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Simple Summary: Visuospatial circuits (VS) must be preserved during brain tumours' excision. Navigated TMS is a valid tool to preoperatively map VS networks and to optimise functional preservation. In this work, we tested 27 patients with nTMS preoperative mapping and an experimental test for VS abilities, called VISA, demonstrating a good clinical outcome (functional recovery 80–98.86%) and a useful nTMS map for tractography reconstruction (with the main involvement of the second and the third branches of the superior longitudinal fasciculus). Finally, a comparison of nTMS and DCS points in awake surgery (n = 10 patients) documented a sensitivity (Se) of 12%, a specificity (Sp) of 91.21%, a positive predictive value (PPV) of 42%, a negative predictive value (NPV) of 66%, and an accuracy of ~63.7%. According to our preliminary results, nTMS is advantageous to study cognitive functions, minimising neurological impairment. Further analyses are needed to validate our data. Objective: Navigated transcranial magnetic stimulation (nTMS) has seldom been used to study visuospatial (VS) circuits so far. Our work studied (I) VS functions in neurosurgical oncological patients by using repetitive nTMS (rnTMS), (II) the possible subcortical circuits underneath, and (III) the correspondence between nTMS and direct cortical stimulation (DCS) during awake procedures. Methods: We designed a monocentric prospective study, adopting a protocol to use rnTMS for preoperative planning, including VS functions for lesions potentially involving the VS network, including neurosurgical awake and asleep procedures. nTMS-based-DTI tractography allowed the visualization of subcortical circuits. Statistical analyses on nTMS/DCS points were performed. Clinical results were collected pre- and postoperatively. Results: Finally, 27 patients with primitive intra-axial brain lesions were enrolled between April 2023 and March 2024. Specific tests and an experimental integrated VS test (VISA) were used. The clinical evaluation (at 5 ± 7, 30 ± 10, 90 ± 10 days after surgery) documented 33% of patients with neglect in the left hemisphere four days after surgery and, during the 3-month follow-up, preservation of visuospatial function/clinical recovery (90.62% in MMSE, 98.86% in the bell test, 80% in the clock test, and 98% in the OCS test). The surgical strategy was modulated according to the nTMS map. Subcortical bundles were traced to identify those most involved in these functions: SFLII > SLFII > SLFI. A comparison of the nTMS and DCS points in awake surgery (n = 10 patients) documented a sensitivity (Se) of 12%, a specificity (Sp) of 91.21%, a positive predictive value (PPV) of 42%, a negative predictive value (NPV) of 66%, and an accuracy of ~63.7%. Conclusions: Based on our preliminary results, nTMS is advantageous for studying cognitive functions, minimising neurological impairment. Further analyses are needed to validate our data. [ABSTRACT FROM AUTHOR]

Simple Summary: The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. Analyses of the NEPA provide additional information to the magnetic resonance imaging (MRI) evaluation of the enhancing part of brain tumors. NEPA analyses of central nervous system malignancies with conventional and advanced MRI techniques give interesting highlights in the differential diagnosis of solid contrast-enhanced brain tumors regarding the prognostic stratification and treatment response. Considering the rapid technological changes in advanced MRI imaging, we assume that an update on this topic might be of interest. The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. The NEPA corresponds to different pathological processes, including vasogenic edema and infiltrative edema. The analysis of the NEPA with conventional and advanced magnetic resonance imaging (MRI) was proposed in the differential diagnosis of solid brain tumors, showing higher accuracy than MRI evaluation of the enhancing part of the tumor. In particular, MRI assessment of the NEPA was demonstrated to be a promising tool for distinguishing high-grade gliomas from primary lymphoma and brain metastases. Additionally, the MRI characteristics of the NEPA were found to correlate with prognosis and treatment response. The purpose of this narrative review was to describe MRI features of the NEPA obtained with conventional and advanced MRI techniques to better understand their potential in identifying the different characteristics of high-grade gliomas, primary lymphoma and brain metastases and in predicting clinical outcome and response to surgery and chemo-irradiation. Diffusion and perfusion techniques, such as diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), dynamic susceptibility contrast-enhanced (DSC) perfusion imaging, dynamic contrast-enhanced (DCE) perfusion imaging, arterial spin labeling (ASL), spectroscopy and amide proton transfer (APT), were the advanced MRI procedures we reviewed. [ABSTRACT FROM AUTHOR]

