From identification to forecasting: the potential of image recognition and artificial intelligence for aphid pest monitoring.

Insect monitoring has gained global public attention in recent years in the context of insect decline and biodiversity loss. Monitoring methods that can collect samples over a long period of time and independently of human influences are of particular importance. While these passive collection methods, e.g. suction traps, provide standardized and comparable data sets, the time required to analyze the large number of samples and trapped specimens is high. Another challenge is the necessary high level of taxonomic expertise required for accurate specimen processing. These factors create a bottleneck in specimen processing. In this context, machine learning, image recognition and artificial intelligence have emerged as promising tools to address the shortcomings of manual identification and quantification in the analysis of such trap catches. Aphids are important agricultural pests that pose a significant risk to several important crops and cause high economic losses through feeding damage and transmission of plant viruses. It has been shown that long-term monitoring of migrating aphids using suction traps can be used to make, adjust and improve predictions of their abundance so that the risk of plant viruses spreading through aphids can be more accurately predicted. With the increasing demand for alternatives to conventional pesticide use in crop protection, the need for predictive models is growing, e.g. as a basis for resistance development and as a measure for resistance management. In this context, advancing climate change has a strong influence on the total abundance of migrating aphids as well as on the peak occurrences of aphids within a year. Using aphids as a model organism, we demonstrate the possibilities of systematic monitoring of insect pests and the potential of future technical developments in the subsequent automated identification of individuals through to the use of case data for intelligent forecasting models. Using aphids as an example, we show the potential for systematic monitoring of insect pests through technical developments in the automated identification of individuals from static images (i.e. advances in image recognition software). We discuss the potential applications with regard to the automatic processing of insect case data and the development of intelligent prediction models.

Landscape of Genomic Alterations and PD-L1 Expression in Early-Stage Non-Small-Cell Lung Cancer (NSCLC)-A Single Center, Retrospective Observational Study.

Precision oncology and immunotherapy have revolutionized the treatment of advanced non-small-cell lung cancer (NSCLC). Emerging studies show that targeted therapies are also beneficial for patients with driver alterations such as epidermal growth factor receptor (EGFR) mutations in early-stage NSCLC (stages I-IIIA). Furthermore, patients with elevated programmed death-ligand 1 (PD-L1) expression appear to respond favorably to adjuvant immunotherapy. To determine the frequency of genomic alterations and PD-L1 status in early-stage NSCLC, we retrospectively analyzed data from 2066 unselected, single-center patients with NSCLC diagnosed using next-generation sequencing and immunohistochemistry. Nine-hundred and sixty-two patients (46.9%) presented with early-stage NSCLC. Of these, 37.0% had genomic alterations for which targeted therapies have already been approved for advanced NSCLC. The frequencies of driver mutations in the early stages were equivalent to those in advanced stages, i.e., the rates of EGFR mutations in adenocarcinomas were 12.7% (72/567) and 12.0% (78/650) in early and advanced NSCLC, respectively (p = 0778). In addition, 46.3% of early-stage NSCLC cases were PD-L1-positive, with a tumor proportion score (TPS) of ≥1%. With comparable frequencies of driver mutations in early and advanced NSCLC and PD-L1 overexpression in nearly half of patients with early-stage NSCLC, a broad spectrum of biomarkers for adjuvant and neoadjuvant therapies is available, and several are currently being investigated in clinical trials.

Semi-automatic detection of honeybee brood hygiene-an example of artificial learning to facilitate ethological studies on social insects.

Machine-learning techniques are shifting the boundaries of feasibility in many fields of ethological research. Here, we describe an application of machine learning to the detection/measurement of hygienic behaviour, an important breeding trait in the honey bee (Apis mellifera). Hygienic worker bees are able to detect and destroy diseased brood, thereby reducing the reproduction of economically important pathogens and parasites such as the Varroa mite (Varroa destructor). Video observation of this behaviour on infested combs has many advantages over other methods of measurement, but analysing the recorded material is extremely time-consuming. We approached this problem by combining automatic tracking of bees in the video recordings, extracting relevant features, and training a multi-layer discriminator on positive and negative examples of the behaviour of interest. Including expert knowledge into the design of the features lead to an efficient model for identifying the uninteresting parts of the video which can be safely skipped. This algorithm was then used to semiautomatically identify individual worker bees involved in the behaviour. Application of the machine-learning method allowed to save 70% of the time required for manual analysis, and substantially increased the number of cell openings correctly identified. It thereby turns video-observation of individual cell opening events into an economically competitive method for selecting potentially resistant bees. This method presents an example of how machine learning can be used to boost ethological research, and how it can generate new knowledge by explaining the learned decision rule in form of meaningful parameters.

Efficacy of Immune Checkpoint Inhibitors Alone or in Combination With Chemotherapy in NSCLC Harboring ERBB2 Mutations.

