Search

Abstract Eels migrate along largely unknown routes to their spawning ground. By coupling Zermelo’s navigation solution and data from the Japan Coastal Ocean Predictability Experiment 2 (JCOPE2M), we simulated a range of seasonal scenarios, swimming speeds, and swimming depths to predict paths that minimize migration duration and energy cost. Our simulations predict a trade-off between migration duration and energy cost. Given that eels do not refuel during their migration, our simulations suggest eels should travel at speeds of 0.4–0.6 body-length per second to retain enough energy reserves for reproduction. For real eels without full information of the ocean currents, they cannot optimize their migration in strong surface currents, thus when swimming at slow swimming speeds, they should swim at depths of 200 m or greater. Eels swimming near the surface are also influenced by seasonal factors, however, migrating at greater depths mitigates these effects. While greater depths present more favorable flow conditions, water temperature may become increasingly unfavorable, dropping near or below 5 °C. Our results serve as a benchmark, demonstrating the complex interplay between swimming speed, depth, seasonal factors, migration time, and energy consumption, to comprehend the migratory behaviors of Japanese eels and other migratory fish.

Abstract Integrating flexible electronics and photonics can create revolutionary technologies, but combining these components on a single polymer device has been difficult, particularly for high-volume manufacturing. Here, we present a robust chiplet-level heterogeneous integration of polymer-based circuits (CHIP), where ultrathin polymer electronic and optoelectronic chiplets are vertically bonded at room temperature and shaped into application-specific forms with monolithic Input/Output (I/O). This process was used to develop a flexible 3D integrated optrode with high-density microelectrodes for electrical recording, micro light-emitting diodes (μLEDs) for optogenetic stimulation, temperature sensors for bio-safe operations, and shielding designs to prevent optoelectronic artifacts. CHIP enables simple, high-yield, and scalable 3D integration, double-sided area utilization, and miniaturization of connection I/O. Systematic characterization demonstrated the scheme’s success and also identified frequency-dependent origins of optoelectronic artifacts. We envision CHIP being applied to numerous polymer-based devices for a wide range of applications.

Abstract Activated Wnt/β-catenin pathway is a key genetic event in liver cancer development. Solute carrier (SLC) transporters are promising drug targets. Here, we identify SLC13A3 as a drug-targetable effector downstream of β-catenin in liver cancer. SLC13A3 expression is elevated in human liver cancer samples with gain of function (GOF) mutant CTNNB1, the gene encoding β-catenin. Activation of β-catenin up-regulates SLC13A3, leading to intracellular accumulation of endogenous SLC13A3 substrates. SLC13A3 is identified as a low-affinity transporter for glutathione (GSH). Silencing of SLC13A3 downregulates the leucine transporter SLC7A5 via c-MYC signaling, leading to leucine depletion and mTOR inactivation. Furthermore, silencing of SLC13A3 depletes GSH and induces autophagic ferroptosis in β-catenin-activated liver cancer cells. Importantly, both genetic inhibition of SLC13A3 and a small molecule SLC13A3 inhibitor suppress β-catenin-driven hepatocarcinogenesis in mice. Altogether, our study suggests that SLC13A3 could be a promising therapeutic target for treating human liver cancers with GOF CTNNB1 mutations.

Abstract Background The genetic susceptibility association between viral infection and the risk of colorectal cancer (CRC) has not been established. Methods We conducted two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data. In addition to traditional MR methods, we employed several other approaches, including cML, ConMix, MR-RAPS, and dIVW, to comprehensively assess causal effects. Sensitivity analyses were also performed to ensure the robustness of the results. Results After sensitivity analysis, presence of SNPs linked to increased susceptibility to cold sores infection was found to decrease the risk of CRC (OR: 0.73, 95% CI: 0.57–0.93, P = 0.01). In subgroup analysis, presence of SNPs linked to increased susceptibility to viral hepatitis (OR: 0.89, 95% CI: 0.81–0.98, P = 0.02) and infectious mononucleosis (OR: 0.91, 95% CI: 0.84–0.98, P = 0.02) were associated with a decreased risk of colon cancer, while measles virus (OR: 1.41, 95% CI: 1.07–1.85, P = 0.01) was associated with an increased risk of colon cancer. Presence of SNPs linked to increased susceptibility to herpes zoster (OR: 1.26, 95% CI: 1.05–1.52, P = 0.01) was associated with an increased risk of rectal cancer, while infectious mononucleosis (OR: 0.809, 95% CI: 0.80–0.98, P = 0.02) was associated with a decreased risk. Conclusion The study provides the first evidence of the genetic susceptibility associations between different viral infections and CRC, enhancing our understanding of the etiology of CRC.

Abstract Background Osteosarcoma (OS) is one of the most common primary malignant tumors of bone in children, which develops from osteoblasts and typically occurs during the rapid growth phase of the bone. Recently, Super-Enhancers(SEs)have been reported to play a crucial role in osteosarcoma growth and metastasis. Therefore, there is an urgent need to identify specific targeted inhibitors of SEs to assist clinical therapy. This study aimed to elucidate the role of BRD4 inhibitor GNE-987 targeting SEs in OS and preliminarily explore its mechanism. Methods We evaluated changes in osteosarcoma cells following treatment with a BRD4 inhibitor GNE-987. We assessed the anti-tumor effect of GNE-987 in vitro and in vivo by Western blot, CCK8, flow cytometry detection, clone formation, xenograft tumor size measurements, and Ki67 immunohistochemical staining, and combined ChIP-seq with RNA-seq techniques to find its anti-tumor mechanism. Results In this study, we found that extremely low concentrations of GNE-987(2–10 nM) significantly reduced the proliferation and survival of OS cells by degrading BRD4. In addition, we found that GNE-987 markedly induced cell cycle arrest and apoptosis in OS cells. Further study indicated that VHL was critical for GNE-987 to exert its antitumor effect in OS cells. Consistent with in vitro results, GNE-987 administration significantly reduced tumor size in xenograft models with minimal toxicity, and partially degraded the BRD4 protein. KRT80 was identified through analysis of the RNA-seq and ChIP-seq data. U2OS HiC analysis suggested a higher frequency of chromatin interactions near the KRT80 binding site. The enrichment of H3K27ac modification at KRT80 was significantly reduced after GNE-987 treatment. KRT80 was identified as playing an important role in OS occurrence and development. Conclusions This research revealed that GNE-987 selectively degraded BRD4 and disrupted the transcriptional regulation of oncogenes in OS. GNE-987 has the potential to affect KRT80 against OS.

Abstract Background Contrast-induced acute kidney injury (CI-AKI) is an acute renal complication that occurs after intravascular contrast agent administration. Sodium selenite (SS) is an inorganic source of Se and has potent antioxidant properties. This study intends to examine its anti-inflammatory and antioxidant effects in CI-AKI. Methods A rat CI-AKI model was established with the pretreatment of SS (0.35 mg/kg). Hematoxylin-eosin staining was employed for histopathological analysis of rat kidney specimens. Biochemical analysis was conducted for renal function detection. Tissue levels of oxidative stress-related markers were estimated. Reverse transcription-quantitative polymerase chain reaction revealed the mRNA levels of proinflammatory cytokines. Western blotting showed the Nrf2 signaling-related protein expression in the rat kidney. Results SS administration alleviated the renal pathological changes and reduced the serum levels of serum creatinine, blood urea nitrogen, neutrophil gelatinase-associated lipocalin, cystatin C, and urinary level of kidney injury molecule-1 in CI-AKI rats. SS attenuated oxidative stress and inflammatory response in CI-AKI rat kidney tissues. SS activated the Nrf2 signaling transduction in the renal tissues of rats with CI-AKI. Conclusion SS ameliorates CI-AKI in rats by reducing oxidative stress and inflammation via the Nrf2 signaling.

