C-X-C motif chemokine ligand 12-C-X-C chemokine receptor type 4 signaling axis in cancer and the development of chemotherapeutic molecules.

Chemokines are small, secreted cytokines crucial in the regulation of a variety of cell functions. The binding of chemokine C-X-C motif chemokine ligand 12 (CXCL12) (stromal cell-derived factor 1) to a G-protein-coupled receptor C-X-C chemokine receptor type 4 (CXCR4) triggers downstream signaling pathways with effects on cell survival, proliferation, chemotaxis, migration, and gene expression. Intensive and extensive investigations have provided evidence suggesting that the CXCL12-CXCR4 axis plays a pivotal role in tumor development, survival, angiogenesis, metastasis, as well as in creating tumor microenvironment, thus implying that this axis is a potential target for the development of cancer therapies. The structures of CXCL12 and CXCR4 have been resolved with experimental methods such as X-ray crystallography, NMR, or cryo-EM. Therefore, it is possible to apply structure-based computational approaches to discover, design, and modify therapeutic molecules for cancer treatments. Here, we summarize the current understanding of the roles played by the CXCL12-CXCR4 signaling axis in cellular functions linking to cancer progression and metastasis. This review also provides an introduction to protein structures of CXCL12 and CXCR4 and the application of computer simulation and analysis in understanding CXCR4 activation and antagonist binding. Furthermore, examples of strategies and current progress in CXCL12-CXCR4 axis-targeted development of therapeutic anticancer inhibitors are discussed.

Overview of clinical status, treatment, and long-term outcomes of pediatric autosomal-dominant polycystic kidney disease: a nationwide survey in Taiwan.

This retrospective study investigated the incidence, medication use, and outcomes in pediatric autosomal-dominant polycystic kidney disease (ADPKD) using Taiwan's National Health Insurance Research Database (NHIRD). A 1:4 matched control group of individuals included in the NHIRD during the same period was used for comparative analyses. A total of 621 pediatric patients were identified from 2009 to 2019 (mean age, 9.51 ± 6.43 years), and ADPKD incidence ranged from 2.32 to 4.45 per 100,000 individuals (cumulative incidence, 1.26-1.57%). The incidence of newly developed hypertension, anti-hypertensive agent use, nephrolithiasis, and proteinuria were significantly higher in the ADPKD group than the non-ADPKD group (0.7 vs. 0.04, 2.26 vs. 0.30, 0.4 vs. 0.02, and 0.73 vs. 0.05 per 100 person-years, respectively). The adjusted hazard ratios for developing hypertension, proteinuria, nephrolithiasis and anti-hypertensive agent use in cases of newly-diagnosed pediatric ADPKD were 12.36 (95% CI 4.92-31.0), 13.49 (95% CI 5.23-34.79), 13.17 (95% CI 2.48-69.98), and 6.38 (95% CI 4.12-9.89), respectively. The incidence of congenital cardiac defects, hematuria, urinary tract infections, gastrointestinal diverticulosis, dyslipidemia, and hyperuricemia were also higher in the ADPKD group. Our study offers valuable insights into the epidemiology of pediatric ADPKD in Taiwan and could help in formulating guidelines for its appropriate management.

Anti-oxidative and anti-inflammatory effects of Ginkgo biloba extract (EGb761) on hindlimb skeletal muscle ischemia-reperfusion injury in rats.

In posterior spine surgery, retractors exert pressure on paraspinal muscles, elevating intramuscular pressure and compromising blood flow, potentially causing muscle injury during ischemia-reperfusion. Ginkgo biloba extract (EGb 761), known for its antioxidant and free radical scavenging properties and its role in treating cerebrovascular diseases, is investigated for its protective effects against muscle ischemia-reperfusion injury in vitro and in vivo. Animals were randomly divided into the control group, receiving normal saline, and experimental groups, receiving varying doses of EGb761 (25/50/100/200 mg/kg). A 2-h hind limb tourniquet-induced ischemia was followed by reperfusion. Blood samples collected pre-ischemia and 24 h post-reperfusion, along with muscle tissue samples after 24 h, demonstrated that EGb761 at 1000 µg/mL effectively inhibited IL-6 and TNF-α secretion in RAW 264.7 cells without cytotoxicity. EGb761 significantly reduced nitric oxide (NO) and malondialdehyde (MDA) levels, myeloperoxidase (MPO) activity, and increased glutathione (GSH) levels compared to the control after 24 h. Muscle tissue sections revealed more severe damage in the control group, indicating EGb761's potential in mitigating inflammatory responses and oxidative stress during ischemia-reperfusion injury, effectively protecting against muscle damage.

