Reverse Mapping Research Articles

BMISP: Bidirectional mapping of image signal processing pipeline

After being processed by the image signal processing (ISP) pipeline in digital cameras, the sRGB images are nonlinear, and thus are not suitable for the computer vision tasks which work best in a linear color space. Therefore, mapping nonlinear sRGB images back to a linear color space is a highly valuable task. To achieve an accurate mapping, this paper proposes a framework based on convolutional neural networks, which models the ISP pipeline in both reverse and forward directions. In particular, for the reverse mapping, a U-net structure is applied to extract features from a given sRGB image, and the extracted features are utilized to estimate the linear and nonlinear transformations in the ISP pipeline. For the forward mapping, the original sRGB image is used as a guidance to embed the camera-style information. To incorporate the encoded prior knowledge, affine transformations are employed to modulate the features. Experiments demonstrate that the proposed framework is able to achieve the state-of-the-art performance.

Reliable Location of Upper Extremity Lymphatic Channels for Use in Immediate Lymphatic Reconstruction.

Breast cancer-related lymphedema (BCRL) is a limiting sequelae of breast cancer treatment that may negatively impact 30% to 50% of high-risk breast cancer survivors. Risk factors for development of BCRL include axillary lymph node dissection (ALND), and recently, axillary reverse lymphatic mapping and immediate lymphovenous reconstruction (ILR) at time of ALND have been implemented to prevent BCRL. Reliable anatomy of neighboring venules has been commented on in the literature; however, little information exists about anatomical location of local lymphatic channels amenable for bypass. After institutional review board approval, patients who underwent ALND with axillary reverse lymphatic mapping and ILR at a tertiary cancer center from November 2021 to August 2022 were applicable for this study. The location and number of lymphatic channels used for ILR were identified and measured intraoperatively with the arm abducted to 90 degrees and soft tissue under no tension. Four measurements were taken to localize each lymphatic and were based on relationship with reliable anatomic landmarks including 4th rib, anterior axillary line, and lower border of the pectoralis major muscle. Demographics, oncologic treatments, intraoperative factors, and outcomes were prospectively maintained. Twenty-seven patients met inclusion for this study by August 2022 with a total of 86 lymphatic channels identified. Patients were on average 50 ± 12 years old with a body mass index of 30 ± 6 and had an average of 1 vein and 3 identifiable lymphatic channels amenable to bypass. Seventy percent of lymphatic channels were found in a cluster of 2 or more channels. The average horizontal location was 4.5 ± 1.4 cm lateral to the 4th rib. The average vertical location was 1.3 ± 0.9 cm from the superior border of the 4th rib. These data comment upon intraoperatively identified and consistent location of upper extremity lymphatic channels used for ILR. These lymphatic channels are often found in clusters with 2 or more lymphatic channels at the same location. Such insight may aid in easier intraoperative identification of amenable vessels for the unexperienced surgeon, decrease in intraoperative time, and higher success of ILR.

Reversible Mapping of Relational and Graph Databases

Reversible Mapping of Relational and Graph Databases

The involvement of axillary reverse mapping nodes in patients with node-positive breast cancer

IntroductionAxillary reverse mapping (ARM) procedure is useful in reducing lymphedema. However, concerns regarding oncologic safety have limited the adoption of the ARM procedure. This study aimed to evaluate the involvement of ARM nodes in node-positive breast cancer patients. Materials and methodsTwo hundred twenty-three node-positive patients were enrolled in this study: 90 were clinically node-negative, but had one or more positive sentinel lymph nodes (SLNs) (SLN-positive group); 68 were clinicopathologically node-positive (CpN-positive group); and 65 had confirmed nodal involvement and received neoadjuvant chemotherapy (NAC) (NAC group). All patients underwent axillary lymph node dissection with fluorescent ARM. ResultsARM nodes were involved in 33 (36.7%) patients of the SLN-group. Residual ARM nodes after SLN biopsy were involved in 11 patients (12.2%), including 5 patients (19.2%) with crossover type nodes and 6 patients (9.4%) with non-crossover type nodes. However, the difference in involvement rates between the two types was not high enough to be significant. Of these 11 patients, moreover, four patients had three or more than 3 involved SLNs. On the other hand, the involvement rate of ARM nodes in the NAC group was significantly lower than that of the CpN-positive group (35.4% vs. 64.7%: p < 0.01). Despite lower involvement, the risk of metastases in the ARM nodes was still too high to spare ARM nodes in both the NAC group and CpN-positive group. ConclusionsSuspicious or involved ARM nodes should be removed even when detected in ARM procedure, particularly in NAC-group and CpN-positive-group patients.