Simple Summary: To examine the role of [18F]FDG PET/CT for assessing response to immunotherapy in patients with some solid tumors. Seventeen Italian centers analyzed the role of serial [18F]FDG PET/CT scans in patients candidates and, later undergoing immunotherapy for some solid cancers. Serial [18F]FDG PET/CT can be useful in evaluating the response to therapy, soon after 3 and 6-months from the start of immunotherapy. The evidences were foud both in patients affected by lung cancer and malignant melanoma, although large prospective trials are needed for definitively confirmed these findings. AIM: To examine the role of [18F]FDG PET/CT for assessing response to immunotherapy in patients with some solid tumors. METHODS: Data recorded in a multicenter (n = 17), retrospective database between March and November 2021 were analyzed. The sample included patients with a confirmed diagnosis of a solid tumor who underwent serial [18F]FDG PET/CT (before and after one or more cycles of immunotherapy), who were >18 years of age, and had a follow-up of at least 12 months after their first PET/CT scan. Patients enrolled in clinical trials or without a confirmed diagnosis of cancer were excluded. The authors classified cases as having a complete or partial metabolic response to immunotherapy, or stable or progressive metabolic disease, based on a visual and semiquantitative analysis according to the EORTC criteria. Clinical response to immunotherapy was assessed at much the same time points as the serial PET scans, and both the obtained responses were compared. RESULTS: The study concerned 311 patients (median age: 67; range: 31–89 years) in all. The most common neoplasm was lung cancer (56.9%), followed by malignant melanoma (32.5%). Nivolumab was administered in 46.3%, and pembrolizumab in 40.5% of patients. Baseline PET and a first PET scan performed at a median 3 months after starting immunotherapy were available for all 311 patients, while subsequent PET scans were obtained after a median 6, 12, 16, and 21 months for 199 (64%), 102 (33%), 46 (15%), and 23 (7%) patients, respectively. Clinical response to therapy was recorded at around the same time points after starting immunotherapy for 252 (81%), 173 (56%), 85 (27%), 40 (13%), and 22 (7%) patients, respectively. After a median 18 (1–137) months, 113 (36.3%) patients had died. On Kaplan–Meier analysis, metabolic responders on the first two serial PET scans showed a better prognosis than non-responders, while clinical response became prognostically informative from the second assessment after starting immunotherapy onwards. CONCLUSIONS: [18F]FDG PET/CT could have a role in the assessment of response to immunotherapy in patients with some solid tumors. It can provide prognostic information and thus contribute to a patient's appropriate treatment. Prospective randomized controlled trials are mandatory. [ABSTRACT FROM AUTHOR]

Screening of Pap smear images continues to depend upon cytopathologists' manual scrutiny, and the results are highly influenced by professional experience, leading to varying degrees of cell classification inaccuracies. In order to improve the quality of the Pap smear results, several efforts have been made to create software to automate and standardize the processing of medical images. In this work, we developed the CEA (Cytopathologist Eye Assistant), an easy-to-use tool to aid cytopathologists in performing their daily activities. In addition, the tool was tested by a group of cytopathologists, whose feedback indicates that CEA could be a valuable tool to be integrated into Pap smear image analysis routines. For the construction of the tool, we evaluate different YOLO configurations and classification approaches. The best combination of algorithms uses YOLOv5s as a detection algorithm and an ensemble of EfficientNets as a classification algorithm. This configuration achieved 0.726 precision, 0.906 recall, and 0.805 F1-score when considering individual cells. We also made an analysis to classify the image as a whole, in which case, the best configuration was the YOLOv5s to perform the detection and classification tasks, and it achieved 0.975 precision, 0.992 recall, 0.970 accuracy, and 0.983 F1-score. [ABSTRACT FROM AUTHOR]

