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The implementation of turn restrictions represents a critical research challenge in chiplet-based systems, with the objective of achieving deadlock-free communication. Nevertheless, existing methodologies encounter difficulties in terms of computational complexity, which impedes the design process. Moreover, as the scale of the problem increases, the cost of addressing it becomes increasingly untenable. In this paper, we introduce the efficient turn restrictions setting (ETRS) method to reduce the computational cost of implementing turn restrictions for boundary routers in chiplet-based systems. In stage 1, we present a symmetry-based preprocessing algorithm (SBPA). SBPA exploits the symmetry inherent in chiplet topologies by generating multiple sets of identical modes, ensuring that scenarios with the same objective function value are calculated only once per iteration. In stage 2, a heuristic selection algorithm (HSA) for turn restrictions based on NSGA-II is proposed as a means of searching for approximately optimal solutions and of solving the problem quickly. In stage 3, different filtering criteria are introduced to evaluate the Pareto fronts of HSA for making decisions on the placement of boundary routers and their turn restrictions. Evaluation results reveal that the proposed ETRS method surpasses existing solutions in terms of computation efficiency. Moreover, it delivers satisfactory optimal objective values. [ABSTRACT FROM AUTHOR]

• Competitive null models may yield false positives from co-expression. • Self-contained null models may yield false positives from bimodal correlations. • Test statistics interact differently with two types of null models. • Supplementary analyses with various configurations support the findings. Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests. [ABSTRACT FROM AUTHOR]