Axillary reverse mapping in breast cancer: Anoverview.

Standard operative management for breast carcinoma has significantly shifted from extensive procedures to minor interventions.Although axillary dissection was a fundamental component of operative management, sentinel biopsy is an actual process for axillary staging. Axillary dissection may be postponed for cases that have negative SLNs or 1 or 2 infiltrated lymph nodes undergoing breast or axillary radiation. Contrarily, axillary dissection is still the conventional management for patients with clinically positive nodes.Arm lymphedema is a frequent and overwhelming complication of axillary dissection, with a worse impact on the patient's life.Axillary reverse mapping was recently introduced to map and conserve the lymph drain of the upper limb throughout axillary dissection or sentinel biopsy. A technique based on the theory that the breast's lymphatic drainage differs from those that drain the arm, so preserving lymphatic drainage of the upper limb can prevent lymphedema, thereby not raising the risk of axillary recurrence.Therefore, this technique is the reverse of sentinel biopsy, which remove the lymph nodes that drain the breast.

State retrieval beyond Bayes&amp;apos; retrodiction

In the context of irreversible dynamics, associating to a physical process its intuitive reverse can result to be a quite ambiguous task. It is a standard choice to define the reverse process using Bayes&amp;apos; theorem, but, in general, this choice is not optimal. In this work we explore whether it is possible to characterise an optimal reverse map building from the concept of state retrieval maps. In doing so, we propose a set of principles that state retrieval maps should satisfy. We find out that the Bayes inspired reverse is just one case in a whole class of possible choices, which can be optimised to give a map retrieving the initial state more precisely than the Bayes rule. Our analysis has the advantage of naturally extending to the quantum regime. In fact, we find a class of reverse transformations containing the Petz recovery map as a particular case, corroborating its interpretation as quantum analogue of the Bayes retrieval. Finally, we present numerical evidences that by adding a single extra axiom one can isolate the usual reverse process derived from Bayes&amp;apos; theorem.

BLA2C2: Design of a Novel Blockchain-based Light-Weight Authentication &amp; Access Control Layer for Cloud Deployments

Cloud deployments are consistently under attack, from both internal and external adversaries. These attacks include, but are not limited to brute force, masquerading, improper access, session hijacking, cross site scripting (XSS), etc. To mitigate these attacks, a wide variety of authentication &amp; access control models are proposed by researchers, and each of them vary in terms of their internal implementation characteristics. It was observed that these models are either highly complex, or lack in terms of security under multiple attacks, which limits their applicability for real-time deployments. Moreover, some of these models are not flexible and cannot be deployed under dynamic cloud scenarios (like constant reconfigurations of Virtual Machines, dynamic authentication use-cases, etc.). To overcome these issues, this text proposes design of a novel blockchain-based Light-weight authentication &amp; access control layer that can be used for dynamic cloud deployments. The proposed model initially applies a header-level light-weight sanitization layer that removes Cross Site Scripting, SQL Injection, and other data-level attacks. This is followed by a light-weight authentication layer, that assists in improving login-level security for external attacks. The authentication layer uses IP matching with reverse geolocation mapping in order to estimate outlier login attempts. This layer is cascaded with an efficient blockchain-based access control model, which assists in mitigating session hijacking, masquerading, sybil and other control-level attacks. The blockchain model is developed via integration of Grey Wolf Optimization (GWO) to reduce unnecessary complexities, and provides faster response when compared with existing blockchain-based security deployments. Efficiency of the model was estimated in terms of accuracy of detection for different attack types, delay needed for detection of these attacks, and computational complexity during attack mitigation operations. This performance was compared with existing models, and it was observed that the proposed model showcases 8.3% higher accuracy, with 10.5% lower delay, and 5.9% lower complexity w.r.t. standard blockchain-based &amp; other security models. Due to these enhancements, the proposed model was capable of deployment for a wide variety of large-scale scenarios.

Tracking talker-specific cues to lexical stress: Evidence from perceptual learning.

