Evaluating a Natural Language Processing-Driven, AI-Assisted International Classification of Diseases, 10th Revision, Clinical Modification, Coding System for Diagnosis Related Groups in a Real Hospital Environment: Algorithm Development and Validation Study.

BACKGROUND: International Classification of Diseases codes are widely used to describe diagnosis information, but manual coding relies heavily on human interpretation, which can be expensive, time consuming, and prone to errors. With the transition from the International Classification of Diseases, Ninth Revision, to the International Classification of Diseases, Tenth Revision (ICD-10), the coding process has become more complex, highlighting the need for automated approaches to enhance coding efficiency and accuracy. Inaccurate coding can result in substantial financial losses for hospitals, and a precise assessment of outcomes generated by a natural language processing (NLP)-driven autocoding system thus assumes a critical role in safeguarding the accuracy of the Taiwan diagnosis related groups (Tw-DRGs). OBJECTIVE: This study aims to evaluate the feasibility of applying an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), autocoding system that can automatically determine diagnoses and codes based on free-text discharge summaries to facilitate the assessment of Tw-DRGs, specifically principal diagnosis and major diagnostic categories (MDCs). METHODS: By using the patient discharge summaries from Kaohsiung Medical University Chung-Ho Memorial Hospital (KMUCHH) from April 2019 to December 2020 as a reference data set we developed artificial intelligence (AI)-assisted ICD-10-CM coding systems based on deep learning models. We constructed a web-based user interface for the AI-assisted coding system and deployed the system to the workflow of the certified coding specialists (CCSs) of KMUCHH. The data used for the assessment of Tw-DRGs were manually curated by a CCS with the principal diagnosis and MDC was determined from discharge summaries collected at KMUCHH from February 2023 to April 2023. RESULTS: Both the reference data set and real hospital data were used to assess performance in determining ICD-10-CM coding, principal diagnosis, and MDC for Tw-DRGs. Among all methods, the GPT-2 (OpenAI)-based model achieved the highest F1-score, 0.667 (F1-score 0.851 for the top 50 codes), on the KMUCHH test set and a slightly lower F1-score, 0.621, in real hospital data. Cohen κ evaluation for the agreement of MDC between the models and the CCS revealed that the overall average κ value for GPT-2 (κ=0.714) was approximately 12.2 percentage points higher than that of the hierarchy attention network (κ=0.592). GPT-2 demonstrated superior agreement with the CCS across 6 categories of MDC, with an average κ value of approximately 0.869 (SD 0.033), underscoring the effectiveness of the developed AI-assisted coding system in supporting the work of CCSs. CONCLUSIONS: An NLP-driven AI-assisted coding system can assist CCSs in ICD-10-CM coding by offering coding references via a user interface, demonstrating the potential to reduce the manual workload and expedite Tw-DRG assessment. Consistency in performance affirmed the effectiveness of the system in supporting CCSs in ICD-10-CM coding and the judgment of Tw-DRGs.

Exploring the role of spinal astrocytes in the onset of hyperalgesic priming signals in acid-induced chronic muscle pain.

Hyperalgesic priming, a form of pain plasticity initiated by initial injury, leads to heightened sensitivity to subsequent noxious stimuli, contributing to chronic pain development in animals. While astrocytes play active roles in modulating synaptic transmission in various pain models, their specific involvement in hyperalgesic priming remains elusive. Here, we show that spinal astrocytes are essential for hyperalgesic priming formation in a mouse model of acid-induced muscle pain. We observed spinal astrocyte activation 4 h after initial acid injection, and inhibition of this activation prevented chronic pain development upon subsequent acid injection. Chemogenetic activation of spinal astrocytes mimicked the first acid-induced hyperalgesic priming. We also demonstrated that spinal phosphorylated extracellular regulated kinase (pERK)-positive neurons were mainly vesicular glutamate transporter-2 positive (Vglut2+) neurons after the first acid injection, and inhibition of spinal pERK prevented astrocyte activation. Furthermore, pharmacological inhibition of astrocytic glutamate transporters glutamate transporter-1 and glutamate-aspartate transporter abolished the hyperalgesic priming. Collectively, our results suggest that pERK activation in Vglut2+ neurons activate astrocytes through astrocytic glutamate transporters. This process eventually establishes hyperalgesic priming through spinal D-serine. We conclude that spinal astrocytes play a crucial role in the transition from acute to chronic pain.

