Borane-Catalyzed Coupling of Diazooxindoles and Difluoroenoxysilanes to Tetrasubstituted Monofluoroalkenes.

A highly stereoselective coupling reaction of diazooxindoles with difluoroenoxysilanes catalyzed by Lewis acidic boranes has been developed. The reaction proceeded at ambient temperature under transition metal-free conditions with wide functional group tolerance. By using this simple procedure, a series of tetrasubstituted monofluoroalkenes can be accessed in good yield with high selectivity.

Maximizing carbon sequestration potential in Chinese forests through optimal management.

Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1-3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

Long-term warming increased carbon sequestration capacity in a humid subtropical forest.

Tropical and subtropical forests play a crucial role in global carbon (C) pools, and their responses to warming can significantly impact C-climate feedback and predictions of future global warming. Despite earth system models projecting reductions in land C storage with warming, the magnitude of this response varies greatly between models, particularly in tropical and subtropical regions. Here, we conducted a field ecosystem-level warming experiment in a subtropical forest in southern China, by translocating mesocosms (ecosystem composed of soils and plants) across 600 m elevation gradients with temperature gradients of 2.1°C (moderate warming), to explore the response of ecosystem C dynamics of the subtropical forest to continuous 6-year warming. Compared with the control, the ecosystem C stock decreased by 3.8% under the first year of 2.1°C warming; but increased by 13.4% by the sixth year of 2.1°C warming. The increased ecosystem C stock by the sixth year of warming was mainly attributed to a combination of sustained increased plant C stock due to the maintenance of a high plant growth rate and unchanged soil C stock. The unchanged soil C stock was driven by compensating and offsetting thermal adaptation of soil microorganisms (unresponsive soil respiration and enzyme activity, and more stable microbial community), increased plant C input, and inhibitory C loss (decreased C leaching and inhibited temperature sensitivity of soil respiration) from soil drying. These results suggest that the humid subtropical forest C pool would not necessarily diminish consistently under future long-term warming. We highlight that differential and asynchronous responses of plant and soil C processes over relatively long-term periods should be considered when predicting the effects of climate warming on ecosystem C dynamics of subtropical forests.

Climate change-related biodiversity fluctuations and composition changes in an old-growth subtropical forest: A 26-yr study.

The detection and attribution of biodiversity change is of great scientific interest and central to policy effects aimed at meeting biodiversity targets. Yet, how such a diverse climate scenarios influence forest biodiversity and composition dynamics remains unclear, particularly in high diversity systems of subtropical forests. Here we used data collected from the permanent sample plot spanning 26 years in an old-growth subtropical forest. Combining various climatic events (extreme drought, subsequent drought, warming, and windstorm), we analyzed long-term dynamics in multiple metrics: richness, turnover, density, abundance, reordering and stability. We did not observe consistent and directional trends in species richness under various climatic scenarios. Still, drought and windstorm events either reduced species gains or increased species loss, ultimately increased species turnover. Tree density increased significantly over time as a result of rapid increase in smaller individuals due to mortality in larger trees. Climate events caused rapid changes in dominant populations due to a handful of species undergoing strong increases or declines in abundance over time simultaneously. Species abundance composition underwent significant changes, particularly in the presence of drought and windstorm events. High variance ratio and species synchrony weaken community stability under various climate stress. Our study demonstrates that all processes underlying forest community composition changes often occur simultaneously and are equally affected by climate events, necessitating a holistic approach to quantifying community changes. By recognizing the interconnected nature of these processes, future research should accelerate comprehensive understanding and predicting of how forest vegetation responds to global climate change.

Rising rainfall intensity induces spatially divergent hydrological changes within a large river basin.

Droughts or floods are usually attributed to precipitation deficits or surpluses, both of which may become more frequent and severe under continued global warming. Concurring large-scale droughts in the Southwest and flooding in the Southeast of China in recent decades have attracted considerable attention, but their causes and interrelations are not well understood. Here, we examine spatiotemporal changes in hydrometeorological variables and investigate the mechanism underlying contrasting soil dryness/wetness patterns over a 54-year period (1965-2018) across a representative mega-watershed in South China-the West River Basin. We demonstrate that increasing rainfall intensity leads to severe drying upstream with decreases in soil water storage, water yield, and baseflow, versus increases therein downstream. Our study highlights a simultaneous occurrence of increased drought and flooding risks due to contrasting interactions between rainfall intensification and topography across the river basin, implying increasingly vulnerable water and food security under continued climate change.

