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Plants (Basel, Switzerland) Jun 2024Pepper is a high-economic-value agricultural crop that faces diverse disease challenges such as blight and anthracnose. These diseases not only reduce the yield of...
Pepper is a high-economic-value agricultural crop that faces diverse disease challenges such as blight and anthracnose. These diseases not only reduce the yield of pepper but, in severe cases, can also cause significant economic losses and threaten food security. The timely and accurate identification of pepper diseases is crucial. Image recognition technology plays a key role in this aspect by automating and efficiently identifying pepper diseases, helping agricultural workers to adopt and implement effective control strategies, alleviating the impact of diseases, and being of great importance for improving agricultural production efficiency and promoting sustainable agricultural development. In response to issues such as edge-blurring and the extraction of minute features in pepper disease image recognition, as well as the difficulty in determining the optimal learning rate during the training process of traditional pepper disease identification networks, a new pepper disease recognition model based on the TPSAO-AMWNet is proposed. First, an Adaptive Residual Pyramid Convolution (ARPC) structure combined with a Squeeze-and-Excitation (SE) module is proposed to solve the problem of edge-blurring by utilizing adaptivity and channel attention; secondly, to address the issue of micro-feature extraction, Minor Triplet Disease Focus Attention (MTDFA) is proposed to enhance the capture of local details of pepper leaf disease features while maintaining attention to global features, reducing interference from irrelevant regions; then, a mixed loss function combining Weighted Focal Loss and L2 regularization (WfrLoss) is introduced to refine the learning strategy during dataset processing, enhancing the model's performance and generalization capabilities while preventing overfitting. Subsequently, to tackle the challenge of determining the optimal learning rate, the tent particle snow ablation optimizer (TPSAO) is developed to accurately identify the most effective learning rate. The TPSAO-AMWNet model, trained on our custom datasets, is evaluated against other existing methods. The model attains an average accuracy of 93.52% and an F1 score of 93.15%, demonstrating robust effectiveness and practicality in classifying pepper diseases. These results also offer valuable insights for disease detection in various other crops.
PubMed: 38891389
DOI: 10.3390/plants13111581 -
Blood Cancer Journal Jun 2024Current therapies for high-grade TP53-mutated myeloid neoplasms (≥10% blasts) do not offer a meaningful survival benefit except allogeneic stem cell transplantation in...
Current therapies for high-grade TP53-mutated myeloid neoplasms (≥10% blasts) do not offer a meaningful survival benefit except allogeneic stem cell transplantation in the minority who achieve a complete response to first line therapy (CR1). To identify reliable pre-therapy predictors of complete response to first-line therapy (CR1) and outcomes, we assembled a cohort of 242 individuals with TP53-mutated myeloid neoplasms and ≥10% blasts with well-annotated clinical, molecular and pathology data. Key outcomes examined were CR1 & 24-month survival (OS24). In this elderly cohort (median age 68.2 years) with 74.0% receiving frontline non-intensive regimens (hypomethylating agents +/- venetoclax), the overall cohort CR1 rate was 25.6% (50/195). We additionally identified several pre-therapy factors predictive of inferior CR1 including male gender (P = 0.026), ≥2 autosomal monosomies (P < 0.001), -17/17p (P = 0.011), multi-hit TP53 allelic state (P < 0.001) and CUX1 co-alterations (P = 0.010). In univariable analysis of the entire cohort, inferior OS24 was predicated by ≥2 monosomies (P = 0.004), TP53 VAF > 25% (P = 0.002), TP53 splice junction mutations (P = 0.007) and antecedent treated myeloid neoplasm (P = 0.001). In addition, mutations/deletions in CUX1, U2AF1, EZH2, TET2, CBL, or KRAS ('EPI6' signature) predicted inferior OS24 (HR = 2.0 [1.5-2.8]; P < 0.0001). In a subgroup analysis of HMA +/-Ven treated individuals (N = 144), TP53 VAF and monosomies did not impact OS24. A risk score for HMA +/-Ven treated individuals incorporating three pre-therapy predictors including TP53 splice junction mutations, EPI6 and antecedent treated myeloid neoplasm stratified 3 prognostic distinct groups: intermediate, intermediate-poor, and poor with significantly different median (12.8, 6.0, 4.3 months) and 24-month (20.9%, 5.7%, 0.5%) survival (P < 0.0001). For the first time, in a seemingly monolithic high-risk cohort, our data identifies several baseline factors that predict response and 24-month survival.
