Beyond black-box models: explainable AI for embryo ploidy prediction and patient-centric consultation.

PURPOSE: To determine if an explainable artificial intelligence (XAI) model enhances the accuracy and transparency of predicting embryo ploidy status based on embryonic characteristics and clinical data. METHODS: This retrospective study utilized a dataset of 1908 blastocyst embryos. The dataset includes ploidy status, morphokinetic features, morphology grades, and 11 clinical variables. Six machine learning (ML) models including Random Forest (RF), Linear Discriminant Analysis (LDA), Logistic Regression (LR), Support Vector Machine (SVM), AdaBoost (ADA), and Light Gradient-Boosting Machine (LGBM) were trained to predict ploidy status probabilities across three distinct datasets: high-grade embryos (HGE, n = 1107), low-grade embryos (LGE, n = 364), and all-grade embryos (AGE, n = 1471). The model's performance was interpreted using XAI, including SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) techniques. RESULTS: The mean maternal age was 38.5 ± 3.85 years. The Random Forest (RF) model exhibited superior performance compared to the other five ML models, achieving an accuracy of 0.749 and an AUC of 0.808 for AGE. In the external test set, the RF model achieved an accuracy of 0.714 and an AUC of 0.750 (95% CI, 0.702-0.796). SHAP's feature impact analysis highlighted that maternal age, paternal age, time to blastocyst (tB), and day 5 morphology grade significantly impacted the predictive model. In addition, LIME offered specific case-ploidy prediction probabilities, revealing the model's assigned values for each variable within a finite range. CONCLUSION: The model highlights the potential of using XAI algorithms to enhance ploidy prediction, optimize embryo selection as patient-centric consultation, and provides reliability and transparent insights into the decision-making process.

Data on annotation and analysis of genome sequence of Paenibacillus elgii YSY-1.2, a promising chitinase-producing, plant-growth-promoting, and biocontrol agent.

The bacterium Paenibacillus elgii YSY-1.2 was recently isolated from soil collected from Yok Don National Park in Vietnam. Previous experiments showed this bacterium possesses high chitin-degrading activity, plant-growth promotion, and biocontrol capacity. Here, we report the draft genome sequence of strain YSY-1.2 for further characterizations related to crop production. The genome sequencing was performed using the DNBSeq-G99 with the Illumina platform. The draft genome of P. elgii YSY-1.2 has 8,240,519 bp in length and comprises 135 contigs. It has an N50 of 315,408 bp and a GC% of 52.8%. The genome contains 7498 protein-coding genes, 87 tRNA genes, and 1 rRNA gene. Among the protein-coding sequences, 6610 were assigned by COG, while 3230 were assigned by KEGG. The genome possesses at least 61 genes involved in environmental adaptation and plant growth promotion. Additionally; there are 258 carbohydrate-active enzymes deduced from the genome; among them, at least 14 may contribute to the biocontrol capacity. The chitin-degrading system of strain YSY-1.2 contains 16 chitinolytic enzymes, comprising 10 chitinases, 4 ß-N-acetylhexosaminidases, and 2 auxiliary activities. Furthermore, 32 gene clusters encoding antimicrobial metabolites were identified from the genome, with 17 showing no sequence similarities to reported clusters. Data provide an insight into the genomic information of strain YSY-1.2 and could lead to valuable further explorations and applications in crop production. This is the first report describing the genome sequence of P. elgii isolated from Vietnam.

Arteriovenous malformation in the kidney allograft: A rare cause of hematuria in the post-transplant patient.

Gross hematuria is one of the most common complications in postrenal transplant patients, accounting for 12% of all renal recipients. The management plan in these cases varies depending on different entities, including infection, renal cell carcinoma, chronic graft rejection, kidney calculus, or recurrence of primary disease. On the other hand, vascular malformation like arteriovenous malformation was less likely to be mentioned due to a lack of consensus in the natural history, pathogenesis, and current management. In this article, we report a 62-year-old man presenting with spontaneous hematuria for a week and 2 days of anuria after 3 years of renal transplantation. Abdominal ultrasound and abdominopelvic computed tomography noted an obstruction of the renal pelvis due to blood clots without signs of vascular injuries. An emergency operation was performed to remove blood clots in the renal pelvis, but after that, hematuria was still recurrence. A digital renal graft subtraction angiography (DSA) revealed an arteriovenous malformation (AVM)in the kidney allograft. This lesion was then successfully selective embolized with glue. Given the high accuracy of DSA, our case highlights the potential role of this imaging modality in diagnosing and treating AVM after failure with other modalities.

