The wide base bipedicled (WIBB) flap in nipple-sparing skin-reducing mastectomy.

In this article, we present a modification of the NS/SRM technique in which the mastopexy design for skin reduction is undertaken with a wide-base bipedicled (WIBB) flap. The WIBB flap can be applied in both autologous and implant-based breast reconstruction. Our reconstructive algorithm is also presented. The clinical data of patients operated on from June 2017 to November 2022 were collected: 51 patients for a total of 71 breasts. Personal data, BMI, type and volume of implants used, and major and minor complications were analyzed by descriptive statistics. The mean age was 48.3 years. BMI ranged between 21.5 and 30.9 kg/m2. Thirty-one patients underwent unilateral mastectomy, while twenty patients underwent bilateral surgery. In 25 breasts, immediate reconstruction was performed with implants and ADM. In 40 breasts, reconstruction was performed with a subpectoral tissue expander, and in 6 breasts, reconstruction was performed with a DIEP flap. We observed only one case (1.4%) of periprosthetic infection requiring implant removal under general anesthesia. Minor complications occurred in 14.1% of patients. The use of both the WIBB flap and our algorithm maintained a low complication rate in our series, ensuring oncological radicality and a good aesthetic result at the same time.

Molecular monitoring of viral infections in immunocompromised patients in a large university hospital in Italy: reflections after thirteen years of real-life activity.

PURPOSE: This study aimed to investigate the prevalence and viral reactivations of clinical interest in the immunocompromised patient with particular focus on hematologic and solid organ transplant recipients. METHODS: Molecular screening data of CMV, EBV, JCV and BKV from 2011 to 2023 were analyzed. This extensive time span allowed the access to more than 100,000 samples from over 20,000 patients treated at Policlinico Umberto I. It was possible to temporally investigate patient attendance patterns, average age distribution, seasonality of infections, and positivity rates of the analyzed viruses. RESULTS: Between 2019 and 2022 a significant reduction in organ transplants performed and in the positive molecular detection of EBV, JCV and BKV was observed. Additionally, there has been a noteworthy decrease in CMV reactivations, with a reduction of up to 50% starting in 2019. A remarkable reduction of 39% in the rate of CMV viral reactivation has been also achieved in SOT between 2016 and 2023. CONCLUSION: The years following 2019 were profoundly impacted by the COVID-19 pandemic era. This period resulted in a substantial reduction in healthcare services and hospital visits. Furthermore, the introduction of the drug Letermovir in Italy in 2019 demonstrated remarkable efficacy, evidenced by a reduction in CMV reactivations. Additionally, the adoption of a novel clinical approach centered on personalized therapy facilitated improved management of immunocompromised patients.

Adaptive introgression of a visual preference gene.

Visual preferences are important drivers of mate choice and sexual selection, but little is known of how they evolve at the genetic level. In this study, we took advantage of the diversity of bright warning patterns displayed by Heliconius butterflies, which are also used during mate choice. Combining behavioral, population genomic, and expression analyses, we show that two Heliconius species have evolved the same preferences for red patterns by exchanging genetic material through hybridization. Neural expression of regucalcin1 correlates with visual preference across populations, and disruption of regucalcin1 with CRISPR-Cas9 impairs courtship toward conspecific females, providing a direct link between gene and behavior. Our results support a role for hybridization during behavioral evolution and show how visually guided behaviors contributing to adaptation and speciation are encoded within the genome.

Feasibility of proton dosimetry overriding planning CT with daily CBCT elaborated through generative artificial intelligence tools.

