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The identification of sex chromosomes is fundamental for exploring the mechanism and evolution of sex determination. Platichthys stellatus , a species exhibiting clear sexual dimorphism and homomorphic chromosome pairs, has received limited research concerning its sex determination mechanisms. Clarifying the sex chromosome of P. stellatus will enhance our understanding of sex chromosome evolution in Pleuronectiformes. This study employed whole-genome resequencing to investigate the sex chromosome and sex determination system in P. stellatus . Notably, Chr23 was identified as the sex chromosome in P. stellatus , with the sex-determining region (SDR) occupying 48.1% of the chromosome and featuring an XX/XY system. Sex chromosome turnover was observed within Pleuronectiformes, with P. stellatus , Verasper variegatus , and Hippoglossus hippoglossus sharing a common ancestral karyotype. No inversions were detected within the SDR of P. stellatus , although chromosomal rearrangements between sex chromosomes and autosomes were identified. Additionally, a sex-specific marker for P. stellatus was ascertained, enabling genetic sex identification, with significant implications for improving breeding programs and aquaculture practices.

Long noncoding RNAs (lncRNAs) have significant regulatory roles in gene expression. Interactions with proteins are one of the ways lncRNAs play their roles. Since experiments to determine lncRNA-protein interactions (LPIs) are expensive and time-consuming, many computational methods for predicting LPIs have been proposed as alternatives. In the LPIs prediction problem, there commonly exists the imbalance in the distribution of positive and negative samples. However, there are few existing methods that give specific consideration to this problem. In this paper, we proposed a new clustering-based LPIs prediction method using segmented k-mer frequencies and multi-space clustering (LPI-SKMSC). It was dedicated to handling the imbalance of positive and negative samples. We constructed segmented k-mer frequencies to obtain global and local features of lncRNA and protein sequences. Then, the multi-space clustering was applied to LPI-SKMSC. The convolutional neural network (CNN)-based encoders were used to map different features of a sample to different spaces. It used multiple spaces to jointly constrain the classification of samples. Finally, the distances between the output features of the encoder and the cluster center in each space were calculated. The sum of distances in all spaces was compared with the cluster radius to predict the LPIs. We performed cross-validation on 3 public datasets and LPI-SKMSC showed the best performance compared to other existing methods. Experimental results showed that LPI-SKMSC could predict LPIs more effectively when faced with imbalanced positive and negative samples. In addition, we illustrated that our model was better at uncovering potential lncRNA-protein interaction pairs., (© 2024. International Association of Scientists in the Interdisciplinary Areas.)

Background: Currently, the association between the consumption of polyunsaturated fatty acids (PUFAs) and the susceptibility to autoimmune rheumatic diseases (ARDs) remains conflict and lacks substantial evidence in various clinical studies. To address this issue, we employed Mendelian randomization (MR) to establish causal links between six types of PUFAs and their connection to the risk of ARDs., Methods: We retrieved summary-level data on six types of PUFAs, and five different types of ARDs from publicly accessible GWAS statistics. Causal relationships were determined using a two-sample MR analysis, with the IVW approach serving as the primary analysis method. To ensure the reliability of our research findings, we used four complementary approaches and conducted multivariable MR analysis (MVMR). Additionally, we investigated reverse causality through a reverse MR analysis., Results: Our results indicate that a heightened genetic predisposition for elevated levels of EPA (OR IVW : 0.924, 95% CI: 0.666-1.283, P IVW = 0.025) was linked to a decreased susceptibility to psoriatic arthritis (PsA). Importantly, the genetically predicted higher levels of EPA remain significantly associated with an reduced risk of PsA, even after adjusting for multiple testing using the FDR method ( P IVW -FDR-corrected  = 0.033) and multivariable MR analysis ( P MV-IVW  < 0.05), indicating that EPA may be considered as the risk-protecting PUFAs for PsA. Additionally, high levels of LA showed a positive causal relationship with a higher risk of PsA (OR IVW : 1.248, 95% CI: 1.013-1.538, P IVW = 0.037). It is interesting to note, however, that the effects of these associations were weakened in our MVMR analyses, which incorporated adjustment for lipid profiles ( P MV-IVW > 0.05) and multiple testing using the FDR method ( P IVW-FDR-corrected = 0.062). Moreover, effects of total omega-3 PUFAs, DHA, EPA, and LA on PsA, were massively driven by SNP effects in the FADS gene region. Furthermore, no causal association was identified between the concentrations of other circulating PUFAs and the risk of other ARDs. Further analysis revealed no significant horizontal pleiotropy and heterogeneity or reverse causality., Conclusion: Our comprehensive MR analysis indicated that EPA is a key omega-3 PUFA that may protect against PsA but not other ARDs. The FADS2 gene appears to play a central role in mediating the effects of omega-3 PUFAs on PsA risk. These findings suggest that EPA supplementation may be a promising strategy for preventing PsA onset. Further well-powered epidemiological studies and clinical trials are warranted to explore the potential mechanisms underlying the protective effects of EPA in PsA., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xu, Xu, Zakeri, Wang, Yan, Wang, Li, Sun, Wang and Miao.)

