Therapeutic applications of RNA nanostructures.

RNA-based therapeutics have gained wide public interest in recent years. RNA is a versatile molecule that exists in many forms including mRNA, siRNA, miRNA, ribozymes, and other non-coding RNAs and is primarily applied for gene therapy. RNA is also used as a modular building block to construct RNA nanostructures. The programmable nature of RNA nanostructures enables the generation of simple, modulable, and multi-functional RNA-based therapeutics. Although the therapeutic application of RNA may be limited due to its structural instability, advances in RNA nanotechnology have improved the stability of RNA nanostructures for greater application. Various strategies have been developed to enhance the stability of RNA nanostructures enabling their application in vivo. In this review, we examine the therapeutic applications of RNA nanostructures. Non-immunogenic RNA nanostructures can be rationally designed with functional RNA molecules to modulate gene expression for gene therapy. On the other hand, nucleic acids can be sensed by cellular receptors to elicit an innate immune response, for which certain DNA and RNA motifs can function as adjuvants. Taking advantage of this adjuvant potential, RNA nanostructures can be used for immunotherapy and be designed for cancer vaccines. Thus, we examine the therapeutic application of immunogenic RNA nanostructures for cancer immunotherapy. RNA nanostructures represent promising platforms to design new nanodrugs, gene therapeutics, immunotherapeutic adjuvants, and cancer vaccines. Ongoing research in the field of RNA nanotechnology will continue to empower the development of RNA nanostructure-based therapeutics with high efficacy and limited toxicity.

Acute necrotizing encephalopathy in adult patients with influenza: a case report and review of the literature.

The neurological complications of influenza affect mainly the pediatric Asian population. In the category of influenza-associated encephalopathy, acute necrotizing encephalopathy (ANE) is a rapidly progressive and fulminant brain disorder associated with significant neurological sequelae and mortality. To date, only a few adult cases of influenza-associated ANE have been reported. We describe a 44-year-old woman who presented with rapid progression of consciousness impairment and recurrent generalized convulsions. Influenza was diagnosed three days prior to presentation, and infection with influenza A (H3N2) pdm09 was subsequently confirmed. A diagnosis of ANE was made based on the presence of characteristic brain MRI findings, the exclusion of central nervous system infection, and an elevated serum interleukin-6 level. Pulse steroid therapy followed by tocilizumab was initiated, which led to clinical stabilization and improvement. Genetic testing revealed that the patient carried heterozygous human leukocyte antigen DQB1 03:03 and DRB1 09:01 genotypes. An analysis of the adult cases of influenza-associated ANE in the literature and the present case revealed a wide range of ages (22-71 years), a short interval (median 3 days) between the clinical onset of influenza and ANE, and a high overall mortality rate (32%). The thalamus was the most frequent (91%) location of the lesions. Our report highlights the importance of identifying this devastating but treatable neurological complication of influenza in adults, especially those of Asian descent. As a cytokine storm is the most accepted pathogenic mechanism for ANE, cytokine-directed therapies may be promising treatments for which further investigation is warranted.

The emergence of transposon-driven multidrug resistance in invasive nontypeable Haemophilus influenzae over the last decade.

Nontypeable Haemophilus influenzae (NTHi), once considered a harmless commensal, has emerged as a significant concern due to the increased prevalence of multidrug-resistant (MDR) strains and their association with invasive infections. This study aimed to explore the epidemiology and molecular resistance mechanisms of 51 NTHi isolates collected from patients with invasive infections in northern Taiwan between 2011 and 2020. This investigation revealed substantial genetic diversity, encompassing 29 distinct sequence types and 18 clonal complexes. Notably, 68.6% of the isolates exhibited ampicillin resistance, with 28 categorized as MDR and four isolates were even resistant to up to six antibiotic classes. Among the MDR isolates, 18 pulsotypes were identified, indicating diverse genetic lineages. Elucidation of their resistance mechanisms revealed 18 ß-lactamase-producing amoxicillin-clavulanate-resistant (BLPACR) isolates, 12 ß-lactamase-producing ampicillin-resistant (BLPAR) isolates, and 5 ß-lactamase-nonproducing ampicillin-resistant (BLNAR) isolates. PBP3 analysis revealed 22 unique substitutions in BLPACR and BLNAR, potentially contributing to cephem resistance. Notably, novel transposons, Tn7736-Tn7739, which contain critical resistance genes, were discovered. Three strains harboured Tn7739, containing seven resistance genes [aph(3')-Ia, blaTEM-1, catA, sul2, strA, strB, and tet(B)], while four other strains carried Tn7736, Tn7737, and Tn7738, each containing three resistance genes [blaTEM-1, catA, and tet(B)]. The emergence of these novel transposons underscores the alarming threat posed by highly resistant NTHi strains. Our findings indicated that robust surveillance and comprehensive genomic studies are needed to address this growing public health challenge.