Erector Spinae Plane Block Versus Thoracolumbar Interfascial Plane Block in Lumbar Spine Surgery: A Meta-Analysis of Randomized Controlled Trials.

STUDY DESIGN: Meta-analysis. OBJECTIVE: To compare the effectiveness of postoperative pain control between erector spinae plane block (ESPB) and thoracolumbar interfascial plane (TLIP) block in lumbar spine surgery. METHODS: PubMed, Embase, and MEDLINE electronic databases were searched for articles containing randomized controlled trials (RCTs) published between January 1900 and January 2024. We extracted the postoperative mean pain score, the first 24-h postoperative morphine consumption, and their standard deviation from the included studies. Meta-analysis was performed using the functions available in the metafor package in R software. We pooled continuous variables using an inverse variance method with a random-effects model and summarized them as standardized mean differences. RESULTS: Five RCTs that directly compared the ESPB and TLIP block in lumbar spine surgery were included, enrolling 432 participants randomly into the two groups with 216 participants in each group. The pooled analyses showed that there was no significant difference between the ESPB and TLIP groups in terms of lower pain scores during the early (1 h) (standardized mean difference [SMD] -1.49, 95% confidence interval [CI], -3.10; 0.11), middle (12 h) (SMD -3.12, 95% CI, -6.86; 0.61), and late (24 h) (SMD -1.38, 95% CI, -3.01; 0.24) postoperative periods. There was also no significant difference in the first 24-h postoperative morphine equivalent consumption between the ESPB and TLIP groups (SMD -0.46 mg, 95% CI -1.23; 0.31). CONCLUSION: No significant difference was observed between the ESPB and TLIP block in terms of postoperative pain control and 24-h morphine equivalent consumption for lumbar spine surgery.

Integrating Clinical Variability into PBPK Models for Virtual Bioequivalence of Single and Multiple Doses of Tofacitinib Modified-Release Dosage Form.

Tofacitinib is a potent, selective inhibitor of the Janus kinase (JAK) family of kinases with a high degree of selectivity within the human genome's set of protein kinases. Currently approved formulations for tofacitinib citrate are immediate-release (IR) tablets, modified-release (MR) tablets, and IR solution. A once daily MR microsphere formulation was developed for use in pediatric patients. Demonstration of bioequivalence (BE) between the 10 mg once daily (q.d.) MR microsphere formulation and 5 mg twice daily (b.i.d.) IR solution is needed to enable the exposure-response analyses-based bridging to support regulatory approval. To assess BE between MR microsphere and IR solution, an innovative approach was utilized with physiologically-based pharmacokinetic (PBPK) virtual BE trials (VBE) in lieu of a clinical BE trial. A PBPK model was developed to characterize the absorption of different formulations of tofacitinib using Simcyp ADAM module. VBE trials were conducted by simulating PK profiles using the verified PBPK model and integrating the clinically observed intrasubject coefficient of variation (ICV) where BE was assessed with a predetermined sample size and prespecified criteria. The VBE trials demonstrated BE between IR solution 5 mg b.i.d. and MR microsphere 10 mg q.d. after a single dose on day 1 and after multiple doses on day 5. This research presents an innovative approach that incorporates clinically observed ICV in PBPK model-based VBE trials, which could reduce unnecessary drug exposure to healthy volunteers and streamline new formulation development strategies.

Reinforcement learning for closed-loop regulation of cardiovascular system with vagus nerve stimulation: a computational study.

