a single-center, retrospective cohort study of adult patients admitted to intensive care units (ICU) at a tertiary referral hospital requiring ECMO from July 1, 2015, to August 30, 2019. We assessed the temporal relationship of AKI and renal replacement therapy with ECMO type (VV vs. VA). The primary outcome was in-hospital mortality rates. We used Kruskal–Wallis or chi-square tests for pairwise comparisons, cause-specific Cox proportional hazards models were utilized for the association between AKI prevalence and in-hospital mortality, and a time-dependent Cox model was used to describe the association between AKI incidence and mortality. After the screening, 190 patients met eligibility criteria [133 (70%) AKI, 81 (43%) required RRT]. The median age was 61 years, and 61% were males. Among AKI patients, 48 (36%) and 85 (64%) patients developed AKI before and after ECMO, respectively. The SOFA Day 1, baseline creatinine, respiratory rate (RR), use of vasopressin, vancomycin, proton pump inhibitor, antibiotics, duration of mechanical ventilation and ECMO, and ICU length of stay were higher in AKI patients compared with those without AKI (P

Abstract Background Artificial intelligence (AI) tools are more effective if accepted by clinicians. We developed an AI-based clinical decision support system (CDSS) to facilitate vancomycin dosing. This qualitative study assesses clinicians' perceptions regarding CDSS implementation. Methods Thirteen semi-structured interviews were conducted with critical care pharmacists, at Mayo Clinic (Rochester, MN), from March through April 2020. Eight clinical cases were discussed with each pharmacist (N = 104). Following initial responses, we revealed the CDSS recommendations to assess participants' reactions and feedback. Interviews were audio-recorded, transcribed, and summarized. Results The participants reported considerable time and effort invested daily in individualizing vancomycin therapy for hospitalized patients. Most pharmacists agreed that such a CDSS could favorably affect (N = 8, 62%) or enhance (9, 69%) their ability to make vancomycin dosing decisions. In case-based evaluations, pharmacists' empiric doses differed from the CDSS recommendation in most cases (88/104, 85%). Following revealing the CDSS recommendations, we noted 78% (69/88) discrepant doses. In discrepant cases, pharmacists indicated they would not alter their recommendations. The reasons for declining the CDSS recommendation were general distrust of CDSS, lack of dynamic evaluation and in-depth analysis, inability to integrate all clinical data, and lack of a risk index. Conclusion While pharmacists acknowledged enthusiasm about the advantages of AI-based models to improve drug dosing, they were reluctant to integrate the tool into clinical practice. Additional research is necessary to determine the optimal approach to implementing CDSS at the point of care acceptable to clinicians and effective at improving patient outcomes.

Abstract Purpose Continuous kidney replacement therapy (CKRT) is an increasingly common intervention for critically ill patients with kidney failure. Because CKRT affects body temperature, detecting infections in patients on CKRT is challenging. Understanding the relation between CKRT and body temperature may facilitate earlier detection of infection. Methods We retrospectively reviewed adult patients (≥ 18 years) admitted to the intensive care unit at Mayo Clinic in Rochester, Minnesota, from December 1, 2006, through November 31, 2015, who required CKRT. We summarized central body temperatures for these patients according to the presence or absence of infection. Results We identified 587 patients who underwent CKRT during the study period, of whom 365 had infections, and 222 did not have infections. We observed no statistically significant differences in minimum (P = .70), maximum (P = .22), or mean (P = .55) central body temperature for patients on CKRT with infection vs. those without infection. While not on CKRT (before CKRT initiation and after cessation), all three body temperature measurements were significantly higher in patients with infection than in those without infection (all P

