In this paper, the author proves a generalized Donaldson-Uhlenbeck-Yau theorem for twisted holomorphic chain on a non-compact Kähler manifold. As an application, the author obtains a Bogomolov type ...Chern numbers inequality for semistable twisted holomorphic chain.
In this paper, we introduce a family of generalized Donaldson functionals on holomorphic vector bundles, whose Euler–Lagrange equations are a vector bundle version of the complex
k
-Hessian ...equations. We also study the uniqueness of solutions to these equations.
In this paper, we study Higgs bundles on non-compact Hermitian manifolds. Under some assumptions for the underlying Hermitian manifolds which are not necessarily Kähler, we solve the ...Hermitian–Einstein equation on analytically stable Higgs bundles.
The non-abelian Hodge correspondence was established by Corlette (1988), Donaldson (1987), Hitchin (1987) and Simpson (1988, 1992). It states that on a compact Kähler manifold (
X,ω
), there is a ...one-to-one correspondence between the moduli space of semi-simple flat complex vector bundles and the moduli space of poly-stable Higgs bundles with vanishing Chern numbers. In this paper, we extend this correspondence to the projectively flat bundles over some non-Kähler manifold cases. Firstly, we prove an existence theorem of Poisson metrics on simple projectively flat bundles over compact Hermitian manifolds. As its application, we obtain a vanishing theorem of characteristic classes of projectively flat bundles. Secondly, on compact Hermitian manifolds which satisfy Gauduchon and astheno-Kähler conditions, we combine the continuity method and the heat flow method to prove that every semi-stable Higgs bundle with
Δ
(
E
,
∂
¯
E
)
⋅
ω
n
−
2
=
0
must be an extension of stable Higgs bundles. Using the above results, over some compact non-Kähler manifolds (
M,ω
), we establish an equivalence of categories between the category of semi-stable (poly-stable) Higgs bundles
(
E
,
∂
¯
E
,
ϕ
)
with
Δ
(
E
,
∂
¯
E
)
⋅
ω
n
−
2
=
0
and the category of (semi-simple) projectively flat bundles (
E, D
) with
−
1
F
D
=
α
⊗
Id
E
for some real (1,1)-form
α
).
A Frölicher-type inequality for Bott-Chern cohomology and its relation with
∂
∂
¯
-lemma were introduced in
1
. In this paper, we generalize these results to the cohomology groups with coefficients ...in flat complex vector bundles.
An improved hybrid grey wolf optimization algorithm (IHGWO) is proposed to solve the problem of population diversity, imbalance of exploration and development capabilities, and premature convergence. ...The algorithm benefits from particle swarm optimization and a dimension learning-based hunting search strategy. In the particle swarm algorithm search strategy, linear variable social learning and self-learning are introduced to improve the population's ability to communicate information. The individual position, current iteration optimal position, and optimal population position of grey wolves are combined to update the individual position information, thus strengthening the communication between individuals and the population. In the dimension learning-based hunting search strategy, neighborhoods are built for each search member, and neighborhood members can share information, balance global and local searches, and maintain diversity. To validate the algorithm, 23 typical benchmark functions, CEC2022 benchmark functions, and engineering problem sinusoidal low-order-polynomial prediction of positioning error of numerical control machine tools are used to optimize the algorithm's parameters. Results are compared with those from four other algorithms and analyzed using Friedman's statistical test. Experimental and statistical tests reveal that the IHGWO algorithm has the best overall benchmark function rating, with an overall effectiveness of 87.23%. In the engineering parameter optimization problem, the mean square error, root mean square error, and goodness of fit of the prediction equation after IHGWO algorithm optimization are 95.3761, 9.7661, and 97.47%, respectively. These numerical values are superior to those of the compared algorithms, effectively demonstrating the comprehensive performance and applicability of the algorithm.
•Doxorubicin induces acute cardiotoxicity accompanied by disordered apoptosis and autophagy in vivo and vitro.•Fucoidan could restore doxorubicin-induced acute cardiotoxicity by inhibiting apoptosis ...and promoting autophagy.•The protective role of fucoidan can be impaired by inhibiting the activation of the JAK2/STAT3 pathway.
Doxorubicin (DOX) is well-known for its potent antitumor activity but limited by its multiple and serious adverse effects. A major adverse effect is acute cardiotoxicity; yet, its mechanism has not been elucidated. Fucoidan is a multifunctional and nontoxic polysaccharide that is widely studied because of its favorable biological activities and safety. Hence, we proposed that fucoidan may play a protective role in DOX-induced acute cardiotoxicity without causing additional side effects. Sprague-Dawley rats were injected intraperitoneally with a single high dose of DOX to induce acute cardiac injury. Fucoidan was administered orally before DOX injection and AG490, a JAK2 inhibitor, was applied to verify the participation of the JAK2/STAT3 pathway. In vitro, H9C2 cells were treated with the same drugs at different concentrations and intervention times. in vivo and in vitro results demonstrated that DOX administration induced myocardial damage accompanied by acceleratory apoptosis and deficient autophagy in heart tissues or cells, which could be significantly improved by fucoidan supplement. AG490 partly abolished the cardioprotective effects of fucoidan, suggesting the involvement of JAK2 signaling. Additionally, western blotting revealed DOX-induced JAK2/STAT3 pathway activation, which was enhanced by fucoidan and weaken by AG490. Hence, fucoidan exerted a favorable effect on DOX-induced cardiotoxicity by enhancing autophagy and suppressing apoptosis in a JAK2/STAT3-dependent manner, which may provide a promising and novel therapeutic strategy against negative chemotherapy-induced effects.