Simple Summary: Anticancer treatments commonly cause adverse events (AE). Among others, pneumatosis intestinalis (PI) is reported to be infrequent, though it can lead to severe consequences. The aim of our systematic review was to investigate the concurrency of PI and oncological therapy exposure; moreover, we defined the characteristics of patients and the primarily involved tumor types. We analyzed 88 different episodes of PI. The median time of onset was 6 weeks and oncological patients with respiratory system cancers and those treated with targeted therapies appeared be at higher risk. Symptoms were frequently mild to absent; nevertheless, life-threatening complications were reported. Therefore, this AE, although uncommon, should be considered in the case of specific symptoms. Potential pharmacological mechanisms of anticancer drugs in inducing PI are also discussed. Pneumatosis intestinalis (PI) is a rare condition due to the presence of gas within the bowel wall; it is mainly caused by endoscopic procedures, infections and other gastrointestinal diseases. Oncological therapies have been reported to be a cause of PI as well, but their role is not clearly defined. This systematic review investigates the concurrency of PI and antitumor therapy in cancer patients, considering both solid tumors and onco-hematological ones. We performed a literature review of PubMed, Embase and the Web of Science up to September 2021 according to the PRISMA guidelines. A total of 62 papers reporting 88 different episodes were included. PI was mainly reported with targeted therapies (sunitinib and bevacizumab above all) within the first 12 weeks of treatment. This adverse event mostly occurred in the metastatic setting, but in 10 cases, it also occurred also in the neoadjuvant and adjuvant setting. PI was mostly localized in the large intestine, being fatal in 11 cases, while in the remaining cases, symptoms were usually mild, or even absent. A significant risk of PI reoccurrence after drug reintroduction was also reported (6/18 patients), with no fatal outcomes. Potential pharmacological mechanisms underlying PI pathogenesis are also discussed. In conclusion, although uncommonly, PI can occur during oncological therapies and may lead to life-threatening complications; therefore, consideration of its occurrence among other adverse events is warranted in the presence of clinical suspicion. [ABSTRACT FROM AUTHOR]

Purpose. Nerve growth factor efficacy was demonstrated for corneal lesions treatment, and recombinant human NGF (rhNGF) was approved for neurotrophic keratitis therapy. However, NGF-induced molecular responses in cornea are still largely unknown. We analyzed microRNAs expression in human epithelial corneal cells after time-dependent rhNGF treatment. Methods. Nearly 700 microRNAs were analyzed by qRT-PCR. MicroRNAs showing significant expression differences were examined by DIANA-miRpath v.3.0 to identify target genes and pathways. Immunoblots were performed to preliminarily assess the strength of the in silico results. Results. Twenty-one microRNAs (miR-26a-1-3p, miR-30d-3p, miR-27b-5p, miR-146a-5p, miR-362-5p, mir-550a-5p, mir-34a-3p, mir-1227-3p, mir-27a-5p, mir-222-5p, mir-151a-5p, miR-449a, let7c-5p, miR-337-5p, mir-29b-3p, miR-200b-3p, miR-141-3p, miR-671-3p, miR-324-5p, mir-411-3p, and mir-425-3p) were significantly regulated in response to rhNGF. In silico analysis evidenced interesting target genes and pathways, including that of neurotrophin, when analyzed in depth. Almost 80 unique target genes (e.g., PI3K, AKT, MAPK, KRAS, BRAF, RhoA, Cdc42, Rac1, Bax, Bcl2, FasL) were identified as being among those most involved in neurotrophin signaling and in controlling cell proliferation, growth, and apoptosis. AKT and RhoA immunoblots demonstrated congruence with microRNA expression, providing preliminary validation of in silico data. Conclusions. MicroRNA levels in response to rhNGF were for the first time analyzed in corneal cells. Novel insights about microRNAs, target genes, pathways modulation, and possible biological responses were provided. Importantly, given the putative role of microRNAs as biomarkers or therapeutic targets, our results make available data which might be potentially exploitable for clinical applications. [ABSTRACT FROM AUTHOR]

In recent years, deep learning methods have outperformed previous state-of-the-art machine learning techniques for several problems, including image classification. Classifying cells in Pap smear images is very challenging, and it is still of paramount importance for cytopathologists. The Pap test is a cervical cancer prevention test that tracks preneoplastic changes in cervical epithelial cells. Carrying out this exam is important in that early detection. It is directly related to a greater chance of curing or reducing the number of deaths caused by the disease. The analysis of Pap smears is exhaustive and repetitive, as it is performed manually by cytopathologists. Therefore, a tool that assists cytopathologists is needed. This work considers 10 deep convolutional neural networks and proposes an ensemble of the three best architectures to classify cervical cancer upon cell nuclei and reduce the professionals' workload. The dataset used in the experiments is available in the Center for Recognition and Inspection of Cells (CRIC) Searchable Image Database. Considering the metrics of precision, recall, F1-score, accuracy, and sensitivity, the proposed ensemble improves previous methods shown in the literature for two- and three-class classification. We also introduce the six-class classification outcome. [ABSTRACT FROM AUTHOR]