Abstract Background The mental health inequality between migrants and non-migrants was exacerbated by the COVID-19 pandemic. Identifying key determinants of this inequality is essential in promoting health equity. Methods This cross-sectional study recruited Shanghai residents by purposive sampling during the city-wide lockdown (from April 29 to June 1, 2022) using an online questionnaire. Migration statuses (non-migrants, permanent migrants, and temporary migrants) were identified by migration experience and by household registration in Shanghai. Mental health symptoms (depression, anxiety, loneliness, and problematic anger) were assessed by self-report scales. The nonlinear Blinder-Oaxaca decomposition was used to quantify mental health inequality (i.e., differences in predicted probabilities between migration groups) and the contribution of expected correlates (i.e., change in predicted probability associated with variation in the correlate divided by the group difference). Results The study included 2738 participants (771 [28.2%] non-migrants; 389 [14.2%] permanent migrants; 1578 [57.6%] temporary migrants). We found inequalities in depression (7.1%) and problematic anger (7.8%) between permanent migrants and non-migrants, and inequalities in anxiety (7.3%) and loneliness (11.3%) between temporary migrants and non-migrants. When comparing permanent migrants and non-migrants, age and social capital explained 12.7% and 17.1% of the inequality in depression, and 13.3% and 21.4% of the inequality in problematic anger. Between temporary migrants and non-migrants, age and social capital also significantly contributed to anxiety inequality (23.0% and 18.2%) and loneliness inequality (26.5% and 16.3%), while monthly household income (20.4%) and loss of monthly household income (34.0%) contributed the most to anxiety inequality. Conclusions Significant inequalities in depression and problematic anger among permanent migrants and inequalities in anxiety and loneliness among temporary migrants were observed. Strengthening social capital and economic security can aid in public health emergency preparedness and promote mental health equity among migrant populations.

Abstract This study aimed to develop and internally validate a nomogram model for assessing the risk of intraoperative hypothermia in patients undergoing video-assisted thoracoscopic (VATS) lobectomy. This study is a retrospective study. A total of 530 patients who undergoing VATS lobectomy from January 2022 to December 2023 in a tertiary hospital in Wuhan were selected. Patients were divided into hypothermia group (n = 346) and non-hypothermia group (n = 184) according to whether hypothermia occurred during the operation. Lasso regression was used to screen the independent variables. Logistic regression was used to analyze the risk factors of hypothermia during operation, and a nomogram model was established. Bootstrap method was used to internally verify the nomogram model. Receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the model. Calibration curve and Hosmer Lemeshow test were used to evaluate the accuracy of the model. Decision curve analysis (DCA) was used to evaluate the clinical utility of the model. Intraoperative hypothermia occurred in 346 of 530 patients undergoing VATS lobectomy (65.28%). Logistic regression analysis showed that age, serum total bilirubin, inhaled desflurane, anesthesia duration, intraoperative infusion volume, intraoperative blood loss and body mass index were risk factors for intraoperative hypothermia in patients undergoing VATS lobectomy (P

The title compound, C12H10N2O3, was obtained by the deacetylation reaction of 1-(6-amino-5-nitronaphthalen-2-yl)ethanone in a concentrated sulfuric acid methanol solution. The molecule comprises a naphthalene ring system bearing an acetyl group (C-3), an amino group (C-7), and a nitro group (C-8). In the crystal, the molecules are assembled into a two-dimensional network by N...H/H...N and O...H/H...O hydrogen-bonding interactions. n–π and π–π stacking interactions are the dominant interactions in the three-dimensional crystal packing. Hirshfeld surface analysis indicates that the most important contributions are from O...H/H...O (34.9%), H...H (33.7%), and C...H/H...C (11.0%) contacts. The energies of the frontier molecular orbitals were computed using density functional theory (DFT) calculations at the B3LYP-D3BJ/def2-TZVP level of theory and the LUMO–HOMO energy gap of the molecule is 3.765 eV.

This paper introduces a comprehensive approach for predicting chemical concentrations (C) of sulfur compound in a two-dimensional space (x, y) by numerical solution of mass transfer equation and integration of machine learning. Data of training/validation are obtained from mass transfer modeling on adsorption separation utilizing porous adsorbent for petroleum desulfurization. Mass transfer modeling data were utilized for machine learning models which included three different regression models, namely Support Vector Machine (SVM), Decision Tree Regression (DT), and Multilayer Perceptron (MLP). The hyper-parameters of these base models were optimized using the Grey Wolf Optimization (GWO) algorithm. The ensemble models, denoted as ADA-DT, ADA-MLP, and ADA-SVM were assessed based on key performance metrics, including R2, MAE, RMSE, and MAPE. Results demonstrated the efficacy of the ensemble models in capturing complex relationships within the dataset. ADA-DT obtained an exceptional R2 score of 0.99031, highlighting its outstanding predictive accuracy. Similarly, ADA-MLP and ADA-SVM showed great accuracy, achieving R2 of 0.88272 and 0.96842, respectively. In this study, we uncover valuable insights into the application of ensemble methods and hybridized optimization methods for accurate and robust regression modeling in chemical concentration prediction scenarios applicable for petroleum engineering.

Abstract The 3' untranslated regions (3'UTRs) of messenger RNAs contain many important cis‐regulatory elements that are under functional and evolutionary constraints. It is hypothesized that these constraints are similar to grammars and syntaxes in human languages and can be modeled by advanced natural language techniques such as Transformers, which has been very effective in modeling complex protein sequence and structures. Here 3UTRBERT is described, which implements an attention‐based language model, i.e., Bidirectional Encoder Representations from Transformers (BERT). 3UTRBERT is pre‐trained on aggregated 3'UTR sequences of human mRNAs in a task‐agnostic manner; the pre‐trained model is then fine‐tuned for specific downstream tasks such as identifying RBP binding sites, m6A RNA modification sites, and predicting RNA sub‐cellular localizations. Benchmark results show that 3UTRBERT generally outperformed other contemporary methods in each of these tasks. More importantly, the self‐attention mechanism within 3UTRBERT allows direct visualization of the semantic relationship between sequence elements and effectively identifies regions with important regulatory potential. It is expected that 3UTRBERT model can serve as the foundational tool to analyze various sequence labeling tasks within the 3'UTR fields, thus enhancing the decipherability of post‐transcriptional regulatory mechanisms.

IntroductionHousehold health expenditure plays a crucial role in the daily spending of individuals. Meanwhile, the attention of the public to subjective well-being (SWB) is constantly increasing in China. Household health expenditure could reduce real family income, harming personal SWB. However, the aim of household health expenditure is to improve the physical condition of an individual, and improvements in individual health could enhance personal SWB. Therefore, the effect of household health expenditure on personal SWB is uncertain; hence, it is essential to assess the effects of household health expenditure on the SWB of Chinese residents.MethodsThe Chinese family panel studies database from 2016 to 2020 was applied in this study. A fixed effects model was used to examine the impact of household medical and health protection expenses on personal SWB. Fixed effects instrumental variable regression and propensity score matching were then used to conduct robustness testing.ResultsOn the basis of a fixed effects model, it was found that household medical and health protection expenditure did not improve the happiness and life satisfaction of individuals; rather, household health protection expenditure could significantly reduce personal happiness. Fixed effects instrumental variable regression and propensity score matching analysis supported these results. Household health protection expenditure had a greater negative impact on the happiness and life satisfaction of females compared with males.ConclusionHousehold health expenditure does not improve the SWB of individuals in China; this has certain significance for the formulation of relevant policies.

