Caracterização fitossanitária do componente arbóreo marginalde um trecho de linha férrea no município de Três Barras, SC / Phytosanitary characterization of the marginal arboreal componentof the railway line in the municipality of Três Barras, SC

As condições fitossanitárias de plantas arbóreas podem ser utilizadas para caracterizar comunidades vegetais, indicando condições de qualidade estrutural do componente vegetal. Assim, ambientes alterados antropicamente podem representar uma ameaça à fitossanidade. O objetivo deste estudo foi averiguar as características fitossanitárias do componente arbóreo em um trecho de 400 metros de extensão ao longo da linha férrea localizada no município de Três Barras, estado de Santa Catarina, Brasil. Foram registradas 33 espécies arbóreas, 29 gêneros e 19 famílias. Os índices ecológicos avaliados foram a abundância, densidade, riqueza e equabilidade. Foram avaliados 190 indivíduos em relação a qualidade da copa, grau de infestação de cipós e sanidade da árvore. Embora a qualidade da copa e a sanidade sejam majoritariamente boas, houve um relativo alto número de infestação de cipós. Tal ocorrência pode ser devido à condição de borda em que as plantas se encontram. Os bons índices ecológicos aliados ao baixo número de espécies arbóreas exóticas também indicam boas condições ecológicas e de fitossanidade local. Contudo, são necessários mais estudos (p. ex. florísticos e fitossociológicos) na área. A arborização urbana das proximidades aliada à formação de corredores ecológicos que liguem os fragmentos à Floresta Nacional de Três Barras pode ser uma medida de conservação e regeneração a ser explorada.

Phytosanitary conditions of tree plants can be used to characterize plant communities, indicating structural quality conditions of the plant component. Thus, anthropically altered environments may pose a threat to plant health. The objective of this study was to investigate the phytosanitary and ecological condition of the tree component in a stretch of 400 meters along the railway line located in the municipality of Três Barras, Santa Catarina state, Brazil. Thirty-three tree species were recorded, in addition to 54 taxonomically unidentified individuals. The ecological indices evaluated were abundance, density, richness and evenness. 190 individuals were evaluated in terms of crown quality, Abstract degree of liana infestation and tree health. Although canopy quality and health are mostly good, there was a relatively high number of vine infestations. Such an occurrence may be due to the edge condition in which the plants are located. The good ecological indices combined with the low number of exotic tree species also indicate good ecological conditions and local plant health. However, more studies are needed in the area. Urban afforestation, combined with the formation of ecological corridors that connect the fragments to the Três Barras National Forest, can be a conservation and regeneration measure to be explored.

Anatomical traits explain drought response of seedlings from wet tropical forests.

Water availability regulates plant community dynamics but the drought response of seedlings remains poorly known, despite their vulnerability, especially for the Asian tropics. In particular, discerning how functional traits of seedlings mediate drought response can aid generalizable predictions of tree responses to global environmental change. We assessed interspecific variation in drought response explained by above- and below-ground seedling traits. We conducted a dry-down experiment in the greenhouse using 16 tree species from the humid forests of Western Ghats in southern India, chosen to represent differences in affinity to conditions of high and low seasonal drought (seasonality affiliation). We compared survival, growth, and photosynthetic performance under drought and well-watered conditions and assessed the extent to which species' responses were explained by seasonality affiliation and 12 traits of root, stem and leaf. We found that the species from seasonally dry forest reduced photosynthetic rate in drought compared with well-watered conditions, but seasonality affiliation did not explain differences in growth and survival. Performance in drought vs well-watered conditions were best explained by anatomical traits of xylem, veins and stomata. Species with larger xylem reduced their growth and photosynthesis to tolerate desiccation. In drought, species with smaller stomata correlated with lower survival even though photosynthetic activity decreased by a larger extent with larger stomata. Overall, anatomical traits of xylem and stomata, directly related to water transport and gas-exchange, played a more prominent role than commonly used traits (e.g., specific leaf area, leaf dry matter content) in explaining species response to drought, and may offer a good proxy for physiological traits related to drought tolerance of seedlings.

Left atrial function in patients with rheumatic mitral stenosis: addressing prognostic insights beyond atrial fibrillation prediction.