Objective. Vagus nerve stimulation (VNS) is being investigated as a potential therapy for cardiovascular diseases including heart failure, cardiac arrhythmia, and hypertension. The lack of a systematic approach for controlling and tuning the VNS parameters poses a significant challenge. Closed-loop VNS strategies combined with artificial intelligence (AI) approaches offer a framework for systematically learning and adapting the optimal stimulation parameters. In this study, we presented an interactive AI framework using reinforcement learning (RL) for automated data-driven design of closed-loop VNS control systems in a computational study.Approach.Multiple simulation environments with a standard application programming interface were developed to facilitate the design and evaluation of the automated data-driven closed-loop VNS control systems. These environments simulate the hemodynamic response to multi-location VNS using biophysics-based computational models of healthy and hypertensive rat cardiovascular systems in resting and exercise states. We designed and implemented the RL-based closed-loop VNS control frameworks in the context of controlling the heart rate and the mean arterial pressure for a set point tracking task. Our experimental design included two approaches; a general policy using deep RL algorithms and a sample-efficient adaptive policy using probabilistic inference for learning and control.Main results.Our simulation results demonstrated the capabilities of the closed-loop RL-based approaches to learn optimal VNS control policies and to adapt to variations in the target set points and the underlying dynamics of the cardiovascular system. Our findings highlighted the trade-off between sample-efficiency and generalizability, providing insights for proper algorithm selection. Finally, we demonstrated that transfer learning improves the sample efficiency of deep RL algorithms allowing the development of more efficient and personalized closed-loop VNS systems.Significance.We demonstrated the capability of RL-based closed-loop VNS systems. Our approach provided a systematic adaptable framework for learning control strategies without requiring prior knowledge about the underlying dynamics.

ε-Neural Thompson Sampling of Deep Brain Stimulation for Parkinson Disease Treatment.

Deep Brain Stimulation (DBS) stands as an effective intervention for alleviating the motor symptoms of Parkinson's disease (PD). Traditional commercial DBS devices are only able to deliver fixed-frequency periodic pulses to the basal ganglia (BG) regions of the brain, i.e., continuous DBS (cDBS). However, they in general suffer from energy inefficiency and side effects, such as speech impairment. Recent research has focused on adaptive DBS (aDBS) to resolve the limitations of cDBS. Specifically, reinforcement learning (RL) based approaches have been developed to adapt the frequencies of the stimuli in order to achieve both energy efficiency and treatment efficacy. However, RL approaches in general require significant amount of training data and computational resources, making it intractable to integrate RL policies into real-time embedded systems as needed in aDBS. In contrast, contextual multi-armed bandits (CMAB) in general lead to better sample efficiency compared to RL. In this study, we propose a CMAB solution for aDBS. Specifically, we define the context as the signals capturing irregular neuronal firing activities in the BG regions (i.e., beta-band power spectral density), while each arm signifies the (discretized) pulse frequency of the stimulation. Moreover, an {\epsilon}-exploring strategy is introduced on top of the classic Thompson sampling method, leading to an algorithm called {\epsilon}-Neural Thompson sampling ({\epsilon}-NeuralTS), such that the learned CMAB policy can better balance exploration and exploitation of the BG environment. The {\epsilon}-NeuralTS algorithm is evaluated using a computation BG model that captures the neuronal activities in PD patients' brains. The results show that our method outperforms both existing cDBS methods and CMAB baselines.

Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions.

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. A General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) was employed to acquire two DTI (diffusion tensor imaging) sequences of the left knee on each child at 3T: an in-plane 2.0 × 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel; neither had an intersection gap. For image acquisition, a multi-band DTI with a fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 s/mm2) was utilized. The MR vendor-provided a commercially available DL model which was applied with 75% noise reduction settings to the same subject DTI sequences at different spatial resolutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for the femur and tibia at each spatial resolution. Differences were evaluated using Wilcoxon-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffusion metrics in femur and tibia using the 2 mm × 2 mm × 3 mm voxel dimension, there were no significant differences between tract count (p = 0.1, p = 0.14) tract volume (p = 0.1, p = 0.29) or tibial tract length (p = 0.16); femur tract length exhibited a significant difference (p < 0.01). All diffusion metrics (tract count, volume, length, and fractional anisotropy (FA)) derived from the DL-reconstructed scans, were significantly different from the non-denoised scan DTI metrics in both the femur and tibial physes using the 2 mm3 voxel size (p < 0.001). DL reconstruction resulted in a significant decrease in femorotibial FA for both voxel dimensions (p < 0.01). Leveraging denoising algorithms could address the drawbacks of lower signal-to-noise ratios (SNRs) associated with smaller voxel volumes and capitalize on their better spatial resolutions, allowing for more accurate quantification of diffusion metrics.