Radiotherapy commonly utilizes cone beam computed tomography (CBCT) for patient positioning and treatment monitoring. CBCT is deemed to be secure for patients, making it suitable for the delivery of fractional doses. However, limitations such as a narrow field of view, beam hardening, scattered radiation artifacts, and variability in pixel intensity hinder the direct use of raw CBCT for dose recalculation during treatment. To address this issue, reliable correction techniques are necessary to remove artifacts and remap pixel intensity into Hounsfield Units (HU) values. This study proposes a deep-learning framework for calibrating CBCT images acquired with narrow field of view (FOV) systems and demonstrates its potential use in proton treatment planning updates. Cycle-consistent generative adversarial networks (cGAN) processes raw CBCT to reduce scatter and remap HU. Monte Carlo simulation is used to generate CBCT scans, enabling the possibility to focus solely on the algorithm's ability to reduce artifacts and cupping effects without considering intra-patient longitudinal variability and producing a fair comparison between planning CT (pCT) and calibrated CBCT dosimetry. To showcase the viability of the approach using real-world data, experiments were also conducted using real CBCT. Tests were performed on a publicly available dataset of 40 patients who received ablative radiation therapy for pancreatic cancer. The simulated CBCT calibration led to a difference in proton dosimetry of less than 2%, compared to the planning CT. The potential toxicity effect on the organs at risk decreased from about 50% (uncalibrated) up the 2% (calibrated). The gamma pass rate at 3%/2 mm produced an improvement of about 37% in replicating the prescribed dose before and after calibration (53.78% vs 90.26%). Real data also confirmed this with slightly inferior performances for the same criteria (65.36% vs 87.20%). These results may confirm that generative artificial intelligence brings the use of narrow FOV CBCT scans incrementally closer to clinical translation in proton therapy planning updates.

Mixed Reality and Artificial Intelligence: A Holistic Approach to Multimodal Visualization and Extended Interaction in Knee Osteotomy.

OBJECTIVE: Recent advancements in augmented reality led to planning and navigation systems for orthopedic surgery. However little is known about mixed reality (MR) in orthopedics. Furthermore, artificial intelligence (AI) has the potential to boost the capabilities of MR by enabling automation and personalization. The purpose of this work is to assess Holoknee prototype, based on AI and MR for multimodal data visualization and surgical planning in knee osteotomy, developed to run on the HoloLens 2 headset. METHODS: Two preclinical test sessions were performed with 11 participants (eight surgeons, two residents, and one medical student) executing three times six tasks, corresponding to a number of holographic data interactions and preoperative planning steps. At the end of each session, participants answered a questionnaire on user perception and usability. RESULTS: During the second trial, the participants were faster in all tasks than in the first one, while in the third one, the time of execution decreased only for two tasks ("Patient selection" and "Scrolling through radiograph") with respect to the second attempt, but without statistically significant difference (respectively [Formula: see text] = 0.14 and [Formula: see text] = 0.13, [Formula: see text]). All subjects strongly agreed that MR can be used effectively for surgical training, whereas 10 (90.9%) strongly agreed that it can be used effectively for preoperative planning. Six (54.5%) agreed and two of them (18.2%) strongly agreed that it can be used effectively for intraoperative guidance. DISCUSSION/CONCLUSION: In this work, we presented Holoknee, the first holistic application of AI and MR for surgical planning for knee osteotomy. It reported promising results on its potential translation to surgical training, preoperative planning, and surgical guidance. Clinical and Translational Impact Statement - Holoknee can be helpful to support surgeons in the preoperative planning of knee osteotomy. It has the potential to impact positively the training of the future generation of residents and aid surgeons in the intraoperative stage.

Multidisciplinary monitoring of an in-situ remediation test of chlorinated solvents.

Pollutions on and within the underground poses risks for groundwater contamination and is a widespread global problem. Common remediation methods based on digging and removal can be expensive and have limitations, while in-situ remediation is an attractive alternative. However, there is a need to develop tools to monitor the effectiveness both in terms of the successful injection of remediation fluids but also the effectiveness of the treatment, i.e., degree of degradation/removal of the pollutants and possible metabolites. This paper presents a methodology for monitoring the changes following an in-situ remediation treatment of a site contaminated with chlorinated solvents. The methodology consists of two different methods, where Direct Current resistivity and time-domain Induced Polarization (DCIP) was used to acquire daily data and geochemical analyses on water samples were collected approximately every three months. The geophysical results provide insights on how the injected fluids are spreading and assist in acquiring a better understanding of the geological and hydrogeological system. On the other hand, the geochemical sampling enhances our knowledge about the hydrochemistry of the system and the concentration of the pollutants. Our research highlights the challenges of monitoring in-situ bioremediation experiments in complex environments and in cases where pollutants are situated in low hydraulic conductivity formations. The joint interpretation of the data shows the importance of an interdisciplinary approach to understand complex systems.