Comparative Efficacy of Fecal Microbiota Transplantation in Treating Refractory or Recurrent Clostridioides difficile Infection among Patients with and without Inflammatory Bowel Disease: A Retrospective Cohort Study.

Clostridioides difficile infection (CDI) worsens inflammatory bowel disease (IBD) prognosis. While fecal microbiota transplantation (FMT) is effective for refractory or recurrent CDI (rrCDI), comparative success rates between IBD and non-IBD patients are scarce. This study addresses this gap. A retrospective cohort study was conducted at Chang Gung Memorial Hospital from April 2019 to October 2023. Patients receiving FMT for rrCDI were categorized into IBD and non-IBD groups. Baseline characteristics and outcomes were compared at one month and one year, with successful FMT defined as the resolution of diarrhea without CDI recurrence. The study included 88 patients: 30 with IBD and 58 without IBD. The IBD group was younger, with fewer comorbidities. Success rates at one month were similar between groups (IBD: 80.0% vs. non-IBD: 78.9%, p = 0.908), as were negative toxin tests (IBD: 83.3% vs. non-IBD: 63.8%, p = 0.174). One-year success rates (IBD: 70.0% vs. non-IBD: 67.6%, p = 0.857) and eradication rates (IBD: 94.4% vs. non-IBD: 73.9%, p = 0.112) were also similar. Poor bowel preparation predicted FMT failure at one month (OR = 0.23, p = 0.019). No safety issues were reported. FMT is a safe, effective treatment for rrCDI, demonstrating similar success rates in patients with and without IBD.

Integrating predictive coding and a user-centric interface for enhanced auditing and quality in cancer registry data.

Data curation for a hospital-based cancer registry heavily relies on the labor-intensive manual abstraction process by cancer registrars to identify cancer-related information from free-text electronic health records. To streamline this process, a natural language processing system incorporating a hybrid of deep learning-based and rule-based approaches for identifying lung cancer registry-related concepts, along with a symbolic expert system that generates registry coding based on weighted rules, was developed. The system is integrated with the hospital information system at a medical center to provide cancer registrars with a patient journey visualization platform. The embedded system offers a comprehensive view of patient reports annotated with significant registry concepts to facilitate the manual coding process and elevate overall quality. Extensive evaluations, including comparisons with state-of-the-art methods, were conducted using a lung cancer dataset comprising 1428 patients from the medical center. The experimental results illustrate the effectiveness of the developed system, consistently achieving F1-scores of 0.85 and 1.00 across 30 coding items. Registrar feedback highlights the system's reliability as a tool for assisting and auditing the abstraction. By presenting key registry items along the timeline of a patient's reports with accurate code predictions, the system improves the quality of registrar outcomes and reduces the labor resources and time required for data abstraction. Our study highlights advancements in cancer registry coding practices, demonstrating that the proposed hybrid weighted neural-symbolic cancer registry system is reliable and efficient for assisting cancer registrars in the coding workflow and contributing to clinical outcomes.

The trends of pediatric duodenal ulcer and predictors of recurrence.