Xanthohumol, a prenylated chalcone, regulates lipid metabolism by modulating the LXRα/RXR-ANGPTL3-LPL axis in hepatic cell lines and high-fat diet-fed zebrafish models.

Angiopoietin-like 3 (ANGPTL3) acts as an inhibitor of lipoprotein lipase (LPL), impeding the breakdown of triglyceride-rich lipoproteins (TGRLs) in circulation. Targeting ANGPTL3 is considered a novel strategy for improving dyslipidemia and atherosclerotic cardiovascular diseases (ASCVD). Hops (Humulus lupulus L.) contain several bioactive prenylflavonoids, including xanthohumol (Xan), isoxanthohumol (Isoxan), 6-prenylnaringenin (6-PN), and 8-prenylnaringenin (8-PN), with the potential to manage lipid metabolism. The aim of this study was to investigate the lipid-lowering effects of Xan, the effective prenylated chalcone in attenuating ANGPTL3 transcriptional activity, both in vitro using hepatic cells and in vivo using zebrafish models, along with exploring the underlying mechanisms. Xan (10 and 20 µM) significantly reduced ANGPTL3 mRNA and protein expression in HepG2 and Huh7 cells, leading to a marked decrease in secreted ANGPTL3 proteins via hepatic cells. In animal studies, orally administered Xan significantly alleviated plasma triglyceride (TG) and cholesterol levels in zebrafish fed a high-fat diet. Furthermore, it reduced hepatic ANGPTL3 protein levels and increased LPL activity in zebrafish models, indicating its potential to modulate lipid profiles in circulation. Furthermore, molecular docking results predicted that Xan exhibits a higher binding affinity to interact with liver X receptor α (LXRα) and retinoic acid X receptor (RXR) than their respective agonists, T0901317 and 9-Cis-retinoic acid (9-Cis-RA). We observed that Xan suppressed hepatic ANGPTL3 expression by antagonizing the LXRα/RXR-mediated transcription. These findings suggest that Xan ameliorates dyslipidemia by modulating the LXRα/RXR-ANGPTL3-LPL axis. Xan represents a novel potential inhibitor of ANGPTL3 for the prevention or treatment of ASCVD.

P. aeruginosa CtpA protease adopts a novel activation mechanism to initiate the proteolytic process.

During bacterial cell growth, hydrolases cleave peptide cross-links between strands of the peptidoglycan sacculus to allow new strand insertion. The Pseudomonas aeruginosa carboxyl-terminal processing protease (CTP) CtpA regulates some of these hydrolases by degrading them. CtpA assembles as an inactive hexamer composed of a trimer-of-dimers, but its lipoprotein binding partner LbcA activates CtpA by an unknown mechanism. Here, we report the cryo-EM structures of the CtpA-LbcA complex. LbcA has an N-terminal adaptor domain that binds to CtpA, and a C-terminal superhelical tetratricopeptide repeat domain. One LbcA molecule attaches to each of the three vertices of a CtpA hexamer. LbcA triggers relocation of the CtpA PDZ domain, remodeling of the substrate binding pocket, and realignment of the catalytic residues. Surprisingly, only one CtpA molecule in a CtpA dimer is activated upon LbcA binding. Also, a long loop from one CtpA dimer inserts into a neighboring dimer to facilitate the proteolytic activity. This work has revealed an activation mechanism for a bacterial CTP that is strikingly different from other CTPs that have been characterized structurally.

Surgical excision and radiotherapy for brain metastasis from colorectal cancer: How frailty and comorbidity indices influence outcome.