BackgroundThe intensive care unit (ICU) is a department with a high risk of MDR bacteria, and ICU nurses and physicians play critical roles in bacterial multidrug resistance (MDR) prevention.ObjectivesTo explore the knowledge, attitudes, and practice (KAP) towards bacterial MDR among ICU nurses and physicians.MethodsA self-designed questionnaire was administered to collect data. Structural equation modeling (SEM) was applied to assess the associations among study variables.ResultsA total of 369 questionnaires were collected; 43 questionnaires were excluded due to self-contradictory on the trap question or the obviously repeated pattern. Finally, 326 (88.35%) valid questionnaires were included in the analysis. The knowledge, attitudes, and practice were 13.57 ± 1.69 (90.47%, possible range: 0-15), 38.75 ± 2.23 (96.88%, possible range: 8-40), and 47.40 ± 3.59 (94.80%, possible range: 10-50). The SEM showed that knowledge had a direct effect on attitude with a direct effect value of 0.61 (P < 0.001) and a direct negative effect on practice with a direct effect value of -0.30 (P = 0.009). The direct effect of attitude on practice was 0.89 (P < 0.001); the indirect effect of knowledge through attitude on practice was 0.52 (P < 0.001). Job satisfaction had a direct effect on attitude and practice, with an effect value of 0.52 (P = 0.030) and 0.75 (P = 0.040). Being a physician (OR = 0.354, 95%CI: 0.159-0.790, P = 0.011), 5-9.9 years of practice (OR = 4.534, 95%CI: 1.878-8.721, P < 0.001), and ≥ 10 years of practice (OR = 3.369, 95%CI: 1.301-8.721, P = 0.012) were independently associated with good knowledge. The attitude scores (OR = 1.499, 95%CI: 1.227-1.830, P < 0.001), male gender (OR = 0.390, 95%CI: 0.175-0.870, P = 0.022), and 5-9.9 years of experience (OR = 0.373, 95%CI: 0.177-0.787, P = 0.010) were independently associated with proactive practice.ConclusionNurses and physicians in the ICU showed good knowledge, positive attitudes, and proactive practice toward bacterial MDR. Nurses and physicians' knowledge had a direct effect on their attitude, while attitude might directly influence the practice and also play a mediating role between knowledge and practice. Job satisfaction might directly support the positive attitude and practice toward bacterial MDR.

Sepsis-Associated Liver Injury (SALI) is an independent risk factor for death from sepsis. The aim of this study was to develop an interpretable machine learning model for early prediction of 28-day mortality in patients with SALI. Data from the Medical Information Mart for Intensive Care (MIMIC-IV, v2.2, MIMIC-III, v1.4) were used in this study. The study cohort from MIMIC-IV was randomized to the training set (0.7) and the internal validation set (0.3), with MIMIC-III (2001 to 2008) as external validation. The features with more than 20% missing values were deleted and the remaining features were multiple interpolated. Lasso-CV that lasso linear model with iterative fitting along a regularization path in which the best model is selected by cross-validation was used to select important features for model development. Eight machine learning models including Random Forest (RF), Logistic Regression, Decision Tree, Extreme Gradient Boost (XGBoost), K Nearest Neighbor, Support Vector Machine, Generalized Linear Models in which the best model is selected by cross-validation (CV_glmnet), and Linear Discriminant Analysis (LDA) were developed. Shapley additive interpretation (SHAP) was used to improve the interpretability of the optimal model. At last, a total of 1043 patients were included, of whom 710 were from MIMIC-IV and 333 from MIMIC-III. Twenty-four clinically relevant parameters were selected for model construction. For the prediction of 28-day mortality of SALI in the internal validation set, the area under the curve (AUC (95% CI)) of RF was 0.79 (95% CI: 0.73-0.86), and which performed the best. Compared with the traditional disease severity scores including Oxford Acute Severity of Illness Score (OASIS), Sequential Organ Failure Assessment (SOFA), Simplified Acute Physiology Score II (SAPS II), Logistic Organ Dysfunction Score (LODS), Systemic Inflammatory Response Syndrome (SIRS), and Acute Physiology Score III (APS III), RF also had the best performance. SHAP analysis found that Urine output, Charlson Comorbidity Index (CCI), minimal Glasgow Coma Scale (GCS_min), blood urea nitrogen (BUN) and admission_age were the five most important features affecting RF model. Therefore, RF has good predictive ability for 28-day mortality prediction in SALI. Urine output, CCI, GCS_min, BUN and age at admission(admission_age) within 24 h after intensive care unit(ICU) admission contribute significantly to model prediction.