When recognizing spoken words, listeners are confronted by variability in the speech signal caused by talker differences. Previous research has focused on segmental talker variability; less is known about how suprasegmental variability is handled. Here we investigated the use of perceptual learning to deal with between-talker differences in lexical stress. Two groups of participants heard Dutch minimal stress pairs (e.g., VOORnaam vs. voorNAAM, "first name" vs. "respectable") spoken by two male talkers. Group 1 heard Talker 1 use only F0 to signal stress (intensity and duration values were ambiguous), while Talker 2 used only intensity (F0 and duration were ambiguous). Group 2 heard the reverse talker-cue mappings. After training, participants were tested on words from both talkers containing conflicting stress cues ("mixed items"; e.g., one spoken by Talker 1 with F0 signaling initial stress and intensity signaling final stress). We found that listeners used previously learned information about which talker used which cue to interpret the mixed items. For example, the mixed item described above tended to be interpreted as having initial stress by Group 1 but as having final stress by Group 2. This demonstrates that listeners learn how individual talkers signal stress and use that knowledge in spoken-word recognition. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Expensive Multiobjective Optimization Based on Information Transfer Surrogate

Objective value estimation based on computationally efficient surrogate models is widely used to reduce the computational cost in solving expensive multiobjective optimization problems (MOPs). However, due to the scarcity of training data and the lack of data sharing between training tasks in a surrogate-based system, the estimation effectiveness of the surrogate models might not be satisfactory. In this study, we present a novel surrogate methodology based on information transfer to deal with this problem. Particularly, in the proposed framework, the objectives of an MOP that may have little apparent similarity or correlation are linearly mapped to a number of related tasks. Afterward, the related tasks are used to train a multitask Gaussian process (MTGP). MTGP expands the training data leading to more confident learning of the parameters of the model. The predicted values of the objective functions can be obtained by a reverse mapping from the learned MTGP model. In this way, the computational burden of the expensive objective functions of an MOP can be substantially reduced while maintaining good estimation accuracy. MTGP facilitates mutual information transfer across tasks, avoids learning from scratch for new tasks, and captures the underlying structural information between tasks. The proposed surrogate approach is merged into MOEA/D to address MOPs. Experimental tests under various scenarios indicate that the resultant algorithm outperforms other state-of-the-art surrogate-based multiobjective optimization algorithms.

Assessing the preventive effect of immediate lymphatic reconstruction on the upper extremity lymphedema.

An immediate lymphatic reconstruction (ILR) combining axillary reverse lymphatic mapping (ARLM) and lymphovenous anastomosis (LVA) has been gradually in the spotlight as a novel surgical technique to prevent lymphedema. In this study, we investigate the preventive effect of ILR for the risk of upper extremity lymphedema. We will compare the incidence of postoperative lymphedema between the ILR treatment group and the no-try or failure group during the same period with analysis of the effects of different variables. In this retrospective cohort study, we analyzed 213 patients who had undergone mastectomy for node-positive unilateral breast cancer in our institution between November 1, 2019 and February 28, 2021. To assess the effect of preventive ILR, we divided the patients into a treatment group (n=30) and a control group (n=183). Univariate and multivariate Cox proportional hazards regression models were used to evaluate the association between ILR and lymphedema occurrence. Of the 30 patients who were attempted, we successfully performed ILRs in 26 patients (86.7%). During a mean follow-up of 14 months, one patient (3.8%) was confirmed to have upper extremity lymphedema in the treatment group, whereas 14 out of 183 patients (7.7%) were diagnosed in the control group. In multivariate analysis, ILR success showed a borderline significant decrease in risk of lymphedema [hazard ratio (HR) =0.174; 95% confidence interval (CI): 0.022-1.374; P=0.097]. Our results suggested that ILR may be a promising surgical treatment to prevent postoperative lymphedema. There is a need for larger studies with longer follow-up to confirm the findings obtained in our study.

Underwater optical image enhancement based on super-resolution convolutional neural network and perceptual fusion.