Background: Major depressive disorder (MDD) plays a crucial role in the occurrence of heart failure (HF). This investigation was undertaken to explore the possible mechanism of MDD’s involvement in ...HF pathogenesis and identify candidate biomarkers for the diagnosis of MDD with HF. Methods: GWAS data for MDD and HF were collected, and Mendelian randomization (MR) analysis was performed to investigate the causal relationship between MDD and HF. Differential expression analysis (DEA) and WGCNA were used to detect HF key genes and MDD-associated secretory proteins. Protein–protein interaction (PPI), functional enrichment, and cMAP analysis were used to reveal potential mechanisms and drugs for MDD-related HF. Then, four machine learning (ML) algorithms (including GLM, RF, SVM, and XGB) were used to screen candidate biomarkers, construct diagnostic nomograms, and predict MDD-related HF. Furthermore, the MCPcounter algorithm was used to explore immune cell infiltration in HF, and MR analysis was performed to explore the causal effect of immunophenotypes on HF. Finally, the validation of the association of MDD with reduced left ventricular ejection fraction (LVEF) and the performance assessment of diagnostic biomarkers was accomplished based on animal models mimicking MDD. Results: The MR analysis showed that the MDD was linked to an increased risk of HF (OR = 1.129, p < 0.001). DEA combined with WGCNA and secretory protein gene set identified 315 HF key genes and 332 MDD-associated secretory proteins, respectively. Through PPI and MCODE analysis, 78 genes were pinpointed as MDD-related pathogenic genes for HF. The enrichment analysis revealed that these genes were predominantly enriched in immune and inflammatory regulation. Through four ML algorithms, two hub genes (ISLR/SFRP4) were identified as candidate HF biomarkers, and a nomogram was developed. ROC analysis showed that the AUC of the nomogram was higher than 0.90 in both the HF combined dataset and two external cohorts. In addition, an immune cell infiltration analysis revealed the immune dysregulation in HF, with ISLR/SFRP4 displaying notable associations with the infiltration of B cells, CD8 T cells, and fibroblasts. More importantly, animal experiments showed that the expression levels of ISLR (r = −0.653, p < 0.001) and SFRP4 (r = −0.476, p = 0.008) were significantly negatively correlated with LVEF. Conclusions: The MR analysis indicated that MDD is a risk factor for HF at the genetic level. Bioinformatics analysis and the ML results suggest that ISLR and SFRP4 have the potential to serve as diagnostic biomarkers for HF. Animal experiments showed a negative correlation between the serum levels of ISLR/SFRP4 and LVEF, emphasizing the need for additional clinical studies to elucidate their diagnostic value.
Background
The high prevalence of patent foramen ovale (PFO) in cryptogenic stroke suggested a stroke-causing role for PFO. As risk factors for recurrence of such stroke are not recognized, ...clinicians cannot sufficiently identify, treat, and follow-up high-risk patients. Therefore, this study aimed to establish a prediction model for PFO-related stroke recurrence.
Methods
This study included 392 patients with PFO-related stroke in a training set and 164 patients with PFO-related stroke in an independent validation set. In the training set, independent risk factors for recurrence identified using forward stepwise Cox regression were included in nomogram 1, and those identified using least absolute shrinkage and selection operator(LASSO)regression were included in nomogram 2. Nomogram performance and discrimination were assessed using the concordance index (C-index), area under the curve (AUC), calibration curve, and decision curve analyses (DCA). The results were also validated in the validation set.
Results
Nomogram 1 was based on homocysteine (Hcy), high-sensitivity C-reactive protein (hsCRP), and albumin (ALB), and nomogram 2 was based on age, diabetes, hypertension, right-to-left shunt, ALB, prealbumin, hsCRP, and Hcy. The C-index of nomogram 1 was 0.861, which was not significantly different from that of nomogram 2 (0.893). The 2- and 5-year AUCs of nomogram 1 were 0.863 and 0.777, respectively. In the validation set, nomogram 1 still had good discrimination (C-index, 0.862; 2-year AUC, 0.839; 5-year AUC, 0.990). The calibration curve showed good homogeneity between the prediction by nomogram 1 and the actual observation. DCA demonstrated that nomogram 1 was clinically useful. Moreover, patients were successfully divided into two distinct risk groups (low and high risk) for recurrence rate by nomogram 1.
Conclusions
Nomogram 1, based on Hcy, hsCRP, and ALB levels, provided a more clinically realistic prognostic prediction for patients with PFO-related stroke. This model could help patients with PFO-related stroke to facilitate personalized prognostic evaluations.
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