Development of deep learning algorithm for detecting dyskalemia based on electrocardiogram.

Dyskalemia is a common electrolyte abnormality. Since dyskalemia can cause fatal arrhythmias and cardiac arrest in severe cases, it is crucial to monitor serum potassium (K+) levels on time. We developed deep learning models to detect hyperkalemia (K+ ≥ 5.5 mEq/L) and hypokalemia (K+ < 3.5 mEq/L) from electrocardiograms (ECGs), which are noninvasive and can be quickly measured. The retrospective cohort study was conducted at two hospitals from 2006 to 2020. The training set, validation set, internal testing cohort, and external validation cohort comprised 310,449, 15,828, 23,849, and 130,415 ECG-K+ samples, respectively. Deep learning models demonstrated high diagnostic performance in detecting hyperkalemia (AUROC 0.929, 0.912, 0.887 with sensitivity 0.926, 0.924, 0.907 and specificity 0.706, 0.676, 0.635 for 12-lead, limb-lead, lead I ECGs) and hypokalemia (AUROC 0.925, 0.896, 0.885 with sensitivity 0.912, 0.896, 0.904 and specificity 0.790, 0.734, 0.694) in the internal testing cohort. The group predicted to be positive by the hyperkalemia model showed a lower 30-day survival rate compared to the negative group (p < 0.001), supporting the clinical efficacy of the model. We also compared the importance of ECG segments (P, QRS, and T) on dyskalemia prediction of the model for interpretability. By applying these models in clinical practice, it will be possible to diagnose dyskalemia simply and quickly, thereby contributing to the improvement of patient outcomes.

A 13.56-MHz 93.5%-Efficiency Optimal On/Off Timing Tracking Active Rectifier with Digital Feedback-Based Adaptive Delay Control.

This paper presents an adaptive active rectifier with digital feedback delay controllers (DFDC) which quickly tracks optimal on/off timing against input voltage and load variations. To efficiently generate the on/off transition, the proposed active rectifier adopts dynamically controlled coarse/fine delay lines rather than using conventional power-hungry static comparators, while removing the risk of unwanted multiple driving pulses to pass transistors. DFDC conducts the dual-loop digital feedback to independently adjust on/off timing with high-speed 13.56-MHz loop bandwidth, improving the voltage conversion ratio (VCR) and power conversion efficiency (PCE). DFDC can enable real-time power-saving mode control that automatically masks clock-toggling to non-essential blocks to minimize dynamic power loss while driving power transistors. To validate the efficacy of the proposed adaptive rectifier during digital feedback and settling procedures, experiments were carried out with 0.25 µm CMOS prototype at the carrier frequency of 13.56-MHz, input voltages between 1.7 and 2.6 V, and load ranges from 0.33 to 2.2 kΩ. The proposed active rectifier employing DFDC achieves a peak PCE of 93.5% and the peak VCR of 96.3% at the output power of 12.52 mW and 2.02 mW, respectively.

A Multi-bit ECRAM-Based Analog Neuromorphic System with High-Precision Current Readout Achieving 97.3% Inference Accuracy.

This article proposes an analog neuromorphic system that enhances symmetry, linearity, and endurance by using a high-precision current readout circuit for multi-bit nonvolatile electro-chemical random-access memory (ECRAM). For on-chip training and inference, the system uses activation modules and matrix processing units to manage analog update/read paths and perform precise output sensing with feedback-based current scaling on the ECRAM array. The 250nm CMOS neuromorphic chip was tested with a 32 x 32 ECRAM synaptic array, achieving linear and symmetric updates and accurate read operations. The proposed circuit system updates the 32 x 32 ECRAM across 100 levels, maintaining consistent synaptic weights, and operates with an output error rate of up to 2.59% per column. It consumes 5.9 mW of power excluding the ECRAM array and achieves 97.3% inference accuracy on the MNIST dataset, close to the software-confirmed 97.78%, with only the final layer (64 x 10) mapped to the ECRAM.

Development of Ocular Muscle Stimulation Systems and Optimization of Electrical Stimulus Parameters for Paralytic Strabismus Treatment.

