Search

Abstract Purpose Sleep disorders are becoming more prevalent in hospitalized patients with acute myocardial infarction (AMI). We aimed to investigate the risk factors for sleep disorders in hospitalized patients with AMI, then develop and validate a prediction nomogram for the risk of sleep disorders. Methods Clinical data were collected from patients with AMI hospitalized in our hospital from January 2020 to June 2023. All patients were divided into the training group and the validation group with a ratio of 7:3 in sequential order. The LASSO regression analysis and multivariate logistic regression analysis were used to screen potential risk factors for sleep disorders. The concordance index (C-index), calibration curves, and decision curve analysis (DCA) were plotted. Results A total of 256 hospitalized patients with AMI were enrolled. Patients were divided into the training group (180) and the validation group (76) according to a scale of 7:3. Of the 256 patients, 90 patients (35.16%) suffered from sleep disorders, and 33 patients (12.89%) needed hypnotics. The variables screened by LASSO regression included age, smoking, NYHA class, anxiety status at admission, depression status at admission, and strangeness of environment. A nomogram model was established by incorporating the risk factors selected. The C-index, calibration curve, and DCA showed good predictive performance. Conclusions We identified six clinical characteristics as predictors of sleep disorders in hospitalized patients with AMI. It helps nurses make appropriate decisions in clinical practice.

Abstract Background Climate change is expected to alter the factors that drive changes in adaptive variation. This is especially true for species with long life spans and limited dispersal capabilities. Rapid climate changes may disrupt the migration of beneficial genetic variations, making it challenging for them to keep up with changing environments. Understanding adaptive genetic variations in tree species is crucial for conservation and effective forest management. Our study used landscape genomic analyses and phenotypic traits from a thorough sampling across the entire range of Quercus longinux, an oak species native to Taiwan, to investigate the signals of adaptation within this species. Results Using ecological data, phenotypic traits, and 1,933 single-nucleotide polymorphisms (SNPs) from 205 individuals, we classified three genetic groups, which were also phenotypically and ecologically divergent. Thirty-five genes related to drought and freeze resistance displayed signatures of natural selection. The adaptive variation was driven by diverse environmental pressures such as low spring precipitation, low annual temperature, and soil grid sizes. Using linear-regression-based methods, we identified isolation by environment (IBE) as the optimal model for adaptive SNPs. Redundancy analysis (RDA) further revealed a substantial joint influence of demography, geology, and environments, suggesting a covariation between environmental gradients and colonization history. Lastly, we utilized adaptive signals to estimate the genetic offset for each individual under diverse climate change scenarios. The required genetic changes and migration distance are larger in severe climates. Our prediction also reveals potential threats to edge populations in northern and southeastern Taiwan due to escalating temperatures and precipitation reallocation. Conclusions We demonstrate the intricate influence of ecological heterogeneity on genetic and phenotypic adaptation of an oak species. The adaptation is also driven by some rarely studied environmental factors, including wind speed and soil features. Furthermore, the genetic offset analysis predicted that the edge populations of Q. longinux in lower elevations might face higher risks of local extinctions under climate change.

Abstract We study the unflavored Schur indices in the N $$ \mathcal{N} $$ = 4 super-Yang-Mills theory for the B n , C n , D n , G 2 gauge groups. We explore two methods, namely the character expansion method and the Fermi gas method, to efficiently compute the q-series expansion of the Schur indices to some high orders. Using the available data and the modular properties, we are able to fix the exact formulas for the general gauge groups up to some high ranks and discover some interesting new features. We also identify some empirical modular anomaly equations, but unlike the case of A n groups, they are quite complicated and not sufficiently useful to fix exact formulas for gauge groups of arbitrary rank.

Impaired differentiation of megakaryocytes constitutes the principal etiology of thrombocytopenia. The signal transducer and activator of transcription 3 (STAT3) is a crucial transcription factor in regulating megakaryocyte differentiation, yet the precise mechanism of its activation remains unclear. PALLD, an actin-associated protein, has been increasingly recognized for its essential functions in multiple biological processes. This study revealed that megakaryocyte/plateletspecific knockout of PALLD in mice exhibited thrombocytopenia due to diminished platelet biogenesis. In megakaryocytes, PALLD deficiency led to impaired proplatelet formation and polyploidization, ultimately weakening their differentiation for platelet production. Mechanistic studies demonstrated that PALLD bound to STAT3 and interacted with its DNA-binding domain (DBD) and Src homology 2 (SH2) domain via Immunoglobulin domain 3 (Ig3). Moreover, the absence of PALLD attenuated STAT3 Y705 phosphorylation and impeded STAT3 nuclear translocation. Based on the PALLD-STAT3 binding sequence, we designed a peptide C-P3, which can facilitate megakaryocyte differentiation and accelerate platelet production in vivo. In conclusion, this study highlights the pivotal role of PALLD in megakaryocyte differentiation and proposes a novel approach for treating thrombocytopenia by targeting the PALLD-STAT3 interaction.

