Partitioning Analysis Research Articles

SURG-21. DEVELOPMENT AND VALIDATION OF A CLINICAL RISK SCORE FOR POSTOPERATIVE OUTCOME IN NEWLY DIAGNOSED GLIOBLASTOMA: A REPORT OF THE RANORESECT GROUP

Abstract BACKGROUND Following resection or biopsy, patients with newly diagnosed glioblastoma frequently enter clinical trials. Nuanced risk assessment is warranted to reduce imbalances between study arms. Here, we aim to make use of our RANO classification for extent of resection (I) to analyze the interactive effects of residual tumor with clinical and molecular factors on outcome and (II) to define a postoperative risk assessment tool. METHODS The RANO resect group retrospectively compiled an international, seven-center training cohort of patients with newly diagnosed glioblastoma. The combined associations of residual tumor with molecular or clinical factors and survival were analyzed, and recursive partitioning analysis was performed for risk modeling. The resulting model was prognostically verified in a separate external validation cohort. RESULTS Our training cohort compromised 1003 patients with newly diagnosed IDH-wildtype glioblastoma, including 744 patients who underwent adjuvant radiochemotherapy (TMZ/RT→TMZ). Residual tumor, MGMT promotor methylation status, age, and KPS were prognostic of overall survival and forwarded into regression tree analysis. By combining eleven terminal nodes and individually weighting the prognostic factors, an additive scale (range, 0-9 points) integrating these four variables distinguished patients with low (0-2 points), intermediate (3-5 points), and high risk (6-9 points) for poor postoperative outcome (median overall survival: 24 vs. 16 vs. 6 months; p<0.01). The presence of the three risk groups was confirmed in the subgroups of patients treated with or without RT/TMZ→TMZ. The prognostic value of the risk score was verified in a external single-center validation cohort of newly diagnosed glioblastoma (n = 258, p<0.01). Compared to previously postulated models, goodness-of-fit measurements were superior for our score. CONCLUSIONS The novel RANO risk score serves as an easy-to-use, yet highly prognostic tool for postoperative patient stratification prior to further therapy. The score may serve to guide patient management and reduce imbalances between study arms in prospective trials.

How do urban green space attributes affect visitation and satisfaction? An empirical study based on multisource data

Urban green spaces (UGSs) are major settings of human–nature interaction and important to public well-being. Visitation and satisfaction are indicators that reflect the utilization degree of and feedback regarding UGSs. The focus of this study is to analyze the visitation and satisfaction characteristics of different types of UGSs, analyze the dominant factors affecting these indicators, and rank their importance to provide strategies for improving management. Here, 50 typical UGSs in Shanghai are selected. All-subset regression, hierarchical partitioning analysis and other methods are comprehensively used to explore the influencing factors. The results are as follows: 1) Comprehensive parks have the highest visitation rates, whereas community parks have the lowest visitation rates but the highest satisfaction rates. 2) UGS size has the greatest influence on visitation, followed by connectivity, building shape index, and edge density, with contributions of 69.35 %, 16.40 %, 8.50 %, and 5.75 %, respectively. 3) Transportation facility density and edge density have the greatest influences on satisfaction, with contributions of 51.49 % and 48.51 %, respectively. In this study, the applicability of using multisource data to analyze UGS attributes and their factors affecting visitation and satisfaction are demonstrated. Targeted strategies for constructing UGSs will help authorities plan and manage UGSs effectively.

