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Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by Intergovernmental Panel on Climate Change (IPCC) assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced RF and the consequent global warming impact (GWIΔα). We then highlight the shortcomings of available current databases and methodologies for calculating GWIΔα at multiple temporal scales. There is a clear lack of comprehensive in situ measurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from earth system models (ESMs) suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWIΔα is substantial, exceeding the RFΔα values of IPCC reports. Inclusion of GWIΔα to landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWIΔα component into future ESMs.

Abstract Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.

Abstract Background Noninvasive prenatal testing (NIPT) is widely used to screen for fetal aneuploidies. However, there are few reports of using NIPT for screening chromosomal microduplications and microdeletions. This study aimed to investigate the application efficiency of NIPT for detecting chromosomal microduplications. Methods Four cases of copy number gains on the long arm of chromosome 17 (17q12) were detected using NIPT and further confirmed using copy number variation (CNV) analysis based on chromosome microarray analysis (CMA). Results The prenatal diagnosis CMA results of the three cases showed that the microduplications in 17q12 (ranging from 1.5 to 1.9 Mb) were consistent with the NIPT results. The karyotypic analysis excluded other possible unbalanced rearrangements. The positive predictive value of NIPT for detecting chromosomal 17q12 microduplication was 75.0%. Conclusions NIPT has a good screening effect on 17q12 syndrome through prenatal diagnosis, therefore it could be considered for screening fetal CNV during the second trimester. With the clinical application of NIPT, invasive prenatal diagnoses could be effectively reduced while also improving the detection rate of fetal CNV.

Abstract Mitochondria are the centers of energy and material metabolism, and they also serve as the storage and dispatch hubs of metal ions. Damage to mitochondrial structure and function can cause abnormal levels and distribution of metal ions, leading to cell dysfunction and even death. For a long time, mitochondrial quality control pathways such as mitochondrial dynamics and mitophagy have been considered to inhibit metal-induced cell death. However, with the discovery of new metal-dependent cell death including ferroptosis and cuproptosis, increasing evidence shows that there is a complex relationship between mitochondrial quality control and metal-dependent cell death. This article reviews the latest research results and mechanisms of crosstalk between mitochondrial quality control and metal-dependent cell death in recent years, as well as their involvement in neurodegenerative diseases, tumors and other diseases, in order to provide new ideas for the research and treatment of related diseases.

Soils store more carbon than other terrestrial ecosystems1,2. How soil organic carbon (SOC) forms and persists remains uncertain1,3, which makes it challenging to understand how it will respond to climatic change3,4. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss5-7. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways4,6,8-11, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes12,13. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved7,14,15. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

AIM: To explore the clinical efficacy and safety of stromal lenticule addition keratoplasty (SLAK) with corneal crosslinking (CXL) on patients with corneal ectasia secondary to femtosecond laser-assisted in situ keratomileusis (FS-LASIK). METHODS: A series of 5 patients undertaking SLAK with CXL for the treatment of corneal ectasia secondary to FS-LASIK were followed for 4-9mo. The lenticules were collected from patients undertaking small incision lenticule extraction (SMILE) for the correction of myopia. Adding a stromal lenticule was aimed at improving the corneal thickness for the safe application of crosslinking and compensating for the thin cornea to improve its mechanical strength. RESULTS: All surgeries were conducted successfully with no significant complications. Their best corrected visual acuity (BCVA) ranged from 0.05 to 0.8-2 before surgery. The pre-operational total corneal thickness ranged from 345-404 μm and maximum keratometry (Kmax) ranged from 50.8 to 86.3. After the combination surgery, both the corneal keratometry (range 55.9 to 92.8) and total corneal thickness (range 413-482 μm) significantly increased. Four out of 5 patients had improvement of corneal biomechanical parameters (reflected by stiffness parameter A1 in Corvis ST). However, 3 patients showed decreased BCVA after surgery due to the development of irregular astigmatism and transient haze. Despite the onset of corneal edema right after SLAK, the corneal topography and thickness generally stabilized after 3mo. CONCLUSION: SLAK with CXL is a potentially beneficial and safe therapy for advanced corneal ectasia. Future work needs to address the poor predictability of corneal refractometry and compare the outcomes of different surgical modes.