Paralysis of the extraocular muscles can lead to complications such as strabismus, diplopia, and loss of stereopsis. Current surgical treatments aim to mitigate these issues by resecting the paralyzed muscle or transposing the other recti muscles to the paralyzed muscle, but they do not fully improve the patient's quality of life. Electrical stimulation shows promise, while requiring further in vivo experiments and research on various stimulation parameters. In this study, we conducted experiments on rabbits to stimulate the superior rectus (SR) muscles using different parameters and stimulation waveforms. To provide various types of electrical stimulation, we developed the ocular muscle stimulation systems capable of both current controlled stimulation (CCS) and high-frequency stimulation (HFS), along with the chip that enables energy-efficient and safe switched-capacitor stimulation (SCS). We also developed electrodes for easy implantation and employed safe and efficient stimulation methods including CCS, SCS, and HFS. The in vivo animal experiments on normal and paralyzed SR muscles of rabbits showed that eyeball abduction angles were proportional to the current and pulse width of the stimulation. With the decaying exponential stimuli of the SCS system, eyeball abductions were 2.58× and 5.65× larger for normal and paralyzed muscles, respectively, compared to the rectangular stimulus of CCS. HFS achieved 0.92× and 0.26× abduction for normal and paralyzed muscles, respectively, with half energy compared to CCS. In addition, the continuous changes in eyeball abduction angle in response to varying stimulation intensity over time were observed.

Patient-reported outcomes between whole-breast plus regional irradiation and whole-breast irradiation only in pN1 breast cancer after breast conserving surgery and taxane-based chemotherapy: A randomized phase 3 clinical trial (KROG 17-01).

BACKGROUND: The role of regional node irradiation (RNI) with whole-breast irradiation (WBI) in patients with pN1 breast cancer receiving taxane-based adjuvant chemotherapy is not well defined. The KROG 1701 trial, a phase III, multicenter, non-inferiority study, aimed to compare the disease-free survival between WBI+RNI and WBI alone in this patient cohort. Comprehensive patient-reported outcomes (PROs) collected at multiple time points are reported. METHODS: The trial (NCT03269981) enrolled patients with pN1 breast cancer after breast-conserving surgery and taxane-based adjuvant chemotherapy, allocating them to receive either WBI +RNI or WBI only. PROs were assessed using EORTC QLQ-C30 and QLQ-BR23 modules at baseline, during RT, and at subsequent follow-up intervals of 3-6 months, and annually up to 4years. RESULTS: From April 2017 to December 2021, 840 patients were enrolled; 777 received intervention as assigned, and 750 completed baseline PRO questionnaires (387 in WBI+RNI, 363 in WBI only). All PRO domains showed improvements over time (p<0.001). During RT, the WBI+RNI group reported greater fatigue and nausea. Higher arm symptom scores were observed in the WBI+RNI group 3 months post-treatment (p=0.030). No other significant PRO domain differences, including arm/breast symptoms, were observed between the two groups. CONCLUSION: In patients with pN1 breast cancer treated with taxane-based chemotherapy, adding RNI to WBI resulted in minor, temporary declines in specific PRO domains, but these differences were not clinically significant. This indicates that overall patient experience between WBI+RNI and WBI is comparable, supporting the safety and patient tolerability of both treatments.

Metabolic Dysfunction-Associated Steatotic Liver Disease Is Associated with Increased Risk of Kidney Cancer: A Nationwide Study.

Background: This study investigated the association between metabolic dysfunction-associated steatotic liver disease (MASLD) and Kidney Cancer Risk, as the incidence of both diseases gradually increases owing to metabolic health issues. Methods: Participants (aged 20-79) undergoing a national health examination between 2009 and 2010 were monitored for new-onset kidney cancer. The MASLD spectrum was classified as non-MASLD, MASLD, or MASLD with increased alcohol uptake (MetALD). Kidney Cancer Risk associated with the MASLD spectrum was estimated using multivariate Cox proportional hazard models. Age- and sex-stratified analyses were also performed. Results: Among 8,829,510 participants (median follow-up 13.3 years), the proportion of non-MASLD, MASLD, and MetALD was 64.9%, 30.3%, and 4.7%, respectively, with newly developed kidney cancer in 17,555 participants. Kidney cancer was significantly increased with MASLD (adjusted hazard ratio [aHR] 1.51, 95% confidence interval [CI] 1.46-1.56) and MetALD (aHR 1.51, 95% CI 1.42-1.61), compared with the non-MASLD group. Kidney Cancer Risk was the highest among young populations (aHR 1.93, 95% CI 1.77-2.11 for MASLD and aHR 1.91, 95% CI 1.65-2.22 for MetALD), according to stratification analysis. Furthermore, the cumulative relationship between metabolic dysfunction and Kidney Cancer Risk was confirmed across all MASLD spectra. Conclusions: Our study highlights the positive association between MASLD and Kidney Cancer Risk, emphasizing a comprehensive approach to metabolic health. This also serves as a call to devote closer attention to the metabolic health of younger patients.