Cholecystokinin (CCK) is an essential modulator for neuroplasticity in sensory and emotional domains. Here, we investigated the role of CCK in motor learning using a single pellet reaching task in mice. Mice with a knockout of Cck gene (Cck−/−) or blockade of CCK-B receptor (CCKBR) showed defective motor learning ability; the success rate of retrieving reward remained at the baseline level compared to the wildtype mice with significantly increased success rate. We observed no long-term potentiation upon high-frequency stimulation in the motor cortex of Cck−/− mice, indicating a possible association between motor learning deficiency and neuroplasticity in the motor cortex. In vivo calcium imaging demonstrated that the deficiency of CCK signaling disrupted the refinement of population neuronal activity in the motor cortex during motor skill training. Anatomical tracing revealed direct projections from CCK-expressing neurons in the rhinal cortex to the motor cortex. Inactivation of the CCK neurons in the rhinal cortex that project to the motor cortex bilaterally using chemogenetic methods significantly suppressed motor learning, and intraperitoneal application of CCK4, a tetrapeptide CCK agonist, rescued the motor learning deficits of Cck−/− mice. In summary, our results suggest that CCK, which could be provided from the rhinal cortex, may surpport motor skill learning by modulating neuroplasticity in the motor cortex.

Abstract Prostate cancer (PCa) patients with lymph node involvement (LNI) constitute a single-risk group with varied prognoses. Existing studies on this group have focused solely on those who underwent prostatectomy (RP), using statistical models to predict prognosis. This study aimed to develop an easily accessible individual survival prediction tool based on multiple machine learning (ML) algorithms to predict survival probability for PCa patients with LNI. A total of 3280 PCa patients with LNI were identified from the Surveillance, Epidemiology, and End Results (SEER) database, covering the years 2000–2019. The primary endpoint was overall survival (OS). Gradient Boosting Survival Analysis (GBSA), Random Survival Forest (RSF), and Extra Survival Trees (EST) were used to develop prognosis models, which were compared to Cox regression. Discrimination was evaluated using the time-dependent areas under the receiver operating characteristic curve (time-dependent AUC) and the concordance index (c-index). Calibration was assessed using the time-dependent Brier score (time-dependent BS) and the integrated Brier score (IBS). Moreover, the beeswarm summary plot in SHAP (SHapley Additive exPlanations) was used to display the contribution of variables to the results. The 3280 patients were randomly split into a training cohort (n = 2624) and a validation cohort (n = 656). Nine variables including age at diagnosis, race, marital status, clinical T stage, prostate-specific antigen (PSA) level at diagnosis, Gleason Score (GS), number of positive lymph nodes, radical prostatectomy (RP), and radiotherapy (RT) were used to develop models. The mean time-dependent AUC for GBSA, RSF, and EST was 0.782 (95% confidence interval [CI] 0.779–0.783), 0.779 (95% CI 0.776–0.780), and 0.781 (95% CI 0.778–0.782), respectively, which were higher than the Cox regression model of 0.770 (95% CI 0.769–0.773). Additionally, all models demonstrated almost similar calibration, with low IBS. A web-based prediction tool was developed using the best-performing GBSA, which is accessible at https://pengzihexjtu-pca-n1.streamlit.app/ . ML algorithms showed better performance compared with Cox regression and we developed a web-based tool, which may help to guide patient treatment and follow-up.

Abstract Mitochondria are essential organelles for cellular metabolism and physiology in eukaryotic cells. Human mitochondria have their own genome (mtDNA), which is maternally inherited with 37 genes, encoding 13 polypeptides for oxidative phosphorylation, and 22 tRNAs and 2 rRNAs for translation. mtDNA mutations are associated with a wide spectrum of degenerative and neuromuscular diseases. However, the pathophysiology of mitochondrial diseases, especially for threshold effect and tissue specificity, is not well understood and there is no effective treatment for these disorders. Especially, the lack of appropriate cell and animal disease models has been significant obstacles for deep elucidating the pathophysiology of maternally transmitted diseases and developing the effective therapy approach. The use of human induced pluripotent stem cells (iPSCs) derived from patients to obtain terminally differentiated specific lineages such as inner ear hair cells is a revolutionary approach to deeply understand pathogenic mechanisms and develop the therapeutic interventions of mitochondrial disorders. Here, we review the recent advances in patients-derived iPSCs as ex vivo models for mitochondrial diseases. Those patients-derived iPSCs have been differentiated into specific targeting cells such as retinal ganglion cells and eventually organoid for the disease modeling. These disease models have advanced our understanding of the pathophysiology of maternally inherited diseases and stepped toward therapeutic interventions for these diseases.