Development and Clinical Application of Artificial Intelligence Assistant System for Rotator Cuff Ultrasound Scanning.

OBJECTIVE: We developed an intelligent assistance system for shoulder ultrasound imaging, incorporating deep-learning algorithms to facilitate standard plane recognition and automatic tissue segmentation of the rotator cuff and its surrounding structures. We evaluated the system's performance using a dedicated data set of rotator cuff ultrasound images to assess its feasibility in clinical practice. METHODS: To fulfill the system's primary functions, we designed a standard plane recognition module based on the ResNet50 network and an automatic tissue segmentation module using the Mask R-CNN model. The modules were trained on carefully curated data sets. The standard plane recognition module automatically identifies a specific standard plane based on the ultrasound image characteristics. The automatic tissue segmentation module effectively delineates and segments anatomical structures within the identified standard plane. RESULTS: With the use of 59,265 shoulder joint ultrasound images, the standard plane recognition model achieved an impressive recognition accuracy of 94.9% in the test set, with an average precision rate of 96.4%, recall rate of 95.4% and F1 score of 95.9%. The automatic tissue segmentation model, tested on 1886 images, exhibited a commendable average intersection over union value of 96.2%, indicating robustness and accuracy. The model achieved mean intersection over union values exceeding 90.0% for all standard planes, indicating its effectiveness in precisely delineating the anatomical structures. CONCLUSION: Our shoulder joint musculoskeletal intelligence system swiftly and accurately identifies standard planes and performs automatic tissue segmentation.

Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

Acidity of Soil and Water Decreases in Acid-Sensitive Forests of Tropical China.

Acid deposition in China has been declining since the 2000s. While this may help mitigate acidification in forest soils and water, little is known about the recovery of soils and water from previous severe acidification in tropical China. Here, we assessed the chemistry of mineral soils, water, and acid gases (SO2 and NOx) from three successional forest types in tropical China from 2000 to 2022. Our results showed that soil pH increased synchronously from 3.9 (2000-2015) to 4.2 (2016-2022) across all three forest types, with exchangeable acid initially decreasing and thereafter stabilizing. Surface and ground water pH also gradually increased throughout the monitoring period. Soil pH recovery was stronger in the primary than in the planted forest. However, soil pH recovery lagged behind the increase in rainfall pH by approximately a decade. The recovery of soil pH was likely related to the positive effects of the dissolution of Al/Fe-hydroxysulfate mineral and subsequent sulfur desorption on soil acid-neutralizing capacity, increased soil organic matter, and climate warming, but was likely moderated by increased exchangeable aluminum and potentially proton-producing hydroxysulfate mineral dissolution that caused the lagged soil pH recovery. Surface and ground water pH recovery was attributed to increased water acid-neutralizing capacity. Our study reports the potential for the recovery of acidified soil and water following decreased acid deposition and provides new insights into the functional recovery of acid-sensitive forests.

Ultrasound identification of hepatic echinococcosis using a deep convolutional neural network model in China: a retrospective, large-scale, multicentre, diagnostic accuracy study.

