Unravelling the Antimicrobial, Antibiofilm, Suppressing Fibronectin Binding Protein A (fnba) and cna Virulence Genes, Anti-Inflammatory and Antioxidant Potential of Biosynthesized Solanum lycopersicum Silver Nanoparticles.

Background and Objectives: Urinary tract infections [UTIs] are considered the third most known risk of infection in human health around the world. There is increasing appreciation for the pathogenicity of Gram-positive and Gram-negative strains in UTIs, aside from fungal infection, as they have numerous virulence factors. Materials and Methods: In this study, fifty urine samples were collected from patients suffering from UTI. Among the isolates of UTI microbes, six isolates were described as MDR isolates after an antibiotic susceptibility test carried out using ten different antibiotics. An alternative treatment for microbial elimination involved the use of biosynthesized silver nanoparticles (AgNPs) derived from Solanum lycopersicum [S. cumin]. Results: The sizes and shapes of AgNPs were characterized through TEM imaging, which showed spherical particles in a size range of 35-80 nm, of which the average size was 53 nm. Additionally, the silver nanoparticles (AgNPs) demonstrated inhibitory activity against Staphylococcus aureus (OR648079), exhibiting a 31 mm zone of inhibition at a minimum inhibitory concentration (MIC) of 4 mg/mL and a minimum bactericidal concentration (MBC) of 8 mg/mL. This was followed by Aspergillus niger (OR648075), which showed a 30 mm inhibition zone at an MIC of 16 mg/mL and a minimum fungicidal concentration (MFC) of 32 mg/mL. Then, Enterococcus faecalis (OR648078), Klebsiella pneumoniae (OR648081), and Acinetobacter baumannii (OR648080) each displayed a 29 mm zone of inhibition at an MIC of 8 mg/mL and an MBC of 16 mg/mL. The least inhibition was observed against Candida auris (OR648076), with a 25 mm inhibition zone at an MIC of 16 mg/mL and an MFC of 32 mg/mL. Furthermore, AgNPs at different concentrations removed DPPH and H2O2 at an IC50 value of 13.54 µg/mL. Also, AgNPs at 3 mg/mL showed remarkable DNA fragmentation in all bacterial strains except Enterococcus faecalis. The phytochemical analysis showed the presence of different active organic components in the plant extract, which concluded that rutin was 88.3 mg/g, garlic acid was 70.4 mg/g, and tannic acid was 23.7 mg/g. Finally, AgNPs concentrations in the range of 3-6 mg/mL showed decreased expression of two of the fundamental genes necessary for biofilm formation within Staphylococcus aureus, fnbA (6 folds), and Cna (12.5 folds) when compared with the RecA gene, which decreased by one-fold when compared with the control sample. These two genes were submitted with NCBI accession numbers [OR682119] and [OR682118], respectively. Conclusions: The findings from this study indicate that biosynthesized AgNPs from Solanum lycopersicum exhibit promising antimicrobial and antioxidant properties against UTI pathogens, including strains resistant to multiple antibiotics. This suggests their potential as an effective alternative treatment for UTIs. Further research is warranted to fully understand the mechanisms of action and to explore the therapeutic applications of these nanoparticles in combating UTIs.

Redirecting pantoprazole as a metallo-beta-lactamase inhibitor in carbapenem-resistant Klebsiella pneumoniae.

The development of resistance to carbapenems in Klebsiella pneumoniae due to the production of metallo-ß-lactamases (MBLs) is a critical public health problem because carbapenems are the last-resort drugs used for treating severe infections of extended-spectrum ß-lactamases (ESBLs) producing K. pneumoniae. Restoring the activity of carbapenems by the inhibition of metallo-ß-lactamases is a valuable approach to combat carbapenem resistance. In this study, two well-characterized clinical multidrug and carbapenem-resistant K. pneumoniae isolates were used. The sub-inhibitory concentrations of pantoprazole and the well-reported metallo-ß-lactamase inhibitor captopril inhibited the hydrolytic activities of metallo-ß-lactamases, with pantoprazole having more inhibiting activities. Both drugs, when used in combination with meropenem, exhibited synergistic activities. Pantoprazole could also downregulate the expression of the metallo-ß-lactamase genes bla NDM and bla VIM. A docking study revealed that pantoprazole could bind to and chelate zinc ions of New Delhi and Verona integron-encoded MBL (VIM) enzymes with higher affinity than the control drug captopril and with comparable affinity to the natural ligand meropenem, indicating the significant inhibitory activity of pantoprazole against metallo-ß-lactamases. In conclusion, pantoprazole can be used in combination with meropenem as a new strategy for treating serious infections caused by metallo-ß-lactamases producing K. pneumoniae.

