Lung adenocarcinoma promotion by air pollutants.

A complete understanding of how exposure to environmental substances promotes cancer formation is lacking. More than 70 years ago, tumorigenesis was proposed to occur in a two-step process: an initiating step that induces mutations in healthy cells, followed by a promoter step that triggers cancer development1. Here we propose that environmental particulate matter measuring ≤2.5 µm (PM2.5), known to be associated with lung cancer risk, promotes lung cancer by acting on cells that harbour pre-existing oncogenic mutations in healthy lung tissue. Focusing on EGFR-driven lung cancer, which is more common in never-smokers or light smokers, we found a significant association between PM2.5 levels and the incidence of lung cancer for 32,957 EGFR-driven lung cancer cases in four within-country cohorts. Functional mouse models revealed that air pollutants cause an influx of macrophages into the lung and release of interleukin-1ß. This process results in a progenitor-like cell state within EGFR mutant lung alveolar type II epithelial cells that fuels tumorigenesis. Ultradeep mutational profiling of histologically normal lung tissue from 295 individuals across 3 clinical cohorts revealed oncogenic EGFR and KRAS driver mutations in 18% and 53% of healthy tissue samples, respectively. These findings collectively support a tumour-promoting role for  PM2.5 air pollutants  and provide impetus for public health policy initiatives to address air pollution to reduce disease burden.

Prognostic Implications of Early Prediction in Posttraumatic Epilepsy.

Posttraumatic epilepsy (PTE) is a complication of traumatic brain injury that can increase morbidity, but predicting which patients may develop PTE remains a challenge. Much work has been done to identify a variety of risk factors and biomarkers, or a combination thereof, for patients at highest risk of PTE. However, several issues have hampered progress toward fully adapted PTE models. Such issues include the need for models that are well-validated, cost-effective, and account for competing outcomes like death. Additionally, while an accurate PTE prediction model can provide quantitative prognostic information, how such information is communicated to inform shared decision-making and treatment strategies requires consideration of an individual patient's clinical trajectory and unique values, especially given the current absence of direct anti-epileptogenic treatments. Future work exploring approaches integrating individualized communication of prediction model results are needed.

Chlorogenic acid, caffeic acid and luteolin from dandelion as urease inhibitors: insights into the molecular interactions and inhibition mechanism.

BACKGROUND: Dandelion contains hundreds of active compounds capable of inhibiting urease activity, but the individual compounds have not yet been fully identified, and their effects and underlying mechanisms are not clear. The present study aimed to screen the urease inhibition active compounds of dandelion by urease inhibitory activity evaluation HPLC-tandem mass spectrometry analysis, their mechanism of urease inhibition by polyphenols was explored using enzyme kinetic studies via Lineweaver-Burk plots. Other investigations included isothermal titration calorimetry and surface plasmon resonance sensing, fluorescence quenching experiments, and single ligand molecular docking and two-ligand simultaneous docking techniques. RESULTS: The results indicated that the ethyl acetate fraction of dandelion flower exhibited the greatest inhibition (lowest IC50 0.184 ± 0.007 mg mL-1). Chlorogenic acid, caffeic acid and luteolin could be effective urease inhibitors that acted in a non-competitive inhibition manner. Individually, chlorogenic acid could not only fast bind to urease, but also dissociate rapidly, whereas luteolin might interact with urease with the weakest affinity. The chlorogenic acid-caffeic acid combination exhibited an additive effect in urease inhibition. However, the chlorogenic acid-luteolin and caffeic acid-luteolin combinations exhibited antagonistic effects, with the caffeic acid-luteolin combination showing greater antagonism. CONCLUSION: The present study reveals that chlorogenic acid, caffeic acid and luteolin are major bioactive compounds for urease inhibition, indicating the molecular mechanisms. The antagonistic effects were observed between luteolin and chlorogenic acid/caffeic acid, and the interactions of the catalytic site and flap may account for the antagonistic effects. © 2024 Society of Chemical Industry.

Preparation and functional properties of rice bran globulin-chitooligosaccharide-quercetin-resveratrol covalent complex.

