The clinical value of inflammation index in predicting ICU mortality of critically ill patients with intracerebral hemorrhage.

Background: The inflammatory response holds paramount significance in the context of intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates. Biological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) play crucial roles in influencing the systemic inflammatory response following ICH. This study aims to compare the predictive efficacy of NLR, PLR, LMR, SII, and SIRI concerning the risk of mortality in the intensive care unit (ICU) among critically ill patients with ICH. Such a comparison seeks to elucidate their early warning capabilities in the management and treatment of ICH. Methods: Patients with severe ICH requiring admission to the ICU were screened from the Medical Information Marketplace for Intensive Care (MIMIC-IV) database. The outcomes studied included ICU mortality and 30 day ICU hospitalization rates, based on tertiles of the NLR index level. To explore the relationship between the NLR index and clinical outcomes in critically ill patients with ICH, we utilized receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and multivariate logistic regression analysis. Results: A total of 869 patients (51.9% male) were included in the study, with an ICU mortality rate of 22.9% and a 30 day ICU hospitalization rate of 98.4%. Among the five indicators examined, both the ROC curve and DCA indicated that NLR (AUC: 0.660, 95%CI: 0.617-0.703) had the highest predictive ability for ICU mortality. Moreover, this association remained significant even after adjusting for other confounding factors during multivariate analysis (HR: 3.520, 95%CI: 2.039-6.077). Based on the results of the multivariate analysis, incorporating age, albumin, lactic acid, NLR, and GCS score as variables, we developed a nomogram to predict ICU mortality in critically ill patients with ICH. Conclusion: NLR emerges as the most effective predictor of ICU mortality risk among critically ill patients grappling with ICH when compared to the other four indicators. Furthermore, the integration of albumin and lactic acid indicators into the NLR nomogram enhances the ability to promptly identify ICU mortality in individuals facing severe ICH.

Gene Expression Profile Identifies LncRNA AL355974.3 As a Potential Glioma Biomarker.

OBJECTIVE: Glioma is a central nervous system tumor arising from glial cells. Despite significant advances in diagnosis and treatment, most patients with high-grade gliomas have a poor prognosis. Many studies have shown that long noncoding RNAs (lncRNAs) may play important roles in the development, progression and treatment of many tumors, including gliomas. Molecularly targeted therapy may be a new direction for the adjuvant treatment of glioma. Therefore, we hope that by studying differentially expressed lncRNAs (DElncRNAs) in glioma, we can discover lncRNAs that can serve as biomarkers for glioma and provide better therapeutic modalities for glioma patients. METHODS: First, the expression of lncRNAs in 5 normal brain (NB) tissues and 10 glioma tissues was examined by RNA sequencing (RNA-seq). Next, we performed Kaplan-Meier analysis of data from The Cancer Genome Atlas (TCGA) database to assess the prognostic value of these variables. Finally, functional analysis of the DElncRNAs was performed by means of Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. RESULTS: RNA sequencing analysis revealed 85 upregulated miRNAs and 71 downregulated lncRNAs in low-grade glioma (LGG) and 50 upregulated lncRNAs and 70 downregulated lncRNAs in glioblastoma (GBM). Among them, AL355974.3 was the most upregulated lncRNA. LINC00632 was the most downregulated lncRNA. Second, LGG patients with higher AL355974.3 expression had worse overall survival according to Kaplan-Meier analysis of the TCGA database. Finally, bioinformatics analysis revealed that the target genes of these DElncRNAs were enriched in various biological processes and signaling pathways, such as cell metabolic and developmental processes. CONCLUSION: Our findings provide evidence that AL355974.3 may be a new biomarker for glioma.

Acute kidney injury after intracerebral hemorrhage: a mini review.

