Latent space representation of electronic health records for clustering dialysis-associated kidney failure subtypes.

OBJECTIVE: Kidney failure manifests in various forms, from sudden occurrences such as Acute Kidney Injury (AKI) to progressive like Chronic Kidney Disease (CKD). Given its intricate nature, marked by overlapping comorbidities and clinical similarities-including treatment modalities like dialysis-we sought to design and validate an end-to-end framework for clustering kidney failure subtypes. MATERIALS AND METHODS: Our emphasis was on dialysis, utilizing a comprehensive dataset from the UK Biobank (UKB). We transformed raw Electronic Health Record (EHR) data into standardized matrices that incorporate patient demographics, clinical visit data, and the innovative feature of visit time-gaps. This matrix structure was achieved using a unique data cutting method. Latent space transformation was facilitated using a convolution autoencoder (ConvAE) model, which was then subjected to clustering using Principal Component Analysis (PCA) and K-means algorithms. RESULTS: Our transformation model effectively reduced data dimensionality, thereby accelerating computational processes. The derived latent space demonstrated remarkable clustering capacities. Through cluster analysis, two distinct groups were identified: CKD-majority (cluster 1) and a mixed group of non-CKD and some CKD subtypes (cluster 0). Cluster 1 exhibited notably low survival probability, suggesting it predominantly represented severe CKD. In contrast, cluster 0, with substantially higher survival probability, likely to include milder CKD forms and severe AKI. Our end-to-end framework effectively differentiates kidney failure subtypes using the UKB dataset, offering potential for nuanced therapeutic interventions. CONCLUSIONS: This innovative approach integrates diverse data sources, providing a holistic understanding of kidney failure, which is imperative for patient management and targeted therapeutic interventions.

Hollow Copper Sulfide Nanocubes Loaded with Pt(IV) Complexes for Cancer Multimodal Therapy.

Chemotherapy (CT) can significantly inhibit tumor growth, metastasis, and recurrence during cancer therapy. People have widely used platinum drugs in cancer treatment. However, as most chemotherapeutic drugs, platinum drugs still have shortcomings such as poor solubility, low cell uptake, nonspecific distribution, multidrug resistance, and adverse side effects. Therefore, we synthesized hollow copper sulfide (CuS) nanocubes with photothermal and photodynamic properties as carriers for Pt(IV) drugs. Hollow CuS nanocubes have attracted considerable interest in the field of cancer photothermal therapy (PTT) using multiple biological windows. Under near-infrared (NIR) laser irradiation, Cu2+ can be reduced into Cu+ in the presence of hydrogen peroxide in the tumor microenvironment. The resulting Cu+ can be used for photodynamic therapy (PDT), which can perform a Fenton-like reaction under acidic conditions (pH 5.5-6.5) and catalyze hydrogen peroxide to produce ·OH in the tumor microenvironment. In addition, compared with Pt(II) drugs, Pt(IV) drugs not only have lower systemic toxicity but also consume glutathione (GSH), thereby increasing reactive oxygen species (ROS) levels in tumor cells and effectively promoting PDT. In this study, we oxidized ethylenediamine platinum chloride to its tetravalent state, loaded the Pt(IV) complexes using hollow CuS nanocubes, and modified the surfaces of the nanoparticles with PEG to improve the EPR effect. The Pt(IV)-loaded hollow CuS nanocubes modified with PEG (Pt(IV)-CuS@PEG) are expected to be used for tumor chemo/photothermal/photodynamic therapy.

Optimized Machine Learning Model for Predicting Compressive Strength of Alkali-Activated Concrete Through Multi-Faceted Comparative Analysis.