BackgroundDepression and anxiety have become increasingly prevalent across the globe. The rising need for treatment and the lack of clinicians has resulted in prolonged waiting times for patients to receive their first session. Responding to this gap, digital mental health interventions (DMHIs) have been found effective in treating depression and anxiety and are potentially promising pretreatments for patients who are awaiting face-to-face psychotherapy. Nevertheless, whether digital interventions effectively alleviate symptoms for patients on waiting lists for face-to-face psychotherapy remains unclear. ObjectiveThis review aimed to synthesize the effectiveness of DMHIs for relieving depression and anxiety symptoms of patients on waiting lists for face-to-face therapy. This review also investigated the features, perceived credibility, and usability of DMHIs during waiting times. MethodsIn this systematic review, we searched PubMed, PsycINFO, Cochrane, and Web of Science for research studies investigating the effectiveness of DMHIs in reducing either depression or anxiety symptoms among individuals waiting for face-to-face psychotherapy. The search was conducted in June 2024, and we have included the studies that met the inclusion criteria and were published before June 6, 2024. ResultsOf the 9267 unique records identified, 8 studies met the eligibility criteria and were included in the systematic review. Five studies were randomized controlled trials (RCTs), and 3 studies were not. Among the RCTs, we found that digital interventions reduced depression and anxiety symptoms, but the majority of interventions were not more effective compared to the control groups where participants simply waited or received a self-help book. For the non-RCTs, the interventions also reduced symptoms, but without control groups, the interpretation of the findings is limited. Finally, participants in the included studies perceived the digital interventions to be credible and useful, but high dropout rates raised concerns about treatment adherence. ConclusionsDue to the lack of effective interventions among the reviewed studies, especially among the RCTs, our results suggest that waiting list DMHIs are not more effective compared to simply waiting or using a self-help book. However, more high-quality RCTs with larger sample sizes are warranted in order to draw a more robust conclusion. Additionally, as this review revealed concerns regarding the high dropout rate in digital interventions, future studies could perhaps adopt more personalized and human-centered functions in interventions to increase user engagement, with the potential to increase treatment adherence and effectiveness.

Diabetic wounds are a severe complication of diabetes, characterized by persistent, non-healing ulcers due to disrupted wound-healing mechanisms in a hyperglycemic environment. Key factors in the pathogenesis of these chronic wounds include unresolved inflammation and antioxidant defense imbalances. The cystine/glutamate antiporter SLC7A11 (xCT) is crucial for cystine import, glutathione production, and antioxidant protection, positioning it as a vital regulator of diabetic wound healing. Recent studies underscore the role of SLC7A11 in modulating immune responses and oxidative stress in diabetic wounds. Moreover, SLC7A11 influences critical processes such as insulin secretion and the mTOR signaling pathway, both of which are implicated in delayed wound healing. This review explores the mechanisms regulating SLC7A11 and its impact on immune response, antioxidant defenses, insulin secretion, and mTOR pathways in diabetic wounds. Additionally, we highlight the current advancements in targeting SLC7A11 for treating related diseases and conceptualize its potential applications and value in diabetic wound treatment strategies, along with the challenges encountered in this context.

The title compound, C14H12N2O4, was obtained from 2-acetyl-6-aminonaphthalene through two-step reactions of acetylation and nitration. The molecule comprises the naphthalene ring system consisting of functional systems bearing a acetyl group (C-2), a nitro group (C-5), and an acetylamino group (C-6). In the crystal, the molecules are assembled into two-dimensional sheet-like structures by intermolecular N—H...O and C—H...O hydrogen-bonding interactions. Hirshfeld surface analysis illustrates that the most important contributions to the crystal packing are from O...H/H...O (43.7%), H...H (31.0%), and C...H/H...C (8.5%) contacts.

Abstract Neuroblastoma (NB) is a common childhood tumor with a high incidence worldwide. The regulatory role of RNA N6-methyladenosine (m6A) in gene expression has attracted significant attention, and the impact of methyltransferase-like 14 (METTL14) on tumor progression has been extensively studied in various types of cancer. However, the specific influence of METTL14 on NB remains unexplored. Using data from the Target database, our study revealed significant upregulation of METTL14 expression in high-risk NB patients, with strong correlation with poor prognosis. Furthermore, we identified ETS1 and YY1 as upstream regulators that control the expression of METTL14. In vitro experiments involving the knockdown of METTL14 in NB cells demonstrated significant inhibition of cell proliferation, migration, and invasion. In addition, suppressing METTL14 inhibited NB tumorigenesis in nude mouse models. Through MeRIP-seq and RNA-seq analyses, we further discovered that YWHAH is a downstream target gene of METTL14. Mechanistically, we observed that methylated YWHAH transcripts, particularly those in the 5′ UTR, were specifically recognized by the m6A “reader” protein YTHDF1, leading to the degradation of YWHAH mRNA. Moreover, the downregulation of YWHAH expression activated the PI3K/AKT signaling pathway, promoting NB cell activity. Overall, our study provides valuable insights into the oncogenic effects of METTL14 in NB cells, highlighting its role in inhibiting YWHAH expression through an m6A-YTHDF1-dependent mechanism. These findings also suggest the potential utility of a biomarker panel for prognostic prediction in NB patients.

Abstract In implantable electrophysiological recording systems, the headstage typically comprises neural probes that interface with brain tissue and integrated circuit chips for signal processing. While advancements in MEMS and CMOS technology have significantly improved these components, their interconnection still relies on conventional printed circuit boards and sophisticated adapters. This conventional approach adds considerable weight and volume to the package, especially for high channel count systems. To address this issue, we developed a through-polymer via (TPV) method inspired by the through-silicon via (TSV) technique in advanced three-dimensional packaging. This innovation enables the vertical integration of flexible probes, amplifier chips, and PCBs, realizing a flexible, lightweight, and integrated device (FLID). The total weight of the FLIDis only 25% that of its conventional counterparts relying on adapters, which significantly increased the activity levels of animals wearing the FLIDs to nearly match the levels of control animals without implants. Furthermore, by incorporating a platinum-iridium alloy as the top layer material for electrical contact, the FLID realizes exceptional electrical performance, enabling in vivo measurements of both local field potentials and individual neuron action potentials. These findings showcase the potential of FLIDs in scaling up implantable neural recording systems and mark a significant advancement in the field of neurotechnology.

Abstract There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the Gene-Lifestyle Interactions Working Group within the Cohorts for Heart and Aging Research in Genetic Epidemiology Consortium has been spearheading efforts to investigate G × E in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identify and confirm 5 loci (6 independent signals) interacted with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrate that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated heritability is significant (P

Based on the simulation results of ProCAST software for the filling and solidification process, the formation mechanism of the VIM electrode ingot's pipe and porosities and the influence of the casting process on the formation of electrode shrinkage were studied in detail. The research results indicate that the critical condition for the formation of 200 kg grade C650R heat-resistant alloy is verified to be G/R≤5.0 (K·s)0.5/cm. In addition to the alloy's inherent characteristics, the substantial height to diameter ratio (H/D) of the VIM electrode ingot is the primary factor contributing to the formation of deep pipe and severe porosities. Simply adjusting the casting time or casting speed alone does not significantly improve the solidification quality of the ingot. While the use of a hot top can eliminate pipe, its effectiveness is limited, as the alloy melt at the hot top location has minimal influence on the solidification process in the lower regions of the electrode ingot, thereby failing to effectively reduce the formation of porosities. Properly reducing the casting speed and casting superheat lead to the formation of a V-shaped melt at localized positions during the final stage of solidification. This enhances the ability of the liquid phase for further feeding, ultimately significantly decreasing both the depth of pipe and the porosity rate. The optimal casting process optimization solution for C650R alloy electrode ingot with a size of Φ130 mm × 1240 mm is the casting speed of 60 kg/min and the superheat of 40 °C.

