Association of glycemic variability and prognosis in patients with traumatic brain injury: A retrospective study from the MIMIC-IV database.

BACKGROUND: Elevated glycemic variability (GV) often occurs in intensive care unit (ICU) patients and is associated with patient prognosis. However, the association between GV and prognosis in ICU patients with traumatic brain injury (TBI) remains unclear. METHOD: Clinical data of ICU patients with TBI were obtained from the Medical Information Mart for Intensive Care (MIMIC) -IV database. The coefficient of variation (CV) was utilized to quantify GV, while the Glasgow Coma Scale (GCS) was employed to evaluate the consciousness status of TBI patients. Pearson linear correlation analysis, linear regression, COX regression and restricted cubic spline (RCS) were used to investigate the relationship between CV and consciousness impairment, as well as the risk of in-hospital mortality. RESULT: A total of 1641 ICU patients with TBI were included in the study from the MIMIC-IV database. Pearson linear correlation and restricted cubic spline (RCS) analysis results showed a negative linear relationship between CV and the last GCS (P = 0.002) with no evidence of nonlinearity (P for nonlinear = 0.733). Multivariable linear regression suggested a higher CV was associated with a lower discharge GCS [ß (95 %CI) = -1.86 (-3.08 âˆ¼ -0.65), P = 0.003]. Furthermore, multivariable COX regression indicated that CV ≥ 0.3 was a risk factor for in-hospital death in TBI patients [HR (95 %CI) = 1.74 (1.15-2.62), P = 0.003], and this result was also consistent across sensitivity and subgroup analyses. CONCLUSION: Higher GV is related to poorer consciousness outcomes and increased risk of in-hospital death in ICU patients with TBI. Additional research is needed to understand the logical relationship between GV and TBI progression.

Epigenomic landscapes during prefrontal cortex development and aging in rhesus.

The prefrontal cortex (PFC) is essential for higher-level cognitive functions. How epigenetic dynamics participates in PFC development and aging is largely unknown. Here, we profiled epigenomic landscapes of rhesus monkey PFCs from prenatal to aging stages. The dynamics of chromatin states, including higher-order chromatin structure, chromatin interaction and histone modifications are coordinated to regulate stage-specific gene transcription, participating in distinct processes of neurodevelopment. Dramatic changes of epigenetic signals occur around the birth stage. Notably, genes involved in neuronal cell differentiation and layer specification are pre-configured by bivalent promoters. We identified a cis-regulatory module and the transcription factors (TFs) associated with basal radial glia development, which was associated with large brain size in primates. These TFs include GLI3, CREB5 and SOX9. Interestingly, the genes associated with the basal radial glia (bRG)-associated cis-element module, such as SRY and SOX9, are enriched in sex differentiation. Schizophrenia-associated single nucleotide polymorphisms are more enriched in super enhancers (SEs) than typical enhancers, suggesting that SEs play an important role in neural network wiring. A cis-regulatory element of DBN1 is identified, which is critical for neuronal cell proliferation and synaptic neuron differentiation. Notably, the loss of distal chromatin interaction and H3K27me3 signal are hallmarks of PFC aging, which are associated with abnormal expression of aging-related genes and transposon activation, respectively. Collectively, our findings shed light on epigenetic mechanisms underlying primate brain development and aging.

Examination of Beam Theories for Buckling and Free Vibration of Functionally Graded Porous Beams.

This paper examines the accuracy and effectiveness of various beam theories in predicting the critical buckling loads and fundamental frequencies of functionally graded porous (FGP) beams whose material properties change continuously across the thickness. The beam theories considered are classical beam theory (CBT), first-order shear deformation beam theory (FSDBT), third-order shear deformation beam theory (TSDBT), and the broken-line hypothesis-based shear deformation beam theory (BSDBT). Governing equations for those beam theories are formulated by using the Hamilton's principle and are then solved by means of the generalised differential quadrature method. Finite element simulation solutions are provided as reference results to assess the predictions of those beam theories. Comprehensive numerical results are presented to evaluate the influences of the porosity distribution and coefficient, slenderness ratio, and boundary condition on the difference between theoretical predictions and simulation results. It is found that the differences significantly increase as the porosity coefficient rises, and this effect becomes more noticeable for the rigid beam with a smaller slenderness ratio. Nonetheless, the results produced by the BSDBT are always the closest to simulation ones. The findings in this paper will contribute to the establishment of more refined theories for the mechanical analysis of FGP structures.