Abstract Numerous drivers such as farming practices, erosion, land-use change, and soil biogeochemical background, determine the global spatial distribution of phosphorus (P) in agricultural soils. Here, we revised an approach published earlier (called here GPASOIL-v0), in which several global datasets describing these drivers were combined with a process model for soil P dynamics to reconstruct the past and current distribution of P in cropland and grassland soils. The objective of the present update, called GPASOIL-v1, is to incorporate recent advances in process understanding about soil inorganic P dynamics, in datasets to describe the different drivers, and in regional soil P measurements for benchmarking. We trace the impact of the update on the reconstructed soil P. After the update we estimate a global averaged inorganic labile P of 187 kgP ha−1 for cropland and 91 kgP ha−1 for grassland in 2018 for the top 0–0.3 m soil layer, but these values are sensitive to the mineralization rates chosen for the organic P pools. Uncertainty in the driver estimates lead to coefficients of variation of 0.22 and 0.54 for cropland and grassland, respectively. This work makes the methods for simulating the agricultural soil P maps more transparent and reproducible than previous estimates, and increases the confidence in the new estimates, while the evaluation against regional dataset still suggests rooms for further improvement.

Introduction and Objectives: The increasing incidence of hepatocellular carcinoma (HCC) in China is an urgent issue, necessitating early diagnosis and treatment. This study aimed to develop personalized predictive models by combining machine learning (ML) technology with a demographic, medical history, and noninvasive biomarker data. These models can enhance the decision-making capabilities of physicians for HCC in hepatitis B virus (HBV)-related cirrhosis patients with low serum alpha-fetoprotein (AFP) levels. Patients and Methods: A total of 6,980 patients treated between January 2012 and December 2018 were included. Pre-treatment laboratory tests and clinical data were obtained. The significant risk factors for HCC were identified, and the relative risk of each variable affecting its diagnosis was calculated using ML and univariate regression analysis. The data set was then randomly partitioned into validation (20 %) and training sets (80 %) to develop the ML models. Results: Twelve independent risk factors for HCC were identified using Gaussian naïve Bayes, extreme gradient boosting (XGBoost), random forest, and least absolute shrinkage and selection operation regression models. Multivariate analysis revealed that male sex, age >60 years, alkaline phosphate >150 U/L, AFP >25 ng/mL, carcinoembryonic antigen >5 ng/mL, and fibrinogen >4 g/L were the risk factors, whereas hypertension, calcium 6.8 μmol/L, hemoglobin 40 U/L were the protective factors in HCC patients. Based on these factors, a nomogram was constructed, showing an area under the curve (AUC) of 0.746 (sensitivity = 0.710, specificity=0.646), which was significantly higher than AFP AUC of 0.658 (sensitivity = 0.462, specificity=0.766). Compared with several ML algorithms, the XGBoost model had an AUC of 0.832 (sensitivity = 0.745, specificity=0.766) and an independent validation AUC of 0.829 (sensitivity = 0.766, specificity = 0.737), making it the top-performing model in both sets. The external validation results have proven the accuracy of the XGBoost model. Conclusions: The proposed XGBoost demonstrated a promising ability for individualized prediction of HCC in HBV-related cirrhosis patients with low-level AFP.

Abstract Background The allocation of photosynthate among the parts of plants (e.g., leaves, wood tissues and roots) strongly regulates their growth, and this conditions the terrestrial carbon cycle. Recent studies have shown that atmospheric CO2 and climate change dominate the changes in carbon allocation in plants, but the magnitude and mechanism of its effects remain unclear. Methods The Community Atmosphere Biosphere Land Exchange (CABLE) model can accurately simulate the responses of carbon allocation to environmental changes. This study quantifies the contributions of four environmental factors—atmospheric CO2, temperature, precipitation, and radiation—on resource availability and carbon allocation from 1979 to 2014 by using the CABLE model. Results The results of the CABLE model showed that rising CO2 significantly reduced carbon allocation to the leaves of plants at a global scale, but the other three environmental factors exhibited contrasting effects that dominated the rise in carbon allocation to the leaves. The increased precipitation and CO2 significantly reduced the light availability and increased carbon allocation to the wooden parts of plants. By contrast, the rising temperature reduced the water availability, resulting in a decrease in carbon allocation to the wooden parts. All four environmental factors consistently exhibited negative effects on carbon allocation to the roots, with rising precipitation causing the largest reduction in carbon allocation to them. Moreover, except for CO2, the effects of the other three environmental factors were heterogeneous owing to their variable interactions in different regions. Conclusions The CABLE model can accurately represent the mechanisms of response of resource availability and carbon allocation to environmental changes. Our study highlights the substantial environmental regulation of global carbon allocation. The responses of carbon allocation to global environmental changes need to be extensively studied through ecosystem models based on different hypotheses.

