Case report: Immune response characterization of a pseudoprogression in a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated metastatic NSCLC.

A patient with a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated metastatic non-small cell lung cancer (NSCLC) experienced a multisite radiological progression at 3 months after initiation of chemoimmunotherapy as first-line treatment for metastatic disease. After the radiological progression, while she was not undergoing treatment, the patient had spontaneous lesions shrinkage and further achieved a prolonged complete response. Genomic and transcriptomic data collected at baseline and at the time of pseudoprogression allowed us to biologically characterize this rare response pattern. We observed the presence of a tumor-specific T-cell response against tumor-specific neoantigens (TNAs). Endogenous retroviruses (ERVs) expression following chemoimmunotherapy was also observed, concurrent with biological features of an anti-viral-like innate immune response with type I IFN signaling and production of CXCR3-associated chemokines. This is the first biological characterization of a NSCLC pseudoprogression under chemoimmunotherapy followed by a prolonged complete response in a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated NSCLC. These clinical and biological data underline that even patients with multiple factors of resistance to immune checkpoint inhibitors could trigger a tumor-specific immune response to tumor neoantigen, leading to complete eradication of the tumor and probably a vaccinal immune response.

Activation of the helper NRC4 immune receptor forms a hexameric resistosome.

Innate immune responses to microbial pathogens are regulated by intracellular receptors known as nucleotide-binding leucine-rich repeat receptors (NLRs) in both the plant and animal kingdoms. Across plant innate immune systems, "helper" NLRs (hNLRs) work in coordination with "sensor" NLRs (sNLRs) to modulate disease resistance signaling pathways. Activation mechanisms of hNLRs based on structures are unknown. Our research reveals that the hNLR, known as NLR required for cell death 4 (NRC4), assembles into a hexameric resistosome upon activation by the sNLR Bs2 and the pathogenic effector AvrBs2. This conformational change triggers immune responses by facilitating the influx of calcium ions (Ca2+) into the cytosol. The activation mimic alleles of NRC2, NRC3, or NRC4 alone did not induce Ca2+ influx and cell death in animal cells, suggesting that unknown plant-specific factors regulate NRCs' activation in plants. These findings significantly advance our understanding of the regulatory mechanisms governing plant immune responses.

Early pragmatic expectations in human infancy.

There is no room for pragmatic expectations about communicative interactions in core cognition. Spelke takes the combinatorial power of the human language faculty to overcome the limits of core cognition. The question is: Why should the combinatorial power of the human language faculty support infants' pragmatic expectations not merely about speech, but also about nonverbal communicative interactions?

Carboplatin and Etoposide for the Treatment of Metastatic Prostate Cancer with or without Neuroendocrine Features: A French Single-Center Experience.

BACKGROUND: Chemotherapy using carboplatin and etoposide (CE) is frequently pragmatically proposed to treat metastatic prostate cancer (mPC), both primary small-cell neuroendocrine (PSC-NE) carcinoma and adenocarcinoma with or without neuroendocrine (NE) marker elevation. However, the real benefit of CE is poorly reported in the recent therapeutic context. METHODS: We retrospectively analyzed the efficacy and tolerance of CE chemotherapy in these three different groups of mPC patients. Efficacy endpoints included radiological response, progression-free survival (PFS), and overall survival (OS), as well as PSA response and PFS2/PFS1 ratio in patients with adenocarcinoma. RESULTS: Sixty-nine patients were included in this single-center study (N = 18 with PSC-NE carcinoma and 51 with adenocarcinoma with (N = 18) or without (N = 33) NE marker elevation). Patients with adenocarcinoma were highly pretreated with next-generation hormonal agents (NHAs) and taxanes. In patients with adenocarcinoma, a PSA response ≥50% was observed in six patients (15.8%), four of whom had NE marker elevation. The radiological response was higher in PSC-NE and tended to be higher in adenocarcinoma when NE marker elevation was present. Comparing patients with adenocarcinoma with vs. without NE marker elevation, the median PFS was 3.7 and 2.1 months and the median OS was 7.7 and 4.7 months, respectively. Overall, 62.3% of patients experienced grade 3-4 adverse events (mainly hematological), and three treatment-related deaths were recorded. CONCLUSION: Reports of the clinical results of CE suggest that we should not mix PSC-NE and castration-resistant adenocarcinoma of the prostate. In patients with heavily pretreated adenocarcinoma, the benefit/risk ratio of CE chemotherapy seems unfavorable due to poor response and high toxicity.