BACKGROUND: Duodenal ulcer (DU) causes various symptoms in children. The prevalence of Helicobacter pylori (Hp)-associated DU has been reducing in some regions, yet the updated trend in Taiwan is unknown. Risk factors of DU recurrence have not been comprehensively investigated in children. METHODS: This retrospective study included children diagnosed with DU to evaluate the demographics, symptoms, diagnostics, treatment, and outcomes. Specific populations (infant, surgery required) were sorted for subgroup analysis. Predictors of DU recurrence was analyzed in patients who received endoscopic follow-ups. RESULTS: A total of 488 children were included. Most patients were male (72.5%), school-aged (11.3 ± 4.8 years old), and with varied underlying diseases in one-fifth. The annual incidences were around 3-5%, with a declining trend of case numbers and the Hp-positive proportion. Hp infection, concurrent gastric ulcer, perforation, and mortality were noted in 32.7%, 16%, 1.6%, and 1% of patients. Patients with or without Hp infection showed different clinical features but similar outcomes. The characteristics of subpopulations were depicted respectively. Male sex, lower Hb level, and perforation were independent risk factors associated with recurrence. CONCLUSIONS: Hp-positive DU seems to wane. Patients with male sex, lower Hb level, or perforation at diagnosis carried a higher risk of recurrence, which may warrant active surveillance and endoscopic follow-up.

Twenty years' experience of midgut malrotation and volvulus in a tertiary center in northern Taiwan: A retrospective study.

BACKGROUND: Early diagnosis and surgical intervention for midgut malrotation with bowel obstruction are crucial. We aimed to identify risk factors for adverse outcomes in infants with midgut malrotation and to develop a prediction model. METHODS: We reviewed the operation records of infants surgically diagnosed with midgut malrotation at Chang Gung Children's Medical Center between January 2000 and December 2020. Patients were classified into the poor-outcome group (PO) if they underwent bowel resection or experienced mortality; all others were categorized as the favorable-outcome group (FO). Data on demographics, initial presentations, laboratory results, radiographic or sonographic findings, maternal conditions, and outcomes were collected and analyzed. Fisher's exact test, the independent sample t-test, and the Mann-Whitney test were utilized for comparative analysis when suitable. RESULTS: The study included 103 infants. Eleven were in the PO group, and 92 were in the FO group. Initial presentations such as respiratory distress, poor activity, and shock status were notably more prevalent in the PO group. The INR, hemoglobin, HCO3, base excess, and aspartate transaminase values showed significant variation between the two groups. Multivariate analysis identified that lower hemoglobin (OR 0.677, p = 0.043) and higher AST (OR 1.036, p = 0.044) were independent predictors of adverse outcomes. An AST/Hb ratio of <3.78 demonstrated a high negative predictive value (98.6%) for an adverse outcome in midgut malrotation. CONCLUSIONS: Prompt diagnosis and surgical treatment of midgut malrotation are vital to prevent bowel resection or mortality. The independent predicting factors for poor outcomes include low hemoglobin and elevated AST levels.

Clinical significance of incidental common bile duct dilatation in children: A 10-year single medical center experience.

BACKGROUND: With the widespread use of abdominal ultrasonography (US), incidental detection of common bile duct (CBD) dilatation is common in pediatric populations. This study investigated the causes and clinical significance of CBD dilatation in children without biliary symptoms, jaundice, or causative lesions in US. METHODS: We retrospectively reviewed pediatric patients with CBD dilatation from July 2013 to June 2023. All cases were detected via abdominal US. We analyzed the patients' clinical manifestations, laboratory data, diagnosis, underlying diseases, and clinical course. RESULTS: In a total of 687 patients enrolled, 338 met inclusion criteria (90 in hepatobiliary, 248 in CBD dilatation group). Of 128 patients with incidental CBD dilatation who underwent regular US examinations, 91 (71.1%) experienced resolution during follow-up. The proportion of patients with intrahepatic duct dilatation was significantly higher in the non-resolution group (p = 0.038). General health examination group had significant smaller CBD diameter compared to the gastrointestinal and infection groups. Correlation analysis found starting point of resolution decline at 3.24 mm (all-inclusive) and 2.51 mm (infant group) CBD diameter. CONCLUSIONS: Most children with incidental CBD dilatation did not have abnormal hepatobiliary function or other sonographic abnormalities. They usually remained asymptomatic and experienced uneventful clinical courses.

