The CT Classification of Multilevel Cervical Ossification of the Posterior Longitudinal Ligament to Guide Hybrid Anterior Controllable Antedisplacement and Fusion vs. Posterior Laminoplasty.

OBJECTIVE: For precise and minimally invasive treatment of ossification of the posterior longitudinal ligament of the cervical spine, the lifting segment is minimized, anterior controllable antedisplacement and fusion (ACAF) was refined and improved. In addition, the development of appropriate surgical procedures for the ossification of each segment was rarely reported. Therefore, this study aimed to compare the efficacy and safety of hybrid anterior controlled antedisplacement fusion (Hybrid ACAF) with laminoplasty for multilevel ossification of the posterior longitudinal ligament (OPLL). METHODS: Between May 2018 and May 2021, 70 patients with multilevel OPLL were divided into a hybrid ACAF group and a laminoplasty group according to surgical methods. All patients were followed up for at least 1 year. Japanese Orthopaedic Association (JOA) score and recovery rate (JOARR), (VAS, NDI) score and C2-C7 Cobb angle, the sagittal vertical axis of the neck (SVA), and complications (cerebrospinal fluid leakage, C5 paralysis, etc.) were compared between the two groups by t test or non-parametric test. RESULTS: The operation time of hybrid ACAF was longer. C5 paralysis and axial pain were more common in the laminoplasty group, while dysphagia and hoarseness were more common in the hybrid ACAF group. At the last follow-up, the hybrid ACAF group had better recovery and maintenance of cervical lordosis and sagittal plane balance and a higher JOA score and recovery rate than the laminoplasty group. CONCLUSIONS: Hybrid ACAF can reduce the number of vertebral bodies and expand the decompression range, which is safe, effective, and tailored to local conditions. Compared with laminoplasty, hybrid ACAF is a precise alternative for patients with OPLL.

The exploration of surgery and survival prediction in patients with peritoneal metastasis from gastric adenocarcinoma based on the SEER database.

Background: As one of the most common diseases in terms of cancer-related mortality worldwide, gastric adenocarcinoma (GA) frequently develops peritoneal metastases (PMs) in advanced stages. Systemic therapy or optimal supportive care are recommended for advanced GA; however, patients frequently develop drug resistance. Surgical resection is not recommended for stage IV patients, and there have been some controversies regarding the role of it in GA patients with PMs. The aim of the study was to preliminarily evaluate the possible effect of surgical treatments on patients with only PMs from GA. Methods: Data were collected from the Surveillance, Epidemiology and End Results (SEER) database (year 2000-2022). A propensity score matching (PSM) was performed to reduce the influence of selection bias and confounding variables on comparisons. Then Cox proportional hazard regression, Kaplan-Meier analysis, and log-rank test were performed to assess the efficacy of surgical treatment in patients with PMs from GA. Results: A total of 399 patients diagnosed with PMs from GA were enrolled for our analysis, of which, 180 (45.1%) patients did not receive surgery and 219 (54.9%) patients received surgery. Multivariate Cox regression analysis before PSM indicated higher rates of overall survival (OS) outcome for patients who had received surgery [hazard ratio (HR) =0.4342, 95% confidence interval (CI): 0.3283-0.5742, P<0.001]. After PSM, a total of 172 patients were enrolled, with 86 in each group. Multivariate Cox analysis showed that surgery was the independent factor reflecting patients' survival (HR =0.4382, 95% CI: 0.3037-0.6324, P<0.001). Subgroup survival analysis revealed that surgery may bring advantages to patients with grades I-IV, stages T1-T4, stage N0, and tumor size less than 71 mm (P<0.05). We also found that the OS of chemotherapy patients who had undergone surgery was better than that of chemotherapy patients who had not undergone surgery (P<0.01). Conclusions: Based on the SEER database, surgery has better OS for patients only with PMs from GA. Patients without lymph node metastasis and those who received chemotherapy before may benefit from surgery. These specific groups of patients may have surgery as an option to improve the prognosis.

Screening and optimization of shark nanobodies against SARS-CoV-2 spike RBD.