An annotated wing interferential pattern dataset of dipteran insects of medical interest for deep learning.

Several Diptera species are known to transmit pathogens of medical and veterinary interest. However, identifying these species using conventional methods can be time-consuming, labor-intensive, or expensive. A computer vision-based system that uses Wing interferential patterns (WIPs) to identify these insects could solve this problem. This study introduces a dataset for training and evaluating a recognition system for dipteran insects of medical and veterinary importance using WIPs. The dataset includes pictures of Culicidae, Calliphoridae, Muscidae, Tabanidae, Ceratopogonidae, and Psychodidae. The dataset is complemented by previously published datasets of Glossinidae and some Culicidae members. The new dataset contains 2,399 pictures of 18 genera, with each genus documented by a variable number of species and annotated as a class. The dataset covers species variation, with some genera having up to 300 samples.

Species identification of phlebotomine sandflies using deep learning and wing interferential pattern (WIP).

Sandflies (Diptera; Psychodidae) are medical and veterinary vectors that transmit diverse parasitic, viral, and bacterial pathogens. Their identification has always been challenging, particularly at the specific and sub-specific levels, because it relies on examining minute and mostly internal structures. Here, to circumvent such limitations, we have evaluated the accuracy and reliability of Wing Interferential Patterns (WIPs) generated on the surface of sandfly wings in conjunction with deep learning (DL) procedures to assign specimens at various taxonomic levels. Our dataset proves that the method can accurately identify sandflies over other dipteran insects at the family, genus, subgenus, and species level with an accuracy higher than 77.0%, regardless of the taxonomic level challenged. This approach does not require inspection of internal organs to address identification, does not rely on identification keys, and can be implemented under field or near-field conditions, showing promise for sandfly pro-active and passive entomological surveys in an era of scarcity in medical entomologists.

A phase I study of the combination of atezolizumab, tiragolumab, and stereotactic body radiation therapy in patients with metastatic multiorgan cancer.

BACKGROUND: Immunotherapy targeting the PD-1/PD-L1 pathway is a standard of care in a number of metastatic malignancies, but less than a fifth of patients are expected to respond to ICIs (Immune Checkpoint Inhibitors). In a clinical trial, combining the anti-TIGIT (T cell immunoreceptor with Ig and ITIM domains) Mab (monoclonal antibody) tiragolumab with atezolizumab improved outcomes in non-small cell lung cancer. In preclinical models, SBRT (Stereotactic Body Radiation Therapy) could increase expression levels of the inhibitory co-receptors TIGIT and PD-L1. We aim to assess the combination of tiragolumab with atezolizumab and SBRT in metastatic, previously treated by ICIs, non-small cell lung cancer, head and neck cancer, bladder cancer, and renal cell cancer. METHODS: This phase I study (ClinicalTrials.gov NCT05259319) will assess the efficacy and safety of the combination of atezolizumab with tiragolumab and stereotactic body radiation therapy in patients with histologically proven metastatic non-small cell lung cancer, renal cell cancer, bladder cancer, and head and neck cancer previously treated. First part: 2 different schedules of SBRT in association with a fixed dose of atezolizumab and tiragolumab will be investigated only with metastatic non-small cell lung cancer patients (cohort 1). The expansion cohorts phase will be a multicentric, open-label study at the recommended scheme of administration and enroll additional patients with metastatic bladder cancer, renal cell cancer, and head and neck cancer (cohort 2, 3 and 4). Patients will be treated until disease progression, unacceptable toxicity, intercurrent conditions that preclude continuation of treatment, or patient refusal in the absence of progression or intolerance. The primary endpoint of the first phase is the safety of the combination in a sequential or concomitant scheme and to determine the expansion cohorts phase recommended scheme of administration. The primary endpoint of phase II is to evaluate the efficacy of tiragolumab + atezolizumab + SBRT in terms of 6-month PFS (Progression-Free Survival). Ancillary analyses will be performed with peripheral and intratumoral immune biomarker assessments. TRIAL REGISTRATION: This study is registered on ClinicalTrials.gov: NCT05259319, since February 28th, 2022.