Computational prediction of protein interactions in single cells by proximity sequencing.

Proximity sequencing (Prox-seq) simultaneously measures gene expression, protein expression and protein complexes on single cells. Using information from dual-antibody binding events, Prox-seq infers surface protein dimers at the single-cell level. Prox-seq provides multi-dimensional phenotyping of single cells in high throughput, and was recently used to track the formation of receptor complexes during cell signaling and discovered a novel interaction between CD9 and CD8 in naïve T cells. The distribution of protein abundance can affect identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model of Prox-seq and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq data, which resulted in more accurate and robust quantification of protein complexes. Finally, our Prox-seq model offers a simple way to investigate the behavior of Prox-seq data under various biological conditions and guide users toward selecting the best analysis method for their data.

A 3D scaling law for supravalvular aortic stenosis suited for stethoscopic auscultations.

In this study a frequency scaling law for 3D anatomically representative supravalvular aortic stenosis (SVAS) cases is proposed. The law is uncovered for stethoscopy's preferred auscultation range (70-120 Hz). LES simulations are performed on the CFD solver Fluent, leveraging Simulia's Living Heart Human Model (LHHM), modified to feature hourglass stenoses that range between 30 to 80 percent (mild to severe) in addition to the descending aorta. For physiological hemodynamic boundary conditions the Windkessel model is implemented via a UDF subroutine. The flow-generated acoustic signal is then extracted using the FW-H model and analyzed using FFT. A preferred receiver location that matches clinical practice is confirmed (right intercostal space) and a correlation between the degree of stenosis and a corresponding acoustic frequency is obtained. Five clinical auscultation signals are tested against the scaling law, with the findings interpreted in relation to the NHS classification of stenosis and to the assessments of experienced cardiologists. The scaling law is thus shown to succeed as a potential quantitative decision-support tool for clinicians, enabling them to reliably interpret stethoscopic auscultations for all degrees of stenosis, which is especially useful for moderate degrees of SVAS. Computational investigation of more complex stenotic cases would enhance the clinical relevance of this proposed scaling law, and will be explored in future research.

Discovery of new thymol-3,4-disubstituted thiazole hybrids as dual COX-2/5-LOX inhibitors with in vivo proof.

New thymol-3,4-disubstitutedthiazole hybrids were synthesised as dual COX-2/5-LOX inhibitors. Compounds 6b, 6d, 6e, and 6f displayed in vitro inhibitory activity against COX-2 (IC50= 0.037, 0.042, 0.046, and 0.039 µM) nearly equal to celecoxib (IC50= 0.045 µM). 6b, 6d, and 6f showed SI (379, 341, and 374, respectively) higher than that of celecoxib (327). 6a-l elicited in vitro 5-LOX inhibitory activity higher than quercetin. 6a-f, 6i-l, 7a, and 7c possessed in vivo inhibition of formalin induced paw edoema higher than celecoxib. 6a, 6b, 6f, 6h-l, and 7b showed gastrointestinal safety profile as celecoxib and diclofenac sodium in the population of fasted rats. Induced fit docking and molecular dynamics simulation predicted good fitting of 6b and 6f without changing the packing and globularity of the apo protein. In conclusion, 6b and 6f achieved the target goal as multitarget inhibitors of inflammation.

Reliable Prediction of Discharge Disposition Following Cervical Spine Surgery With Ensemble Machine Learning and Validation on a National Cohort.

