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In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
The damage characteristics of fused silica were investigated under low-temporal coherence light (LTCL). It was found that the laser-induced damage threshold (LIDT) of fused silica for the LTCL was lower than that of the single longitudinal mode pulse laser, and for the LTCLs, the LIDTs decrease with the increasing of laser bandwidth, which is not consistent with the temporal spike intensity. This is due to the nonlinear self-focusing effect and multi-pulse accumulation effect. The specific reasons were analyzed based on theoretical simulation and experimental study. This research work is helpful and of great significance for the construction of high-power LTCL devices.
Creating an environmentally friendly precursor to form a kaolinite intercalation compound is important for promoting the applications of nanohybrid kaolinite in electrochemical sensors, low- or zero-toxicity drug carriers, and clay-polymer nanocompounds. In the present study, a stable hydrated kaolinite pre-cursor with d001= 0.84 nm was prepared successfully by heating the transition phase, the as-prepared kaolinite-hydrazine intercalate, at temperatures between 40 and 70ºC. The structure of the hydrated kaolinite was characterized by X-ray diffraction and infrared spectroscopy. The morphology was examined using scanning electron microscopy. The results showed that the hydrated hydrazine of the transition phase was easy to decompose to hydrazines and water molecules in the interlayer at 40-70ºC. Hydrazine molecules de-intercalated gradually, and water molecules remained in the ditrigonal holes of the silicate layer with sufficient stability, finally forming the stable 0.84 nm hydrated kaolinite in the system with a success rate of 80–90%. The 0.84 nm hydrated kaolinite may become an excellent precursor for the preparation of other kaolinite intercalates. A degree of intercalation of ~100% was obtained for the kaolinite-ethylene glycol intercalate, and a degree of intercalation of ~80% was obtained for the kaolinite-glycine intercalate from the 0.84 nm hydrated kaolinite precursor.
There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.
Methods
In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.
Results
In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.
Conclusions
These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.
Two-dimensional simulations are conducted to investigate the direct initiation of cylindrical detonation in hydrogen/air mixtures with detailed chemistry. The effects of hotspot condition and mixture composition gradient on detonation initiation are studied. Different hotspot pressures and compositions are first considered in the uniform mixture. It is found that detonation initiation fails for low hotspot pressures and the critical regime dominates with high hotspot pressures. Detonation is directly initiated from the reactive hotspot, whilst it is ignited somewhere beyond the non-reactive hotspots. Two cell diverging patterns (i.e. abrupt and gradual) are identified and the detailed mechanisms are analysed. Moreover, cell coalescence occurs if many irregular cells are generated initially, which promotes the local cell growth. We also consider non-uniform detonable mixtures. The results show that the initiated detonation experiences self-sustaining propagation, highly unstable propagation and extinction in mixtures with a linearly decreasing equivalence ratio along the radial direction, i.e. 1 → 0.9, 1 → 0.5 and 1 → 0. Moreover, the hydrodynamic structure analysis shows that, for the self-sustaining detonations, the hydrodynamic thickness increases at the overdriven stage, decreases as the cells are generated and eventually becomes almost constant at the cell diverging stage, within which the sonic plane shows a ‘sawtooth’ pattern. However, in the detonation extinction cases, the hydrodynamic thickness continuously increases, and no ‘sawtooth’ sonic plane can be observed.
The rearrangement of drainage basins provides critical insight into crustal deformation and geodynamic mechanisms. Near the southeastern boundary of the Tibetan Plateau, the Dadu River abruptly shifts from south- to east-flowing, providing important implications for regional tectonogeomorphic development since the mid-Pleistocene. South of the bend, the headwaters of the Anning River occupy an unusually wide valley. Field investigations show that large quantities of fluvial/lacustrine sediments are widespread along the Dadu and Anning rivers and are exposed at their drainage divide. Detrital zircon U-Pb age patterns confirm that these fluvial/lacustrine sediments are the remnants of the paleo-Dadu River, which strongly suggests that the paleo-Dadu River originally flowed southward into the Anning River. The cosmogenic nuclide burial ages of the lacustrine sediments along the Dadu and Anning rivers suggest deposition of these sediments from separate dammed lakes ca. 1.2 Ma ago, ca. 0.6 Ma ago, and ca. 0.9 Ma ago from north to south, respectively. Provenance and burial-age studies indicate that reorganization of the Dadu drainage occurred within the last 0.6 Ma. We propose that this drainage reorganization in southeastern Tibet resulted from progressive convergence between the India and Eurasian plates during the Pleistocene.
Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders.
Methods
Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed.
Results
Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network.
Conclusions
These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.
Many protected areas worldwide have been established to protect the last natural refuges of flagship animal species. However, long-established protected areas do not always match the current distributions of target species under changing environmental conditions. Here we present a case study of the Asian elephant Elephas maximus in Xishuangbanna, south-west China, to evaluate whether the established protected areas match the species’ current distribution and to identify key habitat patches for Asian elephant conservation. Our results show that currently only 24.5% of the predicted Asian elephant distribution in Xishuangbanna is located within Xishuangbanna National Nature Reserve, which was established for elephant conservation. Based on the predicted Asian elephant distribution, we identified the most important habitat patches for elephant conservation in Xishuangbanna. The three most important patches were outside Xishuangbanna National Nature Reserve and together they contained 43.3% of the estimated food resources for Asian elephants in all patches in Xishuangbanna. Thus, we identified a spatial mismatch between immobile protected areas and mobile animals. We recommend the inclusion of the three identified key habitat patches in a new national park currently being planned by the Chinese authorities for the conservation of the Asian elephant.
COVID-19 has long-term impacts on public mental health, while few research studies incorporate multidimensional methods to thoroughly characterise the psychological profile of general population and little detailed guidance exists for mental health management during the pandemic. This research aims to capture long-term psychological profile of general population following COVID-19 by integrating trajectory modelling approaches, latent trajectory pattern identification and network analyses.
Methods
Longitudinal data were collected from a nationwide sample of 18 804 adults in 12 months after COVID-19 outbreak in China. Patient Health Questionnaire-9, Generalised Anxiety Disorder-7 and Insomnia Severity Index were used to measure depression, anxiety and insomnia, respectively. The unconditional and conditional latent growth curve models were fitted to investigate trajectories and long-term predictors for psychological symptoms. We employed latent growth mixture model to identify the major psychological symptom trajectory patterns, and ran sparse Gaussian graphical models with graphical lasso to explore the evolution of psychopathological network.
Results
At 12 months after COVID-19 outbreak, psychological symptoms generally alleviated, and five psychological symptom trajectories with different demographics were identified: normal stable (63.4%), mild stable (15.3%), mild-increase to decrease (11.7%), mild-decrease to increase (4.0%) and moderate/severe stable (5.5%). The finding indicated that there were still about 5% individuals showing consistently severe distress and approximately 16% following fluctuating psychological trajectories, who should be continuously monitored. For individuals with persistently severe trajectories and those with fluctuating trajectories, central or bridge symptoms in the network were mainly ‘motor abnormality’ and ‘sad mood’, respectively. Compared with initial peak and late COVID-19 phase, aftermath of initial peak might be a psychologically vulnerable period with highest network connectivity. The central and bridge symptoms for aftermath of initial peak (‘appetite change’ and ‘trouble of relaxing’) were totally different from those at other pandemic phases (‘sad mood’).
Conclusions
This research identified the overall growing trend, long-term predictors, trajectory classes and evolutionary pattern of psychopathological network of psychological symptoms in 12 months after COVID-19 outbreak. It provides a multidimensional long-term psychological profile of the general population after COVID-19 outbreak, and accentuates the essentiality of continuous psychological monitoring, as well as population- and time-specific psychological management after COVID-19. We believe our findings can offer reference for long-term psychological management after pandemics.
Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis.
Methods
T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges.
Results
As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms.
Conclusions
In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.