Latitudinal Patterns and Macroclimatic Drivers of Phylogenetic Structure in Regional Liverwort Assemblages in North America

ABSTRACTAimMost plant groups originated under tropical conditions, leading to the hypothesis of tropical niche conservatism, according to which species assemblages of a clade originating and diversifying in tropical climates are expected to have low phylogenetic diversity and dispersion in temperate climates because only few lineages have adapted to these novel conditions. The opposite may be expected for clades originating under temperate conditions, but this temperate niche conservatism hypothesis has not been tested for a broad temperature gradient including both tropical and arctic climates. Liverworts are thought to have originated in temperate climates, and may thus follow the pattern of temperate niche conservatism. Here, we test this hypothesis using regional liverwort floras across a nearly full temperature gradient from tropical through temperate to arctic climates in North America. In addition, we investigate whether temperature‐related variables and climate extreme variables play a more important role in determining phylogenetic structure of liverwort assemblages, compared to precipitation‐related variables and climate seasonality variables, respectively.LocationNorth America.TaxonLiverworts (Marchantiophyta).MethodsPhylogenetic diversity (measured as mean pairwise distance) and phylogenetic dispersion (measured as standardised effect size of mean pairwise distance) in liverworts in regional floras in North America were related to latitude and climatic variables. Variation partitioning analysis was used to assess the relative importance of temperature‐ versus precipitation‐related variables and of climate extremes versus seasonality on phylogenetic diversity and dispersion.ResultsPhylogenetic diversity and dispersion in liverworts is highest in temperate climates, compared to both tropical and arctic climates. Temperature‐related variables and climate extreme variables explained more variation in phylogenetic diversity and dispersion of liverwort assemblages than did precipitation‐related variables and climate seasonality variables, respectively.Main ConclusionsVariations in phylogenetic diversity and dispersion in liverworts along the latitudinal gradient in North America are consistent with the temperate niche conservatism hypothesis.

Development and validation of a clinical risk model for postoperative outcome in newly diagnosed glioblastoma: a report of the RANO resect group.

Following surgery, patients with newly diagnosed glioblastoma frequently enter clinical trials. Nuanced risk assessment is warranted to reduce imbalances between study arms. Here, we aimed (I) to analyze the interactive effects of residual tumor with clinical and molecular factors on outcome and (II) to define a postoperative risk assessment tool. The RANO resect group retrospectively compiled an international, seven-center training cohort of patients with newly diagnosed glioblastoma. The combined associations of residual tumor with molecular or clinical factors and survival were analyzed, and recursive partitioning analysis was performed for risk modeling. The resulting model was prognostically verified in a separate external validation cohort. Our training cohort compromised 1003 patients with newly diagnosed isocitrate dehydrogenase-wildtype glioblastoma. Residual tumor, O6-methylguanine DNA methyltransferase (MGMT) promotor methylation status, age, and postoperative KPS were prognostic for survival and incorporated into regression tree analysis. By individually weighting the prognostic factors, an additive score (range, 0-9 points) integrating these four variables distinguished patients with low (0-2 points), intermediate (3-5 points), and high risk (6-9 points) for inferior survival. The prognostic value of our risk model was retained in treatment-based subgroups and confirmed in an external validation cohort of 258 patients with glioblastoma. Compared to previously postulated models, goodness-of-fit measurements were superior for our model. The novel RANO risk model serves as an easy-to-use, yet highly prognostic tool for postoperative patient stratification prior to further therapy. The model may serve to guide patient management and reduce imbalances between study arms in prospective trials.

Machine learning-inspired study of dynamical parameters of single vapor bubble under nucleate flow boiling regime

Heat transfer performance of nucleate boiling is interlinked with the departure dynamics of vapor bubbles, which also serves as the basis for heat transfer partitioning schemes and bubble growth models. Given the fast transients and multiple bubble ebullition cycles, boiling experiments lead to voluminous data that are to be analysed for determining the bubble dynamic parameters, and subsequently, the boiling heat transfer rates. Conventional approach of manual handling of such temporal and spatially-resolved experimental data is inherently time-consuming and error-prone. In the backdrop of these limitations, importance of machine learning algorithms gets highlighted in making the entire process automated and accurate as they minimize the need of any human intervention. The present work explores the potential of machine learning techniques towards quantifying the bubble departure characteristics and heat transfer partitioning during nucleate flow boiling. Water-based experiments have been conducted in a vertical channel under varying subcooling levels (ΔTsub = 2, 5, and 8 K) and flow rates (Re = 2400, and 3600). Mask R-CNN machine learning (ML) model is employed to evaluate the temporal variations of dynamical parameters of vapor bubbles and departure characteristics. The bubble departure characteristics as well as the corresponding evaporative and convective heat transfer rates, as retrieved through ML-generated masks, showed a strong dependence on the level of bulk fluid subcooling and flow rates. Heat transfer partitioning analysis revealed a competing interplay between the evaporative and condensation components of overall boiling heat transfer rates. These findings demonstrate the potential of ML techniques towards optimizing the thermal performance of boiling phenomena that have significant implications in a range of critical engineering applications.