Preoperative Factors on Loss of Range of Motion after Posterior Cervical Foraminotomy.

Background and Objectives: Posterior cervical foraminotomy (PCF) aims to resolve cervical radiculopathy while preserving range of motion (ROM). However, its effectiveness in maintaining ROM is uncertain. This study investigates the changes in ROM after PCF and identifies preoperative factors that influence ROM reduction post surgery. Materials and Methods: This retrospective cohort study included patients treated at our hospital from August 2016 to September 2021. Clinical outcomes were assessed using the visual analog scale (VAS) for neck and arm pain and the neck disability index (NDI). Radiological outcomes included the segmental angle (SA), cervical angle (CA), C2-C7 SVA, Pfirrmann grade, extent of facetectomy, foraminal stenosis, and ROM. Patients were categorized into two groups based on segmental ROM changes: decreased (Group D) and maintained (Group M). Radiological and clinical outcomes were compared between the groups. Univariate and multivariate regression analyses were performed to identify risk factors for ROM loss after PCF. Results: 76 patients were included: 34 in Group D and 42 in Group M, with no demographic differences. Preoperatively, Group D had significantly larger flexion segmental and cervical angles than Group M (segmental, p < 0.001; cervical, p = 0.001). Group D also had a higher Pfirrmann grade (p = 0.014) and more bony bridge formations (p = 0.004). While no significant differences were observed in arm pain VAS and NDI scores, Group D exhibited worse neck pain VAS at the last follow-up (p = 0.03). Univariate linear regression indicated that preoperative segmental ROM (p < 0.001, B = 0.82) and bony bridge formation (p = 0.046, B = 5.33) were significant predictors of ROM loss post PCF. Conclusions: Patients with higher preoperative flexion angles and Pfirrmann grades at the operative level are at an increased risk for ROM loss and neck pain and often exhibit bony bridge formation. Accounting for these factors can improve surgical planning and patient outcomes.

Cryo-EM structure of human class C orphan GPCR GPR179 involved in visual processing.

GPR179, an orphan class C GPCR, is expressed at the dendritic tips of ON-bipolar cells in the retina. It plays a pivotal role in the initial synaptic transmission of visual signals from photoreceptors, and its deficiency is known to be the cause of complete congenital stationary night blindness. Here, we present the cryo-electron microscopy structure of human GPR179. Notably, the transmembrane domain (TMD) of GPR179 forms a homodimer through the TM1/7 interface with a single inter-protomer disulfide bond, adopting a noncanonical dimerization mode. Furthermore, the TMD dimer exhibits architecture well-suited for the highly curved membrane of the dendritic tip and distinct from the flat membrane arrangement observed in other class C GPCR dimers. Our structure reveals unique structural features of GPR179 TMD, setting it apart from other class C GPCRs. These findings provide a foundation for understanding signal transduction through GPR179 in visual processing and offers insights into the underlying causes of ocular diseases.

Comparison of NLP machine learning models with human physicians for ASA Physical Status classification.

The American Society of Anesthesiologist's Physical Status (ASA-PS) classification system assesses comorbidities before sedation and analgesia, but inconsistencies among raters have hindered its objective use. This study aimed to develop natural language processing (NLP) models to classify ASA-PS using pre-anesthesia evaluation summaries, comparing their performance to human physicians. Data from 717,389 surgical cases in a tertiary hospital (October 2004-May 2023) was split into training, tuning, and test datasets. Board-certified anesthesiologists created reference labels for tuning and test datasets. The NLP models, including ClinicalBigBird, BioClinicalBERT, and Generative Pretrained Transformer 4, were validated against anesthesiologists. The ClinicalBigBird model achieved an area under the receiver operating characteristic curve of 0.915. It outperformed board-certified anesthesiologists with a specificity of 0.901 vs. 0.897, precision of 0.732 vs. 0.715, and F1-score of 0.716 vs. 0.713 (all p <0.01). This approach will facilitate automatic and objective ASA-PS classification, thereby streamlining the clinical workflow.