Intracerebral hemorrhage (ICH) stands as a prevalent and pivotal clinical condition. The potential cooccurrence of acute kidney injury (AKI) among afflicted individuals can profoundly influence their prognosis. In recent times, there has been a growing focus among clinical practitioners on researching the relationship between ICH and AKI. AKI occurring concurrently with ICH predominantly arises from both hemodynamic and non-hemodynamic mechanisms. The latter encompasses neurohumoral regulation, inflammatory response, oxidative stress, and iatrogenic factors such as contrast agents, dehydrating agents, antibiotics, and diuretics. Moreover, advanced age, hypertension, elevated baseline creatinine levels, chronic kidney disease, and larger hematomas predispose patients to AKI. Additionally, the current utilization of biomarkers and the development of predictive models appear promising in identifying patients at risk of AKI after ICH. This article aims to underscore the potential of the aforementioned insights to inspire novel approaches to early clinical intervention.

De novo variants in the RNU4-2 snRNA cause a frequent neurodevelopmental syndrome.

Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes1. Large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here we identify the non-coding RNA RNU4-2 as a syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome2. We identify an 18 base pair region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 115 individuals with NDD. Most individuals (77.4%) have the same highly recurrent single base insertion (n.64_65insT). In 54 individuals in whom it could be determined, the de novo variants were all on the maternal allele. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to RNU4-1 and other U4 homologues. Using RNA sequencing, we show how 5' splice-site use is systematically disrupted in individuals with RNU4-2 variants, consistent with the known role of this region during spliceosome activation. Finally, we estimate that variants in this 18 base pair region explain 0.4% of individuals with NDD. This work underscores the importance of non-coding genes in rare disorders and will provide a diagnosis to thousands of individuals with NDD worldwide.

The association between physical activity and cardiovascular events, tumors and all-cause mortality in patients with maintenance hemodialysis with different nutritional status.

The current research focuses on the effects of nutritional supplementation and exercise on dialysis patients, but whether physical activity (PA) can reduce the risk of adverse outcomes for patients with different nutritional status is not clear. The maintenance hemodialysis (MHD) patients were recruited from April 2021 to April 2022. The information of PA was obtained from the international physical activity questionnaire (IPAQ). The outcomes were cardiovascular death, myocardial infarction, stroke, heart failure, atrial fibrillation, tumor and all-cause death. We used COX proportional risk model to estimate the association between PA and the outcomes of MHD patients. Patients are classified into two groups based on geriatric nutritional risk index (GNRI) and classified by age, and we used COX proportional risk model to estimate the association of PA and outcomes in subgroups. The isotemporal substitution model (ISM) was used to estimate the effects of replacing light physical activity (LPA) with moderate physical activity (MPA) or vigorous physical activity (VPA) on risk of cardiovascular events, tumors, and all-cause death in different subgroups. The effects of PA on ankle-brachial index (ABI) and body fat content were analyzed in different IPAQ groups. A total of 241 maintenance hemodialysis patients were included, 105 peoples developed cardiovascular death, myocardial infarction, stroke, heart failure, atrial fibrillation, tumor and all-cause death (43.6%). The median follow-up time was 12 months. MPA reduced the risk of outcome in MHD patients or high GNRI patients (40% vs 39%).In MHD patients who was under 65 years with high GNRI, MPA reduced cardiovascular death, myocardial infarction, stroke, heart failure, atrial fibrillation, tumor and all-cause death by 55%.PA reduced the risk of cardiovascular event by 65%, but did not reduce the risk of tumor or all-cause death. Replacing LPA with VPA did not improve clinical outcomes. It actually increases the risk of heart failure 0.4%. MPA reduced the risk of cardiovascular death, myocardial infarction, stroke, heart failure, atrial fibrillation, tumor, all-cause death in MHD patients under 65 years, while VPA had no health benefit.Trial registration: ChiCTR210050998.

Strong and consistent effects of waterbird composition on HPAI H5 occurrences across Europe.