BACKGROUND: Ultrasonography is the most widely used technique to diagnose echinococcosis; however, challenges in using this technique and the demand on medical resources, especially in low-income or remote areas, can delay diagnosis. We aimed to develop a deep convolutional neural network (DCNN) model based on ultrasonography to identify echinococcosis and its types, especially alveolar echinococcosis. METHODS: This retrospective, large-scale, multicentre study used ultrasound images from patients assessed at 84 hospitals in China, obtained between Jan 1, 2002, and Dec 31, 2021. Patients with a diagnosis of cystic echinococcosis, alveolar echinococcosis, or seven other types of focal liver lesions were included. We tested ResNet-50, ResNext-50, and VGG-16 as the backbone network architecture for a classification DCNN model and input the perinodular information from the ultrasound images. We trained and validated the DCNN model to diagnose and classify echinococcosis using still greyscale ultrasound images of focal liver lesions in four stages: differentiating between echinococcosis and other focal liver lesions (stage one); differentiating cystic echinococcosis, alveolar echinococcosis, and other focal liver lesions (stage two); differentiating cystic echinococcosis, alveolar echinococcosis, benign other focal liver lesions, and malignant focal liver lesions (stage three); and differentiating between active and transitional cystic echinococcosis and inactive cystic echinococcosis (stage four). We then tested the algorithm on internal, external, and prospective test datasets. The performance of DCNN was also compared with that of 12 radiologists recruited between Jan 15, 2022, and Jan 28, 2022, from Qinghai, Xinjiang, Anhui, Henan, Xizang, and Beijing, China, with different levels of diagnostic experience for echinococcosis and other focal liver lesions in a subset of ultrasound data that were randomly chosen from the prospective test dataset. The study is registered at ClinicalTrials.gov (NCT03871140). FINDINGS: The study took place between Jan 1, 2002, and Dec 31, 2021. In total, to train and test the DCNN model, we used 9631 liver ultrasound images from 6784 patients (2819 [41·7%] female patients and 3943 [58·3%] male patients) from 87 Chinese hospitals. The DCNN model was trained with 6328 images, internally validated with 984 images, and tested with 2319 images. The ResNet-50 network architecture outperformed VGG-16 and ResNext-50 and was generalisable, with areas under the receiver operating characteristic curve (AUCs) of 0·982 (95% CI 0·960-0·994), 0·984 (0·972-0·992), and 0·913 (0·886-0·935) in distinguishing echinococcosis from other focal liver lesions; 0·986 (0·966-0·996), 0·962 (0·946-0·975), and 0·900 (0·872-0·924) in distinguishing alveolar echinococcosis from cystic echinococcosis and other focal liver lesions; and 0·974 (0·818-1·000), 0·956 (0·875-0·991), and 0·944 (0·844-0·988) in distinguishing active and transitional cystic echinococcosis from inactive echinococcosis in the three test datasets. Specifically, in patients with the hepatitis B or hepatitis C virus, the model could distinguish alveolar echinococcosis from hepatocellular carcinoma with an AUC of 0·892 (0·812-0·946). In identifying echinococcosis, the model showed significantly better performance compared with senior radiologists from a high-endemicity area (AUC 0·942 [0·904-0·967] vs 0·844 [0·820-0·866]; p=0·027) and improved the diagnostic ability of junior, attending, and senior radiologists before and after assistance with AI with comparison of AUCs of 0·743 (0·714-0·770) versus 0·850 (0·826-0·871); p<0·0001, 0·808 (0·782-0·832) versus 0·886 (0·864-0·905); p<0·0001, and 0·844 (0·820-0·866) versus 0·870 (0·847-0·890); p=0·092, respectively. INTERPRETATION: The DCNN model was shown to be accurate and robust, and could improve the ultrasound diagnostic ability of radiologists for echinococcosis and its types for highly endemic and remote regions. FUNDING: National Natural Science Foundation of China and National Key Research & Development Program of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Safety profile of 0.0015% tafluprost eye drops in China: a post-marketing observational study.

AIM: To investigate the treatment pattern and safety of tafluprost for glaucoma and ocular hypertension (OH) in clinical practice in China. METHODS: This post-marketing observational study included patients who received tafluprost to lower intraocular pressure (IOP) within 30d between September 2017 and March 2020 in 20 hospitals in China. Adverse drug reactions (ADRs) during tafluprost treatment and within 30d after the treatment were collected. RESULTS: A total of 2544 patients were included in this study, of them 58.5% (1488/2544) had primary open angle glaucoma (POAG), 21.9% (556/2544) had OH and 19.7% (500/2544) used tafluprost for other reasons. Of 359 ADRs occurred in 10.1% (258/2544) patients, and no serious adverse event occurred. The most common ADR was conjunctival hyperemia (128 ADRs in 124 patients, 4.9%). Totally 1670 participants (65.6%) combined tafluprost with carbonic anhydrase inhibitors (CAIs; 37.1%, 620/1670), sympathomimetics (33.5%, 559/1670), ß-blockers (33.2%, 555/1670), other prostaglandin analogs (PGAs; 15.6%, 260/1670) and other eye drops (15.1%, 253/1670). The highest incidence of conjunctival hyperemia was noted in patients who received tafluprost in combination with other PGAs (23 ADRs in 23 patients, 8.8%, 23/260) and the lowest was in combination with CAIs (16 ADRs in 16 patients, 2.6%, 16/620). Tafluprost was applied in primary angle-closure glaucoma (41.6%, 208/500), after glaucoma surgery (17.8%, 89/500) and after non-glaucoma surgery (15.8%, 79/500). CONCLUSION: Tafluprost is safe for POAG and OH, and tolerable when combined with other eye drops and under various clinical circumstances.