The role of dietary factors in osteoporotic fractures (OFs) in women is not fully elucidated. We investigated the associations between incidence of OF and dietary calcium, magnesium and soy isoflavone intake in a longitudinal study of 48 584 postmenopausal women. Multivariable Cox regression was applied to derive hazard ratios (HRs) and 95 % confidence intervals (CIs) to evaluate associations between dietary intake, based on the averages of two assessments that took place with a median interval of 2⋅4 years, and fracture risk. The average age of study participants is 61⋅4 years (range 43⋅3–76⋅7 years) at study entry. During a median follow-up of 10⋅1 years, 4⋅3 % participants experienced OF. Compared with daily calcium intake ≤400 mg/d, higher calcium intake (>400 mg/d) was significantly associated with about a 40–50 % reduction of OF risk among women with a calcium/magnesium (Ca/Mg) intake ratio ≥1⋅7. Among women with prior fracture history, high soy isoflavone intake was associated with reduced OF risk; the HR was 0⋅72 (95 % CI 0⋅55, 0⋅93) for the highest (>42⋅0 mg/d) v. lowest (<18⋅7 mg/d) quartile intake. This inverse association was more evident among recently menopausal women (<10 years). No significant association between magnesium intake and OF risk was observed. Our findings provide novel information suggesting that the association of OF risk with dietary calcium intake was modified by Ca/Mg ratio, and soy isoflavone intake was modified by history of fractures and time since menopause. Our findings, if confirmed, can help to guide further dietary intervention strategies for OF prevention.
Celestial navigation is an important means of maritime navigation; it can automatically achieve inertially referenced positioning and orientation after a long period of development. However, the impact of different accuracy of observations and the influence of nonstationary states, such as ship speed change and steering, are not taken into account in existing algorithms. To solve this problem, this paper proposes an adaptively robust maritime celestial navigation algorithm, in which each observation value is given an equivalent weight according to the robust estimation theory, and the dynamic balance between astronomical observation and prediction values of vessel motion is adjusted by applying the adaptive factor. With this system, compared with the frequently used least square method and extended Kalman filter algorithm, not only are the real-time and high-precision navigation parameters, such as position, course, and speed for the vessel, calculated simultaneously, but also the influence of abnormal observation and vessel motion status change could be well suppressed.
As a neuroprogressive illness, depression is accompanied by brain structural abnormality that extends to many brain regions. However, the progressive structural alteration pattern remains unknown.
Methods
To elaborate the progressive structural alteration of depression according to illness duration, we recruited 195 never-treated first-episode patients with depression and 130 healthy controls (HCs) undergoing T1-weighted MRI scans. Voxel-based morphometry method was adopted to measure gray matter volume (GMV) for each participant. Patients were first divided into three stages according to the length of illness duration, then we explored stage-specific GMV alterations and the causal effect relationship between them using causal structural covariance network (CaSCN) analysis.
Results
Overall, patients with depression presented stage-specific GMV alterations compared with HCs. Regions including the hippocampus, the thalamus and the ventral medial prefrontal cortex (vmPFC) presented GMV alteration at onset of illness. Then as the illness advanced, others regions began to present GMV alterations. These results suggested that GMV alteration originated from the hippocampus, the thalamus and vmPFC then expanded to other brain regions. The results of CaSCN analysis revealed that the hippocampus and the vmPFC corporately exerted causal effect on regions such as nucleus accumbens, the precuneus and the cerebellum. In addition, GMV alteration in the hippocampus was also potentially causally related to that in the dorsolateral frontal gyrus.
Conclusions
Consistent with the neuroprogressive hypothesis, our results reveal progressive morphological alteration originating from the vmPFC and the hippocampus and further elucidate possible details about disease progression of depression.
Recent regional cooling has impacted the natural systems of the Antarctic Peninsula (AP); however, little is known concerning the changes in the high parts of the glacial systems. Dry-snow line (DSL), situated in the high parts of glaciers, is the uppermost limit of frequent or occasional surface melt. We analyse dry-snow line altitude (DSLA) changes on the AP during 2004–2020 using C-band synthetic aperture radar time series data. We demonstrate that the DSLA in the eastern part of the AP is usually higher than that of the western part. Moreover, using simulated climatic variables from regional climate models, the lowering in altitude of DSL of glaciers in most areas is identified as a response to a decrease in snowmelt and an increase in precipitation. Furthermore, correlation analyses between simulated climatic variables and the DSLA are conducted. These results present the sensitive response of variations in DSLA to meteorological conditions, and the capability of DSLA being a proxy of polar local climate in high-altitude areas with no in situ meteorological observations.
