Characterizing the Relationship between Expression Quantitative Trait Loci (eQTLs), DNA Methylation Quantitative Trait Loci (mQTLs), and Breast Cancer Risk Variants.

PURPOSE: To assess the association of a polygenic risk score (PRS) for functional genetic variants with the risk of developing breast cancer. METHODS: Summary data-based Mendelian randomization (SMR) and heterogeneity in dependent instruments (HEIDI) were used to identify breast cancer risk variants associated with gene expression and DNA methylation levels. A new SMR-based PRS was computed from the identified variants (functional PRS) and compared to an established 313-variant breast cancer PRS (GWAS PRS). The two scores were evaluated in 3560 breast cancer cases and 3383 non-cancer controls and also in a prospective study (n = 10,213) comprising 418 cases. RESULTS: We identified 149 variants showing pleiotropic association with breast cancer risk (eQTLHEIDI > 0.05 = 9, mQTLHEIDI > 0.05 = 165). The discriminatory ability of the functional PRS (AUCcontinuous [95% CI]: 0.540 [0.526 to 0.553]) was found to be lower than that of the GWAS PRS (AUCcontinuous [95% CI]: 0.609 [0.596 to 0.622]). Even when utilizing 457 distinct variants from both the functional and GWAS PRS, the combined discriminatory performance remained below that of the GWAS PRS (AUCcontinuous, combined [95% CI]: 0.561 [0.548 to 0.575]). A binary high/low-risk classification based on the 80th centile PRS in controls revealed a 6% increase in cases using the GWAS PRS compared to the functional PRS. The functional PRS identified an additional 12% of high-risk cases but also led to a 13% increase in high-risk classification among controls. Similar findings were observed in the SCHS prospective cohort, where the GWAS PRS outperformed the functional PRS, and the highest-performing PRS, a combined model, did not significantly improve over the GWAS PRS. CONCLUSIONS: While this study identified potentially functional variants associated with breast cancer risk, their inclusion did not substantially enhance the predictive accuracy of the GWAS PRS.

Integrated mendelian randomization analyses highlight AFF3 as a novel eQTL-mediated susceptibility gene in renal cancer and its potential mechanisms.

BACKGROUNDS: A growing number of expression quantitative trait loci (eQTLs) have been found to be linked with tumorigenesis. In this article, we employed integrated Mendelian randomization (MR) analyses to identify novel susceptibility genes in renal cancer (RC) and reveal their potential mechanisms. METHODS: Two-sample MR analyses were performed to infer causal relationships between eQTLs, metabolites, and RC risks through the "TwoSampleMR" R package. Sensitivity analyses, such as heterogeneity, pleiotropy, and leave-one-out analysis, were used to assess the stability of our outcomes. Summary-data-based MR (SMR) analyses were used to verify the causal relationships among cis-eQTLs and RC risks via the SMR 1.3.1 software. RESULTS: Our results provided the first evidence for AFF3 eQTL elevating RC risks, suggesting its oncogenic roles (IVW method; odds ratio (OR) = 1.0005; 95% confidence interval (CI) = 1.0001-1.0010; P = 0.0285; heterogeneity = 0.9588; pleiotropy = 0.8397). Further SMR analysis validated the causal relationships among AFF3 cis-eQTLs and RC risks (P < 0.05). Moreover, the TCGA-KIRC, the ICGC-RC, and the GSE159115 datasets verified that the AFF3 gene was more highly expressed in RC tumors than normal control via scRNA-sequencing and bulk RNA-sequencing (P < 0.05). Gene set enrichment analysis (GSEA) analysis identified six potential biological pathways of AFF3 involved in RC. As for the potential mechanism of AFF3 in RC, we concluded in this article that AFF3 eQTL could negatively modulate the levels of the X-11,315 metabolite (IVW method; OR = 0.9127; 95% CI = 0.8530-0.9765; P = 0.0081; heterogeneity = 0.4150; pleiotropy = 0.8852), exhibiting preventive effects against RC risks (IVW method; OR = 0.9987; 95% CI = 0.9975-0.9999; P = 0.0380; heterogeneity = 0.5362; pleiotropy = 0.9808). CONCLUSIONS: We concluded that AFF3 could serve as a novel eQTL-mediated susceptibility gene in RC and reveal its potential mechanism of elevating RC risks via negatively regulating the X-11,315 metabolite levels.