Establishment of a Novel Risk Stratification System Integrating Clinical and Pathological Parameters for Prognostication and Clinical Decision‐Making in Early‐Stage Cervical Cancer

ABSTRACTBackgroundHighly heterogeneity and inconsistency in terms of prognosis are widely identified for early‐stage cervical cancer (esCC). Herein, we aim to investigate for an intuitional risk stratification model for better prognostication and decision‐making in combination with clinical and pathological variables.MethodsWe enrolled 2071 CC patients with preoperative biopsy‐confirmed and clinically diagnosed with FIGO stage IA‐IIA who received radical hysterectomy from 2013 to 2018. Patients were randomly assigned to the training set (n = 1450) and internal validation set (n = 621), in a ratio of 7:3. We used recursive partitioning analysis (RPA) to develop a risk stratification model and assessed the ability of discrimination and calibration of the RPA‐derived model. The performances of the model were compared with the conventional FIGO 2018 and 9th edition T or N stage classifications.ResultsRPA divided patients into four risk groups with distinct survival: 5‐year OS for RPA I to IV were 98%, 95%, 85.5%, and 64.2%, respectively, in training cohort; and 99.5%, 93.2%, 85%, and 68.3% in internal validation cohort (log‐rank p < 0.001). Calibration curves confirmed that the RPA‐predicted survivals were in good agreement with the actual survivals. The RPA model outperformed the existing staging systems, with highest AUC for OS (training: 0.778 vs. 0.6–0.717; internal validation: 0.772 vs. 0.595–0.704; all p < 0.05), and C‐index for OS (training: 0.768 vs. 0.598–0.707; internal validation: 0.741 vs. 0.583–0.676; all p < 0.05). Importantly, there were associations between RPA groups and the efficacy of treatment regimens. No obvious discrepancy was observed among different treatment modalities in RPA I (p = 0.922), whereas significant survival improvements were identified in patients who received adjuvant chemoradiotherapy in RPA II–IV (p value were 0.028, 0.036, and 0.024, respectively).ConclusionWe presented a validated novel clinicopathological risk stratification signature for robust prognostication of esCC, which may be used for streamlining treatment strategies.

Dynamic evolution trend and driving mechanisms of water conservation in the Yellow River Basin, China

Water conservation (WC) is a critical ecological service function in the Yellow River Basin (YRB). There is currently a lack of detailed exploration of WC development processes and the impact mechanisms of driving factors at spatiotemporal scales in the YRB. By collecting data on DEM, land use, soil, meteorology, reservoirs, and observed discharge, this study established a large-scale WC model using the soil and water assessment tool (SWAT). The abrupt change test, empirical orthogonal function (EOF), wavelet analysis, hierarchical partitioning analysis (HPA), geodetectors, and aridity index were employed to analyze the multi-spatiotemporal characteristics and driving forces of WC calculated using the water balance method. The results are as follows: (1) The average WC among the YRB was 9.11 mm (74.68 × 108 m3) from 1960 to 2020. Pasture and forests contributed to 48.65% and 22.05% of the average annual WC, respectively. (2) WC exhibited four forms: less/more in the YRB, more in the southeast (northwest), and less in the northwest (southeast). (3) Forests and pastures in land use had higher average WC capacity, while Gansu, Shaanxi, and Qinghai ranked in the top three for average WC among the nine provinces. (4) Precipitation was the major driving force affecting WC variations, with the interaction between precipitation and actual evapotranspiration being the most significant. (5) Drought was a significant cause of negative WC. Protecting and managing crucial WC areas was essential for improving the ecological environment. This research elucidates the driving forces of WC in the YRB, providing scientific support for improving regional WC and promoting sustainable development.