Underwater optical images often have serious quality degradations and distortions, which hinders the development of underwater optics and vision systems. Currently, there are two mainstream solutions: non-learning based and learning-based. Both have their advantages and disadvantages. To fully integrate the advantages of both, we propose an enhancement method based on superresolution convolutional neural network (SRCNN) and perceptual fusion. First, we introduce a weighted fusion BL estimation model with a saturation correction factor (SCF-BLs fusion), the accuracy of image prior information is improved effectively. Next, a refined underwater dark channel prior (RUDCP) is proposed, which combines guided filtering and an adaptive reverse saturation map (ARSM) to restore the image, which not only preserves edge details but also avoids the interference of artificial light. Then, the SRCNN fusion adaptive contrast enhancement is proposed to enhance the colour and contrast. Finally, to further enhance image quality, we employ efficient perceptual fusion to blend the different resulting outputs. Extensive experiments demonstrate that our method has outstanding visual results in underwater optical image dehazing, color enhancement and is artefact- and halo-free.

Abstract P2-14-10: Axillary Reverse Mapping Aids in Reducing the Rates of BCRL in Underserved Ethnically Diverse Population

Abstract Background: Breast Cancer Related Lymphedema (BCRL), is a long-term side effect affecting the patient’s quality of life after lymph node surgery. Historically BCRL is seen in 5-7% and 15-40% of patients undergoing sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) respectively; with the risk increasing two-fold in low-income and ethnic minority groups. Axillary Reverse Mapping (ARM) is a novel technique to distinguish drainage pathways of the arm and breast, and prior studies have reported significantly lower rates of BCRL with ARM. Lymphatic re-approximation can prevent and/or reduce lymphedema rates in cases where crossover nodes are encountered. Furthermore, blue nodes can be preserved during ALND; however, if resected during ALND, lymphatic venous (LYMPHA) procedure can help to restore lymphatic flow. However, there is a paucity of literature looking at the utility of ARM in ethnically minority groups. Therefore, we aimed to evaluate the prevalence of lymphedema in our patient population with breast cancer undergoing SLNB and ALND using ARM and in turn compare these findings to historical controls. Materials &amp; Methods: A retrospective study was carried out on patients who underwent axillary surgery with ARM from January 2019 to July 2021. Patient demographics such as age, BMI, gender, and ethnicity were recorded. Patients undergoing mastectomy vs breast conservation with SLNB ± ALND associated with ARM were monitored for lymphedema for a year at 3-month intervals using SOZO® scores, and then for another 2 years clinically. At each follow-up, SOZO® scores were computed using bioimpedance spectroscopy and compared to preoperative baseline scores. Results: A total of 142 patients’ data was evaluated, of which 83.8% belonged to the minority group (African American = 46, Hispanic = 63, Asian = 10). Mean BMI accounted for 29.1+5.31. Breast conservation surgery and mastectomy were performed in 71.8% (n=102) and 28.1% (n=40) of patients respectively. SLNB was performed on 88.7% (n=126) of the patients and ALND was carried out on 11.3% (n=16). Furthermore, 73.9% (n=105) of the patients underwent radiation therapy. Positive lymph nodes were identified in 24.6% (n=35) of patients. Blue nodes and blue lymphatics were encountered in 17.6% (n=25) and 32.4% (n=46) of patients respectively. Out of the blue nodes identified (n=25), 44% (n=11) were excised and 32% (n=8) were diagnosed as crossover nodes. All the crossover nodes were resected but none of them contributed to the development of lymphedema. Moreover, 90.9% of the patients with blue lymphatics underwent lymphatic re-approximation after excision of the blue nodes. Of the 142 patients, 59 had a three-month follow-up of which 2 patients (3.4%) developed clinical lymphedema diagnosed via SOZO® who had undergone SLNB which resolved by 6-month follow-up. Additionally, compared to the historical incidence of BCRL which accounts for up to 40.4% in ethnic minorities, we found a significantly lower incidence of lymphedema (p&amp;lt; 0.001) in our patient population. Moreover, in our study, ALND and radiation therapy did not contribute to lymphedema rates. Conclusion: ARM procedure can significantly lower BCRL even in ethnically minority groups. 3.4% of patients undergoing SLNB developed BCRL, which was significantly lower than historically reported data. Furthermore, in our study, no patients who underwent ALND developed lymphedema. Also, crossover nodes or radiation therapy did not contribute to the development of lymphedema after surgery demonstrating the effectiveness of ARM technique. Further studies with larger sample size and longer follow-up duration are necessary to better understand the utility of ARM technique in this population. Table 1 Baseline characteristics and follow-up data of the patients undergoing Axillary Reverse Mapping with SLNB ± ALND Citation Format: Fardeen Bhimani, Maureen McEvoy, Kelly Johnson, Sheldon Feldman. Axillary Reverse Mapping Aids in Reducing the Rates of BCRL in Underserved Ethnically Diverse Population [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-14-10.

