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Adrenal vein sampling is required for the staging diagnosis of primary aldosteronism, and the frames in which the adrenal veins are presented are called key frames. Currently, the selection of key frames relies on the doctor's visual judgement which is time-consuming and laborious. This study proposes a key frame recognition algorithm based on deep learning. Firstly, wavelet denoising and multi-scale vessel-enhanced filtering are used to preserve the morphological features of the adrenal veins. Furthermore, by incorporating the self-attention mechanism, an improved recognition model called ResNet50-SA is obtained. Compared with commonly used transfer learning, the new model achieves 97.11% in accuracy, precision, recall, F1, and AUC, which is superior to other models and can help clinicians quickly identify key frames in adrenal veins.

Abstract Nucleotide second messengers are highly versatile signaling molecules that regulate a variety of key biological processes in bacteria. The best‐studied examples are cyclic AMP (cAMP) and bis‐(3′–5′)‐cyclic dimeric guanosine monophosphate (c‐di‐GMP), which both act as global regulators. Global regulatory frameworks of c‐di‐GMP and cAMP in bacteria show several parallels but also significant variances. In this review, we illustrate the global regulatory models of the two nucleotide second messengers, compare the different regulatory frameworks between c‐di‐GMP and cAMP, and discuss the mechanisms and physiological significance of cross‐regulation between c‐di‐GMP and cAMP. c‐di‐GMP responds to numerous signals dependent on a great number of metabolic enzymes, and it regulates various signal transduction pathways through its huge number of effectors with varying activities. In contrast, due to the limited quantity, the cAMP metabolic enzymes and its major effector are regulated at different levels by diverse signals. cAMP performs its global regulatory function primarily by controlling the transcription of a large number of genes via cAMP receptor protein (CRP) in most bacteria. This review can help us understand how bacteria use the two typical nucleotide second messengers to effectively coordinate and integrate various physiological processes, providing theoretical guidelines for future research.

Abstract α-Synuclein forms amyloid fibrils that are critical in the progression of Parkinson’s disease and serves as the pathological hallmark of this condition. Different posttranslational modifications have been identified at multiple sites of α-synuclein, influencing its conformation, aggregation and function. Here, we investigate how disease-related phosphorylation and O-GlcNAcylation at the same α-synuclein site (S87) affect fibril structure and neuropathology. Using semi-synthesis, we obtained homogenous α-synuclein monomer with site-specific phosphorylation (pS87) and O-GlcNAcylation (gS87) at S87, respectively. Cryo-EM revealed that pS87 and gS87 α-synuclein form two distinct fibril structures. The GlcNAc situated at S87 establishes interactions with K80 and E61, inducing a unique iron-like fold with the GlcNAc molecule on the iron handle. Phosphorylation at the same site prevents a lengthy C-terminal region including residues 73 to 140 from incorporating into the fibril core due to electrostatic repulsion. Instead, the N-terminal half of the fibril (1–72) takes on an arch-like fibril structure. We further show that both pS87 and gS87 α-synuclein fibrils display reduced neurotoxicity and propagation activity compared with unmodified α-synuclein fibrils. Our findings demonstrate that different posttranslational modifications at the same site can produce distinct fibril structures, which emphasizes link between posttranslational modifications and amyloid fibril formation and pathology.

Abstract Background This study seeks to investigate the impacts of Lactobacillus reuteri (L. reuteri) on hepatic ischemia-reperfusion (I/R) injury and uncover the mechanisms involved. Methods Mice in the I/R groups were orally administered low and high doses of L.reuteri (L.reuteri-low and L. reuteri-hi; 1 × 1010 CFU/d and 1 × 1011 CFU/d), for 4 weeks prior to surgery. Following this, mice in the model group were treated with an Nrf2 inhibitor (ML-385), palmitoylcarnitine, or a combination of both. Results After treatment with L. reuteri, mice exhibited reduced levels of serum aminotransferase (ALT), aspartate aminotransferase (AST), and myeloperoxidase (MPO) activity, as well as a lower Suzuki score and apoptosis rate. L. reuteri effectively reversed the I/R-induced decrease in Bcl2 expression, and the significant increases in the levels of Bax, cleaved-Caspase3, p-p65/p65, p-IκB/IκB, p-p38/p38, p-JNK/JNK, and p-ERK/ERK. Furthermore, the administration of L. reuteri markedly reduced the inflammatory response and oxidative stress triggered by I/R. This treatment also facilitated the activation of the Nrf2/HO-1 pathway. L. reuteri effectively counteracted the decrease in levels of beneficial gut microbiota species (such as Blautia, Lachnospiraceae NK4A136, and Muribaculum) and metabolites (including palmitoylcarnitine) induced by I/R. Likewise, the introduction of exogenous palmitoylcarnitine demonstrated a beneficial impact in mitigating hepatic injury induced by I/R. However, when ML-385 was administered prior to palmitoylcarnitine treatment, the previously observed effects were reversed. Conclusion L. reuteri exerts protective effects against I/R-induced hepatic injury, and its mechanism may be related to the promotion of probiotic enrichment, differential metabolite homeostasis, and the Nrf2/HO-1 pathway, laying the foundation for future clinical applications.

Abstract The burgeoning comprehension of protein phase separation (PS) has ushered in a wealth of bioinformatics tools for the prediction of phase-separating proteins (PSPs). These tools often skew towards PSPs with a high content of intrinsically disordered regions (IDRs), thus frequently undervaluing potential PSPs without IDRs. Nonetheless, PS is not only steered by IDRs but also by the structured modular domains and interactions that aren’t necessarily reflected in amino acid sequences. In this work, we introduce PSPire, a machine learning predictor that incorporates both residue-level and structure-level features for the precise prediction of PSPs. Compared to current PSP predictors, PSPire shows a notable improvement in identifying PSPs without IDRs, which underscores the crucial role of non-IDR, structure-based characteristics in multivalent interactions throughout the PS process. Additionally, our biological validation experiments substantiate the predictive capacity of PSPire, with 9 out of 11 chosen candidate PSPs confirmed to form condensates within cells.

Abstract Background Systemic lupus erythematosus (SLE) is a rare autoimmune disorder characterized by an unpredictable course of flares and remission with diverse manifestations. Lupus nephritis, one of the major disease manifestations of SLE for organ damage and mortality, is a key component of lupus classification criteria. Accurately identifying lupus nephritis in electronic health records (EHRs) would therefore benefit large cohort observational studies and clinical trials where characterization of the patient population is critical for recruitment, study design, and analysis. Lupus nephritis can be recognized through procedure codes and structured data, such as laboratory tests. However, other critical information documenting lupus nephritis, such as histologic reports from kidney biopsies and prior medical history narratives, require sophisticated text processing to mine information from pathology reports and clinical notes. In this study, we developed algorithms to identify lupus nephritis with and without natural language processing (NLP) using EHR data from the Northwestern Medicine Enterprise Data Warehouse (NMEDW). Methods We developed five algorithms: a rule-based algorithm using only structured data (baseline algorithm) and four algorithms using different NLP models. The first NLP model applied simple regular expression for keywords search combined with structured data. The other three NLP models were based on regularized logistic regression and used different sets of features including positive mention of concept unique identifiers (CUIs), number of appearances of CUIs, and a mixture of three components (i.e. a curated list of CUIs, regular expression concepts, structured data) respectively. The baseline algorithm and the best performing NLP algorithm were externally validated on a dataset from Vanderbilt University Medical Center (VUMC). Results Our best performing NLP model incorporated features from both structured data, regular expression concepts, and mapped concept unique identifiers (CUIs) and showed improved F measure in both the NMEDW (0.41 vs 0.79) and VUMC (0.52 vs 0.93) datasets compared to the baseline lupus nephritis algorithm. Conclusion Our NLP MetaMap mixed model improved the F-measure greatly compared to the structured data only algorithm in both internal and external validation datasets. The NLP algorithms can serve as powerful tools to accurately identify lupus nephritis phenotype in EHR for clinical research and better targeted therapies.