Abstract Introduction The primary objective of this study was to develop an end-to-end model that can accurately identify corneal endothelial cells and diagnose keratoconus based on corneal endothelial images acquired from a non-contact specular microscope. Methods This was a retrospective case–control study performed at the Refractive Surgery Center of West China Hospital. A total of 403 keratoconus eyes (221 patients) and 370 myopic eyes (185 normal controls) were consecutively recruited from January 2021 to September 2022. Specular microscopy was used to image and measure the morphometric parameters of the corneal endothelial cells. A Fully Convolutional Network model with a ResNet50 (FCN_ResNet50) was established to perform the endothelial segmentation. The images were then classified using an ensemble machine learning system consisting of four pre-trained deep learning networks: DenseNet121, ResNet50, Inception_v3, and MobileNet_v2. The performance of the models was evaluated based on different metrics, such as accuracy, intersection over union (IoU), and mean IoU. Results We established a fully end-to-end deep-learning model for the segmentation of endothelial and diagnosis of keratoconus. For endothelial segmentation, the accuracy of the FCN_ResNet50 model achieved near 90% with mean IoU converging to about 80%. The ensemble machine learning system can achieve over 92% accuracy, and > 98% area under curve (AUC) values to diagnose keratoconus with endothelial cell images. In addition, we constructed a diagnostic model based on deep-learning features and developed an associated nomogram which manifested an excellent performance for diagnosis and monitoring the progression of keratoconus. Conclusions Our research developed an end-to-end model to automatically identify and assess corneal endothelial morphological changes in keratoconus eyes. Moreover, we also constructed a novel nomogram, which can provide valuable information for the diagnosis, monitoring, and management of the disease.

AIM: To investigate the relationship between the levels of chemokine receptor 2(CXCR2)and basic fibroblast growth factor(bFGF)in aqueous humor and the prognosis of trabeculectomy in patients with acute primary angle-closure glaucoma(APACG).METHODS: A total of 80 cases(80 eyes)APACG patients who underwent trabeculectomy in our hospital from June 2020 to January 2022 were collected in the case group. According to the postoperative efficacy, they were grouped into a success group of 60 cases(60 eyes)and a failure group of 20 cases(20 eyes). Another 86 cataract patients(86 eyes)who underwent phacoemulsification with normal intraocular pressure in our hospital during the same period were included in the control group. Enzyme linked immunosorbent assay was applied to detect the levels of CXCR2 and bFGF in aqueous humor. ROC curve was applied to analyze the value of predicting trabeculectomy failure in APACG patients by the levels of CXCR2 and bFGF in aqueous humor. Furthermore, multivariate Logistic regression was applied to analyze the influencing factors of trabeculectomy failure in APACG patients.RESULTS: The levels of CXCR2 and bFGF in the aqueous humor of the case group were significantly higher than those of the control group(P

Drilling with prestressed concrete (DPC) pipe pile is a nonsqueezing pile sinking technology, employing drilling, simultaneous pile sinking, a pipe pile protection wall, and pile side grouting. The unloading induced by drilling, the pipe pile supporting effect, and the dissipation of the negative excess pore-water pressure after pile sinking, all of which have significant effects on the recovery of soil pressure on the pile side, are the main concerns of this study, which aim to establish a method to reasonably evaluate the timing selection of pile side grouting. The theoretical solutions for characterizing the unloading and dissipation of the negative excess pore-water pressure are presented based on the cylindrical cavity contraction model and the separated variable method. By inverse-analyzing the measured initial pore pressure change data from borehole unloading, initial soil pressures on the pile side of each soil layer are determined using the presented theoretical solutions. Then, the presented theoretical solutions were verified through a comparative analysis with the corresponding measured results. Moreover, by introducing time-dependent coefficients αt1 and αt2 to characterize the pore pressure dissipation and rheology effects, the effects of the negative excess pore-water pressure dissipation on the pile-side soil pressure recovery are discussed in detail.