Alkali-activated concrete (AAC), produced from industrial by-products like fly ash and slag, offers a promising alternative to traditional Portland cement concrete by significantly reducing carbon emissions. Yet, the inherent variability in AAC formulations presents a challenge for accurately predicting its compressive strength using conventional approaches. To address this, we leverage machine learning (ML) techniques, which enable more precise strength predictions based on a combination of material properties and cement mix design parameters. In this study, we curated an extensive dataset comprising 1756 unique AAC mixtures to support robust ML-based modeling. Four distinct input variable schemes were devised to identify the optimal predictor set, and a comparative analysis was performed to evaluate their effectiveness. After this, we investigated the performance of several popular ML algorithms, including random forest (RF), adaptive boosting (AdaBoost), gradient boosting regression trees (GBRTs), and extreme gradient boosting (XGBoost). Among these, the XGBoost model consistently outperformed its counterparts. To further enhance the predictive accuracy of the XGBoost model, we applied four state-of-the-art optimization techniques: the Gray Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), beetle antennae search (BAS), and Bayesian optimization (BO). The optimized XGBoost model delivered superior performance, achieving a remarkable coefficient of determination (R2) of 0.99 on the training set and 0.94 across the entire dataset. Finally, we employed SHapely Additive exPlanations (SHAP) to imbue the optimized model with interpretability, enabling deeper insights into the complex relationships governing AAC formulations. Through the lens of ML, we highlight the benefits of the multi-faceted synergistic approach for AAC strength prediction, which combines careful input parameter selection, optimal hyperparameter tuning, and enhanced model interpretability. This integrated strategy improves both the robustness and scalability of the model, offering a clear and reliable prediction of AAC performance.

Clustering-based risk stratification of prediabetes populations: Insights from the Taiwan and UK Biobanks.

AIMS/INTRODUCTION: This study aimed to identify low- and high-risk diabetes groups within prediabetes populations using data from the Taiwan Biobank (TWB) and UK Biobank (UKB) through a clustering-based Unsupervised Learning (UL) approach, to inform targeted type 2 diabetes (T2D) interventions. MATERIALS AND METHODS: Data from TWB and UKB, comprising clinical and genetic information, were analyzed. Prediabetes was defined by glucose thresholds, and incident T2D was identified through follow-up data. K-means clustering was performed on prediabetes participants using significant features determined through logistic regression and LASSO. Cluster stability was assessed using mean Jaccard similarity, silhouette score, and the elbow method. RESULTS: We identified two stable clusters representing high- and low-risk diabetes groups in both biobanks. The high-risk clusters showed higher diabetes incidence, with 15.7% in TWB and 13.0% in UKB, compared to 7.3% and 9.1% in the low-risk clusters, respectively. Notably, males were predominant in the high-risk groups, constituting 76.6% in TWB and 52.7% in UKB. In TWB, the high-risk group also exhibited significantly higher BMI, fasting glucose, and triglycerides, while UKB showed marginal significance in BMI and other metabolic indicators. Current smoking was significantly associated with increased diabetes risk in the TWB high-risk group (P < 0.001). Kaplan-Meier curves indicated significant differences in diabetes complication incidences between clusters. CONCLUSIONS: UL effectively identified risk-specific groups within prediabetes populations, with high-risk groups strongly associated male gender, higher BMI, smoking, and metabolic markers. Tailored preventive strategies, particularly for young males in Taiwan, are crucial to reducing T2D risk.

[Different Prophylaxis Strategies for Central Nervous System Recurrence of Diffuse Large B-Cell Lymphoma].

OBJECTIVE: To analyze the effects of highdose methotrexate (HD-MTX) and lenalidomide as central nervous system (CNS) prophylaxis strategies in patients with diffuse large B-cell lymphoma (DLBCL). METHODS: The data of DLBCL patients with high risk of CNS recurrence who were initially treated in Fujian Provincial Hospital and Fujian Cancer Hospital from January 2012 to June 2022 were analyzed retrospectively. The patients were divided into HD-MTX group and lenalidomide group according to different prophylaxis strategies. Each group was further divided into high-risk group and medium-risk group based on CNS-IPI score and/or testicular involvement. The CNS relapse-free survival (CRFS) rate, adverse effects, and the effects of different prophylaxis strategies on overall survival (OS) rate and progression-free survival (PFS) rate were evaluated in different groups and subgroups. RESULTS: There were 200 patients enrolled in this study, 80 cases in lenalidomide group and 120 cases in HD-MTX group. According to the delivery timing of prophylactic HD-MTX, the patients in HD-MTX group were further divided into two groups: 80 cases at the end of induction chemotherapy and 40 cases during chemotherapy interval. At a median follow-up of 48(14-133) months, the 4-year CRFS rate, 4-year PFS rate, and 4-year OS rate of the HD-MTX group was 93.6%, 57.2%, and 68.8%, respectively, while that of the lenalidomide group was 90.4%, 69.4% and 75.6%. There were no significant differences in 4-year CRFS rate, 4-year PFS rate, and 4-year OS rate between HD-MTX group and lenalidomide group (all P >0.05), but lenalidomide group showed a trend of improvement in PFS. Further subgroup analysis showed that there was no significant difference in 4-year CRFS rate between high-risk patients of the two groups (91.7% vs 83.4%, P >0.05), while 4-year PFS rate showed difference (49.5% vs 64.2%, P <0.05). A total of 248 cycles were collected for adverse reaction analysis in the HD-MTX group, and 25 cycles occurred neutropenia accompanied with infection (10.1%), while in lenalidomide group 240 cycles were collected in which 20 cycles occurred neutropenia accompanied with infection (8.3%). Both the two groups had no treatment-related deaths. CONCLUSION: Compared with HD-MTX, lenalidomide combined with immunochemotherapy can prevent CNS relapse, at the same time, improve prognosis, which is a safe and well tolerated central prophylaxis strategy.