Copper‐Catalyzed Asymmetric Hydrogenation of Unsymmetrical ortho‐Br Substituted Benzophenones

AbstractThe asymmetric hydrogenation of benzophenones, catalyzed by low‐activity earth‐abundant metal copper, has hitherto remained a challenge due to the substrates equipped with two indistinguishably similar aryl groups. In this study, we demonstrated that the prochiral carbon of the ortho‐bromine substrate exhibits the highest electrophilicity and high reactivity among the ortho‐halogen substituted benzophenones, as determined by the Fukui function (f+) analysis and hydrogenation reaction. Considering that the enantiodirecting functional bromine group can be easily derivatized and removed in the products, we successfully achieved a green copper‐catalyzed asymmetric hydrogenation of ortho‐bromine substituted benzophenones. This method yielded a series of chiral benzhydrols with excellent results. The utility of this protocol has been validated through a gram‐scale reaction and subsequent product transformations. Independent gradient model based on Hirshfeld partition (IGMH) and energy decomposition analysis (EDA) indicate that the CH⋅⋅⋅HC multiple attractive dispersion interactions (MADI) effect between the catalyst and substrate enhances the catalyst's activity.

Concentric dual π delocalisation and conflicting aromaticity in bowl-like B56 cluster: an all-boron analogue of circumbiphenyl C38H16

We present computational evidence for concentric dual π delocalisation and conflicting aromaticity in an elongated quasi-planar bowl-like B56 (C 2v, 1A1) cluster, using the canonical molecular orbital (CMO) and the adaptive natural density partitioning (AdNDP) analyses at the density functional theory (DFT) level. The first B12 and second B18 rings constitute an inner BDR ribbon, and the second B18 and third B24 rings form an outer BDR ribbon. Chemical bonding analyses indicate that the 19 delocalised π bonds can be divided into two separate π subsystems, with inner 14π and outer 24π delocalised electrons. The bonding pattern is consistent with conflicting π aromaticity, which leads to an elongated geometry. A refined bonding model is also proposed for circumbiphenyl molecule C38H16, of which the B56 cluster is an inorganic analogue. The updated bonding pictures differ from that reported in prior studies on the system. It is further unravelled the mechanism as to why the two hexagonal holes prefer to be located at the centre. This research enriches the analogous relationship between quasi-planar boron clusters and their polycyclic hydrocarbons counterparts.

Soil total phosphorus mediate the assembly processes of rhizosphere microbial communities of ficus species in a tropical rainforest

Revealing the assembly processes of plant rhizosphere microbial communities and the underlying influencing factors is essential for understanding the biodiversity and function of forest ecosystem. However, it remains unclear how deterministic and stochastic processes shape community structure and their relative importance in phosphorus-limited tropical environments. Here, we investigated the diversity, composition, and assembly processes of rhizosphere microbial communities of Ficus species in the Xishuangbanna region of southwest China, using methods such as high-throughput sequencing, variance partitioning analysis and null model analysis. We found that the community assembly processes of bacteria and fungi were primarily dominated by deterministic processes, with the fungal group being more deterministic than the bacteria group. Soil total phosphorus (TP) was the primary determinant of the composition and assembly of the rhizosphere microbial community, explaining 12.58% and 21.35% of the compositional variation in bacterial and fungal communities, respectively, and accounting for 14% of the microbial community assembly, but has a minor impact on their alpha diversity. This study highlights the distinct environmental driving factors of community composition and community assembly. The exposed positive relationship between soil TP and microbial deterministic process has inspiration for link of microbial community functions to soil function and sustainable forest management.