Abstract Background Deep learning has been extensively used in digital histopathology. The purpose of this study was to test deep learning (DL) algorithms for predicting the vital status of whole-slide image (WSI) of uveal melanoma (UM). Methods We developed a deep learning model (Google-net) to predict the vital status of UM patients from histopathological images in TCGA-UVM cohort and validated it in an internal cohort. The histopathological DL features extracted from the model and then were applied to classify UM patients into two subtypes. The differences between two subtypes in clinical outcomes, tumor mutation, and microenvironment, and probability of drug therapeutic response were investigated further. Results We observed that the developed DL model can achieve a high accuracy of > = 90% for patches and WSIs prediction. Using 14 histopathological DL features, we successfully classified UM patients into Cluster1 and Cluster2 subtypes. Compared to Cluster2, patients in the Cluster1 subtype have a poor survival outcome, increased expression levels of immune-checkpoint genes, higher immune-infiltration of CD8 + T cell and CD4 + T cells, and more sensitivity to anti-PD-1 therapy. Besides, we established and verified prognostic histopathological DL-signature and gene-signature which outperformed the traditional clinical features. Finally, a well-performed nomogram combining the DL-signature and gene-signature was constructed to predict the mortality of UM patients. Conclusions Our findings suggest that DL model can accurately predict vital status in UM patents just using histopathological images. We found out two subgroups based on histopathological DL features, which may in favor of immunotherapy and chemotherapy. Finally, a well-performing nomogram that combines DL-signature and gene-signature was constructed to give a more straightforward and reliable prognosis for UM patients in treatment and management.

The ocean is a high-quality development strategy critically, promoting economic high-quality development in the ocean is an inevitable choice for building marine powerhouses. In this paper, from the connotation of high-quality marine economic development, based on a new development concept, the entropy weight TOPSIS model was used to evaluate the comprehensive ability of the quality of marine economic development in coastal regions and analyze their regional differences. The empirical results showed that: (1) the top five guideline layer indicators were ranked in order of weight from highest to lowest are: marine science and technology innovation > opening up to the outside > marine economic structure > social welfare > marine ecological environment; (2) The fluctuating and rising level of high-quality development of sea economic in coastal regions during the study period, and the gap in sea economic development quality between provinces (autonomous regions, municipalities) became gradually smaller; (3) Affecting the quality of marine economic development in each subsystem, the northern marine economic circle was at a low level in each of the five subsystem scores. The promotion path for promoting high-quality development of marine economies was proposed: Marine science and technology innovation and marine industry structure upgrade should be developed synergistically, marine ecological and environmental protection policies should be improved, and new patterns should be created to open up.

In recent years, China's marine economy has developed rapidly, but due to the different basis of marine industry in various regions, the quantity and mode of factor investment are also different, especially the ability and efficiency of marine scientific and technological innovation still have great room for improvement. With the help of Entropy TOPSIS method and Three-stage DEA model, this paper measured the ability and efficiency of marine scientific and technological innovation in coastal areas, summarized the characteristics of temporal and spatial differences, and then used Tobit model and grey correlation method to analyze the influencing factors of differences. The results showed that: ① the marine scientific and technological innovation ability of coastal areas showed a "decline-rise-decline" trend. Among them, there was an obvious gap between the marine scientific and technological innovation ability of Beibu Gulf region and the Pearl River Delta and Yangtze River Delta. ② The comprehensive efficiency of marine scientific and technological innovation in the five regions was ranked as Pearl River Delta > Bohai Rim > Yangtze River Delta > West Bank of the Strait > Beibu Gulf. ③ The upgrading index of marine industrial structure had the greatest impact on the development level of marine science and technology innovation, and the impact of marine infrastructure construction was the weakest. There were differences in the contribution of marine science and technology investment to the development level of marine science and technology innovation in different regions. It was suggested to adjust the investment structure of marine science and technology, speed up the construction of marine scientific research talent team, and further improve the ecological environment of marine scientific and technological innovation, so as to improve the ability and efficiency of marine scientific and technological innovation.

AIM: To compare the subjective and objective visual quality between small incision lenticule extraction (SMILE) and transepithelial photorefractive keratectomy (tPRK) in patients with low and moderate myopia. METHODS: Patients undertaking SMILE or tPRK for the correction of low and moderate myopia were consecutively recruited in this prospective cohort study with a 3-month follow-up period. Objective evaluation [visual acuity test, manifest refraction, wavefront aberrations, the total cut-off value of the total modulation transfer function (MTFcut-off), and Strehl ratio (SR)] and subjective evaluation of visual quality (quality-of-life questionnaire) were conducted before surgery and at days 1, 7, 30, and 90 after surgery. RESULTS: A total of 47 patients (94 eyes) with SMILE and 22 patients (22 eyes) with tPRK were enrolled. The uncorrected visual acuity (UCVA) was better in SMILE patients on day 7 after surgery (1.13±0.13 vs 0.99±0.17, t=4.85, P