IntroductionProgrammed cell death (PCD) is a fundamental biological process crucial for plant development. Despite recent advancements in our understanding of PCD’s molecular mechanisms, the intricate orchestration of this process within plant cells remains enigmatic. To address this knowledge gap, the present study focuses on Decaisnea insignis, a plant species renowned for its unique fruit anatomy, including laticiferous canals that secrete latex. While extensive anatomical studies have elucidated the structural features of these canals,molecular insights into their developmental regulation, particularly the involvement of PCD, are lacking.MethodsIn this study, we sequenced the single-cell transcriptomes at two developmental stage of Decaisnea insignis fruit using the technology known as 10x Genomics (S1, S2). Using sequencing technology combining full- length RNA sequencing and single-nucleus RNA sequencing (snRNA-seq) in combination with ultrastructural analyses, our study revealed a cellular map of Decaisnea insignis fruit at the single-cell level and identified different cell types.ResultsIn particular, we identified a possible PCD-mediated cluster of Decaisnea insignis fruit lactiferous canals in epidermal cells and clarified the expression patterns of DiRD21A (a hydrolase) and DiLSD1 (a transcription factor), which may be closely related to the development of laticiferous canals in Decaisnea insignis fruits.DiscussionBy integrating high-resolution gene expression profiling with visual insights into cellular transformations, we sought to more precisely characterize the regulatory role of PCD during the developmental formation of lactiferous canals in Decaisnea insignis fruit.

Background: Patients with fractures of the proximal humerus often local complications and failures attributed to osteoporosis. Currently, there is a lack of straight forward screening methods for assessing the extent of local osteoporosis in the proximal humerus. This study utilizes machine learning techniques to establish a diagnostic approach for evaluating local osteoporosis by analyzing the patient's demographic data, bone density, and X-ray ratio of the proximal humerus. Methods: A cohort comprising a total of 102 hospitalized patients admitted during the period spanning from 2021 to 2023 underwent random selection procedures. Resulting in exclusion of 5 patients while enrolling 97 patients for analysis encompassing patient demographics, shoulder joint anteroposterior radiographs, and bone density information. Using the modified Tingart index methodology involving multiple measurements denoted as M1 through M4 obtained from humeral shafts. Within this cohort comprised 76 females (78.4 %) and 21 males (21.6 %), with an average age of 73.0 years (range: 43–98 years). There were 25 cases with normal bone density, 35 with osteopenia, and 37 with osteoporosis. Machine learning techniques were used to randomly divide the 97 cases into training (n = 59) and validation (n = 38) sets with a ratio of 6:4 using stratified random sampling. A decision tree model was built in the training set, and significant diagnostic indicators were selected, with the performance of the decision tree evaluated using the validation set. Multinomial logistic regression methods were used to verify the strength of the relationship between the selected indicators and osteoporosis. Results: The decision tree identified significant diagnostic indicators as the humeral shaft medullary cavity ratio M2/M4, age, and gender. M2/M4 ≥ 1.13 can be used as an important screening criterion; M2/M4 < 1.13 was predicted as local osteoporosis; M2/M4 ≥ 1.13 and age ≥83 years were also predicted as osteoporosis. M2/M4 ≥ 1.13 and age

Introduction: Orthostatic hypotension (OH) is common among the older population. The mechanism hypothesized by OH as a risk factor for cognitive decline and dementia is repeated transient cerebral blood flow deficiency. However, to our knowledge, quantitative evaluation of cardiac output and cerebral blood flow due to acute blood pressure changes resulting from postural changes is rare.Methods: We report a new fluid-structure interaction model to analyze the quantitative relationship of cerebral blood flow during OH episodes. A device was designed to simulate the aging of blood vessels.Results and Discussion: The results showed that OH was associated with decreased transient cerebral blood flow. With the arterial aging, lesions, the reduction in cerebral blood flow is accelerated. These findings suggest that systolic blood pressure regulation is more strongly associated with cerebral blood flow than diastolic blood pressure, and that more severe OH carries a greater risk of dementia. The model containing multiple risk factors could apply to analyze and predict for individual patients. This study could explain the hypothesis that transient cerebral blood flow deficiency in recurrent OH is associated with cognitive decline and dementia.

ObjectivesThis study aimed to elucidate the influences of 1p/19q co-deletion on structural connectivity alterations in patients with dominant hemisphere insular diffuse gliomas.MethodsWe incorporated 32 cases of left insular gliomas and 20 healthy controls for this study. Using diffusion MRI, we applied correlational tractography, differential tractography, and graph theoretical analysis to explore the potential connectivity associated with 1p/19q co-deletion.ResultsThe study revealed that the quantitative anisotropy (QA) of key deep medial fiber tracts, including the anterior thalamic radiation, superior thalamic radiation, fornix, and cingulum, had significant negative associations with 1p/19q co-deletion (FDR = 4.72 × 10–5). These tracts are crucial in maintaining the integrity of brain networks. Differential analysis further supported these findings (FWER-corrected p < 0.05). The 1p/19q non-co-deletion group exhibited significantly higher clustering coefficients (FDR-corrected p < 0.05) and reduced betweenness centrality (FDR-corrected p < 0.05) in regions around the tumor compared to HC group. Graph theoretical analysis indicated that non-co-deletion patients had increased local clustering and decreased betweenness centrality in peritumoral brain regions compared to co-deletion patients and healthy controls (FDR-corrected p < 0.05). Additionally, despite not being significant through correction, patients with 1p/19q co-deletion exhibited lower trends in weighted average clustering coefficient, transitivity, small worldness, and global efficiency, while showing higher tendencies in weighted path length compared to patients without the co-deletion.ConclusionThe findings of this study underline the significant role of 1p/19q co-deletion in altering structural connectivity in insular glioma patients. These alterations in brain networks could have profound implications for the neural functionality in patients with dominant hemisphere insular gliomas.