Impact of an Epstein-Barr Virus Serology-Based Screening Program on Nasopharyngeal Carcinoma Mortality: A Cluster-Randomized Controlled Trial.

PURPOSE: Screening for nasopharyngeal carcinoma (NPC) has shown an improvement in early detection and survival rates of NPC in endemic regions. It is critical to evaluate whether NPC screening can reduce NPC-specific mortality in the population. METHODS: Sixteen towns in Sihui and Zhongshan cities, China, were selected; eight were randomly allocated to the screening group and eight to the control group. Residents age 30-69 years with no history of NPC were included from January 1, 2008, to December 31, 2015. Residents in the screening towns were invited to undergo serum Epstein-Barr virus (EBV) viral capsid antigen/nuclear antigen 1-immunoglobulin A antibody tests; others received no intervention. The population was followed until December 31, 2019. Nonparametric tests and Poisson regression models were used to estimate the screening effect on NPC mortality, accounting for the cluster-randomized design. The trial is registered with ClinicalTrials.gov (identifier: NCT00941538). RESULTS: A total of 174,943 residents in the screening group and 186,263 residents in the control group were included. NPC incidence and overall mortality were similar between the two groups. A total of 52,498 (30.0% of 174,943) residents participated in the serum EBV antibody test. The overall compliance rate for endoscopic examination and/or biopsies among baseline and ever-classified high-risk participants was 65.9% (1,110 of 1,685) and 67.6% (1,703 of 2,518), respectively. A significant 30% reduction in NPC mortality was observed in the screening group compared with the control group (standardized NPC-specific mortality rate of 8.2 NPC deaths per 1,000 person-years versus 12.5; adjusted rate ratio [RR], 0.70 [95% CI, 0.49 to 0.997]; P = .048). This benefit was most evident among individuals age 50 years and older (RR, 0.56 [95% CI, 0.37 to 0.85]; P = .007) compared with those younger than 50 years (RR, 0.96 [95% CI, 0.64 to 1.46]; P = .856). CONCLUSION: In this 12-year trial, EBV antibody testing resulted in a significant reduction in NPC mortality.

Dissociation of Nicotine from Acetylcholine-Binding Protein under Terahertz Waves Radiation.

The binding of nicotine (NCT) to acetylcholine-binding protein (AChBP) plays an important role in synaptic transmission and neurotransmitter regulation. However, effectively regulating their binding or dissociation processes remains a challenging problem. In this study, we employed all-atom molecular dynamics (MD) simulations to systematically investigate the impact of external terahertz (THz) waves on the binding kinetics between AChBP and NCT. We first identified the key residues (i.e., W143) and the key interactions (i.e., hydrogen bonding and cation-π interaction) in AChBP-NCT binding without THz waves. We then investigated the binding and dissociation of charged NCT with AChBP at three different frequencies (i.e., 13.02, 21.44, 42.55 THz). Importantly, the predominant vibrational modes at 13.02 THz can drive the rotation of the pentagonal ring on NCT. This leads to the disruption of hydrogen bonds between NCT and W143 and a reduced likelihood of forming cation-π interactions, resulting in the dissociation of NCT from AChBP. Additionally, we further investigated the influence of electric field intensities on the dissociation kinetics and found that when the electric field intensity exceeds a critical value (∼0.60 V/nm), the probability of ligand dissociation gradually rises as the intensity increases. In general, this study contributes to a better understanding of the effects of THz waves on protein-ligand interactions, which might also shed some light on potential applications in nicotine addiction treatment and therapeutic strategies for neurodegenerative diseases.