A Retrospective Comparison of Diagnostic Tools of Bullous Pemphigoid for Elderly Patients.

BACKGROUND: Older patients who are predisposed to bullous pemphigoid (BP) may exhibit reluctance to undergo skin biopsy due to potential complications. OBJECTIVES: This study aimed to conduct a comparative evaluation among histology, direct immunofluorescence (DIF), and indirect immunofluorescence (IIF) to determine the optimal diagnostic tool in elderly patients. METHODS: A retrospective study was conducted on 841 patients suspected of having BP. All cases were initially classified as BP and non-BP in accordance with the diagnostic criteria. Student's t-test and chi-squared test examined differences between the 2 groups. We evaluated the sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio detected by the 3 tools. We stratified the analysis by age to compare the performance of the diagnostic tools and examined the risk factors associated with BP using logistic regression. RESULTS: Overall, histology exhibited the highest sensitivity (89.4%), while DIF demonstrated the highest specificity (67.1%). In the elderly, the IIF test exhibited the highest specificity (57.5%), the highest positive likelihood ratio (2.047), and the lowest negative likelihood ratio (0.226). Among patients taking Dipeptidyl Peptidase-4 (DPP-4) inhibitors, IIF demonstrated the highest positive likelihood ratio (3.194) and the second-lowest negative likelihood ratio (0.235). CONCLUSIONS: In cases that elderly patients suspected of having BP are reluctant to undergo skin biopsy, IIF demonstrates the optimal diagnostic method due to its highest positive likelihood ratio, the lowest negative likelihood ratio among the 3 diagnostic measures. Moreover, IIF is found to be a more effective tool for detecting BP in patients using DPP-4 inhibitors.

Body Mass Index Is Associated with Post-Acute Elevations in Biomarkers of Platelet Activation and Inflammation in Unvaccinated Adults Diagnosed with COVID-19 in the Previous 8 Weeks.

INTRODUCTION: Obesity has arisen as a prominent risk factor for COVID-19 severity and long COVID, potentially owed in part to the obesity-induced proinflammatory state. This study aimed to examine relationships among circulating inflammatory biomarkers and body mass index in nonhospitalized adults recently diagnosed with COVID-19. METHODS: This analysis included participants who completed a randomized placebo-controlled trial conducted in October 2020-March 2021. Participants (19-53 years) were unvaccinated and enrolled following COVID-19 diagnosis as allowed by CDC return-to-work guidance. Anthropometrics and biomarkers were assessed at study baseline and week four. We examined the associations between body mass index (BMI) and inflammatory biomarkers via multiple regression models. RESULTS: At study baseline (i.e., the point of enrollment following COVID-19 diagnosis) across all participants (N = 60), a higher BMI was associated with elevations in several inflammatory biomarkers including IL-6 (ß = 7.63, 95% CI = 3.54, 11.89, p = 0.0004), ferritin (ß = 6.31, 95% CI = 1.97, 10.83, p = 0.0047), high sensitivity C-reactive protein (ß = 13.1, 95% CI = 8.03, 18.42, p = < 0.0001), tumor necrosis factor-α (ß = 3.23, 95% CI = 0.91, 5.60, p = 0.0069), IL-12p40 (ß = 3.69, 95% CI = 0.93, 6.52, p = 0.0094), IL-13 (ß = 5.11, 95% CI = 1.00, 9.40, p = 0.0154), and IL-1Ra (ß = 7.57, 95% CI = 3.61, 11.70, p = 0.0003). In control group participants (n = 30) after 4 weeks, a higher BMI was associated with elevations in IL-4 (ß = 17.8, 95% CI = 0.84, 37.6, p = 0.0397) and sP-selectin (ß = 1.16, 95% CI = 0.22, 2.11, p = 0.0182), controlling for baseline and covariates. CONCLUSIONS: Here, BMI was positively associated with circulating biomarkers of platelet activation and inflammation in adults recently diagnosed with COVID-19 after 4 weeks. The shift in post-acute COVID-19 inflammatory biomarkers associated with an increasing BMI noted here shares similarities to biomarkers of LC reported in the literature.

