With the rapid development of sequencing technologies, the detection of alternative polyadenylation (APA) in mammals has become more precise. APA precisely regulates gene expression by altering the length and position of the poly(A) tail, and is involved in various biological processes such as disease occurrence and embryonic development. The research on APA in mammals mainly focuses on the following aspects:(1) identifying APA based on transcriptome data and elucidating their characteristics; (2) investigating the relationship between APA and gene expression regulation to reveal its important role in life regulation;(3) exploring the intrinsic connections between APA and disease occurrence, embryonic development, differentiation, and other life processes to provide new perspectives and methods for disease diagnosis and treatment, as well as uncovering embryonic development regulatory mechanisms. In this review, the classification, mechanisms and functions of APA were elaborated in detail and the methods for APA identifying and APA data resources based on various transcriptome data were systematically summarized. Moreover, we epitomized and provided an outlook on research on APA, emphasizing the role of sequencing technologies in driving studies on APA in mammals. In the future, with the further development of sequencing technology, the regulatory mechanisms of APA in mammals will become clearer.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

N-acetyl-p-aminophenol （APAP） is an antipyretic analgesic commonly used in clinical practice， and APAP overdose can cause severe liver injury and even death. In recent years， the incidence rate of APAP-induced liver injury （AILI） tends to increase， and it has become the second most common cause of liver transplantation worldwide. Autophagy is a highly conserved catabolic process that removes unwanted cytosolic proteins and organelles through lysosomal degradation to achieve the metabolic needs of cells themselves and the renewal of organelles. A large number of studies have shown that autophagy plays a key role in the pathophysiology of AILI， involving the mechanisms such as APAP protein conjugates， oxidative stress， JNK activation， mitochondrial dysfunction， inflammatory response and apoptosis. This article elaborates on the biological mechanism of autophagy in AILI， in order to provide a theoretical basis for the treatment of AILI and the development of autophagy regulators.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.

Purpose: This study aimed to assess prognostic factors associated with combined hepatocellular-cholangiocarcinoma (cHCC-CCA) and to predict 5-year survival based on these factors. Materials and Methods: Patients who underwent definitive hepatectomy from 2006 to 2022 at a single institution was retrospectively analyzed. Inclusion criteria involved a pathologically confirmed diagnosis of cHCC-CCA. Results: A total of 80 patients with diagnosed cHCC-CCA were included in the analysis. The median progression-free survival was 15.6 months, while distant metastasis-free survival (DMFS), hepatic progression-free survival, and overall survival (OS) were 50.8, 21.5, and 85.1 months, respectively. In 52 cases of recurrence, intrahepatic recurrence was the most common initial recurrence (34/52), with distant metastasis in 17 cases. Factors associated with poor DMFS included tumor necrosis, lymphovascular invasion (LVI), perineural invasion, and histologic compact type. Postoperative carbohydrate antigen 19-9, tumor necrosis, LVI, and close/positive margin were associated with poor OS. LVI emerged as a key factor affecting both DMFS and OS, with a 5-year OS of 93.3% for patients without LVI compared to 35.8% with LVI. Based on these factors, a nomogram predicting 3-year and 5-year DMFS and OS was developed, demonstrating high concordance with actual survival in the cohort (Harrell C-index 0.809 for OS, 0.801 for DMFS, respectively). Conclusion The prognosis of cHCC-CCA is notably poor when combined with LVI. Given the significant impact of adverse features, accurate outcome prediction is crucial. Moreover, consideration of adjuvant therapy may be warranted for patients exhibiting poor survival and increased risk of local recurrence or distant metastasis.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.