Prevention of cervical cancer could be performed using Pap smear image analysis. This test screens pre-neoplastic changes in the cervical epithelial cells; accurate screening can reduce deaths caused by the disease. Pap smear test analysis is exhaustive and repetitive work performed visually by a cytopathologist. This article proposes a workload-reducing algorithm for cervical cancer detection based on analysis of cell nuclei features within Pap smear images. We investigate eight traditional machine learning methods to perform a hierarchical classification. We propose a hierarchical classification methodology for computer-aided screening of cell lesions, which can recommend fields of view from the microscopy image based on the nuclei detection of cervical cells. We evaluate the performance of several algorithms against the Herlev and CRIC databases, using a varying number of classes during image classification. Results indicate that the hierarchical classification performed best when using Random Forest as the key classifier, particularly when compared with decision trees, k-NN, and the Ridge methods. [ABSTRACT FROM AUTHOR]

Simple Summary: The efficacy and safety of oxaliplatin-based regimens in late-care settings have been poorly reported. In 119 mCRC patients, the oxaliplatin retreatment response rate (RR) was 21.6%. The median progression-free survival was 5.1 months. A total of 34/119 (28.6%) discontinued treatments were due to toxicities. Oxaliplatin retreatment produced further RR, but one-third of patients discontinued treatment due to adverse events. Thus, translational studies that improve patient selections are warranted. Background: oxaliplatin with fluoropyrimidine is a "mainstay" regarding the upfront treatment of metastatic colorectal cancer (mCRC). In contrast, the efficacy and safety of oxaliplatin-based regimens in late-care settings have been poorly reported. Methods: we identified a real-world mCRC patient cohort who were re-treated with oxaliplatin, and in which clinicopathological features were retrospectively analyzed to identify efficacy–predictive determinants (RETROX-CRC study). Results: of 2606 patients, 119 fulfilled the eligibility criteria. Oxaliplatin retreatment response rate (RR) and disease control rate (DCR) were 21.6% (CI 14.4–31.0%), and 57.8% (CI 47.7–67.4). A trend towards better RR and DCR was observed among patients who had first oxaliplatin in an adjuvant setting; a poorer outcome was observed if two or more intervening treatments were delivered. Median progression-free survival (PFS) was 5.1 months (95%CI 4.3–6.1), reducing to 4.0 months (95%CI 3.07–5.13) if oxaliplatin was readministered beyond third-line (HR 2.02; 1.25–3.25; p = 0.004). Safety data were retrieved in 65 patients (54.6%); 18.5% (12/65) and 7.7% (5/65) had G3–4 toxicities. Toxicities led to discontinuation in 34/119 (28.6%). Conclusions: oxaliplatin retreatment produced further RR in around one-fifth of patients and DCR 57.8%. Efficacy decreased in more pre-treated patients and around one-third of patients discontinued treatment due to adverse events. Translational studies improving patient selection are warranted. [ABSTRACT FROM AUTHOR]

There is a constant risk of iron ore collapsing during its transfer between processing stages in beneficiation plants. Existing instrumentation is not only expensive but also complex and challenging to maintain. In this research, we propose using edge artificial intelligence for early detection of landslide risk based on images of iron ore transported on conveyor belts. During this work, we defined the device edge and the deep neural network model. Then, we built a prototype will to collect images that will be used for training the model. This model will be compressed for use in the device edge. This same prototype will be used for field tests of the model under operational conditions. In building the prototype, a real-time clock was used to ensure the synchronization of image records with the plant's process information, ensuring the correct classification of images by the process specialist. The results obtained in the field tests of the prototype with an accuracy of 91% and a recall of 96% indicate the feasibility of using deep learning at the edge to detect the type of iron ore and prevent its risk of avalanche. [ABSTRACT FROM AUTHOR]

Diffusion-based magnetic resonance imaging (MRI) studies, namely diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI), have been performed in the context of systemic lupus erythematosus (SLE), either with or without neuropsychiatric (NP) involvement, to deepen cerebral microstructure alterations. These techniques permit the measurement of the variations in random movement of water molecules in tissues, enabling their microarchitecture analysis. While DWI is recommended as part of the initial MRI assessment of SLE patients suspected for NP involvement, DTI is not routinely part of the instrumental evaluation for clinical purposes, and it has been mainly used for research. DWI and DTI studies revealed less restricted movement of water molecules inside cerebral white matter (WM), expression of a global loss of WM density, occurring in the context of SLE, prevalently, but not exclusively, in case of NP involvement. More advanced studies have combined DTI with other quantitative MRI techniques, to further characterize disease pathogenesis, while brain connectomes analysis revealed structural WM network disruption. In this narrative review, the authors provide a summary of the evidence regarding cerebral microstructure analysis by DWI and DTI studies in SLE, focusing on lessons learned and future research perspectives. [ABSTRACT FROM AUTHOR]