A pre-trained language model for emergency department intervention prediction using routine physiological data and clinical narratives.

INTRODUCTION: The urgency and complexity of emergency room (ER) settings require precise and swift decision-making processes for patient care. Ensuring the timely execution of critical examinations and interventions is vital for reducing diagnostic errors, but the literature highlights a need for innovative approaches to optimize diagnostic accuracy and patient outcomes. In response, our study endeavors to create predictive models for timely examinations and interventions by leveraging the patient's symptoms and vital signs recorded during triage, and in so doing, augment traditional diagnostic methodologies. METHODS: Focusing on four key areas-medication dispensing, vital interventions, laboratory testing, and emergency radiology exams, the study employed Natural Language Processing (NLP) and seven advanced machine learning techniques. The research was centered around the innovative use of BioClinicalBERT, a state-of-the-art NLP framework. RESULTS: BioClinicalBERT emerged as the superior model, outperforming others in predictive accuracy. The integration of physiological data with patient narrative symptoms demonstrated greater effectiveness compared to models based solely on textual data. The robustness of our approach was confirmed by an Area Under the Receiver Operating Characteristic curve (AUROC) score of 0.9. CONCLUSION: The findings of our study underscore the feasibility of establishing a decision support system for emergency patients, targeting timely interventions and examinations based on a nuanced analysis of symptoms. By using an advanced natural language processing technique, our approach shows promise for enhancing diagnostic accuracy. However, the current model is not yet fully mature for direct implementation into daily clinical practice. Recognizing the imperative nature of precision in the ER environment, future research endeavors must focus on refining and expanding predictive models to include detailed timely examinations and interventions. Although the progress achieved in this study represents an encouraging step towards a more innovative and technology-driven paradigm in emergency care, full clinical integration warrants further exploration and validation.

A Novel Out-of-Control Action Plan (OCAP) for Optimizing Efficiency and Quality in the Wafer Probing Process for Semiconductor Manufacturing.

The out-of-control action plan (OCAP) is crucial in the wafer probing process of semiconductor manufacturing as it systematically addresses and corrects deviations, ensuring the high quality and reliability of semiconductor devices. However, the traditional OCAP involves many redundant and complicated processes after failures occur on production lines, which can delay production and escalate costs. To overcome the traditional OCAP's limitations, this paper proposes a novel OCAP aimed at enhancing the wafer probing process in semiconductor manufacturing. The proposed OCAP integrates proactive measures such as preventive maintenance and advanced monitoring technologies, which are tested and verified through a comprehensive experimental setup. Implementing the novel OCAP in a case company's production line reduced machine downtime by over 24 h per week and increased wafer production by about 23 wafers per week. Additionally, probe test yield improved by an average of 1.1%, demonstrating the effectiveness of the proposed method. This paper not only explores the implementation of the novel OCAP but also compares it with the traditional OCAP, highlighting significant improvements in efficiency and production output. The results underscore the potential of advanced OCAP to enhance manufacturing processes by reducing dependency on human judgment, thus lowering the likelihood of errors and improving overall equipment effectiveness (OEE).

What is the best predictor of mortality in patients with type 2 diabetes and chronic kidney disease: mean, variability of HbA1c or HbA1c-Hemoglobin ratio?

AIM: Limitations in the measurement of glycated hemoglobin (HbA1c) in patients with type 2 diabetes (T2D) and chronic kidney disease (CKD) result in uncertainty about the best predictor of mortality among these patients. Our study aimed to determine the association between the mean and average real variability (ARV) of HbA1c, as well as HbA1c-hemoglobin (HH) ratio with mortality among patients with T2D and CKD. MATERIALS AND METHODS: We identified 16,868 T2D patients with stage 3 or above CKD from outpatient visits during 2003-2018. We ascertained all-cause and cardiovascular mortality through linkage to Taiwan's National Death Registry. Mortality rates were estimated using the Poisson distribution, and we conducted Cox proportional hazards regressions to assess relative risks of mortality corresponding to the mean HbA1c, ARV of HbA1c and HH ratio. RESULTS: Compared to patients with a mean HbA1c of 7.0-7.9%, a mean HbA1c < 7.0% was persistently associated with highest risk of all-cause but not cardiovascular mortality after adjusting for confounders. On the contrary, patients with HbA1c-ARV in the second to fourth quartiles and HH ratios in the higher quartiles showed increased risk of all-cause and cardiovascular mortality compared to those in the first quartiles. CONCLUSIONS: HbA1c-ARV was more effective than mean HbA1c or HH ratio in predicting mortality in T2D patients with CKD. Apart from optimal glucose control, multidisciplinary care focusing on glycemic variability is essential for reducing mortality in these patients.