STUDY DESIGN: A retrospective cohort study. OBJECTIVE: The purpose of this study is to develop a machine learning algorithm to predict nonhome discharge after cervical spine surgery that is validated and usable on a national scale to ensure generalizability and elucidate candidate drivers for prediction. SUMMARY OF BACKGROUND DATA: Excessive length of hospital stay can be attributed to delays in postoperative referrals to intermediate care rehabilitation centers or skilled nursing facilities. Accurate preoperative prediction of patients who may require access to these resources can facilitate a more efficient referral and discharge process, thereby reducing hospital and patient costs in addition to minimizing the risk of hospital-acquired complications. METHODS: Electronic medical records were retrospectively reviewed from a single-center data warehouse (SCDW) to identify patients undergoing cervical spine surgeries between 2008 and 2019 for machine learning algorithm development and internal validation. The National Inpatient Sample (NIS) database was queried to identify cervical spine fusion surgeries between 2009 and 2017 for external validation of algorithm performance. Gradient-boosted trees were constructed to predict nonhome discharge across patient cohorts. The area under the receiver operating characteristic curve (AUROC) was used to measure model performance. SHAP values were used to identify nonlinear risk factors for nonhome discharge and to interpret algorithm predictions. RESULTS: A total of 3523 cases of cervical spine fusion surgeries were included from the SCDW data set, and 311,582 cases were isolated from NIS. The model demonstrated robust prediction of nonhome discharge across all cohorts, achieving an area under the receiver operating characteristic curve of 0.87 (SD=0.01) on both the SCDW and nationwide NIS test sets. Anterior approach only, age, elective admission status, Medicare insurance status, and total Elixhauser Comorbidity Index score were the most important predictors of discharge destination. CONCLUSIONS: Machine learning algorithms reliably predict nonhome discharge across single-center and national cohorts and identify preoperative features of importance following cervical spine fusion surgery.

Imparting aromaticity to 2-pyridone derivatives by O-alkylation resulted in new competitive and non-competitive PIM-1 kinase inhibitors with caspase-activated apoptosis.

New aromatic O-alkyl pyridine derivatives were designed and synthesised as Proviral Integration Moloney (PIM)-1 kinase inhibitors. 4c and 4f showed potent in vitro anticancer activity against NFS-60, HepG-2, PC-3, and Caco-2 cell lines and low toxicity against normal human lung fibroblast Wi-38 cell line. Moreover, 4c and 4f induced apoptosis in the four tested cancer cell lines with high percentage. In addition, 4c and 4f significantly induced caspase 3/7 activation in HepG-2 cell line. Furthermore, 4c and 4f showed potent PIM-1 kinase inhibitory activity with IC50 = 0.110, 0.095 µM, respectively. Kinetic studies indicated that 4c and 4f were both competitive and non-competitive inhibitors for PIM-1 kinase enzyme. In addition, in silico prediction of physiochemical properties, pharmacokinetic profile, ligand efficiency, ligand lipophilic efficiency, and induced fit docking studies were consistent with the biological and kinetic studies, and predicted that 4c and 4f could act as PIM-1 kinase competitive non-adenosine triphosphate (ATP) mimetics with drug like properties.

Novel indolinone-tethered benzothiophenes as anti-tubercular agents against MDR/XDR M. tuberculosis: Design, synthesis, biological evaluation and in vivo pharmacokinetic study.

Joining the global effort to eradicate tuberculosis, one of the deadliest infectious killers in the world, we disclose in this paper the design and synthesis of new indolinone-tethered benzothiophene hybrids 6a-i and 7a-i as potential anti-tubercular agents. The MICs were determined in vitro for the synthesized compounds against the sensitive M. tuberculosis strain ATCC 25177. Potent compounds 6b, 6d, 6f, 6h, 7a, 7b, 7d, 7f, 7h and 7i were furtherly assessed versus resistant MDR-TB and XDR-TB. Structure activity relationship investigation of the synthesized compounds was illustrated, accordingly. Superlative potency was unveiled for compound 6h (MIC = 0.48, 1.95 and 7.81 µg/mL for ATCC 25177 sensitive TB strain, resistant MDR-TB and XDR-TB, respectively). Moreover, validated in vivo pharmacokinetic study was performed for the most potent derivative 6h revealing superior pharmacokinetic profile over the reference drug. For further exploration of the anti-tubercular mechanism of action, molecular docking was carried out for the former compound in DprE1 active site as one of the important biological targets of TB. The binding mode and the docking score uncovered exceptional binding when compared to the co-crystallized ligand suggesting that it maybe the underlying target for its outstanding anti-tubercular potency.

TRIBAL: Tree Inference of B cell Clonal Lineages.