A dynamic approach to support outbreak management using reinforcement learning and semi-connected SEIQR models.

BACKGROUND: Containment measures slowed the spread of COVID-19 but led to a global economic crisis. We establish a reinforcement learning (RL) algorithm that balances disease control and economic activities. METHODS: To train the RL agent, we design an RL environment with 4 semi-connected regions to represent the COVID-19 epidemic in Tokyo, Osaka, Okinawa, and Hokkaido, Japan. Every region is governed by a Susceptible-Exposed-Infected-Quarantined-Removed (SEIQR) model and has a transport hub to connect with other regions. The allocation of the synthetic population and inter-regional traveling is determined by population-weighted density. The agent learns the best policy from interacting with the RL environment, which involves obtaining daily observations, performing actions on individual movement and screening, and receiving feedback from the reward function. After training, we implement the agent into RL environments describing the actual epidemic waves of the four regions to observe the agent's performance. RESULTS: For all epidemic waves covered by our study, the trained agent reduces the peak number of infectious cases and shortens the epidemics (from 165 to 35 cases and 148 to 131 days for the 5th wave). The agent is generally strict on screening but easy on movement, except for Okinawa, where the agent is easy on both actions. Action timing analyses indicate that restriction on movement is elevated when the number of exposed or infectious cases remains high or infectious cases increase rapidly, and stringency on screening is eased when the number of exposed or infectious cases drops quickly or to a regional low. For Okinawa, action on screening is tightened when the number of exposed or infectious cases increases rapidly. CONCLUSIONS: Our experiments exhibit the potential of the RL in assisting policy-making and how the semi-connected SEIQR models establish an interactive environment for imitating cross-regional human flows.

Cytomegalovirus Diseases of the Gastrointestinal Tract in Immunocompetent Patients: A Narrative Review.

Cytomegalovirus (CMV) is a potential pathogen that causes gastrointestinal (GI) tract diseases regardless of host immunity. In contrast to immunocompromised individuals, immunocompetent patients lack a comprehensive overview of the gastrointestinal manifestations. This study aims to provide a comprehensive summary of the current evidence regarding presentations, diagnostics, management, risk assessment, and outcomes in immunocompetent patients with CMV GI disease. A thorough literature search of English publications up to April 2022 was conducted across electronic databases to identify relevant articles, with eligible case series selected for detailed analysis. The majority of immunocompetent patients affected by CMV GI disease are typically elderly, critically ill, or burdened with comorbidities that compromise immunity. Clinical presentations range from subtle symptoms to severe surgical conditions, including instances of mortality. Specific clinical presentations, blood test results, or endoscopic features are lacking, necessitating reliance on histopathological tests such as immunohistochemistry staining for diagnosis. While antiviral therapy may offer benefits in improving outcomes, careful individual assessment is warranted due to diverse comorbidities and potential side effects. Mortality rates vary considerably based on underlying medical conditions and therapeutic approaches. It is imperative for clinicians to maintain vigilance for CMV GI disease among high-risk groups, despite their baseline immunocompetence, in order to enhance clinical outcomes.

Comparative Analysis of Cytomegalovirus Gastrointestinal Disease in Immunocompetent and Immunocompromised Patients.