Topics: Humans; Male; Female; Aged; Tumor Suppressor Protein p53; Mutation; Middle Aged; Aged, 80 and over; Adult; Prognosis; Treatment Outcome
PubMed: 38890297
DOI: 10.1038/s41408-024-01077-9 -
Cell Death & Disease Jun 2024Radiation therapy (RT) remains a common treatment for cancer patients worldwide, despite the development of targeted biological compounds and immunotherapeutic drugs....
Radiation therapy (RT) remains a common treatment for cancer patients worldwide, despite the development of targeted biological compounds and immunotherapeutic drugs. The challenge in RT lies in delivering a lethal dose to the cancerous site while sparing the surrounding healthy tissues. Low linear energy transfer (low-LET) and high linear energy transfer (high-LET) radiations have distinct effects on cells. High-LET radiation, such as alpha particles, induces clustered DNA double-strand breaks (DSBs), potentially inducing cell death more effectively. However, due to limited range, alpha-particle therapies have been restricted. In human cancer, mutations in TP53 (encoding for the p53 tumor suppressor) are the most common genetic alteration. It was previously reported that cells carrying wild-type (WT) p53 exhibit accelerated senescence and significant rates of apoptosis in response to RT, whereas cells harboring mutant p53 (mutp53) do not. This study investigated the combination of the alpha-emitting atoms RT based on internal Radium-224 (Ra) sources and systemic APR-246 (a p53 reactivating compound) to treat tumors with mutant p53. Cellular models of colorectal cancer (CRC) or pancreatic ductal adenocarcinoma (PDAC) harboring mutant p53, were exposed to alpha particles, and tumor xenografts with mutant p53 were treated using Ra source and APR-246. Effects on cell survival and tumor growth, were assessed. The spread of alpha emitters in tumors was also evaluated as well as the spatial distribution of apoptosis within the treated tumors. We show that mutant p53 cancer cells exhibit radio-sensitivity to alpha particles in vitro and to alpha-particles-based RT in vivo. APR-246 treatment enhanced sensitivity to alpha radiation, leading to reduced tumor growth and increased rates of tumor eradication. Combining alpha-particles-based RT with p53 restoration via APR-246 triggered cell death, resulting in improved therapeutic outcomes. Further preclinical and clinical studies are needed to provide a promising approach for improving treatment outcomes in patients with mutant p53 tumors.
Topics: Alpha Particles; Humans; Tumor Suppressor Protein p53; Animals; Mice; Radiation-Sensitizing Agents; Mutation; Quinuclidines; Cell Line, Tumor; Mice, Nude; Xenograft Model Antitumor Assays; Apoptosis; Neoplasms
PubMed: 38890278
DOI: 10.1038/s41419-024-06830-3 -
Immunity Jun 2024Expression of the transcriptional regulator ZFP318 is induced in germinal center (GC)-exiting memory B cell precursors and memory B cells (MBCs). Using a conditional...
Expression of the transcriptional regulator ZFP318 is induced in germinal center (GC)-exiting memory B cell precursors and memory B cells (MBCs). Using a conditional ZFP318 fluorescence reporter that also enables ablation of ZFP318-expressing cells, we found that ZFP318-expressing MBCs were highly enriched with GC-derived cells. Although ZFP318-expressing MBCs constituted only a minority of the antigen-specific MBC compartment, their ablation severely impaired recall responses. Deletion of Zfp318 did not alter the magnitude of primary responses but markedly reduced MBC participation in recall. CD40 ligation promoted Zfp318 expression, whereas B cell receptor (BCR) signaling was inhibitory. Enforced ZFP318 expression enhanced recall performance of MBCs that otherwise responded poorly. ZFP318-deficient MBCs expressed less mitochondrial genes, had structurally compromised mitochondria, and were susceptible to reactivation-induced cell death. The abundance of ZFP318-expressing MBCs, instead of the number of antigen-specific MBCs, correlated with the potency of prime-boost vaccination. Therefore, ZFP318 controls the MBC recallability and represents a quality checkpoint of humoral immune memory.