INTRODUCTION: In contrast to other driver mutations, no targeted therapies have yet been approved in ERBB2-mutated NSCLC (HER2mu NSCLC). Nevertheless, several compounds have revealed promising early efficacy data, which need to be evaluated in the context of current standard approaches. Although data on the efficacy of immune checkpoint inhibitors (ICIs) in second or subsequent lines of treatment remain limited and conflicting, there are virtually no data on patient outcome under ICI/platinum-doublet combinations in the first-line setting. METHODS: We retrospectively evaluated outcomes of patients with HER2mu NSCLC treated with ICI alone or in combination with chemotherapy within the German National Network Genomic Medicine Lung Cancer consortium by means of overall response rate (ORR), progression-free survival (PFS), and overall survival (OS). RESULTS: ICI either in combination with chemotherapy or as monotherapy was applied as first-line treatment in 27 patients, whereas 34 received single-agent ICI in second or subsequent lines. Patient characteristics were in line with previously published data. In treatment-naive patients receiving ICI in combination with chemotherapy, the ORR, median PFS, and OS rate at 1 year were 52%, 6 months, and 88%, respectively. In second or subsequent lines, ICI monotherapy was associated with an ORR of 16%, a median PFS of 4 months, and a median OS of 10 months. CONCLUSIONS: ICIs are effective as monotherapy and in combination with platinum-doublet chemotherapy. Therefore, ICI-based treatments may be found as the current standard of care and benchmark for targeted therapies in HER2mu NSCLC.

Autoimmune disorders and paraneoplastic syndromes in thymoma.

Thymomas are counted among the rare tumour entities which are associated with autoimmune disorders (AIDs) and paraneoplastic syndromes (PNS) far more often than other malignancies. Through its complex immunological function in the context of the selection and maturation of T cells, the thymus is at the same time highly susceptible to disruptive factors caused by the development and growth of thymic tumours. These T cells, which are thought to develop to competent immune cells in the thymus, can instead adopt autoreactive behaviour due to the uncontrolled interplay of thymomas and become the trigger for AID or PNS affecting numerous organs and tissues within the human body. While myasthenia gravis is the most prevalent PNS in thymoma, numerous others have been described, be they related to neurological, cardiovascular, gastrointestinal, haematological, dermatological, endocrine or systemic disorders. This review article sheds light on the pathophysiology, epidemiology, specific clinical features and therapeutic options of the various forms as well as courses and outcomes of AID/PNS in association with thymomas. Whenever suitable and backed by the limited available evidence, the perspectives from both the thymoma and the affected organ/tissue will be highlighted. Specific issues addressed are the prognostic significance of thymectomy on myasthenia gravis and other thymoma-associated AID/PND and further the impact and safety of immunotherapies on AID and PND relating to thymomas.

Clinical Experience of Immunotherapy Treatment: Efficacy and Toxicity Analysis of the Compassionate Use Program of Nivolumab in Patients with Advanced Squamous Cell Non-Small Cell Lung Cancer.

BACKGROUND: Anti-PD1 monoclonal antibody nivolumab is an approved therapy option for the treatment of advanced squamous cell non-small cell lung cancer (SQ-NSCLC) patients. Data outside clinical trials about therapy efficacy and safety in later therapy line treatments have rarely been described until now. METHODS: We performed a retrospective data analysis of patients who were enrolled into the nivolu-mab Compassionate Use Program (CUP) in Germany. Sufficient clinical data of 40 patients were available for efficacy and safety analysis. RESULTS: Overall, 47.5% of all treated patients were not affected by any adverse events (AEs); 17.5% of patients suffered from severe AEs. The 1-year survival rate was 61.3%. Estimated median progression-free survival (PFS) was 5.3 months. Patients who received nivolumab as third or later therapy line treatment (77.5%) achieved similar median PFS and 12-month overall survival rate of 52%. CONCLUSION: Our findings of immunotherapy treatment outside clinical trials support the results of studies in the past and confirm the efficacy and favorable toxicity profile of nivolumab treatment in advanced SQ-NSCLC patients. In addition, we can present some rarely described information about nivolumab treatment of heavily pretreated patients, which provides some evidence that immunotherapy could also be useful in later therapy lines.

Differential expression of classical nuclear transport factors during cellular proliferation and differentiation.

We recently cloned six human importin a proteins that transport specific substrates in complex with importin beta into the nucleus. We now compared their absolute expression levels in different human cell lines. We examined their expression regulation during human cell proliferation and differentiation by means of specific antibodies. Proliferation inhibition by starvation of HeLa and HaCaT cells led to a marked decrease in the expression of various nuclear transport factors. In contrast, re-addition of serum increased alpha-importin expression. We analyzed two models for cell differentiation and found differential importin regulation. Stimulation of rat pancreatic AR42J cell differentiation towards a neuroendocrine phenotype with activin A or towards an acinar phenotype with dexamethasone, caused strong upregulation of importin alpha3 and alpha4 expression. Phorbol ester-induced differentiation of human leukemia (HL60) cells towards a macrophage phenotype led to downregulation of importin alpha1 and alpha4 expression after 72 hours. Similarly, importins alpha1 and alpha4 displayed a strong downregulation when HL60 cells were directed towards a neutrophil phenotype by DMSO treatment. This study is the first to assess all the human importin alpha isoforms in documenting differential nuclear transport factor regulation during cell proliferation and differentiation.