BACKGROUND: Cytomegalovirus (CMV) gastrointestinal (GI) diseases impact both immunocompromised and immunocompetent individuals, yet comprehensive studies highlighting the differences between these groups are lacking. METHODS: In this retrospective study (January 2000 to July 2022) of 401 patients with confirmed CMV GI diseases, we categorized them based on immunological status and compared manifestations, treatments, outcomes, and prognostic factors. RESULTS: The immunocompromised patients (n = 193) showed older age, severe illnesses, and higher comorbidity rates. GI bleeding, the predominant manifestation, occurred more in the immunocompetent group (92.6% vs. 63.6%, p = 0.009). Despite longer antiviral therapy, the immunocompromised patients had higher in-hospital (32.2% vs. 18.9%, p = 0.034) and overall mortality rates (91.1% vs. 43.4%, p < 0.001). The independent factors influencing in-hospital mortality in the immunocompromised patients included GI bleeding (OR 5.782, 95% CI 1.257-26.599, p = 0.024) and antiviral therapy ≥ 14 days (OR 0.232, 95% CI 0.059-0.911, p = 0.036). In the immunocompetent patients, age (OR 1.08, 95% CI 1.006-1.159, p = 0.032), GI bleeding (OR 10.036, 95% CI 1.183-85.133, p = 0.035), and time to diagnosis (OR 1.029, 95% CI 1.004-1.055, p = 0.021) were significant prognostic factors, with the age and diagnosis time cut-offs for survival being 70 years and 31.5 days, respectively. CONCLUSIONS: GI bleeding is the most common manifestation and prognostic factor in both groups. Early diagnosis and effective antiviral therapy can significantly reduce in-hospital mortality.

Cav3.1 T-type calcium channel blocker NNC 55-0396 reduces atherosclerosis by increasing cholesterol efflux.

Calcium channel blockers (CCBs) are commonly used as antihypertensive agents. While certain L-type CCBs exhibit antiatherogenic effects, the impact of Cav3.1 T-type CCBs on antiatherogenesis and lipid metabolism remains unexplored. NNC 55-0396 (NNC) is a highly selective blocker of T-type calcium channels (Cav3.1 channels). We investigated the effects of NNC on relevant molecules and molecular mechanisms in human THP-1 macrophages. Cholesterol efflux, an indicator of reverse cholesterol transport (RCT) efficiency, was assessed using [3H]-labeled cholesterol. In vivo, high cholesterol diet (HCD)-fed LDL receptor knockout (Ldlr-/-) mice, an atherosclerosis-prone model, underwent histochemical staining to analyze plaque burden. Treatment of THP-1 macrophages with NNC facilitated cholesterol efflux and reduced intracellular cholesterol accumulation. Pharmacological and genetic interventions demonstrated that NNC treatment or Cav3.1 knockdown significantly enhanced the protein expression of scavenger receptor B1 (SR-B1), ATP-binding cassette transporter A1 (ABCA1), ATP-binding cassette transporter G1 (ABCG1), and liver X receptor alpha (LXRα) transcription factor. Mechanistic analysis revealed that NNC activates p38 and c-Jun N-terminal kinase (JNK) phosphorylation, leading to increased expression of ABCA1, ABCG1, and LXRα-without involving the microRNA pathway. LXRα isrequired for NNC-induced ABCA1 and ABCG1 expression. Administering NNC diminished atherosclerotic lesion area and lipid deposition in HCD-fed Ldlr-/- mice. NNC's anti-atherosclerotic effects, achieved through enhanced cholesterol efflux and inhibition of lipid accumulation, suggest a promising therapeutic approach for hypertensive patients with atherosclerosis. This research highlights the potential of Cav3.1 T-type CCBs in addressing cardiovascular complications associated with hypertension.

Aspirin-exacerbated respiratory disease is associated with variants in filaggrin, epithelial integrity, and cellular interactions.

Background: Previous studies have determined that up to 6% of patients with aspirin-exacerbated respiratory disease (AERD) have family history of AERD, indicating a possible link with genetic polymorphisms. However, whole exome sequencing (WES) studies of such associations are currently lacking. Objectives: We sought to examine whether WES can identify pathogenic variants associated with AERD. Methods: Diagnoses of AERD were confirmed in patients with nasal polyps and asthma. WES was performed using an Illumina sequencing platform. Human Phenotype Ontology terms were used to define the patients' phenotypes. Exomiser was used to annotate, filter, and prioritize possible disease-causing genetic variants. Results: Of 39 patients with AERD, 41% reported a family history of asthma and 5% reported a family history of AERD. Pathogenic exome variants in the filaggrin gene (FLG) were found in 2 patients (5%). Other variants not known to be pathogenic were detected in an additional 16 patients (41%) in genes related to epithelial integrity and cellular interactions, including genes encoding desmoglein 3 (DSG3), dynein axonemal heavy chain 9 (DNAH9), collagen type VII alpha 1 chain (COL7A1), collagen type XVII alpha 1 chain (COL17A1), chromodomain helicase DNA binding protein-7 (CHD7), TSC complex subunit 2/tuberous sclerosis-2 protein (TSC2), P-selectin (SELP), and platelet-derived growth factor receptor-alpha (PDGFRA). Conclusion: WES identified a monogenic susceptibility to AERD in 5% of patients with FLG pathogenic variants. Other variants not previously identified as pathogenic were found in genes relevant to epithelial integrity and cellular interactions and may further reveal genetic factors that contribute to this condition.