B cells are a critical component of the adaptive immune system, responsible for producing antibodies that help protect the body from infections and foreign substances. Single cell RNA-sequencing (scRNA-seq) has allowed for both profiling of B cell receptor (BCR) sequences and gene expression. However, understanding the adaptive and evolutionary mechanisms of B cells in response to specific stimuli remains a significant challenge in the field of immunology. We introduce a new method, TRIBAL, which aims to infer the evolutionary history of clonally related B cells from scRNA-seq data. The key insight of TRIBAL is that inclusion of isotype data into the B cell lineage inference problem is valuable for reducing phylogenetic uncertainty that arises when only considering the receptor sequences. Consequently, the TRIBAL inferred B cell lineage trees jointly capture the somatic mutations introduced to the B cell receptor during affinity maturation and isotype transitions during class switch recombination. In addition, TRIBAL infers isotype transition probabilities that are valuable for gaining insight into the dynamics of class switching. Via in silico experiments, we demonstrate that TRIBAL infers isotype transition probabilities with the ability to distinguish between direct versus sequential switching in a B cell population. This results in more accurate B cell lineage trees and corresponding ancestral sequence and class switch reconstruction compared to competing methods. Using real-world scRNA-seq datasets, we show that TRIBAL recapitulates expected biological trends in a model affinity maturation system. Furthermore, the B cell lineage trees inferred by TRIBAL were equally plausible for the BCR sequences as those inferred by competing methods but yielded lower entropic partitions for the isotypes of the sequenced B cell. Thus, our method holds the potential to further advance our understanding of vaccine responses, disease progression, and the identification of therapeutic antibodies.

ATAT: Automated Tissue Alignment and Traversal in Spatial Transcriptomics with Self-Supervised Learning.

Spatial transcriptomics (ST) has enhanced RNA analysis in tissue biopsies, but interpreting these data is challenging without expert input. We present Automated Tissue Alignment and Traversal (ATAT), a novel computational framework designed to enhance ST analysis in the context of multiple and complex tissue architectures and morphologies, such as those found in biopsies of the gastrointestinal tract. ATAT utilizes self-supervised contrastive learning on hematoxylin and eosin (H&E) stained images to automate the alignment and traversal of ST data. This approach addresses a critical gap in current ST analysis methodologies, which rely heavily on manual annotation and pathologist expertise to delineate regions of interest for accurate gene expression modeling. Our framework not only streamlines the alignment of multiple ST samples, but also demonstrates robustness in modeling gene expression transitions across specific regions. Additionally, we highlight the ability of ATAT to traverse complex tissue topologies in real-world cases from various individuals and conditions. Our method successfully elucidates differences in immune infiltration patterns across the intestinal wall, enabling the modeling of transcriptional changes across histological layers. We show that ATAT achieves comparable performance to the state-of-the-art method, while alleviating the burden of manual annotation and enabling alignment of tissue samples with complex morphologies.

AI-Assisted Cotton Grading: Active and Semi-Supervised Learning to Reduce the Image-Labelling Burden.

The assessment of food and industrial crops during harvesting is important to determine the quality and downstream processing requirements, which in turn affect their market value. While machine learning models have been developed for this purpose, their deployment is hindered by the high cost of labelling the crop images to provide data for model training. This study examines the capabilities of semi-supervised and active learning to minimise effort when labelling cotton lint samples while maintaining high classification accuracy. Random forest classification models were developed using supervised learning, semi-supervised learning, and active learning to determine Egyptian cotton grade. Compared to supervised learning (80.20-82.66%) and semi-supervised learning (81.39-85.26%), active learning models were able to achieve higher accuracy (82.85-85.33%) with up to 46.4% reduction in the volume of labelled data required. The primary obstacle when using machine learning for Egyptian cotton grading is the time required for labelling cotton lint samples. However, by applying active learning, this study successfully decreased the time needed from 422.5 to 177.5 min. The findings of this study demonstrate that active learning is a promising approach for developing accurate and efficient machine learning models for grading food and industrial crops.

Protective effect of vitamin C against thiamethoxam-induced toxicity in male rats.