SARS-CoV-2 continues to threaten human health, antibody therapy is one way to control the infection. Because new SARS-CoV-2 mutations are constantly emerging, there is an urgent need to develop broadly neutralizing antibodies to block the viral entry into host cells. VNAR from sharks is the smallest natural antigen binding domain, with the advantages of small size, flexible paratopes, good stability, and low manufacturing cost. Here, we used recombinant SARS-CoV-2 Spike-RBD to immunize sharks and constructed a VNAR phage display library. VNAR R1C2, selected from the library, efficiently binds to the RBD domain and blocks the infection of ACE2-positive cells by pseudovirus. Next, homologous bivalent VNARs were constructed through the tandem fusion of two R1C2 units, which enhanced both the affinity and neutralizing activity of R1C2. R1C2 was predicted to bind to a relatively conserved region within the RBD. By introducing mutations at four key binding sites within the CDR3 and HV2 regions of R1C2, the affinity and neutralizing activity of R1C2 were significantly improved. Furthermore, R1C2 also exhibits an effective capacity of binding to the Omicron variants (BA.2 and XBB.1). Together, these results suggest that R1C2 could serve as a valuable candidate for preventing and treating SARS-CoV-2 infections.

Early identification of autism spectrum disorder based on machine learning with eye-tracking data.

BACKGROUND: Early identification of autism spectrum disorder (ASD) improves long-term outcomes, yet significant diagnostic delays persist. METHODS: A retrospective cohort of 449 children (ASD: 246, typically developing [TD]: 203) was used for model development. Eye-movement data were collected from the participants watching videos that featured eye-tracking paradigms for assessing social and non-social cognition. Five machine learning algorithms, namely random forest, support vector machine, logistic regression, artificial neural network, and extreme gradient boosting, were trained to classify children with ASD and TD. The best-performing algorithm was selected to build the final model which was further evaluated in a prospective cohort of 80 children. The Shapley values interpreted important eye-tracking features. RESULTS: Random forest outperformed other algorithms during model development and achieved an area under the curve of 0.849 (< 3 years: 0.832, ≥ 3 years: 0.868) on the external validation set. Of the ten most important eye-tracking features, three measured social cognition, and the rest were related to non-social cognition. A deterioration in model performance was observed using only the social or non-social cognition-related eye-tracking features. LIMITATIONS: The sample size of this study, although larger than that of existing studies of ASD based on eye-tracking data, was still relatively small compared to the number of features. CONCLUSIONS: Machine learning models based on eye-tracking data have the potential to be cost- and time-efficient digital tools for the early identification of ASD. Eye-tracking phenotypes related to social and non-social cognition play an important role in distinguishing children with ASD from TD children.

FraHMT: A Fragment-Oriented Heterogeneous Graph Molecular Generation Model for Target Proteins.

The molecular generation task stands as a pivotal step in the domains of computational chemistry and drug discovery, aiming to computationally generate molecular structures for specific properties. In contrast to previous models that focused primarily on SMILES strings or molecular graphs, our model placed a special emphasis on the substructure information on molecules, enabling the model to learn richer chemical rules and structure features from fragments and chemical reaction information on molecules. To accomplish this, we fragmented the molecules to construct heterogeneous graph representations based on atom and fragment information. Then our model mapped the heterogeneous graph data into a latent vector space by using an encoder and employed a self-regressive generative model as a decoder for molecular generation. Additionally, we performed transfer learning on the model using a small set of ligand molecules known to be active against the target protein to generate molecules that bind better to the target protein. Experimental results demonstrate that our model is highly competitive with state-of-the-art models. It can generate valid and diverse molecules with favorable physicochemical properties and drug-likeness. Importantly, they produce novel molecules with high docking scores against the target proteins.

Preparation, characterisation, and pharmacodynamic study of myricetin pH-sensitive liposomes.