Wing Interferential Patterns (WIPs) and machine learning for the classification of some Aedes species of medical interest.

Hematophagous insects belonging to the Aedes genus are proven vectors of viral and filarial pathogens of medical interest. Aedes albopictus is an increasingly important vector because of its rapid worldwide expansion. In the context of global climate change and the emergence of zoonotic infectious diseases, identification tools with field application are required to strengthen efforts in the entomological survey of arthropods with medical interest. Large scales and proactive entomological surveys of Aedes mosquitoes need skilled technicians and/or costly technical equipment, further puzzled by the vast amount of named species. In this study, we developed an automatic classification system of Aedes species by taking advantage of the species-specific marker displayed by Wing Interferential Patterns. A database holding 494 photomicrographs of 24 Aedes spp. from which those documented with more than ten pictures have undergone a deep learning methodology to train a convolutional neural network and test its accuracy to classify samples at the genus, subgenus, and species taxonomic levels. We recorded an accuracy of 95% at the genus level and > 85% for two (Ochlerotatus and Stegomyia) out of three subgenera tested. Lastly, eight were accurately classified among the 10 Aedes sp. that have undergone a training process with an overall accuracy of > 70%. Altogether, these results demonstrate the potential of this methodology for Aedes species identification and will represent a tool for the future implementation of large-scale entomological surveys.

Deep learning and wing interferential patterns identify Anopheles species and discriminate amongst Gambiae complex species.

We present a new and innovative identification method based on deep learning of the wing interferential patterns carried by mosquitoes of the Anopheles genus to classify and assign 20 Anopheles species, including 13 malaria vectors. We provide additional evidence that this approach can identify Anopheles spp. with an accuracy of up to 100% for ten out of 20 species. Although, this accuracy was moderate (> 65%) or weak (50%) for three and seven species. The accuracy of the process to discriminate cryptic or sibling species is also assessed on three species belonging to the Gambiae complex. Strikingly, An. gambiae, An. arabiensis and An. coluzzii, morphologically indistinguishable species belonging to the Gambiae complex, were distinguished with 100%, 100%, and 88% accuracy respectively. Therefore, this tool would help entomological surveys of malaria vectors and vector control implementation. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases.

Is localized acquired resistance the mechanism for effector-triggered disease resistance in plants?

Plant nucleotide-binding leucine-rich repeat receptors (NLRs) are intracellular immune receptors that are activated by their direct or indirect interactions with virulence effectors. NLR activation triggers a strong immune response and consequent disease resistance. However, the NLR-driven immune response can be targeted by virulence effectors. It is thus unclear how immune activation can occur concomitantly with virulence effector suppression of immunity. Recent observations suggest that the activation of effector-triggered immunity does not sustain defence gene expression in tissues in contact with the hemi-biotrophic pathogen Pseudomonas syringae pv. tomato. Instead, strong defence was observed on the border of the infection area. This response is reminiscent of localized acquired resistance (LAR). LAR is a strong defence response occurring in a ~2 mm area around cells in contact with the pathogen and probably serves to prevent the spread of pathogens. Here we propose that effector-triggered immunity is essentially a quarantining mechanism to prevent systemic pathogen spread and disease, and that the induction of LAR is a key component of this mechanism.