BackgroundRapid and accurate diagnosis of the causative agents is essential for clinical management of bloodstream infections (BSIs) that might induce sepsis/septic shock. A considerable number of suspected sepsis patients initially enter the health-care system through an emergency department (ED), hence it is vital to establish an early strategy to recognize sepsis and initiate prompt care in ED. This study aimed to evaluate the diagnostic performance and clinical value of droplet digital PCR (ddPCR) assay in suspected sepsis patients in the ED.MethodsThis was a prospective single-centered observational study including patients admitted to the ED from 25 October 2022 to 3 June 2023 with suspected BSIs screened by Modified Shapiro Score (MSS) score. The comparison between ddPCR and blood culture (BC) was performed to evaluate the diagnostic performance of ddPCR for BSIs. Meanwhile, correlative analysis between ddPCR and the inflammatory and prognostic-related biomarkers were conducted to explore the relevance. Further, the health economic evaluation of the ddPCR was analyzed.Results258 samples from 228 patients, with BC and ddPCR performed simultaneously, were included in this study. We found that ddPCR results were positive in 48.13% (103 of 214) of episodes, with identification of 132 pathogens. In contrast, BC only detected 18 positives, 88.89% of which were identified by ddPCR. When considering culture-proven BSIs, ddPCR shows an overall sensitivity of 88.89% and specificity of 55.61%, the optimal diagnostic power for quantifying BSI through ddPCR is achieved with a copy cutoff of 155.5. We further found that ddPCR exhibited a high accuracy especially in liver abscess patients. Among all the identified virus by ddPCR, EBV has a substantially higher positive rate with a link to immunosuppression. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity as well as prognosis. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.ConclusionsThe multiplexed ddPCR delivers precise and quantitative load data on the causal pathogen, offers the ability to monitor the patient’s condition and may serve as early warning of sepsis in time-urgent clinical situations as ED.ImportanceEarly detection and effective administration of antibiotics are essential to improve clinical outcomes for those with life-threatening infection in the emergency department. ddPCR, an emerging tool for rapid and sensitive pathogen identification used as a precise bedside test, has developed to address the current challenges of BSI diagnosis and precise treatment. It characterizes sensitivity, specificity, reproducibility, and absolute quantifications without a standard curve. ddPCR can detect causative pathogens and related resistance genes in patients with suspected BSIs within a span of three hours. In addition, it can identify polymicrobial BSIs and dynamically monitor changes in pathogenic microorganisms in the blood and can be used to evaluate antibiotic efficacy and survival prognosis. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.

This is an article in the field of earth sciences. Xidamingshan polymetallic ore concentration area is critical mineral prospecting district in Guangxi. With the promotion of the large-scale mineral breakthrough work, the Xidamingshan mineral exploration, the Nongtun large-scale Pb-Zn deposit has been newly discovered. However, the understanding of the metallogenic characteristics of the deposit, especially the genesis of the deposit, is still at the superficial stage. Based on detailed field geological investigations and previous work, this paper systematically summarizes the regional metallogenic geological background, mining area and geological characteristics, and analyzes the genesis of the Nongtun lead-zinc deposit to find out the metallogenic mechanism. The study shows the Nongtun Pb-Zn deposit is related-magmatic hydrothermal deposit, the ore-forming fluids originated from magmatic, and later mixed with meteoric water. The fluids extracted Pb and Zn ore-forming elements from the strata during long-distance transport, and combined with S of magmatic fluids to synthesize [HS]-ligand that converged in the fracture zone and transported to the shallow part, thus forming Pb-Zn ore vein. The above research results have established the metallogenic model of the Nongtun Pb-Zn deposit, which provides a good guidance for prospecting prediction and exploration.

Abstract Background Glioblastoma (GBM) is a relatively prevalent primary tumor of the central nervous system in children, characterized by its high malignancy and mortality rates, along with the intricate challenges of achieving complete surgical resection. Recently, an increasing number of studies have focused on the crucial role of super-enhancers (SEs) in the occurrence and development of GBM. This study embarks on the task of evaluating the effectiveness of MZ1, an inhibitor of BRD4 meticulously designed to specifically target SEs, within the intricate framework of GBM. Methods The clinical data of GBM patients was sourced from the Chinese Glioma Genome Atlas (CGGA) and the Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and the gene expression data of tumor cell lines was derived from the Cancer Cell Line Encyclopedia (CCLE). The impact of MZ1 on GBM was assessed through CCK-8, colony formation assays, EdU incorporation analysis, flow cytometry, and xenograft mouse models. The underlying mechanism was investigated through RNA-seq and ChIP-seq analyses. Results In this investigation, we made a noteworthy observation that MZ1 exhibited a substantial reduction in the proliferation of GBM cells by effectively degrading BRD4. Additionally, MZ1 displayed a notable capability in inducing significant cell cycle arrest and apoptosis in GBM cells. These findings were in line with our in vitro outcomes. Notably, MZ1 administration resulted in a remarkable decrease in tumor size within the xenograft model with diminished toxicity. Furthermore, on a mechanistic level, the administration of MZ1 resulted in a significant suppression of pivotal genes closely associated with cell cycle regulation and epithelial-mesenchymal transition (EMT). Interestingly, our analysis of RNA-seq and ChIP-seq data unveiled the discovery of a novel prospective oncogene, SDC1, which assumed a pivotal role in the tumorigenesis and progression of GBM. Conclusion In summary, our findings revealed that MZ1 effectively disrupted the aberrant transcriptional regulation of oncogenes in GBM by degradation of BRD4. This positions MZ1 as a promising candidate in the realm of therapeutic options for GBM treatment.

Abstract Common mental disorders among young people are rising globally. Current university-based interventions are inadequate to address the need for evidence-based interventions. We investigated the effectiveness and implementation of Step-by-Step (SbS), a WHO digital intervention to address depression, among Chinese university students with depressive symptoms. In this paper, we report a type 1 hybrid effectiveness-implementation randomized controlled trial conducted between September 2021 and September 2022. The control condition was enhanced treatment as usual (ETAU, psychoeducation). The primary outcome was improvement in depression symptoms. Secondary outcomes were improvements in psychological well-being, anxiety symptoms, and self-identified psychosocial problems. Effectiveness of the intervention was evaluated using generalized linear mixed models. Implementation outcomes were evaluated by thematic analysis of participant interviews. A total of 371 participants were enrolled to two treatment conditions in a 1:1 ratio. SbS resulted in a greater reduction in depressive symptoms at posttreatment (p = 0.004, Hedges’ g = 0.35), but no significant difference between SbS and ETAU was observed at three-month follow-up (p = 0.179, Hedges’ g = 0.16). The treatment effect was larger among those who adhered to the treatment (Hedges’ gs = 0.59 and 0.30). Subjective well-being also improved for SbS at both time points (Hedges’ gs = 0.31 and 0.30). In addition, SbS resulted in more improvement in anxiety symptoms at posttreatment (p = 0.029, Hedges’ g = 0.26), but not at three-month follow-up (p = 0.265, Hedges’ g = 0.13). The qualitative results demonstrated that the intervention was well-implemented as a self-help mental health service, with minimal support from peer supporters. In conclusion, Step-by-Step, a digital intervention developed by WHO, was effective in reducing depressive symptoms in the short term and improving psychological well-being in a longer term. The sustained effect on depression needs further investigation. Improving uptake and engagement in the program is needed for its scale-up implementation as a university-based mental health service for Chinese young adults. Trial registration: ChiCTR2100050214.

Lunar tidal deformation (LTD), characterized by the vertical (${{{\bm{h}}}_2}$) and horizontal (${{{\bm{l}}}_2}$) displacement Love numbers, is a key to deciphering the interior structure of the Moon. However, the small deformation amplitude of only up to 10 cm makes their measurements very challenging. In this article, we propose a novel method named Earth-based repeat-pass SAR interferometry (EBRP-InSAR) to measure the LTD and displacement Love numbers. We analyzed the potential and performance of EBRP-InSAR in detail based on the LTD model and existing planetary radar capabilities. The error budget and simulation results show that the relative measurement accuracy of LTD could be better than 2 mm. Furthermore, compared with lunar laser ranging (LLR) and lunar orbiter laser altimeter (LOLA), the two-pass EBRP-InSAR cannot only directly estimate ${{{\bm{h}}}_2}$ but also ${{{\bm{l}}}_2}$ with accuracies better than ${{\text{10}}^{ - 3}}$ and${{\text{10}}^{ - 4}}$, respectively, which is comparable to that of LLR and LOLA methods. In addition, through long-term time-series observations, it will be possible to assess the spatial inhomogeneity of LTD response to the forcing potential in the near side with time-series EBRP-InSAR. After spatial smoothing, a space variation as small as on the order of ${{\text{10}}^{ - 4}}$ and ${{\text{10}}^{ - 5}}$ in ${{{\bm{h}}}_2}$ and ${{{\bm{l}}}_2}$, respectively, can be distinguished on the lunar near side. As another measurement technology independent of LLR and LOLA, the EBRP-InSAR is expected to explain the difference between the observations from LLR and LOLA and the modeled lunar interior structure, and first estimate the lunar horizontal displacement Love number.