Enzyme Substrate Prediction from Three-Dimensional Feature Representations Using Space-Filling Curves.

Compact and interpretable structural feature representations are required for accurately predicting properties and function of proteins. In this work, we construct and evaluate three-dimensional feature representations of protein structures based on space-filling curves (SFCs). We focus on the problem of enzyme substrate prediction, using two ubiquitous enzyme families as case studies: the short-chain dehydrogenase/reductases (SDRs) and the S-adenosylmethionine-dependent methyltransferases (SAM-MTases). Space-filling curves such as the Hilbert curve and the Morton curve generate a reversible mapping from discretized three-dimensional to one-dimensional representations and thus help to encode three-dimensional molecular structures in a system-independent way and with only a few adjustable parameters. Using three-dimensional structures of SDRs and SAM-MTases generated using AlphaFold2, we assess the performance of the SFC-based feature representations in predictions on a new benchmark database of enzyme classification tasks including their cofactor and substrate selectivity. Gradient-boosted tree classifiers yield binary prediction accuracy of 0.77-0.91 and area under curve (AUC) characteristics of 0.83-0.92 for the classification tasks. We investigate the effects of amino acid encoding, spatial orientation, and (the few) parameters of SFC-based encodings on the accuracy of the predictions. Our results suggest that geometry-based approaches such as SFCs are promising for generating protein structural representations and are complementary to the existing protein feature representations such as evolutionary scale modeling (ESM) sequence embeddings.

НОВЫЙ ПОДХОД К РАЗРАБОТКЕ АЛГОРИТМОВ МНОГОМЕРНОЙ КРИПТОГРАФИИ

Purpose of work is the reduction in the size of the public key of public-key algorithms of multivariate cryptography based on the computational difficulty of solving systems of many power equations with many unknowns. Research method is use of non-linear mappings defined as exponentiation operations in finite extended fields GF(qm) represented in the form of finite algebras. The latter makes it possible to perform the exponentiation operation in the field GF(qm) by calculating the values of power polynomials over the field GF(q), which define a hardly reversible nonlinear mapping of the vector space over GF(q) with a secret trapdoor. Due to the use of nonlinear mappings of this type, it is possible to specify a public key in multidimensional cryptography algorithms in the form of a nonlinear mapping implemented as a calculation of the values of a set of polynomials of the third and sixth degree. At the same time, due to the use of masking linear mappings that do not lead to an increase in the number of terms in polynomials, the size of the public key is reduced in comparison with known analogue algorithms, in which the public key is represented by a set of polynomials of the second and third degrees. The proposed approach potentially expands the areas of practical application of post-quantum algorithms for public encryption and electronic digital signature, related to multidimensional cryptography, by significantly reducing the size of the public key. Results of the study are the main provisions of a new approach to the development of algorithms of multidimensional cryptography are formulated. Hardly invertible nonlinear mappings with a secret trapdoor are proposed in the form of exponentiation operations to the second and third powers in finite extended fields GF(qm), represented in a form of a finite algebra. A rationale is given for specifying a public key in a form that includes a superposition of two non-linear mappings performed as a calculation of a set of second and third degree polynomials defined over GF(q). Techniques for implementing mappings of this type are proposed and specific options for specifying the fields GF(qm) in the form of finite algebras are considered. An estimate of the size of the public key in the algorithms developed within the framework of the new approach is made. at a given security level.. Practical relevance includes the developed main provisions of a new method for constructing multidimensional cryptography algorithms based on the computational difficulty of solving systems of many power equations with many unknowns and related to post-quantum cryptoschemes. The proposed approach expands the areas of practical application of post-quantum algorithms of this type by significantly reducing the size of the public key, which provides the prerequisites for improving performance and reducing technical resources for their implementation

KAM theorem for reversible mapping of low smoothness with application

KAM theorem for reversible mapping of low smoothness with application

Triple mapping for axillary staging after neoadjuvant therapy: Axillary reverse mapping with indocyanine green and dual agent sentinel lymph node biopsy