A simple scoring algorithm predicting paravertebral and/or iliopsoas abscess among adults with community-onset bloodstream infections: matters of PVL-producing Staphylococcus aureus.

PURPOSE: Misdiagnosis or delayed diagnosis of paravertebral and/or iliopsoas abscess (PVIPA) has been frequently reported to be associated with unfavorable prognosis. We aimed to develop a scoring algorithm that can easily and accurately identify patients at greater risk for PVIPA among individuals with community-onset bloodstream infections. METHODS: In a multicenter, retrospective cohort study, the score was developed with the first four study years and validated with the remaining two years. Applying logistic regression, the score values of prediction determinants were derived from the adjusted odds ratios (AOR). The performance of the scoring algorithm was assessed with the receiver operating characteristic (ROC) curve. RESULTS: In the derivation (3869 patients) and validation (1608) cohorts, patients with PVIPA accounted for 1.7% and 1.4%, respectively. In the derivation cohort, five independent predictors of PVIPA were recognized using multivariable analyses: time-to-defervescence > 5 days (AOR, 7.00; 2 points), Panton-Valentine Leukocidin (PVL)-producing Staphylococcus aureus (AOR, 5.98; 2 points), intravenous drug users (AOR, 2.60; 1 points), and comorbid hemato-oncology (AOR, 0.41; -1 point) or liver cirrhosis (AOR, 2.56; 1 points). In the derivation and validation cohorts, areas under ROC curves (95% confidence intervals) of the prediction algorithm are 0.83 (0.77-0.88) and 0.85 (0.80-0.90), and a cutoff score of + 2 represents sensitivity of 83.3% and 95.7%, specificity of 68.6% and 67.7%, positive predictive values of 4.4% and 4.1%, and negative predictive values of 99.6% and 99.9%, respectively. CONCLUSIONS: Of a scoring algorithm with substantial sensitivity and specificity in predicting PVIPA, PVL-producing S. aureus and Time-to-defervescence > 5 days were crucial determinants.

Reduced-dose chemotherapy and blinatumomab as induction treatment for newly diagnosed Ph-negative B-cell precursor acute lymphoblastic leukemia: a phase 2 trial.

Blinatumomab has emerged as a promising component of first-line therapy for acute B-cell precursor lymphoblastic leukemia (BCP-ALL), bolstering treatment efficacy. To mitigate CD19 selection pressure and reduce the incidence of blinatumomab-associated toxicities, pre-treatment chemotherapy is recommended before administering blinatumomab. From September 2022 to December 2023, we conducted a single-arm, multicenter, phase 2 trial (NCT05557110) in newly diagnosed Philadelphia chromosome-negative BCP-ALL (Ph-negative BCP-ALL) patients. Participants received induction treatment with reduced-dose chemotherapy (RDC), comprising idarubicin, vindesine, and dexamethasone over 7 days, followed by 2 weeks of blinatumomab. Those failing to achieve composite complete remission (CRc) received an additional 2 weeks of blinatumomab. The primary endpoint was the CRc rate post initial induction treatment. Of the 35 enrolled patients, 33 (94%) achieved CRc after 2 weeks of blinatumomab, with 30 (86%) achieving measurable residual disease (MRD) negativity. Two patients extended blinatumomab to 4 weeks. With either 2 or 4 weeks of blinatumomab treatment, all patients achieved CR (35/35) and 89% (31/35) were MRD negativity. The median time to CR was 22 days. Immune effector cell-associated neurotoxicity syndrome was limited (14%, all grade 1). Non-hematological adverse events of grade 3 or higher included pneumonia (17%), sepsis (6%), and cytokine release syndrome (9%). With a median follow-up of 11.5 months, estimated 1-year overall survival and 1-year progression-free survival rates were 97.1% and 82.2%, respectively. These findings affirm that RDC followed by blinatumomab is an effective and well-tolerated induction regimen for newly diagnosed Ph-negative BCP-ALL, supporting a shift towards less intensive and more targeted therapeutic approaches. Trial registration: https://www.clinicaltrials.Gov . Identifier NCT05557110.

