Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks

In this paper, we propose a novel layer-adaptive weight-pruning approach for Deep Neural Networks (DNNs) that addresses the challenge of optimizing the output distortion minimization while adhering to a target pruning ratio constraint. Our approach takes into account the collective influence of all layers to design a layer-adaptive pruning scheme. We discover and utilize a very important additivity property of output distortion caused by pruning weights on multiple layers. This property enables us to formulate the pruning as a combinatorial optimization problem and efficiently solve it through dynamic programming. By decomposing the problem into sub-problems, we achieve linear time complexity, making our optimization algorithm fast and feasible to run on CPUs. Our extensive experiments demonstrate the superiority of our approach over existing methods on the ImageNet and CIFAR-10 datasets. On CIFAR-10, our method achieves remarkable improvements, outperforming others by up to 1.0% for ResNet-32, 0.5% for VGG-16, and 0.7% for DenseNet-121 in terms of top-1 accuracy. On ImageNet, we achieve up to 4.7% and 4.6% higher top-1 accuracy compared to other methods for VGG-16 and ResNet-50, respectively. These results highlight the effectiveness and practicality of our approach for enhancing DNN performance through layer-adaptive weight pruning. Code will be available on https://github.com/Akimoto-Cris/RD_VIT_PRUNE

Functional evaluation of Asp76, 84, 102 and 150 in human arsenic(III) methyltransferase (hAS3MT) interacting with S-adenosylmethionine

AbstractWe prepared eight mutants (D76P, D76N, D84P, D84N, D102P, D102N, D150P and D150N) to investigate the functions of residues Asp76, 84, 102 and 150 in human arsenic(III) methyltransferase (hAS3MT) interacting with the S-adenosylmethionine (SAM)-binding. The affinity of all the mutants for SAM were weakened. All the mutants except for D150N completely lost their methylation activities. Residues Asp76, 84, 102 and 150 greatly influenced hAS3MT catalytic activity via affecting SAM-binding or methyl transfer. Asp76 and 84 were located in the SAM-binding pocket, and Asp102 significantly affected SAM-binding via forming hydrogen bonds with SAM

PI3K/AKT/mTOR pathway-derived risk score exhibits correlation with immune infiltration in uveal melanoma patients

Uveal melanoma (UVM) is a rare but highly aggressive intraocular tumor with a poor prognosis and limited therapeutic options. Recent studies have implicated the PI3K/AKT/mTOR pathway in the pathogenesis and progression of UVM. Here, we aimed to explore the potential mechanism of PI3K/AKT/mTOR pathway-related genes (PRGs) in UVM and develop a novel prognostic-related risk model. Using unsupervised clustering on 14 PRGs profiles, we identified three distinct subtypes with varying immune characteristics. Subtype A demonstrated the worst overall survival and showed higher expression of human leukocyte antigen, immune checkpoints, and immune cell infiltration. Further enrichment analysis revealed that subtype A mainly functioned in inflammatory response, apoptosis, angiogenesis, and the PI3K/AKT/mTOR signaling pathway. Differential analysis between different subtypes identified 56 differentially expressed genes (DEGs), with the major enrichment pathway of these DEGs associated with PI3K/AKT/mTOR. Based on these DEGs, we developed a consensus machine learning-derived signature (RSF model) that exhibited the best power for predicting prognosis among 76 algorithm combinations. The novel signature demonstrated excellent robustness and predictive ability for the overall survival of patients. Moreover, we observed that patients classified by risk scores had distinguishable immune status and mutation. In conclusion, our study identified a consensus machine learning-derived signature as a potential biomarker for prognostic prediction in UVM patients. Our findings suggest that this signature is correlated with tumor immune infiltration and may serve as a valuable tool for personalized therapy in the clinical setting

Clinical outcome and prognostic factors of patients with non-traumatic angiography-negative subarachnoid hemorrhage

PurposeThe cause of spontaneous subarachnoid hemorrhage (SAH) is unknown in 10% of cases. The aim of this study was to demonstrate the characteristics of patients with angiography-negative subarachnoid hemorrhage (anSAH) and to analyze factors influencing the clinical outcome in patients suffering from anSAH.MethodsA retrospective cohort of 75 patients with anSAH [26 perimesencephalic (pmSAH) and 49 non-perimesencephalic SAH (npmSAH)] admitted between January 2016 and June 2022 was included. We analyzed demographic, clinical data and 6-month functional outcomes. Enter regression analysis was performed to identify factors associated with outcomes.ResultsUnfavorable outcome was achieved in 10 of 75 patients (13.3%). Unfavorable outcome was associated with senior adults (p = 0.008), Hijdra cistern score (HCS) elevation (p = 0.015), long-time lumbar cistern continuous drainage (LCFD; p = 0.029) and hydrocephalus (p = 0.046). The only significant risk factor for unfavorable outcome after npmSAH was the HCS (OR 1.213 (95%CI 1.007–1.462), p = 0.042).ConclusionOur study provides valuable information on both SAH patterns and functional outcome in patients suffering from anSAH and should be taken into consideration during management of these patients

Predictive values of clinical data,molecular biomarkers, and echocardiographic measurements in preterm infants with bronchopulmonary dysplasia