Epigenetic therapy potentiates transposable element transcription to create tumor-enriched antigens in glioblastoma cells.

Inhibiting epigenetic modulators can transcriptionally reactivate transposable elements (TEs). These TE transcripts often generate unique peptides that can serve as immunogenic antigens for immunotherapy. Here, we ask whether TEs activated by epigenetic therapy could appreciably increase the antigen repertoire in glioblastoma, an aggressive brain cancer with low mutation and neoantigen burden. We treated patient-derived primary glioblastoma stem cell lines, an astrocyte cell line and primary fibroblast cell lines with epigenetic drugs, and identified treatment-induced, TE-derived transcripts that are preferentially expressed in cancer cells. We verified that these transcripts could produce human leukocyte antigen class I-presented antigens using liquid chromatography with tandem mass spectrometry pulldown experiments. Importantly, many TEs were also transcribed, even in proliferating nontumor cell lines, after epigenetic therapy, which suggests that targeted strategies like CRISPR-mediated activation could minimize potential side effects of activating unwanted genomic regions. The results highlight both the need for caution and the promise of future translational efforts in harnessing treatment-induced TE-derived antigens for targeted immunotherapy.

Effect of Erector Spinae Plane Block on Postoperative Quality of Recovery in Patients Undergoing Transforaminal or Oblique Lumbar Interbody Fusion: A Randomized Controlled Trial.

BACKGROUND: Erector spinae plane block (ESPB) can has been used for analgesia after lumbar spine surgery. However, its effect on postoperative quality of recovery (QoR) remains underexplored in patients undergoing transforaminal lumbar interbody fusion (TLIF) or oblique lumbar interbody fusion (OLIF). This study hypothesized that ESPB would improve postoperative QoR in this patient cohort. METHODS: Patients undergoing TLIF or OLIF were randomized into ESPB (n=38) and control groups (n=38). In the ESPB group, 25 mL of 0.375% bupivacaine was injected into each erector spinae plane at the T12 level under ultrasound guidance before skin incision. Multimodal analgesia, including wound infiltration, was applied in both groups. The QoR-15 score was measured before surgery and 1 day (primary outcome) and 3 days after surgery. Postoperative pain at rest and during ambulation and postoperative ambulation were also evaluated for 3 days after surgery. RESULTS: Perioperative QoR-15 scores were not significantly different between the ESPB and control groups including at 1 day after surgery (80±28 vs. 81±25, respectively; P=0.897). Patients in the ESPB group had a significantly lower mean (±SD) pain score during ambulation 1 hour after surgery (7±3 vs. 9±1, respectively; P=0.013) and significantly shorter median (interquartile range) time to the first ambulation after surgery (2.0 [1.0 to 5.5] h vs. 5.0 [1.8 to 10.0] h, respectively; P=0.038). There were no between-group differences in pain scores at other times or in the cumulative number of postoperative ambulations. CONCLUSION: ESPB, as performed in this study, did not improve the QoR after TLIF or OLIF with multimodal analgesia.

A machine learning model to predict liver-related outcomes after the functional cure of chronic hepatitis B.

BACKGROUND & AIMS: The risk of hepatocellular carcinoma (HCC) and hepatic decompensation persists after hepatitis B surface antigen (HBsAg) seroclearance. This study aimed to develop and validate a machine learning model to predict the risk of liver-related outcomes (LROs) following HBsAg seroclearance. METHODS: A total of 4,787 consecutive patients who achieved HBsAg seroclearance between 2000 and 2022 were enrolled from 6 centers in South Korea and a territory-wide database in Hong Kong, comprising the training (n=944), internal validation (n=1,102), and external validation (n=2,741) cohorts. Three machine learning-based models were developed and compared in each cohort. The primary outcome was the development of any LRO, including HCC, decompensation, and liver-related death. RESULTS: During a median follow-up of 55.2 (interquartile range=30.1-92.3) months, 123 LROs were confirmed (1.1%/person-year) in the Korean cohort. A model with the best predictive performance in the training cohort was selected as the final model (designated as PLAN-B-CURE), which was constructed using a gradient boosting algorithm and 7 variables (age, sex, diabetes, alcohol consumption, cirrhosis, albumin, and platelet count). Compared to previous HCC prediction models, PLAN-B-CURE showed significantly superior accuracy in the training cohort (c-index: 0.82 vs. 0.63-0.70, all P<0.001; area under the receiver operating characteristic curve: 0.86 vs. 0.62-0.72, all P<0.01; area under the precision-recall curve: 0.53 vs. 0.13-0.29, all P<0.01). PLAN-B-CURE showed a reliable calibration function (Hosmer-Lemeshow test P>0.05) and these results were reproduced in the internal and external validation cohorts. CONCLUSION: This novel machine learning model consisting of 7 variables provides reliable risk prediction of LRO after HBsAg seroclearance that can be used for personalized surveillance.