BACKGROUND: As the major protein (approximately 36%) in rice bran, globulin exhibits excellent foaming and emulsifying properties, endowing its useful application as a foaming and emulsifying agent in the food industry. However, the low water solubility restricts its commercial potential in industrial applications. The present study aimed to improve this protein's processing and functional properties. RESULTS: A novel covalent complex was fabricated by a combination of the Maillard reaction and alkaline oxidation using rice bran globulin (RBG), chitooligosaccharide (C), quercetin (Que) and resveratrol (Res). The Maillard reaction improved the solubility, emulsifying and foaming properties of RBG. The resultant glycosylated protein was covalently bonded with quercetin and resveratrol to form a (RBG-C)-Que-Res complex. (RBG-C)-Que-Res exhibited higher thermal stability and antioxidant ability than the native protein, binary globulin-chitooligosaccharide or ternary globulin-chitooligosaccharide-polyphenol (only containing quercetin or resveratrol) conjugates. (RBG-C)-Que-Res exerted better cytoprotection against the generation of malondialdehyde and reactive oxygen species in HepG2 cells, which was associated with increased activities of antioxidative enzymes superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GSH-Px) through upregulated genes SOD1, CAT, GPX1 (i.e. gene for glutathione peroxidase-1), GCLM (i.e. gene for glutamate cysteine ligase modifier subunit), SLC1A11 (i.e. gene for solute carrier family 7, member 11) and SRXN1 (i.e. gene for sulfiredoxin-1). The anti-apoptotic effect of (RBG-C)-Que-Res was confirmed by the downregulation of caspase-3 and p53 and the upregulation of B-cell lymphoma-2 gene expression. CONCLUSION: The present study highlights the potential of (RBG-C)-Que-Res conjugates as functional ingredients in healthy foods. © 2024 Society of Chemical Industry.

Mitochondrial heteroplasmic shifts reveal a positive selection of breast cancer.

BACKGROUND: Breast cancer is, despite screening, not always detected early enough and is together with other tumor types known to shed genetic information in circulation. Unlike single-copy nuclear DNA, mitochondrial DNA (mtDNA) copies range from 100s to 10,000s per cell, thus providing a potentially alternative to identify potential missing cancer information in circulation at an early stage. METHODS: To characterize mitochondrial mutation landscapes in breast cancer, whole mtDNA sequencing and bioinformatics analyses were performed on 86 breast cancer biopsies and 50 available matched baseline cancer-free whole blood samples from the same individuals, selected from a cohort of middle-aged women in Sweden. To determine whether the mutations can be detected in blood plasma prior to cancer diagnosis, we further designed a nested case-control study (n = 663) and validated the shortlisted mutations using droplet digital PCR. RESULTS: We detected different mutation landscapes between biopsies and matched whole blood samples. Compared to whole blood samples, mtDNA from biopsies had higher heteroplasmic mutations in the D-loop region (P = 0.02), RNR2 (P = 0.005), COX1 (P = 0.037) and CYTB (P = 0.006). Furthermore, the germline mtDNA mutations had higher heteroplasmy level than the lost (P = 0.002) and de novo mutations (P = 0.04). The nonsynonymous to synonymous substitution ratio (dN/dS) was higher for the heteroplasmic mutations (P = 7.25 × 10-12) than that for the homoplasmic mutations, but the de novo (P = 0.06) and lost mutations (P = 0.03) had lower dN/dS than the germline mutations. Interestingly, we found that the critical regions for mitochondrial transcription: MT-HSP1 (odds ratio [OR]: 21.41), MT-TFH (OR: 7.70) and MT-TAS2 (OR: 3.62), had significantly higher heteroplasmic mutations than the rest of the D-loop sub-regions. Finally, we found that the presence of mt.16093T > C mutation increases 67% risk of developing breast cancer. CONCLUSIONS: Our findings show that mitochondrial genetic landscape changes during cancer pathogenesis and positive selection of mtDNA heteroplasmic mutations in breast cancer. Most importantly, the mitochondrial mutations identified in biopsies can be traced back in matched plasma samples and could potentially be used as early breast cancer diagnostic biomarkers.