Impact of age on surgical outcomes for world federation of neurosurgical societies grade I and II aneurysmal subarachnoid haemorrhage: a novel prognostic model using recursive partitioning analysis

This study aimed to evaluate age as a prognostic factor and develop a comprehensive prognostic model for patients undergoing clipping surgery for World Federation of Neurosurgical Societies (WFNS) grade I/II aneurysmal subarachnoid haemorrhage (SAH). We retrospectively investigated 188 patients with WFNS grade I/II SAH who underwent microsurgical clipping at our institute between December 2010 and January 2020. The data of 176 patients (75 with grade I and 101 with grade II) were analysed. Data on patient demographics, aneurysm characteristics, SAH factors, surgical details, and clinical outcomes were collected. Prognostic factors were assessed using bivariate and multivariable logistic regression analyses, and recursive partitioning analysis. Favourable outcomes (mRS 0–2) were observed in 76% of patients. Age, a significant negative prognostic factor in multivariable analysis (odds ratio 0.55, 95% confidence interval 0.40–0.76, p < 0.001), was cutoff at 70 years by the receiver operating characteristic curve. Patients aged ≤ 70 years had significantly better outcomes than those aged > 70 years (84% vs. 46%, respectively; p < 0.001). Epileptic seizures were significantly associated with poor outcomes in older adults (p < 0.001). A prognostic model (favourable, intermediate, and poor) based on age and postoperative adverse events showed significantly different outcomes between age groups (p < 0.001). Age was a stronger prognostic factor than WFNS grading for patients with grade I/II SAH undergoing microsurgical clipping. For patients aged ≤ 70 years, precise microsurgeries with fewer complications were associated with favourable outcomes beyond WFNS grade. For older patients, postoperative intensive seizure management may prevent poor outcomes.

The role of surgery in recurrent local cerebral metastases: a multi-institutional retrospective analysis.

Local recurrent brain metastases are defined as lesions that recur in the brain at the same site after a previous local therapy. In patients already submitted to surgery, a second operation may be potentially challenging due to scar formation, infiltration of cerebral vessels or eloquent brain areas and local effect of previous radiotherapy. The aim of this study is to retrospectively review the results and complications of a second surgical treatment in a series of local recurrent lesions and to review the literature on this topic. 37 patients submitted to surgery for a local, histologically confirmed, recurrent brain metastases between 2000 and 2022 were retrospectively analyzed with respect to the following parameters: age, histology, anatomic location, time to recurrence, previous radiotherapy, size of recurrent tumors, preoperative and postoperative Karnofsky Performance Status(KPS) score, recursive partitioning analysis (RPA) class and graded prognostic assessment (GPA) score, surgery-related complications and the presence of further cerebral metastases. Overall survival (OS) was calculated using the Kaplan-Meier method. A multivariate Cox proportional hazard model was developed using stepwise regression (forwards selection) with predictive variables that were significant in the univariate analyses. A significant improvement of post-operative KPS status was obtained after second surgery. At multivariate analysis better results in terms of OS were achieved in patients with a pre-operative KPS ≥ 70 and in patients who had received radiotherapy after the initial surgery. No significant postoperative complications related to previous treatments were observed. Surgical resection of local recurrent brain metastases may improve patients ́ neurologic conditions allowing more time for systemic therapies to act with a low incidence of surgery-related morbidity and mortality. However, careful patient selection with a fair pre-operative clinical status seems mandatory to achieve the best post-operative results, since uniform treatment-paradigms cannot be established yet, due to the highly heterogeneous patient cohort.