Abstract Chronic stress is the primary environmental risk factor for major depressive disorder (MDD), and there is compelling evidence that neuroinflammation is the major pathomechanism linking chronic stress to MDD. Mitogen-activated protein kinase (MAPK) phosphatase-1 (MKP-1) is a negative regulator of MAPK signaling pathways involved in cellular stress responses, survival, and neuroinflammation. We examined the possible contributions of MKP-1 to stress-induced MDD by comparing depression-like behaviors (anhedonia, motor retardation, behavioral despair), neuroinflammatory marker expression, and MAPK signaling pathways among rats exposed to chronic unpredictable mild stress (CUMS), overexpressing MKP-1 in the hippocampus, and CUMS-exposed rats underexpressing MKP-1 in the hippocampus. Rats exposed to CUMS exhibited MKP-1 overexpression, greater numbers of activated microglia, and enhanced expressions of neuroinflammatory markers (interleukin [IL]-6, [IL]-1β, tumor necrosis factor [TNF]-ɑ, and decreased phosphorylation levels of ERK and p38 in the hippocampus as well as anhedonia in the sucrose preference test, motor retardation in the open field, and greater immobility (despair) in the forced swimming tests. These signs of neuroinflammation and depression-like behaviors and phosphorylation levels of ERK and p38 were also observed in rats overexpressing MKP-1 without CUMS exposure, while CUMS-induced neuroinflammation, microglial activation, phosphorylation levels of ERK and p38, and depression-like behaviors were significantly reversed by MKP-1 knockdown. Moreover, MKP-1 knockdown promoted the activation of the MAPK isoform ERK, implying that the antidepressant-like effects of MKP-1 knockdown may be mediated by the ERK pathway disinhibition. These findings suggested that hippocampal MKP-1 is an essential regulator of stress-induced neuroinflammation and a promising target for antidepressant development.

This study delves into the intricate corrosion behavior of ferrous and non-ferrous alloys in the challenging Antarctic marine atmosphere. Despite the harsh conditions and exceptionally low anthropogenic emissions in Antarctica, materials are still susceptible to severe corrosion. The investigation focuses on two materials: Q235 carbon steel and T2 copper. Both display distinct corrosion cases between their skyward and groundward sides due to the abrasive impact of persistent strong winds carrying ice particles and grit. Electrochemical reactions at the anode and cathode drive surface corrosion processes, involving Cl− and SO42−, ultimately leading to the formation of various corrosion products. The study highlights the role of sulfur-containing aerosols, Methanesulfonic acid (MSA) and non-sea-salt sulfate (nss-SO42-) in corrosion processes, as well as the interaction between Cl− and copper in forming corrosion products. The findings emphasize the complex interplay of environmental factors like wind, ice cover, and aerosols with materials, leading to diverse corrosion products and surface transformations. Further research is crucial to gain a comprehensive understanding of corrosion challenges in extreme environments like Antarctica and to develop effective mitigation strategies.

ObjectiveThis study focuses on the deposition characteristics of oil mist on metal and fabric surfaces in ship cabin. MethodsOil mist is released in an experimental cabin and allowed to deposit on the target surfaces. The mass difference before and after deposition on the surfaces is weighed to determine the deposition mass, and the oil mist deposition characteristics of surfaces with different orientations and materials are compared. The deposition on the horizontal downward surface is reasonably assumed to be gas phase deposition. Its contribution is then estimated and the particle phase deposition velocity is calculated. ResultsThe deposition mass on the horizontal upward surface of the metal is 3.98 times and 4.66 times greater than that on the vertical surface and horizontal downward surface. For fabric surfaces, the deposition mass on the horizontal upward surface is 1.08 times and 1.20 times greater than that of the vertical surface and horizontal downward surface. For material comparison, the deposition mass on the horizontal upward, vertical and horizontal downward surfaces of the fabric is 49.1 times, 169.8 times and 155.5 times greater than that of the metal surface facing in the same direction respectively. Estimates show that the contribution of phase deposition to the metal horizontal and vertical surfaces are 21.5% and 79.2% respectively. The contribution of phase deposition to the fabric surfaces is about 90%. ConclusionsThe oil mist deposition on fabric surfaces is much stronger than that on metal surfaces. The deposition on the metal horizontal upward surface is much greater than that on the vertical surface and horizontal downward surface. The deposition differences between the fabric surfaces in the three orientations are not significant. Regardless of orientation or material, gas phase deposition cannot be ignored as it plays a dominant role in ship cabin environments.

Abstract Family processes such as maternal parenting and family screen exposure are significantly related to children’s gains in behavioral self-regulation, but the potential mechanism of these relations remains unknown. In this study, we investigated how maternal depression is associated with children’s behavioral self-regulation through the mediating role of maternal supportive parenting and children’s family screen time. A total sample of 657 Chinese children and their mothers was recruited. Results from structural equation models indicated that supportive parenting and screen time partially mediated the effect of maternal depression on children’s behavioral self-regulation by the sequential, after controlling for child demographic variables. Furthermore, supportive parenting played a partially mediating role in associations between maternal depression and children’s self-regulation. The findings provide insights into parenting practices for early childhood development in the Chinese family environment.

Abstract Collapse is a major engineering hazard in open-cut foundation pit construction, and risk assessment is crucial for considerably reducing engineering hazards. This study aims to address the ambiguity problem of qualitative index quantification and the failure of high-conflict evidence fusion in risk assessment. Thus, a fast-converging and high-reliability multi-source data fusion method based on the cloud model (CM) and improved Dempster–Shafer evidence theory is proposed. The method can achieve an accurate assessment of subway pit collapse risks. First, the CM is introduced to quantify the qualitative metrics. Then, a new correction parameter is defined for improving the conflicts among evidence bodies based on conflict degree, discrepancy degree and uncertainty, while a fine-tuning term is added to reduce the subjective effect of global focal element assignment. Finally, the risk assessment result is obtained according to the maximum affiliation principle. The method is successfully applied to Luochongwei Station, where the difference between the maximum value and the second largest value of the basic probability assignment is 0.624, and the global uncertainty degree is 0.087. Both values satisfy the decision evaluation condition; however, values of other methods only satisfy one or neither condition. In addition, the proposed method requires only four cycles to reach the steady state by fusing data of the same index, which has faster convergence compared with that of other methods. The proposed method has good universality and effectiveness in subway pit collapse risk assessment.

Abstract Aim This study aimed to verify the accuracy of intraoperative femurofibular angle combined with tibiofibular angle (FFA–TFA) measurement and compare it with traditional alignment line methods in open-wedge high tibial osteotomy (OWHTO). Methods A total of 174 knees of 122 patients undergoing OWHTO and using an alignment line or FFA–TFA measurement as an index of optimal correction were included in this retrospective study. The intraoperative alignment line passed through the targeted weight-bearing line (WBL) of the tibial plateau in the alignment line group. The intraoperative FFA–TFA aligned to the preplanned FFA–TFA angle in the FFA–TFA group. WBL, FFA, TFA, and knee joint-line convergence angle of the femur and tibia were assessed as radiological results preoperatively and one year after surgery. The Knee Society Score and the Western Ontario and McMaster Universities were assessed as objective clinical results. Results Postoperative WBL in the FFA–TFA group was closer to the target WBL than in the alignment line group (FFA–TFA vs alignment line group: 1.43 ± 1.20% vs 3.82 ± 3.29%; P 0.05). Conclusions The intraoperative measurement of FFA–TFA had fewer complications in terms of under-correction and over-correction compared with the alignment line measurement. No significant differences between the two methods were observed in clinical results one year after surgery.