Marine derived macrolide bryostatin 4 inhibits the TGF-ß signaling pathway against acute erythroleukemia.

PURPOSE: Acute erythroleukemia (AEL) is a rare and highly aggressive subtype of acute myeloid leukemia (AML) with an extremely poor prognosis when treated with available drugs. Therefore, new investigational agents capable of inducing remission are urgently required. METHODS: Bioinformatics analysis, western blot and qRT-PCR were used to reveal the potential biological mechanism of bryostatin 4 (B4), an antineoplastic macrolide derived from the marine bryozoan Bugula neritina. Then, in vivo experiments were conducted to evaluate the role of transforming growth factor (TGF)-ß signaling in the progression of AEL. RESULTS: Our results revealed that the proliferation of K562 cells and TF-1 cells was significantly inhibited by B4 at IC50 values of 37 nM and 52 nM, respectively. B4 inhibited TGF-ß signaling and its downstream pathway targets, particularly the phosphorylation of Smad2, Smad3, Ras, C-RAF, ERK1/2, and MEK. B4 also played an important role in cell invasion and migration in K562 cells and TF-1 cells by reducing the protein levels of the mesenchymal cell marker vimentin. Moreover, Flow cytometry and western blot analyses demonstrated that B4 induced apoptosis and initiated G0/G1 phase arrest by modulating mitochondrial dysfunction and cyclin-dependent kinase (CDK) expression. CONCLUSION: These findings indicated that B4 could inhibit the proliferation, migration, invasion, and TGF-ß signaling pathways of AEL cells, thus suggesting that B4 possesses therapeutic potential as a treatment for AEL.

Genomic characterization of Escherichia coli harbor a polyketide synthase ( pks ) island associated with colorectal cancer (CRC) development.

The E. coli strain harboring the polyketide synthase ( Pks) island encodes the genotoxin colibactin, a secondary metabolite reported to have severe implications for human health and for the progression of colorectal cancer. The present study involved whole-genome-wide comparison and phylogenetic analysis of pks harboring E. coli isolates to gain insight into the distribution and evolution of these organism. Fifteen E. coli strains isolated from patients with ulcerative colitis were sequenced, 13 of which harbored pks islands. In addition, 2,654 genomes from the public database were also screened for pks harboring E. coli genomes, 158 of which were pks -positive isolates. Whole-genome-wide comparison and phylogenetic analysis revealed that 171 (158+13) pks -positive isolates belonged to phylogroup B2, and most of the isolates associated to sequence types ST73 and ST95. One isolate from an ulcerative colitis (UC) patient was of the sequence type ST8303. The maximum likelihood tree based on the core genome of pks -positive isolates revealed horizontal gene transfer across sequence types and serotypes. Virulome and resistome analyses revealed the preponderance of virulence genes and a reduced number of antimicrobial genes in Pks -positive isolates. This study strongly contributes to understanding the evolution of pks islands in E. coli .

Discovery of a mu-opioid receptor modulator that in combination with morphinan antagonists induces analgesia.

Morphinan antagonists, which block opioid effects at mu-opioid receptors, have been studied for their analgesic potential. Previous studies have suggested that these antagonists elicit analgesia with fewer adverse effects in the presence of the mutant mu-opioid receptor (MOR; S196A). However, introducing a mutant receptor for medical applications represents significant challenges. We hypothesize that binding a chemical compound to the MOR may elicit a comparable effect to the S196A mutation. Through high-throughput screening and structure-activity relationship studies, we identified a modulator, 4-(2-(4-fluorophenyl)-4-oxothiazolidin-3-yl)-3-methylbenzoic acid (BPRMU191), which confers agonistic properties to small-molecule morphinan antagonists, which induce G protein-dependent MOR activation. Co-application of BPRMU191 and morphinan antagonists resulted in MOR-dependent analgesia with diminished side effects, including gastrointestinal dysfunction, antinociceptive tolerance, and physical and psychological dependence. Combining BPRMU191 and morphinan antagonists could serve as a potential therapeutic strategy for severe pain with reduced adverse effects and provide an avenue for studying G protein-coupled receptor modulation.