Biodegradation of low-density polyethylene by mixed fungi composed of Alternaria sp. and Trametes sp. isolated from landfill sites.

With the development of industry and modern manufacturing, nondegradable low-density polyethylene (LDPE) has been widely used, posing a rising environmental hazard to natural ecosystems and public health. In this study, we isolated a series of LDPE-degrading fungi from landfill sites and carried out LDPE degradation experiments by combining highly efficient degrading fungi in pairs. The results showed that the mixed microorganisms composed of Alternaria sp. CPEF-1 and Trametes sp. PE2F-4 (H-3 group) had a greater degradation effect on heat-treated LDPE (T-LDPE). After 30 days of inoculation with combination strain H-3, the weight loss rate of the T-LDPE film was approximately 154% higher than that of the untreated LDPE (U-LDPE) film, and the weight loss rate reached 0.66 ± 0.06%. Environmental scanning electron microscopy (ESEM) and Fourier transform infrared spectroscopy (FTIR) were used to further investigate the biodegradation impacts of T-LDPE, including the changes on the surface and depolymerization of the LDPE films during the fungal degradation process. Our findings revealed that the combined fungal treatment is more effective at degrading T-LDPE than the single strain treatment, and it is expected that properly altering the composition of the microbial community can help lessen the detrimental impact of plastics on the environment.

Discovery of A-910, a Highly Potent and Orally Bioavailable Dual MerTK/Axl-Selective Tyrosine Kinase Inhibitor.

TAM receptor tyrosine kinases have emerged as promising therapeutic targets for cancer treatment due to their roles in both tumor intrinsic survival mechanisms and suppression of antitumor immunity within the tumor microenvironment. Inhibiting MerTK and Axl selectively is believed to hinder cancer cell survival, reverse the protumor myeloid phenotype, and suppress efferocytosis, thereby eliciting an antitumor immune response. In this study, we present the discovery of A-910, a highly potent and selective dual MerTK/Axl inhibitor, achieved through a structure-based medicinal chemistry campaign. The lead compound exhibits favorable oral bioavailability, exceptional kinome selectivity, and significantly improved in vivo target engagement. These findings support the use of A-910 as an orally bioavailable in vivo tool compound for investigating the immunotherapy potential of dual MerTK/Axl inhibition.

Low level laser therapy alleviates mechanical allodynia in a postoperative and neuropathic pain model and alters the levels of inflammatory factors in rats.

Background: This study aimed to investigate the analgesic and preventive effect of low-level laser therapy (LLLT) on the incisional pain model and spinal nerve ligation (SNL) model in rats and identify the possible mechanisms of action. Methods: Male Sprague-Dawley rats were used, divided into different treatment groups. The single application group received LLLT before or after skin incision or SNL. The consecutive application group received LLLT for six consecutive days post-incision, three days pre-incision, or three consecutive days pre-SNL. The control group underwent skin incision or SNL without LLLT. The von Frey test was used to quantify the pain associated with mechanical allodynia. Pro-inflammatory cytokine level and alterations in nerve growth factor (NGF) expression were measured by using ELISA and immunohistochemistry, respectively in the skin, muscle of the paw, and spinal cord dorsal horn (SCDH). Results: In the incisional pain model, LLLT showed significant analgesic and preventive effect. LLLT ameliorated SNL-induced mechanical allodynia but LLLT had no preventive effect. LLLT decreased interleukin-1ß (IL-1ß) expression levels in the skin, muscle, and SCDH and reduced the optical density of skin and spinal cord NGF in the incisional pain model. Conclusions: LLLT alleviated incisional pain and neuropathic pain caused by SNL in rats, and reduced the levels of IL-1ß and NGF in the peripheral tissue and SCDH in the incisional pain model. LLLT might be effective in patients with post-operative pain and peripheral neuropathic pain.

Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices.

PURPOSE: Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive arterial blood pressure monitors. This study tested whether routine non-invasive monitors could also predict intraoperative hypotension using deep learning algorithms. METHODS: An open-source database of non-cardiac surgery patients ( https://vitadb.net/dataset ) was used to develop the deep learning algorithm. The algorithm was validated using external data obtained from a tertiary Korean hospital. Intraoperative hypotension was defined as a systolic blood pressure less than 90 mmHg. The input data included five monitors: non-invasive blood pressure, electrocardiography, photoplethysmography, capnography, and bispectral index. The primary outcome was the performance of the deep learning model as assessed by the area under the receiver operating characteristic curve (AUROC). RESULTS: Data from 4754 and 421 patients were used for algorithm development and external validation, respectively. The fully connected model of Multi-head Attention architecture and the Globally Attentive Locally Recurrent model with Focal Loss function were able to predict intraoperative hypotension 5 min before its occurrence. The AUROC of the algorithm was 0.917 (95% confidence interval [CI], 0.915-0.918) for the original data and 0.833 (95% CI, 0.830-0.836) for the external validation data. Attention map, which quantified the contributions of each monitor, showed that our algorithm utilized data from each monitor with weights ranging from 8 to 22% for determining hypotension. CONCLUSIONS: A deep learning model utilizing multi-channel non-invasive monitors could predict intraoperative hypotension with high accuracy. Future prospective studies are needed to determine whether this model can assist clinicians in preventing hypotension in patients undergoing surgery with non-invasive monitoring.

Prediction for Perioperative Stroke Using Intraoperative Parameters.

BACKGROUND: Perioperative stroke is a severe complication following surgery. To identify patients at risk for perioperative stroke, several prediction models based on the preoperative factors were suggested. Prediction models often focus on preoperative patient characteristics to assess stroke risk. However, most existing models primarily base their predictions on the patient's baseline characteristics before surgery. We aimed to develop a machine-learning model incorporating both pre- and intraoperative variables to predict perioperative stroke. METHODS AND RESULTS: This study included patients who underwent noncardiac surgery at 2 hospitals with the data of 15 752 patients from Seoul National University Hospital used for development and temporal internal validation, and the data of 449 patients from Boramae Medical Center used for external validation. Perioperative stroke was defined as a newly developed ischemic lesion on diffusion-weighted imaging within 30 days of surgery. We developed a prediction model composed of pre- and intraoperative factors (integrated model) and compared it with a model consisting of preoperative features alone (preoperative model). Perioperative stroke developed in 109 (0.69%) patients in the Seoul National University Hospital group and 11 patients (2.45%) in the Boramae Medical Center group. The integrated model demonstrated superior predictive performance with area under the curve values of 0.824 (95% CI, 0.762-0.880) versus 0.584 (95% CI, 0.499-0.667; P<0.001) in the internal validation; and 0.716 (95% CI, 0.560-0.859) versus 0.505 (95% CI, 0.343-0.654; P=0.018) in the external validation, compared to the preoperative model. CONCLUSIONS: We suggest that incorporating intraoperative factors into perioperative stroke prediction models can improve their accuracy.

The Necroptosis Pathway Is Upregulated in the Cornea in Mice With Ocular Graft-Versus-Host Disease.