Predicting ecosystem productivity based on plant community traits.

With the rapid accumulation of plant trait data, major opportunities have arisen for the integration of these data into predicting ecosystem primary productivity across a range of spatial extents. Traditionally, traits have been used to explain physiological productivity at cell, organ, or plant scales, but scaling up to the ecosystem scale has remained challenging. Here, we show the need to combine measures of community-level traits and environmental factors to predict ecosystem productivity at landscape or biogeographic scales. We show how theory can extend the production ecology equation to enormous potential for integrating traits into ecological models that estimate productivity-related ecosystem functions across ecological scales and to anticipate the response of terrestrial ecosystems to global change.

Forest expansion dominates China's land carbon sink since 1980.

Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased China's reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9 ± 0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting.

Tree species richness as an important biotic factor regulates the soil phosphorus density in China's mature natural forests.

Tree species richness has been recognized as an underlying driving factor for regulating soil phosphorus (P) status in many site-specific studies. However, it remains poorly understood whether this is true at broad scales where soil P strongly rely on climate, soil type and vegetation type. Here, based on the data of 946 mature natural forest sites from a nationwide field survey in China, we analyzed the impact of tree species richness on soil P density of China's mature natural forests (deciduous coniferous forest, DCF; evergreen coniferous forest, ECF; deciduous broad-leaved forest, DBF; evergreen broad-leaved forest, EBF; and mixed coniferous and broad-leaved forest, MF). Our results showed that tree species richness had a negative effect on soil P density in China's mature natural forests. The Random Forest regression model showed that the relative importance of tree species richness to soil P density was second only to the climate factors (mean annual temperature, MAT; mean annual precipitation, MAP). In addition, the structural equation model (SEM) results showed that the goodness fit of SEM increased when the tree species richness was included into the model. These results suggested that tree species richness was an important factor in regulating the China's mature natural forests soil P density. Furthermore, the SEM results showed that the decreased soil P density was related to the increase in ANPP and the decrease in litter P concentration induced by tree species richness. This result indicates that tree species richness could facilitate plant P absorption and inhibit plant P return into the soil, and thus reducing the soil P density in China's mature natural forests. In conclusion, we found tree species richness was an important biotic factor in regulating soil P density at broad scales, which should be fully considered in Earth models that represent P cycle.

Glymphatic System: Emerging Therapeutic Target for Neurological Diseases.

The newly discovered glymphatic system acts as pseudolymphatic vessels subserving brain waste clearance and is functionally dependent on astrocytic aquaporin-4 channels. The glymphatic system primarily functions during sleep as an interchange between cerebrospinal fluid and interstitial fluid, with cerebrospinal fluid flowing into the parenchyma via the perivascular spaces and then exchanging with interstitial fluid. The discovery of meningeal lymphatics helps refine the conceptual framework of glymphatic pathway, as certain waste products collected alongside perivascular spaces ultimately drain into the cervical lymph nodes via meningeal lymphatics, whose function regulates the functioning of the glymphatic system. The glymphatic and meningeal lymphatic systems are critical for the homeostasis of central nervous system, and their malfunctions complicate cerebral dysfunction and diseases. The present review will shed light on the structure, regulation, functions, and interrelationships of the glymphatic system and meningeal lymphatics. We will also expound on their impairments and corresponding targeted intervention in neurodegenerative diseases, traumatic brain injury, stroke, and infectious/autoimmune diseases, offering valuable references for future research.

Warming drives sustained plant phosphorus demand in a humid tropical forest.