ObjectiveWe aimed to use molecular biomarkers and clinical data and echocardiograms that were collected during admission to predict bronchopulmonary dysplasia (BPD) in preterm infants with gestational age ≤32 weeks.MethodsEighty-two patients (40 with BPD, BPD group and 42 healthy as controls, non-BPD group) admitted to the Department of Neonatology of the Children's Hospital of Soochow University between October 1, 2018, and February 29, 2020, were enrolled in this study at the tertiary hospital. Basic clinical data on the perinatal period, echocardiographic measurements, and molecular biomarkers (N-terminal-pro-B-brain natriuretic peptide, NT-proBNP) were collected. We used multiple logistic regression analysis to establish an early predictive model for detecting BPD development in preterm infants of gestational age ≤32 weeks. We also used a receiver operating characteristic curve to assess the sensitivity and specificity of the model.ResultsNo significant differences were found between the BPD and non-BPD groups in terms of sex, birth weight, gestational age, incidence of asphyxia, maternal age, gravidity, parity, mode of delivery, premature rupture of membranes >18 h, use of prenatal hormones, placental abruption, gestational diabetes mellitus, amniotic fluid contamination, prenatal infections, and maternal diseases. The use of caffeine, albumin, gamma globulin; ventilation; days of FiO2 ≥ 40%; oxygen inhalation time; red blood cell suspension infusion volume (ml/kg); and proportion of infants who received total enteral nutrition (120 kcal/kg.d) ≥24 d after birth were higher in the BPD group than in the non-BPD group. The levels of hemoglobin, hematocrit, and albumin in the BPD group were significantly lower than those in the non-BPD group. The total calorie intake was significantly lower in the BPD group on the 3rd, 7th, and 14th day after birth than in the non-BPD group (P < 0.05). The incidence rates of patent ductus arteriosus (PDA), pulmonary hypertension, and tricuspid regurgitation were significantly higher in the BPD group than in the non-BPD group (P < 0.05). The serum level of NT-proBNP 24 h after birth was significantly higher in the BPD group than in the non-BPD group (P < 0.05). Serum NT-proBNP levels were significantly higher in infants with severe BPD than in those with mild or moderate BPD (P < 0.05).ConclusionAs there were various risk factors for BPD, a combining clinical data, molecular biomarkers, and echocardiogram measurements can be valuable in predicting the BPD. The tricuspid regurgitation flow rate (m/s), NT-proBNP (pg/ml), ventilator-associated pneumonia, days of FiO2 ≥ 40% (d), red blood cell suspension infusion volume (ml/kg), and proportion of infants who received total enteral nutrition (120 kcal/kg.d) ≥24 d after birth were the most practical factors considered for designing an appropriate model for predicting the risk of BPD

CAMKs support development of acute myeloid leukemia.

BACKGROUND: We recently identified the human leukocyte immunoglobulin-like receptor B2 (LILRB2) and its mouse ortholog-paired Ig-like receptor (PirB) as receptors for several angiopoietin-like proteins (Angptls). We also demonstrated that PirB is important for the development of acute myeloid leukemia (AML), but exactly how an inhibitory receptor such as PirB can support cancer development is intriguing. RESULTS: Here, we showed that the activation of Ca (2+)/calmodulin-dependent protein kinases (CAMKs) is coupled with PirB signaling in AML cells. High expression of CAMKs is associated with a poor overall survival probability in patients with AML. Knockdown of CAMKI or CAMKIV decreased human acute leukemia development in vitro and in vivo. Mouse AML cells that are defective in PirB signaling had decreased activation of CAMKs, and the forced expression of CAMK partially rescued the PirB-defective phenotype in the MLL-AF9 AML mouse model. The inhibition of CAMK kinase activity or deletion of CAMKIV significantly slowed AML development and decreased the AML stem cell activity. We also found that CAMKIV acts through the phosphorylation of one of its well-known target (CREB) in AML cells. CONCLUSION: CAMKs are essential for the growth of human and mouse AML. The inhibition of CAMK signaling may become an effective strategy for treating leukemia

Molecular Characterization, Phylogenetic, Expression, and Protective Immunity Analysis of OmpF, a Promising Candidate Immunogen Against Yersinia ruckeri Infection in Channel Catfish

Outer membrane porins, as the major components of Gram-negative bacterial membrane proteins, have been proven to be involved in interactions with the host immune system and potent protective antigen candidates against bacterial infection in fish. Outer membrane porin F (OmpF) is one of the major porins of Yersinia ruckeri (Y. ruckeri), the causative agent of enteric red mouth disease of salmonid and non-salmonid fish. In the present study, the molecular characterization and phylogenetic analysis of OmpF gene was studied, heterogenous expression, immunogenicity and protective immunity of OmpF were systemically evaluated as a subunit vaccine for channel catfish against Y. ruckeri infection. The results showed that OmpF gene was highly conserved among 15 known Yersinia species based on the analysis of conserved motifs, sequences alignment and phylogenetic tree, and was subjected to negative/purifying selection with global dN/dS ratios value of 0.649 throughout the evolution. Besides, OmpF was also identified to have immunogenicity by western blotting and was verified to be located on the surface of Y. ruckeri using cell surface staining and indirect immunofluorescence assays. Moreover, recombinant OmpF (rtOmpF) as a subunit vaccine was injected with commercial adjuvant ISA763, significantly enhanced the immune response by increasing serum antibody levels, lysozyme activity, complement C3 activity, total protein content, SOD activity, immune-related genes expression in the head kidney and spleen, and survival percent of channel catfish against Y. ruckeri infection. Thus, our present results not only enriched the information of molecular characterization and phylogenetics of OmpF, but also demonstrated that OmpF holds promise to be used as a potential antigen against Y. ruckeri infection in fish