[Treatment of massive rotator cuff tears with modified Chinese-way technique].

OBJECTIVE: To explore clinical effect of modified Chinese-way technique under shoulder arthroscopy in treating massive rotator cuff tears. METHODS: From January 2019 to June 2022, 22 patients with massive rotator cuff tears who underwent arthroscopic rotator cuff repair with improved Chinese-way technique, including 10 males and 12 females, aged from 46 to 76 years old with an average of(64.14±7.45) years old;the courses of disease ranged from 5 to 14 months with an average of(8.32±2.42) months;19 patients were complete repaired, and 3 patients were partial repaired. Visual analogue scale (VAS) and University of California at Los Angeles (UCLA) scale were used to evaluate pain and function of shoulder joint preoperatively and 1 year postoperatively. Postoperative complications, the integrity of reconstructed tissue structure and the size of subacromial space were observed. RESULTS: All patients were followed up from 12 to 34 months with an average of (17.14±5.93) months. Re-tear were occurred in 4 patients during MRI follow-up, but clinical symptoms of patients were improved significantly and they were satisfied with the treatment, the others were no complications such as incision infection, peripheral nerve injury, loosening and falling off of internal fixation anchors. Preoperative and 1 year after operation VAS were (8.05±1.12) and (1.82±1.50), UCLA scores were (7.45±1.65) and (31.41±2.87) respectively, and the difference was statistically significant (P<0.05). CONCLUSION: The modified Chinese-way technique under shoulder arthroscopy for the massive rotator cuff tear could relieve pain obviously and recovery postoperative function well, with satisfactory curative effect.

Current landscape of mRNA technologies and delivery systems for new modality therapeutics.

Realizing the immense clinical potential of mRNA-based drugs will require continued development of methods to safely deliver the bioactive agents with high efficiency and without triggering side effects. In this regard, lipid nanoparticles have been successfully utilized to improve mRNA delivery and protect the cargo from extracellular degradation. Encapsulation in lipid nanoparticles was an essential factor in the successful clinical application of mRNA vaccines, which conclusively demonstrated the technology's potential to yield approved medicines. In this review, we begin by describing current advances in mRNA modifications, design of novel lipids and development of lipid nanoparticle components for mRNA-based drugs. Then, we summarize key points pertaining to preclinical and clinical development of mRNA therapeutics. Finally, we cover topics related to targeted delivery systems, including endosomal escape and targeting of immune cells, tumors and organs for use with mRNA vaccines and new treatment modalities for human diseases.

A multi-pronged approach to assessing antimicrobial resistance risks in coastal waters and aquaculture systems.

Antimicrobial resistance (AMR) is a global challenge that has impacted aquaculture and surrounding marine environments. In this study, a year-long monitoring program was implemented to evaluate AMR in two different aquaculture settings (i.e., open cage farming, recirculating aquaculture system (RAS)) and surrounding marine environment within a tropical coastal region. The objectives of this study are to (i) investigate the prevalence and co-occurrence of antibiotic-resistant bacteria (ARB), antibiotic resistance genes (ARGs), antibiotics (AB) and various associated chemical compounds at these study sites; (ii) explore the contributing factors to development and propagation of AMR in the coastal environment; and (iii) assess the AMR risks from different perspectives based on the three AMR determinants (i.e., ARB, ARGs and AB). Key findings revealed a distinct pattern of AMR across the different aquaculture settings, notably a higher prevalence of antibiotic-resistant Vibrio at RAS outfalls, suggesting a potential accumulation of microorganisms within the treatment system. Despite the relative uniform distribution of ARGs across marine sites, specific genes such as qepA, blaCTX-M and bacA, were found to be abundant in fish samples, especially from the RAS. Variations in chemical contaminant prevalence across sites highlighted possible anthropogenic impacts. Moreover, environmental and seasonal variations were found to significantly influence the distribution of ARGs and chemical compounds in the coastal waters. Hierarchical cluster analysis that was based on ARGs, chemical compounds and environmental data, categorized the sites into three distinct clusters which reflected strong association with location, seasonality and aquaculture activities. The observed weak correlations between ARGs and chemical compounds imply that low environmental concentrations may be insufficient for resistance selection. A comprehensive risk assessment using methodologies such as the multiple antibiotic resistance (MAR) index, comparative AMR risk index (CAMRI) and Risk quotient (RQ) underscored the complexity of AMR risks. This research significantly contributes to the understanding of AMR dynamics in natural aquatic systems and provides valuable insights for managing and mitigating AMR risks in coastal environments.

