The carbon sequestration capacity in urban agglomeration ecosystems is crucial for enhancing scientific understanding of the carbon cycle and promoting sustainable development to mitigate climate change. However, existing studies on driving factors, particularly regarding determining causal mechanisms and critical thresholds for carbon sequestration in urban agglomeration ecosystems remain unclear. To address this knowledge gap, we propose a CMSC framework which integrates causal inference and machine learning methods to reveal the underlying mechanisms and determine the thresholds of drivers affecting carbon sequestration in the Yangtze River Delta urban agglomeration (YRDUA). The underlying driving mechanisms of carbon sequestration were heterogeneous between municipal county and non-municipal county in YRDUA. The thresholds of nighttime light, surface solar radiation downwards, air temperature, total precipitation and population density that impacted carbon sequestration in non-municipal (municipal) counties of YRDUA were 0.04 (0.4) nW·cm⁻²·sr⁻¹·yr⁻¹, −6.1 × 10⁴ (−5.46 × 10⁴) J·m⁻²·yr⁻¹, 0.013 (0.017) K·yr⁻¹, 3.64 × 10⁻⁵ (2.51 × 10⁻⁵) m·yr⁻¹ and −0.04 people·km⁻²·yr⁻¹, respectively. Furthermore, the long-term (from 2021 to 2100) carbon sequestration dataset with county-level scale in the YRDUA was generated using the causal inference-based machine learning model. In the context of carbon neutrality, we found that the optimal emission scenario for low-carbon sustainable development of YRDUA is SSP3, under which the average carbon sequestration in most counties will exceed 1 × 10⁷ t. Our study provides a constructive basis for a science-based carbon cycle and ecological management in the urban agglomeration of China.

The carbon sequestration capacity in urban agglomeration ecosystems is crucial for enhancing scientific understanding of the carbon cycle and promoting sustainable development to mitigate climate change. However, existing studies on driving factors, particularly regarding determining causal mechanisms and critical thresholds for carbon sequestration in urban agglomeration ecosystems remain unclear. To address this knowledge gap, we propose a CMSC framework which integrates causal inference and machine learning methods to reveal the underlying mechanisms and determine the thresholds of drivers affecting carbon sequestration in the Yangtze River Delta urban agglomeration (YRDUA). The underlying driving mechanisms of carbon sequestration were heterogeneous between municipal county and non-municipal county in YRDUA. The thresholds of nighttime light, surface solar radiation downwards, air temperature, total precipitation and population density that impacted carbon sequestration in non-municipal (municipal) counties of YRDUA were 0.04 (0.4) nW·cm⁻²·sr⁻¹·yr⁻¹, −6.1 × 10⁴ (−5.46 × 10⁴) J·m⁻²·yr⁻¹, 0.013 (0.017) K·yr⁻¹, 3.64 × 10⁻⁵ (2.51 × 10⁻⁵) m·yr⁻¹ and −0.04 people·km⁻²·yr⁻¹, respectively. Furthermore, the long-term (from 2021 to 2100) carbon sequestration dataset with county-level scale in the YRDUA was generated using the causal inference-based machine learning model. In the context of carbon neutrality, we found that the optimal emission scenario for low-carbon sustainable development of YRDUA is SSP3, under which the average carbon sequestration in most counties will exceed 1 × 10⁷ t. Our study provides a constructive basis for a science-based carbon cycle and ecological management in the urban agglomeration of China.

The data is the source for all the figures and tables.

The data is the source for all the figures and tables.