Since 2014, highly pathogenic avian influenza (HPAI) H5 viruses of clade 2.3.4.4 have been dominating the outbreaks across Europe, causing massive deaths among poultry and wild birds. However, the factors shaping these broad-scale outbreak patterns, especially those related to waterbird community composition, remain unclear. In particular, we do not know whether these risk factors differ from those of other H5 clades. Addressing this knowledge gap is important for predicting and preventing future HPAI outbreaks. Using extensive waterbird survey datasets from about 6883 sites, we here explored the effect of waterbird community composition on HPAI H5Nx (clade 2.3.4.4) spatial patterns in the 2016/2017 and 2020/2021 epidemics in Europe, and compared it with the 2005/2006 HPAI H5N1 (clade 2.2) epidemic. We showed that HPAI H5 occurrences in wild birds in the three epidemics were strongly associated with very similar waterbird community attributes, which suggested that, in nature, similar interspecific transmission processes operate between the HPAI H5 subtypes or clades. Importantly, community phylogenetic diversity consistently showed a negative association with H5 occurrence in all three epidemics, suggesting a dilution effect of phylogenetic diversity. In contrast, waterbird community variables showed much weaker associations with HPAI H5Nx occurrence in poultry. Our results demonstrate that models based on previous epidemics can predict future HPAI H5 patterns in wild birds, implying that it is important to include waterbird community factors in future HPAI studies to predict outbreaks and improve surveillance activities.

The clinical value of nutritional and inflammatory indicators in predicting pneumonia among patients with intracerebral hemorrhage.

Immunosuppression and malnutrition play pivotal roles in the complications of intracerebral hemorrhage (ICH) and are intricately linked to the development of stroke-associated pneumonia (SAP). Inflammatory markers, including NLR (neutrophil-to-lymphocyte ratio), SII (systemic immune inflammation index), SIRI (systemic inflammatory response index), and SIS (systemic inflammation score), along with nutritional indexes such as CONUT (controlling nutritional status) and PNI (prognostic nutritional index), are crucial indicators influencing the inflammatory state following ICH. In this study, our objective was to compare the predictive efficacy of inflammatory and nutritional indices for SAP in ICH patients, aiming to determine and explore their clinical utility in early pneumonia detection. Patients with severe ICH requiring ICU admission were screened from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The outcomes included the occurrence of SAP and in-hospital death. Receiver operating characteristic (ROC) analysis, multivariate logistic regression, smooth curve analysis, and stratified analysis were employed to investigate the relationship between the CONUT index and the clinical outcomes of patients with severe ICH. A total of 348 patients were enrolled in the study. The incidence of SAP was 21.3%, and the in-hospital mortality rate was 17.0%. Among these indicators, multiple regression analysis revealed that CONUT, PNI, and SIRI were independently associated with SAP. Further ROC curve analysis demonstrated that CONUT (AUC 0.6743, 95% CI 0.6079-0.7408) exhibited the most robust predictive ability for SAP in patients with ICH. Threshold analysis revealed that when CONUT < 6, an increase of 1 point in CONUT was associated with a 1.39 times higher risk of SAP. Similarly, our findings indicate that CONUT has the potential to predict the prognosis of patients with ICH. Among the inflammatory and nutritional markers, CONUT stands out as the most reliable predictor of SAP in patients with ICH. Additionally, it proves to be a valuable indicator for assessing the prognosis of patients with ICH.

A new artificial intelligence system for both stomach and small-bowel capsule endoscopy.