Impacts of the coexistence of polystyrene microplastics and pesticide imidacloprid on soil nitrogen transformations and microbial communities

The pollution of agricultural soils by microplastics (MPs) and pesticides has attracted significant attention. However, the combined impact of MPs and pesticides on soil nitrogen transformation and microbial communities remains unclear. In this study, we conducted a 28-day soil incubation experiment, introducing polystyrene microplastics (PS-MPs) at concentrations of 0.1% and 10% (w/w) and pesticide imidacloprid at concentrations of 0.1 mg/kg and 1.0 mg/kg. Our aim was to investigate the individual and combined effects of these pollutants on nitrogen transformations and microbial communities in agricultural soils. Imidacloprid accelerated the decline in soil pH, while PS-MPs slowed the process. Imidacloprid hindered soil nitrification and denitrification processes, however, the presence of PS-MPs mitigated the inhibitory effects of imidacloprid. Based on microbial community and functional annotation analyses, this is mainly attributed to the different effects of PS-MPs and imidacloprid on soil microbial communities and the expression of key nitrogen transformation-related genes. Variance partitioning analysis and partial least squares path modeling analyses revealed that PS-MPs and imidacloprid indirectly influenced the microbial community structure, primarily through changes in soil pH. This study elucidates the mechanism through which the combined stress of MPs and pesticides in agricultural soils influence soil nitrogen transformation and microbial communities. The findings offer valuable insights for the systematic evaluation of the ecological risks posed by the coexistence of these pollutants.

Phylogenetic Insights Into Canidae Trait Variation Across Continents

ABSTRACTAimUnderstanding the spatial structuring of ecological communities involves considering the interplay between evolutionary history and environmental factors. This study investigates how the phylogenetic structure of Canidae influences the geographical distribution and trait patterns of lineages globally, and how these patterns relate to Bergmann's and Rapoport's rules.LocationAmericas, Africa, Eurasia.Time Period12 million years ago—present.Major Taxa StudiedCanidae.MethodsUsing distribution data and phylogenetic information for 37 Canidae species, we analysed key ecological, functional and evolutionary variables. We applied phylogenetic fuzzy‐weighting via principal coordinates of phylogenetic structure (PCPS) and variance partitioning analysis (VPA) to assess the contributions of phylogenetic structure and environmental factors to trait variation among species.ResultsOur results revealed distinct global patterns in body size, body weight, range size, habitat use and evolutionary distinctiveness among lineages. We also identified the shared contributions of phylogenetic structure and temperature to trait variation using variance partitioning analysis. The PCPS axes highlighted the influence of phylogenetic relationships on Canidae assemblages, particularly in South America.Main ConclusionsImportantly, the study challenges the applicability of Bergmann's and Rapoport's rules across continents. The unique diversification history of Canidae in South America and Africa and their diverse environmental conditions likely contribute to the observed trait patterns that make both continents so distinguished when compared to North America and Eurasia. Our findings underscore the need to incorporate phylogenetic information in models assessing trait variation across geographic scales for unbiased estimates.

Efficacy and safety of bevacizumab combined with temozolomide in the treatment of glioma a systematic review and meta-analysis of clinical trials.

Glioma is the most common malignant brain tumor in neurosurgery. Bevacizumab (BEV) is a monoclonal antibody that inhibits tumors by inhibiting vascular endothelial growth factor and reducing tumor angiogenesis. To evaluate the efficacy and safety of BEV combined with temozolomide (TMZ) in glioma, we performed a meta-analysis. PubMed, Embase, The Cochrane Library, and Web of Science databases were searched for randomized controlled trials comparing survival outcomes between TMZ combined with BEV and TMZ alone as well as cohort studies were included in our study. The primary outcome measures analyzed were overall survival (OS) and progression-free survival (PFS). A total of six randomized controlled trials and four cohort studies with a total of 2515 patients were included in our meta-analysis. The results of meta-analysis suggested that there were no significant improvements in overall survival, but the combination of TMZ and BEV prolonged progression-free survival, improved overall response rate (ORR), and increased the incidence of some adverse reactions, compared with TMZ alone. Subgroup analysis suggested sex, recursive partitioning analysis (RPA) grade, MGMT gene status and radiotherapy combination did not affect the improvement of OS with the combination of the two drugs, and RPA grade did not affect the improvement of PFS with the combination of the two drugs. The combination of TMZ and BEV can improve PFS as well as ORR in patients and has no benefit on OS. At the same time, the adverse reactions during the combination of the two drugs were acceptable.