Abstract Background Peach (Prunus persica L. Batsch) is one of the most popular fruits worldwide. Although the reference genome of ‘Lovell’ peach has been released, the diversity of genome-level variations cannot be explored with one genome. To detect these variations, it is necessary to assemble more genomes. Results We sequenced and de novo assembled the genome of ‘Feichenghongli’ (FCHL), a representative landrace with strict self-pollination, which maintained the homozygosity of the genome as much as possible. The chromosome-level genome of FCHL was 239.06 Mb in size with a contig N50 of 26.93 Mb and only 4 gaps at the scaffold level. The alignment of the FCHL genome with the reference ‘Lovell’ genome enabled the identification of 432535 SNPs, 101244 insertions and deletions, and 7299 structural variants. Gene family analysis showed that the expanded genes in FCHL were enriched in sesquiterpenoids and triterpenoid biosynthesis. RNA-seq analyses were carried out to investigate the two distinct traits of late florescence and narrow leaves. Two key genes, PpDAM4 and PpAGL31, were identified candidates for the control of flower bud dormancy, and an F-box gene, PpFBX92, was identified as a good candidate gene in the regulation of leaf size. Conclusions The assembled high-quality genome could deepen our understanding of variations among diverse genomes and provide valuable information for identifying functional genes and improving the molecular breeding process.

Background: Primary carnitine deficiency (PCD) is an autosomal recessive disease caused by mutations in the SLC22A5 gene, which encodes the organic cation transporter 2 (OCTN2). Patients with PCD may be at risk of skeletal or cardiac myopathy, metabolic decompensation, and even sudden death. This study aimed to analyze the biochemical, clinical, and genetic characteristics of PCD patients identified by newborn screening (NBS) in Shanghai.Methods: Dried blood spot (DBS) samples of newborns were analyzed through tandem mass spectrometry (MS/MS) from January 2003 to December 2021. Newborns with low free carnitine (C0) levels were recalled. Mutation in the SLC22A5 gene was analyzed on suspected positive newborns with low C0 levels after recall.Results: 1,247,274 newborns were screened by MS/MS and 40 newborns were diagnosed with PCD, therefore the incidence of PCD in Shanghai was approximately 1:31,200. The mean C0 level in newborns with PCD was 5.37 ± 1.79 μmol/L before treatment and increased to 24.45 ± 10.87 μmol/L after treatment with L-carnitine. Twenty-three different variants were identified in the SLC22A5 gene, including 8 novel variants, of which c.51C>G (p.F17L) was the most frequent (27.27%, 18/66), followed by c.1400C>G (p.S467C) (25.76%, 17/66). Almost all the screened PCD patients were asymptomatic.Conclusion: NBS via MS/MS was a quick and efficient method for the early diagnosis of PCD. The incidence of PCD in Shanghai was 1:31,200. Eight novel variants were identified, which greatly expanded the variant spectrum of SLC22A5. MS/MS combined with genetic testing could effectively improve the diagnostic accuracy of PCD.

Pentagalloyl glucose (PGG) is a natural hydrolyzable gallotannin abundant in various plants and herbs. It has a broad range of biological activities, specifically anticancer activities, and numerous molecular targets. Despite multiple studies available on the pharmacological action of PGG, the molecular mechanisms underlying the anticancer effects of PGG are unclear. Here, we have critically reviewed the natural sources of PGG, its anticancer properties, and underlying mechanisms of action. We found that multiple natural sources of PGG are available, and the existing production technology is sufficient to produce large quantities of the required product. Three plants (or their parts) with maximum PGG content were Rhus chinensis Mill, Bouea macrophylla seed, and Mangifera indica kernel. PGG acts on multiple molecular targets and signaling pathways associated with the hallmarks of cancer to inhibit growth, angiogenesis, and metastasis of several cancers. Moreover, PGG can enhance the efficacy of chemotherapy and radiotherapy by modulating various cancer-associated pathways. Therefore, PGG can be used for treating different human cancers; nevertheless, the data on the pharmacokinetics and safety profile of PGG are limited, and further studies are essential to define the clinical use of PGG in cancer therapies.