Aims: Rheumatic mitral stenosis (MS) frequently leads to impaired left atrial (LA) function because of pressure overload, highlighting the underlying atrial pathology. Two-dimensional speckle tracking echocardiography (2D-STE) offers early detection of LA dysfunction, potentially improving risk assessment in patients with MS. This study aims to evaluate the predictive value of LA function assessed by 2D-STE for clinical outcomes in patients with MS. Methods and results: Between 2011 and 2021, patients with MS underwent LA function assessment using 2D-STE, with focus on the reservoir phase (LASr). Atrial fibrillation (AF) development constituted the primary outcome, with death or valve replacement as the secondary outcome. Conditional inference trees were employed for analysis, validated through sample splitting. The study included 493 patients with MS (mean valve area 1.1 ± 0.4 cm2, 84% female). At baseline, 166 patients (34%) had AF, with 62 patients (19%) developing AF during follow-up. LASr emerged as the primary predictor for new-onset AF, with a threshold of 17.9%. Over a mean 3.8-year follow-up, 125 patients (25%) underwent mitral valve replacement, and 32 patients (6.5%) died. A decision tree analysis identified key predictors such as age, LASr, severity of tricuspid regurgitation (TR), net atrioventricular compliance (C n), and early percutaneous mitral valvuloplasty, especially in patients aged ≤49 years, where LASr, with a threshold of 12.8%, significantly predicted adverse outcomes. Conclusion: LASr emerged as a significant predictor of cardiovascular events in this MS cohort, validated through a decision tree analysis. Patients were stratified into low- or high-risk categories for adverse outcomes, taking into account LASr, age, TR severity, and C n.

Tree Frogs Alter Their Behavioral Strategies While Landing On Vertical Perches.

As an arboreal animal, tree frogs face diverse challenges when landing on perches, including variations in substrate shape, diameter, flexibility, and angular distribution, with potentially significant consequences for failed landings. Research on tree frog landing behavior on perches, especially concerning landing on vertical substrates, remains limited. This study investigated the landing strategies (forelimb, abdomen, and hindlimb) of tree frogs on vertical perches, considering perch diameter. Although all three strategies were observed across perches of different diameters, their frequencies differed. Forelimb landing was most common across all perch diameters, with its frequency increasing with perch diameter, while abdomen and hindlimb landing strategies were more prevalent on smaller diameter perches. During the process from take-off to landing, the body axis underwent some deviation owing to the asymmetric movement of the left and right limbs; however, these deviations did not significantly differ among landing strategies. Additionally, different landing strategies led to variations in the landing forces, with abdominal landings generating significantly higher impact forces than the other two strategies. These findings provide insights into the biomechanics and biological adaptations of tree frogs when landing on challenging substrates, such as leaves or branches.

Chlorophyllase (PsCLH) and light-harvesting chlorophyll a/b binding protein 1 (PsLhcb1) and PsLhcb5 maintain petal greenness in Paeonia suffruticosa 'Lv Mu Yin Yu'.

INTRODUCTION: Green flowers are not an adaptive trait in natural plants due to the challenge for pollinators to discriminate from leaves, but they are valuable in horticulture. The molecular mechanisms of green petals remain unclear. Tree peony (Paeonia suffruticosa) is a globally cultivated ornamental plant and considered the 'King of Flowers' in China. The P. suffruticosa 'Lv Mu Yin Yu (LMYY)' cultivar with green petals could be utilized as a representative model for understanding petal-specific chlorophyll (Chl) accumulation and color formation. OBJECTIVES: Identify the key genes related to Chl metabolism and understand the molecular mechanism of petal color changes. METHODS: The petal color parameter was analyzed at five developmental stages using a Chroma Spectrophotometer, and Chl and anthocyanin accumulation patterns were examined. Based on comparative transcriptomes, differentially expressed genes (DEGs) were identified, among which three were functionally characterized through overexpression in tobacco plants or silencing in 'LMYY' petals. RESULTS: During flower development and blooming, flower color changed from green to pale pink, consistent with the Chl and anthocyanin levels. The level of Chl demonstrated a similar pattern with petal epidermal cell striation density. The DEGs responsible for chlorophyll and anthocyanin metabolism were characterized through a comparative transcriptome analysis of flower petals over three critical developmental stages. The key chlorophyllase (PsCLH1) and light-harvesting chlorophyll a/b binding protein 1 (PsLhcb1) and PsLhcb5 influenced the Chl accumulation and the greenness of 'LMYY' petals. CONCLUSION: PsCLH1, PsLhcb1, and PsLhcb5 were critical in accumulating the Chl and maintaining the petal greenness. Flower color changes from green to pale pink were regulated by the homeostasis of Chl degradation and anthocyanin biosynthesis. This study offers insights into underlying molecular mechanisms in the green petal and a strategy for germplasm innovation.