Soft tissue reconstruction of the trunk with pedicled perforator and musculocutaneous flaps: A single-center comparative retrospective study.

BACKGROUND: Soft tissue trunk reconstruction is often challenging. Although free microvascular flaps are a feasible option in case of extensive defects involving deep structures, pedicled flaps represent a good alternative, especially if harvested and dissected with a "microsurgical" approach. The aim of this study is to evaluate the feasibility of trunk reconstruction with the use of pedicled flaps, according to the application of our reconstructive algorithm, and to compare it to other reconstructive methods. PATIENTS AND METHODS: From January 2017 to December 2021, we retrospectively analyzed patients who underwent soft tissue reconstruction of the trunk with pedicled flaps at the authors' institution. Patient's demographic, clinical and surgical characteristics and postoperative complications were recorded and analyzed by descriptive statistics. A comparative analysis was made between the study group and two other groups who underwent reconstruction of trunk defects with free flaps and skin grafts, respectively, at the authors' institution. RESULTS: Forty-seven patients were included in the study. Patients' age ranged between 36 and 82 years (mean: 57.8 years). Twenty-eight patients were male, while 19 patients were female. In 76.6% of patients (36 out of 47), reconstructive procedures were performed to repair defects resulting from cancer resection. Reconstruction of superficial defects was always achieved with perforator flaps (n = 25). In case of full-thickness defects, reconstruction was carried out with musculocutaneous flaps (n = 22); latissimus dorsi and vastus lateralis were the most used flaps for chest and abdominal wall reconstruction, respectively. In our series, we observed only one case of total flap loss requiring re-operation under general anesthesia. Minor complications occurred in 8.5% of cases (4 out of 47 patients). We observed two cases of partial flap necrosis and two cases of wound dehiscence. In the skin grafts group (n = 53), the mean age was 54.5 years (range 39-85) and 56% of patients were male (n = 30). In 66% of cases (n = 30) the defect resulted from oncological resection. The overall complication rate was 18.8% (n = 10). In the free flaps group (n = 10), the mean age was 49.0 years (range 29-77) and 60% of patients (n = 6) were male. In 70% of cases (n = 7) the defect was caused by oncological resection. Complications occurred in two patients (20%). No statistically significant differences were found in terms of overall complication rate between the study group and the two comparative groups (p = .48). A significant correlation was found between the reconstructive method and the type and size of the defect, with reconstruction through free flaps being associated with larger (344.0 vs. 220.4 cm2 ) (p = .04) and full-thickness defects (80.0% vs. 46.8%) (p < .01) if compared to pedicled flaps. CONCLUSIONS: In the new era of microsurgery, pedicled flaps represent a valid alternative to free flaps for the majority of soft tissue defects of the trunk. In our series, no statistically significant differences in terms of complications were found between reconstructions of similar defects achieved with pedicled and free flaps, and free flap use was limited to extensive full-thickness defects. In addition, the rate of postoperative complications with pedicled flaps found in our cohort was lower than the rate reported in the literature.

Genetics and the Evolution of Prezygotic Isolation.

The significance of prezygotic isolation for speciation has been recognized at least since the Modern Synthesis. However, fundamental questions remain. For example, how are genetic associations between traits that contribute to prezygotic isolation maintained? What is the source of genetic variation underlying the evolution of these traits? And how do prezygotic barriers affect patterns of gene flow? We address these questions by reviewing genetic features shared across plants and animals that influence prezygotic isolation. Emerging technologies increasingly enable the identification and functional characterization of the genes involved, allowing us to test established theoretical expectations. Embedding these genes in their developmental context will allow further predictions about what constrains the evolution of prezygotic isolation. Ongoing improvements in statistical and computational tools will reveal how pre- and postzygotic isolation may differ in how they influence gene flow across the genome. Finally, we highlight opportunities for progress by combining theory with appropriate data.