Purpose: ATG-101, a bispecific antibody that simultaneously targets the immune checkpoint PD-L1 and the costimulatory receptor 4-1BB, activates exhausted T cells upon PD-L1 crosslinking. Previous studies demonstrated promising anti-tumour efficacy of ATG-101 in preclinical models. Here, we labelled ATG-101 with 89Zr to confirm its tumour targeting effect and tissue biodistribution in a preclinical model. We also evaluated the use of immuno-PET to study tumour uptake of ATG-101 in vivo.ATG-101, anti-PD-L1, and an isotype control were conjugated with p-SCN-Deferoxamine (Df). The Df-conjugated antibodies were radiolabelled with 89Zr, and their radiochemical purity, immunoreactivity, and serum stability were assessed. We conducted PET/MRI and biodistribution studies on [89Zr]Zr-Df-ATG-101 in BALB/c nude mice bearing PD-L1-expressing MDA-MB-231 breast cancer xenografts for up to 10 days after intravenous administration of [89Zr]Zr-labelled antibodies. The specificity of [89Zr]Zr-Df-ATG-101 was evaluated through a competition study with unlabelled ATG-101 and anti-PD-L1 antibodies.The Df-conjugation and [89Zr]Zr -radiolabelling did not affect the target binding of ATG-101. Biodistribution and imaging studies demonstrated biological similarity of [89Zr]Zr-Df-ATG-101 and [89Zr]Zr-Df-anti-PD-L1. Tumour uptake of [89Zr]Zr-Df-ATG-101 was clearly visualised using small-animal PET imaging up to 7 days post-injection. Competition studies confirmed the specificity of PD-L1 targeting in vivo.[89Zr]Zr-Df-ATG-101 in vivo distribution is dependent on PD-L1 expression in the MDA-MB-231 xenograft model. Immuno-PET with [89Zr]Zr-Df-ATG-101 provides real-time information about ATG-101 distribution and tumour uptake in vivo. Our data support the use of [89Zr]Zr-Df-ATG-101 to assess tumour and tissue uptake of ATG-101.Methods: ATG-101, a bispecific antibody that simultaneously targets the immune checkpoint PD-L1 and the costimulatory receptor 4-1BB, activates exhausted T cells upon PD-L1 crosslinking. Previous studies demonstrated promising anti-tumour efficacy of ATG-101 in preclinical models. Here, we labelled ATG-101 with 89Zr to confirm its tumour targeting effect and tissue biodistribution in a preclinical model. We also evaluated the use of immuno-PET to study tumour uptake of ATG-101 in vivo.ATG-101, anti-PD-L1, and an isotype control were conjugated with p-SCN-Deferoxamine (Df). The Df-conjugated antibodies were radiolabelled with 89Zr, and their radiochemical purity, immunoreactivity, and serum stability were assessed. We conducted PET/MRI and biodistribution studies on [89Zr]Zr-Df-ATG-101 in BALB/c nude mice bearing PD-L1-expressing MDA-MB-231 breast cancer xenografts for up to 10 days after intravenous administration of [89Zr]Zr-labelled antibodies. The specificity of [89Zr]Zr-Df-ATG-101 was evaluated through a competition study with unlabelled ATG-101 and anti-PD-L1 antibodies.The Df-conjugation and [89Zr]Zr -radiolabelling did not affect the target binding of ATG-101. Biodistribution and imaging studies demonstrated biological similarity of [89Zr]Zr-Df-ATG-101 and [89Zr]Zr-Df-anti-PD-L1. Tumour uptake of [89Zr]Zr-Df-ATG-101 was clearly visualised using small-animal PET imaging up to 7 days post-injection. Competition studies confirmed the specificity of PD-L1 targeting in vivo.[89Zr]Zr-Df-ATG-101 in vivo distribution is dependent on PD-L1 expression in the MDA-MB-231 xenograft model. Immuno-PET with [89Zr]Zr-Df-ATG-101 provides real-time information about ATG-101 distribution and tumour uptake in vivo. Our data support the use of [89Zr]Zr-Df-ATG-101 to assess tumour and tissue uptake of ATG-101.Results: ATG-101, a bispecific antibody that simultaneously targets the immune checkpoint PD-L1 and the costimulatory receptor 4-1BB, activates exhausted T cells upon PD-L1 crosslinking. Previous studies demonstrated promising anti-tumour efficacy of ATG-101 in preclinical models. Here, we labelled ATG-101 with 89Zr to confirm its tumour targeting effect and tissue biodistribution in a preclinical model. We also evaluated the use of immuno-PET to study tumour uptake of ATG-101 in vivo.ATG-101, anti-PD-L1, and an isotype control were conjugated with p-SCN-Deferoxamine (Df). The Df-conjugated antibodies were radiolabelled with 89Zr, and their radiochemical purity, immunoreactivity, and serum stability were assessed. We conducted PET/MRI and biodistribution studies on [89Zr]Zr-Df-ATG-101 in BALB/c nude mice bearing PD-L1-expressing MDA-MB-231 breast cancer xenografts for up to 10 days after intravenous administration of [89Zr]Zr-labelled antibodies. The specificity of [89Zr]Zr-Df-ATG-101 was evaluated through a competition study with unlabelled ATG-101 and anti-PD-L1 antibodies.The Df-conjugation and [89Zr]Zr -radiolabelling did not affect the target binding of ATG-101. Biodistribution and imaging studies demonstrated biological similarity of [89Zr]Zr-Df-ATG-101 and [89Zr]Zr-Df-anti-PD-L1. Tumour uptake of [89Zr]Zr-Df-ATG-101 was clearly visualised using small-animal PET imaging up to 7 days post-injection. Competition studies confirmed the specificity of PD-L1 targeting in vivo.[89Zr]Zr-Df-ATG-101 in vivo distribution is dependent on PD-L1 expression in the MDA-MB-231 xenograft model. Immuno-PET with [89Zr]Zr-Df-ATG-101 provides real-time information about ATG-101 distribution and tumour uptake in vivo. Our data support the use of [89Zr]Zr-Df-ATG-101 to assess tumour and tissue uptake of ATG-101.Conclusion: ATG-101, a bispecific antibody that simultaneously targets the immune checkpoint PD-L1 and the costimulatory receptor 4-1BB, activates exhausted T cells upon PD-L1 crosslinking. Previous studies demonstrated promising anti-tumour efficacy of ATG-101 in preclinical models. Here, we labelled ATG-101 with 89Zr to confirm its tumour targeting effect and tissue biodistribution in a preclinical model. We also evaluated the use of immuno-PET to study tumour uptake of ATG-101 in vivo.ATG-101, anti-PD-L1, and an isotype control were conjugated with p-SCN-Deferoxamine (Df). The Df-conjugated antibodies were radiolabelled with 89Zr, and their radiochemical purity, immunoreactivity, and serum stability were assessed. We conducted PET/MRI and biodistribution studies on [89Zr]Zr-Df-ATG-101 in BALB/c nude mice bearing PD-L1-expressing MDA-MB-231 breast cancer xenografts for up to 10 days after intravenous administration of [89Zr]Zr-labelled antibodies. The specificity of [89Zr]Zr-Df-ATG-101 was evaluated through a competition study with unlabelled ATG-101 and anti-PD-L1 antibodies.The Df-conjugation and [89Zr]Zr -radiolabelling did not affect the target binding of ATG-101. Biodistribution and imaging studies demonstrated biological similarity of [89Zr]Zr-Df-ATG-101 and [89Zr]Zr-Df-anti-PD-L1. Tumour uptake of [89Zr]Zr-Df-ATG-101 was clearly visualised using small-animal PET imaging up to 7 days post-injection. Competition studies confirmed the specificity of PD-L1 targeting in vivo.[89Zr]Zr-Df-ATG-101 in vivo distribution is dependent on PD-L1 expression in the MDA-MB-231 xenograft model. Immuno-PET with [89Zr]Zr-Df-ATG-101 provides real-time information about ATG-101 distribution and tumour uptake in vivo. Our data support the use of [89Zr]Zr-Df-ATG-101 to assess tumour and tissue uptake of ATG-101. [ABSTRACT FROM AUTHOR]