Marine sponge-derived alkaloid inhibits the PI3K/AKT/mTOR signaling pathway against diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous non-Hodgkin lymphoma that is extremely aggressive and has an intermediate to high malignancy. Some patients still experience treatment failure, relapse, or resistance to rituximab, cyclophosphamide, adriamycin, vincristine, and prednisone (R-CHOP) therapy. Therefore, there is an urgent need for further research on new agents for the treatment of DLBCL. AP-48 is an aaptamine alkaloid analog with potent anti-tumor effects that originates from marine natural products. In this study, we found that AP-48 exhibits dose-dependent cytotoxicity in DLBCL cell lines. Flow cytometry showed that AP-48 induced cell cycle arrest in the G0/G1 phase in SU-DHL-4 and Farage cells and in the S phase in WSU-DLCL-2 cells. AP-48 also accelerated apoptosis via the caspase-3-mediated intrinsic apoptotic pathway. Further experiments demonstrated that AP-48 exerted its anti-DLBCL effects through the PI3K/AKT/mTOR pathway, and that the PI3K agonist YS49 partially alleviated the inhibition of cell proliferation and apoptosis induced by AP-48. Finally, in a tumor xenograft model, AP-48 inhibited tumor growth and promoted apoptosis in tumor tissues, indicating its therapeutic potential in DLBCL.

Machine Learning Model for Anesthetic Risk Stratification for Gynecologic and Obstetric Patients: Cross-Sectional Study Outlining a Novel Approach for Early Detection.

BACKGROUND: Preoperative evaluation is important, and this study explored the application of machine learning methods for anesthetic risk classification and the evaluation of the contributions of various factors. To minimize the effects of confounding variables during model training, we used a homogenous group with similar physiological states and ages undergoing similar pelvic organ-related procedures not involving malignancies. OBJECTIVE: Data on women of reproductive age (age 20-50 years) who underwent gestational or gynecological surgery between January 1, 2017, and December 31, 2021, were obtained from the National Taiwan University Hospital Integrated Medical Database. METHODS: We first performed an exploratory analysis and selected key features. We then performed data preprocessing to acquire relevant features related to preoperative examination. To further enhance predictive performance, we used the log-likelihood ratio algorithm to generate comorbidity patterns. Finally, we input the processed features into the light gradient boosting machine (LightGBM) model for training and subsequent prediction. RESULTS: A total of 10,892 patients were included. Within this data set, 9893 patients were classified as having low anesthetic risk (American Society of Anesthesiologists physical status score of 1-2), and 999 patients were classified as having high anesthetic risk (American Society of Anesthesiologists physical status score of >2). The area under the receiver operating characteristic curve of the proposed model was 0.6831. CONCLUSIONS: By combining comorbidity information and clinical laboratory data, our methodology based on the LightGBM model provides more accurate predictions for anesthetic risk classification. TRIAL REGISTRATION: Research Ethics Committee of the National Taiwan University Hospital 202204010RINB; https://www.ntuh.gov.tw/RECO/Index.action.

CXCR7 activation evokes the anti-PD-L1 antibody against glioblastoma by remodeling CXCL12-mediated immunity.

The interaction between glioblastoma cells and glioblastoma-associated macrophages (GAMs) influences the immunosuppressive tumor microenvironment, leading to ineffective immunotherapies. We hypothesized that disrupting the communication between tumors and macrophages would enhance the efficacy of immunotherapies. Transcriptomic analysis of recurrent glioblastoma specimens indicated an enhanced neuroinflammatory pathway, with CXCL12 emerging as the top-ranked gene in secretory molecules. Single-cell transcriptome profiling of naïve glioblastoma specimens revealed CXCL12 expression in tumor and myeloid clusters. An analysis of public glioblastoma datasets has confirmed the association of CXCL12 with disease and PD-L1 expression. In vitro studies have demonstrated that exogenous CXCL12 induces pro-tumorigenic characteristics in macrophage-like cells and upregulated PD-L1 expression through NF-κB signaling. We identified CXCR7, an atypical receptor for CXCL12 predominantly present in tumor cells, as a negative regulator of CXCL12 expression by interfering with extracellular signal-regulated kinase activation. CXCR7 knockdown in a glioblastoma mouse model resulted in worse survival outcomes, increased PD-L1 expression in GAMs, and reduced CD8+ T-cell infiltration compared with the control group. Ex vivo T-cell experiments demonstrated enhanced cytotoxicity against tumor cells with a selective CXCR7 agonist, VUF11207, reversing GAM-induced immunosuppression in a glioblastoma cell-macrophage-T-cell co-culture system. Notably, VUF11207 prolonged survival and potentiated the anti-tumor effect of the anti-PD-L1 antibody in glioblastoma-bearing mice. This effect was mitigated by an anti-CD8ß antibody, indicating the synergistic effect of VUF11207. In conclusion, CXCL12 conferred immunosuppression mediated by pro-tumorigenic and PD-L1-expressing GAMs in glioblastoma. Targeted activation of glioblastoma-derived CXCR7 inhibits CXCL12, thereby eliciting anti-tumor immunity and enhancing the efficacy of anti-PD-L1 antibodies.