Combined Edge Loss UNet for Optimized Segmentation in Total Knee Arthroplasty Preoperative Planning.

Bone segmentation and 3D reconstruction are crucial for total knee arthroplasty (TKA) surgical planning with Personalized Surgical Instruments (PSIs). Traditional semi-automatic approaches are time-consuming and operator-dependent, although they provide reliable outcomes. Moreover, the recent expansion of artificial intelligence (AI) tools towards various medical domains is transforming modern healthcare. Accordingly, this study introduces an automated AI-based pipeline to replace the current operator-based tibia and femur 3D reconstruction procedure enhancing TKA preoperative planning. Leveraging an 822 CT image dataset, a novel patch-based method and an improved segmentation label generation algorithm were coupled to a Combined Edge Loss UNet (CEL-UNet), a novel CNN architecture featuring an additional decoding branch to boost the bone boundary segmentation. Root Mean Squared Errors and Hausdorff distances compared the predicted surfaces to the reference bones showing median and interquartile values of 0.26 (0.19-0.36) mm and 0.24 (0.18-0.32) mm, and of 1.06 (0.73-2.15) mm and 1.43 (0.82-2.86) mm for the tibia and femur, respectively, outperforming previous results of our group, state-of-the-art, and UNet models. A feasibility analysis for a PSI-based surgical plan revealed sub-millimetric distance errors and sub-angular alignment uncertainties in the PSI contact areas and the two cutting planes. Finally, operational environment testing underscored the pipeline's efficiency. More than half of the processed cases complied with the PSI prototyping requirements, reducing the overall time from 35 min to 13.1 s, while the remaining ones underwent a manual refinement step to achieve such PSI requirements, performing the procedure four to eleven times faster than the manufacturer standards. To conclude, this research advocates the need for real-world applicability and optimization of AI solutions in orthopedic surgical practice.

Efficient shRNA-based knockdown of multiple target genes for cell therapy using a chimeric miRNA cluster platform.

Genome engineering technologies are powerful tools in cell-based immunotherapy to optimize or fine-tune cell functionalities. However, their use for multiple gene edits poses relevant biological and technical challenges. Short hairpin RNA (shRNA)-based cell engineering bypasses these criticalities and represents a valid alternative to CRISPR-based gene editing. Here, we describe a microRNA (miRNA)-based multiplex shRNA platform obtained by combining highly efficient miRNA scaffolds into a chimeric cluster, to deliver up to four shRNA-like sequences. Thanks to its limited size, our cassette could be deployed in a one-step process along with all the CAR components, streamlining the generation of engineered CAR T cells. The plug-and-play design of the shRNA platform allowed us to swap each shRNA-derived guide sequence without affecting the system performance. Appropriately choosing the target sequences, we were able to either achieve a functional KO, or fine-tune the expression levels of the target genes, all without the need for gene editing. Through our strategy we achieved easy, safe, efficient, and tunable modulation of multiple target genes simultaneously. This approach allows for the effective introduction of multiple functionally relevant tweaks in the transcriptome of the engineered cells, which may lead to increased performance in challenging environments, e.g., solid tumors.

A new system for in-room image guidance in particle therapy at CNAO.

This paper describes the design, installation, and commissioning of an in-room imaging device developed at the Centro Nazionale di Adroterapia Oncologica (CNAO, Pavia, Italy). The system is an upgraded version of the one previously installed in 2014, and its design accounted for the experience gained in a decade of clinical practice of patient setup verification and correction through robotic-supported, off-isocenter in-room image guidance. The system's basic feature consists of image-based setup correction through 2D/3D and 3D/3D registration through a dedicated HW/SW platform. The major update with respect to the device already under clinical usage resides in the implementation of a functionality for extending the field of view of the reconstructed Cone Beam CT (CBCT) volume, along with improved overall safety and functional optimization. We report here details on the procedures implemented for system calibration under all imaging modalities and the results of the technical and preclinical commissioning of the device performed on two different phantoms. In the technical commissioning, specific attention was given to the assessment of the accuracy with which the six-degrees-of-freedom correction vector computed at the off-isocenter imaging position was propagated to the planned isocentric irradiation geometry. During the preclinical commissioning, the entire clinical-like procedure for detecting and correcting imposed, known setup deviation was tested on an anthropomorphic radioequivalent phantom. Results showed system performance within the sub-millimeter and sub-degree range according to project specifications under each imaging modality, making it ready for clinical application.

