The AT-hook protein AHL29 promotes Bacillus subtilis colonization by suppressing SWEET2-mediated sugar retrieval in Arabidopsis roots.

Beneficial Bacillus subtilis (BS) symbiosis could combat root pathogenesis, but it relies on root-secreted sugars. Understanding the molecular control of sugar flux during colonization would benefit biocontrol applications. The SWEET (Sugar Will Eventually Be Exported Transporter) uniporter regulates microbe-induced sugar secretion from roots; thus, its homologs may modulate sugar distribution upon BS colonization. Quantitative polymerase chain reaction revealed that gene transcripts of SWEET2, but not SWEET16 and 17, were significantly induced in seedling roots after 12 h of BS inoculation. Particularly, SWEET2-ß-glucuronidase fusion proteins accumulated in the apical mature zone where BS abundantly colonized. Yet, enhanced BS colonization in sweet2 mutant roots suggested a specific role for SWEET2 to constrain BS propagation, probably by limiting hexose secretion. By employing yeast one-hybrid screening and ectopic expression in Arabidopsis protoplasts, the transcription factor AHL29 was identified to function as a repressor of SWEET2 expression through the AT-hook motif. Repression occurred despite immunity signals. Additionally, enhanced SWEET2 expression and reduced colonies were specifically detected in roots of BS-colonized ahl29 mutant. Taken together, we propose that BS colonization may activate repression of AHL29 on SWEET2 transcription that would be enhanced by immunity signals, thereby maintaining adequate sugar secretion for a beneficial Bacillus association.

Smoking increases the risk of postoperative wound complications: A propensity score-matched cohort study.

Cigarette smoking is associated with surgical complications, including wound healing and surgical site infection. However, the association between smoking status and postoperative wound complications is not completely understood. Our objective was to investigate the effect of smoking on postoperative wound complications for major surgeries. Data were collected from the 2013 to 2018 participant use files of the American College of Surgeons National Surgical Quality Improvement Program database. A propensity score matching procedure was used to create the balanced smoker and nonsmoker groups. Multivariable logistic regression was used to calculate the odds ratios (ORs) with 95% confidence intervals (CIs) for postoperative wound complications, pulmonary complications, and in-hospital mortality associated with smokers. A total of 1 156 002 patients (578 001 smokers and 578 001 nonsmokers) were included in the propensity score matching analysis. Smoking was associated with a significantly increased risk of postoperative wound disruption (OR 1.65, 95% CI 1.56-1.75), surgical site infection (OR 1.31, 95% CI 1.28-1.34), reintubation (OR 1.47, 95% CI 1.40-1.54), and in-hospital mortality (OR 1.13, 95% CI 1.07-1.19) compared with nonsmoking. The length of hospital stay was significantly increased in smokers compared with nonsmokers. Our analysis indicates that smoking is associated with an increased risk of surgical site infection, wound disruption, and postoperative pulmonary complications. The results may drive the clinicians to encourage patients to quit smoking before surgery.

Hybrid Machine Learning-Enabled Potential Energy Model for Atomistic Simulation of Lithium Intercalation into Graphite from Plating to Overlithiation.

Graphite is one of the most widely used negative electrode materials for lithium ion batteries (LIBs). However, because of the rapid growth of demands pursuing higher energy density and charging rates, comprehensive insights into the lithium intercalation and plating processes are critical for further boosting the potential of graphite electrodes. Herein, by utilizing the dihedral-angle-corrected registry-dependent potential (DRIP) (Wen et al., Phys. Rev. B 2018, 98, 235404), the Ziegler-Biersack-Littmark (ZBL) potential (Ziegler and Biersack, Astrophysics, Chemistry, and Condensed Matter; 1985, pp 93-129), and the machine learning-based spectral neighbor analysis (SNAP) potential (Thompson et al., J. Comput, Phys. 2015, 285, 316-330), we have successfully trained a hybrid machine learning-enabled potential energy model capable of simulating a wide spectrum of lithium intercalation scenario from plating to overlithiation. Our extensive atomistic simulations reveal the trapping of intercalated lithium atoms close to the graphite edges due to high hopping barriers, resulting in lithium plating. Furthermore, we report a stable dense graphite intercalation compound (GIC) LiC4 with a theoretical capacity of 558 mAh/g, wherein lithium atoms occupy alternating upper/lower graphene hollow sites with a nearest Li-Li distance of 2.8 Å. Surprisingly, following the same lithium insertion manner would allow the nearest Li-Li distance to be retained until the capacity reaches 845.2 mAh/g, corresponding to a GIC of LiC2.6. Hence, the present study demonstrates that the hybrid machine learning approach could further extend the scope of machine learning energy models, allowing us to investigate the lithium intercalation into graphite over a wide range of intercalation capacity to unveil the underlying mechanisms of lithium plating, diffusion, and discovery of new dense GICs for advanced LIBs with high charging rates and high energy densities.

General versus Neuraxial Anesthesia on Clinical Outcomes in Patients Receiving Hip Fracture Surgery: An Analysis of the ACS NSQIP Database.