The relationship between innate/adaptive immunity and gastrointestinal cancer : a multi-omics Mendelian randomization study.

BACKGROUND: Innate/adaptive immunity is the key to anti-tumor therapy. However, its causal relationship to Gastrointestinal (GI) cancer remains unclear. METHODS: Immunity genes were extracted from the MSigDB database. The Genome-wide association studies (GWAS) summary data of GI cancer were integrated with expression quantitative trait loci (eQTL) and DNA methylation quantitative trait loci (mQTL) associated with genes. Summary-data-based Mendelian randomization (SMR) and co-localization analysis were used to reveal causal relationships between genes and GI cancer. Two-sample MR analysis was used for sensitivity analysis. Single cell analysis clarified the enrichment of genes. RESULTS: Three-step SMR analysis showed that a putative mechanism, cg17294865 CpG site regulating HLA-DRA expression was negatively associated with gastric cancer risk. HLA-DRA was significantly differentially expressed in monocyte/macrophage and myeloid cells in gastric cancer. CONCLUSION: This study provides evidence that upregulating the expression level of HLA-DRA can reduce the risk of gastric cancer.

Mechanical Properties Comparison of Isotropic vs. Anisotropic Hybrid Magnetorheological Elastomer-Fluid.

Magnetorheological (MR) materials are smart materials that can change their rheological characteristics when exposed to a magnetic field. Such rheological properties include viscosity and dynamic modulus. MR materials have emerged as one of the most efficient smart materials that can modify mechanical and viscoelastic characteristics. Depending on the medium used, MR materials can be classified into two types: magnetorheological fluids (MRFs) and magnetorheological elastomers (MREs). MREs are classified as isotropic or anisotropic based on CIP distribution inside the elastomer matrix. A unique hybrid material incorporating MRE and MRF is constructed in this work to investigate, compare, and the dynamic properties of isotropic, anisotropic, hybrid isotropic, and hybrid anisotropic MREs under various magnetic fields (0, 104, and 160.2 mT). The created samples are subjected to extensive testing, including static and dynamic evaluations. In the static tests, experiments use a compression linear displacement mode with a fixed maximum gap change of 3 mm. The temperature is maintained at a constant level of 24 °C throughout the 40 s test duration for each test, and the magnetic field is incrementally increased by varying the number of magnets, ranging from 0 to 160.2 mT for dynamic qualities using compression oscillations on a dynamic mechanical analyzer (DMA), including frequency and strain-dependent data. These experiments, carried out using sinusoidal shear movements, include an excitation frequency range of 0.1 Hz to 15 Hz while preserving, with a fixed shear strain of 2%.

Mendelian randomization combined with multi-omics explores the relationship between heart failure and cancer.

Background: Whether there is an association between HF (HF) and cancer has not been conclusively established, and it is not clear whether patients with cancer can share similar hospitalization strategies and outcomes with patients with HF. Methods: Genome-wide association summary statistics were performed using a two-sample Mendelian randomization (MR) method for HF patients and cancer patients from the GWAS directory, with co-localization and Summary Data-Based Mendelian Randomization (SMR) analyses to identify HF-associated genes, and transcriptomic analyses to analyze the roles of these genes in the clinical diagnosis and targeted therapies of multiple cancer types. Results: Two-sample MR analysis showed that increased risk of HF was associated with decreased risk of cervical, brain, breast, colorectal, lung, and skin cancers, and co-localization combined with SMR analysis identified ABO and SURF1 as HF-associated genes, and transcriptomic analyses showed that ABO is a risk factor for HF and a protective factor against cancer, whereas SURF1 is a protective factor against HF and a protective factor against cancer. Conclusion: There was no causal relationship between heart failure and cancers (Cervical, brain, breast, colorectal, lung and skin cancers) risk factors, however there was a trend toward a negative causal relationship between heart failure and cancers (Cervical, brain, breast, colorectal, lung and skin cancers) occurrence.