Connecting working and long-term memory: Bayesian-hierarchical multinomial model-based analyses reveal storage next to retrieval differences.

Individual differences in working memory capacity (WMC) are correlated with long-term memory (LTM) differences. Whether this is because high-WMC individuals encode more effectively, resulting in better LTM storage, or because they better retrieve information from LTM is debated. In two experiments, we used Bayesian-hierarchical multinomial modeling to correlate participant-level storage and retrieval processes from LTM recall to WMC abilities estimated from operation and symmetry complex span tasks. In Experiment 1, we presented participants with 20 consecutive words, including semantically associated pairs (e.g., knife and fork), to assess LTM processes. Participants received standard (n = 242) or associative-storage instructions (n = 222) and then completed a free recall task. In Experiment 2, we instructed participants (N = 239) to memorize 40 cue-target words as pairs before completing free and cued recall tasks. Correlations with WMC emerged with storage and retrieval processes and only when an associative storage strategy was instructed (Experiment 1). When associative processing was inherent to the task (Experiment 2), only the associative storage, not the retrieval advantage, replicated. The strategy reports suggest that high-WMC individuals use associative encoding strategies more effectively, resulting in better storage in LTM.

Phylogenetic association analysis with conditional rank correlation.

Phylogenetic association analysis plays a crucial role in investigating the correlation between microbial compositions and specific outcomes of interest in microbiome studies. However, existing methods for testing such associations have limitations related to the assumption of a linear association in high-dimensional settings and the handling of confounding effects. Hence, there is a need for methods capable of characterizing complex associations, including nonmonotonic relationships. This article introduces a novel phylogenetic association analysis framework and associated tests to address these challenges by employing conditional rank correlation as a measure of association. The proposed tests account for confounders in a fully nonparametric manner, ensuring robustness against outliers and the ability to detect diverse dependencies. The proposed framework aggregates conditional rank correlations for subtrees using weighted sum and maximum approaches to capture both dense and sparse signals. The significance level of the test statistics is determined by calibration through a nearest-neighbour bootstrapping method, which is straightforward to implement and can accommodate additional datasets when these are available. The practical advantages of the proposed framework are demonstrated through numerical experiments using both simulated and real microbiome datasets.

Tall Bornean forests experience higher canopy disturbance rates than those in the eastern Amazon or Guiana shield.

The future of tropical forests hinges on the balance between disturbance rates, which are expected to increase with climate change, and tree growth. Whereas tree growth is a slow process, disturbance events occur sporadically and tend to be short-lived. This difference challenges forest monitoring to achieve sufficient resolution to capture tree growth, while covering the necessary scale to characterize disturbance rates. Airborne LiDAR time series can address this challenge by measuring landscape scale changes in canopy height at 1 m resolution. In this study, we present a robust framework for analysing disturbance and recovery processes in LiDAR time series data. We apply this framework to 8000 ha of old-growth tropical forests over a 4-5-year time frame, comparing growth and disturbance rates between Borneo, the eastern Amazon and the Guiana shield. Our findings reveal that disturbance was balanced by growth in eastern Amazonia and the Guiana shield, resulting in a relatively stable mean canopy height. In contrast, tall Bornean forests experienced a decrease in canopy height due to numerous small-scale (<0.1 ha) disturbance events outweighing the gains due to growth. Within sites, we found that disturbance rates were weakly related to topography, but significantly increased with maximum canopy height. This could be because taller trees were particularly vulnerable to disturbance agents such as drought, wind and lightning. Consequently, we anticipate that tall forests, which contain substantial carbon stocks, will be disproportionately affected by the increasing severity of extreme weather events driven by climate change.

Fast-and-frugal decision tree for the rapid critical appraisal of systematic reviews.

Conducting high-quality overviews of reviews (OoR) is time-consuming. Because the quality of systematic reviews (SRs) varies, it is necessary to critically appraise SRs when conducting an OoR. A well-established appraisal tool is A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2, which takes about 15-32 min per application. To save time, we developed two fast-and-frugal decision trees (FFTs) for assessing the methodological quality of SR for OoR either during the full-text screening stage (Screening FFT) or to the resulting pool of SRs (Rapid Appraisal FFT). To build a data set for developing the FFT, we identified published AMSTAR 2 appraisals. Overall confidence ratings of the AMSTAR 2 were used as a criterion and the 16 items as cues. One thousand five hundred and nineteen appraisals were obtained from 24 publications and divided into training and test data sets. The resulting Screening FFT consists of three items and correctly identifies all non-critically low-quality SRs (sensitivity of 100%), but has a positive predictive value of 59%. The three-item Rapid Appraisal FFT correctly identifies 80% of the high-quality SRs and correctly identifies 97% of the low-quality SRs, resulting in an accuracy of 95%. The FFTs require about 10% of the 16 AMSTAR 2 items. The Screening FFT may be applied during full-text screening to exclude SRs with critically low quality. The Rapid Appraisal FFT may be applied to the final SR pool to identify SR that might be of high methodological quality.