Phosphorus (P) is often one of the most limiting nutrients in highly weathered soils of humid tropical forests and may regulate the responses of carbon (C) feedback to climate warming. However, the response of P to warming at the ecosystem level in tropical forests is not well understood because previous studies have not comprehensively assessed changes in multiple P processes associated with warming. Here, we detected changes in the ecosystem P cycle in response to a 7-year continuous warming experiment by translocating model plant-soil ecosystems across a 600-m elevation gradient, equivalent to a temperature change of 2.1°C. We found that warming increased plant P content (55.4%) and decreased foliar N:P. Increased plant P content was supplied by multiple processes, including enhanced plant P resorption (9.7%), soil P mineralization (15.5% decrease in moderately available organic P), and dissolution (6.8% decrease in iron-bound inorganic P), without changing litter P mineralization and leachate P. These findings suggest that warming sustained plant P demand by increasing the biological and geochemical controls of the plant-soil P-cycle, which has important implications for C fixation in P-deficient and highly productive tropical forests in future warmer climates.

Retention of deposited ammonium and nitrate and its impact on the global forest carbon sink.

The impacts of enhanced nitrogen (N) deposition on the global forest carbon (C) sink and other ecosystem services may depend on whether N is deposited in reduced (mainly as ammonium) or oxidized forms (mainly as nitrate) and the subsequent fate of each. However, the fates of the two key reactive N forms and their contributions to forest C sinks are unclear. Here, we analyze results from 13 ecosystem-scale paired 15N-labelling experiments in temperate, subtropical, and tropical forests. Results show that total ecosystem N retention is similar for ammonium and nitrate, but plants take up more labelled nitrate ([Formula: see text]%) ([Formula: see text]) than ammonium ([Formula: see text]%) while soils retain more ammonium ([Formula: see text]%) than nitrate ([Formula: see text]%). We estimate that the N deposition-induced C sink in forests in the 2010s  is [Formula: see text] Pg C yr-1, higher than previous estimates because of a larger role for oxidized N and greater rates of global N deposition.

Nitrogen deposition accelerates soil carbon sequestration in tropical forests.

Terrestrial ecosystem carbon (C) sequestration plays an important role in ameliorating global climate change. While tropical forests exert a disproportionately large influence on global C cycling, there remains an open question on changes in below-ground soil C stocks with global increases in nitrogen (N) deposition, because N supply often does not constrain the growth of tropical forests. We quantified soil C sequestration through more than a decade of continuous N addition experiment in an N-rich primary tropical forest. Results showed that long-term N additions increased soil C stocks by 7 to 21%, mainly arising from decreased C output fluxes and physical protection mechanisms without changes in the chemical composition of organic matter. A meta-analysis further verified that soil C sequestration induced by excess N inputs is a general phenomenon in tropical forests. Notably, soil N sequestration can keep pace with soil C, based on consistent C/N ratios under N additions. These findings provide empirical evidence that below-ground C sequestration can be stimulated in mature tropical forests under excess N deposition, which has important implications for predicting future terrestrial sinks for both elevated anthropogenic CO2 and N deposition. We further developed a conceptual model hypothesis depicting how soil C sequestration happens under chronic N deposition in N-limited and N-rich ecosystems, suggesting a direction to incorporate N deposition and N cycling into terrestrial C cycle models to improve the predictability on C sink strength as enhanced N deposition spreads from temperate into tropical systems.

Spatial distribution patterns of soil total phosphorus influenced by climatic factors in China's forest ecosystems.

Phosphorus (P) is an important element in terrestrial ecosystems and plays a critical role in soil quality and ecosystem productivity. Soil total P distributions have undergone large spatial changes as a result of centuries of climate change. It is necessary to study the characteristics of the horizontal and vertical distributions of soil total P and its influencing factors. In particular, the influence of climatic factors on the spatial distribution of soil total P in China's forest ecosystems remain relatively unknown. Here, we conducted an intensive field investigation in different forest ecosystems in China to assess the effect of climatic factors on soil total P concentration and distribution. The results showed that soil total P concentration significantly decreased with increasing soil depth. The spatial distribution of soil total P increased with increasing latitude and elevation gradient but decreased with increasing longitude gradient. Random forest models and linear regression analyses showed that the explanation rate of bioclimatic factors and their relationship with soil total P concentration gradually decreased with increasing soil depths. Variance partitioning analysis demonstrated that the most important factor affecting soil total P distribution was the combined effect of temperature and precipitation factor, and the single effect of temperature factors had a higher explanation rate compare with the single effect of precipitation factors. This work provides a new farmework for the geographic distribution pattern of soil total P and the impact of climate variability on P distribution in forest ecosystems.