Abstract The temperature distribution of ultrahigh voltage (UHV) converter transformer is the key to its service life, allowable load and safe operation. The influence of a high‐proportion and large‐value harmonic current on the magnetic field, loss and temperature distribution of a UHV converter transformer is studied. A new calculation method is proposed to determine the winding temperature under the combined actions of multiple key factors. First, the skin effect of UHV converter transformer winding under high proportion and high current harmonics is analysed extensively. It is found that the increase of harmonic current frequency leads to exponential increase of winding loss and temperature by changing skin depth. Second, based on the superposition principle, a calculation method for winding loss considering harmonic current and different load rates is developed. The temperature distribution under different harmonic current frequencies and contents is obtained. The winding losses and temperature under different harmonic currents are quantified. Finally, a new calculation method is proposed for the converter transformer winding temperature, considering the combined actions of factors such as load rate, cooling oil inlet rate and temperature, harmonic current frequency and content. Experimental verification showed an error of only 0.58 K in the actual transformer hotspot temperature, confirming the effectiveness of this method. This method is of great significance for temperature control and safe operation of UHV converter transformers.

Abstract Due to the huge cost of manual annotations, the labelled data may not be sufficient to train a dynamic facial expression (DFR) recogniser with good performance. To address this, the authors propose a multi‐modal pre‐training method with a pseudo‐label guidance mechanism to make full use of unlabelled video data for learning informative representations of facial expressions. First, the authors build a pre‐training dataset of videos with aligned vision and audio modals. Second, the vision and audio feature encoders are trained through an instance discrimination strategy and a cross‐modal alignment strategy on the pre‐training data. Third, the vision feature encoder is extended as a dynamic expression recogniser and is fine‐tuned on the labelled training data. Fourth, the fine‐tuned expression recogniser is adopted to predict pseudo‐labels for the pre‐training data, and then start a new pre‐training phase with the guidance of pseudo‐labels to alleviate the long‐tail distribution problem and the instance‐class confliction. Fifth, since the representations learnt with the guidance of pseudo‐labels are more informative, a new fine‐tuning phase is added to further boost the generalisation performance on the DFR recognition task. Experimental results on the Dynamic Facial Expression in the Wild dataset demonstrate the superiority of the proposed method.

Abstract Heterogeneous nano-electrocatalysts doped with nonmetal atoms have been studied extensively based on the so-called dopant-based active sites, while little attention has been paid to the stability of these dopants under working conditions. In this work, we reveal significantly, when the redox working potential is too low negatively or too high positively, the active sites based on these dopants actually tend to collapse. It means that some previously observed “remarkable catalytic performance” actually originated from some unknown active sites formed in situ. Take the Bi-F for the CO2RR as an example, results show that the observed remarkable activity and stability were not directly from F-based active sites, but the defective Bi sites formed in situ after the dopant leaching. Such a fact is unveiled from several heteroatom-doped nanocatalysts for four typical reactions (CO2RR, HER, ORR, and OER). This work provides insight into the role of dopants in electrocatalysis.

This paper introduces a novel action recognition model named ViT-Shift, which combines the Time Shift Module (TSM) with the Vision Transformer (ViT) architecture. Traditional video action recognition tasks face significant computational challenges, requiring substantial computing resources. However, our model successfully addresses this issue by incorporating the TSM, achieving outstanding performance while significantly reducing computational costs. Our approach is based on the latest Transformer self-attention mechanism, applied to video sequence processing instead of traditional convolutional methods. To preserve the core architecture of ViT and transfer its excellent performance in image recognition to video action recognition, we strategically introduce the TSM only before the multi-head attention layer of ViT. This design allows us to simulate temporal interactions using channel shifts, effectively reducing computational complexity. We carefully design the position and shift parameters of the TSM to maximize the model’s performance. Experimental results demonstrate that ViT-Shift achieves remarkable results on two standard action recognition datasets. With ImageNet-21K pretraining, we achieve an accuracy of 77.55% on the Kinetics-400 dataset and 93.07% on the UCF-101 dataset.

Abstract Background The consolidation tumor ratio (CTR) is a predictor of invasiveness in peripheral T1N0M0 lung adenocarcinoma. However, its association with spread through air spaces (STAS) remains largely unexplored. We aimed to explore the correlation between the CTR of primary tumors and STAS in peripheral T1N0M0 lung adenocarcinoma. Methods We collected data from patients who underwent surgery for malignant lung neoplasms between January and November 2022. Univariate and multivariate analyses following propensity-score matching with sex, age, BMI, were performed to identify the independent risk factors for STAS. The incidence of STAS was compared based on pulmonary nodule type. A smooth fitting curve between CTR and STAS was produced by the generalized additive model (GAM) and a multiple regression model was established using CTR and STAS to determine the dose-response relationship and calculate the odds ratio (OR) and 95% confidence interval (CI). Results 17 (14.5%) were diagnosed with STAS. The univariate analysis demonstrated that the history of the diabetes, size of solid components, spiculation, pleural indentation, pulmonary nodule type, consolidation/tumor ratio of the primary tumor were statistically significant between the STAS-positive and STAS-negative groups following propensity-score matching(p = 0.047, 0.049, 0.030, 0.006, 0.026, and

Abstract Background Some studies have assessed the predictive role of the atherogenic index of plasma (AIP) for macrovascular diseases. This prospective investigation aimed to elucidate whether AIP is associated with diabetic kidney disease (DKD) and diabetic retinopathy (DR) incidence. Methods The data were extracted from 4831 participants, of whom 2943 and 3360 participants with type 2 diabetes (T2D) were included in the DKD and DR follow-up analyses, respectively. Cox regression models were performed to test the relationships of AIP value at baseline with the risk of incident DKD and DR. Group-based trajectory modelling was utilized to discern AIP trajectories during the follow-up period. Subsequently, logistic regressions were applied to ascertain the influence of AIP trajectories on the incidence of DKD and DR. Results During the follow-up period, 709 (24.1%) and 193 (5.7%) participants developed DKD and DR, respectively. The median (interquartile range) follow-up time was 24.2 (26.3) months for DKD and 25.7 (27.0) months for DR. According to the multivariate Cox regression models, baseline AIP was positively and linearly related to the occurrence of DKD, with a hazard ratio of 1.75 (95% confidence interval [CI] 1.36–2.26). Three distinct trajectories of AIP were identified throughout the follow-up time: Low (31.4%), Median (50.2%), and High (18.3%). Compared to participants with the Low AIP trajectory, those with High and Median AIP trajectories presented 117% (95% CI: 1.62–2.91) and 84% (95% CI 1.46–2.32) greater odds of developing DKD, respectively. However, neither baseline levels nor trajectories of AIP were shown to be related to DR after adjusting for confounding factors. Conclusions Baseline levels and trajectories of AIP were independently related to elevated DKD risk, indicating that AIP could be used as a predictor for identifying T2D participants at higher risk of DKD. No association between AIP and DR was detected.

As urban aging issues intensify, the impact of the built environment in urban neighborhoods on the physical and mental health of elderly residents has garnered increasing attention. Previous studies have demonstrated that the built environment is related to various health outcomes; however, most empirical research typically focuses on the objective physical environment, lacking measurements of subjective environmental perceptions. This study, using 24 neighborhoods in Shanghai as case studies, employed deep learning, big data methods, and surveys to collect 462 valid questionnaires from elderly residents. Structural equation modeling was applied to explore the relationship between the built environment and the physical and mental health of elderly residents, incorporating respondents’ subjective perceptions, physical activity, and neighborhood relationships as chain mediation effects. The results indicate that although there is no direct relationship between the built environment and the mental health of elderly residents, the built environment positively impacts mental health through enhancing subjective.