Simple Summary: Oxaliplatin-based chemotherapy remains the mainstay of first-line therapy in patients with metastatic colorectal cancer (mCRC). Unfortunately, only approximately 60% of treated patients achieve response, and half of responders will experience an early onset of disease progression. Furthermore, some individuals will develop a mixed response due to the emergence of resistant tumor subclones. The ability to predicting which patients will acquire resistance could help them avoid the unnecessary toxicity of oxaliplatin therapies. Furthermore, sorting out lesions that do not respond, in the context of an overall good response, could trigger further investigation into their mutational landscape, providing mechanistic insight towards the planning of a more comprehensive treatment. In this study, we validated a delta-radiomics signature capable of predicting response to oxaliplatin-based first-line treatment of individual liver colorectal cancer metastases. Findings could pave the way to a more personalized treatment of patients with mCRC. The purpose of this paper is to develop and validate a delta-radiomics score to predict the response of individual colorectal cancer liver metastases (lmCRC) to first-line FOLFOX chemotherapy. Three hundred one lmCRC were manually segmented on both CT performed at baseline and after the first cycle of first-line FOLFOX, and 107 radiomics features were computed by subtracting textural features of CT at baseline from those at timepoint 1 (TP1). LmCRC were classified as nonresponders (R−) if they showed progression of disease (PD), according to RECIST1.1, before 8 months, and as responders (R+), otherwise. After feature selection, we developed a decision tree statistical model trained using all lmCRC coming from one hospital. The final output was a delta-radiomics signature subsequently validated on an external dataset. Sensitivity, specificity, positive (PPV), and negative (NPV) predictive values in correctly classifying individual lesions were assessed on both datasets. Per-lesion sensitivity, specificity, PPV, and NPV were 99%, 94%, 95%, 99%, 85%, 92%, 90%, and 87%, respectively, in the training and validation datasets. The delta-radiomics signature was able to reliably predict R− lmCRC, which were wrongly classified by lesion RECIST as R+ at TP1, (93%, averaging training and validation set, versus 67% of RECIST). The delta-radiomics signature developed in this study can reliably predict the response of individual lmCRC to oxaliplatin-based chemotherapy. Lesions forecasted as poor or nonresponders by the signature could be further investigated, potentially paving the way to lesion-specific therapies. [ABSTRACT FROM AUTHOR]

Simple Summary: Myelofibrosis (MF) is a progressive myeloproliferative neoplasm with tendency towards leukemic transformation and has the poorest prognosis amongst the Philadelphia-negative classical myeloproliferative neoplasms (MPN). Ruxolitinib, the first FDA-approved JAK1/2 tyrosine kinase inhibitor, is efficient in reducing spleen size and improving patient symptoms, but it has not been shown to eradicate the MF clone. In this study, using functional genomics techniques, we identified the proteasome family as an additional therapeutic target and demonstrated that inhibition of the proteasome family by carfilzomib in combination with ruxolitinib enhanced suppression of primary MF cells in vitro. As the first FDA-approved tyrosine kinase inhibitor for treatment of patients with myelofibrosis (MF), ruxolitinib improves clinical symptoms but does not lead to eradication of the disease or significant reduction of the mutated allele burden. The resistance of MF clones against the suppressive action of ruxolitinib may be due to intrinsic or extrinsic mechanisms leading to activity of additional pro-survival genes or signalling pathways that function independently of JAK2/STAT5. To identify alternative therapeutic targets, we applied a pooled-shRNA library targeting ~5000 genes to a JAK2V617F-positive cell line under a variety of conditions, including absence or presence of ruxolitinib and in the presence of a bone marrow microenvironment-like culture medium. We identified several proteasomal gene family members as essential to HEL cell survival. The importance of these genes was validated in MF cells using the proteasomal inhibitor carfilzomib, which also enhanced lethality in combination with ruxolitinib. We also showed that proteasome gene expression is reduced by ruxolitinib in MF CD34+ cells and that additional targeting of proteasomal activity by carfilzomib enhances the inhibitory action of ruxolitinib in vitro. Hence, this study suggests a potential role for proteasome inhibitors in combination with ruxolitinib for management of MF patients. [ABSTRACT FROM AUTHOR]