Background: Thiamethoxam (THM) is a neonicotinoid insecticide used to control different insect pests on fruits, vegetables, and field crops. The misuse and continuous exposure to THM cause many harmful effects on health and the reproductive system. Aim: This work aims to investigate the efficiency of vitamin C (vit C) in reducing or eliminating the harmful effects of THM on the testes, liver, and kidney of male rats. Methods: Forty-eight sexually mature male Wister albino rats (weight: 170-190 g; age: 10-11 weeks) were randomly allocated into six groups (8 males/group). The control group was orally given distilled water, vit C group was orally treated with 200 mg/kg b.wt of vit C, group 1/10 of THM LD50 orally treated with 156.3 mg/kg b.wt of THM, group 1/20 of THM LD50 orally treated with 78.15 mg/kg b.wt of THM, group 1/10 of THM LD50 + vit C orally treated with 156.3 mg/kg b.wt of THM + 200 mg/kg b.wt of vit C, and group 1/20 of THM LD50 + vit C orally treated with 78.15 mg/kg b.wt of THM + 200 mg/kg b.wt of vit C. All groups were treated for five days per week for a whole period of 58 days. Blood samples were collected at the end of the experiment, and serum was extracted for liver and kidney functions and antioxidant measurements. Reproductive organs (testis, epididymis, and seminal vesicles) were collected and weighed at the end of the experiment. Results: The results showed that groups exposed to 1/10 and 1/20 of THM LD50 significantly (p < 0.05) decreased the body weight, the reproductive organ weights (testis, epididymis, and seminal vesicles), spermatid count, sperm (count and motility), and testosterone concentration with an increase in abnormalities. In addition, the groups exposed to THM showed a decrease in protein concentration, albumin, and globulin, and caused an increase in glucose concentration. The activities of alkaline phosphatase (ALP), alanine transaminase (ALT), aspartate transaminase (AST), creatinine, urea, and malondialdehyde (MDA) were increased while caused decrease in total antioxidant capacity (TAC) due to exposure to THM. The co-administration of vit C with HM modulated the harmful effects of the insecticide on testicular, liver, and kidney parameters, which confirmed in histopathological examination of testis. Groups orally treated with vit C showed a significant increase in spermatogenesis, spermatid numbers, and the weight of seminal vesicles. Conclusion: This study showed the importance of vit C in reducing toxic effects from exposure to THM. Accordingly, the intake of vit C by individuals who regularly handle this insecticide will be beneficial in reducing the adverse effects that may occur in the liver and kidney.

Preparation and characterization of a novel nanocomposite based on MnCr-layered double oxide and CoFe2O4 spinel ferrite for methyl orange adsorption.

Herein, the adsorption of methyl orange (MO), a dangerous anionic dye, from an aqueous solution was investigated using a novel magnetic nanocomposite adsorbent. A nanocomposite entitled manganese chromium-layered double oxide/cobalt spinel ferrite, (MnCr)-LDO5wt.%/CoFe2O4, which links the interlayer structural characteristics of layered double oxides (LDOs) with the magnetic properties of spinel ferrites (SFs) was synthesized using the eco-friendly co-precipitation technique. Determination of structural parameters, crystallite size, and micro-strain was done using X-ray diffraction (XRD) analysis. Transmission electron microscopy (TEM) was used to determine grain shape and size. Surface analysis was performed using X-ray photoelectron spectroscopy (XPS) to identify elements and oxidation states present in the prepared nanocomposite. Vibrating sample magnetometer (VSM) was utilized to examine the magnetic characteristic. A comprehensive comparative study about the effectiveness and durability of CoFe2O4 and (MnCr)5wt.%/CoFe2O4 as nanoadsorbents for MO was conducted. Numerous variables, including contact time, MO concentration, adsorbent dosage, and pH were tested for their effects on the adsorption removal percentages. The findings showed that the maximum removal percentage was 86.1% for 25 ppm of MO was for 0.1 g/100 mL of (MnCr)-LDO5wt.%/CoFe2O4 at pH = 3. Investigations of isotherms and kinetics were conducted under batch conditions. The Langmuir isotherm matched the experimental data, for both nanoadsorbents, quite well due to the homogeneous distribution of active sites. Adsorption kinetics data were found to be compatible with intra-particle diffusion and pseudo-second order models for CoFe2O4 and (MnCr)5wt.%/CoFe2O4, respectively. A total of five adsorption-desorption cycles were performed to determine the prepared adsorbents' recyclable nature.