In recent years, unmanned aerial vehicle (UAV) formation flight has become an effective strategy for urban air mobility (UAM). However, close rotor separation during formation flight leads to complex aerodynamic interference between rotors, significantly affecting UAV flight performance and operational safety. This study systematically examines the effects of axial and lateral rotor separation on the rotor’s thrust performance through wind tunnel experiments. The tests simulate horizontal, vertical, and hovering states by generating relative airflow in the wind tunnel, focusing primarily on the thrust coefficient changes of the bottom rotor at various separations. The results are compared with a single rotor operating under the same conditions without wake interference. Additionally, computational fluid dynamics (CFD) simulations using the Fluent software were conducted to investigate the effect of wake interactions by analyzing the velocity flow field between the two rotors in different separations. Both the experimental and simulation results demonstrate that rotor aerodynamic performance is notably influenced by wake interactions. Under hovering and vertical states, substantial aerodynamic interference occurs in the region directly beneath the top rotor, within 1D ≤ Z ≤ 3D. This interference gradually diminishes as the rotor separation increases. Additionally, the thrust coefficient of the bottom rotor decreases with increasing flight speed due to the wake, and at higher flight speeds, the wake tends to contract. When the lateral separation is X = 0D, the mid-sectional flow field of the two rotors exhibits symmetry; however, with lateral separation, the symmetry of the bottom rotor’s wake velocity field is disrupted. During the horizontal flight, the rotor wake tilts backward due to the relative airflow, and the extent of this influence is governed by both rotor rotational speed and flight velocity. Therefore, when UAVs operate in formation, it is crucial to account for these factors affecting aerodynamic performance, and rotor separation must be optimized to enhance flight safety and efficiency.

(1) Objective: This study investigated the relationship between long-term particulate matter (PM2.5) exposure and optic disc parameters—vertical cup-to-disc ratio (vCDR), vertical optic disc diameter (vDD), and vertical optic cup diameter (vCD)—in patients with type 2 diabetes mellitus (T2DM). (2) Methods: A cross-sectional analysis was conducted using data from 65,750 T2DM patients in the 2017–2018 Shanghai Cohort Study of Diabetic Eye Disease (SCODE). Optic disc parameters were extracted from fundus images, and PM2.5 exposure was estimated using a random forest model incorporating satellite and meteorological data. Multivariate linear regression models were applied, adjusting for confounders including age, gender, body mass index, blood pressure, glucose, time of T2DM duration, smoking, drinking, and physical exercise. (3) Results: A 10 μg/m3 increase in PM2.5 exposure was associated with significant reductions in vCDR (−0.008), vDD (−42.547 μm), and vCD (−30.517 μm) (all p-values < 0.001). These associations persisted after sensitivity analyses and adjustments for other pollutants like O3 and NO2. (4) Conclusions: Long-term PM2.5 exposure is associated with detrimental changes in optic disc parameters in patients with T2DM, suggesting possible optic nerve atrophy. Considering the close relationship between the optic nerve and the central nervous system, these findings may also reflect broader neurodegenerative processes.

Stress granules (SGs), formed by untranslated messenger ribonucleoproteins (mRNPs) during cellular stress in eukaryotes, have been linked to flavivirus interference without clear understanding. This study reveals the role of Zika virus (ZIKV) NS2B as a scaffold protein mediating interaction between protein phosphatase 1α (PP1α) and eukaryotic initiation factor 2α (eIF2α). This interaction promotes eIF2α dephosphorylation by PP1α, inhibiting SG formation. The NS2B-PP1α complex exhibits remarkable stability, resisting ubiquitin-induced degradation and amplifying eIF2α dephosphorylation, thus promoting ZIKV replication. In contrast, the NS2BV35A mutant, interacting exclusively with eIF2α, fails to inhibit SG formation, resulting in reduced viral replication and diminished impact on brain organoid growth. These findings reveal PP1α's dual role in ZIKV infection, inducing interferon production as an antiviral factor and suppressing SG formation as a viral promoter. Moreover, we found that NS2B also serves as a versatile mechanism employed by flaviviruses to counter host antiviral defenses, primarily by broadly inhibiting SG formation. This research advances our comprehension of the complex interplay in flavivirus-host interactions, offering potential for innovative therapeutic strategies against flavivirus infections.

BackgroundThe aim of this cross-sectional study was to elucidate the associations between various domains of physical activity, such as occupation-related (OPA), transportation-related (TPA), leisure-time (LTPA) and overall physical activity (PA), and diabetic kidney disease.MethodsOur study encompassed 2,633 participants, drawn from the cross-sectional surveys of the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2018, and employed survey-weighted logistic regression, generalized linear regression, and restricted cubic spline (RCS) analyses to ascertain the relationship between different domains of physical activity and diabetic kidney disease.ResultsAfter controlling for all confounders, multivariate logistic regression analyses revealed a lack of correlation between the various domains of physical activity and the prevalence of diabetic kidney disease. Multiple generalized linear regression analyses showed that durations of PA (β = 0.05, 95% CI, 0.01–0.09, P = 0.012) and TPA (β = 0.32, 95% CI, 0.10–0.55, P = 0.006) were positively associated with eGFR levels; and LTPA durations were inversely associated with UACR levels (β = -5.97, 95% CI, -10.50 - -1.44, P = 0.011). The RCS curves demonstrated a nonlinear relationship between PA, OPA, and eGFR, as well as a nonlinear correlation between PA and ACR. Subgroup and sensitivity analyses largely aligned with the outcomes of the multivariate generalized linear regression, underscoring the robustness of our findings.ConclusionOur population-based study explored the association between different domains of physical activity and diabetic kidney disease. Contrary to our expectations, we found no significant association between the duration of physical activity across all domains and the prevalence of diabetic nephropathy. Nonetheless, renal function markers, including eGFR and UACR, exhibited significant correlations with the duration of total physical activity (TPA) and leisure-time physical activity (LTPA), respectively, among diabetic patients. Interestingly, our findings suggest that diabetic patients engage in physical activity to preserve renal function, ensuring moderate exercise durations not exceeding 35 hours per week.

Under the background of global climate change, Subsurface Marine Heatwaves (SSMHWs) have become a ‘hot-spot’ research due to their significant impacts on marine ecosystems. Temperature data from the ECCO2 for the years 1992 to 2021 is used to research the spatiotemporal characteristics of SSMHWs in the upper 500 m over the Xisha region (110°E to 113°E, 15°N to 18°N). This study indicates that SSMHWs of high intensity occur in the Xisha area, with the vertical maximum intensity at approximately 100 m. These events exhibit significant seasonal variations, with the highest intensity occurring in May. The intensity of SSMHW in the analysis region varies interannually. SSMHWs have intensified at a rate of 1.53°C·Days/Year and tend to shift to deeper water over the past three decades. A block-based method for SSMHW identification is proposed, in order to take the vertical extent of the event in consideration. By analyzing the eight most intense events based on spatial cumulative intensity, it suggested that warm mesoscale eddies may play an important role on the spatial distribution of the SSMHWs. Statistical analysis shows that the intensity and coverage of the warm mesoscale eddy in the Xisha zone may influence the intensity and evolution of the SSMHWs. Additionally, only 18.27% of SSMHW events occur with apparent surface marine heatwave signals. These findings are vital for uncovering SSMHW dynamics in the Xisha area, and are important for future monitoring, early warnings and marine conservation.

Background: Ultrafine particle (UFP) has been linked with higher risks of cardiovascular diseases; however, the biological mechanisms remain to be fully elucidated. Objectives: This study aims to investigate the cardiovascular responses to short-term UFP exposure and the biological pathways involved. Methods: A longitudinal panel study was conducted among 32 healthy, non-smoking young adults in Shanghai, China, who were engaged in five rounds of follow-ups between December 2020 and November 2021. Individual exposures were calculated based on the indoor and outdoor real-time measurements. Blood pressure, arterial stiffness, targeted biomarkers, and untargeted proteomics and metabolomics were examined during each follow-up. Linear mixed-effect models were applied to analyze the exposure and health data. The differential proteins and metabolites were used for pathway enrichment analyses. Results: Short-term UFP exposure was associated with significant increases in blood pressure and arterial stiffness. For example, systolic blood pressure increased by 2.10 % (95 % confidence interval: 0.63 %, 3.59 %) corresponding to each interquartile increase in UFP concentrations at lag 0–3 h, while pulse wave velocity increased by 2.26 % (95 % confidence interval: 0.52 %, 4.04 %) at lag 7–12 h. In addition, dozens of molecular biomarkers altered significantly. These effects were generally present within 24 h after UFP exposure, and were robust to the adjustment of co-pollutants. Molecular changes detected in proteomics and metabolomics analyses were mainly involved in systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and disturbance in lipid transport and metabolism. Discussion: This study provides novel and compelling evidence on the detrimental subclinical cardiovascular effects in response to short-term UFP exposure. The multi-omics profiling further offers holistic insights into the underlying biological pathways.