PubMed: 38889716
DOI: 10.1016/j.immuni.2024.05.022 -
American Journal of Audiology Jun 2024The objective of this study was to determine the normative vestibulo-ocular reflex gain output values of the computerized rotational head impulse test (crHIT) with...
PURPOSE
The objective of this study was to determine the normative vestibulo-ocular reflex gain output values of the computerized rotational head impulse test (crHIT) with stationary visual targets (earth bound) in healthy participants in each decade age band of life: 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, and 70+ years.
METHOD
Seventy-seven community-dwelling participants (10-85 years of age) with normal lateral semicircular canal (SCC) functioning and no symptoms or history of vestibular dysfunction were recruited through convenience sampling and assessed with the crHIT using stationary targets. These participants were assessed using two standard protocols in a randomized order.
RESULTS
Results from 77 participants ( = 46 years; 43 women, 34 men) were analyzed. Pearson's correlation coefficient and simple linear regression indicated a statistically significant relationship between crHIT gain output and age ( > .05) for right gain, 1030°/s, and left gain, 1005°/s. Although a statistically significant relationship was found, the slope was minor, demonstrating that the clinical effect of age on crHIT gain output was insignificant. Furthermore, no statistically significant relationship exists between crHIT gain output and gender ( > .05). Age-dependent normative data were calculated using the 2.5th and 97.5th confidence interval (CI) percentile method. The responses of angular vestibulo-ocular reflex (aVOR) gain values for crHIT are expected to occur within the range for lower limit reference interval (RI) of 0.85-0.9 and upper limit RI of 1.11-1.18 for 1030°/s and lower limit RI of 0.86-0.92 and upper limit RI of 1.13-1.16 for 1005°/s. It can be expected that 90% CI of the population with normal lateral SCC functioning will have aVOR gain values that fall within this range.
CONCLUSION
Despite a statistically significant relationship that exists with aVOR gain output and age, the changes are minor, declining by 0.0088 units per 10 years, justifying the same normative data for all decade age bands.
PubMed: 38889375
DOI: 10.1044/2024_AJA-22-00190 -
Bioinformatics (Oxford, England) Jun 2024Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs...
MOTIVATION
Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs (ACs), where minor chemical alterations can lead to significant changes in bioactivity. In response, several DGL models have been developed to enhance ligand bioactivity prediction in the presence of ACs. Yet, there remains a largely unexplored opportunity within ACs for optimizing ligand bioactivity, making it an area ripe for further investigation.
RESULTS
We present a novel approach to simultaneously predict and optimize ligand bioactivities through DGL and ACs (OLB-AC). OLB-AC possesses the capability to optimize ligand molecules located near ACs, providing a direct reference for optimizing ligand bioactivities with the matching of original ligands. To accomplish this, a novel attentive graph reconstruction neural network and ligand optimization scheme are proposed. Attentive graph reconstruction neural network reconstructs original ligands and optimizes them through adversarial representations derived from their bioactivity prediction process. Experimental results on nine drug targets reveal that out of the 667 molecules generated through OLB-AC optimization on datasets comprising 974 low-activity, noninhibitor, or highly toxic ligands, 49 are recognized as known highly active, inhibitor, or nontoxic ligands beyond the datasets' scope. The 27 out of 49 matched molecular pairs generated by OLB-AC reveal novel transformations not present in their training sets. The adversarial representations employed for ligand optimization originate from the gradients of bioactivity predictions. Therefore, we also assess OLB-AC's prediction accuracy across 33 different bioactivity datasets. Results show that OLB-AC achieves the best Pearson correlation coefficient (r2) on 27/33 datasets, with an average improvement of 7.2%-22.9% against the state-of-the-art bioactivity prediction methods.
AVAILABILITY AND IMPLEMENTATION
The code and dataset developed in this work are available at github.com/Yueming-Yin/OLB-AC.