[Prediction of liberation cutting intensity effect on the growth of Korean pine in secondary forest based on double dummy variable model]. / åŸºäºŽåŒå“‘å˜é‡æ¨¡åž‹é¢„æµ‹é€å ‰æŠšè‚²å¼ºåº¦å¯¹æ¬¡ç”Ÿæž—å† çº¢æ¾ç”Ÿé•¿çš„å½±å“.

"Planting conifer and reserving broadleaved tree" is an effective way to restore broad-leaved pine forest of temperate zone in Northeast China. Liberation cutting can promote the growth of Korean pine (Pinus koraiensis) under forest crown and accelerate the succession. However, how liberation cutting intensity affects the growth of Korean pine in secondary forest is still unclear. Taking the "Planting conifer and reserving broadleaved tree" Korean pine forest in Changbai Mountain as the object, we constructed a growth model of diameter at breast height (DBH) and tree height of Korean pine with double dummy variables (liberation cutting intensity and tree classification) to predict the growth of Korean pine plantation under different liberation cutting intensities, i.e. control (no liberation cutting), light-intensity liberation cutting (retaining upper canopy closure 0.6), medium-intensity liberation cutting (0.4), heavy-intensity liberation cutting (0.2) and clear cutting (cutting all upper broadleaf trees) stands. We analyzed the effects of liberation cutting intensities on DBH, tree height, and the ratio of tree height to DBH. The results showed that among six theoretical growth equations, the Gompertz model on the DBH (R2=0.46) and tree height (R2=0.81) was optimal basic model. The R2 of the DBH model was increased to 0.65 and 0.89, respectively, after the single dummy variable and the double dummy variable were introduced into the basic model, while the R2 of the tree height model was increased to 0.84 and 0.94. Therefore, the double dummy variable model was the most suitable for predicting the growth of Korean pine. The growth of DBH of pressed tree increased with the increases of liberation cutting intensity (increase by 145.8%-933.3%) during the whole simulation period (0-80 a). Average and dominant trees showed the same pattern at 42 and 60 a. In the early and middle stages of liberation cutting (20 and 42 a), clear cutting and heavy-intensity liberation cutting had similar effects on the height growth of dominant trees (64.8%-68.5%), average trees (100.0%-144.2%), and pressed trees (138.5%-183.9%). The effects of medium-intensity liberation cutting and light-intensity liberation cutting on the height growth were similar (24.3%-35.1%, 56.0%-92.3%, 84.6%-103.2%). While in the middle and late period (42 and 80 a), height growth of three grade trees increased with the increases of liberation cutting intensity. Under each liberation cutting intensity, the ratio of height to DBH of the dominant, average, and pressed trees increased successively, ranging from 0.50-0.95, 0.64-1.23, and 0.73-4.33, respectively. Only the pressed tree decreased with the increases of liberation cutting intensity at 0-80 a. Therefore, about 40 years after the implementation of liberation cutting, the promoting effect of different liberation cutting intensities on DBH growth was significantly weakened, the promoting effect on tree height growth was significantly enhanced, and the ratio of tree height to diameter began to increase. In order to alleviate forest competition, second liberation cutting should be carried out for light-intensity liberation cutting and medium-intensity liberation cutting stands to further release the growth potential of Korean pine, and thinning management should be carried out in clear cutting and heavy-intensity liberation cutting stands.

[Characteristics and influence factors of rainfall redistribution in eight typical plantations in the loess area in West Shanxi, China]. / 晋西黄土区8ç§å ¸åž‹æž—åˆ†é™é›¨å†åˆ†é ç‰¹å¾ä¸Žå½±å“å› ç´ .