Development of a bioluminescent immunoassay based on Fc-specific conjugated antibody-nanoluciferase immunoreagents for determining aflatoxin B1.

Aflatoxin B1 (AFB1) is a potent carcinogen, and is among the most hazardous mycotoxins in agricultural products. Therefore, the development of sensitive and convenient detection methods for AFB1 is significant for food safety against mycotoxins. Herein, a bioluminescent enzyme immunoassay (BLEIA) was developed for ultrasensitive detection of AFB1, based on the novel Fc-specific antibody-nanoluciferase (Ab-Nluc) conjugates which were fabricated using an IgG-binding protein-assisted photo-conjugation strategy. In indirect competitive immunoassay format, the proposed BLEIA exhibited the detection limit of 0.0232 ng mL-1, which was 37.4-fold lower than that obtained using the classical enzyme-linked immunosorbent assay (ELISA) based on Ab-horseradish peroxidase (Ab-HRP) chemical conjugates (0.868 ng mL-1). Meanwhile, the BLEIA exhibited high accuracy and precision. Thus, the proposed Fc-specific Ab-Nluc conjugates-based BLEIA provides an ultrasensitive and reliable method for detecting toxins and has potential for use in food safety monitoring.

In vitro efficacy of next-generation dihydrotriazines and biguanides against babesiosis and malaria parasites.

Babesia and Plasmodium pathogens, the causative agents of babesiosis and malaria, are vector-borne intraerythrocytic protozoan parasites, posing significant threats to both human and animal health. The widespread resistance exhibited by these pathogens to various classes of antiparasitic drugs underscores the need for the development of novel and more effective therapeutic strategies. Antifolates have long been recognized as attractive antiparasitic drugs as they target the folate pathway, which is essential for the biosynthesis of purines and pyrimidines, and thus is vital for the survival and proliferation of protozoan parasites. More efficacious and safer analogs within this class are needed to overcome challenges due to resistance to commonly used antifolates, such as pyrimethamine, and to address liabilities associated with the dihydrotriazines, WR99210 and JPC-2067. Here, we utilized an in vitro culture condition suitable for the continuous propagation of Babesia duncani, Babesia divergens, Babesia MO1, and Plasmodium falciparum in human erythrocytes to screen a library of 50 dihydrotriazines and 29 biguanides for their efficacy in vitro and compared their potency and therapeutic indices across different species and isolates. We identified nine analogs that inhibit the growth of all species, including the P. falciparum pyrimethamine-resistant strain HB3, with IC50 values below 10 nM, and display excellent in vitro therapeutic indices. These compounds hold substantial promise as lead antifolates for further development as broad-spectrum antiparasitic drugs.

Investigating the potential mechanism of Pioglitazone in Sepsis-Related brain injury through transcriptomics.

Sepsis-related brain injury (SRBI) refers to brain dysfunction and structural damage caused by sepsis, which is characterized by inflammation, oxidative stress, and destruction of the blood-brain barrier. Pioglitazone is a PPAR-γ agonist in which PPAR-γ acts as an inflammatory modulator, determining the relationship between PPAR-γ and SRBI and inflammatory state is critical for the disease. This study aimed to construct a drug-target-disease network for SRBI and Pioglitazone based on network pharmacology, and to investigate the therapeutic effect and potential mechanism of Pioglitazone in SRBI induced by lipopolysaccharide (LPS) in rats through transcriptomics. To establish a rat Model of SRBI by intraperitoneal injection of LPS (10 mg/kg): SD rats were divided into Control, Model (LPS), Pioglitazone, (LPS + Pioglitazone) and GW9662 group (LPS+GW9662). The effects and potential mechanisms of Pioglitazone in the treatment of SRBI were studied using biochemical indexes, pathological changes and transcriptome-sequencing (RNA-seq). RNA-seq results showed 620 DEGs between the Model and the Pioglitazone groups. Enrichment analysis involved multiple inflammatory response processes and chemokine receptor binding functions. TLR4 and CXCL10 in the Toll signaling pathway may play an important role in SRBI as important targets. Pioglitazone may ameliorate SRBI through the PPAR-γ/TLR4/CXCL10 pathway.