AIMS: Myricetin (MYR) was incorporated into pH-sensitive liposomes in order to improve its bioavailability and anti-hyperuricemic activity. METHODS: The MYR pH-sensitive liposomes (MYR liposomes) were prepared using thin film dispersion method, and assessed by particle size (PS), polydispersed index (PDI), zeta potential (ZP), encapsulation efficiency, drug loading, and in vitro release rate. Pharmacokinetics and anti-hyperuricemic activities were also evaluated. RESULTS: The PS, PDI, ZP, encapsulation efficiency, and drug loading of MYR liposomes were 184.34 ± 1.05 nm, 0.215 ± 0.005, -38.46 ± 0.30 mV, 83.42 ± 1.07%w/w, and 6.20 ± 0.31%w/w, respectively. The release rate of MYR liposomes was higher than free MYR, wherein the cumulative value responded to pH. Besides, the Cmax of MYR liposomes was 4.92 ± 0.20 µg/mL. The level of uric acid in the M-L-H group (200 mg/kg) was reduced by 54.74%w/v in comparison with the model group. CONCLUSION: MYR liposomes exhibited pH sensitivity and could potentially enhance the oral bioavailability and anti-hyperuricemic efficacy of MYR.

A Novel "De-tension"-guided Anterior Decompression Strategy-Thoracic Anterior Controllable Antedisplacement Fusion (TACAF) for Multilevel Ossification of Posterior Longitudinal Ligament in Thoracic Spine: A Retrospective Study with at Least 2-Year Follow-Up.

OBJECTIVE: To propose a novel surgical strategy-thoracic anterior controllable antedisplacement fusion (TACAF) to treat multilevel thoracic ossification of the posterior longitudinal ligament (mT-OPLL), and investigate its safety and efficacy. METHODS: Between January 2019 and December 2021, a total of 49 patients with thoracic myelopathy due to mT-OPLL surgically treated with TACAF were retrospectively reviewed. Patients' demographic data, radiologic parameters, and surgery-related complications, modified Japanese Orthopedic Association (mJOA) and visual analog scale (VAS) scores, thoracic kyphosis (TK), kyphosis angle in fusion area (FSK), thoracic curvature, spinal cord curvature, and curvature of curved rod in surgical region, diameter, and area of the spinal cord at the most compressed level were included. RESULTS: All patients acquired satisfactory recovery of neurologic function and overall complication rate was low at the final follow up. The mean mJOA of the laminectomy+TACAF and Full Lamina Preservation +TACAF groups, respectively, was 3.74 ± 2.05, 3.67 ± 1.95 before surgery, and 9.97 ± 0.83, 9.80 ± 0.68 at the final followed up, with the recovery rate of 84.26% ± 14.20%, 82.79% ± 10.35%, as to VAS Scores. The mean FSK was 34.50 ± 4.46,35.33 ± 3.44 before surgery, and was restored to 20.97 ± 5.70, 22.93 ± 6.34 at the final followed up respectively, as to mean TK (P < 0.05). Spinal cord curvature was improved from 34.12 ± 3.59, 33.93 ± 3.45 before surgery to 19.47 ± 3.53, 18.80 ± 3.17 at the final follow-up respectively, as to thoracic curvature (P < 0.05). In addition, the area and diameter of the spinal cord was also significantly improved at the final follow up (all P < 0.05). The curvature of the thoracic pulp and thoracic vertebra is closely related to the curvature of the rod. There was no statistically significant difference in the incidence of the pelvis and the slope value of the sacrum. CONCLUSIONS: This strategy provides a novel solution for the treatment of mT-OPLL with favorable recovery of neurological function, the tension of spinal cord, and fewer complications.

Virtual screening and biological evaluation of natural products as urate transporter 1 (URAT1) inhibitors.

Hyperuricemia is mainly caused by insufficient renal urate excretion. Urate transporter 1 (URAT1), an organic anion transporter, is the main protein responsible for urate reabsorption. In this study, we utilized artificial intelligence-based AlphaFold2 program to construct URAT1 structural model. After molecular docking and conformational evaluation, four e-pharmacophoric models were constructed based on the complex structures of probenecid-URAT1, benzbromarone-URAT1, lesinurad-URAT1, and verinurad-URAT1. Combining pharmacophore modeling, molecular docking, MM/GBSA calculation and ADME prediction, 25 flavonoids were selected from the natural products database containing 10,968 molecules. Then, a model of HEK-293T cells overexpressing URAT1 was constructed, and the inhibitory activity to URAT1 of 25 flavonoids was evaluated by measuring their effect on cellular uptake of 6-carboxyfluorescein (6-CFL). Fisetin, baicalein, and acacetin showed the best activity with IC50 values of 12.77, 26.71, and 57.30 µM, respectively. Finally, the structure-activity relationship of these three flavonoids was analyzed by molecular docking and molecular dynamics simulations. The results showed that the carbonyl group on C-4 and hydroxyl group on C-7, C-4', and C-5' in flavonoids were conducive for URAT1 inhibitory effects. This study facilitates the application of flavonoids in the development of URAT1 inhibitors.Communicated by Ramaswamy H. Sarma.