Unlocking the Secrets Behind Advanced Artificial Intelligence Language Models in Deidentifying Chinese-English Mixed Clinical Text: Development and Validation Study.

BACKGROUND: The widespread use of electronic health records in the clinical and biomedical fields makes the removal of protected health information (PHI) essential to maintain privacy. However, a significant portion of information is recorded in unstructured textual forms, posing a challenge for deidentification. In multilingual countries, medical records could be written in a mixture of more than one language, referred to as code mixing. Most current clinical natural language processing techniques are designed for monolingual text, and there is a need to address the deidentification of code-mixed text. OBJECTIVE: The aim of this study was to investigate the effectiveness and underlying mechanism of fine-tuned pretrained language models (PLMs) in identifying PHI in the code-mixed context. Additionally, we aimed to evaluate the potential of prompting large language models (LLMs) for recognizing PHI in a zero-shot manner. METHODS: We compiled the first clinical code-mixed deidentification data set consisting of text written in Chinese and English. We explored the effectiveness of fine-tuned PLMs for recognizing PHI in code-mixed content, with a focus on whether PLMs exploit naming regularity and mention coverage to achieve superior performance, by probing the developed models' outputs to examine their decision-making process. Furthermore, we investigated the potential of prompt-based in-context learning of LLMs for recognizing PHI in code-mixed text. RESULTS: The developed methods were evaluated on a code-mixed deidentification corpus of 1700 discharge summaries. We observed that different PHI types had preferences in their occurrences within the different types of language-mixed sentences, and PLMs could effectively recognize PHI by exploiting the learned name regularity. However, the models may exhibit suboptimal results when regularity is weak or mentions contain unknown words that the representations cannot generate well. We also found that the availability of code-mixed training instances is essential for the model's performance. Furthermore, the LLM-based deidentification method was a feasible and appealing approach that can be controlled and enhanced through natural language prompts. CONCLUSIONS: The study contributes to understanding the underlying mechanism of PLMs in addressing the deidentification process in the code-mixed context and highlights the significance of incorporating code-mixed training instances into the model training phase. To support the advancement of research, we created a manipulated subset of the resynthesized data set available for research purposes. Based on the compiled data set, we found that the LLM-based deidentification method is a feasible approach, but carefully crafted prompts are essential to avoid unwanted output. However, the use of such methods in the hospital setting requires careful consideration of data security and privacy concerns. Further research could explore the augmentation of PLMs and LLMs with external knowledge to improve their strength in recognizing rare PHI.

Comparison of 16S rRNA gene sequencing microbiota among children with serological IgE-mediated food hypersensitivity.