Early-onset palatal myoclonus in Wernekinck commissure syndrome secondary to caudal paramedian midbrain infarction: A case report and a mini review of the literature.

INTRODUCTION: Wernekinck commissure syndrome (WCS) is an extremely rare midbrain syndrome, which selectively destroys the decussation of the superior cerebellar peduncle and the central tegmental tract, which commonly presents with bilateral cerebellar ataxia, dysarthria, and internuclear ophthalmoplegia. Palatal myoclonus in Wernekinck commissure syndrome is uncommon and often occurs as a late phenomenon due to hypertrophic degeneration of bilateral inferior olivary nuclei. MATERIAL AND METHOD: A patient with WCS, admitted to our hospital from December 2023, was chosen for this study, and the syndrome's clinical manifestations, imaging features, and etiology were retrospectively analyzed based on the literature. A 68-year-old right-handed East Asian man presented with dizziness, slurred speech, difficulty with swallowing and walking, and rhythmic contractions of the soft palate. He had several risk factors for ischemic cerebrovascular diseases (age, sex, dyslipidemia, hypertension and smoking history). Brain magnetic resonance imaging showed hyperintensity of DWI and hypointensity of ADC at the caudal midbrain which was around the paramedian mesencephalic tegmentum anterior to the aqueduct of midbrain. RESULTS: He was diagnosed with Wernekinck commissure syndrome (WCS) secondary to caudal paramedian midbrain infarction. He was started on dual antiplatelet therapy (aspirin and clopidogrel) and intensive statin therapy. Blood pressure and glucose were also adjusted. His symptoms improved rapidly, and he walked steadily and speak clearly after 7 days of treatment. CONCLUSIONS: Palatal myoclonus is known to occur as a late phenomenon due to hypertrophic degeneration of bilateral inferior olivary nuclei. However, Our case suggests that palatal myoclonus can occur in the early stages in WCS.

Secreted PTEN binds PLXDC2 on macrophages to drive antitumor immunity and tumor suppression.

Loss of phosphatase and tensin homolog (PTEN) has been linked to an immunosuppressive tumor microenvironment, but its underlying mechanisms remain largely enigmatic. Here, we report that PTEN can be secreted by the transmembrane emp24 domain-containing protein 10 (TMED10)-channeled protein secretion pathway. Inhibiting PTEN secretion from tumor cells contributes to immunosuppression and impairs the tumor-suppressive role of PTEN, while intratumoral injection of PTEN protein promotes antitumor immunity and suppresses tumor growth in mice. Mechanistically, extracellular PTEN binds to the plexin domain-containing protein 2 (PLXDC2) on macrophages, triggering subsequent activation of JAK2-STAT1 signaling, which switches tumor-associated macrophages (TAMs) from the immunosuppressive to inflammatory phenotype, leading to enhanced activation of CD8+ T and natural killer cells. Importantly, PTEN treatment also enhances the therapeutic efficacy of anti-PD-1 treatment in mice and reverses the immune-suppressive phenotype of patient-derived primary TAMs. These data identify a cytokine-like role of PTEN in immune activation and tumor suppression and demonstrate the therapeutic potential for extracellular administration of PTEN in cancer immunotherapy.

[Clinical Characteristics and Prognostic Relevance of Co-Mutated Genes in Acute Myeloid Leukemia Patients with FLT3 Mutations].