Quantitative epileptiform burden and electroencephalography background features predict post-traumatic epilepsy.

BACKGROUND: Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Electroencephalography aids early post-traumatic seizure diagnosis, but its optimal utility for PTE prediction remains unknown. We aim to evaluate the contribution of quantitative electroencephalograms to predict first-year PTE (PTE1). METHODS: We performed a multicentre, retrospective case-control study of patients with TBI. 63 PTE1 patients were matched with 63 non-PTE1 patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE1 using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities. RESULTS: In the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE1 risk based on multivariable logistic regression analysis (area under the receiver operating characteristic curve, AUC (95% CI) 0.69 (0.60 to 0.78)). Among 116 (92%) patients with available CT reports, adding quantitative electroencephalography features to a combined mechanism and CT model improved performance (AUC (95% CI), 0.71 (0.61 to 0.80) vs 0.61 (0.51 to 0.72)). CONCLUSIONS: Epileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE1 prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

Using System Dynamics Approach to Explore the Mode Shift between Automated Vehicles, Conventional Vehicles, and Public Transport in Melbourne, Australia.

With the increasing use of automated vehicles (AVs) in the coming decades, government authorities and private companies must leverage their potential disruption to benefit society. Few studies have considered the impact of AVs towards mode shift by considering a range of factors at the city level, especially in Australia. To address this knowledge gap, we developed a system dynamic (SD)-based model to explore the mode shift between conventional vehicles (CVs), AVs, and public transport (PT) by systematically considering a range of factors, such as road network, vehicle cost, public transport supply, and congestion level. By using Melbourne's Transport Network as a case study, the model simulates the mode shift among AVs, CVs, and PT modes in the transportation system over 50 years, starting from 2018, with the adoption of AVs beginning in 2025. Inputs such as current traffic, road capacity, public perception, and technological advancement of AVs are used to assess the effects of different policy options on the transport systems. The data source used is from the Victorian Integrated Transport Model (VITM), provided by the Department of Transport and Planning, Melbourne, Australia, data from the existing literature, and authors' assumptions. To our best knowledge, this is the first time using an SD model to investigate the impacts of AVs on mode shift in the Australian context. The findings suggest that AVs will gradually replace CVs as another primary mode of transportation. However, PT will still play a significant role in the transportation system, accounting for 50% of total trips by person after 2058. Cost is the most critical factor affecting AV adoption rates, followed by road network capacity and awareness programs. This study also identifies the need for future research to investigate the induced demand for travel due to the adoption of AVs and the application of equilibrium constraints to the traffic assignment model to increase model accuracy. These findings can be helpful for policymakers and stakeholders to make informed decisions regarding AV adoption policies and strategies.

Epigenetic mechanisms underlying the benefits of flavonoids in cardiovascular health and diseases: are long non-coding RNAs rising stars?

Cardiovascular diseases (CVDs) rank as the first leading cause of death globally. High dietary polyphenol (especially flavonoids) intake has strongly been associated with low incidence of the primary outcome, overall mortality, blood pressure, inflammatory biomarkers, onset of new-onset type 2 diabetes mellitus (T2DM), and obesity. Phytogenic flavonoids affect the physiological and pathological processes of CVDs by modulating various biochemical signaling pathways. Non-coding RNAs (ncRNAs) have attracted increasing attention as fundamental regulator of gene expression involved in CVDs. Among the different ncRNA subgroups, long ncRNAs (lncRNAs) have recently emerged as regulatory eukaryotic transcripts and therapeutic targets with important and diverse functions in health and diseases. lncRNAs may be associated with the initiation, development and progression of CVDs by modulating acute and chronic inflammation, adipogenesis and lipid metabolism, and cellular physiology. This review summarizes this research on the modulatory effects of lncRNAs and their roles in mediating cellular processes. The mechanisms of action of flavonoids underlying their therapeutic effects on CVDs are also discussed. Based on our review, flavonoids might facilitate a significant epigenetic modification as part (if not full) of their tissue-/cell-related biological effects. This finding may be attributed to their interaction with cellular signaling pathways involved in chronic diseases. Certain lncRNAs might be the target of specific flavonoids, and some critical signaling processes involved in the intervention of CVDs might mediate the therapeutic roles of flavonoids.