Calycosin Enhances Heat Shock Related-Proteins in H9c2 Cells to Modulate Survival and Apoptosis against Heat Shock.

Heat shock proteins (HSPs), which function as chaperones, are activated in response to various environmental stressors. In addition to their role in diverse aspects of protein production, HSPs protect against harmful protein-related stressors. Calycosin exhibits numerous beneficial properties. This study aims to explore the protective effects of calycosin in the heart under heat shock and determine its underlying mechanism. H9c2 cells, western blot, TUNEL staining, flow cytometry, and immunofluorescence staining were used. The time-dependent effects of heat shock analyzed using western blot revealed increased HSP expression for up to 2[Formula: see text]h, followed by protein degradation after 4[Formula: see text]h. Hence, a heat shock damage duration of 4[Formula: see text]h was chosen for subsequent investigations. Calycosin administered post-heat shock demonstrated dose-dependent recovery of cell viability. Under heat shock conditions, calycosin prevented the apoptosis of H9c2 cells by upregulating HSPs, suppressing p-JNK, enhancing Bcl-2 activation, and inhibiting cleaved caspase 3. Calycosin also inhibited Fas/FasL expression and activated cell survival markers (p-PI3K, p-ERK, p-Akt), indicating their cytoprotective properties through PI3K/Akt activation and JNK inhibition. TUNEL staining and flow cytometry confirmed that calycosin reduced apoptosis. Moreover, calycosin reversed the inhibitory effects of quercetin on HSF1 and Hsp70 expression, illustrating its role in enhancing Hsp70 expression through HSF1 activation during heat shock. Immunofluorescence staining demonstrated HSF1 translocation to the nucleus following calycosin treatment, emphasizing its cytoprotective effects. In conclusion, calycosin exhibits pronounced protective effects against heat shock-induced damages by modulating HSP expression and regulating key signaling pathways to promote cell survival in H9c2 cells.

Use of Sodium-Glucose Co-Transporter 2 Inhibitors in Patients With Type 2 Diabetes and the Incidence of Retinal Vein Occlusion in Taiwan.

Purpose: The purpose of this study was to evaluate the risk of newly diagnosed retinal vein occlusion (RVO) in patients with type 2 diabetes (T2D) using sodium-glucose cotransporter-2 inhibitors (SGLT-2i) compared to dipeptidyl peptidase-4 inhibitors (DPP-4i). Methods: Claims data from the National Health Insurance Research Database of Taiwan were used in this nationwide retrospective cohort study. A target trial emulation framework was applied. Patients with T2D with no prior diagnosis of RVO who had newly commenced treatment with SGLT-2i or DPP-4i between May 1, 2016, and December 31, 2020, were included. Potential systematic differences in baseline characteristics between the paired groups were controlled using stabilized inverse probability of treatment weighting. The outcome of interest was incident RVO. The hazard ratio (HR) for SGLT-2i compared with that of DPP-4i was estimated using a Cox regression model. Results: Data from 123,567 and 578,665 patients receiving SGLT-2i and DPP-4i, respectively, were analyzed. The incidence of RVO was lower in patients newly receiving SGLT-2i (0.59 events per 1000 person-years) compared to those receiving DPP-4i (0.77 events per 1000 person-years) over a mean follow-up of 1.61 years. SGLT-2i users had a significantly lower risk of developing RVO compared with DPP-4i users (HR = 0.76, 95% confidence interval [CI] = 0.59-0.98). In the individual outcome analysis, SGLT-2i use was significantly associated with a lower risk of branch RVO (HR = 0.71, 95% CI = 0.52-0.96), but not central RVO (HR = 0.84, 95% CI = 0.57-1.24). Conclusions: The risk of developing RVO was lower in patients with T2D receiving SGLT-2i compared with that in those receiving DPP-4i.