Aiming for clarifying the potential distribution characteristics of canopy rainfall partitioning of the loess area, we explored the process of rainfall partitioning across eight typical forest stands (Pinus tabuliformis forest, Robinia pseudoacacia forest, Platycladus orientalis forest, mixed forest of Robinia pseudoacacia-Pinus tabuliformis, mixed forest of Platycladus orientalis-Robinia pseudoacacia, Quercus wutaishanica forest, Populus davidiana forest, mixed forest of Quercus wutaishanica-Populus davidiana), and used boosted regression trees (BRT) to quantify the relative influences of stand structures and meteorological environment factors. We established multiple regression relationships according to the most influential factors extracted by BRT, and applied to the dataset of mining to verify the performance of the BRT-derived predictive model. The results showed that the percentages of throughfall (TF), stemflow (SF), and canopy interception (Ic) in total precipitation were 24.5%-95.1%, 0-13.6%, and 0.7%-55.7% among eight typical forest stands, respectively. For the individual rainfall threshold of TF, coniferous forest (3.06±1.21 mm) was significantly higher than broad-leaved forest (1.97±0.52 mm), but there was no significant difference between coniferous forest and broad-leaved mixed forest (3.01±0.98 mm). There was no significant difference in the individual rainfall threshold of SF among different composition stands. BRT analysis showed that stand structure factors accounted for a relatively small proportion for TF and SF, respectively. By contrast, stand structure factors dominated the Ic. Rainfall was the most important factor in determining TF and SF. Tree height was the most important factor in determining Ic, followed by rainfall, canopy area, diameter at breast height, and stand density. Compared with the general linear function and the power function, the prediction effect of BRT prediction model constructed here on TF and SF had been further improved, and the prediction of canopy interception still needed to explore. In conclusion, the BRT model could better quantitatively evaluate the effects of stand structure and meteorological environmental factors on rainfall partitioning components, and the performance of the BRT predictive model could satisfy and lay the foundation for the optimization strategy for stand configuration.

[Effect of competition on the prediction accuracy of individual tree biomass model for natural Larix gmelinii forests]. / ç«žäº‰å¯¹å ´å®‰è½å¶æ¾å¤©ç„¶æž—å•æœ¨ç”Ÿç‰©é‡æ¨¡åž‹é¢„ä¼°ç²¾åº¦çš„å½±å“.

Quantifying the impact of competition on individual tree biomass and its distribution pattern can provide a basis for improving the prediction accuracy of forest biomass models. To accurately quantify the effects of competition factors on individual biomass and its distribution, we constructed three different individual biomass models by using nonlinear coupling equations based on the biomass survey data of 50 Larix gmelinii from 18 plots of Pangu Forest Farm in Daxing'an Mountains. M-1 was a traditional singly additive biomass model. M-2 and M-3 were models taking the distance dependent simple competition index (CI) and distance independent relative diameter (Rd) into account, respectively. Those models were used to reveal the influence of competition factors on the prediction accuracy and distribution pattern of single tree biomass model of L. gmelinii. The results showed that the adjusted R2 of three additive models ranged from 0.694 to 0.974, mean prediction errors ranged from -0.017 to 0.021, and mean absolute errors ranged from 0.152 to 0.357. The introduction of Rd could improve the fitting degree and prediction accuracy of most biomass models, but CI did not affect the model fitting effect and prediction ability. Among the three models, M-3 model had the best performance, with good fitting degree and prediction accuracy of the biomass of each part, which could accurately estimate the single tree biomass of L. gmelinii. Further simulation results showed that the variation of biomass with DBH was mainly affected by CI and Rd grade, and the influence of Rd was stronger than CI. CI had greater influence on root and dry biomass, but less influence on branch and leaf biomass. Rd had a more significant effect on biomass of branch and leaf than on that of root and trunk.

[Effects of tree species assembly on bioavailable P components in rhizosphere soil of southern subtropical plantation]. / å—äºšçƒ­å¸¦äººå·¥æž—æ ‘ç§é ç½®å¯¹æ ¹é™ åœŸå£¤ç”Ÿç‰©æœ‰æ•ˆç£·çš„å½±å“.