Litopenaeus vannamei peritrophin interacts with WSSV and AHPND-causing V. parahaemolyticus to regulate disease pathogenesis.

Peritrophins are peritrophic membrane (PM) proteins that can interact with chitin fibers via chitin-binding domains. Peritrophins have essential roles in providing porosity and strength to the PM that lines the shrimp midgut. Acute hepatopancreatic necrosis disease (AHPND), caused by strains of V. parahaemolyticus, is known to initially colonize the shrimp stomach and simultaneously disrupt its structural barriers (e.g., cuticle or epithelial tissues) to reach the hepatopancreas. Although stomach and hepatopancreas were identified as target tissues involved in AHPND pathogenesis, our results indicated that peritrophin in peritrophic membrane has a crucial role in determining not only colonization of AHPND-causing bacteria but also their tissue distribution. As the interaction between LvPeritrophin (LvPT) and WSSV (white spot syndrome virus) is not well understood, we noted that LvPT expression was upregulated in shrimp stomach challenged with either WSSV or AHPND. In an in vitro pathogen binding assay, there was strong binding of recombinant LvPT WSSV and AHPND-causing V. parahaemolyticus, and various bacteria. Furthermore, dsRNA-mediated LvPT silencing inhibited WSSV gene expression and viral genome replication. However, downregulation of LvPT gene expression increased copies of AHPND-causing bacteria in shrimp digestive tract, and facilitated bacterial colonization in stomach. In conclusion, we speculated that LvPT might regulate bacterial colonization during AHPND, whereas in WSSV infection, LvPT silencing favored the host. Although recombinant LvPT had strong binding with WSSV, the precise role of LvPT in WSSV infection needs further investigation. These findings increased our understanding of host-pathogen interactions in AHPND and WSSV infection that can be applied in shrimp aquaculture for developing effective antibacterial and antiviral strategies.

Peri-radiosurgical administration of bevacizumab improves radiographic response to single and fractionated stereotactic radiosurgery for large brain metastasis.

INTRODUCTION: Stereotactic radiosurgery (SRS) is a standard of care for brain metastases (BM) patients, yet large BM are at a greater risk for radionecrosis and local progression (LP). Concomitant bevacizumab and radiotherapy has been shown to improve outcomes in primary and metastatic brain tumors. This retrospective study investigated the efficacy and safety of concurrent bevacizumab and SRS for large BM. METHODS: From 2015 to 2019, patients with a BM diameter ≥ 2 cm who received either combination therapy (n = 49, SRS + BVZ group), or SRS alone (n = 73, SRS group) were enrolled. Bevacizumab was given peri-radiosurgically with a 2-week interval. Radiographic response was assessed using the RECIST version 1.1. Competing risk and logistic regression analysis were performed to evaluate prognostic factors. RESULTS: Radiographic response was achieved in 41 patients (84%) in the SRS + BVZ group and 37 patients (51%) in the SRS group (p = 0.001). In the multivariate regression analysis, concurrent bevacizumab was independently associated with a better radiographic response (p = 0.003). The cumulative incidences of LP and ≥ grade 2 radionecrosis at 12 months between the SRS + BVZ group and SRS group were 2% versus 6.8%, and 14.3% versus 14.6%, respectively. For patients with BM size ≥ 3 cm, the cumulative incidence of LP was significantly lower in the SRS + BVZ group (p = 0.03). No ≥ grade 4 toxicity was observed in either group. CONCLUSIONS: Concurrent bevacizumab and SRS for large BM is highly effective, with a better radiographic response and minimal excessive treatment-related toxicities. Peri-radiosurgical bevacizumab preferentially reduced the risk of LP, especially for BM size ≥ 3 cm.

Detection of circulating tumor cells and circulating tumor DNA before and after mammographic breast compression in a cohort of breast cancer patients scheduled for neoadjuvant treatment.