Summary: Mitochondria are dynamic organelles in cellular metabolism and physiology. Mitochondrial DNA (mtDNA) mutations are associated with a broad spectrum of clinical abnormalities. However, mechanisms underlying mtDNA mutations regulate intracellular signaling related to the mitochondrial and cellular integrity are less explored. Here, we demonstrated that mt-tRNAMet 4435A>G mutation-induced nucleotide modification deficiency dysregulated the expression of nuclear genes involved in cytosolic proteins involved in oxidative phosphorylation system (OXPHOS) and impaired the assemble and integrity of OXPHOS complexes. These dysfunctions caused mitochondrial dynamic imbalance, thereby increasing fission and decreasing fusion. Excessive fission impaired the process of autophagy including initiation phase, formation, and maturation of autophagosome. Strikingly, the m.4435A>G mutation upregulated the PARKIN dependent mitophagy pathways but downregulated the ubiquitination-independent mitophagy. These alterations promoted intrinsic apoptotic process for the removal of damaged cells. Our findings provide new insights into mechanism underlying deficient tRNA posttranscription modification regulated intracellular signaling related to the mitochondrial and cellular integrity.

Abstract Background Leber’s hereditary optic neuropathy (LHON) is a maternally inherited eye disease due to mutations in mitochondrial DNA. However, there is no effective treatment for this disease. LHON-linked ND6 14484T > C (p.M64V) mutation caused complex I deficiency, diminished ATP production, increased production of reactive oxygen species (ROS), elevated apoptosis, and impaired mitophagy. Here, we investigated if the allotopic expression of human mitochondrial ND6 transgene corrected the mitochondrial dysfunctions due to LHON-associated m.14484T > C mutation. Methods Nucleus-versions of ND6 was generated by changing 6 non-universal codons with universal codons and added to mitochondrial targeting sequence of COX8. Stable transfectants were generated by transferring human ND6 cDNA expressed in a pCDH-puro vector into mutant cybrids carrying the m.14484T > C mutation and control cybrids. The effect of allotopic expression of ND6 on oxidative phosphorylation (OXPHOS) was evaluated using Blue Native gel electrophoresis and extracellular flux analyzer. Assessment of ROS production in cell lines was performed by flow cytometry with MitoSOX Red reagent. Analyses for apoptosis and mitophagy were undertaken via flow cytometry, TUNEL and immunofluorescence assays. Results The transfer of human ND6 into the cybrids carrying the m.14484T > C mutation raised the levels of ND6, ND1 and ND4L but did not change the levels of other mitochondrial proteins. The overexpression of ND6 led to 20~23% increases in the assembly and activity of complex I, and ~ 53% and ~ 33% increases in the levels of mitochondrial ATP and ΔΨm in the mutant cybrids bearing m.14484T > C mutation. Furthermore, mutant cybrids with overexpression of ND6 exhibited marked reductions in the levels of mitochondrial ROS. Strikingly, ND6 overexpression markedly inhibited the apoptosis process and restored impaired mitophagy in the cells carrying m.14484T > C mutation. However, overexpression of ND6 did not affect the ND6 level and mitochondrial functions in the wild-type cybrids, indicating that this ND6 level appeared to be the maximum threshold level to maintain the normal cell function. Conclusion We demonstrated that allotopic expression of nucleus-versions of ND6 restored complex I, apoptosis and mitophagy deficiencies caused by the m.14484T > C mutation. The restoration of m.14484T > C mutation-induced mitochondrial dysfunctions by overexpression of ND6 is a step toward therapeutic interventions for LHON and mitochondrial diseases.

The pyrolysis performances and reaction kinetics of pine needles (PN) were investigated by integrating thermogravimetric analysis, Fourier transform infrared spectroscopy, and pyrolysis-gas chromatography/mass spectrometry. The average activation energy of PN was estimated to be 183.2 kJ/mol by Kissinger Akahira Sunose (KAS) and 183.8 kJ/mol by Flynn Wall Ozawa (FWO), respectively at heating rates of 10, 20, and 40 °C/min. The pyrolysis of PN was found to be more efficient at the lower heating rates, while increased heating rates promoted the reaction. Using the King-Kai (K-K) method, the activation energies of hemicellulose, cellulose, and lignin were calculated to be 156, 165, and 172 kJ/mol, respectively. The descending order of evolving gases and functional groups from PN was found to be CO2, C=C, C=O, H2O, CH4, and CO. The main pyrolytic by-products identified were hydrocarbons, phenols, alcohols, ketones, and aldehydes. The determination of kinetic parameters provides fundamental information for predicting the rates at which chemical reactions occur. This study demonstrates the potential of PN as a suitable source for bioenergy.