Ecological environments research helps to assess the impacts on forests and managing forests. The usage of novel software and hardware technologies enforces the solution of tasks related to this problem. In addition, the lack of connectivity for large data throughput raises the demand for edge-computing-based solutions towards this goal. Therefore, in this work, we evaluate the opportunity of using a Wearable edge AI concept in a forest environment. For this matter, we propose a new approach to the hardware/software co-design process. We also address the possibility of creating wearable edge AI, where the wireless personal and body area networks are platforms for building applications using edge AI. Finally, we evaluate a case study to test the possibility of performing an edge AI task in a wearable-based environment. Thus, in this work, we evaluate the system to achieve the desired task, the hardware resource and performance, and the network latency associated with each part of the process. Through this work, we validated both the design pattern review and case study. In the case study, the developed algorithms could classify diseased leaves with a circa 90% accuracy with the proposed technique in the field. This results can be reviewed in the laboratory with more modern models that reached up to 96% global accuracy. The system could also perform the desired tasks with a quality factor of 0.95, considering the usage of three devices. Finally, it detected a disease epicenter with an offset of circa 0.5 m in a 6 m × 6 m × 12 m space. These results enforce the usage of the proposed methods in the targeted environment and the proposed changes in the co-design pattern. [ABSTRACT FROM AUTHOR]

Simple Summary: A subset of colorectal cancers (CRCs) is characterized by a mismatch repair deficiency that is frequently associated with microsatellite instability (MSI). The compromised DNA repair machinery leads to the accumulation of tumor neoantigens affecting the sensitivity of MSI metastatic CRC to immune checkpoint inhibitors (CPIs), both upfront and in later lines of treatment. However, up to 30% of MSI CRCs exhibit primary resistance to frontline immune based therapy, and an additional subset develops acquired resistance. Here, we first discuss the clinical and molecular features of MSI CRCs and then we review how the loss of antigenicity, immunogenicity, and a hostile tumor microenvironment could influence primary and acquired resistance to CPIs. Finally, we describe strategies to improve the outcome of MSI CRC patients upon CPI treatment. Immune checkpoint inhibitors (CPIs) represent an effective therapeutic strategy for several different types of solid tumors and are remarkably effective in mismatch repair deficient (MMRd) tumors, including colorectal cancer (CRC). The prevalent view is that the elevated and dynamic neoantigen burden associated with the mutator phenotype of MMRd fosters enhanced immune surveillance of these cancers. In addition, recent findings suggest that MMRd tumors have increased cytosolic DNA, which triggers the cGAS STING pathway, leading to interferon-mediated immune response. Unfortunately, approximately 30% of MMRd CRC exhibit primary resistance to CPIs, while a substantial fraction of tumors acquires resistance after an initial benefit. Profiling of clinical samples and preclinical studies suggests that alterations in the Wnt and the JAK-STAT signaling pathways are associated with refractoriness to CPIs. Intriguingly, mutations in the antigen presentation machinery, such as loss of MHC or Beta-2 microglobulin (B2M), are implicated in initial immune evasion but do not impair response to CPIs. In this review, we outline how understanding the mechanistic basis of immune evasion and CPI resistance in MMRd CRC provides the rationale for innovative strategies to increase the subset of patients benefiting from CPIs. [ABSTRACT FROM AUTHOR]