A study on the antioxidant, anti-inflammatory, and xanthine oxidase inhibitory activity of the Artemisia vulgaris L. extract and its fractions.

ETHNOPHARMACOLOGICAL RELEVANCE: Vietnamese people use mugwort (Artemisia vulgaris L.) to treat arthritis and gout. Our previous research shows that mugwort contains flavonoids, and its extract possesses antibacterial and anti-inflammatory activities. However, no publications have been on the xanthine oxidase inhibitory activity of mugwort and acute anti-inflammatory activity in vivo. AIM OF THE STUDY: The study aimed to verify the antioxidant, xanthine oxidase inhibitory, and anti-inflammatory capabilities of mugwort extract in vitro and in vivo, isolate phyto-compounds from potential bioactive fractions, and then evaluate their potential in inhibiting xanthine oxidase. METHODS: According to established methods, the extract and the active flavonoids were obtained using different chromatographic techniques. DPPH, ABTS, reducing power, and H2O2 elimination were used to evaluate antioxidant activity. The model of LPS-induced RAW264.7 cells was used to measure the inhibition of NO production. The carrageenan-induced paw oedema model was used to assess acute inflammation in mice. In vitro, xanthine oxidase inhibition assay was applied to investigate the effects of extract/compounds on uric acid production. Chemical structures were identified by spectral analysis. RESULTS: The assessment of the acute inflammatory model in mice revealed that both the 96% ethanol and the 50% ethanol extracts significantly decreased oedema in the mice's feet following carrageenan-induced inflammation. 96% ethanol extract exhibited a better reduction in oedema at the low dose. The analysis revealed that the ethyl acetate fraction had the highest levels of total polyphenols and flavonoids. Additionally, this fraction demonstrated significant antioxidant activity in various assays, such as DPPH, ABTS, reducing power, and H2O2 removal. Furthermore, it displayed the most potent inhibition of xanthine oxidase, an anti-inflammatory activity. Five phytochemicals were isolated and determined from the active fraction such as luteolin (1), rutin (2), apigenin (3), myricetin (4), and quercetin (5). Except for rutin, the other compounds demonstrated the ability to inhibit effective xanthine oxidase compared to standard (allopurinol). Moreover, quercetin (5) inhibited NO production (IC50 21.87 µM). CONCLUSION: The results indicate that extracts from A. vulgaris effectively suppressed the activity of xanthine oxidase and exhibited antioxidant and anti-inflammatory properties, potentially leading to a reduction in the production of uric acid in the body and eliminating ROS. The study identified mugwort extract and bioactive compounds derived from Artemisia vulgaris, specifically luteolin, apigenin, and quercetin, as promising xanthine oxidase inhibitors. These findings suggest that further development of these compounds is warranted. At the same time, the above results also strengthen the use of mugwort to treat gout disease in Vietnam.

The Impact of Embryo Quality on Pregnancy Outcomes in Single Day 5 versus Day 6 Euploid Blastocyst Transfer: A Retrospective Cohort Study.

BACKGROUND: Selecting embryos with the highest implantation potential is crucial for in vitro fertilization (IVF) success. Both the timing of blastulation, day 5 (D5) or D6, and the embryo quality have been suggested as influential factors in determining the clinical outcome of single euploid blastocyst transfers. However, evidence supporting the superiority of D5 over D6 blastocysts remains inconclusive. The aim of this study was to compare clinical outcomes following the transfer of euploid blastocysts with different quality and timing of blastulation. MATERIALS AND METHODS: A retrospective cohort study was conducted at our Assisted Reproductive Center, analyzing the outcome of 774 transfers with D5 euploids and 155 transfers with D6 euploids performed between January 2019 and February 2022. RESULTS: The live birth rate was significantly lower in the euploid D6 group compared to the euploid D5 group (38.71vs. 55.04%, P=0.001). The outcome was significantly influenced by the quality of the embryos. Live birth rates were 62.14 and 53.61% following transfers of D5 and D6 excellent embryos respectively, 45.18 and 32.21% following transfer of D5 and D6 good embryos but only 28.64 and 19.32% following transfer of D5 and D6 fair embryos. The outcome difference was statistically significant across embryo quality categories (P=0.001). The adjusted risk ratios (RR) of clinical outcomes indicated that excellent euploid D5 embryos consistently outperformed other types of embryo quality. CONCLUSION: The timing of blastulation and embryo quality are crucial factors in determining the success of single euploid blastocyst transfers. Excellent euploid D5 transfers yielded superior clinical outcomes, providing valuable insights for IVF teams and patients when selecting embryos to be transferred.