Remove and recovery of phosphorus from wastewater is expected to be a promising strategy to solve the shortage of phosphorus resources and control the water environment pollution. In this study, induced crystallization coupled biological phosphorus removal (IC-BPR) process was established to achieve simultaneous removal and recovery of phosphorus in wastewater. The effects of side stream ratio (SSR) on the removal and recovery efficiency of phosphorus and the microbial community structure were explored. The results indicated that the SSR of 40% was optimal to phosphorus removal and recovery in the IC-BPR. The total phosphorus removal efficiency was 94.23% under the SSR of 40%, of which the phosphorus removal efficiency by IC accounted for 74.87%. And the total phosphorus recovery efficiency was 67.29%. The particle size and crystal structure analysis of the crystallized products indicated that the increase of SSR was conductive to heterogeneous crystallization. Furthermore, typical polyphosphate accumulation organisms (PAOs), including Rhodocyclaceae, Acinetobacter, and Dechloromonasin, were enriched under the side stream ratio of 40%. And functional genes related to amino acid transport and metabolism, energy production and conversion were activated. The above results indicated that the IC could significantly enhance the removal and recovery of phosphorus under a suitable SSR condition. It will provide important reference for wastewater treatment coupled phosphorus resource recovery technology.

Background: Sarcopenia is characterized by decreased muscle mass and strength, posing threat to quality of life. Air pollutants are increasingly recognized as risk factors for diseases, while the relationship between the two remains to be elucidated. This study investigated whether exposure to ambient air pollution contributes to the development of sarcopenia. Methods: We employed the data from the UK Biobank with 303,031 eligible participants. Concentrations of PM2·5, NO2, and NOx were estimated. Cox proportional hazard regression models were applied to investigate the associations between pollutants and sarcopenia. Results: 30,766 probable sarcopenia cases was identified during the follow-up. We observed that exposure to PM2.5 (HR, 1.232; 95% CI, 1.053–1.440), NO2 (HR, 1.055; 95% CI, 1.032–1.078) and NOx (HR, 1.016; 95% CI, 1.007–1.026) were all significantly associated with increased risk for probable sarcopenia for each 10 μg/m3 increase in pollutant concentration. In comparison with individuals in the lowest quartiles of exposure, those in the upper quartiles had significantly increased risk of probable sarcopenia. Sarcopenia-related factors, e.g., reduced lean muscle mass, diminished walking pace, and elevated muscle fat infiltration ratio, also exhibited positive associations with exposure to ambient air pollution. On the contrary, high level physical activity significantly mitigated the influence of air pollutants on the development of probable sarcopenia. Conclusions: Air pollution exposure elevated the risk of developing sarcopenia and related manifestations in a dose-dependent manner, while physical activity maintained protective under this circumstance. Efforts should be made to control air pollution and emphasize the importance of physical activity for skeletal muscle health under this circumstance.

T-cell immunoglobulin domain and mucin domain-3 (Tim-3) is a versatile immunomodulator that protects against intestinal inflammation. Necroptosis is a type of cell death that regulates intestinal homeostasis and inflammation. The mechanism(s) underlying the protective role of macrophage Tim-3 in intestinal inflammation is unclear; thus, we investigated whether specific Tim-3 knockdown in macrophages drives intestinal inflammation via necroptosis. Tim-3 protein and mRNA expression were assessed via double immunofluorescence staining and single-cell RNA sequencing (sc-RNA seq), respectively, in the colonic tissues of patients with inflammatory bowel disease (IBD) and healthy controls. Macrophage-specific Tim3-knockout (Tim-3M−KO) mice were generated to explore the function and mechanism of Tim-3 in dextran sodium sulfate (DSS)-induced colitis. Necroptosis was blocked by pharmacological inhibitors of receptor-interacting protein kinase (RIP)1, RIP3, and reactive oxygen species (ROS). Additionally, in vitro experiments were performed to assess the mechanisms of neutrophil necroptosis induced by Tim-3 knockdown macrophages. Although Tim-3 is relatively inactive in macrophages during colon homeostasis, it is highly active during colitis. Compared to those in controls, Tim-3M−KO mice showed increased susceptibility to colitis, higher colitis scores, and increased pro-inflammatory mediator expression. Following the administration of RIP1/RIP3 or ROS inhibitors, a significant reduction in intestinal inflammation symptoms was observed in DSS-treated Tim-3M−KO mice. Further analysis indicated the TLR4/NF-κB pathway in Tim-3 knockdown macrophages mediates the TNF-α-induced necroptosis pathway in neutrophils. Macrophage Tim-3 regulates neutrophil necroptosis via intracellular ROS signaling. Tim-3 knockdown macrophages can recruit neutrophils and induce neutrophil necroptosis, thereby damaging the intestinal mucosal barrier and triggering a vicious cycle in the development of colitis. Our results demonstrate a protective role of macrophage Tim-3 in maintaining gut homeostasis by inhibiting neutrophil necroptosis and provide novel insights into the pathogenesis of IBD.

AbstractBackground The Global Initiative for Chronic Obstructive Lung Disease (GOLD) document suggests that patients with chronic obstructive pulmonary disease (COPD) should be divided into a less symptomatic group. Moreover, single-inhaled drugs are recommended as initial inhalation therapy for them. However, many less symptomatic patients are provided double or triple-inhaled drugs as initial therapy in the real world. This study aimed to describe the inhalation prescriptions and compare the effects of different inhalation therapies on less symptomatic COPD patients.Patients and methods This was an observational study. Stable COPD patients were recruited and divided into a less symptomatic group including Groups A and C based on the GOLD 2019 document. We collected the data of inhalation therapies prescriptions. Then, the patients were classified into long-acting muscarinic antagonist (LAMA), long-acting β2-agonist (LABA) + inhaled corticosteroid (ICS), LABA + LAMA, and LABA + LAMA + ICS groups. All the patients were followed up for 1 year to collect exacerbation and mortality data.Results We found that only 45.4% of patients in Group A and 43.6% of patients in Group C received reasonable inhalation therapy in reference to the GOLD document. In addition, the LAMA group had a higher forced expiratory volume in one second (FEV1), FEV1%pred, FEV1/forced vital capacity and peak expiratory flow compared with LABA + ICS, LABA + LAMA and LABA + LAMA + ICS groups. However, we did not find any significant differences of exacerbation, hospitalization and mortality during the follow-up among different inhalation therapies groups on less symptomatic COPD patients.Conclusion Over half of the less symptomatic patients received inhalation therapy that were inconsistent with the GOLD document recommendations in a Chinese population in the real world. In fact, the single inhaled drug of LAMA should be recommended and pulmonary function is not a good indicator for the choice of initial inhalation therapy in less symptomatic COPD patients.KEY MESSAGESOver half of the less symptomatic COPD patients received inhalation therapy that were inconsistent with the GOLD document recommendations in a Chinese population in the real world.The clinicians should offer a single inhaled drug of LAMA to less symptomatic COPD patients and pulmonary function is not a good indicator for the choice of initial inhalation therapy.