PURPOSE: It is not known if mammographic breast compression of a primary tumor causes shedding of tumor cells into the circulatory system. Little is known about how the detection of circulating biomarkers such as circulating tumor cells (CTCs) or circulating tumor DNA (ctDNA) is affected by breast compression intervention. METHODS: CTCs and ctDNA were analyzed in blood samples collected before and after breast compression in 31 patients with primary breast cancer scheduled for neoadjuvant therapy. All patients had a central venous access to allow administration of intravenous neoadjuvant chemotherapy, which enabled blood collection from superior vena cava, draining the breasts, in addition to sampling from a peripheral vein. RESULTS: CTC and ctDNA positivity was seen in 26% and 65% of the patients, respectively. There was a significant increase of ctDNA after breast compression in central blood (p = 0.01), not observed in peripheral testing. No increase related with breast compression was observed for CTC. ctDNA positivity was associated with older age (p = 0.05), and ctDNA increase after breast compression was associated with high Ki67 proliferating tumors (p = 0.04). CTCs were more abundant in central compared to peripheral blood samples (p = 0.04). CONCLUSIONS: There was no significant release of CTCs after mammographic breast compression but more CTCs were present in central compared to peripheral blood. No significant difference between central and peripheral levels of ctDNA was observed. The small average increase in ctDNA after breast compression is unlikely to be clinically relevant. The results give support for mammography as a safe procedure from the point of view of CTC and ctDNA shedding to the blood circulation. The results may have implications for the standardization of sampling procedures for circulating tumor markers.

The Significance of Regulatory MicroRNAs: Their Roles in Toxicodynamics of Mycotoxins and in the Protection Offered by Dietary Therapeutics Against Mycotoxin-Induced Toxicity.

Mycotoxins are contaminants commonly found in foods and represent a worldwide threat to human health and welfare. Efforts have been undertaken to reduce mycotoxins and their toxicity, including the introduction of good agricultural practices, appropriate food processing, specific biotransformation approaches, and pursue therapeutic agents to counteract mycotoxins. Efficient and predictive tools are required for investigations on mycotoxins and their toxicodynamics, and strategies for mycotoxin reduction. Gene expression and transcriptome analysis can unravel the mode of action, transformation and combined toxicity of mycotoxins, or mycotoxin's interactions with food components including dietary therapeutics, at the cellular level and from a molecular perspective. MicroRNAs (miRNAs) regulate endogenously and posttranscriptionally the expression of target genes and enzymes involved in physiological, disease and toxicological responses, and the metabolism of therapeutic agents. Accordingly, this review aimed to collect up-to-date information on (1) the regulatory role of miRNAs in mycotoxin-initiated toxicological processes and (2) the protective role of active ingredients from plants on mycotoxin-induced toxicity. Through such a review of published evidence, we found some common signal pathways involving miRNAs shared by these two types of biological events. This finding indicates the possibility of using miRNAs as biomarkers in assessing and controlling mycotoxins in food via cellular mechanisms.

Role of BMI and age in predicting pathologic vertebral fractures in newly diagnosed multiple myeloma patients: A retrospective cohort study.

Vertebral fractures affect approximately 30% of myeloma patients and lead to a poor impact on survival and life quality. In general, age and body mass index (BMI) are reported to have an important role in vertebral fractures. However, the triangle relationship among age, BMI, and vertebral fractures is still unclear in newly diagnosed multiple myeloma (NDMM) patients. This study recruited consecutive 394 patients with NDMM at Taipei Veterans General Hospital between January 1, 2005 and December 31, 2015. Risk factors for vertebral fractures in NDMM patients were collected and analyzed. The survival curves were demonstrated using Kaplan-Meier estimate. In total, 301 (76.4%) NDMM patients were enrolled in the cohort. In the median follow-up period of 18.0 months, the median survival duration in those with vertebral fractures ≥ 2 was shorter than those with vertebral fracture < 2 (59.3 vs 28.6 months; P = 0.017). In multivariate Poisson regression, BMI < 18.5 kg/m2 declared increased vertebral fractures compared with BMI ≥ 24.0 kg/m2 (adjusted RR, 2.79; 95% CI, 1.44-5.43). In multivariable logistic regression, BMI < 18.5 kg/m2 was an independent risk factor for vertebral fractures ≥ 2 compared with BMI ≥ 24.0 kg/m2 (adjusted OR, 6.05; 95% CI, 2.43-15.08). Among age stratifications, patients with both old age and low BMI were at a greater risk suffering from increased vertebral fractures, especially in patients > 75 years and BMI < 18.5 kg/m2 (adjusted RR, 12.22; 95% CI, 3.02-49.40). This is the first study that demonstrated that age had a significant impact on vertebral fractures in NDMM patients with low BMI. Elder patients with low BMI should consider to routinely receive spinal radiographic examinations and regular follow-up.