OBJECTIVE: To investigate the clinical characteristics and influence of co-mutated gene on acute myeloid leukemia patients (AML) with FMS-like tyrosine kinase-3 (FLT3) mutations. METHODS: A total of 273 FLT3+ AML patients were enrolled, and the co-mutation gene data of the patients were collected to further analyze the prognosis of the patients. FLT3 and other common mutations were quantified by PCR amplification products direct sequencing and second-generation sequencing (NGS). RESULTS: When patients were divided into FLT3- ITD +, FLT3- TKD +, FLT3- ITD ++TKD + and FLT3- ITD -+TKD - group according to the type of FLT3 mutations, it was found that the frequencies of TET2, GATA2, NRAS and ASXL1 mutation were significantly different among the 4 groups (all P < 0.05). When patients were divided into allelic ratio (AR) ≥0.5 and <0.5 group, it was found that the frequencies of FLT3- ITD +, FLT3 -ITD - +TKD -, NPM1, NRAS and C-kit were significantly different between the two groups (all P < 0.05). When patients were divided into normal and abnormal karyotype group, it was found that the frequencies of FLT3- ITD +, FLT3- TKD +, NPM1, GATA2 and C-kit were significantly different between the two groups (all P < 0.05). The median overall survival (OS) of AML patients with FLT3 -TKD + (including FLT3- ITD ++TKD +) was longer than that of patients with FLT3- ITD + alone (P < 0.05). The OS and relapse-free survival (RFS) of AML patients with FLT3++TET2+ were both shorter than those of patients with FLT3++TET2- (both P < 0.05). CONCLUSION: The mutation frequencies of co-mutated genes are correlated with subtypes of FLT3, karyotype and AR. AML patients with FLT3 -TKD + have longer OS than patients with FLT3- ITD + alone, and patients with co-mutation of TET2 have shorter median OS and RFS.

Exploring the impact of gut microbiota on liver health in mice and patients with Wilson disease.

BACKGROUND AND AIMS: Distinctive gut microbial profiles have been observed between patients with Wilson disease (WD) and healthy individuals. Despite this, the exact relationship and influence of gut microbiota on the advancement of WD-related liver damage remain ambiguous. This research seeks to clarify the gut microbiota characteristics in both human patients and mouse models of WD, as well as their impact on liver injury. METHODS: Gut microbial features in healthy individuals, patients with WD, healthy mice and mice with early- and late-stage WD were analysed using 16S rRNA gene sequencing. Additionally, WD-afflicted mice underwent treatment with either an antibiotic cocktail (with normal saline as a control) or healthy microbiota (using disease microbiota as a control). The study assessed gut microbiota composition, hepatic transcriptome profiles, liver copper concentrations and hepatic pathological injuries. RESULTS: Patients with hepatic WD and mice with WD-related liver injury displayed altered gut microbiota composition, notably with a significant reduction in Lactobacillus abundance. Additionally, the abundances of several gut genera, including Lactobacillus, Veillonella and Eubacterium coprostanoligenes, showed significant correlations with the severity of liver injury in patients with WD. In WD mice, antibiotic treatment or transplantation of healthy microbiota altered the gut microbial structure, increased Lactobacillus abundance and modified the hepatic transcriptional profile. These interventions resulted in reduced hepatic copper concentration and alleviation of WD-related liver injury. CONCLUSIONS: Individuals and mice with pronounced WD-related liver injury exhibited shifts in gut microbial composition. Regulating gut microbiota through healthy microbiota transplantation emerges as a promising therapeutic approach for treating WD-related liver injury.

Using large language model (LLM) to identify high-burden informal caregivers in long-term care.

BACKGROUND: The rising global elderly population increases the demand for caregiving, yet traditional methods may not fully assess the challenges faced by vital informal caregivers. OBJECTIVE: To investigate the efficacy of Large Language Model (LLM) in detecting overburdened informal caregivers, benchmarking against rule-based and machine learning methods. METHODS: 1,791 eligible informal caregivers from Southern Taiwan and utilized their textual case summary reports for the LLM. We also employed structured questionnaire results for machine learning models. Furthermore, we leveraged the visualization of the LLM's attention mechanisms to enhance our understanding of the model's interpretative capabilities. RESULTS: The LLM achieved an Area Under the Receiver Operating Characteristic (AUROC) curve of 0.84 and an Area Under the Precision-Recall Curve (AUPRC) of 0.70, marking an 8% and 14% improvement over traditional methods. The visualization of the attention mechanism accurately reflected the evaluations of human experts, concentrating on descriptions of high-burden descriptions and the relationships between caregivers and recipients. CONCLUSION: This research demonstrates the notable capability of LLM to accurately identify high-burden caregivers in Long-term Care (LTC) settings. Compared to traditional approaches, LLM offers an opportunity for the future of LTC research and policymaking.