Heat shock factor 1 (HSF1), an essential transcription factor for stress response, is exploited by various tumors to facilitate their initiation, progression, invasion, and migration. Amplification of HSF1 is widely regarded as an indicator in predicting cancer severity, the likelihood of treatment failure and reduced patient survival. Notably, HSF1 is markedly amplified in 40% of pancreatic cancer (PC), which typically have limited treatment options. HSF1 has been proven to be a promising therapeutic target for multiple cancers. However, a direct small molecule HSF1 inhibitor with sufficient bioactivity and reliable safety has not been developed clinically. In this study, we successfully established a high-throughput screening system utilizing luciferase reporter assay specifically designed for HSF1, which leads to the discovery of a potent small molecule inhibitor targeting HSF1. Homoharringtonine (HHT) selectively inhibited PC cell viability with high HSF1 expression and induced a markedly stronger tumor regression effect in the subcutaneous xenograft model than the comparator drug KRIBB11, known for its direct action on HSF1. Moreover, HHT shows promise in countering the resistance encountered with HSP90 inhibitors, which have been observed to increase heat shock response intensity in clinical trials. Mechanistically, HHT directly bound to HSF1, suppressing its expression and thereby inhibiting transcription of HSF1 target genes. In conclusion, our work presents a preclinical discovery and validation for HHT as a HSF1 inhibitor for PC treatment., Competing Interests: None., (AJCR Copyright © 2024.)

Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Background: Currently, there has been observed a significant alteration in the composition of the gut microbiome (GM) and serum metabolites in patients with psoriatic arthritis (PsA) compared to healthy individuals. However, previous observational studies have shown inconsistent results regarding the alteration of gut microbiota/metabolites. In order to shed light on this matter, we utilized Mendelian randomization to determine the causal effect of GM/metabolites on PsA., Methods: We retrieved summary-level data of GM taxa/metabolites and PsA from publicly available GWAS statistics. Causal relationships between GM/metabolites and PsA were determined using a two-sample MR analysis, with the IVW approach serving as the primary analysis method. To ensure the robustness of our findings, we conducted sensitivity analyses, multivariable MR analysis (MVMR), and additional analysis including replication verification analysis, LDSC regression, and Steiger test analysis. Furthermore, we investigated reverse causality through a reverse MR analysis. Finally, we conducted an analysis of expression quantitative trait loci (eQTLs) involved in the metabolic pathway to explore potential molecular mechanisms of metabolism., Results: Our findings reveal that eight GM taxa and twenty-three serum metabolites are causally related to PsA ( P < 0.05). Notably, a higher relative abundance of Family Rikenellaceae (OR IVW : 0.622, 95% CI: 0.438-0.883, FDR = 0.045) and elevated serum levels of X-11538 (OR IVW : 0.442, 95% CI: 0.250-0.781, FDR = 0.046) maintain significant causal associations with a reduced risk of PsA, even after adjusting for multiple testing correction and conducting MVMR analysis. These findings suggest that Family Rikenellaceae and X-11538 may have protective effects against PsA. Our sensitivity analysis and additional analysis revealed no significant horizontal pleiotropy, reverse causality, or heterogeneity. The functional enrichment analysis revealed that the eQTLs examined were primarily associated with glycerolipid metabolism and the expression of key metabolic factors influenced by bacterial infections ( Vibrio cholerae and Helicobacter pylori ) as well as the mTOR signaling pathway., Conclusion: In conclusion, our study demonstrates that Family Rikenellacea e and X-11538 exhibit a strong and negative causal relationship with PsA. These particular GM taxa and metabolites have the potential to serve as innovative biomarkers, offering valuable insights into the treatment and prevention of PsA. Moreover, bacterial infections and mTOR-mediated activation of metabolic factors may play an important role in this process., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xu, Wu, Wang, Yan, Wang, Li, Sun and Zhao.)

Synergistic bioassay-guided isolation of the extracts of Artemisia rupestris L, which belongs to the family Asteraceae, afforded two acetylenic spiroketal enol ethers, namely rupesdiynes A ( 1 ) and B ( 2 ). Their structures were determined based on spectroscopic analysis and experimental and calculated ECD investigations. The two compounds exhibited synergistic activity and were able to reduce the minimum inhibitory concentration (MIC) of oxacillin four-fold, with a fractional inhibitory concentration index (FICI) of 0.5 in combination with oxacillin against the oxacillin-resistant EMRSA-16. Biofilm formation inhibitory and Ethidium bromide (EtBr) efflux assay were further employed to verify the possible mechanism of the synergistic antibacterial effect. Additionally, molecular docking studies were conducted to investigate the binding affinities of the two compounds with penicillin-binding protein 2a (PBP2a) of EMRSA-16. Taken together, rupesdiynes A ( 1 ) and rupesdiyne B ( 2 ) showed moderate synergistic activity against EMRSA-16 with oxacillin via inhibiting biofilm formation and efflux pump activity, respectively.