Percutaneous coronary stent implantation in children and young infants following surgical repair of congenital heart disease.

Background: Coronary artery stent implantation (CSI) in the pediatric population is rare. Only a few reports were published on managing postoperative coronary artery obstruction using coronary stents following surgical repair of congenital heart diseases (CHD). This study aimed to analyze the feasibility, indications, procedural technique, risk factors, and short-term outcomes of CSI after pediatric cardiac surgery. Methods: In this retrospective cohort study, we reviewed all pediatric patients who underwent surgical repair of CHD requiring postoperative CSI in two cardiac centers (King Abdulaziz University Hospital and King Faisal Specialist Hospital and Research Center) between 2012 and 2022. Survival to hospital discharge was the study's primary outcome. The secondary outcomes included procedural success, duration of mechanical ventilation, intensive care unit (ICU) stay, hospital stay, need for coronary reintervention, and late mortality. A descriptive analysis was performed for the collected data from the patients' medical records. Results: Eleven patients who underwent postoperative CSI were identified. The most common anatomic diagnosis was congenital aortic valve stenosis. All patients underwent cardiac catheterization on extracorporeal membrane oxygenation support except one patient, who presented with chest pain after cardiac surgery. Procedural success was achieved in all patients with excellent revascularization documented by post-procedural angiograms. Both patients who had late coronary events after cardiac surgery survived hospital discharge. There was no in-hospital mortality among the two patients who required stenting of only the right coronary artery. The four patients who required more than 120 minutes to complete the procedure had early mortality. After CSI, the median duration of mechanical ventilation and ICU stay was 12 and 17 days, respectively. Six patients (54.5%) survived hospital discharge post-CSI; they did not require re-intervention during the follow-up period (38-1,695 days). Conclusions: CSI in pediatric patients can be performed with excellent procedural success for treating coronary artery stenosis after cardiac surgery. It could be considered a potential treatment strategy for this population.

Computational prediction of protein interactions on single cells by proximity sequencing.

Proximity sequencing (Prox-seq) measures gene expression, protein expression, and protein complexes at the single cell level, using information from dual-antibody binding events and a single cell sequencing readout. Prox-seq provides multi-dimensional phenotyping of single cells and was recently used to track the formation of receptor complexes during inflammatory signaling in macrophages and to discover a new interaction between CD9/CD8 proteins on naïve T cells. The distribution of protein abundance affects identification of protein complexes in a complicated manner in dual-binding assays like Prox-seq. These effects are difficult to explore with experiments, yet important for accurate quantification of protein complexes. Here, we introduce a physical model for protein dimer formation on single cells and computationally evaluate several different methods for reducing background noise when quantifying protein complexes. Furthermore, we developed an improved method for analysis of Prox-seq single-cell data, which resulted in more accurate and robust quantification of protein complexes. Finally, our model offers a simple way to investigate the behavior of Prox-seq under various biological conditions and guide users toward selecting the best analysis method for their data.

Osseous Metastases in Thyroid Cancer: Unveiling Risk Factors, Disease Outcomes, and Treatment Impact.

Bone is the second most common site of metastasis in patients with thyroid cancer (TC) and dramatically impacts overall survival and quality of life with no definitive cure, yet there is no extensive study of the demographic and clinical risk factors in the recent literature. Data regarding 120,754 TC patients with bone metastasis were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate analyses were used to identify the risk factors of bone metastasis occurring in various histologies of TC. Cox regression was performed to analyze the influence of bone metastasis on overall survival. Hazard ratios were computed to analyze the association between bone metastasis and the primary outcomes. Of the 120,754 records collected from the SEER database from 2000 to 2019, 976 (0.8%) presented with bone metastasis, with occurrence being the greatest in patients of age ≥ 55 years (OR = 5.63, 95%CI = 4.72-6.71), males (OR = 2.60, 95%CI = 2.27-2.97), Blacks (OR = 2.38, 95%CI = 1.95-2.9) and Asian or Pacific Islanders (OR = 1.90, 95%CI = 1.58-2.27), and single marital status. TC patients presenting with bone metastasis (HR = 2.78, 95%CI = 2.34-3.3) or concurrent bone and brain metastases (HR = 1.62, 95%CI = 1.03-2.55) had a higher mortality risk. Older age, gender, race, and single marital status were associated with bone metastasis and poorer prognosis in TC patients at initial diagnosis. Understanding such risk factors can potentially assist clinicians in making early diagnoses and personalized treatment plans, as well as researchers in developing more therapeutic protocols.