Altitude Distribution Patterns and Driving Factors of Rhizosphere Soil Microbial Diversity in the Mountainous and Hilly Region of Southwest, China

The distribution characteristics of the microbial community in rhizosphere soils of different altitudinal gradients were explored to uncover ecological factors affecting microbial community composition. In this study, the community variations of bacteria and fungi in the rhizosphere soil of Chrysanthemum indicum L. were analyzed. Samples were distributed along an altitudinal gradient of 300–1500 m above sea level in the Fuling watershed of the Three Gorges Reservoir area, China. The analysis was conducted using Illumina MiSeq high-throughput sequencing and bioinformatics analyses. Through correlation analysis with ecological factors, the altitude distribution pattern and driving factors of soil microbial diversity in the mountainous and hilly region of Chongqing were explored. According to the results, the richness and diversity of rhizosphere soil bacteria increased with altitude, while fungi were the richest and most diverse at an altitude of 900 m. The composition of the microbial community differed among different altitudes. Actinobacteria, Proteobacteria, Acidobacteriota, Chloroflexi, Bacteroidota, Ascomycota, unclassified_k_Fungi, Basidiomycota, and Mortierellomycota dominated the microbial community in rhizosphere soil. Correlation analysis showed that the distribution of rhizosphere soil microbial communities correlated with soil ecological factors at different altitudes. Moisture, pH, total nitrogen, total potassium, available potassium, urease, and catalase were significantly positively correlated with rhizosphere soil bacterial α-diversity, while their correlations with fungi were not significant. Variation partition analysis showed that the combined effects of soil physical and chemical factors, enzyme activity, and microbial quantity regulated bacterial community structure and composition. Their combined contributions (19.21%) were lower than the individual effects of soil physical and chemical factors (48.49%), enzyme activity (53.24%), and microbial quantity (60.38%). The effects of ecological factors on fungal communities differed: While the soil physical and chemical factors (44.43%) alone had a clear effect on fungal community structures, their combined contributions had no apparent effect. The results of this study not only contribute to a deeper understanding of the impact mechanism of altitude gradient on the diversity of rhizosphere soil microbial communities, but also provide a scientific basis for the protection and management of mountainous and hilly ecosystems. It lays a foundation for the future exploration of the relationship between microbial communities and plant–soil interactions.

Delving into nitrogen and phosphorus dynamics in shallow eutrophic lakes: Multi-interface response to freeze-thaw cycles

Assessing the impact of freeze-thaw cycles on nutrient transfer in lakes is crucial for addressing the global eutrophication of freshwater ecosystems in cold and arid regions. However, available information about the dynamics of nitrogen (N) and phosphorus (P) release during intact freeze-thaw cycles, especially in the sediment–porewater–water column continuum of lakes, is limited. This study collected the samples during ice-covered (January) and non-ice-covered (April, July, and October) periods. The changes in total nitrogen (TN) and total phosphorus (TP) were analyzed to estimate their release fluxes from the sediment-water interface. Both redundancy analysis (RDA) and variance partitioning analysis (VPA) were used to explore the effects of environmental variables on N and P. The results indicated that during the ice-covered period (ICP), the surface water content of different forms of N and P was lower than that of the overlying water, whereas the opposite was true during the non-ice-covered period (NICP). The overall trend for the different forms of N was TN > DIN > NH4-N > NO3-N > NO2-N, and for P, it was TP > PP > DTP > DOP>DIP. The vertical profiles of the porewater TN and TP generally demonstrated an increase followed by a decrease from the surface to the bottom, with an inflection point at 15 cm. Sediment TN and TP trends over time matched porewater trends, with both being spatially highest at the lake inlet. ICP sediments acted as sinks for TN and TP, and NICP sediments acted as sources. N and P in the water column were significantly correlated mainly with physicochemical indicators, whereas sediment contributed positively to TN and TP in the porewater. VPA indicated that environmental factors explained 46.45 % of the variation in TN and TP in the porewater. These findings emphasize the importance of freeze-thaw cycling processes in driving N and P nutrient enrichment, source-sink effects, and multi-media coupling in shallow lakes in arid plateau regions.