AbstractBackground Septic shock is the development of sepsis to refractory circulatory collapse and metabolic derangements, characterized by persistent hypotension and increased lactate levels. Anisodamine hydrobromide (Ani HBr) is a Chinese medicine used to improve blood flow in circulatory disorders. The purpose of this study was to determine the therapeutic efficacy of Ani HBr in the treatment of patients with septic shock.Methods This was a prospective, multicenter, randomized controlled trial focusing on patients with septic shock in 16 hospitals in China. Patients were randomly assigned in a 1:1 ratio to either the treatment group or the control group. The primary endpoint was 28-day mortality. The secondary outcomes included 7-day mortality, hospital mortality, hospital length of stay, vasopressor-free days within 7 days, etc. These indicators were measured and collected at 0, 6h, 24h, 48h, 72h and 7d after the diagnosis.Results Between September 2017 and March 2021, 404 subjects were enrolled. 203 subjects received Ani HBr and 201 subjects were assigned to the control group. The treated group showed lower 28-day mortality than the control group. Stratified analysis further showed significant differences in 28-day mortality between the two groups for patients with a high level of illness severity. We also observed significant differences in 7-day mortality, hospital mortality and some other clinical indicators between the two groups.Conclusion Ani HBr might be an important adjuvant to conventional treatment to reduce 28-day mortality in patients with septic shock. A large-scale prospective randomized multicenter trial is warranted to confirm our results.

AbstractWe propose a novel acousto-optic (AO) devise using suspended fishbone nanobeams based on phononic and photonic potential well (PnPW and PtPW). We aim to reduce the traditional device size and eliminate the need for mirror regions in 1-D nanobeam cavity. By manipulating the frequencies of slow sound (SS) and slow light (SL) modes through geometric parameters, we can create potential wells for phonons and photons. The potential wells concentrate the waves inside the resonant cavity simultaneously, leading to an increase in AO coupling rate. We demonstrate the capability of potential wells in improving the AO coupling rate and investigate the impact of both wells. Some distribution of the phonons may affect the photons with a negative contribution, leading to a decrease in the coupling rate. Careful selection of appropriate acoustic and optical modes can overcome this limitation, making this structure a promising candidate for designing AO devices in silicon photonics.

COVID-19 is a respiratory illness caused by a novel coronavirus called SARS-CoV-2. The viral spike (S) protein engages the human angiotensin-converting enzyme 2 (ACE2) receptor to invade host cells with ~10-15-fold higher affinity compared to SARS-CoV S-protein, making it highly infectious. Here, we assessed if ACE2 polymorphisms can alter host susceptibility to SARS-CoV-2 by affecting this interaction. We analyzed over 290,000 samples representing >400 population groups from public genomic datasets and identified multiple ACE2 protein-altering variants. Using reported structural data, we identified natural ACE2 variants that could potentially affect virus-host interaction and thereby alter host susceptibility. These include variants S19P, I21V, E23K, K26R, T27A, N64K, T92I, Q102P and H378R that were predicted to increase susceptibility, while variants K31R, N33I, H34R, E35K, E37K, D38V, Y50F, N51S, M62V, K68E, F72V, Y83H, G326E, G352V, D355N, Q388L and D509Y were predicted to be protective variants that show decreased binding to S-protein. Using biochemical assays, we confirmed that K31R and E37K had decreased affinity, and K26R and T92I variants showed increased affinity for S-protein when compared to wildtype ACE2. Consistent with this, soluble ACE2 K26R and T92I were more effective in blocking entry of S-protein pseudotyped virus suggesting that ACE2 variants can modulate susceptibility to SARS-CoV-2.

In order to cope with the new challenges of marine fishery development, promote the coordinated development of fishery economy and ecological environment, and practice the requirements of comprehensive and coordinated sustainable development, based on the data of coastal provinces and cities from 2009 to 2019, this paper used the stochastic frontier production function and the Thiel index including the ecological environment to quantify the green production efficiency of marine fisheries in China and its regional differences and changes, and conducted regression analysis of its influencing factors. The results showed that: (1) from 2009 to 2019, the green production efficiency of China's marine fisheries showed an upward trend year by year, but the overall level was still not high, and with the gradual improvement of the green production efficiency level of marine fisheries, its growth rate showed a downward trend; (2) the Thiel index decreased year by year, indicating that the regional differences in the green production efficiency of marine fisheries in China were gradually narrowing; (3) the proportion of marine fishery economic output value in regional GDP, the proportion of marine fishing output in seawater product production, and the degree of specialization of fishery practitioners, the funding for the promotion of aquatic technology had a significant positive impact on the green production efficiency of China's marine fisheries, and the loss of aquatic products due to pollution had a negative impact. Accordingly, countermeasures and suggestions such as strengthening the monitoring of marine resources, strengthening the scientific and technological support of marine fisheries, and changing the development mode of fisheries were proposed.