BACKGROUND: We hypothesized that specific food hypersensitivity (FH) in children is linked to specific gut microbiota. The aim of our study was to quantify and evaluate differences in gut microbial composition among children with different IgE-mediated FH. METHODS: Children (n = 81) aged 18 to 36 months were enrolled, fecal samples of 57 children with FH and 24 healthy children were evaluated using next-generation sequencing. Individual microbial diversity and composition were analyzed via targeting the 16 S rRNA gene hypervariable V3-V5 regions. RESULTS: Children with IgE-mediated FH (in milk, egg white, soy) had significantly lower gut microbiota diversity and richness than healthy children. Children with IgE-mediated FH exhibited relatively high abundances of Firmicutes and relative underrepresentation of the phylum Bacteroidetes. We observed significant increases in relative abundances of Ruminococcaceae, Clostridiaceae, and Erysipelotrichaceae (p < 0.01, compared to control) in children with milk hypersensitivity and of Clostridiaceae and Erysipelotrichaceae (p < 0.01) in children with peanut hypersensitivity. We also found significant increases in the numbers of Clostridiaceae, Lachnospiraceae and Pasteurellaceae (p < 0.01) in children with egg white hypersensitivity. CONCLUSIONS: These findings identify early evidence of different gut microbiota development/ differentiation in children with food hypersensitivity. Specific food hypersensitivities may be associated with compositional changes in intestinal microbiota. IMPACT: These findings identify early evidence of different gut microbiota development/differentiation in children with food hypersensitivity. We built a gut microbial profile that could identify toddlers at risk for food hypersensitivity. Children with enriched Firmicutes (phylum) with partial different families may be associated with food hypersensitivity. Enriched family Clostridiaceae, Ruminococcaceae, Lachnospiraceae, or Erysipelotrichaceae in gut microbiota may be associated with specific food hypersensitivities (such as milk, egg white, peanut) in children.

Epigenetic regulator RNF20 underlies temporal hierarchy of gene expression to regulate postnatal cardiomyocyte polarization.

Differentiated cardiomyocytes (CMs) must undergo diverse morphological and functional changes during postnatal development. However, the mechanisms underlying initiation and coordination of these changes remain unclear. Here, we delineate an integrated, time-ordered transcriptional network that begins with expression of genes for cell-cell connections and leads to a sequence of structural, cell-cycle, functional, and metabolic transitions in mouse postnatal hearts. Depletion of histone H2B ubiquitin ligase RNF20 disrupts this gene network and impairs CM polarization. Subsequently, assay for transposase-accessible chromatin using sequencing (ATAC-seq) analysis confirmed that RNF20 contributes to chromatin accessibility in this context. As such, RNF20 is likely to facilitate binding of transcription factors at the promoters of genes involved in cell-cell connections and actin organization, which are crucial for CM polarization and functional integration. These results suggest that CM polarization is one of the earliest events during postnatal heart development and provide insights into how RNF20 regulates CM polarity and the postnatal gene program.

Identification of Novel Targeting Sites of Calcineurin and CaMKII in Human CaV3.2 T-Type Calcium Channel.

The Cav3.2 T-type calcium channel is implicated in various pathological conditions, including cardiac hypertrophy, epilepsy, autism, and chronic pain. Phosphorylation of Cav3.2 by multiple kinases plays a pivotal role in regulating its calcium channel function. The calcium/calmodulin-dependent serine/threonine phosphatase, calcineurin, interacts physically with Cav3.2 and modulates its activity. However, it remains unclear whether calcineurin dephosphorylates Cav3.2, the specific spatial regions on Cav3.2 involved, and the extent of the quantitative impact. In this study, we elucidated the serine/threonine residues on Cav3.2 targeted by calcineurin using quantitative mass spectrometry. We identified six serine residues in the N-terminus, II-III loop, and C-terminus of Cav3.2 that were dephosphorylated by calcineurin. Notably, a higher level of dephosphorylation was observed in the Cav3.2 C-terminus, where calcineurin binds to this channel. Additionally, a previously known CaMKII-phosphorylated site, S1198, was found to be dephosphorylated by calcineurin. Furthermore, we also discovered that a novel CaMKII-phosphorylated site, S2137, underwent dephosphorylation by calcineurin. In CAD cells, a mouse central nervous system cell line, membrane depolarization led to an increase in the phosphorylation of endogenous Cav3.2 at S2137. Mutation of S2137 affected the calcium channel function of Cav3.2. Our findings advance the understanding of Cav3.2 regulation not only through kinase phosphorylation but also via calcineurin phosphatase dephosphorylation.