Center-level variation in hospitalization costs of pancreaticoduodenectomy for pancreatic cancer.

BACKGROUND: Pancreaticoduodenectomy is a highly morbid operation with significant resource utilization. Using a national cohort, we examined the interhospital variation in pancreaticoduodenectomy hospitalization cost in the United States. METHODS: Adults undergoing elective pancreaticoduodenectomy in the setting of pancreatic cancer were tabulated from the 2016-2020 Nationwide Readmissions Database. A 2-level mixed-effects model was developed to evaluate the interhospital variation in pancreaticoduodenectomy hospitalization costs. Institutions within the top decile of risk-adjusted expenditures were defined as high-cost hospitals. Multivariable regression models were fitted to examine the association between high-cost hospital status and outcomes of interest. To account for the effects of complications on expenditures, a subgroup analysis comprising of patients with no adverse events was conducted. RESULTS: The study included an estimated 24,779 patients with a median hospitalization cost of $38,800. After mixed-effects modeling, 40.9% of the cost variation was attributable to hospital, rather than patient, factors. Multivariable regression models revealed an association between high-cost hospital status and greater odds of complications and longer length of stay. Among patients without an adverse event, interhospital cost variation remained significant at 61.0%, and treatment at high-cost hospitals was similarly linked to longer length of stay. CONCLUSION: Our study identified significant interhospital variation in pancreaticoduodenectomy hospitalization costs in the United States. Although high-cost hospital status was associated with increased odds of complications, variation remained significant even among patients without an adverse event. These results suggest the important role of hospital practices as contributors to expenditures. Further efforts to identify drivers of costs and standardize pancreatic surgical care are warranted.

In silico screening of Fyn kinase inhibitors using classification-based QSAR model, molecular docking, molecular dynamics and ADME study.

This study aimed to use a computational approach that combined the classification-based QSAR model, molecular docking, ADME studies, and molecular dynamics (MD) to identify potential inhibitors of Fyn kinase. First, a robust classification model was developed from a dataset of 1,078 compounds with known Fyn kinase inhibitory activity, using the XGBoost algorithm. After that, molecular docking was performed between potential compounds identified from the QSAR model and Fyn kinase to assess their binding strengths and key interactions, followed by MD simulations. ADME studies were additionally conducted to preliminarily evaluate the pharmacokinetics and drug-like characteristics of these compounds. The results showed that our obtained model exhibited good predictive performance with an accuracy of 0.95 on the test set, affirming its reliability in identifying potent Fyn kinase inhibitors. Through the application of this model in conjunction with molecular docking and ADME studies, nine compounds were identified as potential Fyn kinase inhibitors, including 208 (ZINC70708110), 728 (ZINC8792432), 734 (ZINC8792187), 736 (ZINC8792350), 738 (ZINC8792286), 739 (ZINC8792309), 817 (ZINC33901069), 852 (ZINC20759145), and 1227 (ZINC100006936). MD simulations further demonstrated that the four most promising compounds, 728, 734, 736, and 852 exhibited stable binding with Fyn kinase during the simulation process. Additionally, a web-based platform ( https://fynkinase.streamlit.app/ ) has been developed to streamline the screening process. This platform enables users to predict the activity of their substances of interest on Fyn kinase from their SMILES, using our classification-based QSAR model and molecular docking.

Association of severe obesity with risk of conversion to open in laparoscopic cholecystectomy for acute cholecystitis.