Deciphering recovery paradigms: Foam rolling's impact on DOMS and lactate dynamics in elite volleyball athletes.

This study examines the effects of Self-Myofascial Release (SMR) techniques on post-exercise recovery in elite volleyball athletes. Through a controlled investigation involving eighteen Chinese Men's National Volleyball Team athletes, the research assessed the impact of foam rolling (FR) versus passive recovery (PAS) on blood lactate clearance and Delayed Onset Muscle Soreness (DOMS), as measured by Visual Analogue Scale (VAS) scores. Findings indicated that FR significantly reduces VAS scores and facilitates lactate clearance when compared to PAS, suggesting foam rolling may enhance post-exercise recovery. While confirming foam rolling's benefits, this research calls for further exploration into recovery mechanisms, emphasizing a cautious interpretation of foam rolling as part of a comprehensive recovery strategy.

xWAS analysis in neuropsychiatric disorders by integrating multi-molecular phenotype quantitative trait loci and GWAS summary data.

BACKGROUND: Integrating quantitative trait loci (QTL) data related to molecular phenotypes with genome-wide association study (GWAS) data is an important post-GWAS strategic approach employed to identify disease-associated molecular features. Various types of molecular phenotypes have been investigated in neuropsychiatric disorders. However, these findings pertaining to distinct molecular features are often independent of each other, posing challenges for having an overview of the mapped genes. METHODS: In this study, we comprehensively summarized published analyses focusing on four types of risk-related molecular features (gene expression, splicing transcriptome, protein abundance, and DNA methylation) across five common neuropsychiatric disorders. Subsequently, we conducted supplementary analyses with the latest GWAS dataset and corresponding deficient molecular phenotypes using Functional Summary-based Imputation (FUSION) and summary data-based Mendelian randomization (SMR). Based on the curated and supplemented results, novel reliable genes and their functions were explored. RESULTS: Our findings revealed that eQTL exhibited superior ability in prioritizing risk genes compared to the other QTL, followed by sQTL. Approximately half of the genes associated with splicing transcriptome, protein abundance, and DNA methylation were successfully replicated by eQTL-associated genes across all five disorders. Furthermore, we identified 436 novel reliable genes, which enriched in pathways related with neurotransmitter transportation such as synaptic, dendrite, vesicles, axon along with correlations with other neuropsychiatric disorders. Finally, we identified ten multiple molecular involved regulation patterns (MMRP), which may provide valuable insights into understanding the contribution of molecular regulation network targeting these disease-associated genes. CONCLUSIONS: The analyses prioritized novel and reliable gene sets related with five molecular features based on published and supplementary results for five common neuropsychiatric disorders, which were missed in the original GWAS analysis. Besides, the involved MMRP behind these genes could be given priority for further investigation to elucidate the pathogenic molecular mechanisms underlying neuropsychiatric disorders in future studies.

Machine learning and XAI approaches highlight the strong connection between O 3 and N O 2 pollutants and Alzheimer's disease.

Alzheimer's disease (AD) is the most common type of dementia with millions of affected patients worldwide. Currently, there is still no cure and AD is often diagnosed long time after onset because there is no clear diagnosis. Thus, it is essential to study the physiology and pathogenesis of AD, investigating the risk factors that could be strongly connected to the disease onset. Despite AD, like other complex diseases, is the result of the combination of several factors, there is emerging agreement that environmental pollution should play a pivotal role in the causes of disease. In this work, we implemented an Artificial Intelligence model to predict AD mortality, expressed as Standardized Mortality Ratio, at Italian provincial level over 5 years. We employed a set of publicly available variables concerning pollution, health, society and economy to feed a Random Forest algorithm. Using methods based on eXplainable Artificial Intelligence (XAI) we found that air pollution (mainly O 3 and N O 2 ) contribute the most to AD mortality prediction. These results could help to shed light on the etiology of Alzheimer's disease and to confirm the urgent need to further investigate the relationship between the environment and the disease.