Protein Binder Toolbox for Studies of Solute Carrier Transporters.

Transporters of the solute carrier superfamily (SLCs) are responsible for the transmembrane traffic of the majority of chemical substances in cells and tissues and are therefore of fundamental biological importance. As is often the case with membrane proteins that can be heavily glycosylated, a lack of reliable high-affinity binders hinders their functional analysis. Purifying and reconstituting transmembrane proteins in their lipidic environments remains challenging and standard approaches to generate binders for multi-transmembrane proteins, such as SLCs, channels or G protein-coupled receptors (GPCRs) are lacking. While generating protein binders to 27 SLCs, we produced full length protein or cell lines as input material for binder generation by selected binder generation platforms. As a result, we obtained 525 binders for 22 SLCs. We validated the binders with a cell-based validation workflow using immunofluorescent and immunoprecipitation methods to process all obtained binders. Finally, we demonstrated the potential applications of the binders that passed our validation pipeline in structural, biochemical, and biological applications using the exemplary protein SLC12A6, an ion transporter relevant in human disease. With this work, we were able to generate easily renewable and highly specific binders against SLCs, which will greatly facilitate the study of this neglected protein family. We hope that the process will serve as blueprint for the generation of binders against the entire superfamily of SLC transporters.

The Interrelationship of Benefit Finding, Demoralization, and Stigma among Patients with Parkinson's Disease and Their Caregivers.

Parkinson's disease (PD) is a debilitating neurodegenerative disease with a relentlessly progressive course of illness. This study aimed to assess the dyadic dynamics of benefit finding (BF), demoralization, and stigma on the depression severity of PD patients and their caregivers. This study used a cross-sectional design with purposive sampling. In total, 120 PD patients and 120 caregivers were recruited from the neurological ward or neurological outpatient clinic of a medical center in Taiwan from October 2021 to September 2022. PD patients and their caregivers were enrolled and assessed using the Mini International Neuropsychiatric Interview, the Benefit Finding scale, Demoralization Scale, Stigma Subscale of the Explanatory Model Interview Catalogue, and Taiwanese Depression Questionnaire. Among the 120 patients and 120 caregivers that successfully completed the study, 41.7% (N = 50) and 60% (N = 72) were female, respectively. The most common psychiatric diagnoses of both the PD patients (17.5%) and their caregivers (13.3%) were depressive disorders. Using structural equation modeling, we found that the stigma, BF, and demoralization of PD patients might contribute to their depression severity. Demoralization and stigma of PD patients' caregivers might also contribute to the depression severity of PD patients. Caregivers' BF and demoralization were significantly linked with their depression severity. PD patients' BF degree and their caregivers' BF degree had significant interactive effects. Both patients' and their caregivers' stigma levels had significant interactive effects. Clinicians should be aware of and manage these contributing factors between PD patients and their caregivers in order to prevent them from exacerbating each other's depression.

Using a clinical narrative-aware pre-trained language model for predicting emergency department patient disposition and unscheduled return visits.

The increasing prevalence of overcrowding in Emergency Departments (EDs) threatens the effective delivery of urgent healthcare. Mitigation strategies include the deployment of monitoring systems capable of tracking and managing patient disposition to facilitate appropriate and timely care, which subsequently reduces patient revisits, optimizes resource allocation, and enhances patient outcomes. This study used âˆ¼ 250,000 emergency department visit records from Taipei Medical University-Shuang Ho Hospital to develop a natural language processing model using BlueBERT, a biomedical domain-specific pre-trained language model, to predict patient disposition status and unplanned readmissions. Data preprocessing and the integration of both structured and unstructured data were central to our approach. Compared to other models, BlueBERT outperformed due to its pre-training on a diverse range of medical literature, enabling it to better comprehend the specialized terminology, relationships, and context present in ED data. We found that translating Chinese-English clinical narratives into English and textualizing numerical data into categorical representations significantly improved the prediction of patient disposition (AUROC = 0.9014) and 72-hour unscheduled return visits (AUROC = 0.6475). The study concludes that the BlueBERT-based model demonstrated superior prediction capabilities, surpassing the performance of prior patient disposition predictive models, thus offering promising applications in the realm of ED clinical practice.