BACKGROUND AND AIMS: Despite the benefits of artificial intelligence in small-bowel (SB) capsule endoscopy (CE) image reading, information on its application in the stomach and SB CE is lacking. METHODS: In this multicenter, retrospective diagnostic study, gastric imaging data were added to the deep learning-based SmartScan (SS), which has been described previously. A total of 1069 magnetically controlled GI CE examinations (comprising 2,672,542 gastric images) were used in the training phase for recognizing gastric pathologies, producing a new artificial intelligence algorithm named SS Plus. A total of 342 fully automated, magnetically controlled CE examinations were included in the validation phase. The performance of both senior and junior endoscopists with both the SS Plus-assisted reading (SSP-AR) and conventional reading (CR) modes was assessed. RESULTS: SS Plus was designed to recognize 5 types of gastric lesions and 17 types of SB lesions. SS Plus reduced the number of CE images required for review to 873.90 (median, 1000; interquartile range [IQR], 814.50-1000) versus 44,322.73 (median, 42,393; IQR, 31,722.75-54,971.25) for CR. Furthermore, with SSP-AR, endoscopists took 9.54 minutes (median, 8.51; IQR, 6.05-13.13) to complete the CE video reading. In the 342 CE videos, SS Plus identified 411 gastric and 422 SB lesions, whereas 400 gastric and 368 intestinal lesions were detected with CR. Moreover, junior endoscopists remarkably improved their CE image reading ability with SSP-AR. CONCLUSIONS: Our study shows that the newly upgraded deep learning-based algorithm SS Plus can detect GI lesions and help improve the diagnostic performance of junior endoscopists in interpreting CE videos.

Water Transport-Induced Liquid-Liquid Phase Separation Facilitates Gelation for Controllable and Facile Fabrication of Physically Crosslinked Microgels.

Physically crosslinked microgels (PCMs) offer a biocompatible platform for various biomedical applications. However, current PCM fabrication methods suffer from their complexity and poor controllability, due to their reliance on altering physical conditions to initiate gelation and their dependence on specific materials. To address this issue, a novel PCM fabrication method is devised, which employs water transport-induced liquid-liquid phase separation (LLPS) to trigger the intermolecular interaction-supported sol-gel transition within aqueous emulsion droplets. This method enables the controllable and facile generation of PCMs through a single emulsification step, allowing for the facile production of PCMs with various materials and sizes, as well as controllable structures and mechanical properties. Moreover, this PCM fabrication method holds great promise for diverse biomedical applications. The interior of the PCM not only supports the encapsulation and proliferation of bacteria but also facilitates the encapsulation of eukaryotic cells after transforming the system into an all-aqueous emulsion. Furthermore, through appropriate surface functionalization, the PCMs effectively activate T cells in vitro upon coculturing. This work represents an advancement in PCM fabrication and offers new insights and perspectives for microgel engineering.

Intermediate open state of CD4-bound HIV-1 env heterotrimers in asia CRFs.

The HIV-1 envelope glycoprotein (Env) plays crucial role in viral infection by facilitating viral attachment to host cells and inducing fusion of the virus with the host cell membrane. This fusion allows the HIV-1 viral genome to enter the target cell then triggering various stages of the viral life cycle. The native Env directly interacts with the main receptor CD4 and the co-receptor (CCR5 or CXCR4) in human cell membrane then induces membrane fusion. The elucidation of the structure of Env with CD4 and co-receptors in different HIV-1 subtypes is essential for the understanding of the mechanism of virus entry. Here we report the Cryo-EM structure of the CD4-bound HIV-1 heterotrimeric Env from Asia prevalent CRF07_BC CH119 strain. In this structure, the binding of three CD4 molecules with Env induced extensively conformational changes in gp120, resulting in the transformation of the Env from close state to intermediate open state. Additionally, the conformational shift of V1/V2 loops of the heterotrimeric Env allosterically expose the V3 loop and promoting the further interactions with co-receptor CCR5 or CXCR4. These findings not only illustrate the structural complexity and plasticity of HIV-1 Env but also give new insights how the biological trimeric Env initialize the immune recognition and membrane fusion.

Glutathione-responsive Aggregation-induced Emission Photosensitizers for Enhanced Photodynamic Therapy of Lung Cancer.