Topics: Ligands; Deep Learning; Neural Networks, Computer; Drug Discovery
PubMed: 38889277
DOI: 10.1093/bioinformatics/btae365 -
JAMA Network Open Jun 2024Large language models (LLMs) recently developed an unprecedented ability to answer questions. Studies of LLMs from other fields may not generalize to medical oncology, a...
IMPORTANCE
Large language models (LLMs) recently developed an unprecedented ability to answer questions. Studies of LLMs from other fields may not generalize to medical oncology, a high-stakes clinical setting requiring rapid integration of new information.
OBJECTIVE
To evaluate the accuracy and safety of LLM answers on medical oncology examination questions.
DESIGN, SETTING, AND PARTICIPANTS
This cross-sectional study was conducted between May 28 and October 11, 2023. The American Society of Clinical Oncology (ASCO) Oncology Self-Assessment Series on ASCO Connection, the European Society of Medical Oncology (ESMO) Examination Trial questions, and an original set of board-style medical oncology multiple-choice questions were presented to 8 LLMs.
MAIN OUTCOMES AND MEASURES
The primary outcome was the percentage of correct answers. Medical oncologists evaluated the explanations provided by the best LLM for accuracy, classified the types of errors, and estimated the likelihood and extent of potential clinical harm.
RESULTS
Proprietary LLM 2 correctly answered 125 of 147 questions (85.0%; 95% CI, 78.2%-90.4%; P < .001 vs random answering). Proprietary LLM 2 outperformed an earlier version, proprietary LLM 1, which correctly answered 89 of 147 questions (60.5%; 95% CI, 52.2%-68.5%; P < .001), and the best open-source LLM, Mixtral-8x7B-v0.1, which correctly answered 87 of 147 questions (59.2%; 95% CI, 50.0%-66.4%; P < .001). The explanations provided by proprietary LLM 2 contained no or minor errors for 138 of 147 questions (93.9%; 95% CI, 88.7%-97.2%). Incorrect responses were most commonly associated with errors in information retrieval, particularly with recent publications, followed by erroneous reasoning and reading comprehension. If acted upon in clinical practice, 18 of 22 incorrect answers (81.8%; 95% CI, 59.7%-94.8%) would have a medium or high likelihood of moderate to severe harm.
CONCLUSIONS AND RELEVANCE
In this cross-sectional study of the performance of LLMs on medical oncology examination questions, the best LLM answered questions with remarkable performance, although errors raised safety concerns. These results demonstrated an opportunity to develop and evaluate LLMs to improve health care clinician experiences and patient care, considering the potential impact on capabilities and safety.
Topics: Humans; Cross-Sectional Studies; Medical Oncology; Educational Measurement; Language
PubMed: 38888919
DOI: 10.1001/jamanetworkopen.2024.17641 -
ACS Applied Materials & Interfaces Jun 2024Inflammatory bowel disease (IBD) is a chronic and recurrent inflammatory disease that affects the gastrointestinal tract. The major hurdles impeding IBD treatment are...
Inflammatory bowel disease (IBD) is a chronic and recurrent inflammatory disease that affects the gastrointestinal tract. The major hurdles impeding IBD treatment are the low targeting efficiency and short retention time of drugs in IBD sites. Nanoparticles with specific shapes have demonstrated the ability to improve mucus retention and cellular uptake. Herein, mesoporous silica nanoparticles (MSNs) with various morphologies were used to deliver budesonide (BUD) for the treatment of IBD. The therapeutic efficacy is strongly dependent on their shapes. The system comprises different shapes of MSNs as carriers for budesonide (BUD), along with Eudragit S100 as the enteric release shell. The encapsulation of Eudragit S100 not only improved the stability of MSNs-BUD in the gastrointestinal tract but also conferred pH-responsive drug release properties. Then, MSNs efficiently deliver BUD to the colon site, and the special shape of MSNs plays a critical role in enhancing their permeability and retention in the mucus layer. Among them, dendritic MSNs (MSND) effectively reduced myeloperoxidase (MPO) activity and levels of inflammatory cytokines in the colon due to long retention time and rapid release in IBD sites, thereby enhancing the therapeutic efficacy against colitis. Given the special shapes of MSNs and pH-responsivity of Eudragit S100, BUD loaded in the voids of MSND (E@MSNs-BUD) could penetrate the mucous layer and be accurately delivered to the colon with minor side effects. This system is expected to complement current treatment strategies for the IBD.