Abstract Large-scale brain activity mapping is important for understanding the neural basis of behaviour. Electrocorticograms (ECoGs) have high spatiotemporal resolution, bandwidth, and signal quality. However, the invasiveness and surgical risks of electrode array implantation limit its application scope. We developed an ultrathin, flexible shape-changing electrode array (SCEA) for large-scale ECoG mapping with minimal invasiveness. SCEAs were inserted into cortical surfaces in compressed states through small openings in the skull or dura and fully expanded to cover large cortical areas. MRI and histological studies on rats proved the minimal invasiveness of the implantation process and the high chronic biocompatibility of the SCEAs. High-quality micro-ECoG activities mapped with SCEAs from male rodent brains during seizures and canine brains during the emergence period revealed the spatiotemporal organization of different brain states with resolution and bandwidth that cannot be achieved using existing noninvasive techniques. The biocompatibility and ability to map large-scale physiological and pathological cortical activities with high spatiotemporal resolution, bandwidth, and signal quality in a minimally invasive manner offer SCEAs as a superior tool for applications ranging from fundamental brain research to brain-machine interfaces.

The increasing integration of distributed household photovoltaics (PVs) and electric vehicles (EVs) may further aggravate voltage violations and unbalance of low-voltage distribution networks (LVDNs). DC distribution networks can increase the accommodation of PVs and EVs and mitigate mutilple power quality problems by the flexible power regulation capability of voltage source converters. This paper proposes schemes to establish hybrid AC/DC LVDNs considering the conversion of the existing three-phase four-wire low-voltage AC systems to DC operation. The characteristics and DC conversion constraints of typical LVDNs are analyzed. In addition, converter configurations for typical LVDNs are proposed based on the three-phase four-wire characteristics and quantitative analysis of various DC configurations. Moreover, an optimal planning method of hybrid AC/DC LVDNs is proposed, which is modeled as a bi-level programming model considering the annual investments and three-phase unbalance. Simulations are conducted to verify the effectiveness of the proposed optimal planning method. Simulation results show that the proposed optimal planning method can increase the integration of PVs while simultaneously reducing issues related to voltage violation and unbalance.

In this study, a MOF-199/Ag@Au SERS sensing structure was successfully synthesized by combining metal–organic frameworks (MOFs) with surface-enhanced Raman scattering (SERS) technology for the efficient detection of dopamine (DA), a biomarker for neurological diseases, in serum. Using electrochemical methods, a copper-based MOF (MOF-199) was synthesized in situ on copper substrates and further deposited with silver nanoparticles (AgNPs). Subsequently, gold nanoshells were encapsulated around these silver cores by in situ chemical deposition. This preparation process is simple, controllable, and inexpensive. Furthermore, a novel Azo reaction-based DA SERS method was proposed to detect 1 pM DA, which represents an improvement in sensitivity by two orders of magnitude compared to previous unlabeled SERS detection methods and by four orders of magnitude compared to another SERS approach proposed in this work. There was an excellent linear relationship (R2 = 0.976) between the SERS signal at 1140 cm−1 and the DA concentration (0.001 M~1 pM). The results indicate that the MOF-199/Ag@Au sensor structure can successfully achieve both the qualitative and quantitative detection of DA in serum, thus providing a robust technical basis for the application of SERS technology in the field of clinical neurological disease screening.

In order to accurately estimate the distribution of Trachinotus ovatus in marine cages, a novel method was developed using omnidirectional scanning sonar and deep-learning techniques. This method involved differentiating water layers and clustering data layer by layer to achieve precise location estimation. The approach comprised two main components: fish identification and fish clustering. Firstly, omnidirectional scanning sonar was employed to perform spiral detection within marine cages, capturing fish image data. These images were then labeled to construct a training dataset for an enhanced CS-YOLOv8s model. After training, the CS-YOLOv8s model was used to identify and locate fish within the images. Secondly, the cages were divided into water layers with depth intervals of 40 cm. The identification coordinate data for each water layer were clustered using the DBSCAN method to generate location coordinates for the fish in each layer. Finally, the coordinate data from all water layers were consolidated to determine the overall distribution of fish within the cage. This method was shown, through multiple experimental results, to effectively estimate the distribution of Trachinotus ovatus in marine cages, closely matching the distributions detected manually.

ObjectiveTo investigate the causal contributions of Sodium-glucose cotransporter 2 (SGLT2) inhibition on Heart Failure (HF) and identify the circulating proteins that mediate SGLT2 inhibition's effects on HF.MethodsApplying a two-sample, two-step Mendelian Randomization (MR) analysis, we aimed to estimate: (1) the causal impact of SGLT2 inhibition on HF; (2) the causal correlation of SGLT2 inhibition on 4,907 circulating proteins; (3) the causal association of SGLT2 inhibition-driven plasma proteins on HF. Genetic variants linked to SGLT2 inhibition derived from the previous studies. The 4,907 circulating proteins were derived from the deCODE study. Genetic links to HF were obtained through the Heart Failure Molecular Epidemiology for Therapeutic Targets (HERMES) consortium.ResultsSGLT2 inhibition demonstrated a lower risk of HF (odds ratio [OR] = 0.44, 95% CI [0.26, 0.76], P = 0.003). Among 4,907 circulating proteins, we identified leucine rich repeat transmembrane protein 2 (LRRTM2), which was related to both SGLT2 inhibition and HF. Mediation analysis revealed that the impact of SGLT2 inhibition on HF operates indirectly through LRRTM2 [β = −0.20, 95% CI (−0.39, −0.06), P = 0.02] with a mediation proportion of 24.6%. Colocalization analysis provided support for the connections between LRRTM2 and HF.ConclusionThe study indicated a causative link between SGLT2 inhibition and HF, with plasma LRRTM2 potentially serving as a mediator.