Integrated molecular pathway analysis informs a synergistic combination therapy targeting PTEN/PI3K and EGFR pathways for basal-like breast cancer.

BACKGROUND: The basal-like breast cancer (BLBC) subtype is characterized by positive staining for basal mammary epithelial cytokeratin markers, lack of hormone receptor and HER2 expression, and poor prognosis with currently no approved molecularly-targeted therapies. The oncogenic signaling pathways driving basal-like tumorigenesis are not fully elucidated. METHODS: One hundred sixteen unselected breast tumors were subjected to integrated analysis of phosphoinositide 3-kinase (PI3K) pathway related molecular aberrations by immunohistochemistry, mutation analysis, and gene expression profiling. Incidence and relationships between molecular biomarkers were characterized. Findings for select biomarkers were validated in an independent series. Synergistic cell killing in vitro and in vivo tumor therapy was investigated in breast cancer cell lines and mouse xenograft models, respectively. RESULTS: Sixty-four % of cases had an oncogenic alteration to PIK3CA, PTEN, or INPP4B; when including upstream kinases HER2 and EGFR, 75 % of cases had one or more aberration including 97 % of estrogen receptor (ER)-negative tumors. PTEN-loss was significantly associated to stathmin and EGFR overexpression, positivity for the BLBC markers cytokeratin 5/14, and the BLBC molecular subtype by gene expression profiling, informing a potential therapeutic combination targeting these pathways in BLBC. Combination treatment of BLBC cell lines with the EGFR-inhibitor gefitinib plus the PI3K pathway inhibitor LY294002 was synergistic, and correspondingly, in an in vivo BLBC xenograft mouse model, gefitinib plus PI3K-inhibitor PWT-458 was more effective than either monotherapy and caused tumor regression. CONCLUSIONS: Our study emphasizes the importance of PI3K/PTEN pathway activity in ER-negative and basal-like breast cancer and supports the future clinical evaluation of combining EGFR and PI3K pathway inhibitors for the treatment of BLBC.

Contralateral breast cancer can represent a metastatic spread of the first primary tumor: determination of clonal relationship between contralateral breast cancers using next-generation whole genome sequencing.

INTRODUCTION: By convention, a contralateral breast cancer (CBC) is treated as a new primary tumor, independent of the first cancer (BC1). Although there have been indications that the second tumor (BC2) sometimes may represent a metastatic spread of BC1, this has never been conclusively shown. We sought to apply next-generation sequencing to determine a "genetic barcode" for each tumor and reveal the clonal relationship of CBCs. METHODS: Ten CBC patients with detailed clinical information and available fresh frozen tumor tissue were studied. Using low-coverage whole genome DNA-sequencing data for each tumor, chromosomal rearrangements were enumerated and copy number profiles were generated. Comparisons between tumors provided an estimate of clonal relatedness for tumor pairs within individual patients. RESULTS: Between 15-256 rearrangements were detected in each tumor (median 87). For one patient, 76 % (68 out of 90) of the rearrangements were shared between BC1 and BC2, highly consistent with what has been seen for true primary-metastasis pairs (>50 %) and thus confirming a common clonal origin of the two tumors. For most of the remaining cases, BC1 and BC2 had similarly low overlap as unmatched randomized pairs of tumors from different individuals, suggesting the CBC to represent a new independent primary tumor. CONCLUSION: Using rearrangement fingerprinting, we show for the first time with certainty that a contralateral BC2 can represent a metastatic spread of BC1. Given the poor prognosis of a generalized disease compared to a new primary tumor, these women need to be identified at diagnosis of CBC for appropriate determination of treatment. Our approach generates a promising new method to assess clonal relationship between tumors. Additional studies are required to confirm the frequency of CBCs representing metastatic events.