Whether the use of neuraxial anesthesia or general anesthesia leads to more favorable postoperative outcomes in patients receiving hip fracture surgery remains unclear. We used data from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Data Files between 2016 and 2020 to investigate the association of neuraxial anesthesia and general anesthesia with morbidity and mortality after hip fracture surgery. Inverse probability of treatment weighting (IPTW) was used to balance the baseline characteristics, and multivariable Cox regression models were used to estimate the hazard ratio (HR) with a 95% confidence interval (CI) for postoperative morbidity and mortality among the different anesthesia groups. A total of 45,874 patients were included in this study. Postoperative adverse events occurred in 1087 of 9864 patients (11.0%) who received neuraxial anesthesia and in 4635 of 36,010 patients (12.9%) who received general anesthesia. After adjustment for IPTW, the multivariable Cox regressions revealed that general anesthesia was associated with increased risks of postoperative morbidity (adjusted HR, 1.19; 95% CI, 1.14-1.24) and mortality (adjusted HR, 1.09; 95% CI, 1.03-1.16). The results of the present study suggest that, compared with general anesthesia, neuraxial anesthesia is associated with lower risks of postoperative adverse events in patients undergoing hip fracture surgery.

Motor-Sparing Effect of Adductor Canal Block for Knee Analgesia: An Updated Review and a Subgroup Analysis of Randomized Controlled Trials Based on a Corrected Classification System.

OBJECTIVE: Discrepancies in the definition of adductor canal block (ACB) lead to inconsistent results. To investigate the actual analgesic and motor-sparing effects of ACB by anatomically defining femoral triangle block (FTB), proximal ACB (p-ACB), and distal ACB (d-ACB), we re-classified the previously claimed ACB approaches according to the ultrasound findings or descriptions in the corresponding published articles. A meta-analysis with subsequent subgroup analyses based on these corrected results was performed to examine the true impact of ACB on its analgesic effect and motor function (quadriceps muscle strength or mobilization ability). An optimal ACB technique was also suggested based on an updated review of evidence and ultrasound anatomy. MATERIALS AND METHODS: We systematically searched studies describing the use of ACB for knee surgery. Cochrane Library, PubMed, Web of Science, and Embase were searched with the exclusion of non-English articles from inception to 28 February 2022. The motor-sparing and analgesic aspects in true ACB were evaluated using meta-analyses with subsequent subgroup analyses according to the corrected classification system. RESULTS: The meta-analysis includes 19 randomized controlled trials. Compared with the femoral nerve block group, the quadriceps muscle strength (standardized mean difference (SMD) = 0.33, 95%-CI [0.01; 0.65]) and mobilization ability (SMD = -22.44, 95%-CI [-35.37; -9.51]) are more preserved in the mixed ACB group at 24 h after knee surgery. Compared with the true ACB group, the FTB group (SMD = 5.59, 95%-CI [3.44; 8.46]) has a significantly decreased mobilization ability at 24 h after knee surgery. CONCLUSION: By using the corrected classification system, we proved the motor-sparing effect of true ACB compared to FTB. According to the updated ultrasound anatomy, we suggested proximal ACB to be the analgesic technique of choice for knee surgery. Although a single-shot ACB is limited in duration, it remains the candidate of the analgesic standard for knee surgery on postoperative day 1 or 2 because it induces analgesia with less motor involvement in the era of multimodal analgesia. Furthermore, data from the corrected classification system may provide the basis for future research.

End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins.

Structural proteins are the basis of many biomaterials and key construction and functional components of all life. Further, it is well-known that the diversity of proteins' function relies on their local structures derived from their primary amino acid sequences. Here, we report a deep learning model to predict the secondary structure content of proteins directly from primary sequences, with high computational efficiency. Understanding the secondary structure content of proteins is crucial to designing proteins with targeted material functions, especially mechanical properties. Using convolutional and recurrent architectures and natural language models, our deep learning model predicts the content of two essential types of secondary structures, the α-helix and the ß-sheet. The training data are collected from the Protein Data Bank and contain many existing protein geometries. We find that our model can learn the hidden features as patterns of input sequences that can then be directly related to secondary structure content. The α-helix and ß-sheet content predictions show excellent agreement with training data and newly deposited protein structures that were recently identified and that were not included in the original training set. We further demonstrate the features of the model by a search for de novo protein sequences that optimize max/min α-helix/ß-sheet content and compare the predictions with folded models of these sequences based on AlphaFold2. Excellent agreement is found, underscoring that our model has predictive potential for rapidly designing proteins with specific secondary structures and could be widely applied to biomedical industries, including protein biomaterial designs and regenerative medicine applications.

Simple and specific dual-wavelength excitable dye staining for glycoprotein detection in polyacrylamide gels and its application in glycoproteomics.