Lung cancer, a highly prevalent and lethal form of cancer, is often associated with oxidative stress. Photodynamic therapy (PDT) has emerged as a promising alternative therapeutic tool in cancer treatments, but its efficacy is closely correlated to the photosensitizers generating reactive oxygen species (ROS) and the antioxidant capacity of tumor cells. In particular, glutathione (GSH) can reduce the ROS and thus compromise PDT efficacy. In this study, a GSH-responsive near-infrared photosensitizer (TBPPN) based on aggregation-induced emission for real-time monitoring of GSH levels and enhanced PDT for lung cancer treatment is developed. The strategic design of TBPPN, consisting of a donor-acceptor structure and incorporation of dinitrobenzene, enables dual functionality by not only the fluorescence being activated by GSH but also depleting GSH to enhance the cytotoxic effect of PDT. TBPPN demonstrates synergistic PDT efficacy in vitro against A549 lung cancer cells by specifically targeting different cellular compartments and depleting intracellular GSH. In vivo studies further confirm that TBPPN can effectively inhibit tumor growth in a mouse model with lung cancer, highlighting its potential as an integrated agent for the diagnosis and treatment of lung cancer. This approach enhances the effectiveness of PDT for lung cancer and deserves further exploration of its potential for clinical application.

Analysis of MRI features and associated factors of the pituitary neuroendocrine tumor streaky sign.

OBJECTIVES: Observation of pituitary neuroendocrine tumors with streaky sign on MRI, analysis of their features on imaging and further investigation of the relationship between the direction of the streak sign and the direction of optimal tumor expansion. METHODS: The MR images of 237 patients with pituitary neuroendocrine tumors were retrospectively analyzed. The streaky-like high signal with a substantial length of more than 10 mm and obvious enhancement on T1WI was defined as the streaky sign. Finally, 66 patients were included in the study, comprising 33 patients with streaky sign pituitary neuroendocrine tumors and 33 randomly selected patients with non-streaky sign pituitary neuroendocrine tumors. The general condition of these 66 patients, the imaging features of the tumor, and the measurement and analysis of the direction of the streaky sign in relation to the direction of optimal tumor extension were observed and analyzed. RESULTS: On MRI, 85 streaky signs were observed. The average deviation between the direction angle of all the streaky signs and the optimal extension direction angle of the tumor was approximately 11°. The longest streaky sign angle was positively correlated with the optimal extension angle of the tumor, with a correlation coefficient of 0.967. CONCLUSION: The presence of a streaky sign of pituitary neuroendocrine tumors may indicate a dilated sinus or a small blood vessel. Its direction is highly consistent with the optimal extension direction of the tumor, which has a certain supporting effect on the long-distance growth of the tumor.

Indian Ocean temperature anomalies predict long-term global dengue trends.

Despite identifying El Niño events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.

Does digital infrastructure construction impact urban carbon emission reduction? Evidence from China's smart city construction.

As the cornerstone of the digital economy, the construction of digital infrastructure plays a crucial role in promoting China's high-quality economic growth.. Against the backdrop of the "dual-carbon" goals, the development of digital infrastructure will provide new momentum for carbon emissions reduction in urban areas. This study utilizes unbalanced panel data from 277 prefecture-level cities in China between 2008 and 2019, treating the smart city construction as a quasi-natural experiment, to systematically evaluate the impact of the pilot construction of smart city on urban carbon emissions intensity. The research findings reveal that the construction of the smart city has significantly contributed to the reduction of urban carbon emissions intensity, indicating that digital infrastructure contributes to urban carbon emission reduction. The reduction of carbon emissions resulting from smart city construction is particularly significant in the East and Central regions., as well as regions with high financial development levels, regions with high human capital levels and non resource-based cities. The construction of the smart city primarily achieves the reduction of urban carbon emissions intensity through two main pathways: improving the penetration rate of digital infrastructure and enhancing technological innovation capability. Therefore, this study recommends that local governments strengthen the integration and penetration of digital infrastructure with traditional industries, foster urban innovation vitality, and accelerate the transformation towards green and low-carbon cities.

Discovery of an immunosuppressive functional metabolite from the insect-derived endophytic Aspergillus taichungensis SMU01.