Improving the availability of soil phosphorus (P) and promoting tree growth through tree species selection and assembly are the critical issue. We conducted an afforestation experiment following randomized block experimental design with 1, 2, 4, and 6 tree species richness in south subtropics, including Pinus massoniana, Mytilaria laosensis, Erythrophleum fordii, Castanopsis hystrix, Michelia macclurei, Manglietia glauca, Aquilaria sinensis, and Dalbergia odorifera. We measured the bioavailable P components (CaCl2-P, citrate-P, enzyme-P and HCl-P) and examined the effects of different tree species assembly on bioavailable P components and tree growth. The results showed that, compared with non-nitrogen-fixing tree species, the mixing of nitrogen-fixing tree species (E. fordii and D. odorifera) effectively increased the contents of soil water, total nitrogen, total phosphorus, and microbial biomass P (MBP). The assembly of specific tree species improved the accumulation of bioavailable P. Mixing of nitrogen-fixing tree species significantly increased CaCl2-P content by 46.2% to 160.3%, the enzyme-P content produced by microbial mineralization by 69.3% to 688.2%, and HCl-P by 31.5% to 81.3%, increased MBP by 81.8% to 149.4%, and microbial biomass N (MBN) by 88.1% to 160.6%, respectively. Redundancy and correlation analysis results showed that MBP, available P, total phosphorus, L-leucine aminopeptidase, cellobiose, acid phosphatase, MBN and soil organic carbon were key factors driving the variation of rhizosphere soil bioavailable P. Mixing of nitrogen-fixing tree species increased enzyme-P and citrate-P, and the availability of which were positively correlated to tree basal area. In this study, mixing of nitrogen-fixing tree species increased the rhizosphere soil bioavailable P content, which facilitates tree growth.

Key traits influencing the resistance of Eucalyptus camaldulensis to wind damage in coastal areas of South China.

Aims: China is one of the countries in the world most seriously affected by typhoons, which pose a great threat to the eucalyptus plantation industry. However, few studies have comprehensively accounted for the impact of key traits on the wind damage/resistance of eucalyptus. Methods: To identify the key factors affecting the wind resistance of eucalyptus, 20 eucalyptus genotypes were selected; a total of 18 traits, including the wind damage index, growth traits, and wood traits, were measured, and the wind resistance was determined via the tree-pulling test. Results: Correlation, principal component, canonical correlation, and path analyses were performed to evaluate these traits. Correlation analysis revealed that the wind resistance of eucalyptus plants was related to the tree height, volume, and duration of stress wave propagation. Principal components and tree-pulling variables were further used for correlation and path analyses. Canonical correlation analysis and the PA-OV model showed that holocellulose and lignin contents and fiber width, as well as growth traits, were important factors affecting the stability of standing trees under typhoon conditions. The key traits influencing the wind resistance of Eucalyptus camaldulensis, which may provide a reference for evaluating the wind resistance of Eucalyptus varieties for forest management, were identified. Conclusion: This study provides a knowledge base for forest management and planning in typhoon-prone coastal areas, and provides a theoretical basis for the breeding and genetically improving eucalyptus stocks based on wind resistance characteristics.

Minimum spanning tree analysis of unimpaired individuals at risk of Alzheimer's disease.

Identifying early and non-invasive biomarkers to detect individuals in the earliest stages of the Alzheimer's disease continuum is crucial. As a result, electrophysiology and plasma biomarkers are emerging as great candidates in this pursuit due to their low invasiveness. This is the first magnetoencephalography study to assess the relationship between minimum spanning tree parameters, an alternative to overcome the comparability and thresholding problem issues characteristic of conventional brain network analyses, and plasma phosphorylated tau231 levels in unimpaired individuals, with different risk levels of Alzheimer's disease. Seventy-six individuals with available magnetoencephalography recordings and phosphorylated tau231 plasma determination were included. The minimum spanning tree for the theta, alpha and beta bands for each subject was obtained, and the leaf fraction, tree hierarchy and diameter were calculated. To study the relationship between these topological parameters and phosphorylated tau231, we performed correlation analyses, for the whole sample and considering the two risk sub-groups separately. Increasing concentrations of phosphorylated tau231 were associated with greater leaf fraction and tree hierarchy values, along with lower diameter values, for the alpha and theta frequency bands. These results emerged for the whole sample and the higher risk group, but not for the lower risk group. Our results indicate that the network topology of cognitively unimpaired individuals with elevated plasma phosphorylated tau231 levels, a marker of Alzheimer's disease pathology and amyloid-ß accumulation, is already altered, shifting towards a more integrated network increasing its vulnerability and hub-dependency, mostly in the alpha band. This is indicated by increases in leaf fraction and tree hierarchy, along with reductions in diameter. These results match the initial trajectory proposed by theoretical models of disease progression and network disruption and suggest that changes in brain function and organization begin early on.

Palatal groove associated with periodontal lesions: a systematic review illustrated by a decisional tree for management.