Abstract Background Intracardiac leiomyoma is a rare benign right heart tumor that usually extends from the intravenous system. The patient often has a history of uterine leiomyoma. Case presentation We report a 46-year-old female patient who presented to us with exertional dyspnea, chest tightness, and shortness of breath for two weeks and had a history of uterine leiomyoma resection. Echocardiography showed a pedunculated solid mass in the right heart with the pedicle attached to the inferior vena cava. The surgery was performed under cardiopulmonary bypass established through the femoral artery and vein with a probable diagnosis of leiomyoma. The tumor was removed by ingenious surgical technique: a snare made of silk suture in which the tumor’s pedicle was trapped, and the tumor with its pedicle was carefully removed with the help of a scalpel along the silk suture. The histopathology report confirmed the diagnosis of intravenous leiomyoma. The postoperative course was uneventful and the patient was discharged a week later. Conclusion Intracardiac leiomyoma is a rare benign smooth muscle tumor. Surgery is the mainstay of treatment with different surgical approaches available. It is possible to completely remove cardiac leiomyomas through sternotomy without the need for an abdominal incision if the leiomyoma is originated in the inferior vena cava not far from the right atrium.

Abstract Background The positive effects of exposing corals to microorganisms have been reported though how the benefits are conferred are poorly understood. Here, we isolated an actinobacterial strain (SCSIO 13291) from Pocillopora damicornis with capabilities to synthesize antioxidants, vitamins, and antibacterial and antiviral compounds supported with phenotypic and/or genomic evidence. Strain SCSIO 13291 was labeled with 5 (and − 6)-carboxytetramethylrhodamine, succinimidyl ester and the labeled cell suspension directly inoculated onto the coral polyp tissues when nubbins were under thermal stress in a mesocosm experiment. We then visualized the labelled bacterial cells and analyzed the coral physiological, transcriptome and microbiome to elucidate the effect this strain conferred on the coral holobiont under thermal stress. Results Subsequent microscopic observations confirmed the presence of the bacterium attached to the coral polyps. Addition of the SCSIO 13291 strain reduced signs of bleaching in the corals subjected to heat stress. At the same time, alterations in gene expression, which were involved in reactive oxygen species and light damage mitigation, attenuated apoptosis and exocytosis in addition to metabolite utilization, were observed in the coral host and Symbiodiniaceae populations. In addition, the coral associated bacterial community altered with a more stable ecological network for samples inoculated with the bacterial strain. Conclusions Our results provide insights into the benefits of a putative actinobacterial probiotic strain that mitigate coral bleaching signs. This study suggests that the inoculation of bacteria can potentially directly benefit the coral holobiont through conferring metabolic activities or through indirect mechanisms of suppling additional nutrient sources.

Introduction Abnormal apoptosis of pulmonary microvascular endothelial cells (PMVECs) participates in the pathogenesis of COPD. Studies have shown that microRNAs (miRNAs) contribute to the pathogenesis of pulmonary diseases by regulating cell apoptosis. The present study aimed to investigate the effects of miR-216a in cigarette smoke extract (CSE)-induced apoptosis of PMVECs in COPD and explore the potential mechanisms. Methods The emphysema model mice were treated with CSE and CS exposure. The expression of miR-216a and DNA methyltransferase 1 (DNMT1) was assessed in emphysema mice and COPD patients. The miR-216a mimic and Lenti-DNMT1 were transfected into PMVECs to identify the underlying mechanisms. The expression levels of miR-216a and DNMT1 were detected by real-time quantitative polymerase chain reaction (RT-qPCR) or Western blot. Moreover, cell apoptosis was examined by flow cytometry assays. Results The results show that the expression of miR-216a was decreased, whereas the expression of DNMT1 was increased in the lung tissue of emphysema mice and COPD patients. In addition, the expression of miR-216a was significantly reduced in CSE-treated PMVECs, and the overexpression of miR-216a attenuated CSEinduced PMVEC apoptosis. Furthermore, the expression of DNMT1 was increased in the CSE-induced PMVECs and then was reduced after the overexpression of miR-216a in the CSE-stimulated PMVECs. Luciferase reporter assays confirmed the target reaction between miR-216a and DNMT1. Also, the overexpression of DNMT1 was able to reverse the anti-apoptotic effect of miR-216a in CSE-induced PMVECs. Conclusions The results indicate that miR-216a may play a crucial role in CSEinduced apoptosis by directly regulating its target gene DNMT1 in COPD. It provides insights into the function of MiR-216a/DNMT1 as a potential molecule in COPD.

Abstract Temperature-economic growth relationships are computed to quantify the impact of climate change on the economy. However, model performance and differences of predictions among research complicate the use of climate econometric estimation. Machine learning methods provide an alternative that might improve the predictive effects. However, time series and extrapolation issues constrain methods such as random forests. We apply a simple thought experiment with national marginal GDP growth by aggregating subnational climate impact to alleviate the shortcomings in random forests. This paper uses random forests, multivariate cubic regression, and linear spline regression to examine the direct impacts of temperature on economic development and conducts a performance comparison of the methods. The model results indicate an optimal temperature of 15°C, 15°C or 21°C for each model. Furthermore, a thought experiment indicates that the marginal predictions of national GDP changes by approximately 1%, −3%, or −6% for models with 1°C warming. The performance comparison suggests that random forests have stable model performance and better prediction performance in bootstrapping. However, the extrapolation problem in random forests causes underestimation of climate impact in 5% of cells under 6°C warming. Overall, our results suggest that temperature should be considered in economic projections under climate change scenarios. We also suggest the use of more machine learning methods in climate impact assessment.

Background: Ulcerative colitis (UC) is an intestinal disorder marked by chronic, recurring inflammation, yet its underlying mechanisms have not been fully elucidated. Methods: The current research dealt with examining the biological impacts of toll-like receptor 2 (TLR2) on dextran sulfate sodium (DSS)-triggered inflammation in the intestines of wild-type (WT) and TLR2-knockout (TLR2-KO) colitis mouse models. To elucidate the protective function of TLR2 in DSS-triggered colitis, RNA-sequencing (RNA-Seq) was carried out to compare the global gene expression data in the gut of WT and TLR2-KO mice. Further, 16S rRNA gene sequencing revealed notable variations in gut microbiota composition between WT and TLR2-KO colitis mice. Results: It was revealed that TLR2-KO mice exhibited increased susceptibility to DSS-triggered colitis. RNA-Seq results demonstrated that cell cycle pathway-related genes were notably downregulated in TLR2-KO colitis mice (enrichment score = 30, p < 0.001). 16S rRNA gene sequencing revealed that in comparison to the WT colitis mice, the relative abundance of Marinifilacea (p = 0.006), Rikenellacea (p = 0.005), Desulfovibrionaceae (p = 0.045), Tannerellaceae (p = 0.038), Ruminococcaceae (p = 0.003), Clostridia (p = 0.027), and Mycoplasmataceae (p = 0.0009) was significantly increased at the family level in the gut of TLR2-KO colitis mice. In addition, microbiome diversity-transcriptome collaboration analysis highlighted that the relative abundance of Marinifilaceae was negatively linked to the expression of cell cycle signaling-related genes (p values were all less than 0.001). Conclusion: Based on these findings, we concluded that TLR2-KO exacerbates DSS-triggered intestinal injury by mitigating cell cycle signaling in a Marinifilaceae-dependent manner.

The bioavailability of a monoclonal antibody (mAb) or another therapeutic protein after subcutaneous (SC) dosing is challenging to predict from first principles, even if the impact of injection site physiology and drug properties on mAb bioavailability is generally understood. We used a physiologically based pharmacokinetic model to predict pre-systemic clearance after SC administration mechanistically by incorporating the FcRn salvage pathway in antigen-presenting cells (APCs) in peripheral lymph nodes, draining the injection site. Clinically observed data of the removal rate of IgG from the arm as well as its plasma concentration after SC dosing were mostly predicted within the 95% confidence interval. The bioavailability of IgG was predicted to be 70%, which mechanistically relates to macropinocytosis in the draining lymph nodes and transient local dose-dependent partial saturation of the FcRn receptor in the APCs, resulting in higher catabolism and consequently less drug reaching the systemic circulation. The predicted free FcRn concentration was reduced to 40–45%, reaching the minimum 1–2 days after the SC administration of IgG, and returned to baseline after 8–12 days, depending on the site of injection. The model predicted the uptake into APCs, the binding affinity to FcRn, and the dose to be important factors impacting the bioavailability of a mAb.