Broader functions of TIR domains in Arabidopsis immunity.

TIR domains are NAD-degrading enzymes that function during immune signaling in prokaryotes, plants, and animals. In plants, most TIR domains are incorporated into intracellular immune receptors termed TNLs. In Arabidopsis, TIR-derived small molecules bind and activate EDS1 heterodimers, which in turn activate RNLs, a class of cation channel-forming immune receptors. RNL activation drives cytoplasmic Ca2+ influx, transcriptional reprogramming, pathogen resistance, and host cell death. We screened for mutants that suppress an RNL activation mimic allele and identified a TNL, SADR1. Despite being required for the function of an autoactivated RNL, SADR1 is not required for defense signaling triggered by other tested TNLs. SADR1 is required for defense signaling initiated by some transmembrane pattern recognition receptors and contributes to the unbridled spread of cell death in lesion simulating disease 1. Together with RNLs, SADR1 regulates defense gene expression at infection site borders, likely in a non-cell autonomous manner. RNL mutants that cannot sustain this pattern of gene expression are unable to prevent disease spread beyond localized infection sites, suggesting that this pattern corresponds to a pathogen containment mechanism. SADR1 potentiates RNL-driven immune signaling not only through the activation of EDS1 but also partially independently of EDS1. We studied EDS1-independent TIR function using nicotinamide, an NADase inhibitor. Nicotinamide decreased defense induction from transmembrane pattern recognition receptors and decreased calcium influx, pathogen growth restriction, and host cell death following intracellular immune receptor activation. We demonstrate that TIR domains can potentiate calcium influx and defense and are thus broadly required for Arabidopsis immunity.

Long-lasting spatial memory deficits and impaired hippocampal plasticity following unilateral vestibular loss.

Unilateral vestibular loss (UVL) induces a characteristic vestibular syndrome composed of various posturo-locomotor, oculomotor, vegetative and perceptivo-cognitive symptoms. Functional deficits are progressively recovered over time during vestibular compensation, that is supported by the expression of multiscale plasticity mechanisms. While the dynamic of post-UVL posturo-locomotor and oculomotor deficits is well characterized, the expression over time of the cognitive deficits, and in particular spatial memory deficits, is still debated. In this study we aimed at investigating spatial memory deficits and their recovery in a rat model of unilateral vestibular neurectomy (UVN), using a wide spectrum of behavioral tasks. In parallel, we analyzed markers of hippocampal plasticity involved in learning and memory. Our results indicate the UVN affects all domains of spatial memory, from working memory to reference memory and object-in-place recognition. These deficits are associated with long-lasting impaired plasticity in the ipsilesional hippocampus. These results highlight the crucial role of symmetrical vestibular information in spatial memory and contribute to a better understanding of the cognitive disorders observed in vestibular patients.

Zn2+ inhibits spatial memory and hippocampal place cell representation through high-affinity binding to the NMDA receptor GluN2A subunit.

A subset of glutamatergic neurons in the forebrain uses labile Zn2+ as a co-transmitter alongside glutamate. Synaptic Zn2+ plays a key role in learning and memory processes, but its mechanisms of action remain poorly understood. Here, we used a knock-in (KI) mouse line carrying a point mutation at the GluN2A Zn2+ binding site that selectively eliminates zinc inhibition of NMDA receptors. Ablation of Zn2+-GluN2A binding improves spatial memory retention and contextual fear memory formation. Electrophysiological recording of hippocampal neurons in the CA1 area revealed a greater proportion of place cells and substantial place field remapping in KI mice compared to wildtype littermates. Persistent place cell remapping was also seen in KI mice upon repeated testing suggesting an enhanced ability to maintain a distinct representation across multiple overlapping experiences. Together, these findings reveal an original molecular mechanism through which synaptic Zn2+ negatively modulates spatial cognition by dampening GluN2A-containing NMDA receptor signaling.

Wing Interferential Patterns (WIPs) and machine learning, a step toward automatized tsetse (Glossina spp.) identification.