NaY zeolite was synthesized from kaolin/dimethyl sulfoxide (DMSO) intercalation composites using an in situ crystallization technique. The effects of the intercalation ratios and the amounts of the kaolin/DMSO intercalation composite on the synthesis of an NaY zeolite molecular sieve were studied. The samples were characterized by X-ray diffraction, Fourier-transform infrared spectroscopy, differential thermal analysis, N2 adsorption–desorption and scanning electron microscopy. In the in situ synthesis system, when the kaolin/DMSO intercalation composite was added, pure NaY zeolite was formed. By increasing the amount of kaolin/DMSO intercalation composite added, the crystallinity of the samples increased, and after reaching the maximum amount of kaolin/DMSO intercalation composite added, the crystallinity decreased with further increases of the amount of kaolin/DMSO intercalation composite added. To higher intercalation ratio, the crystallinity can be greatly improved at the lower addition content. At an intercalation ratio of 84%, the added amount of kaolin/DMSO intercalation composite was 2.5% and the crystallinity of the NaY zeolite molecular sieve reached a maximum value of 45%. At intercalation ratios of 55% and 22%, the amount of kaolin/DMSO intercalation composite added was 15% and the crystallinities of the NaY zeolite molecular sieves were 44% and 47%, respectively. The NaY zeolite has good thermal stability and a particle diameter of ~0.5 μm. The Brunauer–Emmett–Teller (BET) specific surface area and pore volume of the sample were 519 m2 g–1 and 0.355 cm3 g–1, respectively.
Companies that produce energy transmit it to any or all households via a power grid, which is a regulated power transmission hub that acts as a middleman. When a power grid fails, the whole area it serves is blacked out. To ensure smooth and effective functioning, a power grid monitoring system is required. Computer vision is among the most commonly utilized and active research applications in the world of video surveillance. Though a lot has been accomplished in the field of power grid surveillance, a more effective compression method is still required for large quantities of grid surveillance video data to be archived compactly and sent efficiently. Video compression has become increasingly essential with the advent of contemporary video processing algorithms. An algorithm’s efficacy in a power grid monitoring system depends on the rate at which video data is sent. A novel compression technique for video inputs from power grid monitoring equipment is described in this study. Due to a lack of redundancy in visual input, traditional techniques are unable to fulfill the current demand standards for modern technology. As a result, the volume of data that needs to be saved and handled in live time grows. Encoding frames and decreasing duplication in surveillance video using texture information similarity, the proposed technique overcomes the aforementioned problems by Robust Particle Swarm Optimization (RPSO) based run-length coding approach. Our solution surpasses other current and relevant existing algorithms based on experimental findings and assessments of different surveillance video sequences utilizing varied parameters. A massive collection of surveillance films was compressed at a 50% higher rate using the suggested approach than with existing methods.
The FNDC5 gene encodes the fibronectin type III domain-containing protein 5 that is a membrane protein mainly expressed in skeletal muscle, and the FNDC5 rs3480 polymorphism may be associated with liver disease severity in non-alcoholic fatty liver disease (NAFLD). We investigated the influence of the FNDC5 rs3480 polymorphism on the relationship between sarcopenia and the histological severity of NAFLD. A total of 370 adult individuals with biopsy-proven NAFLD were studied. The association between the key exposure sarcopenia and the outcome liver histological severity was investigated by binary logistic regression. Stratified analyses were undertaken to examine the impact of FNDC5 rs3480 polymorphism on the association between sarcopenia and the severity of NAFLD histology. Patients with sarcopenia had more severe histological grades of steatosis and a higher prevalence of significant fibrosis and definite non-alcoholic steatohepatitis than those without sarcopenia. There was a significant association between sarcopenia and significant fibrosis (adjusted OR 2·79, 95 % CI 1·31, 5·95, P = 0·008), independent of established risk factors and potential confounders. Among patients with sarcopenia, significant fibrosis occurred more frequently in the rs3480 AA genotype carriers than in those carrying the FNDC5 rs3480 G genotype (43·8 v. 17·2 %, P = 0·031). In the association between sarcopenia and liver fibrosis, there was a significant interaction between the FNDC5 genotype and sarcopenia status (P value for interaction = 0·006). Sarcopenia is independently associated with significant liver fibrosis, and the FNDC5 rs3480 G variant influences the association between sarcopenia and liver fibrosis in patients with biopsy-proven NAFLD.