Excess mortality in patients with non-functioning pituitary adenoma: a systematic review and meta-analysis.

BACKGROUND: Patients with non-functioning pituitary adenoma (NFPA) often present with a variety of clinical manifestations and comorbidities, mainly determined by the local mass effect of the tumor and by hypopituitarism. Whether this has an impact on overall mortality, however, is still unclear. METHODS: PubMed/Medline, EMBASE, and Cochrane Library databases were systematically searched until May 2023 for studies reporting data either about standardized mortality ratios (SMRs) or about predictors of mortality in patients with NFPA. Effect sizes were pooled through a random-effect model. This systematic review and meta-analysis was registered in the International Prospective Register of Systematic Reviews (PROSPERO, #CRD42023417782). RESULTS: Eleven studies were eligible for inclusion in the systematic review; among these, five studies reported data on SMRs, with a total follow-up time of approximately 130,000 person-years. Patients with NFPA showed an increased mortality risk compared to the general population (SMR = 1.57 [95%CI: 1.20-1.99], p < 0.01). Age and sex appeared to act as effect modifiers, with a trend towards higher SMRs in females (SMR = 1.57 [95%CI: 0.91-2.41], p = 0.10) than in males (SMR = 1.00 [95%CI: 0.89-1.11], p = 0.97), and in patients diagnosed at age 40 years or younger (SMR = 3.19 [95%CI: 2.50-3.97], p < 0.01) compared to those with later onset of the disease (SMR = 1.26 [95%CI: 0.93-1.65], p = 0.13). The trend towards excess mortality was similar in patients with normal (SMR = 1.22 [95%CI: 0.94-1.53], p = 0.13) or deficient (SMR = 1.26 [95%CI: 0.82-1.79], p = 0.27) pituitary function. CONCLUSIONS: Excess mortality is observed in patients with NFPA, regardless of pituitary function, especially in women and in patients with a younger age at diagnosis.

Neurofeedback and epilepsy: Renaissance of an old self-regulation method?

Neurofeedback is a brain-computer interface tool enabling the user to self-regulate their neuronal activity, and ultimately, induce long-term brain plasticity, making it an interesting instrument to cure brain disorders. Although this method has been used successfully in the past as an adjunctive therapy in drug-resistant epilepsy, this approach remains under-explored and deserves more rigorous scientific inquiry. In this review, we present early neurofeedback protocols employed in epilepsy and provide a critical overview of the main clinical studies. We also describe the potential neurophysiological mechanisms through which neurofeedback may produce its therapeutic effects. Finally, we discuss how to innovate and standardize future neurofeedback clinical trials in epilepsy based on evidence from recent research studies.

Do Miniature Eye Movements Affect Neurofeedback Training Performance? A Combined EEG-Eye Tracking Study.

EEG-based neurofeedback is a prominent method to modulate one's own brain activity in a desired direction. However, the EEG signal can be disturbed by artifacts, e.g., eye movements, which can consequently confound the neurofeedback performance. Involuntary miniature eye movements can be hardly detected by conventional EEG correction methods such as recording the electro-oculogram (EOG) and subtracting EOG activity from the EEG signal. However, such miniature eye movements can influence EEG activity, especially in the Gamma frequency range, enormously. In the present study, we investigated whether power in different EEG frequencies can be effectively modulated by self-control of brain signals during neurofeedback training and/or whether changes in EEG power are provoked by miniature eye movements during the training. To this end, 24 participants performed one session of SMR and one session of Gamma neurofeedback training. Additionally, in each training session sham feedback was performed. An eye tracker was used to detect miniature eye movements (< 1°) during neurofeedback training. About two thirds of the participants were able to increase their SMR power over the course of NF training, while one third was able to increase Gamma power. Generally, miniature eye movements induced a strong Gamma power increase. The number of eye movements also increased numerically over the course of the NF training. However, we did not find a significant relationship with the NF training performance. This is a first indication that miniature saccades do not affect NF training performance, but should not be neglected during NF training. Our results have to be confirmed in future studies.