BACKGROUND: Palatal groove represents a relatively uncommon developmental root anomaly, usually found on the palatal aspect of maxillary incisors. While its origin is controversial, its presence predisposes to severe periodontal defects. AIM: This study aimed to provide a systematic review of the literature focusing on the varied diagnostic techniques and treatment modalities for periodontal lesions arising from the presence of palatal groove. Based on the existing evidence and knowledge, the study also provides a comprehensive decisional tree, guiding clinicians in the challenging decision-making process face to a palatal groove. METHODS: The literature search was conducted on Medline and Cochrane databases by two independent reviewers, who also performed the screening and selection process, looking for English written articles reporting on diagnosis and management (all treatment approaches) of periodontal lesion(s) associated with a palatal groove. Based on this literature, a comprehensive decisional tree, including a standardized palatal groove evaluation and tailored treatment approaches, is proposed. Moreover, a clinical case is described to demonstrate the practical application of the developed decisional tree. RESULTS: Over a total of 451 articles initially identified, 34 were selected, describing 40 patients with 40 periodontal lesions associated with palatal grooves. The case report illustrates a deep, large, circumferential intra-bony defect on the palatal side of the tooth #22 associated with a shallow, moderately long palatal groove in an 18-year-old male patient. Following reevaluation, a single flap surgery was deemed necessary, combined with a regenerative procedure. At 2 years post-treatment, the tooth #22 is healthy, in a functional and esthetic position. The decision-making process, based on local and systemic patient's conditions, should allow an early and precise diagnosis to prevent further complications and undertake an adequate treatment. CONCLUSION: Palatal grooves are relatively rare; however, they are frequently associated with severe periodontal defects. The identification, diagnosis, prompt, and tailored management of the associated lesion is essential to mitigate potential periodontal and endodontic complications related to the presence of palatal groove. SYSTEMATIC REVIEW REGISTRATION: [ https://www.crd.york.ac.uk/prospero/ ], identifier [C CRD42022363194].

Relationship between tree species diversity and water holding capacity of litter layer in subtropical region.

Litter layer, serving as the "skin" of forest soil, plays a crucial role in conserving water resources and maintaining soil and water conservation. We analyzed the relationship of tree species richness, community weighted mean traits, and functional diversity with the standing mass, maximum water holding rate, and effective water sto-rage capacity of litters from various tree species including Liquidambar formosana, Mytilaria laosensis, Castanopsis sclerophylla, Castanopsis hystrix, Cunninghamia lanceolata, Pinus massoniana, Fokienia hodginsii, Taxus wallichiana and their combinations of mixed forests in subtropical region. The results showed that across various tree species combinations, the ranges of maximum water holding rate, standing litter mass and effective water storage capacity of undecomposed layer were 0-419%, 0-0.58 t·hm-2, and 0-1.66 t·hm-2, respectively. For the semi-decomposition layer, these values spanned in 0-375%, 0-6.14 t·hm-2, and 0-16.03 t·hm-2, respectively. Tree species richness and community weighted mean specific leaf area had significantly positive effects on standing mass of litter and effective water storage capacity, while community weighted mean leaf N content had significantly negative effect on standing mass of litter. The maximum water holding rate increased with the increases of functional diversity of specific leaf area and community weighted mean specific leaf area, decreased with the increase of community weighted mean leaf thickness. Results of structural equation model showed that tree species richness increased litter water holding capacity by increasing functional diversity of specific leaf area. The community weighted mean specific leaf area increased the water holding capacity of litter layer by increasing standing mass of litter and the maximum water holding rate. It is necessary to consider planting mixed forest with higher community weighted mean specific leaf area in the management of subtropical artificial forest, so as to improve the water holding capacity of litter layer.

iTRAQ proteome analysis reveals the underling mechanisms of foliage zinc-spraying to improve photosynthetic capacity and seed yields of Peaonia ostii 'Fengdan'.