The meat production traits of pigs are influenced by the expression regulation of multiple gene types, including mRNAs, miRNAs, and lncRNAs. To study the differences in meat production traits at the transcriptional level among individuals with different growth rates, the longissimus dorsi samples from eight Duroc × Bama Xiang F2 crossbred pigs with a fast growth rate (high gTroup) or a slow growth rate (low group) were selected to perform whole transcriptome sequencing and ceRNA regulatory network construction. This study first analyzed the differences in physiological and biochemical indicators, muscle histological characteristics, and muscle fiber types. A total of 248 mRNAs, 25 miRNAs, and 432 lncRNAs were identified as differentially expressed by whole transcriptome sequencing. Key genes that may influence meat production traits include MTMR14, PPP1R3A, PYGM, PGAM2, MYH1, and MYH7. The ceRNA regulatory network map showed that ENSSSCG00000042061-ssc-mir-208b-MYH7, ENSSSCG00000042223-ssc-mir-146a-MTMR14, ENSSSCG00000045539-ssc-mir-9-3-MYH1, and ENSSSCG00000047852-ssc-mir-103-1-PPP1R3A may be the key factors affecting meat production traits through their regulatory relationships. This study provides valuable insights into the molecular mechanisms underlying porcine muscle development and can aid in improving meat production traits.

Land-cover segmentation, a fundamental task within the domain of remote sensing, boasts a broad spectrum of application potential. We address the challenges in land-cover segmentation of remote-sensing imagery and complete the following work. Firstly, to tackle the issues of foreground–background imbalance and scale variation, a module based on multi-dilated rate convolution fusion was integrated into a decoder. This module extended the receptive field through multi-dilated convolution, enhancing the model’s capability to capture global features. Secondly, to address the diversity of scenes and background interference, a hybrid attention module based on large-kernel convolution was employed to improve the performance of the decoder. This module, based on a combination of spatial and channel attention mechanisms, enhanced the extraction of contextual information through large-kernel convolution. A convolution kernel selection mechanism was also introduced to dynamically select the convolution kernel of the appropriate receptive field, suppress irrelevant background information, and improve segmentation accuracy. Ablation studies on the Vaihingen and Potsdam datasets demonstrate that our decoder significantly outperforms the baseline in terms of mean intersection over union and mean F1 score, achieving an increase of up to 1.73% and 1.17%, respectively, compared with the baseline. In quantitative comparisons, the accuracy of our improved decoder also surpasses other algorithms in the majority of categories. The results of this paper indicate that our improved decoder achieves significant performance improvement compared with the old decoder in remote-sensing image-segmentation tasks, which verifies its application potential in the field of land-cover segmentation.

The world’s coral reefs are threatened by the cumulative impacts of global climate change and local stressors. Driven largely by a desire to understand the interactions between corals and their symbiotic microorganisms, and to use this knowledge to eventually improve coral health, interest in coral microbiology and the coral microbiome has increased in recent years. In this review, we summarize the role of the coral microbiome in maintaining a healthy metaorganism by providing nutrients, support for growth and development, protection against pathogens, and mitigation of environmental stressors. We explore the concept of coral microbiome engineering, that is, precise and controlled manipulation of the coral microbiome to aid and enhance coral resilience and tolerance in the changing oceans. Although coral microbiome engineering is clearly in its infancy, several recent breakthroughs indicate that such engineering is an effective tool for restoration and preservation of these valuable ecosystems. To assist with identifying future research targets, we have reviewed the common principles of microbiome engineering and its applications in improving human health and agricultural productivity, drawing parallels to where coral microbiome engineering can advance in the not-too-distant future. Finally, we end by discussing the challenges faced by researchers and practitioners in the application of microbiome engineering in coral reefs and provide recommendations for future work.

Abstract Background Intramuscular fat (IMF) content is the major indicator for evaluating chicken meat quality due to its positive correlation with tenderness, juiciness, and flavor. An increasing number of studies are focusing on the functions of microRNAs (miRNAs) in intramuscular adipocyte differentiation. However, little is known about the association of miR-128-3p with intramuscular adipocyte differentiation. Our previous RNA-seq results indicated that miR-128-3p was differentially expressed at different periods in chicken intramuscular adipocytes, revealing a possible association with intramuscular adipogenesis. The purpose of this research was to investigate the biological functions and regulatory mechanism of miR-128-3p in chicken intramuscular adipogenesis. Results The results of a series of assays confirmed that miR-128-3p could promote the proliferation and inhibit the differentiation of intramuscular adipocytes. A total of 223 and 1,050 differentially expressed genes (DEGs) were identified in the mimic treatment group and inhibitor treatment group, respectively, compared with the control group. Functional enrichment analysis revealed that the DEGs were involved in lipid metabolism-related pathways, such as the MAPK and TGF-β signaling pathways. Furthermore, target gene prediction analysis showed that miR-128-3p can target many of the DEGs, such as FDPS, GGT5, TMEM37, and ASL2. The luciferase assay results showed that miR-128-3p targeted the 3’ UTR of FDPS. The results of subsequent functional assays demonstrated that miR-128-3p acted as an inhibitor of intramuscular adipocyte differentiation by targeting FDPS. Conclusion miR-128-3p inhibits chicken intramuscular adipocyte differentiation by downregulating FDPS. Our findings provide a theoretical basis for the study of lipid metabolism and reveal a potential target for molecular breeding to improve meat quality.

Abstract Objectives This study aimed to integrate positron emission tomography/computed tomography (PET/CT) metrics and genetic mutations to optimize the risk stratification for diffuse large B‐cell lymphoma (DLBCL) patients. Methods The data of 94 primary DLBCL patients with baseline PET/CT examination completed in the Shandong Cancer Hospital and Institute (Jinan, China) were analyzed to establish a training cohort. An independent cohort of 45 DLBCL patients with baseline PET/CT examination from other hospitals was established for external validation. The baseline total metabolic tumor volume (TMTV) and the largest distance between two lesions (Dmax) standardized by patient body surface area (SDmax) were calculated. The pretreatment pathological tissues of all patients were sequenced by a lymphopanel including 43 genes. Results The optimal TMTV cutoff was 285.3 cm3 and the optimal SDmax cutoff was 0.135 m−1. TP53 status was found as an independent predictive factor significantly affecting complete remission (p = 0.001). TMTV, SDmax, and TP53 status were the main factors of the nomogram and could stratify the patients into four distinct subgroups based on their predicted progression‐free survival (PFS). The calibration curve demonstrated satisfactory agreement between the predicted and actual 1‐year PFS of the patients. The receiver operating characteristic curves showed this nomogram based on PET/CT metrics and TP53 mutations had a better predictive ability than the clinic risk scores. Similar results were identified upon external validation. Conclusions The nomogram based on imaging factors and TP53 mutations could lead to a more accurate selection of DLBCL patients with rapid progression, to increase tailor therapy.

With the improvement of data abilities and the development of emerging technologies, there are profound changes occurring in economic patterns and competitive structure of industries.In order to better respond to future opportunities and challenges, and to improve competitiveness of enterprises in new situations, it is necessary to understand and master the knowledge of digital transformation.The new competitive situation was discussed in which traditional enterprises would gradually be replaced by digital-transformed ones, digital transformation was differentiated from digitalization.Main challenges facing traditional enterprises while undergoing digital transformation were pinpointed, which were the lack of funds, talents, data and consciousness.A digital transformation service platform oriented to new competitive situation was proposed, which provided a feasible solution to enhancing enterprise competitiveness and conducting digital transformation.