Do the humeral radiographic changes at 5-year follow-up affect the clinical outcomes of press-fit humeral stems in primary reverse shoulder arthroplasties?

INTRODUCTION: The purposes of this study were to analyze and compare the functional outcomes and radiological changes around the press-fit humeral components in two contemporary medialized reverse total shoulder arthroplasty (RTSA) systems at a minimum of 5-year follow-up. MATERIALS AND METHODS: Between December 2003 and December 2015, 249 consecutive RTSAs were performed at our hospital. Of these, 68 primary uncemented RTSA met our inclusion criteria. The Constant-Murley score (CMS), the modified Constant score, a visual analog scale (VAS) and active shoulder range of motion (ROM) were measured pre- and postoperatively. Radiological assessment was performed by plain radiographs at a minimum of 5 years postoperatively. RESULTS: At a mean follow-up of 80.2 months, there was no significant difference (p = .59) between the postoperative functional scores and range of motion of the two groups (Delta Xtend and Lima SMR). Radiological data of stress-shielding were observed in 38 patients (55.9%) being slightly more frequent in the Lima SMR group (21 patients) than in the Delta Xtend group (17 patients) (p = .62). CONCLUSIONS: Our study shows that the good functional results are similar between the two uncemented RTSA systems used and that they do not depend on the presence of radiological changes (stress-shielding) in the humeral stem at a minimum 5-year follow-up.

The Evolving Concept of Secondary Mitral Regurgitation Phenotypes: Lessons From the M-TEER Trials.

Conflicting results from 2 randomized clinical trials of transcatheter mitral valve edge-to-edge repair in secondary mitral regurgitation (SMR) have led to the recognition that SMR is a heterogeneous disease entity presenting with different functional and morphological phenotypes. This review summarizes the current knowledge on SMR caused primarily by atrial secondary mitral regurgitation (aSMR) and ventricular SMR pathology. Although aSMR is generally characterized by severe left atrial enlargement in the setting of preserved left ventricular anatomy and function, different patterns of mitral annular distortion cause different phenotypes of aSMR. In ventricular SMR, the relation of SMR severity to left ventricular dilation as well as the degree of pulmonary hypertension and right ventricular dysfunction are important phenotypic characteristics, which are key for a better understanding of prognosis and treatment response.

The SIAMESE family of cell-cycle inhibitors in the response of plants to environmental stresses.

Environmental abiotic constraints are known to reduce plant growth. This effect is largely due to the inhibition of cell division in the leaf and root meristems caused by perturbations of the cell cycle machinery. Progression of the cell cycle is regulated by CDK kinases whose phosphorylation activities are dependent on cyclin proteins. Recent results have emphasized the role of inhibitors of the cyclin-CDK complexes in the impairment of the cell cycle and the resulting growth inhibition under environmental constraints. Those cyclin-CDK inhibitors (CKIs) include the KRP and SIAMESE families of proteins. This review presents the current knowledge on how CKIs respond to environmental changes and on the role played by one subclass of CKIs, the SIAMESE RELATED proteins (SMRs), in the tolerance of plants to abiotic stresses. The SMRs could play a central role in adjusting the balance between growth and stress defenses in plants exposed to environmental stresses.

Unraveling motor imagery brain patterns using explainable artificial intelligence based on Shapley values.