Fecal microbiota transplantation for treatment of refractory or recurrent Clostridioides difficile infection in Taiwan: a cost-effectiveness analysis.

Background: Compared to antibiotic treatment, fecal microbiota transplantation (FMT) is a more effective treatment for refractory or recurrent CDI (rCDI). Patients with inflammatory bowel disease (IBD) have a higher incidence of CDI and worse outcomes. There has been no study from Asia to evaluate the cost-effectiveness of FMT for overall rCDI patients and rCDI patients with IBD. Methods: We applied a Markov model with deterministic and probabilistic sensitivity analyses to evaluate the cost and effectiveness of different treatments for rCDI patients with a time horizon of 1 year from the payer's perspective. We compared the cost and clinical outcomes of FMT through colonoscopy to two antibiotics (vancomycin and fidaxomicin) using data from Chang Gung Memorial Hospital, Taoyuan, Taiwan. Results: Compared to vancomycin, FMT was cost-effective in overall rCDI patients as well as IBD patients with rCDI [USD 39356 (NT$1,101,971.98)/quality-adjusted life year (QALY) gained in overall patients; USD65490 (NT$1,833,719.14)/QALY gained in IBD patients]. Compared to fidaxomicin, FMT was only cost-effective in overall rCDI patients [USD20255 (NT$567,133.45)/QALY gained] but slightly increased QALY (0.0018 QALY gained) in IBD patients with rCDI. Conclusion: FMT is cost-effective, compared to vancomycin or fidaxomicin, for the treatment of rCDI in most scenarios from the payers' perspective in Taiwan.

Intelligent Performance Evaluation in Rowing Sport Using a Graph-Matching Network.

Rowing competitions require consistent rowing strokes among crew members to achieve optimal performance. However, existing motion analysis techniques often rely on wearable sensors, leading to challenges in sporter inconvenience. The aim of our work is to use a graph-matching network to analyze the similarity in rowers' rowing posture and further pair rowers to improve the performance of their rowing team. This study proposed a novel video-based performance analysis system to analyze paired rowers using a graph-matching network. The proposed system first detected human joint points, as acquired from the OpenPose system, and then the graph embedding model and graph-matching network model were applied to analyze similarities in rowing postures between paired rowers. When analyzing the postures of the paired rowers, the proposed system detected the same starting point of their rowing postures to achieve more accurate pairing results. Finally, variations in the similarities were displayed using the proposed time-period similarity processing. The experimental results show that the proposed time-period similarity processing of the 2D graph-embedding model (GEM) had the best pairing results.

Feature-aware unsupervised lesion segmentation for brain tumor images using fast data density functional transform.

We demonstrate that isomorphically mapping gray-level medical image matrices onto energy spaces underlying the framework of fast data density functional transform (fDDFT) can achieve the unsupervised recognition of lesion morphology. By introducing the architecture of geometric deep learning and metrics of graph neural networks, gridized density functionals of the fDDFT establish an unsupervised feature-aware mechanism with global convolutional kernels to extract the most likely lesion boundaries and produce lesion segmentation. An AutoEncoder-assisted module reduces the computational complexity from [Formula: see text] to [Formula: see text], thus efficiently speeding up global convolutional operations. We validate their performance utilizing various open-access datasets and discuss limitations. The inference time of each object in large three-dimensional datasets is 1.76 s on average. The proposed gridized density functionals have activation capability synergized with gradient ascent operations, hence can be modularized and embedded in pipelines of modern deep neural networks. Algorithms of geometric stability and similarity convergence also raise the accuracy of unsupervised recognition and segmentation of lesion images. Their performance achieves the standard requirement for conventional deep neural networks; the median dice score is higher than 0.75. The experiment shows that the synergy of fDDFT and a naïve neural network improves the training and inference time by 58% and 51%, respectively, and the dice score raises to 0.9415. This advantage facilitates fast computational modeling in interdisciplinary applications and clinical investigation.