Abstract Background Oral squamous cell carcinoma (SCC) is associated with oral microbial dysbiosis. In this unique study, we compared pre- to post-treatment salivary microbiome in patients with SCC by 16S rRNA gene sequencing and examined how microbiome changes correlated with the expression of an anti-microbial protein. Results Treatment of SCC was associated with a reduction in overall bacterial richness and diversity. There were significant changes in the microbial community structure, including a decrease in the abundance of Porphyromonaceae and Prevotellaceae and an increase in Lactobacillaceae. There were also significant changes in the microbial community structure before and after treatment with chemoradiotherapy, but not with surgery alone. In patients treated with chemoradiotherapy alone, several bacterial populations were differentially abundant between responders and non-responders before and after therapy. Microbiome changes were associated with a change in the expression of DMBT1, an anti-microbial protein in human saliva. Additionally, we found that salivary DMBT1, which increases after treatment, could serve as a post-treatment salivary biomarker that links to microbial changes. Specifically, post-treatment increases in human salivary DMBT1 correlated with increased abundance of Gemella spp., Pasteurellaceae spp., Lactobacillus spp., and Oribacterium spp. This is the first longitudinal study to investigate treatment-associated changes (chemoradiotherapy and surgery) in the oral microbiome in patients with SCC along with changes in expression of an anti-microbial protein in saliva. Conclusions The composition of the oral microbiota may predict treatment responses; salivary DMBT1 may have a role in modulating the oral microbiome in patients with SCC. Graphical Abstract After completion of treatment, 6 months after diagnosis, patients had a less diverse and less rich oral microbiome. Leptotrichia was a highly prevalent bacteria genus associated with disease. Expression of DMBT1 was higher after treatment and associated with microbiome changes, the most prominent genus being Gemella Video Abstract

Two types of triazine-based covalent organic polymers were successfully constructed through a one-pot and catalyst-free polycondensation approach. More specifically, two kinds of aromatic aldehyde containing different hydroxyl content named terephthalaldehyde and 2, 4, 6-trihydroxyisophthalaldehyde were selected and the derived polymers (denoted as POPs-1 and POPs-2) with large Brunauer-Emmett-Teller (BET) surface areas (> 360 m2/g), high total pore volume (> 0.47 m3/g), good stability and different heteroatoms (such as N and O) contents were prepared. Interestingly, POPs-1 featuring high BET surface area and N content (up to 34.83 %) exhibited excellent iodine vapor uptake of 441 wt% at 348 K/1.0 bar, POPs-2 with high O content (up to 25.83 %) showed better CO2 adsorption capacity (91.8 mg/g) at 273 K/1.0 bar and higher isosteric heat of adsorption (up to 85.0 kJ/mol) than that of POPs-1. This value of the isosteric heat is the highest value reported to date for porous organic polymers. This excellent adsorption performance was resulted either from the large BET surface area or high heteroatoms (N and O) contents of the porous adsorbents. The study offer an alternative route to develop high-performance porous adsorbents to capture carbon dioxide and iodine.

Large-depth and multiscale gradient microstructure in dual-phase Al0.6CoCrFeNi high entropy alloy (HEA) were fabricated by explosion hardening (EH) technique. The gradient microstructure evolution was investigated in detail. The microhardness distribution and tensile properties near EH affected surface were also determined. The formation and strengthening mechanisms of gradient microstructure after EH treatment were subsequently analyzed. Experimental results showed that the multiscale gradient microstructure in terms of grain size, phase morphology, dislocation structure, texture was induced in dual-phase (BCC + FCC) HEA by EH technique. The closer to EH affected surface, the finer grain size, higher dislocation density and stronger texture intensity. The deformation and break of spinodal decomposition and formation of new grain boundaries by dislocation structure contributed to grain refinement and transition of equiaxed grains to dendritic grains from lower area to EH affected surface. After EH treatment, the microhardness generally increased with a maximum increase of ∼67% within 5 mm from EH affected surface, the tensile yield stress increased from 320 MPa to maximum of 700 MPa. The strengthening mechanism is different at various depth positions: near EH affected surface, the main strengthening mechanism is high-density dislocations, stacking faults and grain refinement; in areas relatively far from EH affected surface, only dislocation structure contributed to the strengthening of mechanical properties.

Abstract Coal burst is a serious hazard in deep coal mining. To investigate the coal burst proneness evolution during multiple mining disturbances (MMD), this paper implemented a range of uniaxial cyclic loading–unloading tests coupled with acoustic emission (AE) measurement to simulate the loading–unloading effects of the MMD. The maximum load was used to simulate the highest load that the coal has endured in history, the loading–unloading rate was used to simulate the mining speed, and the loading–unloading cycles were used to simulate the number of mining disturbances. Finally, the burst proneness indexes of the damaged coal sample are measured and compared with the origin coal sample. Analysis on the experiment results suggest that, the burst proneness increases when the maximum load is 30% of the uniaxial compressive strength (UCS), interestingly, when the low loading–unloading rate is applied, 50% of the UCS enlarge the burst proneness as well. However, it decreases when the maximum load is 70% of the UCS. Sensitivity analysis indicates that the maximum load, loading–unloading rate, and loading–unloading cycles exhibit decreasing influence sensitivity to the elastic modulus, as well as to the UCS and duration of dynamic fracture. Similarly, the influence sensitivity of maximum load, loading–unloading cycles, and loading–unloading rate to the elastic strain energy index decreases, as well as to the bursting energy index. To ensure the safety of coal mining, it is crucial to avoid the disturbances that would put the coal under low loading and low loading rate.

The summer Asian westerly jet (AWJ)’s shifting in latitudes is one important characteristic of its variability and has great impact on the East Asian summer climate. Based on the observed and reanalyzed datasets from the Hadley Center Sea Ice and Sea Surface Temperature dataset (HadISST), the Japanese 55-year reanalysis (JRA-55), and the fifth generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5), this study investigates the relationship between the spring tripole North Atlantic SST (TNAT) anomalies and the summer meridional shift of the AWJ (MSJ) for the period of 1958–2020. Through the method of correlation analysis and regression analysis, we show that the ‘+ - +’ TNAT anomalies in spring could induce a northward shift of the AWJ in the following summer. However, such a climatic effect of the spring TNAT anomalies on the MSJ is unstable, exhibiting an evident interdecadal strengthening since the early 1990s. Further analysis reveals that this is related to a strengthened intensity of the spring TNAT anomalies in the most recent three decades. Compared to the early epoch (1958–1993), the stronger spring TNAT anomalies in the post epoch (1994–2020) could cause a stronger pan-tropical climate response until the following summer through a series of ocean–atmosphere interactions. Through Gill responses, the resultant more prominent cooling in the central Pacific in response to the ‘+ - +’ TNAT anomalies induces a pan-tropical cooling in the upper troposphere, which weakens the poleward gradient of the tropospheric temperature over subtropical Asia. As a result, the AWJ shifts northward via a thermal wind effect. By contrast, in the early epoch, the spring TNAT anomalies are relatively weaker, inducing weaker pan-tropical ocean–atmosphere interactions and thus less change in the meridional shit of the summer AWJ. Our results highlight a strengthened lagged effect of the spring TNAT anomalies on the following summer MSJ and have important implications for the seasonal climate predictability over Asia.

Timely and accurate detection of viruses is crucial for infection diagnosis and treatment. However, it remains a challenge to develop a portable device that meets the requirement of being portable, powerless, user-friendly, reusable, and low-cost. This work reports a compact ∅30 × 48 mm portable powerless isothermal amplification detection device (material cost ∼$1 USD) relying on LAMP (Loop-Mediated Isothermal Amplification). We have proposed chromatographic-strip-based microporous permeation technology which can precisely control the water flow rate to regulate the exothermic reaction. This powerless heating combined with phase-change materials can maintain a constant temperature between 50 and 70 °C for a duration of up to 49.8 min. Compared with the conventional methods, it avoids the use of an additional insulation layer for heat preservation, greatly reducing the size and cost. We have also deployed a color card and a corresponding algorithm to facilitate color recognition, data analysis, and storage using a mobile phone. The experimental results demonstrate that our device exhibits the same limit of detection (LOD) as the ProFlex PCR for SARS-CoV-2 pseudovirus samples, with that for both being 103 copies/μL, verifying its effectiveness and reliability. This work offers a timely, low-cost, and easy way for respiratory infectious disease detection, which could provide support in curbing virus transmission and protecting the health of humans and animals, especially in remote mountainous areas without access to electricity or trained professionals.