More than 80% of coronavirus disease 2019 (COVID-19) cases are mild or moderate. In this study, a risk model was developed for predicting rehabilitation duration (the time from hospital admission to discharge) of the mild-moderate COVID-19 cases and was used to conduct refined risk management for different risk populations.
Methods:
A total of 90 consecutive patients with mild-moderate COVID-19 were enrolled. Large-scale datasets were extracted from clinical practices. Through the multivariable linear regression analysis, the model was based on significant risk factors and was developed for predicting the rehabilitation duration of mild-moderate cases of COVID-19. To assess the local epidemic situation, risk management was conducted by weighing the risk of populations at different risk.
Results:
Ten risk factors from 44 high-dimensional clinical datasets were significantly correlated to rehabilitation duration (P < 0.05). Among these factors, 5 risk predictors were incorporated into a risk model. Individual rehabilitation durations were effectively calculated. Weighing the local epidemic situation, threshold probability was classified for low risk, intermediate risk, and high risk. Using this classification, risk management was based on a treatment flowchart tailored for clinical decision-making.
Conclusions:
The proposed novel model is a useful tool for individualized risk management of mild-moderate COVID-19 cases, and it may readily facilitate dynamic clinical decision-making for different risk populations.
Novel NiMoO4-integrated electrode materials were successfully prepared by solvothermal method using Na2MoO4·2H2O and NiSO4·6H2O as main raw materials, water, and ethanol as solvents. The morphology, phase, and structure of the as-prepared materials were characterized by SEM, XRD, Raman, and FT-IR. The electrochemical properties of the materials in supercapacitors were investigated by cyclic voltammetry, constant current charge–discharge, and electrochemical impedance spectroscopy techniques. The effects of volume ratio of water to ethanol (W/E) in solvent on the properties of the product were studied. The results show that the pure phase monoclinic crystal NiMoO4 product can be obtained when the W/E is 2:1. The diameter and length are 0.1–0.3 µm and approximately 3 µm, respectively. As an active material for supercapacitor, the NiMoO4 nanorods material delivered a discharge specific capacitance of 672, 498, and 396 F/g at a current density of 4, 7, and 10 A/g, respectively. The discharge specific capacitance slightly decreased from 815 to 588 F/g with a retention of 72% after 1000 cycles at a current density of 1 A/g. With these superior capacitance properties, the novel NiMoO4 integrated electrode materials could be considered as promising material for supercapacitors.
This paper presents new LA-ICP-MS zircon U–Pb chronology, whole-rock geochemical and zircon Hf isotopic data for the felsic lavas of the Huili Group from the southwestern Yangtze Block. LA-ICP-MS zircon U–Pb dating shows that these rocks were emplaced in Late Mesoproterozoic time (∼1028 to 1019 Ma). Relative to typical I-type and S-type granitoids, all the samples are characterized by low Sr and Eu, and high high-field-strength element contents, high TFeO/MgO, enriched rare earth element compositions and negative Eu anomalies, indicating that they share the geochemical signatures of A-type granitoid. They can be further divided into two groups: Group I and Group II. Group I are A1-type felsic rocks and were produced by fractional crystallization of alkaline basaltic magmas. The Group II felsic lavas belong to the A2-type and were derived by partial melting of a crustal source with mixing of mantle-derived magmas. Both Group I and Group II felsic lavas may erupt in a continental back-arc setting. The coexistence of A1- and A2-type rocks in the southwestern Yangtze Block suggests that they can occur in the same tectonic setting.