Construction and Validation of Nomograms for Predicting Overall Survival and Cancer-Specific Survival in Patients with Primary Anaplastic Oligodendroglioma.

OBJECTIVE: Anaplastic oligodendroglioma (AOD) is a rare high-grade central nervous system tumor. The current research on prognostic prediction of AOD remains limited. This study aimed to identify prognostic factors and establish the nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with AOD. METHODS: Patients diagnosed with AOD between 1992 and 2020 were extracted from the Surveillance, Epidemiology, and End Result database. We performed univariate and multivariate Cox regression analyses to identify independent prognostic factors based on the training group. Kaplan-Meier survival curves were used to compare the impact of various independent factors on patient prognosis. For OS and CSS, the nomograms were constructed and verified by the validation group. Harrell''s concordance index, receiver operating characteristic curves, calibration curves, and decision curve analyses were used to assess the discrimination, consistency, and clinical value of the nomograms. RESULTS: A total of 1202 AOD patients were enrolled, being randomly divided into training (n = 841) and validation (n = 361) groups (7:3 ratio). Univariate and multivariate Cox analysis identified 4 significant independent factors (tumor site, age, surgery, and chemotherapy). For OS and CSS, Harrell''s concordance index were 0.731 (0.705-0.757) and 0.728 (0.701-0.754) in the training group, 0.688 (0.646-0.731) and 0.684 (0.639-0.729) in the validation group, respectively. Receiver operating characteristic curves and Calibration curves showed good discrimination and consistency, respectively. In addition, the decision curve analyses curves showed the nomograms have good clinical benefits. CONCLUSIONS: We successfully established the nomograms to predict the OS and CSS for AOD patients. The nomograms showed good performance in prognostic prediction, assisting clinicians in evaluating patient prognosis and personalizing treatment plans.

Clustered Regularly Interspaced Short Palindromic Repeat/CRISPR-Associated Protein and Its Utility All at Sea: Status, Challenges, and Prospects.

Initially discovered over 35 years ago in the bacterium Escherichia coli as a defense system against invasion of viral (or other exogenous) DNA into the genome, CRISPR/Cas has ushered in a new era of functional genetics and served as a versatile genetic tool in all branches of life science. CRISPR/Cas has revolutionized the methodology of gene knockout with simplicity and rapidity, but it is also powerful for gene knock-in and gene modification. In the field of marine biology and ecology, this tool has been instrumental in the functional characterization of 'dark' genes and the documentation of the functional differentiation of gene paralogs. Powerful as it is, challenges exist that have hindered the advances in functional genetics in some important lineages. This review examines the status of applications of CRISPR/Cas in marine research and assesses the prospect of quickly expanding the deployment of this powerful tool to address the myriad fundamental marine biology and biological oceanography questions.

Construction and validation of a predictive model of pneumonia for ICU patients with traumatic brain injury (TBI).

The incidence of pneumonia in ICU patients with TBI is very high, seriously affecting the prognosis. This study aims to construct a predictive model for pneumonia in ICU patients with TBI and provide help for the prevention of TBI-related pneumonia.Clinical data of ICU patients with TBI were collected from the Medical Information Mart for Intensive Care (MIMIC)-IV database and hospital data. Variables were screened by lasso and multivariate logistic regression to construct a predictive nomogram model, verified in internal validation cohort and external validation cohort by receiver operator characteristic (ROC) curve, calibration curve and decision curve analysis (DCA).A total of 1850 ICU patients with TBI were enrolled in the study from the MIMIC-IV database, including 1298 in the training cohort and 552 in internal validation cohort. The external validation cohort included 240 ICU patients with TBI from hospital data. Nine variables were selected from the training cohort by lasso regression and multivariate logistic regression, and a pneumonia prediction nomogram was constructed. This nomogram has a high discrimination in training, internal validation and external validation cohorts (AUC = 0.857, 0.877, 0.836). The calibration curve and DCA showed that this nomogram had a high calibration and better clinical decision-making efficiency.The nomogram showed excellent discrimination and clinical utility to predict pneumonia, and could identify pneumonia high-risk patients early, thus providing personalised treatment strategies for ICU patients with TBI.