PubMed: 38888094
DOI: 10.1021/acsami.4c05214 -
RSC Advances Jun 2024In recent years, there has been growing interest in the composites of multi-responsive microgels and silver nanoparticles. This innovative hybrid system harnesses the... (Review)
Review
In recent years, there has been growing interest in the composites of multi-responsive microgels and silver nanoparticles. This innovative hybrid system harnesses the responsive qualities of microgels while capitalizing on the optical and electronic attributes of silver nanoparticles. This combined system demonstrates a rapid response to minor changes in pH, temperature, ionic strength of the medium, and the concentration of specific biological substances. This review article presents an overview of the recent advancements in the synthesis, classification, characterization methods, and properties of microgels loaded with silver nanoparticles. Furthermore, it explores the diverse applications of these responsive microgels containing silver nanoparticles in catalysis, the biomedical field, nanotechnology, and the mitigation of harmful environmental pollutants.
PubMed: 38887640
DOI: 10.1039/d4ra02467b -
Genome Medicine Jun 2024Genome-wide functional screening using the CRISPR-Cas9 system is a powerful tool to uncover tumor-specific and common genetic dependencies across cancer cell lines....
BACKGROUND
Genome-wide functional screening using the CRISPR-Cas9 system is a powerful tool to uncover tumor-specific and common genetic dependencies across cancer cell lines. Current CRISPR-Cas9 knockout libraries, however, primarily target protein-coding genes. This limits functional genomics-based investigations of miRNA function.
METHODS
We designed a novel CRISPR-Cas9 knockout library (lentiG-miR) of 8107 distinct sgRNAs targeting a total of 1769 human miRNAs and benchmarked its single guide RNA (sgRNA) composition, predicted on- and off-target activity, and screening performance against previous libraries. Using a total of 45 human cancer cell lines, representing 16 different tumor entities, we performed negative selection screens to identify miRNA fitness genes. Fitness miRNAs in each cell line were scored using a combination of supervised and unsupervised essentiality classifiers. Common essential miRNAs across distinct cancer cell lines were determined using the 90th percentile method. For subsequent validation, we performed knockout experiments for selected common essential miRNAs in distinct cancer cell lines and gene expression profiling.
RESULTS
We found significantly lower off-target activity for protein-coding genes and a higher miRNA gene coverage for lentiG-miR as compared to previously described miRNA-targeting libraries, while preserving high on-target activity. A minor fraction of miRNAs displayed robust depletion of targeting sgRNAs, and we observed a high level of consistency between redundant sgRNAs targeting the same miRNA gene. Across 45 human cancer cell lines, only 217 (12%) of all targeted human miRNAs scored as a fitness gene in at least one model, and fitness effects for most miRNAs were confined to small subsets of cell lines. In contrast, we identified 49 common essential miRNAs with a homogenous fitness profile across the vast majority of all cell lines. Transcriptional profiling verified highly consistent gene expression changes in response to knockout of individual common essential miRNAs across a diverse set of cancer cell lines.
CONCLUSIONS
Our study presents a miRNA-targeting CRISPR-Cas9 knockout library with high gene coverage and optimized on- and off-target activities. Taking advantage of the lentiG-miR library, we define a catalogue of miRNA fitness genes in human cancer cell lines, providing the foundation for further investigation of miRNAs in human cancer.
Topics: Humans; CRISPR-Cas Systems; MicroRNAs; Cell Line, Tumor; Neoplasms; Gene Knockout Techniques; RNA, Guide, CRISPR-Cas Systems; Gene Expression Regulation, Neoplastic; Gene Expression Profiling; Genes, Essential
PubMed: 38886809
DOI: 10.1186/s13073-024-01341-4