Impacts of land use and abiotic factors on fruit, seed, and leaf morphology of the desert date Balanites aegyptiaca in Benin: Implications for management

Preserving intraspecific phenotypic variation within socio-economically important but declining species is fundamental in the current context of rapid change in land use and environmental conditions. Balanites aegyptiaca (L.) Delile is a valuable seed oil tree species native to the arid and semi-arid regions of Africa. Notable morphological variations within the species are recognized by local communities, who often select trees with preferred traits for preservation in croplands. This study compared phenotypic variation in B. aegyptiaca based on sixteen phenotypic traits of fruits, seeds, and leaflets between trees in a strictly protected area and those in croplands. Furthermore, the relative role of land use, soil characteristics, bioclimatic variables, elevation, and slope in the observed variation was analysed. Student t-test, principal component analysis, redundancy analysis, and variance partitioning were used for data analysis in R software. Results showed that, after accounting for tree variation, significant differences were observed in only two traits: seed ratio, and leaflet dry weight, with mean values in cropland being 1.470 (higher), and 0.943 (lower) times that of wild trees, respectively. Furthermore, principal component analysis showed great overlap between ellipses of cropland and wild trees. The variance partitioning analysis showed that bioclimatic variables explained 18 % of the total variation followed by soil characteristics (11 %), and land use (9 %). These findings collectively suggest weak impacts of croplands and a lack of domestication syndrome in B. aegyptiaca in Benin, potentially due to persisting gene flow between wild and cropland trees, inadvertent species management, or low intensity of selection pressures. Future studies should explore organoleptic properties, physico-chemical characteristics of the pulp and seed oil and discern the extent to which observed differences are attributable to genetic factors and biotic factors (pest attacks, plant-plant interactions, etc.).

Low body mass index patients have worse outcomes after mechanical thrombectomy

BackgroundThere is evidence that frailty is an independent predictor of worse outcomes after stroke. Similarly, although obesity is associated with a higher risk for stroke, there are multiple reports describing...

Assessing the Noncovalent Interaction of Deucravacitinib and Ethanol with Special Reference to an Independent Gradient Model Based on Hirshfeld Partition.

The current study begins by optimizing the deucravacitinib molecule in the gas phase at the ωB97XD/cc-pVDZ level of theory using density functional theory and proceeds to study its intramolecular interactions. Further, a molecule of EtOH was introduced at different locations on the deucravacitinib molecule, and the noncovalent interactions arising from them were also investigated using several computational tools. In this way, eight deucravacitinib-EtOH systems (1-8) were identified and their electronic environment was studied after evaluating their binding energy. Using natural bond orbital analysis, the localization of charges between the donor and acceptor fragments in these interacting systems was examined. The nature of interactions was analyzed using the reduced gradient approach (NCI analysis), and few hydrogen bonding interactions (intermolecular and intramolecular) were found in each system. The strength of these hydrogen bonding interactions was further investigated by using theoretical tools such as atoms in molecules analysis and independent gradient model based on Hirshfeld partition analysis. The binding energy of deucravacitinib with EtOH was decomposed into energy components based on the domain-based local pair natural orbital coupled cluster technique using LED analysis. The results from the hydrogen bonding interaction analysis using different computational tools were found to be consistent with the calculated order of binding energy of systems 1-8 and they also pointed toward the higher stability of system 3.