Three p-terphenyl metabolites (1-3), three indole-diterpenoids (4-6), an herbicide sesquiterpene (7), a flavonoid (8), and five other small molecules containing nitrogen (9-13) were isolated from the medicinal insect (Periplaneta americana)-derived endophytic Aspergillus taichungensis SMU01. Their chemical structures were elucidated on the basis of spectroscopic data and quantum chemical computational methods. Biological activity of these isolates in the differentiation of mouse CD4+ T cell subsets was evaluated. Importantly, metabolites 2 targeting JAK-STAT signaling pathway could hold potential benefits in maintaining peripheral immune homeostasis and alleviating the progression of autoimmune diseases.

Improved dual-aggregation polyp segmentation network combining a pyramid vision transformer with a fully convolutional network.

Automatic and precise polyp segmentation in colonoscopy images is highly valuable for diagnosis at an early stage and surgery of colorectal cancer. Nevertheless, it still posed a major challenge due to variations in the size and intricate morphological characteristics of polyps coupled with the indistinct demarcation between polyps and mucosas. To alleviate these challenges, we proposed an improved dual-aggregation polyp segmentation network, dubbed Dua-PSNet, for automatic and accurate full-size polyp prediction by combining both the transformer branch and a fully convolutional network (FCN) branch in a parallel style. Concretely, in the transformer branch, we adopted the B3 variant of pyramid vision transformer v2 (PVTv2-B3) as an image encoder for capturing multi-scale global features and modeling long-distant interdependencies between them whilst designing an innovative multi-stage feature aggregation decoder (MFAD) to highlight critical local feature details and effectively integrate them into global features. In the decoder, the adaptive feature aggregation (AFA) block was constructed for fusing high-level feature representations of different scales generated by the PVTv2-B3 encoder in a stepwise adaptive manner for refining global semantic information, while the ResidualBlock module was devised to mine detailed boundary cues disguised in low-level features. With the assistance of the selective global-to-local fusion head (SGLFH) module, the resulting boundary details were aggregated selectively with these global semantic features, strengthening these hierarchical features to cope with scale variations of polyps. The FCN branch embedded in the designed ResidualBlock module was used to encourage extraction of highly merged fine features to match the outputs of the Transformer branch into full-size segmentation maps. In this way, both branches were reciprocally influenced and complemented to enhance the discrimination capability of polyp features and enable a more accurate prediction of a full-size segmentation map. Extensive experiments on five challenging polyp segmentation benchmarks demonstrated that the proposed Dua-PSNet owned powerful learning and generalization ability and advanced the state-of-the-art segmentation performance among existing cutting-edge methods. These excellent results showed our Dua-PSNet had great potential to be a promising solution for practical polyp segmentation tasks in which wide variations of data typically occurred.

Satellite NO2 Retrieval Complicated by Aerosol Composition over Global Urban Agglomerations: Seasonal Variations and Long-Term Trends (2001-2018).

Tropospheric nitrogen dioxide (NO2) poses a serious threat to the environmental quality and public health. Satellite NO2 observations have been continuously used to monitor NO2 variations and improve model performances. However, the accuracy of satellite NO2 retrieval depends on the knowledge of aerosol optical properties, in particular for urban agglomerations accompanied by significant changes in aerosol characteristics. In this study, we investigate the impacts of aerosol composition on tropospheric NO2 retrieval for an 18 year global data set from Global Ozone Monitoring Experiment (GOME)-series satellite sensors. With a focus on cloud-free scenes dominated by the presence of aerosols, individual aerosol composition affects the uncertainties of tropospheric NO2 columns through impacts on the aerosol loading amount, relative vertical distribution of aerosol and NO2, aerosol absorption properties, and surface albedo determination. Among aerosol compositions, secondary inorganic aerosol mostly dominates the NO2 uncertainty by up to 43.5% in urban agglomerations, while organic aerosols contribute significantly to the NO2 uncertainty by -8.9 to 37.3% during biomass burning seasons. The possible contrary influences from different aerosol species highlight the importance and complexity of aerosol correction on tropospheric NO2 retrieval and indicate the need for a full picture of aerosol properties. This is of particular importance for interpreting seasonal variations or long-term trends of tropospheric NO2 columns as well as for mitigating ozone and fine particulate matter pollution.