Evaluation of ChatGPT-generated medical responses: A systematic review and meta-analysis.

OBJECTIVE: Large language models (LLMs) such as ChatGPT are increasingly explored in medical domains. However, the absence of standard guidelines for performance evaluation has led to methodological inconsistencies. This study aims to summarize the available evidence on evaluating ChatGPT's performance in answering medical questions and provide direction for future research. METHODS: An extensive literature search was conducted on June 15, 2023, across ten medical databases. The keyword used was "ChatGPT," without restrictions on publication type, language, or date. Studies evaluating ChatGPT's performance in answering medical questions were included. Exclusions comprised review articles, comments, patents, non-medical evaluations of ChatGPT, and preprint studies. Data was extracted on general study characteristics, question sources, conversation processes, assessment metrics, and performance of ChatGPT. An evaluation framework for LLM in medical inquiries was proposed by integrating insights from selected literature. This study is registered with PROSPERO, CRD42023456327. RESULTS: A total of 3520 articles were identified, of which 60 were reviewed and summarized in this paper and 17 were included in the meta-analysis. ChatGPT displayed an overall integrated accuracy of 56 % (95 % CI: 51 %-60 %, I2 = 87 %) in addressing medical queries. However, the studies varied in question resource, question-asking process, and evaluation metrics. As per our proposed evaluation framework, many studies failed to report methodological details, such as the date of inquiry, version of ChatGPT, and inter-rater consistency. CONCLUSION: This review reveals ChatGPT's potential in addressing medical inquiries, but the heterogeneity of the study design and insufficient reporting might affect the results' reliability. Our proposed evaluation framework provides insights for the future study design and transparent reporting of LLM in responding to medical questions.

Prediction of tumor lysis syndrome in childhood acute lymphoblastic leukemia based on machine learning models: a retrospective study.

Background: Tumor lysis syndrome (TLS) often occurs early after induction chemotherapy for acute lymphoblastic leukemia (ALL) and can rapidly progress. This study aimed to construct a machine learning model to predict the risk of TLS using clinical indicators at the time of ALL diagnosis. Methods: This observational cohort study was conducted at the National Clinical Research Center for Child Health and Disease. Data were collected from pediatric ALL patients diagnosed between December 2008 and December 2021. Four machine learning models were constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) to select key clinical indicators for model construction. Results: The study included 2,243 pediatric ALL patients, and the occurrence of TLS was 8.87%. A total of 33 indicators with missing values ≤30% were collected, and 12 risk factors were selected through LASSO regression analysis. The CatBoost model with the best performance after feature screening was selected to predict the TLS of ALL patients. The CatBoost model had an AUC of 0.832 and an accuracy of 0.758. The risk factors most associated with TLS were the absence of potassium, phosphorus, aspartate transaminase (AST), white blood cell count (WBC), and urea levels. Conclusion: We developed the first TLS prediction model for pediatric ALL to assist clinicians in risk stratification at diagnosis and in developing personalized treatment protocols. This study is registered on the China Clinical Trials Registry platform (ChiCTR2200060616). Clinical trial registration: https://www.chictr.org.cn/, identifier ChiCTR2200060616.

Predicting autism spectrum disorder using maternal risk factors: A multi-center machine learning study.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a complex environmental etiology involving maternal risk factors, which have been combined with machine learning to predict ASD. However, limited studies have considered the factors throughout preconception, perinatal, and postnatal periods, and even fewer have been conducted in multi-center. In this study, five predictive models were developed using 57 maternal risk factors from a cohort across ten cities (ASD:1232, typically developing[TD]: 1090). The extreme gradient boosting model performed best, achieving an accuracy of 66.2 % on the external cohort from three cities (ASD:266, TD:353). The most important risk factors were identified as unstable emotions and lack of multivitamin supplementation using Shapley values. ASD risk scores were calculated based on predicted probabilities from the optimal model and divided into low, medium, and high-risk groups. The logistic analysis indicated that the high-risk group had a significantly increased risk of ASD compared to the low-risk group. Our study demonstrated the potential of machine learning models in predicting the risk for ASD based on maternal factors. The developed model provided insights into the maternal emotion and nutrition factors associated with ASD and highlighted the potential clinical applicability of the developed model in identifying high-risk populations.