Axillary staging is 1 of the major issues of current breast cancer management after neoadjuvant systemic therapy (NST). Sentinel lymph node biopsy (SLNB) is an option for clinically node negative patients. Axillary reverse mapping (ARM) was introduced to identify and preserve the lymphatic drainage from the arm. The aim of the presented study is to employ triple mapping (radiocolloid, blue dye and indocyanine green [ICG]) to assess the crossover rate and metastatic involvement of ARM nodes after NST. Clinically node positive patients before NST who were converted to N0 and scheduled for targeted axillary dissection were included. sentinel lymph node (SLN) mapping was performed via dual agent mapping. ICG was used for ARM procedure. Blue, hot and fluorescent nodes and lymphatics were visualized in the axilla using infrared camera system and dual opto-nuclear probe (Euoroprobe3). Fifty-two patients underwent targeted axillary dissection and ARM procedures 12 out of whom had axillary node dissection. 45 of the 52 patients had at least 1 hot or blue SLN identified intraoperatively. Of these, 61.5% cases had hot SLNs, 42.3% had hot and blue, 15.4% had hot/blue/fluorescent, 7.7% had blue/fluorescent, 6 11.5% had hot/fluorescent and 7 13.5% had only clipped nodes. The overall identification rate of ARM-nodes by means of ICG technique was 86.5%. Overall crossover of ARM nodes with SLNs was determined in 36.5%. The ICG intensity was found to be higher in both hot and blue SLNS (8 out of 18 ICG positive cases, 44.4%). In 3 of 52 patients (5.7%) metastatic SLNs were hot or blue but fluorescent which predicts metastatic involvement of the ARM-nodes. More than 1-third of the patients revealed a crossover between arm and breast draining nodes. The higher observed rate of overlap might partially explain why more patients develop clinically significant lymphedema after NST even after sentinel lymph node biopsy alone. The triple mapping provides valuable data regarding the competency of lymphatic drainage and would have the potential to serve selecting patients for lymphovenous by-pass procedures at the index procedure. NST reduces the metastatic involvement of the ARM nodes. However, conservative axillary staging with sparing ARM nodes after NST necessitates further studies with larger sample size and longer follow-up.

Prenylated flavonoids with significant anti-hepatoma activity from Daphne giraldii and effects on Fibroblast Growth Factor Receptor 1 (FGFR1)

We report here the orchestration of molecular ion networking (MoIN) and a set of computational and informatics assisted structural elucidation approaches in the discovery of 23 new prenyl-flavonoids and 13 known molecules from Daphne giraldii Nitsche (Thymelaeaceae), some of which possess significant bioactivity against hepatoma carcinoma. Daphnegiratriprenylone A (DPTP-A) represents the class of polyprenyl-flavonoids possessing a triprenyl substitution, and was identified with the guidance of mass spectrometry and nuclear magnetic resonance combined with computational approaches. This approach illustrates a paradigm shift in the application of computational tools for the direct assignment of new natural product structures and it was demonstrated to be reliable compared to conventional 2D-NMR techniques. Seventeen compounds exhibited potent and selective activity against Hep3B cells (IC50 ranging from 0.42 to 7.08 μM). Tyrosine kinase FGFR1 has emerged as a potential target of polyprenyl-flavonoids by a reverse pharmacophore mapping approach. We validated that the prenyl-flavonoids effectively inhibit FGFR1 using the Mobility Shift Assay, Western blot and molecular dynamics simulations, and the results suggest significant potency of the compounds towards FGFR1. These findings provide a new chemical class with strong links to traditional medicines, possessing reasonable safety for developing potential therapeutic agents for FGFR1-related diseases.

Neutrophil Immunomodulatory Activity of Nerolidol, a Major Component of Essential Oils from Populus balsamifera Buds and Propolis.