Simple Summary: Small cell lung cancer (SCLC) is an aggressive tumor, which can occur either de novo or from the histologic transformation of non-small cell lung cancer. Liquid biopsy has demonstrated its capability to detect, characterize and monitor different cancers. The aim of this systematic review was to assess the potential added value of liquid biopsy, in terms of circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs), in the management of SCLC, either de novo or transformed. We found ctDNA analysis as the most valuable and feasible technology to be integrated into clinical for disease monitoring (response, relapse, transformation) or for genomic profiling of SCLC, with a potential use also for prognostic stratification. CTCs hold a strong prognostic significance, as confirmed by our meta-analysis (even if potentially biased), but the heterogeneity of available data, the lack of agreed cut-offs, and the less affordable technology make CTCs more difficult to be integrated into present clinical practice. Background: The potential added value of liquid biopsy (LB) is not well determined in the case of small cell lung cancer (SCLC), an aggressive tumor that can occur either de novo or from the histologic transformation of non-small cell lung cancer (NSCLC). Methods: A systematic review of studies adopting LB in patients with SCLC have been performed to assess the clinical utility of circulating tumor DNA (ctDNA) or circulating tumor cells (CTCs). Results: After a screening of 728 records, 62 studies (32 evaluating CTCs, 27 ctDNA, and 3 both) met predetermined eligibility criteria. Only four studies evaluated LB in the diagnostic setting for SCLC, while its prognostic significance was evaluated in 38 studies and prominently supported by both ctDNA and CTCs. A meta-analysis of 11 studies as for CTCs enumeration showed an HR for overall survival of 2.63 (1.71–4.05), with a potential publication bias. The feasibility of tumor genomic profiling and the predictive role of LB in terms of response/resistance to chemotherapy was assessed in 11 and 24 studies, respectively, with greater consistency for those regarding ctDNA. Intriguingly, several case reports suggest that LB can indirectly capture the transition to SCLC in NSCLC treated with EGFR tyrosine kinase inhibitors. Conclusions: While dedicated trials are needed, LB holds potential clinical roles in both de novo and transformed SCLC. CtDNA analysis appears the most valuable and practicable tool for both disease monitoring and genomic profiling. [ABSTRACT FROM AUTHOR]

The Cdkn2a locus is one of the most studied tumor suppressor loci in the context of several cancer types. However, in the last years, its expression has also been linked to terminal differentiation and the activation of the senescence program in different cellular subtypes. Knock-out (KO) of the entire locus enhances the capability of stem cells to proliferate in some tissues and respond to severe physiological and non-physiological damages in different organs, including the heart. Emery–Dreifuss muscular dystrophy (EDMD) is characterized by severe contractures and muscle loss at the level of skeletal muscles of the elbows, ankles and neck, and by dilated cardiomyopathy. We have recently demonstrated, using the LMNA Δ8–11 murine model of Emery–Dreifuss muscular dystrophy (EDMD), that dystrophic muscle stem cells prematurely express non-lineage-specific genes early on during postnatal growth, leading to rapid exhaustion of the muscle stem cell pool. Knock-out of the Cdkn2a locus in EDMD dystrophic mice partially restores muscle stem cell properties. In the present study, we describe the cardiac phenotype of the LMNA Δ8–11 mouse model and functionally characterize the effects of KO of the Cdkn2a locus on heart functions and life expectancy. [ABSTRACT FROM AUTHOR]

Simple Summary: The BRAFV600E mutation accounts for 8–10% of metastatic colorectal cancer (mCRC) patients and it is an established prognostic factor. Median overall survival of this subset of patients is indeed so poor that it is similar to first line PFS of patients without this molecular alteration. An exception is represented by patients displaying concomitant MSI-H status who can benefit from immunotherapy with checkpoint inhibitors (CPIs). Recently, a targeted therapy with the combination of encorafenib and cetuximab provided for the first time a survival gain and thus translation in the clinic, even though acquired resistance limits the possibility of more than an incremental benefit. Many studies exploiting other different strategies are ongoing. In this review we present current therapies specifically headed to BRAFV600E mutant mCRC and systematically review ongoing clinical trials identifying different approaches under investigations: targeting MAPK pathway (monotherapy or combinations), targeting MAPK pathway combined with cytotoxic agents, intensive cytotoxic regimen combinations, targeted agents combined with CPIs, oxidative stress induction, and cytotoxic agents combined with antiangiogenic drugs and CPIs. The BRAFV600E mutation is found in 8–10% of metastatic colorectal cancer (mCRC) patients and it is recognized as a poor prognostic factor with a median overall survival inferior to 20 months. At present, besides immune checkpoint inhibitors (CPIs) for those tumors with concomitant MSI-H status, recommended treatment options include cytotoxic chemotherapy + anti-VEGF in the first line setting, and a combination of EGFR and a BRAF inhibitor (cetuximab plus encorafenib) in second line. However, even with the latter targeted approach, acquired resistance limits the possibility of more than an incremental benefit and survival is still dismal. In this review, we discuss current treatment options for this subset of patients and perform a systematic review of ongoing clinical trials. Overall, we identified six emerging strategies: targeting MAPK pathway (monotherapy or combinations), targeting MAPK pathway combined with cytotoxic agents, intensive cytotoxic regimen combinations, targeted agents combined with CPIs, oxidative stress induction, and cytotoxic agents combined with antiangiogenic drugs and CPIs. In the future, the integration of new therapeutic strategies targeting key players in the BRAFV600E oncogenic pathways with current treatment approach based on cytotoxic chemotherapy and surgery is likely to redefine the treatment landscape of these CRC patients. [ABSTRACT FROM AUTHOR]