BACKGROUND AND OBJECTIVE: Motor imagery (MI) based brain-computer interfaces (BCIs) are widely used in rehabilitation due to the close relationship that exists between MI and motor execution (ME). However, the underlying brain mechanisms of MI remain not well understood. Most MI-BCIs use the sensorimotor rhythms elicited in the primary motor cortex (M1) and somatosensory cortex (S1), which consist of an event-related desynchronization followed by an event-related synchronization. Consequently, this has resulted in systems that only record signals around M1 and S1. However, MI could involve a more complex network including sensory, association, and motor areas. In this study, we hypothesize that the superior accuracies achieved by new deep learning (DL) models applied to MI decoding rely on focusing on a broader MI activation of the brain. Parallel to the success of DL, the field of explainable artificial intelligence (XAI) has seen continuous development to provide explanations for DL networks success. The goal of this study is to use XAI in combination with DL to extract information about MI brain activation patterns from non-invasive electroencephalography (EEG) signals. METHODS: We applied an adaptation of Shapley additive explanations (SHAP) to EEGSym, a state-of-the-art DL network with exceptional transfer learning capabilities for inter-subject MI classification. We obtained the SHAP values from two public databases comprising 171 users generating left and right hand MI instances with and without real-time feedback. RESULTS: We found that EEGSym based most of its prediction on the signal of the frontal electrodes, i.e. F7 and F8, and on the first 1500 ms of the analyzed imagination period. We also found that MI involves a broad network not only based on M1 and S1, but also on the prefrontal cortex (PFC) and the posterior parietal cortex (PPC). We further applied this knowledge to select a 8-electrode configuration that reached inter-subject accuracies of 86.5% ± 10.6% on the Physionet dataset and 88.7% ± 7.0% on the Carnegie Mellon University's dataset. CONCLUSION: Our results demonstrate the potential of combining DL and SHAP-based XAI to unravel the brain network involved in producing MI. Furthermore, SHAP values can optimize the requirements for out-of-laboratory BCI applications involving real users.

Low skeletal muscle radiodensity is a risk factor for adjuvant chemotherapy discontinuation in colorectal cancer.

BACKGROUND: Previously, we reported SMR (skeletal muscle radiodensity) as a potential prognostic marker for colorectal cancer. However, there have been limited studies on the association between SMR and the continuation of adjuvant chemotherapy in colorectal cancer. METHODS: In this retrospective study, 143 colorectal cancer patients underwent curative surgery and adjuvant chemotherapy using the CAPOX regimen. Patients' SMRs were measured from preoperative CT images and divided into low (bottom quarter) and high (top three quarters) SMR groups. We compared chemotherapy cycles, capecitabine and oxaliplatin doses, and adverse effects in each group. RESULTS: The low SMR group had significantly fewer patients completing adjuvant chemotherapy compared to the high SMR group (44% vs. 68%, P < 0.01). Capecitabine and oxaliplatin doses were also lower in the low SMR group. Incidences of Grade 2 or Grade 3 adverse effects did not differ between groups, but treatment discontinuation due to adverse effects was significantly higher in the low SMR group. Logistic regression analysis revealed Stage III disease (odds ratio 18.09, 95% CI 1.41-231.55) and low SMR (odds ratio 3.26, 95% CI 1.11-9.56) as factors associated with unsuccessful treatment completion. Additionally, a higher proportion of low SMR patients received fewer than 2 cycles of chemotherapy (50% vs. 12%). CONCLUSION: The low SMR group showed higher treatment incompletion rates and received lower drug doses during adjuvant chemotherapy. Low SMR independently contributed to treatment non-completion in colorectal cancer patients.

Functional promiscuity of small multidrug resistance transporters from Staphylococcus aureus, Pseudomonas aeruginosa, and Francisella tularensis.

Small multidrug resistance transporters efflux toxic compounds from bacteria and are a minimal system to understand multidrug transport. Most previous studies have focused on EmrE, the model SMR from Escherichia coli, finding that EmrE has a broader substrate profile than previously thought and that EmrE may perform multiple types of transport, resulting in substrate-dependent resistance or susceptibility. Here, we performed a broad screen to identify potential substrates of three other SMRs: PAsmr from Pseudomonas aeruginosa; FTsmr from Francisella tularensis; and SAsmr from Staphylococcus aureus. This screen tested metabolic differences in E. coli expressing each transporter versus an inactive mutant, for a clean comparison of sequence and substrate-specific differences in transporter function, and identified many substrates for each transporter. In general, resistance compounds were charged, and susceptibility substrates were uncharged, but hydrophobicity was not correlated with phenotype. Two resistance hits and two susceptibility hits were validated via growth assays and IC50 calculations. Susceptibility is proposed to occur via substrate-gated proton leak, and the addition of bicarbonate antagonizes the susceptibility phenotype, consistent with this hypothesis.