A simple method for accurately identifying Glossina spp in the field is a challenge to sustain the future elimination of Human African Trypanosomiasis (HAT) as a public health scourge, as well as for the sustainable management of African Animal Trypanosomiasis (AAT). Current methods for Glossina species identification heavily rely on a few well-trained experts. Methodologies that rely on molecular methodologies like DNA barcoding or mass spectrometry protein profiling (MALDI TOFF) haven't been thoroughly investigated for Glossina sp. Nevertheless, because they are destructive, costly, time-consuming, and expensive in infrastructure and materials, they might not be well adapted for the survey of arthropod vectors involved in the transmission of pathogens responsible for Neglected Tropical Diseases, like HAT. This study demonstrates a new type of methodology to classify Glossina species. In conjunction with a deep learning architecture, a database of Wing Interference Patterns (WIPs) representative of the Glossina species involved in the transmission of HAT and AAT was used. This database has 1766 pictures representing 23 Glossina species. This cost-effective methodology, which requires mounting wings on slides and using a commercially available microscope, demonstrates that WIPs are an excellent medium to automatically recognize Glossina species with very high accuracy.

Allelic variation in the Arabidopsis TNL CHS3/CSA1 immune receptor pair reveals two functional cell-death regulatory modes.

Some plant NLR immune receptors are encoded in head-to-head "sensor-executor" pairs that function together. Alleles of the NLR pair CHS3/CSA1 form three clades. The clade 1 sensor CHS3 contains an integrated domain (ID) with homology to regulatory domains, which is lacking in clades 2 and 3. In this study, we defined two cell-death regulatory modes for CHS3/CSA1 pairs. One is mediated by ID domain on clade 1 CHS3, and the other relies on CHS3/CSA1 pairs from all clades detecting perturbation of an associated pattern-recognition receptor (PRR) co-receptor. Our data support the hypothesis that an ancestral Arabidopsis CHS3/CSA1 pair gained a second recognition specificity and regulatory mechanism through ID acquisition while retaining its original specificity as a "guard" against PRR co-receptor perturbation. This likely comes with a cost, since both ID and non-ID alleles of the pair persist in diverse Arabidopsis populations through balancing selection.

Con-Ca2+ -tenating plant immune responses via calcium-permeable cation channels.

Calcium serves as a second messenger in a variety of developmental and physiological processes and has long been identified as important for plant immune responses. We discuss recent discoveries regarding plant immune-related calcium-permeable channels and how the two intertwined branches of the plant immune system are intricately linked to one another through calcium signalling. Cell surface immune receptors carefully tap the immense calcium gradient that exists between apoplast and cytoplasm in a short burst via tightly regulated plasma membrane (PM)-resident cation channels. Intracellular immune receptors form atypical calcium-permeable cation channels at the PM and mediate a prolonged calcium influx, overcoming the deleterious influence of pathogen effectors and enhancing plant immune responses.

Evaluating the reliability of mobility metrics from aggregated mobile phone data as proxies for SARS-CoV-2 transmission in the USA: a population-based study.