Palbociclib, ribociclib, and abemaciclib belong to the third generation of cyclin-dependent kinases inhibitors (CDKis), an established therapeutic class for advanced and metastatic breast cancer. Interindividual variability in the therapeutic response of CDKis has been reported and some individuals may experience increased and unexpected toxicity. This narrative review aims at identifying the factors potentially concurring at this variability for driving the most appropriate and tailored use of CDKis in the clinic. Specifically, concomitant medications, pharmacogenetic profile, and pathophysiological conditions could influence absorption, distribution, metabolism, and elimination pharmacokinetics. A personalized therapeutic approach taking into consideration all factors potentially contributing to an altered pharmacokinetic/pharmacodynamic profile could better drive safe and effective clinical use. [ABSTRACT FROM AUTHOR]

Frequent and accurate inspections of industrial components and equipment are essential because failures can cause unscheduled downtimes, massive material, and financial losses or even endanger workers. In the mining industry, belt idlers or rollers are examples of such critical components. Although there are many precise laboratory techniques to assess the condition of a roller, companies still have trouble implementing a reliable and scalable procedure to inspect their field assets. This article enumerates and discusses the existing roller inspection techniques and presents a novel approach based on an Unmanned Aerial Vehicle (UAV) integrated with a thermal imaging camera. Our preliminary results indicate that using a signal processing technique, we are able to identify roller failures automatically. We also proposed and implemented a back-end platform that enables field and cloud connectivity with enterprise systems. Finally, we have also cataloged the anomalies detected during the extensive field tests in order to build a structured dataset that will allow for future experimentation. [ABSTRACT FROM AUTHOR]

Although many studies in the literature illustrate the numerous devices and methodologies nowadays existing for assessing the spatial variability within agricultural fields, and indicate the potential for variable-rate irrigation (VRI) in vineyards, only very few works deal with the implementation of VRI systems to manage such heterogeneity, and these studies are usually conducted in experimental fields for research aims. In this study, a VR drip irrigation system was designed for a 1-ha productive vineyard in Northern Italy and managed during the agricultural season 2018, to demonstrate feasibility and effectiveness of a water supply differentiated according to the spatial variability detected in field. Electrical resistivity maps obtained by means of an electro-magnetic induction sensor were used to detect four homogeneous zones with similar soil properties. In each zone, a soil profile was opened, and soil samples were taken and analyzed in laboratory. Two irrigation management zones (MZs) were identified by grouping homogeneous zones on the basis of their hydrological properties, and an irrigation prescription map was built consistently with the total available water (TAW) content in the root zone of the two MZs. The designed drip irrigation system consisted of three independent sectors: the first two supplied water to the two MZs, while the third sector (reference sector) was managed following the farmer's habits. During the season, irrigation in the first two sectors was fine-tuned using information provided by soil moisture probes installed in each sector. Results showed a reduction of water use by 18% compared to the 'reference' sector without losses in yield and product quality, and a grape's maturation more homogeneous in time. [ABSTRACT FROM AUTHOR]

In recent years, deep learning methods have outperformed previous state-of-the-art machine learning techniques for several problems, including image classification. Classifying cells in Pap smear images is very challenging, and it is still of paramount importance for cytopathologists. The Pap test is a cervical cancer prevention test that tracks preneoplastic changes in cervical epithelial cells. Carrying out this exam is important in that early detection. It is directly related to a greater chance of curing or reducing the number of deaths caused by the disease. The analysis of Pap smears is exhaustive and repetitive, as it is performed manually by cytopathologists. Therefore, a tool that assists cytopathologists is needed. This work considers 10 deep convolutional neural networks and proposes an ensemble of the three best architectures to classify cervical cancer upon cell nuclei and reduce the professionals' workload. The dataset used in the experiments is available in the Center for Recognition and Inspection of Cells (CRIC) Searchable Image Database. Considering the metrics of precision, recall, F1-score, accuracy, and sensitivity, the proposed ensemble improves previous methods shown in the literature for two- and three-class classification. We also introduce the six-class classification outcome.