The incidence of brain metastasis (BM) from colorectal cancer (CRC) is increasing. This study aims to identify the clinical prognosticators and evaluate the prognostic validity of common comorbidity indices in patients with BM from CRC. This retrospective single-center study analyzed 93 patients with BM from CRC who received surgical excision and/or radiotherapy. The clinical characteristics and prognostic indices including the 5-item modified frailty index (mFI-5) and prognostic nutritional index (PNI) were calculated from the collected patient data and analyzed. In this study, 66 (71.0%), 10 (10.8%), and 17 (18.3%) patients received whole-brain radiotherapy (WBRT) alone, surgery alone, and surgery plus WBRT, respectively. The median survival of all patients was 3.98 months (IQR: 1.74-7.99). The 2- and 3-year survival rates were 7.4% and 3.7%, respectively. Controlled primary tumor (p = 0.048), solitary BM (p = 0.001), surgery + radiation (p < 0.001), and greater PNI (p = 0.001) were independent predictors of favorable survival. In surgically treated patients, uncontrolled primary tumor (p = 0.006), presence of multiple BM (p < 0.001), and MFI-5 ≥ 2 (p = 0.038) were independent prognosticators. For patients who received WBRT, the presence of two (p = 0.004) or multiple (p < 0.001) BM and PNI (p < 0.001) were independent survival predictors MFI-5, multiple BM, and the status of the primary tumor were independent prognosticators for patients who underwent surgery for CRCBM. For patients who received WBRT, the PNI and the number of BM were independent survival predictors.

Deep Learning-Assisted Diffusion Tensor Imaging for Evaluation of the Physis and Metaphysis.

Diffusion tensor imaging of physis and metaphysis can be used as a biomarker to predict height change in the pediatric population. Current application of this technique requires manual segmentation of the physis which is time-consuming and introduces interobserver variability. UNET Transformers (UNETR) can be used for automatic segmentation to optimize workflow. Three hundred and eighty-five DTI scans from 191 subjects with mean age of 12.6 years ± 2.01 years were retrospectively used for training and validation. The mean Dice correlation coefficient was 0.81 for the UNETR model and 0.68 for the UNET. Manual extraction and segmentation took 15 min per volume, whereas both deep learning segmentation techniques took < 1 s per volume and were deterministic, always producing the same result for a given input. Intraclass correlation coefficient (ICC) for ROI-derived femur diffusion metrics was excellent for tract count (0.95), volume (0.95), and FA (0.97), and good for tract length (0.87). The results support the hypothesis that a hybrid UNETR model can be trained to replace the manual segmentation of physeal DTI images, therefore automating the process.

3D Size-Dependent Dynamic Instability Analysis of FG Cylindrical Microshells Subjected to Combinations of Periodic Axial Compression and External Pressure Using a Hermitian C2 Finite Layer Method Based on the Consistent Couple Stress Theory.

This work develops a three-dimensional (3D) weak formulation, based on the consistent couple stress theory (CCST), for analyzing the size-dependent dynamic instability behavior of simply-supported, functionally graded (FG) cylindrical microshells that are subjected to combinations of periodic axial compression and external pressure. In our formulation, the microshells are artificially divided into nl layers. The displacement components of each individual layer are selected as the primary variables, which are expanded as a double Fourier series in the in-plane domain and are interpolated with Hermitian C2 polynomials in the thickness direction. Incorporating the layer-wise displacement models into our weak formulation, we develop a Hermitian C2 finite layer method (FLM) for addressing the current issue. The accuracy and the convergence rate of our Hermitian C2 FLM are validated by comparing the solutions it produces with the accurate two-dimensional solutions of critical loads and critical pressures of FG cylindrical macroshells and single-walled carbon nanotubes, which were reported in the literature. The numerical results show the effects of the material length-scale parameter, the inhomogeneity index, the radius-to-thickness and length-to-radius ratios, the load magnitude ratio, and the static and dynamic load factors on the first principal and first secondary instability regions of parametric resonance of simply-supported FG cylindrical microshells are significant.

Lung nodule malignancy classification with associated pulmonary fibrosis using 3D attention-gated convolutional network with CT scans.

BACKGROUND: Chest Computed tomography (CT) scans detect lung nodules and assess pulmonary fibrosis. While pulmonary fibrosis indicates increased lung cancer risk, current clinical practice characterizes nodule risk of malignancy based on nodule size and smoking history; little consideration is given to the fibrotic microenvironment. PURPOSE: To evaluate the effect of incorporating fibrotic microenvironment into classifying malignancy of lung nodules in chest CT images using deep learning techniques. MATERIALS AND METHODS: We developed a visualizable 3D classification model trained with in-house CT dataset for the nodule malignancy classification task. Three slightly-modified datasets were created: (1) nodule alone (microenvironment removed); (2) nodule with surrounding lung microenvironment; and (3) nodule in microenvironment with semantic fibrosis metadata. For each of the models, tenfold cross-validation was performed. Results were evaluated using quantitative measures, such as accuracy, sensitivity, specificity, and area-under-curve (AUC), as well as qualitative assessments, such as attention maps and class activation maps (CAM). RESULTS: The classification model trained with nodule alone achieved 75.61% accuracy, 50.00% sensitivity, 88.46% specificity, and 0.78 AUC; the model trained with nodule and microenvironment achieved 79.03% accuracy, 65.46% sensitivity, 85.86% specificity, and 0.84 AUC. The model trained with additional semantic fibrosis metadata achieved 80.84% accuracy, 74.67% sensitivity, 84.95% specificity, and 0.89 AUC. Our visual evaluation of attention maps and CAM suggested that both the nodules and the microenvironment contributed to the task. CONCLUSION: The nodule malignancy classification performance was found to be improving with microenvironment data. Further improvement was found when incorporating semantic fibrosis information.