Abstract Helium, the second most abundant element in the universe, exhibits an extremely large electronic band gap of about 20 eV at ambient pressures. While the metallization pressure of helium has been accurately determined, thus far little attention has been paid to the specific mechanisms driving the band-gap closure and electronic properties of this quantum crystal in the terapascal regime (1 TPa = 10 Mbar). Here, we employ density functional theory and many-body perturbation calculations to fill up this knowledge gap. It is found that prior to reaching metallicity helium becomes an excitonic insulator (EI), an exotic state of matter in which electrostatically bound electron-hole pairs may form spontaneously. Furthermore, we predict metallic helium to be a superconductor with a critical temperature of ≈ 20 K just above its metallization pressure and of ≈ 70 K at 100 TPa. These unforeseen phenomena may be critical for improving our fundamental understanding and modeling of celestial bodies.

Abnormal aggregation and accumulation of pathological amyloid proteins such as amyloid-β, Tau, and α-synuclein play key pathological roles and serve as histological hallmarks in different neurodegenerative diseases (NDs) such as Alzheimer's disease (AD) and Parkinson's disease (PD). In addition, various post-translational modifications (PTMs) have been identified on pathological amyloid proteins and are subjected to change during disease progression. Given the central role of amyloid proteins in NDs, tremendous efforts have been made to develop amyloid-targeting strategies for clinical diagnosis and molecular classification of NDs. In this review, we summarize two major strategies for targeting amyloid aggregates, with a focus on the trials in AD diagnosis. The first strategy is a positron emission tomography (PET) scan of protein aggregation in the brain. We mainly focus on introducing the development of small-molecule PET tracers for specifically recognizing pathological amyloid fibrils. The second strategy is the detection of PTM biomarkers on amyloid proteins in cerebrospinal fluid and plasma. We discuss the pathological roles of different PTMs in diseases and how we can use the PTM profile of amyloid proteins for clinical diagnosis. Finally, we point out the potential technical challenges of these two strategies, and outline other potential strategies, as well as a combination of multiple strategies, for molecular diagnosis of NDs.

Abstract Background Glycemic variability plays an important role in the development of cardiovascular disease (CVD). This study aims to determine whether long-term visit-to-visit glycemic variability is associated with aortic stiffness progression in participants with type 2 diabetes (T2D). Methods Prospective data were obtained from 2115 T2D participants in the National Metabolic Management Center (MMC) from June 2017 to December 2022. Two brachial-ankle pulse wave velocity (ba-PWV) measurements were performed to assess aortic stiffness over a mean follow-up period of 2.6 years. A multivariate latent class growth mixed model was applied to identify trajectories of blood glucose. Logistic regression models were used to determine the odds ratio (OR) for aortic stiffness associated with glycemic variability evaluated by the coefficient of variation (CV), variability independent of the mean (VIM), average real variability (ARV), and successive variation (SV) of blood glucose. Results Four distinct trajectories of glycated hemoglobin (HbA1c) or fasting blood glucose (FBG) were identified. In the U-shape class of HbA1c and FBG, the adjusted ORs were 2.17 and 1.21 for having increased/persistently high ba-PWV, respectively. Additionally, HbA1c variability (CV, VIM, SV) was significantly associated with aortic stiffness progression, with ORs ranging from 1.20 to 1.24. Cross-tabulation analysis indicated that the third tertile of the HbA1c mean and VIM conferred a 78% (95% confidence interval [CI] 1.23–2.58) higher odds of aortic stiffness progression. Sensitivity analysis demonstrated that the SD of HbA1c and the highest HbA1c variability score (HVS) were significantly associated with the adverse outcomes independent of the mean of HbA1c during the follow-up. Conclusions Long-term visit-to-visit HbA1c variability was independently associated with aortic stiffness progression, suggesting that HbA1c variability was a strong predictor of subclinical atherosclerosis in T2D participants.

Iodine is involved in the synthesis of thyroid hormones and plays a crucial role in human life. Both iodine deficiency and excess are common issues in certain populations. Iodine also has extrathyroidal effects on organs that can uptake it independently of thyroid hormones. Recently, multiple clinical studies have shown a connection between iodine intake and metabolic disorders, such as metabolic syndrome, obesity, diabetes, hypertension, and dyslipidemia. However, the results of these studies have been inconsistent, and the mechanisms behind these associations are still not well understood. Therefore, in this review, we aim to examine the recent research progress regarding the relationship between iodine and metabolic disorders, along with the relevant mechanisms.

Objectives To analyse and explore the association between thyroid autoantibodies and diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM).Design A cross-sectional study.Setting Patients were from the inpatient unit at The Second Endocrinology Department of Shengjing Hospital Affiliated to China Medical University (Shenyang, China) between January 2015 and September 2019.Participants A total of 150 Chinese adults with T2DM were included in the study, including 83 men and 67 women. Their age ranged between 25 and 92 years.Methodology They grouped by the presence of DKD, urine albumin-to-creatinine ratio (UACR), estimated glomerular filtration rate, and levels of thyroid peroxidase antibodies (TPOAb) and thyroglobulin antibodies (TgAb). Data on the patients’ general characteristics and laboratory measurements (levels of fasting plasma glucose, glycated haemoglobin, and albumin; renal function; and thyroid function) were collected. Binary logistic regression was performed to identify risk factors for DKD.Results The level of TPOAb, the positivity rates of TPOAb (p

Abstract G‐quadruplex (G4) is a four‐stranded noncanonical DNA structure that has long been recognized as a potential hindrance to DNA replication. However, how replisomes effectively deal with G4s to avoid replication failure is still obscure. Here, using single‐molecule and ensemble approaches, the consequence of the collision between bacteriophage T7 replisome and an intramolecular G4 located on either the leading or lagging strand is examined. It is found that the adjacent fork junctions induced by G4 formation incur the binding of T7 DNA polymerase (DNAP). In addition to G4, these inactive DNAPs present insuperable obstacles, impeding the progression of DNA synthesis. Nevertheless, T7 helicase can dismantle them and resolve lagging‐strand G4s, paving the way for the advancement of the replication fork. Moreover, with the assistance of the single‐stranded DNA binding protein (SSB) gp2.5, T7 helicase is also capable of maintaining a leading‐strand G4 structure in an unfolded state, allowing for a fraction of T7 DNAPs to synthesize through without collapse. These findings broaden the functional repertoire of a replicative helicase and underscore the inherent G4 tolerance of a replisome.

Autoimmune thyroiditis (AITD) is a T-cell-mediated, organ- specific autoimmune disease caused by interactions between genetic and environmental factors. Patients with AITD show thyroid lymphocyte infiltration and an increase in the titer of thyroid autoimmune antibodies, thereby altering the integrity of thyroid follicle epithelial cells and dysregulating their metabolism and immune function, leading to a decrease in multi-tissue metabolic activity. Research has shown that patients with AITD have a significantly higher risk of adverse pregnancy outcomes, such as infertility and miscarriage. Levothyroxine(LT4) treatment can improve the pregnancy outcomes of normal pregnant women with thyroid peroxidase antibodies(TPOAb) positivity, but it is not effective for invitro fertilization embryo transfer (IVF-ET) in women with normal thyroid function and positive TPOAb. Other factors may also influence pregnancy outcomes of patients with AITD. Recent studies have revealed that the gut microbiota participates in the occurrence and development of AITD by influencing the gut-thyroid axis. The bacterial abundance and diversity of patients with Hashimoto thyroiditis (HT) were significantly reduced, and the relative abundances of Bacteroides, fecal Bacillus, Prevotella, and Lactobacillus also decreased. The confirmation of whether adjusting the composition of the gut microbiota can improve pregnancy outcomes in patients with AITD is still pending. This article reviews the characteristics of the gut microbiota in patients with AITD and the current research on its impact in pregnancy.