Virtual screening of natural products targeting ubiquitin-specific protease 7.

Ubiquitin-specific protease 7 (USP7) is a promising prognostic and druggable target for cancer therapy. Inhibition of USP7 can activate the MDM2-P53 signaling pathway, thereby promoting cancer cell apoptosis. This study based on watvina molecular docking of virtual screening method and biological evaluation found the new USP7 inhibitors targeting catalytic active site. Three hits were screened from 3760 natural products and validated as USP7 inhibitors by enzymatic and kinetic assays. The IC50 values of scutellarein (Scu), semethylzeylastera (DML) and salvianolic acid C (SAC) were 3.017, 6.865 and 8.495 µM, respectively. Further, we reported that the hits could downregulate MDM2 and activate p53 signal pathway in HCT116 cells. Molecular dynamics simulation was used to investigate the binding mechanism of USP7 to Scu, the compound with the best performance, which formed stable contact with Val296, Gln297, Phe409, Tyr465 and Tyr514. These interactions are essential for maintaining the biological activity of Scu. Three natural products are suitable as lead compounds for the development of novel USP7 inhibitors, especially anti-colon cancer drugs.Communicated by Ramaswamy H. Sarma.

Fluorescence detecting glycopeptide antibiotics via a dynamic molecular switch.

BACKGROUND: Glycopeptide antibiotics (GPAs) represented by vancomycin (VAN) are clinically used as a first-line treatment for serious infections caused by Gram-positive pathogens. The use and dosing methods of GPAs are rigorously managed for safety considerations, which calls for fast and accurate quantification approaches. RESULT: A new sort of fluorescent probes for GPAs has been proposed, each of which was integrated by a fluorescein-based reporter and a GPAs' recognition peptide D-alanyl-D-alanine (D-Ala-D-Ala). These probes work as dynamic molecular switches, which mainly exist as non-fluorescent spirolactam forms in the absence of GPAs. GPAs binding with the dipeptide regulates the dynamic balance between fluorescence OFF lactam form and fluorescence ON ring-opened form, rendering these probes capable of GPAs detecting. The most promising one P1 exhibits excellent sensitivity and selectivity towards GPAs detection. SIGNIFICANCE: Different to previous developments, P1 consists of a single fluorophore without the need of a fluorescence-quenching group or a secondary dye, which is the smallest fluorescent probe for GPAs up to now. P1 realizes direct VAN quantification from complex biological samples including real serums, dispensing with additional drug extraction. More interestingly, both P1 and P6 can distinguish GPAs with different peptide backbones, which has not been achieved previously.

Radiation reduction for interventional radiology imaging: a video frame interpolation solution.

PURPOSE: The aim of this study was to diminish radiation exposure in interventional radiology (IR) imaging while maintaining image quality. This was achieved by decreasing the acquisition frame rate and employing a deep neural network to interpolate the reduced frames. METHODS: This retrospective study involved the analysis of 1634 IR sequences from 167 pediatric patients (March 2014 to January 2022). The dataset underwent a random split into training and validation subsets (at a 9:1 ratio) for model training and evaluation. Our approach proficiently synthesized absent frames in simulated low-frame-rate sequences by excluding intermediate frames from the validation subset. Accuracy assessments encompassed both objective experiments and subjective evaluations conducted by nine radiologists. RESULTS: The deep learning model adeptly interpolated the eliminated frames within IR sequences, demonstrating encouraging peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) results. The average PSNR values for angiographic, subtraction, and fluoroscopic modes were 44.94 dB, 34.84 dB, and 33.82 dB, respectively, while the corresponding SSIM values were 0.9840, 0.9194, and 0.7752. Subjective experiments conducted with experienced interventional radiologists revealed minimal discernible differences between interpolated and authentic sequences. CONCLUSION: Our method, which interpolates low-frame-rate IR sequences, has shown the capability to produce high-quality IR images. Additionally, the model exhibits potential for reducing the frame rate during IR image acquisition, consequently mitigating radiation exposure. CRITICAL RELEVANCE STATEMENT: This study presents a critical advancement in clinical radiology by demonstrating the effectiveness of a deep neural network in reducing radiation exposure during pediatric interventional radiology while maintaining image quality, offering a potential solution to enhance patient safety. KEY POINTS: • Reducing radiation: cutting IR image to reduce radiation. • Accurate frame interpolation: our model effectively interpolates missing frames. • High visual quality in terms of PSNR and SSIM, making IR procedures safer without sacrificing quality.