Background: Obesity is a known risk factor for cholecystitis and is associated with technical complications during laparoscopic procedures. The present study seeks to assess the association between obesity class and conversion to open (CTO) during laparoscopic cholecystectomy (LC). Methods: Adult acute cholecystitis patients with obesity undergoing non-elective LC were identified in the 2017-2020 Nationwide Readmissions Database. Patients were stratified by obesity class; class 1 (Body Mass Index [BMI] = 30.0-34.9), class 2 (BMI = 35.0-39.9), and class 3 (BMI ≥ 40.0). Multivariable regression models were developed to assess factors associated with CTO and its association with perioperative complications and resource utilization. Results: Of 89,476 patients undergoing LC, 40.6 % had BMI ≥ 40.0. Before adjustment, class 3 obesity was associated with increased rates of CTO compared to class 1-2 (4.6 vs 3.8 %; p < 0.001). Following adjustment, class 3 remained associated with an increased likelihood of CTO (Adjusted Odds Ratio [AOR] 1.45, 95 % Confidence Interval [CI] 1.31-1.61; ref.: class 1-2). Patients undergoing CTO had increased risk of blood transfusion (AOR 3.27, 95 % CI 2.54-4.22) and respiratory complications (AOR 1.36, 95 % CI 1.01-1.85). Finally, CTO was associated with incremental increases in hospitalization costs (ß + $719, 95 % CI 538-899) and length of stay (LOS; ß +2.20 days, 95 % CI 2.05-2.34). Conclusions: Class 3 obesity is a significant risk factor for CTO. Moreover, CTO is associated with increased hospitalization costs and LOS. As the prevalence of obesity grows, improved understanding of operative risk by approach is required to optimize clinical outcomes. Our findings are relevant to shared decision-making and informed consent.

Using a hybrid neural network architecture for DNA sequence representation: A study on N4-methylcytosine sites.

N4-methylcytosine (4mC) is a modified form of cytosine found in DNA, contributing to epigenetic regulation. It exists in various genomes, including the Rosaceae family encompassing significant fruit crops like apples, cherries, and roses. Previous investigations have examined the distribution and functional implications of 4mC sites within the Rosaceae genome, focusing on their potential roles in gene expression regulation, environmental adaptation, and evolution. This research aims to improve the accuracy of predicting 4mC sites within the genome of Fragaria vesca, a Rosaceae plant species. Building upon the original 4mc-w2vec method, which combines word embedding processing and a convolutional neural network (CNN), we have incorporated additional feature encoding techniques and leveraged pre-trained natural language processing (NLP) models with different deep learning architectures including different forms of CNN, recurrent neural networks (RNN) and long short-term memory (LSTM). Our assessments have shown that the best model is derived from a CNN model using fastText encoding. This model demonstrates enhanced performance, achieving a sensitivity of 0.909, specificity of 0.77, and accuracy of 0.879 on an independent dataset. Furthermore, our model surpasses previously published works on the same dataset, thus showcasing its superior predictive capabilities.

National trends and outcomes of robotic emergency general surgery in the United States.

BACKGROUND: Robot-assisted surgery has seen exponential adoption over the last decade. Although the safety and efficacy of robotic surgery in the elective setting have been demonstrated, data regarding robotic emergency general surgery remains sparse. METHODS: All adults undergoing non-elective appendectomy, cholecystectomy, small or large bowel resection, perforated ulcer repair, or lysis of adhesions were identified in the 2008 to 2020 National Inpatient Sample. Temporal trends were analyzed using a rank-based, non-parametric test developed by Cuzick (nptrend). Using laparoscopy as a reference, multivariable regressions were used to evaluate the association between robotic techniques and in-hospital mortality, major complications, and resource use for each emergency general surgery operation. RESULTS: Of an estimated 4,040,555 patients undergoing emergency general surgery, 65,853 (1.6%) were performed using robotic techniques. The robotic proportion of minimally invasive emergency general surgery increased significantly overall, with the largest growth seen in robot-assisted large bowel resections and perforated ulcer repairs. After adjustment for various patient and hospital-level factors, robot-assisted large bowel resection (adjusted odds ratio 0.73, 95% confidence interval 0.58-0.91) and cholecystectomy (adjusted odds ratio 0.66, 95% confidence interval 0.55-0.81) were associated with significantly reduced odds of perioperative blood transfusion compared to traditional laparoscopy. Although robotic techniques were associated with modest reductions in postoperative length of stay, costs were uniformly higher by increments of up to $4,900. CONCLUSION: Robotic surgery appears to be a safe and effective adjunct to laparoscopy in minimally invasive emergency general surgery, although comparable cost-effectiveness has yet to be realized. Increasing use of robotic techniques in emergency general surgery may be attributable in part to reduced complications, including blood loss, in certain operative contexts.

Corrigendum: Effectiveness of perindopril/amlodipine fixed-dose combination in the treatment of hypertension: a systematic review.