Comparison of lung cancer occurring in fibrotic versus non-fibrotic lung on chest CT.

PURPOSE: Evaluate the behavior of lung nodules occurring in areas of pulmonary fibrosis and compare them to pulmonary nodules occurring in the non-fibrotic lung parenchyma. METHODS: This retrospective review of chest CT scans and electronic medical records received expedited IRB approval and a waiver of informed consent. 4500 consecutive patients with a chest CT scan report containing the word fibrosis or a specific type of fibrosis were identified using the system M*Model Catalyst (Maplewood, Minnesota, U.S.). The largest nodule was measured in the longest dimension and re-evaluated, in the same way, on the follow-up exam if multiple time points were available. The nodule doubling time was calculated. If the patient developed cancer, the histologic diagnosis was documented. RESULTS: Six hundred and nine patients were found to have at least one pulmonary nodule on either the first or the second CT scan. 274 of the largest pulmonary nodules were in the fibrotic tissue and 335 were in the non-fibrotic lung parenchyma. Pathology proven cancer was more common in nodules occurring in areas of pulmonary fibrosis compared to nodules occurring in areas of non-fibrotic lung (34% vs 15%, p < 0.01). Adenocarcinoma was the most common cell type in both groups but more frequent in cancers occurring in non-fibrotic tissue. In the non-fibrotic lung, 1 of 126 (0.8%) of nodules measuring 1 to 6 mm were cancer. In contrast, 5 of 49 (10.2%) of nodules in fibrosis measuring 1 to 6 mm represented biopsy-proven cancer (p < 0.01). The doubling time for squamous cell cancer was shorter in the fibrotic lung compared to non-fibrotic lung, however, the difference was not statistically significant (p = 0.24). 15 incident lung nodules on second CT obtained ≤ 18 months after first CT scan was found in fibrotic lung and eight (53%) were diagnosed as cancer. CONCLUSIONS: Nodules occurring in fibrotic lung tissue are more likely to be cancer than nodules in the nonfibrotic lung. Incident pulmonary nodules in pulmonary fibrosis have a high likelihood of being cancer.

Risk Factors for Postoperative Ileus Following Spine Surgery: A Systematic Review With Meta-Analysis.

STUDY DESIGN: Systematic review and meta-analysis. OBJECTIVES: Postoperative ileus (POI) can negatively impact patient recovery and surgical outcomes after spine surgery. Emerging studies have focused on the risk factors for POI after spine surgery. This study aimed to review the available literature on risk factors associated with POI following elective spine surgery. METHODS: Electronic databases were searched to identify relevant studies. Meta-analysis was performed using random-effect model. Risk factors for POI were summarized using pooled odds ratio (OR) with 95% confidence intervals (CI). RESULTS: Twelve studies were included in the present review. Meta-analysis demonstrated males exhibited a higher risk of POI than females odds ratio (OR, 1.76; 95% CI, 1.54-2.01). Patients with anemia had a higher risk of POI than those without anemia (OR, 1.48; 95% CI, 1.04-2.11). Patients with liver disease (OR, 3.3; 95% CI, 1.2-9.08) had a higher risk of POI. The presence of perioperative fluid and electrolyte imbalances was a predictor of POI (OR, 3.24; 95% CI, 2.62-4.02). Spine surgery involving more than 3 levels had a higher risk of POI compared to that with 1-2 levels (OR, 1.82; 95% CI, 1.03-3.23). CONCLUSIONS: Male sex and the presence of anemia and liver disease were significant patient factors associated with POI. Perioperative fluid and electrolyte imbalance and multilevel spine surgery significantly increased the risk of POI. In addition, through this comprehensive review, we identified several perioperative risk factors associated with the development of POI after spine surgery.