LVPocket: integrated 3D global-local information to protein binding pockets prediction with transfer learning of protein structure classification.

BACKGROUND: Previous deep learning methods for predicting protein binding pockets mainly employed 3D convolution, yet an abundance of convolution operations may lead the model to excessively prioritize local information, thus overlooking global information. Moreover, it is essential for us to account for the influence of diverse protein folding structural classes. Because proteins classified differently structurally exhibit varying biological functions, whereas those within the same structural class share similar functional attributes. RESULTS: We proposed LVPocket, a novel method that synergistically captures both local and global information of protein structure through the integration of Transformer encoders, which help the model achieve better performance in binding pockets prediction. And then we tailored prediction models for data of four distinct structural classes of proteins using the transfer learning. The four fine-tuned models were trained on the baseline LVPocket model which was trained on the sc-PDB dataset. LVPocket exhibits superior performance on three independent datasets compared to current state-of-the-art methods. Additionally, the fine-tuned model outperforms the baseline model in terms of performance. SCIENTIFIC CONTRIBUTION: We present a novel model structure for predicting protein binding pockets that provides a solution for relying on extensive convolutional computation while neglecting global information about protein structures. Furthermore, we tackle the impact of different protein folding structures on binding pocket prediction tasks through the application of transfer learning methods.

Digital PCR quantification of ultrahigh ERBB2 copy number identifies poor breast cancer survival after trastuzumab.

HER2/ERBB2 evaluation is necessary for treatment decision-making in breast cancer (BC), however current methods have limitations and considerable variability exists. DNA copy number (CN) evaluation by droplet digital PCR (ddPCR) has complementary advantages for HER2/ERBB2 diagnostics. In this study, we developed a single-reaction multiplex ddPCR assay for determination of ERBB2 CN in reference to two control regions, CEP17 and a copy-number-stable region of chr. 2p13.1, validated CN estimations to clinical in situ hybridization (ISH) HER2 status, and investigated the association of ERBB2 CN with clinical outcomes. 909 primary BC tissues were evaluated and the area under the curve for concordance to HER2 status was 0.93 and 0.96 for ERBB2 CN using either CEP17 or 2p13.1 as reference, respectively. The accuracy of ddPCR ERBB2 CN was 93.7% and 94.1% in the training and validation groups, respectively. Positive and negative predictive value for the classic HER2 amplification and non-amplification groups was 97.2% and 94.8%, respectively. An identified biological "ultrahigh" ERBB2 ddPCR CN group had significantly worse survival within patients treated with adjuvant trastuzumab for both recurrence-free survival (hazard ratio, HR: 3.3; 95% CI 1.1-9.6; p = 0.031, multivariable Cox regression) and overall survival (HR: 3.6; 95% CI 1.1-12.6; p = 0.041). For validation using RNA-seq data as a surrogate, in a population-based SCAN-B cohort (NCT02306096) of 682 consecutive patients receiving adjuvant trastuzumab, the ultrahigh-ERBB2 mRNA group had significantly worse survival. Multiplex ddPCR is useful for ERBB2 CN estimation and ultrahigh ERBB2 may be a predictive factor for decreased long-term survival after trastuzumab treatment.

Rational design of stable Cu and AuCu nanoparticles for investigations of size-enhanced SERS applications.