[This corrects the article DOI: 10.3389/fphar.2023.1156655.].

Polarimeters for the Detection of Anisotropy from Reflectance.

Polarimetry is used to determine the Stokes parameters of a laser beam. Once all four S0,1,2,3 parameters are determined, the state of polarisation is established. Upon reflection of a laser beam with the defined S polarisation state, the directly measured S parameters can be used to determine the optical properties of the surface, which modify the S-state upon reflection. Here, we use polarimetry for the determination of surface anisotropies related to the birefringence and dichroism of different materials, which have a common feature of linear patterns with different alignments and scales. It is shown that polarimetry in the back-reflected light is complementary to ellipsometry and four-polarisation camera imaging; experiments were carried out using a microscope.

Gastrointestinal Perforation After Solid Organ Transplantation: A Case Series.

Although organ transplantation is associated with significant survival rates and cost benefits, postoperative complications still occur. Gastrointestinal complications, including those involving the stomach and intestines, account for 1-6% of posttransplant complications, with intestinal perforation specifically accounting for approximately 9%, depending on the center. In Vietnam, there are no comprehensive reports on these complications. Therefore, we report three clinical cases of gastrointestinal perforation following transplantation. Three cases of intestinal perforation are described in this case series. In 2023, a 16-year-old female patient who underwent heart transplantation for congenital heart disease was diagnosed with intestinal perforation on the 12th day. The patient required continued blood filtration support after surgery. In 2018, six days after liver transplantation, a 56-year-old male patient was diagnosed with intestinal perforation, which was subsequently repaired, and the ends of his intestines were removed. The patient was discharged in stable condition after 30 days. In 2017, five days after kidney transplantation, a 46-year-old female patient was diagnosed with intestinal perforation, which was repaired, and the perforation site was left open. The patient was discharged in stable condition after 40 days. Intestinal perforation is a relatively rare, but not uncommon, complication. Early diagnosis is challenging due to nonspecific clinical symptoms and signs. Considering the possibility of intestinal perforation and obtaining early abdominal computed tomography imaging can help prevent delayed diagnosis.

Recent progress in machine learning approaches for predicting carcinogenicity in drug development.

INTRODUCTION: This review explores the transformative impact of machine learning (ML) on carcinogenicity prediction within drug development. It discusses the historical context and recent advancements, emphasizing the significance of ML methodologies in overcoming challenges related to data interpretation, ethical considerations, and regulatory acceptance. AREAS COVERED: The review comprehensively examines the integration of ML, deep learning, and diverse artificial intelligence (AI) approaches in various aspects of drug development safety assessments. It explores applications ranging from early-phase compound screening to clinical trial optimization, highlighting the versatility of ML in enhancing predictive accuracy and efficiency. EXPERT OPINION: Through the analysis of traditional approaches such as in vivo rodent bioassays and in vitro assays, the review underscores the limitations and resource intensity associated with these methods. It provides expert insights into how ML offers innovative solutions to address these challenges, revolutionizing safety assessments in drug development.

Nationwide Trends in Utilization of Minimally Invasive Techniques for Blunt Abdominal Trauma.

BACKGROUND: Despite increasing use of minimally invasive surgical (MIS) techniques for trauma, limited large-scale studies have evaluated trends, outcomes, and resource utilization at centers that utilize MIS modalities for blunt abdominal trauma. METHODS: Operative adult admissions after blunt assault, falls, or vehicular collisions were tabulated from the 2016-2020 National Inpatient Sample. Patients who received diagnostic laparoscopy or other laparoscopic and robotic intervention were classified as MIS. Institutions with at least one MIS trauma operation in a year were defined as an MIS Performing Institution (MPI; rest: non-MPI). The primary endpoint was mortality, with secondary outcomes of reoperation, complication, postoperative length of stay (LOS), and hospitalization costs. Mixed regression models were used to determine the association of MPI status on the outcomes of interest. RESULTS: Throughout the study period, the proportion of MIS operations and MPI significantly increased from 22.6 to 29.8% and 45.9 to 58.8%, respectively. Of an estimated 77,480 patients, 66.7% underwent care at MPI. After adjustment, MPI status was not associated with increased odds of mortality (adjusted odds ratio [AOR] 1.09, 95% confidence interval [CI] [.96,1.24]), reoperation (AOR 1.02, CI [.87,1.19]), or any of the tabulated complications. There was additionally no difference in adjusted LOS (ß-.18, CI [-.85, +.49]) or costs (ß+$1600, CI [-1600, +4800]), between MPI and non-MPI. DISCUSSION: The use of MIS operations in blunt abdominal trauma has significantly increased, with performing centers experiencing no difference in mortality or resource utilization. Prospectively collected data on outcomes following MIS trauma surgery is necessary to elucidate appropriate applications.