Structural basis for sugar perception by Drosophila gustatory receptors.

Insects rely on a family of seven transmembrane proteins called gustatory receptors (GRs) to encode different taste modalities, such as sweet and bitter. We report structures of Drosophila sweet taste receptors GR43a and GR64a in the apo and sugar-bound states. Both GRs form tetrameric sugar-gated cation channels composed of one central pore domain (PD) and four peripheral ligand-binding domains (LBDs). Whereas GR43a is specifically activated by the monosaccharide fructose that binds to a narrow pocket in LBDs, disaccharides sucrose and maltose selectively activate GR64a by binding to a larger and flatter pocket in LBDs. Sugar binding to LBDs induces local conformational changes, which are subsequently transferred to the PD to cause channel opening. Our studies reveal a structural basis for sugar recognition and activation of GRs.

Three Licorice Extracts' Impact on the Quality of Fresh-Cut Sweet Potato (Ipomoea batatas (L.) Lam) Slices.

The quality of fresh-cut produce, particularly sweet potatoes, is crucial for their value. Licorice extract is an optional additive in fresh-cut sweet potatoes. This study examined the impact of three licorice extracts (licorice acid, LA; licorice flavonoids, LF; and licorice polysaccharides, LP) on the quality of fresh-cut sweet potato slices (FCSPSs) for one week of storage. After one week of storage, the extracts showed varying effects on FCSPSs. LA and LF treatments reduced the area proportion of browning (APB), while LP treatments increased APB and decreased L* values. Antioxidant experiments revealed that LP treatments increased PPO and POD activity while reducing SOD activity. The concentrations of the three licorice extracts showed a strong negative correlation with SOD activity. In conclusion, LP harmed the appearance and antioxidant qualities of FCSPSs. LA and LF may be suitable additive components for FCSPSs, and 30 mg/mL LA and LF treatments were found to maintain the appearance and texture quality of FCSPSs during storage. Therefore, careful consideration should be given when using LP as a food additive for FCSPSs.

Comparative analysis of upper aerodigestive tract and non-upper aerodigestive tract in NK/T-cell lymphoma

Objective Nasal or extranasal natural killer/T-cell lymphoma (NKTCL) is a very rare aggressive lymphoma, but it is increasingly diagnosed. To evaluate some specificity by comparative analysis between primary upper aerodigestive tract (UAT) and non-upper aerodigestive tract (NUAT)NKTCL. Methods A retrospective analysis was performed on NKTCL patients from January 2013 to November 2022 in our cancer center. Results The majority of the lesions were UAT-NKTCL 70 cases (92.1%), the primary NUAT occurred in 6 cases. Patients in the UAT group were mainly in the early stage and in the low and medium risk, while those in the NUAT group were late stage and in high risk (p = 0.000). The expressions of CD3 and TIA-1 in UAT group were higher than those in NUAT group (p = 0.031, p = 0.003), while CD7 was dominant in NUAT group (p = 0.009). For early stage NKTCL, multivariate analysis suggested that gender and PINK score were independent factors affecting PFS and OS (p < 0.05). The 3 year OS rate in initial CR group was 90.1% versus 46.4% in non-CR group (p = 0.000). In advanced stage, KI67% and bone marrow involvement were independent factors affecting OS (p = 0.022, p = 0.038). Conclusion It was difficult to distinguish between UAT and NUAT-NKTCL from histopathology. NUAT-NKTCL patients did have advanced stage and poor outcome. The prognostic value of PINK score and bone marrow involvement was proposed. We aimed to improve initial CR rates, as well as to find new predictive models to predict the whole population (AU)

Preparation, characterization, pharmacokinetics and ulcerative colitis treatment of hyperoside-loaded mixed micelles.