The ionospheric effects in repeat-pass SAR interferometry (InSAR) have become a rising concern with the increasing interest in low-frequency SAR. The ionosphere will introduce serious phase errors in the interferogram, which should be properly corrected. In this paper, the influence of the wavenumber shift on the Range Split-Spectrum (RSS) method is analyzed quantitatively. It is shown that the split-spectrum processing deteriorates the coherence of the sub-band interferogram and then greatly reduces the estimation accuracy. The RSS method combined with common band filtering (CBF) can improve the coherence of sub-band interferograms and estimation accuracy, but the estimation is biased due to the RSS model mismatch. To address the problem, a modified truncated singular value decomposition (MTSVD) based multi-sub-band RSS method is proposed in this paper. The proposed method divides the range common spectrum into multiple sub-bands to jointly estimate the ionospheric phase. The performance of the proposed method is analyzed and validated based on simulation experiments. The results show that the proposed method has stronger robustness and higher accuracy.

Abstract The shape and internal structure of an atomic nucleus can change significantly with increasing excitation energy, angular momentum, or isospin asymmetry. As an example of this structural evolution, linear-chain configurations in carbon or heavier isotopes have been predicted for decades. Recent studies have found non-stability of this structure in 12C while evidenced its appearance in 16C. It is then necessary to investigate the linear-chain molecular structures in 14C to clarify the exact location on the nuclear chart where this structure begins to emerge, and thus to benchmark theoretical models. Here we show a cluster-decay experiment for 14C with all final particles coincidentally detected, allowing a high Q-value resolution, and thus a clear decay-path selection. Unambiguous spin-parity analyses are conducted, strongly evidencing the emergence of the π-bond linear-chain molecular rotational band in 14C. The present results encourage further studies on even longer chain configurations in heavier neutron-rich nuclei.

Abstract Background Cerebral edema is an extremely common secondary disease in post-stroke. Point-of-care testing for cerebral edema types has important clinical significance for the precise management to prevent poor prognosis. Nevertheless, there has not been a fully accepted bedside testing method for that. Methods A symmetric cancellation near-field coupling phase shift (NFCPS) monitoring system is established based on the symmetry of the left and right hemispheres and the fact that unilateral lesions do not affect healthy hemispheres. For exploring the feasibility of this system to reflect the occurrence and development of cerebral edema, 13 rabbits divided into experimental group (n = 8) and control group (n = 5) were performed 24-h NFCPS continuous monitoring experiments. After time difference offset and feature band averaging processing, the changing trend of NFCPS at the stages dominated by cytotoxic edema (CE) and vasogenic edema (VE), respectively, was analyzed. Furthermore, the features under the different time windows were extracted. Then, a discriminative model of cerebral edema types based on support vector machines (SVM) was established and performance of multiple feature combinations was compared. Results The NFCPS monitoring outcomes of experimental group endured focal ischemia modeling by thrombin injection show a trend of first decreasing and then increasing, reaching the lowest value of − 35.05° at the 6th hour. Those of control group do not display obvious upward or downward trend and only fluctuate around the initial value with an average change of − 0.12°. Furthermore, four features under the 1-h and 2-h time windows were extracted. Based on the discriminative model of cerebral edema types, the classification accuracy of 1-h window is higher than 90% and the specificity is close to 1, which is almost the same as the performance of the 2-h window. Conclusion This study proves the feasibility of NFCPS technology combined with SVM to distinguish cerebral edema types in a short time, which is promised to become a new solution for immediate and precise management of dehydration therapy after ischemic stroke.

In the late in-vessel phase of a nuclear reactor severe accident, the internal heat transfer and crust evolution during the debris bed melting process have important effects on the thermal load distribution along the vessel wall, and further affect the reactor pressure vessel (RPV) failure mode and the state of melt during leakage. This study coupled the phase change model and large eddy simulation to investigate the variations of the temperature, melt liquid fraction, crust and heat flux distributions during the debris bed melting process in the hypothetical severe accident of HPR1000. The results indicated that the heat flow towards the vessel wall and upper surface were similar at the beginning stage of debris melting, but the upward heat flow increased significantly as the development of the molten pool. The maximum heat flux towards the vessel wall reached 0.4 MW/m2. The thickness of lower crust decreased as the debris melting. It was much thicker at the bottom region with the azimuthal angle below 20° and decreased rapidly at the azimuthal angle around 20–50°. The maximum and minimum thicknesses were 2 and 90 mm, respectively. By contrast, the distribution of upper crust was uniform and reached stable state much earlier than the lower crust, with the thickness of about 10 mm. Moreover, the sensitivity analysis of initial condition indicated that as the decrease of time interval from reactor scram to debris bed dried-out, the maximum debris temperature and melt fraction became larger, the lower crust thickness became thinner, but the upper crust had no significant change. The sensitivity analysis of in-vessel retention (IVR) strategies indicated that the passive and active external reactor vessel cooling (ERVC) had little effect on the internal heat transfer and crust evolution. In the case not considering the internal reactor vessel cooling (IRVC), the upper crust was not obvious.

Abstract Chiral monodentate biaryl phosphines (MOPs) have attracted intense attention as chiral ligands over the past decades. However, the creation of structurally diverse chiral MOPs with both P- and axial chirality is still in high demand but challenging. Here, we show a distinct strategy for diversity-oriented synthesis of structurally diverse MOPs containing both P- and axial chirality enabled by enantioselective C-P bond cleavage. The key chiral PdII intermediates, generated through the stereoselective oxidative addition of C-P bond, could be trapped by alkynes, R3Si-Bpin, diboron esters or reduced by H2O/B2pin2, leading to enantioenriched structurally diverse MOPs in excellent diastereo- and enantioselectivities. Based on the outstanding properties of the parent scaffolds, the P- and axially chiral monodentate biaryl phosphines serve as excellent catalysts in asymmetric [3 + 2] annulation of MBH carbonate affording the chiral functionalized bicyclic imide.

Abstract Background Timely discharge to post-acute care (PAC) settings, such as skilled nursing facilities, requires early identification of eligible patients. We sought to develop and internally validate a model which predicts a patient’s likelihood of requiring PAC based on information obtained in the first 24 h of hospitalization. Methods This was a retrospective observational cohort study. We collected clinical data and commonly used nursing assessments from the electronic health record (EHR) for all adult inpatient admissions at our academic tertiary care center from September 1, 2017 to August 1, 2018. We performed a multivariable logistic regression to develop the model from the derivation cohort of the available records. We then evaluated the capability of the model to predict discharge destination on an internal validation cohort. Results Age (adjusted odds ratio [AOR], 1.04 [per year]; 95% Confidence Interval [CI], 1.03 to 1.04), admission to the intensive care unit (AOR, 1.51; 95% CI, 1.27 to 1.79), admission from the emergency department (AOR, 1.53; 95% CI, 1.31 to 1.78), more home medication prescriptions (AOR, 1.06 [per medication count increase]; 95% CI 1.05 to 1.07), and higher Morse fall risk scores at admission (AOR, 1.03 [per unit increase]; 95% CI 1.02 to 1.03) were independently associated with higher likelihood of being discharged to PAC facility. The c-statistic of the model derived from the primary analysis was 0.875, and the model predicted the correct discharge destination in 81.2% of the validation cases. Conclusions A model that utilizes baseline clinical factors and risk assessments has excellent model performance in predicting discharge to a PAC facility.