Machine learning prediction of hospitalization costs for coronary artery bypass grafting operations.

BACKGROUND: With the steady rise in health care expenditures, the examination of factors that may influence the costs of care has garnered much attention. Although machine learning models have previously been applied in health economics, their application within cardiac surgery remains limited. We evaluated several machine learning algorithms to model hospitalization costs for coronary artery bypass grafting. METHODS: All adult hospitalizations for isolated coronary artery bypass grafting were identified in the 2016 to 2020 Nationwide Readmissions Database. Machine learning models were trained to predict expenditures and compared with traditional linear regression. Given the significance of postoperative length of stay, we additionally developed models excluding postoperative length of stay to uncover other drivers of costs. To facilitate comparison, machine learning classification models were also trained to predict patients in the highest decile of costs. Significant factors associated with high cost were identified using SHapley Additive exPlanations beeswarm plots. RESULTS: Among 444,740 hospitalizations included for analysis, the median cost of hospitalization in coronary artery bypass grafting patients was $43,103. eXtreme Gradient Boosting most accurately predicted hospitalization costs, with R2 = 0.519 over the validation set. The top predictive features in the eXtreme Gradient Boosting model included elective procedure status, prolonged mechanical ventilation, new-onset respiratory failure or myocardial infarction, and postoperative length of stay. After removing postoperative length of stay, eXtreme Gradient Boosting remained the most accurate model (R2 = 0.38). Prolonged ventilation, respiratory failure, and elective status remained important predictive parameters. CONCLUSION: Machine learning models appear to accurately model total hospitalization costs for coronary artery bypass grafting. Future work is warranted to uncover other drivers of costs and improve the value of care in cardiac surgery.

Mortality and resource utilization in surgical versus transcatheter repeat mitral valve replacement: A national analysis.

BACKGROUND: Transcatheter mitral valve replacement (TMVR) has garnered interest as a viable alternative to the traditional surgical mitral valve replacement (SMVR) for high-risk patients requiring redo operations. This study aims to evaluate the association of TMVR with selected clinical and financial outcomes. METHODS: Adults undergoing isolated redo mitral valve replacement were identified in the 2016-2020 Nationwide Readmissions Database and categorized into TMVR or SMVR cohorts. Various regression models were developed to assess the association between TMVR and in-hospital mortality, as well as additional secondary outcomes. Transseptal and transapical catheter-based approaches were also compared in relation to study endpoints. RESULTS: Of an estimated 7,725 patients, 2,941 (38.1%) underwent TMVR. During the study period, the proportion of TMVR for redo operations increased from 17.8% to 46.7% (nptrend<0.001). Following adjustment, TMVR was associated with similar odds of in-hospital mortality (AOR 0.82, p = 0.48), but lower odds of stroke (AOR 0.44, p = 0.001), prolonged ventilation (AOR 0.43, p<0.001), acute kidney injury (AOR 0.61, p<0.001), and reoperation (AOR 0.29, p = 0.02). TMVR was additionally correlated with shorter postoperative length of stay (pLOS; ß -0.98, p<0.001) and reduced costs (ß -$10,100, p = 0.002). Additional analysis demonstrated that the transseptal approach had lower adjusted mortality (AOR 0.44, p = 0.02), shorter adjusted pLOS (ß -0.43, p<0.001), but higher overall costs (ß $5,200, p = 0.04), compared to transapical. CONCLUSIONS: In this retrospective cohort study, we noted TMVR to yield similar odds of in-hospital mortality as SMVR, but fewer complications and reduced healthcare expenditures. Moreover, transseptal approaches were associated with lower adjusted mortality, shorter pLOS, but higher cost, relative to the transapical. Our findings suggest that TMVR represent a cost-effective and safe treatment modality for patients requiring redo mitral valve procedures. Nevertheless, future studies examining long-term outcomes associated with SMVR and TMVR in redo mitral valve operations, are needed.