Structures revealing mechanisms of resistance and collateral sensitivity of Plasmodium falciparum to proteasome inhibitors.

The proteasome of the malaria parasite Plasmodium falciparum (Pf20S) is an advantageous drug target because its inhibition kills P. falciparum in multiple stages of its life cycle and synergizes with artemisinins. We recently developed a macrocyclic peptide, TDI-8304, that is highly selective for Pf20S over human proteasomes and is potent in vitro and in vivo against P. falciparum. A mutation in the Pf20S ß6 subunit, A117D, confers resistance to TDI-8304, yet enhances both enzyme inhibition and anti-parasite activity of a tripeptide vinyl sulfone ß2 inhibitor, WLW-vs. Here we present the high-resolution cryo-EM structures of Pf20S with TDI-8304, of human constitutive proteasome with TDI-8304, and of Pf20Sß6A117D with WLW-vs that give insights into the species selectivity of TDI-8304, resistance to it, and the collateral sensitivity associated with resistance, including that TDI-8304 binds ß2 and ß5 in wild type Pf20S as well as WLW-vs binds ß2 and ß5 in Pf20Sß6A117D. We further show that TDI-8304 kills P. falciparum as quickly as chloroquine and artemisinin and is active against P. cynomolgi at the liver stage. This increases interest in using these structures to facilitate the development of Pf20S inhibitors that target multiple proteasome subunits and limit the emergence of resistance.

A peptide derived from interleukin-10 exhibits potential anticancer activity and can facilitate cell targeting of gold nanoparticles loaded with anticancer therapeutics.

Human interleukin-10 (IL-10) is an immunosuppressive and anti-inflammatory cytokine, and its expression is upregulated in tumor tissues and serum samples of patients with various cancers. Because of its immunosuppressive nature, IL-10 has also been suggested to be a factor leading to tumor cells' evasion of immune surveillance and clearance by the host immune system. In this study, we refined a peptide with 20 amino acids, named NK20a, derived from the binding region of IL-10 on the basis of in silico analysis of the complex structure of IL-10 with IL-10Ra, the ligand binding subunit of the IL-10 receptor. The binding ability of the peptide was confirmed through in vitro biophysical biolayer interferometry and cellular experiments. The IL-10 inhibitory peptide exerted anticancer effects on lymphoma B cells and could abolish the suppression effect of IL-10 on macrophages. NK20a was also conjugated with gold nanoparticles to target the chemotherapeutic 5-fluorouracil (5-FU)-loaded nanoparticles to enhance the anticancer efficacy of 5-FU against the breast cancer cell line BT-474. Our study demonstrated that NK20a designed in silico with improved binding affinity to the IL-10 receptor can be used as a tool in developing anticancer strategies.

Momordica anti-HIV protein MAP30 abrogates the Epstein-Barr virus nuclear antigen 1 dependent functions in host cells.

Originally extracted from Momordica charantia seeds, the antiviral and anti-tumor activities of Momordica anti-HIV protein MAP30 have become well known. Although MAP30 has been reported to possess antiviral activity against several human viruses, the current understanding of the MAP30-mediated antiviral response is mainly derived from the previous research work on anti-HIV herbal medicines; the mechanistic insight of its effects on other viruses remains largely unknown. In this study, we showed that both ectopically expressed and purified recombinant MAP30 (rMAP30) impeded Epstein-Barr virus Nuclear Antigen 1 (EBNA1)-mediated transcription from the viral latent replication origin. Mechanistically, in vivo and in vitro studies revealed that MAP30 caused EBNA1 to dissociate from the cognate binding sites, which disrupted downstream EBNA1-dependent viral epigenome accumulation and cell maintenance of Epstein-Barr virus (EBV)-associated neoplastic cells. Finally, mutational analysis indicated that the N-terminal ricin A homologous domain shared by ricin-like proteins was implicated in the anti-EBV response. Our study provides evidence to support that MAP30 has a unique property to combat EBV latent infection, suggesting a potential to develop this herbal protein to be an alternative medicine for EBV associated diseases.