At present, ulcerative colitis (UC) has become a global disease due to its high incidence. Hyperoside (HYP) is a naturally occurring flavonoid compound with many pharmacological effects. This study aimed to develop HYP-loaded mixed micelles (HYP-M) to improve oral bioavailability of HYP and to evaluate its therapeutic effect on UC. The prepared HYP-M exhibited stable physical and chemical properties, smaller particle size (PS) (21.48 ± 1.37 nm), good polydispersity index (PDI = 0.178 ± 0.013), negative Zeta potential (ZP) (- 20.00 ± 0.48 mV) and high entrapment rate (EE) (89.59 ± 2.03%). In vitro release and in vivo pharmacokinetic results showed that HYP-M significantly increased the releasing rate of HYP, wherein its oral bioavailability was 4.15 times higher than that of free HYP. In addition, HYP-M was more effective in the treatment of UC than free HYP. In conclusion, HYP-M could serve as a novel approach to improve bioavailability and increase anti-UC activity of HYP.

Comparative analysis of upper aerodigestive tract and non-upper aerodigestive tract in NK/T-cell lymphoma.

OBJECTIVE: Nasal or extranasal natural killer/T-cell lymphoma (NKTCL) is a very rare aggressive lymphoma, but it is increasingly diagnosed. To evaluate some specificity by comparative analysis between primary upper aerodigestive tract (UAT) and non-upper aerodigestive tract (NUAT)NKTCL. METHODS: A retrospective analysis was performed on NKTCL patients from January 2013 to November 2022 in our cancer center. RESULTS: The majority of the lesions were UAT-NKTCL 70 cases (92.1%), the primary NUAT occurred in 6 cases. Patients in the UAT group were mainly in the early stage and in the low and medium risk, while those in the NUAT group were late stage and in high risk (p = 0.000). The expressions of CD3 and TIA-1 in UAT group were higher than those in NUAT group (p = 0.031, p = 0.003), while CD7 was dominant in NUAT group (p = 0.009). For early stage NKTCL, multivariate analysis suggested that gender and PINK score were independent factors affecting PFS and OS (p < 0.05). The 3 year OS rate in initial CR group was 90.1% versus 46.4% in non-CR group (p = 0.000). In advanced stage, KI67% and bone marrow involvement were independent factors affecting OS (p = 0.022, p = 0.038). CONCLUSION: It was difficult to distinguish between UAT and NUAT-NKTCL from histopathology. NUAT-NKTCL patients did have advanced stage and poor outcome. The prognostic value of PINK score and bone marrow involvement was proposed. We aimed to improve initial CR rates, as well as to find new predictive models to predict the whole population.

Isoliquiritigenin Containing PH Sensitive Micelles for Enhanced Anti-Colitis Activity.

Isoliquiritigenin (ISL) is known to have a variety of pharmacological activities, but its poor water solubility limits its application. In order to improve the bioavailability of ISL and its anti-colitis activity, this study aims to develop an effective drug delivery system loaded with ISL. In this study, ISL pH-sensitive micelles (ISL-M) were prepared by thin film hydration method. The micellar size (PS), polydispersity index (PDI), electrokinetic potential (ζ-potential), drug loading (DL), encapsulation rate (EE) and other physical parameters were characterized. The storage stability of ISL-M was tested, release in vitro and pharmacokinetic studies in rats were performed, and the anti-inflammatory effect of ISL-M on ulcerative colitis induced by dextran sulfate sodium (DSS) was evaluated. The results showed that PS, PDI, ZP, EE% and DL% of ISL-M were 151.15±1.04 nm, 0.092±0.014, -31.32±0.721 mV, 93.97±1.53 % and 8.42±0.34 %, respectively. Compared with unformulated ISL (F-ISL), the cumulative release rate of ISL-M in the three different media was significantly increased and showed a certain pH sensitivity. The area under drug curve (AUC0-t) and peak concentration (Cmax) of ISL-M group were 2.94 and 4.06 times higher than those of ISL group. In addition, ISL-M is expected to develop new methods for increasing the bioavailability and anti-inflammatory activity of ISL.