New perspectives on the potential of tetrandrine in the treatment of non-small cell lung cancer: bioinformatics, Mendelian randomization study and experimental investigation.

BACKGROUND: Although there are numerous treatment methods for NSCLC, long-term survival remains a challenge for patients. The objective of this study is to investigate the role and causal relationship between the target of tetrandrine and non-small cell lung cancer (NSCLC) through transcriptome and single-cell sequencing data, summary-data-based Mendelian Randomization (SMR) and basic experiments. The aim is to provide a new perspective for the treatment of NSCLC. METHODS: We obtained the drug target gene of tetrandrine through the drug database, and then used the GSE19188 data set to obtain the NSCLC pathogenic gene, established a drug-disease gene interaction network, screened out the hub drug-disease gene, and performed bioinformatics and tumor cell immune infiltration analysis. Single-cell sequencing data (GSE148071) to determine gene location, SMR to clarify causality and drug experiment verification. RESULTS: 10 drug-disease genes were obtained from 213 drug targets and 529 disease genes. DO/GO/KEGG analysis showed that the above genes were all related to the progression and invasion of NSCLC. Four drug-disease genes were identified from a drug-disease PPI network. These four genes were highly expressed in tumors and positively correlated with plasma cells, T cells, and macrophages. Subsequent single-cell sequencing data confirmed that these four genes were distributed in epithelial cells, and SMR analysis revealed the causal relationship between CCNA2 and CCNB1 and the development of NSCLC. The final molecular docking and drug experiments showed that CCNA2 and CCNB1 are key targets for tetrandrine in the treatment of NSCLC.

omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases.

Treatments for neurodegenerative disorders remain rare, but recent FDA approvals, such as lecanemab and aducanumab for Alzheimer disease (MIM: 607822), highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use summary-data-based Mendelian randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections (pSMR_multi < 2.95 × 10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community.

SMR peptide antagonizes Staphylococcus aureus biofilm formation.

The emergence and international dissemination of multi-drug resistant Staphylococcus aureus (S. aureus) strains challenge current antibiotic-based therapies, representing an urgent threat to public health worldwide. In the U.S. alone, S. aureus infections are responsible for 11,000 deaths and 500,000 hospitalizations annually. Biofilm formation is a major contributor to antibiotic tolerance and resistance-induced delays in empirical therapy with increased infection severity, frequency, treatment failure, and mortality. Developing novel treatment strategies to prevent and disrupt biofilm formation is imperative. In this article, we test the Secretion Modification Region (SMR) peptides for inhibitory effects on resistant S. aureus biofilm-forming capacity by targeting the molecular chaperone DnaK. The dose effect of SMR peptides on biofilm formation was assessed using microtiter plate methods and confocal microscopy. Interaction between the antagonist and DnaK was determined by immune precipitation with anti-Flag M2 Affinity and Western blot analysis. Increasing SMR peptide concentrations exhibited increasing blockade of S. aureus biofilm formation with significant inhibition found at 18 µM, 36 µM, and 72 µM. This work supports the potential therapeutic benefit of SMR peptides in reducing biofilm viability and could improve the susceptibility to antimicrobial agents.IMPORTANCEThe development of anti-biofilm agents is critical to restoring bacterial sensitivity, directly combating the evolution of resistance, and overall reducing the clinical burden related to pervasive biofilm-mediated infections. Thus, in this study, the SMR peptide, a novel small molecule derived from the HIV Nef protein, was preliminarily explored for anti-biofilm properties. The SMR peptide was shown to effectively target the molecular chaperone DnaK and inhibit biofilm formation in a dose-dependent manner. These results support further investigation into the mechanism of SMR peptide-mediated biofilm formation and inhibition to benefit rational drug design and the identification of therapeutic targets.