Deploying synthetic coevolution and machine learning to engineer protein-protein interactions.

Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain-affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. The integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.

Management of metabolic syndrome by nutraceuticals prepared from chitosan and ferulic acid with or without beta-sitosterol and their nanoforms.

Dyslipidemia, steatohepatitis and insulin resistance are among the components of metabolic syndrome (MS). Nutraceuticals containing chitosan, beta-sitosterol and/or ferulic acid and their nanostructures could have a potential role for management of MS. The aim of the present study was to assess the efficacy of the aforementioned nutraceuticals in treatment of MS in rat and their interaction with atorvastatin, a hypolipidemic drug. The two nutraceuticals and their nanostructures were prepared and the nanostructures were assessed by transmission electron microscope and Fourier-Transform Infra-red Spectrometry. MS was induced in rats by feeding high fructose-high fat diet (HFFD). Different groups of rats fed HFFD and treated with the different nutraceuticals, atorvastatin and atorvastatin in combination with different nutraceuticals, control fed on balanced diet and control consumed HFFD without treatments were run. Plasma glucose, lipid profile, aminotransferases activity, total antioxidant capacity, malondialdehyde, urea, creatinine, insulin, high sensitivity C-reactive protein, and adiponectin were assessed along with calculation of insulin resistance. Liver fat and histopathology were investigated. All nutraceuticals in original and nanostructures showed beneficial effects in the treatment of MS, superiority was ascribed to nutraceuticals composed of chitosan and ferulic acid in both forms. A more promising treatment of MS belonged to atorvastatin administered with the different nutraceuticals.

Factors affecting the outcomes after bidirectional Glenn shunt: two decades of experience from a tertiary referral center.

BACKGROUND: Despite the improved management of patients with a single ventricle, the long-term outcomes are not optimal. We reported the outcomes of the bidirectional Glenn procedure (BDG) and factors affecting the length of hospital stay, operative mortality, and Nakata index before Fontan completion. RESULTS: This retrospective study included 259 patients who underwent BDG shunt from 2002 to 2020. The primary study outcomes were operative mortality, duration of hospital stay, and Nakata index before Fontan. Mortality occurred in 10 patients after BDG shunt (3.86%). By univariable logistic regression analysis, postoperative mortality after BDG shunt was associated with high preoperative mean pulmonary artery pressure (OR: 1.06 (95% CI 1.01-1.23); P = 0.02). The median duration of hospital stay after BDG shunt was 12 (9-19) days. Multivariable analysis indicated that Norwood palliation before BDG shunt was significantly associated with prolonged hospital stay (ß: 0.53 (95% CI 0.12-0.95), P = 0.01). Fontan completion was performed in 144 patients (50.03%), and the pre-Fontan Nataka index was 173 (130.92-225.34) mm2/m2. Norwood palliation (ß: - 0.61 (95% CI 62.63-20.18), P = 0.003) and preoperative saturation (ß: - 2.38 (95% CI - 4.49-0.26), P = 0.03) were inversely associated with pre-Fontan Nakata index in patients who had Fontan completion. CONCLUSIONS: BDG had a low mortality rate. Pulmonary artery pressure, Norwood palliation, cardiopulmonary bypass time, and pre-BDG shunt saturation were key factors associated with post-BDG outcomes in our series.

Tunable multichannel Fibonacci one-dimensional terahertz photonic crystal filter.

This paper proposes a multichannel terahertz optical filter based on a one-dimensional photonic crystal with a third-order Fibonacci structure, including a bulk Dirac semimetal. The tuning of the optical properties of the proposed structure has been theoretically studied as a function of the Dirac semimetals' Fermi energy. Furthermore, the effects of the Fibonacci structure's periodic number and light's incident angle on optical channels were investigated. The results reveal that changes in the Fermi energy and incident angle remarkably affect the frequency and transmission of the optical channels. Additionally, the number of optical channels increases by increasing the periodic number of the Fibonacci structure.