Zinc (Zn) deficiency is a significant nutritional limitation to crop yield globally, particularly in calcareous soil environments. Tree peony of Peaonia ostii 'Fengdan' is regarded as an oil crop due to its seeds rich in alpha-linolenic acid, a beneficial compound for health promotion. However, low seed yield remains a primary challenge in attaining sufficient seed oil from tree peony. In this study, Zn fertilization was applied to soil or foliage of P. ostii 'Fengdan' in the growth period before fruit development. Our findings reveal that foliar Zn-spraying, as opposed to soil application, proves to be a more effective method for augmenting seed yield, Zn accumulation and photosynthetic capacity in 'Fengdan'. Comparative analyses of the leaf proteome of 'Fengdan' using iTRAQ profiling under foliar Zn-spraying identified 115 differentially expressed proteins (DEPs), including 36 upregulated proteins, which likely contribute to the observed increase in seed yields of 'Fengdan' caused by foliage Zn-spraying. Specifically, Zn2+ stimulation of phosphatidylinositol signaling initiates a cascade of metabolic regulations. Firstly, ATP synthesis promotes leaf photosynthetic capacity, facilitated by improved sucrose metabolism through upregulated pullulanase and 1,4-alpha-glucan-branching enzyme. Furthermore, lipid synthesis and transport are facilitated by upregulated lipoyl synthase and plastid lipid-associated proteins. Additionally, DEPs involved in secondary metabolism are upregulated in the production of various metabolites conducive to 'Fengdan' growth. Overall, our results demonstrate that foliage Zn-spraying enhances seed yield in P. ostii 'Fengdan' by elevating Zn content and secondary metabolite synthesis in leaves, thereby augmenting leaf photosynthetic capacity and lipid synthesis. This study provides an effective way to increase seed yield of tree peony by exogenous Zn application.

Development and External Validation of Motor-intention Integrated Prediction Model for Upper Extremity Motor Recovery After Intention-driven Robotic-hand Training for Chronic Stroke.

OBJECTIVE: To derive and validate a prediction model for minimal clinically important differences (MCID) in upper extremity (UE) motor function after intention-driven robotic-hand training using residual voluntary EMG signals from affected UE. DESIGN: A prospective longitudinal multicenter cohort study. We collected pre-intervention candidate predictors: demographics, clinical characteristics, Fugl-Meyer assessment of UE (FMAUE), Action Research Arm Test scores, and motor-intention of flexor digitorum and extensor digitorum (ED) measured by EMG during maximal voluntary contraction (MVC). For EMG measures, recognizing challenges for stroke survivors to move paralyzed hand, peak signals were extracted from eight time-windows during MVC-EMG (0.1s-5s) to identify subjects' motor-intention. Classification And Regression Tree algorithm was employed to predict survivors with MCID of FMAUE. Relationship between predictors and motor-improvements was further investigated. SETTING: Nine rehabilitation centers. PARTICIPANTS: Chronic stroke survivors (N=131), including 87 for Derivation-sample, and 44 for Validation-sample. INTERVENTIONS: All participants underwent 20-session robotic-hand training (40min/session, 3-5sessions/week). MAIN OUTCOME MEASURES: Prediction efficacies of models were assessed by area under the receiver operating characteristic curve (AUC). The best effective model was final model and validated using AUC and overall accuracy. RESULTS: The best model comprised FMAUE (cut-off score: 46) and peak activity of ED from one-second MVC-EMG (MVC-EMG 4.604 times higher than resting-EMG), which demonstrated significantly higher prediction accuracy (AUC: 0.807) than other time-windows or solely using clinical-scores (AUC: 0.595). In external validation, this model displayed robust prediction (AUC: 0.916). Significant quadratic relationship was observed between ED-EMG and FMAUE increases. CONCLUSIONS: This study presents a prediction model for intention-driven robotic-hand training in chronic stroke survivors. It highlights significance of capturing motor-intention through 1-second EMG-window as a predictor for MCID improvement in UE motor-function after 20-session robotic-training. Survivors in two conditions showed high percentage of clinical motor-improvement: moderate-to-high motor-intention and low-to-moderate function; as well as high-intention and high-function.

Cardiac disease risk prediction using machine learning algorithms.

Heart attack is a life-threatening condition which is mostly caused due to coronary disease resulting in death in human beings. Detecting the risk of heart diseases is one of the most important problems in medical science that can be prevented and treated with early detection and appropriate medical management; it can also help to predict a large number of medical needs and reduce expenses for treatment. Predicting the occurrence of heart diseases by machine learning (ML) algorithms has become significant work in healthcare industry. This study aims to create a such system that is used for predicting whether a patient is likely to develop heart attacks, by analysing various data sources including electronic health records and clinical diagnosis reports from hospital clinics. ML is used as a process in which computers learn from data in order to make predictions about new datasets. The algorithms created for predictive data analysis are often used for commercial purposes. This paper presents an overview to forecast the likelihood of a heart attack for which many ML methodologies and techniques are applied. In order to improve medical diagnosis, the paper compares various algorithms such as Random Forest, Regression models, K-nearest neighbour imputation (KNN), Naïve Bayes algorithm etc. It is found that the Random Forest algorithm provides a better accuracy of 88.52% in forecasting heart attack risk, which could herald a revolution in the diagnosis and treatment of cardiovascular illnesses.