Chronic kidney disease (CKD) and diabetes mellitus increase atherosclerotic cardiovascular diseases (ASCVD) risk. However, the association between renal outcome of diabetic kidney disease (DKD) and ASCVD risk is unclear. This retrospective study enrolled 218 type 2 diabetic patients with biopsy-proven DKD, and without known cardiovascular diseases. Baseline characteristics were obtained and the 10-year ASCVD risk score was calculated using the Pooled Cohort Equation (PCE). Renal outcome was defined as progression to end-stage renal disease (ESRD). The association between ASCVD risk and renal function and outcome was analyzed with logistic regression and Cox analysis. Among all patients, the median 10-year ASCVD risk score was 14.1%. The median of ASCVD risk score in CKD stage 1, 2, 3, and 4 was 10.9%, 12.3%, 16.5%, and 14.8%, respectively (p = 0.268). Compared with patients with lower ASCVD risk (＜14.1%), those with higher ASCVD risk had lower eGFR, higher systolic blood pressure, and more severe renal interstitial inflammation. High ASCVD risk (>14.1%) was an independent indicator of renal dysfunction in multivariable-adjusted logistic analysis (OR, 3.997; 95%CI, 1.385–11.530; p = 0.010), though failed to be an independent risk factor for ESRD in patients with DKD in univariate and multivariate Cox analysis. DKD patients even in CKD stage 1 had comparable ASCVD risk score to patients in CKD stage 2, 3, and 4. Higher ASCVD risk indicated severe renal insufficiency, while no prognostic value of ASVCD risk for renal outcome was observed, which implied macroangiopathy and microangiopathy in patients with DKD were related, but relatively independent.

Chronic kidney disease (CKD) and diabetes mellitus increase atherosclerotic cardiovascular diseases (ASCVD) risk. However, the association between renal outcome of diabetic kidney disease (DKD) and ASCVD risk is unclear. This retrospective study enrolled 218 type 2 diabetic patients with biopsy-proven DKD, and without known cardiovascular diseases. Baseline characteristics were obtained and the 10-year ASCVD risk score was calculated using the Pooled Cohort Equation (PCE). Renal outcome was defined as progression to end-stage renal disease (ESRD). The association between ASCVD risk and renal function and outcome was analyzed with logistic regression and Cox analysis. Among all patients, the median 10-year ASCVD risk score was 14.1%. The median of ASCVD risk score in CKD stage 1, 2, 3, and 4 was 10.9%, 12.3%, 16.5%, and 14.8%, respectively (p = 0.268). Compared with patients with lower ASCVD risk (＜14.1%), those with higher ASCVD risk had lower eGFR, higher systolic blood pressure, and more severe renal interstitial inflammation. High ASCVD risk (>14.1%) was an independent indicator of renal dysfunction in multivariable-adjusted logistic analysis (OR, 3.997; 95%CI, 1.385–11.530; p = 0.010), though failed to be an independent risk factor for ESRD in patients with DKD in univariate and multivariate Cox analysis. DKD patients even in CKD stage 1 had comparable ASCVD risk score to patients in CKD stage 2, 3, and 4. Higher ASCVD risk indicated severe renal insufficiency, while no prognostic value of ASVCD risk for renal outcome was observed, which implied macroangiopathy and microangiopathy in patients with DKD were related, but relatively independent.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

The Triassic eastern Tethyan faunas have continued to yield numerous specimens of marine reptile taxa in recent years. Nevertheless, compared with other sauropterygian clades, the diversity of placodonts in these faunas is low, and remains of this group are relatively rare in the fossil assemblages. Here, we report a new cyamodontoid specimen (ZMNH M8820) from the early Late Triassic of Guizhou, south-west China. This specimen is a nearly complete skeleton lacking only the forelimbs. It is distinct from other known Chinese placodonts as it features a large skull with remarkably enlarged supratemporal fenestrae and a small and less regularly arranged carapace. Interestingly, this new specimen resembles the European Cyamodus more than any Chinese cyamodontoid genera, particularly when considering the dentition and other cranial morphology. However, it differs from known Cyamodus species in some cranial features (e.g. epipterygoid fully ossified, posttemporal fenestra large, dentition derived) and the absence of a separate pelvic shield. Furthermore, based on an updated data matrix of placodonts, our phylogenetic results support the affinity of this new Chinese specimen with European Cyamodus species, and a new species, Cyamodus orientalis sp. nov., is erected here. This new material represents the first reported Cyamodus specimen in the world that preserves a three-dimensional skull with an associated postcranial skeleton and it extends the distribution of this genus into the early Carnian of the eastern Tethys. The existence of Cyamodus, a nearshore taxon, in south-west China at this time reveals greater similarity and more rapid intercommunication than previously known between western and eastern Tethyan vertebrate faunas, although the palaeobiogeographical origin and migration history of Cyamodontidae – and of other clades of placodont reptiles – are still obscure due to the scarcity of material from the northern and southern margins of the Palaeotethys. http://zoobank.org/urn:lsid:zoobank.org:pub:DE6946AD-B4F4-4FC0-AD2F-C5DB2903876D