De novo variants in the non-coding spliceosomal snRNA gene RNU4-2 are a frequent cause of syndromic neurodevelopmental disorders.

Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes1. Increasingly, large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here, we identify the non-coding RNA RNU4-2 as a novel syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome2. We identify an 18 bp region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and Stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 119 individuals with NDD. The vast majority of individuals (77.3%) have the same highly recurrent single base-pair insertion (n.64_65insT). We estimate that variants in this region explain 0.41% of individuals with NDD. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to its contiguous counterpart RNU4-1 and other U4 homologs, supporting RNU4-2's role as the primary U4 transcript in the brain. Overall, this work underscores the importance of non-coding genes in rare disorders. It will provide a diagnosis to thousands of individuals with NDD worldwide and pave the way for the development of effective treatments for these individuals.

Molecularly-regulating oxygen-containing functional groups of ramie activated carbon for high-performance supercapacitors.

Effectively managing oxygen-containing functional groups (OCFGs) within activated carbon and methodically elucidating their intricate types and proportions are essential for considerably improving the electrochemical performance of carbon-based supercapacitors. Herein, we designed a ZnCl2-based molecular regulation strategy to introduce OCFGs into ramie-activated carbon (RAC), managing different OCFGs and revealing their structure-activity relationship with electrochemical performance. Thus, this regulated RAC, with a 3.5-fold enhancement in advantageous OCFGs (a-OCFGs: CO and COO), exhibits a supreme specific capacitance of 286.4F g-1 at 1 A/g and an excellent capacitance retention rate of 89.7 % at 20 A/g in an aqueous electrolyte, considerably surpassing that of nonregulated RAC (212.0F g-1 and 81.9 %). This confirms that a-OCFGs provide ample ion-storage accommodation and suppress solvent electronic oxidation, thereby enhancing electrochemical performance. Furthermore, its electrochemical performance is competitive with that of the commercial YP-50F (129.2F g-1 at 1 A/g). Therefore, this work not only highlights the contributions of specific OCFGs to high electrochemical performance but also designs a promising commercial electrode material to meet the demands of OCFGs-adequate carbon-based energy storage devices.

Association between ambient air pollutants and short-term mortality risks during 2015-2019 in Guangzhou, China.

With the development of technology and industry, the problem of global air pollution has become difficult to ignore. We investigated the association between air pollutant concentrations and daily all-cause mortality and stratified the analysis by sex, age, and season. Data for six air pollutants [fine particulate matter (PM2.5), inhalable particles (PM10), nitric dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)] and daily mortality rates were collected from 2015 to 2019 in Guangzhou, China. A time-series study using a quasi-Poisson generalized additive model was used to examine the relationships between environmental pollutant concentrations and mortality. Mortality data for 296,939 individuals were included in the analysis. The results showed that an increase of 10 µg/m3 in the concentrations of PM2.5, PM10, SO2, O3, NO2, and CO corresponded to 0.84% [95% confidence interval (CI): 0.47, 1.21%], 0.70% (0.44, 0.96%), 3.59% (1.77, 5.43%), 0.21% (0.05, 0.36%), 1.06% (0.70, 1.41%), and 0.05% (0.02, 0.09%), respectively. The effects of the six air pollutants were more significant for male individuals than female individuals, the cool season than the warm season, and people 75 years or older than those younger than 75 years. PM2.5, PM10, SO2, and NO2 were all associated with neoplasms and circulatory and respiratory diseases. The two-pollutant models found that PM2.5, PM10, and NO2 may independently affect the risk of mortality. The results showed that exposure to PM2.5, PM10 and NO2 may increase the risk of daily all-cause excessive mortality in Guangzhou.