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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 -
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 -
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 -
Journal For Immunotherapy of Cancer Jun 2024Cancer/testis antigens (CTAs) are widely expressed in melanoma and lung cancer, emerging as promising targets for vaccination strategies and T-cell-based therapies in...
Cancer/testis antigens (CTAs) are widely expressed in melanoma and lung cancer, emerging as promising targets for vaccination strategies and T-cell-based therapies in these malignancies. Despite recognizing the essential impact of intratumoral heterogeneity on clinical responses to immunotherapy, our understanding of intratumoral heterogeneity in CTA expression has remained limited. We employed single-cell mRNA sequencing to delineate the CTA expression profiles of cancer cells in clinically derived melanoma and lung cancer samples. Our findings reveal a high degree of intratumoral transcriptional heterogeneity in CTA expression. In melanoma, every cell expressed at least one CTA. However, most individual CTAs, including the widely used therapeutic targets NY-ESO-1 and MAGE, were confined to subpopulations of cells and were uncoordinated in their expression, resulting in mosaics of cancer cells with diverse CTA profiles. Coordinated expression was observed, however, mainly among highly structurally and evolutionarily related CTA genes. Importantly, a minor subset of CTAs, including PRAME and several members of the GAGE and MAGE-A families, were homogenously expressed in melanomas, highlighting their potential as therapeutic targets. Extensive heterogeneity in CTA expression was also observed in lung cancer. However, the frequency of CTA-positive cancer cells was notably lower and homogenously expressed CTAs were only identified in one of five tumors in this cancer type. Our findings underscore the need for careful CTA target selection in immunotherapy development and clinical testing and offer a rational framework for identifying the most promising candidates.
Topics: Humans; Melanoma; Lung Neoplasms; Antigens, Neoplasm; Single-Cell Analysis; Male; Gene Expression Regulation, Neoplastic
PubMed: 38886115
DOI: 10.1136/jitc-2023-008759 -
CMAJ : Canadian Medical Association... Jun 2024The response of Canada's research community to the COVID-19 pandemic provides a unique opportunity to examine the country's clinical health research ecosystem. We sought...
BACKGROUND
The response of Canada's research community to the COVID-19 pandemic provides a unique opportunity to examine the country's clinical health research ecosystem. We sought to describe patterns of enrolment across Canadian Institutes of Health Research (CIHR)-funded studies on COVID-19.
METHODS
We identified COVID-19 studies funded by the CIHR and that enrolled participants from Canadian acute care hospitals between January 2020 and April 2023. We collected information on study-and site-level variables from study leads, site investigators, and public domain sources. We described and evaluated factors associated with cumulative enrolment.
RESULTS
We obtained information for 23 out of 26 (88%) eligible CIHR-funded studies (16 randomized controlled trials [RCTs] and 7 cohort studies). The 23 studies were managed by 12 Canadian and 3 international coordinating centres. Of 419 Canadian hospitals, 97 (23%) enrolled a total of 28 973 participants - 3876 in RCTs across 78 hospitals (median cumulative enrolment per hospital 30, interquartile range [IQR] 10-61), and 25 097 in cohort studies across 62 hospitals (median cumulative enrolment per hospital 158, IQR 6-348). Of 78 hospitals recruiting participants in RCTs, 13 (17%) enrolled 50% of all RCT participants, whereas 6 of 62 hospitals (9.7%) recruited 54% of participants in cohort studies.
INTERPRETATION
A minority of Canadian hospitals enrolled the majority of participants in CIHR-funded studies on COVID-19. This analysis sheds light on the Canadian health research ecosystem and provides information for multiple key partners to consider ways to realize the full research potential of Canada's health systems.
Topics: Humans; Canada; COVID-19; Biomedical Research; SARS-CoV-2; Pandemics; Randomized Controlled Trials as Topic
PubMed: 38885975
DOI: 10.1503/cmaj.230760 -
Frontiers in Neurology 2024Studies of hyperbaric oxygen therapy (HBOT) treatment of mild traumatic brain injury persistent postconcussion syndrome in military and civilian subjects have shown...
BACKGROUND
Studies of hyperbaric oxygen therapy (HBOT) treatment of mild traumatic brain injury persistent postconcussion syndrome in military and civilian subjects have shown simultaneous improvement in posttraumatic stress disorder (PTSD) or PTSD symptoms, suggesting that HBOT may be an effective treatment for PTSD. This is a systematic review and dosage analysis of HBOT treatment of patients with PTSD symptoms.
METHODS
PubMed, CINAHL, and the Cochrane Systematic Review Database were searched from September 18 to November 23, 2023, for all adult clinical studies published in English on HBOT and PTSD. Randomized trials and studies with symptomatic outcomes were selected for final analysis and analyzed according to the dose of oxygen and barometric pressure on symptom outcomes. Outcome assessment was for statistically significant change and Reliable Change or Clinically Significant Change according to the National Center for PTSD Guidelines. Methodologic quality and bias were determined with the PEDro Scale.
RESULTS
Eight studies were included, all with < 75 subjects/study, total 393 subjects: seven randomized trials and one imaging case-controlled study. Six studies were on military subjects, one on civilian and military subjects, and one on civilians. Subjects were 3-450 months post trauma. Statistically significant symptomatic improvements, as well as Reliable Change or Clinically Significant changes, were achieved for patients treated with 40-60 HBOTS over a wide range of pressures from 1.3 to 2.0 ATA. There was a linear dose-response relationship for increased symptomatic improvement with increasing cumulative oxygen dose from 1002 to 11,400 atmosphere-minutes of oxygen. The greater symptomatic response was accompanied by a greater and severe reversible exacerbation of emotional symptoms at the highest oxygen doses in 30-39% of subjects. Other side effects were transient and minor. In three studies the symptomatic improvements were associated with functional and anatomic brain imaging changes. All 7 randomized trials were found to be of good-highest quality by PEDro scale scoring.
DISCUSSION
In multiple randomized and randomized controlled clinical trials HBOT demonstrated statistically significant symptomatic improvements, Reliable Changes, or Clinically Significant Changes in patients with PTSD symptoms or PTSD over a wide range of pressure and oxygen doses. The highest doses were associated with a severe reversible exacerbation of emotional symptoms in 30-39% of subjects. Symptomatic improvements were supported by correlative functional and microstructural imaging changes in PTSD-affected brain regions. The imaging findings and hyperbaric oxygen therapy effects indicate that PTSD can no longer be considered strictly a psychiatric disease.
PubMed: 38882688
DOI: 10.3389/fneur.2024.1360311