Purpose: To identify molecular signatures specific for ocular graft-versus-host disease (GVHD) by proteomic analysis of corneas from mice with GVHD. Methods: We identified differentially expressed proteins (DEPs) in corneal samples from GVHD model mice and syngeneic control mice 4 weeks after bone marrow transplantation. Data-independent acquisition analysis was performed on individual samples, and the roles of DEPs in biological pathways related to GVHD were evaluated via bioinformatics and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Results: Three important signaling pathways were upregulated in the cornea in mice with GVHD: (1) the necroptosis pathway, (2) the mitogen-activated protein kinase (MAPK) pathway, and (3) as previously reported, the neutrophil extracellular trap (NET) pathway. In those signaling pathways, we identified new upregulated molecules, including (1) receptor-interacting protein kinase 1 (RIPK1), RIPK3, interferon regulatory factor 9, the interferon-induced double-stranded RNA-activated protein kinase lipoxygenase, and high mobility group box1 (HMGB1) which are damage-associated molecular patterns (DAMPs) in the necroptosis pathway; (2) the sequentially upregulated interleukin 1 (IL-1) receptor-associated kinase (IRAK), an evolutionarily conserved signaling intermediate in the Toll pathway (ECSIT), and p38, which is downstream of the IL-1 receptor and increased CDC42/Rac (Rac2), a Rho family GTPase in the MAPK pathway; and (3) the integrin components CR3 and macrophage-1 antigen (MAC-1), which are DAMPs, and the pyroptosis-related protein gasdermin D (GSDMD) in the NET pathway. Conclusions: These novel molecules may help researchers elucidate the pathogenesis of GVHD and identify new therapeutic targets for corneal changes in patients with ocular GVHD.

Impact of Fat Mass on Osteoporosis, Sarcopenia, and Osteosarcopenia in Peritoneal Dialysis Patients.

INTRODUCTION: The relationship between fat mass and osteoporosis, sarcopenia, and osteosarcopenia is complex. While higher fat mass generally has a negative impact on bone and muscle health in the general population, the impact in peritoneal dialysis (PD) patients is less well understood. METHODS: In this study of 359 PD patients, sarcopenia was identified using appendicular skeletal muscle per square meter (ASM/m2), with cut-off values of <7.0 kg/m2 for men and <5.5 kg/m2 for women. Fat tissue index (FTI) and lean tissue index (LTI) were determined using body composition monitoring, with the lowest tertile classified as low FTI and low LTI. Bone mineral density was measured, with a T-score below -2.5 indicating osteoporosis. RESULTS: The prevalence of osteoporosis, sarcopenia, and osteosarcopenia was 25%, 32%, and 15%, respectively. Notably, 60% of osteoporotic patients had sarcopenia, and about 45% of sarcopenic patients had osteoporosis. Patients with osteoporosis were older and had significantly lower LTI (15.3 vs. 12.7 kg/m2, p < 0.001) and ASM (7.3 vs. 5.8 kg/m2, p < 0.001). Osteoporotic patients also had lower FTI, but this was more pronounced in men than in women. Patients with both sarcopenia and osteoporosis had the lowest LTI and FTI compared to those with only one or neither condition. Low FTI was a significant determinant for osteoporosis (OR, 2.34; 95% CI, 1.43-3.85; p = 0.001), sarcopenia (OR, 2.91; 95% CI, 1.82-4.64; p < 0.001), and osteosarcopenia (OR, 2.34; 95% CI, 1.30-4.24; p = 0.005) in univariate analysis, and these associations remained significant after adjustment for age and body mass index. CONCLUSION: Osteoporosis and sarcopenia are common and interrelated in PD patients. Low fat mass, but not normal/high fat mass, was significantly associated with these conditions, suggesting the importance of maintaining adequate fat mass in PD patients.

Relationship between short-term ozone exposure, cause-specific mortality, and high-risk populations: A nationwide, time-stratified, case-crossover study.

BACKGROUND: Previous studies reported that short-term exposure to ground-level ozone is associated with mortality risk. However, due to the limited monitored areas, existing studies were limited in assessing the nationwide risk and suggesting specific vulnerable populations to the ozone-mortality risk. METHODS: We performed a nationwide time-stratified case-crossover study to evaluate the association between short-term ozone and cause-specific mortality in South Korea (2015-2019). A machine learning-ensemble prediction model (a test R2 > 0.96) was used to assess the short-term ozone exposure. Stratification analysis was conducted to examine the high-risk populations, and the excess mortality due to non-compliance with the WHO guideline was also assessed. RESULTS: For all-cause mortality (1,343,077 cases), the risk associated with ozone (lag0- 1) was weakly identified (odd ratio: 1.005 with 95% CI: 0.997-1.014), and the risk was prominent in mortality with circulatory system diseases. In addition, based on the point estimates, the ozone-mortality risk was higher in people aged less than 65y, and this pattern was also observed in circulatory system disease deaths and urban areas. CONCLUSIONS: This study provides national estimates of mortality risks associated with short-term ozone. Results showed that the benefits of stricter air quality standards could be greater in vulnerable populations.