Chiplet integration technology offers enhanced performance and reduced costs by breaking down a large chip into smaller chiplets, which are then interconnected using advanced packaging technology. However, the current chiplet interconnects give priority to correctness concerns rather than load balancing issues. While prioritizing correctness aims to prevent deadlocks, a system that is free of deadlocks can still experience load imbalances that compromise its overall performance. This paper presents the LBDR strategy, which is a load-balanced deadlock-free routing strategy for chiplet systems, and effectively enhances the system performance. Firstly, we develop a novel boundary nodes selection criterion and a heuristic algorithm based node binding mechanism to maintain a balanced load on vertical links for each chiplet's outbound traffic. Secondly, we select turn restrictions at the boundary nodes to ensure that inbound traffic flows evenly into the chiplet, while maintaining a deadlock-free system. Experiments using the Garnet in gem5 simulator show that this strategy outperforms existing methods in terms of load balancing, throughput, and latency, and is applicable to a variety of traffic scenarios. • A binding mechanism is proposed to achieve load balancing of outbound traffic. • The turn restrictions are selected for almost equal opportunities to inbound traffic. • The simulation results demonstrate that this method outperforms existing methods. [ABSTRACT FROM AUTHOR]

Endometritis is a significant contributor to reduced productivity in yaks in Tibet, China. The Cyt-c/Caspase-3 signaling axis plays a crucial role in the mitochondrial pathway that triggers cell apoptosis due to endogenous factors. In this study, we examined the endometrial epithelial tissue of yaks with endometritis using pathological examination, immunohistochemical analysis, TUNEL staining, qRT-PCR, and Western blot. The results indicated significant changes in the apoptotic factors of the Cyt-c/Caspase-3 signaling axis. The expression levels of Bak1, Bax, Cyt-c, Apaf-1, Caspase-9, and Caspase-3 were significantly increased (P < 0.05), while the expression level of Bcl-2 was significantly decreased. Immunohistochemistry results revealed significant increase in Bak1, Bax, Cyt-c, Apaf-1, Caspase-9, and Caspase-3 expression in the cytoplasm compared to the healthy group, except for Bcl-2, which showed a significant decrease. Pathological section analysis demonstrated that clinical endometritis in yaks led to structural damage, bleeding, congestion, and inflammatory cell infiltration in the endometrial epithelium. Our study findings indicated that clinical endometritis in yaks can modulate apoptosis of endometrial epithelial cells via the Cyt-c/Caspase-3 signaling pathway, resulting in different levels of damage. This research is pioneering in exploring cell apoptosis induced by clinical endometritis in yaks, offering novel insights and potential strategies for the future prevention and treatment of endometritis in yaks. • The occurrence of yak endometritis is accompanied by cell apoptosis. • The Cyt-c/Caspase-3 signaling axis and its related factors play a significant role in the development of yak endometritis. • This study provides new insights into the relationship between endometritis and apoptosis in yak. [ABSTRACT FROM AUTHOR]

Background and Aims: Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)‐derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies. Design and Setting: Cross‐sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14–22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17–22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22–37 years). Cases: Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected. Measurements Graph theory metrics of segregation and integration were used to summarize SCN. Findings Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = −0.029, P = 0.002], lower modularity (AUC = −0.14, P = 0.004), lower average shortest path length (AUC = −0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = −0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar. Conclusion: Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN‐derived metrics to detect brain‐related psychopathology. [ABSTRACT FROM AUTHOR]