BACKGROUND: In early 2020, the response to the SARS-CoV-2 pandemic focused on non-pharmaceutical interventions, some of which aimed to reduce transmission by changing mixing patterns between people. Aggregated location data from mobile phones are an important source of real-time information about human mobility on a population level, but the degree to which these mobility metrics capture the relevant contact patterns of individuals at risk of transmitting SARS-CoV-2 is not clear. In this study we describe changes in the relationship between mobile phone data and SARS-CoV-2 transmission in the USA. METHODS: In this population-based study, we collected epidemiological data on COVID-19 cases and deaths, as well as human mobility metrics collated by advertisement technology that was derived from global positioning systems, from 1396 counties across the USA that had at least 100 laboratory-confirmed cases of COVID-19. We grouped these counties into six ordinal categories, defined by the National Center for Health Statistics (NCHS) and graded from urban to rural, and quantified the changes in COVID-19 transmission using estimates of the effective reproduction number (Rt) between Jan 22 and July 9, 2020, to investigate the relationship between aggregated mobility metrics and epidemic trajectory. For each county, we model the time series of Rt values with mobility proxies. FINDINGS: We show that the reproduction number is most strongly associated with mobility proxies for change in the travel into counties (0·757 [95% CI 0·689 to 0·857]), but this relationship primarily holds for counties in the three most urban categories as defined by the NCHS. This relationship weakens considerably after the initial 15 weeks of the epidemic (0·442 [-0·492 to -0·392]), consistent with the emergence of more complex local policies and behaviours, including masking. INTERPRETATION: Our study shows that the integration of mobility metrics into retrospective modelling efforts can be useful in identifying links between these metrics and Rt. Importantly, we highlight potential issues in the data generation process for transmission indicators derived from mobile phone data, representativeness, and equity of access, which must be addressed to improve the interpretability of these data in public health. FUNDING: There was no funding source for this study.

Plant "helper" immune receptors are Ca2+-permeable nonselective cation channels.

Plant nucleotide-binding leucine-rich repeat receptors (NLRs) regulate immunity and cell death. In Arabidopsis, a subfamily of "helper" NLRs is required by many "sensor" NLRs. Active NRG1.1 oligomerized, was enriched in plasma membrane puncta, and conferred cytoplasmic calcium ion (Ca2+) influx in plant and human cells. NRG1.1-dependent Ca2+ influx and cell death were sensitive to Ca2+ channel blockers and were suppressed by mutations affecting oligomerization or plasma membrane enrichment. Ca2+ influx and cell death mediated by NRG1.1 and ACTIVATED DISEASE RESISTANCE 1 (ADR1), another helper NLR, required conserved negatively charged N-terminal residues. Whole-cell voltage-clamp recordings demonstrated that Arabidopsis helper NLRs form Ca2+-permeable cation channels to directly regulate cytoplasmic Ca2+ levels and consequent cell death. Thus, helper NLRs transduce cell death signals directly.

The Seed Development Factors TT2 and MYB5 Regulate Heat Stress Response in Arabidopsis.

HEAT SHOCK FACTOR A2 (HSFA2) is a regulator of multiple environmental stress responses required for stress acclimation. We analyzed HSFA2 co-regulated genes and identified 43 genes strongly co-regulated with HSFA2 during multiple stresses. Motif enrichment analysis revealed an over-representation of the site II element (SIIE) in the promoters of these genes. In a yeast 1-hybrid screen with the SIIE, we identified the closely related R2R3-MYB transcription factors TT2 and MYB5. We found overexpression of MYB5 or TT2 rendered plants heat stress tolerant. In contrast, tt2, myb5, and tt2/myb5 loss of function mutants showed heat stress hypersensitivity. Transient expression assays confirmed that MYB5 and TT2 can regulate the HSFA2 promoter together with the other members of the MBW complex, TT8 and TRANSPARENT TESTA GLABRA 1 (TTG1) and that the SIIE was involved in this regulation. Transcriptomic analysis revealed that TT2/MYB5 target promoters were enriched in SIIE. Overall, we report a new function of TT2 and MYB5 in stress resistance and a role in SIIE-mediated HSFA2 regulation.

A Gibbs sampler for a class of random convex polytopes.

We present a Gibbs sampler for the Dempster-Shafer (DS) approach to statistical inference for Categorical distributions. The DS framework extends the Bayesian approach, allows in particular the use of partial prior information, and yields three-valued uncertainty assessments representing probabilities "for", "against", and "don't know" about formal assertions of interest. The proposed algorithm targets the distribution of a class of random convex polytopes which encapsulate the DS inference. The sampler relies on an equivalence between the iterative constraints of the vertex configuration and the non-negativity of cycles in a fully connected directed graph. Illustrations include the testing of independence in 2 × 2 contingency tables and parameter estimation of the linkage model.