Frizzled2 receives WntA signaling during butterfly wing pattern formation.

Butterfly color patterns provide visible and biodiverse phenotypic readouts of the patterning processes. Although the secreted ligand WntA has been shown to instruct the color pattern formation in butterflies, its mode of reception remains elusive. Butterfly genomes encode four homologs of the Frizzled-family of Wnt receptors. Here, we show that CRISPR mosaic knockouts of frizzled2 (fz2) phenocopy the color pattern effects of WntA loss of function in multiple nymphalids. Whereas WntA mosaic clones result in intermediate patterns of reduced size, fz2 clones are cell-autonomous, consistent with a morphogen function. Shifts in expression of WntA and fz2 in WntA crispant pupae show that they are under positive and negative feedback, respectively. Fz1 is required for Wnt-independent planar cell polarity in the wing epithelium. Fz3 and Fz4 show phenotypes consistent with Wnt competitive-antagonist functions in vein formation (Fz3 and Fz4), wing margin specification (Fz3), and color patterning in the Discalis and Marginal Band Systems (Fz4). Overall, these data show that the WntA/Frizzled2 morphogen-receptor pair forms a signaling axis that instructs butterfly color patterning and shed light on the functional diversity of insect Frizzled receptors.

Latissimus Dorsi Flap and Thoracodorsal Artery Perforator Flap with Immediate Fat Transfer (LIFT and TIFT): A Retrospective Study about Total Breast Reconstruction in High-Risk Patients.

INTRODUCTION: Microsurgical breast reconstruction has become popular over the past twenty years and allows a tailor-tuck approach to each patient. However, smoking or coagulation disorders may switch surgeon's choice towards alternative options. When facing these risk factors, we performed pedicled latissimus dorsi (LD) flap and thoracodorsal artery perforator (TDAP) flap reconstruction with immediate fat transfer (LIFT and TIFT), achieving satisfactory surgical outcomes. Hence, we aim to present our seven-years case-series and discuss our decisional algorithm. MATERIALS AND METHODS: Thirty smoker women and seven women affected by coagulation disorder (n = 37) respectively had LIFT and TIFT surgery and were retrospectively evaluated. Patients' demographics and outcomes were recorded and compared. RESULTS: LIFT patients received higher volumes of immediate fat grafting compared to TIFT patients (p < 0.05), which required additional lipofilling to provide adequate volume amount, since the TDAP flap was not immediately grafted. However, the additional lipofilling procedures and fat volume were similar (p > 0.05). Flap survival reached 100%, and flap necrosis or loss did not occur. Few minor complications were evidenced in the LIFT group only (p > 0.05). CONCLUSION: Based on our experience, we support the reliability of pedicled LD and TDAP flaps with immediate fat transfer in breast reconstruction as valuable alternative to microsurgery in smokers (LIFT) and patients with coagulation disorders (TIFT). However, the results of our study are not conclusive since still must be clarified the role of the smoking and coagulation disorders in microsurgery and the real benefit of a non-microsurgical procedure. LEVEL OF EVIDENCE IV: Opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Implant-Based Breast Reconstruction after Risk-Reducing Mastectomy in BRCA Mutation Carriers: A Single-Center Retrospective Study.