A Comprehensive Review on Combinatorial Film via High-Throughput Techniques.

Numerous technological advancements in the 21st century depend on the creation of novel materials possessing enhanced properties; there is a growing reliance on materials that can be optimized to serve multiple functions. To efficiently save time and meet the requirements of diverse applications, high-throughput and combinatorial approaches are increasingly employed to explore and design superior materials. Among them, gradient thin-film deposition is one of the most mature and widely used technologies for high-throughput preparation of material libraries. This review summarizes recent progress in gradient thin-film deposition fabricated by magnetron sputtering, multi-arc ion plating, e-beam evaporation, additive manufacturing, and chemical bath deposition, providing readers with a fundamental understanding of this research field. First, high-throughput synthesis methods for gradient thin films are emphasized. Subsequently, we present the characteristics of combinatorial films, including microstructure, oxidation, corrosion tests, and mechanical properties. Next, the screening methods employed for evaluating these properties are discussed. Furthermore, we delve into the limitations of high-throughput preparation and characterization techniques for combinatorial films. Finally, we provide a summary and offer our perspectives.

Effect of cloprostenol on luteolysis and comparison of different estrus synchronization protocols in jennies.

Estrus synchronization is necessary for intensive donkey farming. Studies on estrus synchronization in jennies are, however, scarce. We aimed to investigate the susceptibility of the donkey corpus luteum to cloprostenol and design a successful estrus synchronization protocol. Firstly, the effects of different cloprostenol doses and the timing effect of cloprostenol treatment on estrous cycle was investigated. The time from treatment to luteolysis, the ovulation interval, pre-ovulatory diameter, and ovulation rates were compared between groups. Secondly, to identify the best protocol, eight estrus synchronization protocols from three categories were examined. In the first category, jennies in groups A (n = 55) and B (n = 30) received a progesterone releasing intra-vaginal device (JVID®) and cloprostenol treatment. In the second category (group C to F), jennies were pretreated with deslorelin, and then treated with JVID and cloprostenol, including groups C (n = 50), D (n = 50), E (n = 70), and F (n = 65). In the third category, jennies were treated with deslorelin and cloprostenol, including groups G (n = 40) and H (n = 40). Comparisons were made among groups regarding the degree of synchronization, ovulation, and pregnancy rates. Treatment with 0.4 mg cloprostenol on the third day following ovulation minimized the length of the luteal phase and estrous cycle. Synchronization rate varied from 60.0% to 88.6% among groups and was highest in group E. Pregnancy rates did not differ among the eight protocols. In conclusion, cloprostenol effectively induced luteolysis in jennies and a treatment protocol combining deslorelin, cloprostenol, and JVID is efficient for estrus synchronization in donkeys.

Analysis of Prognostic Factors and Surgical Management of Elderly Patients with Low-Grade Gliomas.

BACKGROUND: The number of elderly patients with low-grade glioma (LGG) is increasing, but their prognostic factors and surgical treatment are still controversial. This paper aims to investigate the prognostic factors of overall survival and cancer-specific survival in elderly patients with LGG and analyze the optimal surgical treatment strategy. METHODS: Patients in the study were obtained from the Surveillance, Epidemiology, and End Results database and patients were randomized into a training and a test set (7:3). Clinical variables were analyzed by univariate and multivariate Cox regression analysis to screen for significant prognostic factors, and nomograms visualized the prognosis. In addition, survival analysis of elderly patients regarding different surgical management was also analyzed by Kaplan-Meier curves. RESULTS: Six prognostic factors were screened by univariate and multivariate Cox regression analysis on the training set: tumor site, laterality, histological type, the extent of surgery, radiotherapy, and chemotherapy, and all factors were visualized by nomogram. And we evaluated the accuracy of the nomogram model using consistency index, calibration plots, receiver operator characteristic curves, and decision curve analysis, showing that the nomogram has strong accuracy and applicability. We also found that gross total resection improved overall survival and cancer-specific survival in patients with LGG aged ≥65 years relative to those who did not undergo surgery (P < 0.001). CONCLUSIONS: Based on the Surveillance, Epidemiology, and End Results database, we created and validated prognostic nomograms for elderly patients with LGG, which can help clinicians to provide personalized treatment services and clinical decisions for their patients. More importantly, we found that older age alone should not preclude aggressive surgery for LGGs.