In this study, a commercially available fluorescent dye, Lissamine rhodamine B sulfonyl hydrazine (LRSH), was designed to specifically stain the glycoproteins in polyacrylamide gels. Through the periodate/Schiff base mechanism, the fluorescent dye readily attaches to glycoproteins and the fluorescence can be simultaneously observed under either 305 nm or 532 nm excitation therefore, the dye-stained glycoproteins can be detected under a regular UV transilluminator or a more elegant laser-based gel scanner. The specificity and detection limit were examined using a standard protein mixture in polyacrylamide gels in this study. The application of this glycoprotein stain dye was further demonstrated using pregnancy urine samples. The fluorescent spots were further digested in gel and their identities confirmed through LC-MS/MS analysis and database searching. In addition, the N-glycosylation sites of LRSH-labeled uromodulin were readily mapped via in-gel PNGaseF deglycosylation and LC-MS/MS analysis, which indicated that this fluorescent dye labeling does not interfere with enzymatic deglycosylation. Hence, the application of this simple and specific dual-wavelength excitable dye staining in current glycoproteome research is promising.

Cancer DEIso: An integrative analysis platform for investigating differentially expressed gene-level and isoform-level human cancer markers.

Transcript isoforms regulated by alternative splicing can substantially impact carcinogenesis, leading to a need to obtain clues for both gene differential expression and malfunctions of isoform distributions in cancer studies. The Cancer Genome Atlas (TCGA) project was launched in 2008 to collect cancer-related genome mutation raw data from the population. While many repositories tried to add insights into the raw data in TCGA, no existing database provides both comprehensive gene-level and isoform-level cancer stage marker investigation and survival analysis. We constructed Cancer DEIso to facilitate in-depth analyses for both gene-level and isoform-level human cancer studies. Patient RNA-seq data, sample sheets, patient clinical data, and human genome datasets were collected and processed in Cancer DEIso. And four functions to search differentially expressed genes/isoforms between cancer stages were implemented: (i) Search potential gene/isoform markers for a specified cancer type and its two stages; (ii) Search potentially induced cancer types and stages for a gene/isoform; (iii) Expression survival analysis on a given gene/isoform for some cancer; (iv) Gene/isoform stage expression comparison visualization. As an example, we demonstrate that Cancer DEIso can indicate potential colorectal cancer isoform diagnostic markers that are not easily detected when only gene-level expressions are considered. Cancer DEIso is available at http://cosbi4.ee.ncku.edu.tw/DEIso/.

Case Report: Anesthetic Management and Electrical Cardiometry as Intensive Hemodynamic Monitoring During Cheiloplasty in an Infant With Enzyme-Replaced Pompe Disease and Preserved Preoperative Cardiac Function.

Introduction: Pompe disease is caused by deficiency of the lysosomal enzyme acid α-glucosidase, which results in cardiac and muscular complications that can jeopardize perioperative outcomes. We report a 4-month-old infant with Pompe disease receiving cheiloplasty under general anesthesia with the aid of peripheral nerve blocks and intensive hemodynamic monitoring. Case Description: This case report describes a 4-month-old full-term Taiwanese female infant who presented with left unilateral cleft lip and palate in the prenatal examination. She was diagnosed with infantile-onset Pompe disease after acidic α-glucosidase (GAA) gene sequencing. She also received enzyme replacement therapy (ERT) 15 days after birth and regular ERT every other week. Cheiloplasty was performed under general anesthesia uneventfully, and peripheral nerve blocks were adopted for analgesia. Intensive hemodynamic monitoring using electrical cardiometry technology (ICON®) and pulse contour analysis (FloTrac system) were applied during the operation. No adverse effects were observed, and the wound healed well. Therefore, the patient was discharged 4 days after surgery. Conclusion: With the availability of ERT, severe organ dysfunction in infantile-onset Pompe disease patients is no longer common. However, moderate cardiac depression can still occur while increasing inspiratory pressure and deepening the anesthesia level despite a normal preoperative echocardiogram report. Therefore, careful, gradual titration is desirable. Furthermore, electrical cardiometry can detect hemodynamic changes more instantaneously and reliably than pulse contour analysis. In addition, we suggest taking advantage of the peripheral nerve block as a part of balanced anesthesia to alleviate the cardiac suppression caused by general anesthesia.

Operative hysteroscopy intravascular absorption syndrome is more than just the gynecological transurethral resection of the prostate syndrome: A case series and literature review.

OBJECTIVE: Operative hysteroscopy intravascular absorption (OHIA) syndrome refers to fluid overload complications from operative hysteroscopies. Despite guidelines for safe operative hysteroscopies, instances of OHIA syndrome have been reported. CASE REPORT: We reported three cases of OHIA syndrome. A 48-year-old female patient presented net irrigation fluid of 11,900 mL and developed severe metabolic acidosis, conscious disturbance, acute pulmonary edema, and unexpected intensive care unit admission. A 49-year-old female patient presented net irrigation fluid of 4500 mL and developed desaturation and acute pulmonary edema. A 45-year-old female patient presented net irrigation fluid of 2400 mL and developed hyponatremia, increased hilum lung marking, and prolonged postanesthesia care unit observation. CONCLUSION: For safety, clinicians should use isotonic electrolyte-containing distension media and bipolar electrosurgical instruments in operative hysteroscopies, and fluid status should be monitored closely, particularly at net and total irrigation amounts >3000 and > 8000 mL, respectively. Intrauterine pressure should also be minimized to reduce intravascular and intraperitoneal absorption.