BACKGROUND: While significant progress has been made to clarify the effects of Au and Ag nanoparticle size on SERS enhancement, research on the size effects of copper nanoparticles and copper-related nanoalloys on SERS enhancement remain scarce. Nanoscale copper (Cu) is important because of its unique sensing and catalytic properties; however, research on its size and compositional effects remains a significant challenge because of the intricate fabrication process and difficulty in preventing oxidation. RESULTS: Our study elucidated the size-dependent, surface-enhanced Raman scattering (SERS) of Cu NPs, particularly the sensing capabilities of both electromagnetic (EM) SERS at 1.5 × 103 and chemical enhancement (CE) SERS at 3.6 × 104 of approximately 58 nm Cu NPs. Additionally, a solution aging examination revealed preservation of the metal-related core structure, surface plasmon resonance, and SERS features of the PSMA/ONPG-coated Cu NPs for up to 7 days. With the introduction of galvanic replacement reactions and laser ablation syntheses, the incorporation of Au atoms enabled the fabrication of 7-75 nm AuxCuy nanoparticles by using the remaining Cu core after aging in water, which offered precise control over the Cu/Au ratio from 5/95 to 29/71. SERS measurements of the large AuxCuy nanoparticles amplified up to 1.4 × 104 of the EM-mediated vibrational signals from the adsorbed molecules. The strong Au-S chemical bonds of the Au-rich AuxCuy nanocrystals increased the CE SERS to 5.5 × 104, whereas the Au3Cu1 crystals at the AuxCuy interface decreased the CE SERS but improved the electron transfer for catalysis via SERS detection. SIGNIFICANCE: Our research provides further insight into the structural and size effects of Cu and AuCu alloys used as SERS enhancers and offers avenues for designing cutting-edge SERS catalytic sensors tailored to Cu-related catalytic reactive structures. For the first time, we also manipulated the Cu atomic structure and surface composition to understand the significance of surface effects on SERS substrates of the Cu series from a nanoscale analytical perspective.

Atomic Dispersed Co on NC@Cu Core-Shells for Solar Seawater Splitting.

With freshwater resources becoming increasingly scarce, the photocatalytic seawater splitting for hydrogen production has garnered widespread attention. In this study, a novel photocatalyst consisting of a Cu core coated is introduced with N-doped C and decorated with single Co atoms (Co-NC@Cu) for solar to hydrogen production from seawater. This catalyst, without using noble metals or sacrificial agents, demonstrates superior hydrogen production effficiency of 9080 µmolg-1h-1, i.e., 4.78% solar-to-hydrogen conversion efficiency, and exceptional long-term stability, operating over 340 h continuously. The superior performance is attributed to several key factors. First, the focus-light induced photothermal effect enhances redox reaction capabilities, while the salt-ions enabled charge polarization around catalyst surfaces extends charge carrier lifetime. Furthermore, the Co─NC@Cu exhibits excellent broad light absorption, promoting photoexcited charge production. Theoretical calculations reveal that Co─NC acts as the active site, showing low energy barriers for reduction reactions. Additionally, the formation of a strong surface electric field from the localized surface plasmon resonance (LSPR) of Cu nanoparticles further reduces energy barriers for redox reactions, improving seawater splitting activity. This work provides valuable insights into intergrating the reaction environment, broad solar absorption, LSPR, and active single atoms into a core-shell photocatalyst design for efficient and robust solar-driven seawater splitting.

DSGN++: Exploiting Visual-Spatial Relation for Stereo-Based 3D Detectors.

Camera-based 3D object detectors are welcome due to their wider deployment and lower price than LiDAR sensors. We first revisit the prior stereo detector DSGN for its stereo volume construction ways for representing both 3D geometry and semantics. We polish the stereo modeling and propose the advanced version, DSGN++, aiming to enhance effective information flow throughout the 2D-to-3D pipeline in three main aspects. First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features. Second, for grasping differently spaced features, we present a novel stereo volume - Dual-view Stereo Volume (DSV) that integrates front-view and top-view features and reconstructs sub-voxel depth in the camera frustum. Third, as the foreground region becomes less dominant in 3D space, we propose a multi-modal data editing strategy - Stereo-LiDAR Copy-Paste, which ensures cross-modal alignment and improves data efficiency. Without bells and whistles, extensive experiments in various modality setups on the popular KITTI benchmark show that our method consistently outperforms other camera-based 3D detectors for all categories. Code is available at https://github.com/chenyilun95/DSGN2.