Women with BRCA gene mutations have a higher lifetime risk of developing breast cancer. Furthermore, cancer is usually diagnosed at a younger age compared to the wild-type counterpart. Strategies for risk management include intensive surveillance or risk-reducing mastectomy. The latter provides a significant reduction of the risk of developing breast cancer, simultaneously ensuring a natural breast appearance due to the preservation of the skin envelope and the nipple-areola complex. Implant-based breast reconstruction is the most common technique after risk-reducing surgery and can be achieved with either a submuscular or a prepectoral approach, in one or multiple stages. This study analyzes the outcomes of the different reconstructive techniques through a retrospective review on 46 breasts of a consecutive, single-center case series. Data analysis was carried out with EpiInfo version 7.2. Results of this study show no significant differences in postoperative complications between two-stage tissue expander/implant reconstruction and direct-to-implant (DTI) reconstruction, with DTI having superior aesthetic outcomes, especially in the prepectoral subgroup. In our experience, the DTI prepectoral approach has proven to be a safe and less time-consuming alternative to the submuscular two-stage technique, providing a pleasant reconstructed breast and overcoming the drawbacks of subpectoral implant placement.

Link Prediction with Continuous-Time Classical and Quantum Walks.

Protein-protein interaction (PPI) networks consist of the physical and/or functional interactions between the proteins of an organism, and they form the basis for the field of network medicine. Since the biophysical and high-throughput methods used to form PPI networks are expensive, time-consuming, and often contain inaccuracies, the resulting networks are usually incomplete. In order to infer missing interactions in these networks, we propose a novel class of link prediction methods based on continuous-time classical and quantum walks. In the case of quantum walks, we examine the usage of both the network adjacency and Laplacian matrices for specifying the walk dynamics. We define a score function based on the corresponding transition probabilities and perform tests on six real-world PPI datasets. Our results show that continuous-time classical random walks and quantum walks using the network adjacency matrix can successfully predict missing protein-protein interactions, with performance rivalling the state-of-the-art.

Risk of ileocolic anastomosis failure after right hemicolectomy for cancer. A comparison between different techniques.

BACKGROUND: In recent years, the role of laparoscopic approach in the surgical treatment of right colon cancer has increased. Results comparing the different techniques of ileocolic anastomoses are controversial, with studies only reporting some advantages of the intracorporeal laparoscopic technique. The aim of this study is to compare the outcomes between laparoscopic versus open hemicolectomy for right colon cancer, focusing on anastomotic techniques (intracorporeal vs extracorporeal in the laparoscopic procedure, and manual vs mechanical in the laparotomic procedure). METHODS: This is a retrospective single center study enrolling patients with right colon cancer from January 2016 to December 2020. Primary endpoint of the study was the rate of anastomotic leak (AL). RESULTS: A total of 161 patients who underwent right hemicolectomy were enrolled: 91 were performed with laparoscopic technique, and 70 with open technique. Overall, AL occurred in 15 pts (9.3%). We observed 4 AL in intracorporeal (12.9%) and 6 in extracorporeal (10%) anastomoses, respectively. In the laparotomy group 5 patients (7.1%) developed AL, of which 3 (5.7%) and 2 (11.1%) manually and mechanically performed, respectively. CONCLUSIONS: Based on our findings, laparoscopic hemicolectomy has a higher incidence of anastomotic leak. In the laparoscopic group, we observed the lowest rate of AL with extracorporeal mechanical anastomosis. When performed extracorporeally with open technique, hand-sewn anastomosis has better results than mechanical. KEY WORDS: Anastomosis, Cancer, Ileotransverse, Leakage, Right Colectomy.

SLEEP-SEE-THROUGH: Explainable Deep Learning for Sleep Event Detection and Quantification From Wearable Somnography.