Clinical and financial outcomes associated with the utilization of right internal mammary artery versus radial artery in multivessel coronary artery bypass grafting.

BACKGROUND: Multi-arterial coronary bypass grafting with the left internal mammary artery as a conduit has been shown to offer superior long-term survival compared to single-arterial coronary bypass grafting. Nevertheless, the selection of a secondary conduit between the right internal mammary artery and the radial artery remains controversial. Using a national cohort, we examined the relationships between the right internal mammary artery and the radial artery with acute clinical and financial outcomes. METHODS: Adults undergoing on-pump multivessel coronary bypass grafting with left internal mammary artery as the first arterial conduit were identified in the 2016 to 2020 Nationwide Readmissions Database. Patients receiving either the right internal mammary artery or the radial artery, but not both, were included in the analysis. Multivariable regression models were fitted to examine the association between the conduits and in-hospital mortality, as well as additional secondary outcomes. RESULTS: Of an estimated 49,798 patients undergoing multi-arterial coronary bypass grafting, 29,729 (59.7%) comprised the radial artery cohort. During the study period, the proportion of multi-arterial coronary bypass grafting utilizing the radial artery increased from 51.3% to 65.2% (nptrend <0.001). Following adjustment, the radial artery was associated with reduced odds of in-hospital mortality (adjusted odds ratio 0.44), prolonged mechanical ventilation (adjusted odds ratio 0.78), infectious complications (adjusted odds ratio 0.69), and 30-day nonelective readmission (adjusted odds ratio 0.77, all P < .05). CONCLUSION: Despite no definite endorsement from surgical societies, the radial artery is increasingly utilized as a secondary conduit in multi-arterial coronary bypass grafting. Compared to the right internal mammary artery, the radial artery was associated with lower odds of in-hospital mortality, complications, and reduced healthcare expenditures. These results suggest that whenever feasible, the radial artery should be the favored conduit over the right internal mammary artery. Nevertheless, future studies examining long-term outcomes associated with these vessels remain necessary.

Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains.

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR.

Trends in the adoption of diverting loop ileostomy for acute complicated diverticulitis in the United States.

BACKGROUND: Acute complicated diverticulitis poses a substantial burden to individual patients and the health care system. A significant proportion of the cases necessitate emergency operations. The choice between Hartmann's procedure and primary anastomosis with diverting loop ileostomy remains controversial. METHODS: Using American College of Surgeons National Surgical Quality Improvement Program patient user file data from 2012 to 2020, patients undergoing Hartmann's procedure and primary anastomosis with diverting loop ileostomy for nonelective sigmoidectomy for complicated diverticulitis were identified. Major adverse events, 30-day mortality, perioperative complications, operative duration, reoperation, and 30-day readmissions were assessed. RESULTS: Of 16,921 cases, 6.3% underwent primary anastomosis with diverting loop ileostomy, showing a rising trend from 5.3% in 2012 to 8.4% in 2020. Primary anastomosis with diverting loop ileostomy patients, compared to Hartmann's procedure, had similar demographics and fewer severe comorbidities. Primary anastomosis with diverting loop ileostomy exhibited lower rates of major adverse events (24.6% vs 29.3%, P = .001). After risk adjustment, primary anastomosis with diverting loop ileostomy had similar risks of major adverse events and 30-day mortality compared to Hartmann's procedure. While having lower odds of respiratory (adjusted odds ratio 0.61, 95% confidence interval 0.45-0.83) and infectious (adjusted odds ratio 0.78, 95% confidence interval 0.66-0.93) complications, primary anastomosis with diverting loop ileostomy was associated with a 36-minute increment in operative duration and increased odds of 30-day readmission (adjusted odds ratio 1.30, 95% confidence interval 1.07-1.57) compared to Hartmann's procedure. CONCLUSION: Primary anastomosis with diverting loop ileostomy displayed comparable odds of major adverse events compared to Hartmann's procedure in acute complicated diverticulitis while mitigating infectious and respiratory complication risks. However, primary anastomosis with diverting loop ileostomy was associated with longer operative times and greater odds of 30-day readmission. Evolving guidelines and increasing primary anastomosis with diverting loop ileostomy use suggest a shift favoring primary anastomosis, especially in complicated diverticulitis. Future investigation of disparities in surgical approaches and patient outcomes is warranted to optimize acute diverticulitis care pathways.