Evidence is rapidly accumulating that multifactorial nocturnal monitoring, through the coupling of wearable devices and deep learning, may be disruptive for early diagnosis and assessment of sleep disorders. In this work, optical, differential air-pressure and acceleration signals, acquired by a chest-worn sensor, are elaborated into five somnographic-like signals, which are then used to feed a deep network. This addresses a three-fold classification problem to predict the overall signal quality (normal, corrupted), three breathing-related patterns (normal, apnea, irregular) and three sleep-related patterns (normal, snoring, noise). In order to promote explainability, the developed architecture generates additional information in the form of qualitative (saliency maps) and quantitative (confidence indices) data, which helps to improve the interpretation of the predictions. Twenty healthy subjects enrolled in this study were monitored overnight for approximately ten hours during sleep. Somnographic-like signals were manually labeled according to the three class sets to build the training dataset. Both record- and subject-wise analyses were performed to evaluate the prediction performance and the coherence of the results. The network was accurate (0.96) in distinguishing normal from corrupted signals. Breathing patterns were predicted with higher accuracy (0.93) than sleep patterns (0.76). The prediction of irregular breathing was less accurate (0.88) than that of apnea (0.97). In the sleep pattern set, the distinction between snoring (0.73) and noise events (0.61) was less effective. The confidence index associated with the prediction allowed us to elucidate ambiguous predictions better. The saliency map analysis provided useful insights to relate predictions to the input signal content. While preliminary, this work supported the recent perspective on the use of deep learning to detect particular sleep events in multiple somnographic signals, thus representing a step towards bringing the use of AI-based tools for sleep disorder detection incrementally closer to clinical translation.

CEL-Unet: a novel CNN architecture for 3D Segmentation of Knee Bones affected by Severe Osteoarthritis for PSI-Based Surgical Planning.

Unet architectures are promising deep learning networks exploited to perform the automatic segmentation of bone CT images, in line with their ability to deal with pathological deformations and size-varying anatomies. However, bone degeneration, like the development of irregular osteophytes as well as mineral density alterations might interfere with this automated process and demand extensive manual refinement. The aim of this work is to implement an innovative Unet variant, the CEL-Unet, to improve the femur and tibia segmentation outcomes in osteoarthritic knee joints. In this network the decoding path is split into a region and contour-aware branch to increase the prediction reliability in such pathological conditions. The comparison between the segmentation results achieved with a standard Unet and its novel variant (CEL-Unet) was performed as follows: the Unet was trained with 5 different loss functions: Dice Loss, Focal Loss, Exponential Logarithmic Loss, Double Cross Entropy Loss and Distanced Cross Entropy loss. The CEL-Unet was instead trained with two loss functions, one for each of the network outputs, namely Mask and Edge, yielding the so-called Combined Edge Loss (CEL) function. A set of 259 knee CT scans was used to train the model and test segmentation performance. The CEL-Unet outperformed all other Unet-based models, reaching the highest Jaccard values of about 0.97 and 0.96 on femur and tibia, respectively. Clinical Relevance- With the increasing rate of Total Knee Arthoplasty deep learning-based methods can achieve fast accurate and automatic 3D segmentation of the knee joint bones to enhance new costumized pre-operative planning.

Leishmania guyanensis suppressed inducible nitric oxide synthase provoked by its viral endosymbiont.

Inducible nitric oxide synthase (iNOS) is essential to the production of nitric oxide (NO), an efficient effector molecule against intracellular human pathogens such as Leishmania protozoan parasites. Some strains of Leishmania are known to bear a viral endosymbiont termed Leishmania RNA virus 1 (LRV1). Recognition of LRV1 by the innate immune sensor Toll-like receptor-3 (TLR3) leads to conditions worsening the disease severity in mice. This process is governed by type I interferon (type I IFNs) arising downstream of TLR3 stimulation and favoring the formation of secondary metastatic lesions. The formation of these lesions is mediated by the inflammatory cytokine IL-17A and occurs in the absence, or low level of, protective cytokine IFN-γ. Here, we described that the presence of LRV1 led to the initial expression of iNOS and low production of NO that failed to control infection. We subsequently showed that LRV1-triggered type I IFN was essential but insufficient to induce robust iNOS induction, which requires strong activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB). Leishmania guyanensis carrying LRV1 (LgyLRV1+) parasites mitigated strong iNOS production by limiting NF-kB activation via the induction of tumor necrosis factor-alpha-induced protein 3 (TNFAIP3), also known as A20. Moreover, our data suggested that production of LRV1-induced iNOS could be correlated with parasite dissemination and metastasis via elevated secretion of IL-17A in the draining lymph nodes. Our findings support an additional strategy by which LRV1-bearing Leishmania guyanensis evaded killing by nitric oxide and suggest that low levels of LRV1-induced NO might contribute to parasite metastasis.