Propolis is a resinous mixture of substances collected and processed from various botanical sources by honeybees. Black poplar (Populus balsamifera L.) buds are one of the primary sources of propolis. Despite their reported therapeutic properties, little is known about the innate immunomodulatory activity of essential oils from P. balsamifera and propolis. In the present studies, essential oils were isolated from the buds of P. balsamifera and propolis collected in Montana. The main components of the essential oil from P. balsamifera were E-nerolidol (64.0%), 1,8-cineole (10.8%), benzyl benzoate (3.7%), α-terpinyl acetate (2.7%), α-pinene (1.8%), o-methyl anisol (1.8%), salicylaldehyde (1.8%), and benzyl salicylate (1.6%). Likewise, the essential oil from propolis was enriched with E-nerolidol (14.4%), cabreuva oxide-VI (7.9%), α-bisabolol (7.1%), benzyl benzoate (6.1%), β-eudesmol (3.6%), T-cadinol (3.1%), 2-methyl-3-buten-2-ol (3.1%), α-eudesmol (3.0%), fokienol (2.2%), nerolidol oxide derivative (1.9%), decanal (1.8%), 3-butenyl benzene (1.5%), 1,4-dihydronaphthalene (1.5%), selina-4,11-diene (1.5%), α-cadinol (1.5%), linalool (1.4%), γ-cadinene (1.4%), 2-phenylethyl-2-methyl butyrate (1.4%), 2-methyl-2-butenol (1.3%), octanal (1.1%), benzylacetone (1.1%), and eremoligenol (1.1%). A comparison between P. balsamifera and propolis essential oils demonstrated that 22 compounds were found in both essential oil samples. Both were enriched in E-nerolidol and its derivatives, including cabreuva oxide VI and nerolidol oxides. P. balsamifera and propolis essential oils and pure nerolidol activated Ca2+ influx in human neutrophils. Since these treatments activated neutrophils, the essential oil samples were also evaluated for their ability to down-regulate the neutrophil responses to subsequent agonist activation. Indeed, treatment with P. balsamifera and propolis essential oils inhibited subsequent activation of these cells by the N-formyl peptide receptor 1 (FPR1) agonist fMLF and the FPR2 agonist WKYMVM. Likewise, nerolidol inhibited human neutrophil activation induced by fMLF (IC50 = 4.0 μM) and WKYMVM (IC50 = 3.7 μM). Pretreatment with the essential oils and nerolidol also inhibited human neutrophil chemotaxis induced by fMLF, again suggesting that these treatments down-regulated human neutrophil responses to inflammatory chemoattractants. Finally, reverse pharmacophore mapping predicted several potential kinase targets for nerolidol. Thus, our studies have identified nerolidol as a potential anti-inflammatory modulator of human neutrophils.

Comparing Outcomes of Robotically Assisted Latissimus Dorsi Harvest to the Traditional Open Approach in Breast Reconstruction.

We read with interest the article entitled “Comparing Outcomes of Robotically Assisted Latissimus Dorsi Harvest to the Traditional Open Approach in Breast Reconstruction,” published in the December of 2020 issue by Winocour et al.1 The study demonstrates that the postoperative seroma rate is higher in robotically assisted latissimus dorsi harvest than in the traditional open approach (16% versus 0%; P = 0.034).1 Seroma is reported to be the most common complication at the latissimus dorsi (LD) flap donor site. The reported incidence ranges from 21% to more than 79%.2 Several factors contribute to formation of the seroma: the thermal injury of electrocautery to the tissue, the disruption of lymphatic vessels and capillaries, the release of inflammatory mediators, and the creation of dead space. Various methods have been described to reduce the dead space, such as closed suction drainage, quilting of the skin flaps, application of adhesive tissue glues, infiltration of steroids or sclerosing agents, and reduction of the use of electrocautery.3 In our experience, seroma is a disabling postoperative sequela that increases the risk of wound infection, dehiscence, and skin flap necrosis, thereby compromising the success of reconstruction. In the traditional open approach, harvest of the LD muscle inevitably comprises the lesion of thoracic lymphatic vessels, which contributes in a fundamental way to the supply of the seroma. For this reason, we perform a reverse lymphatic mapping of dorsal region with Patent Blue solution.4 At the start of surgery, we inject intradermally and subcutaneously five bumps of 0.2 mL of blue dye 2.5% (Bleu Patent V 2.5%, 2 mL; Monico SPA, Venezia/Mestre, Italy) into five locations on the lower dorsal region. Referring to Suami’s study,5 we thought to mark the lymphosome that may have been damaged during flap preparation, injecting in five places on the umbilical line every 4 cm, from the incision to the midline (Fig. 1). At the end, when the LD flap is harvested, we proceed to close the interrupted lymphatic vessels, colored by Patent Blue dye (Fig. 2). Quilting sutures and fibrin glue (Evicel; Omrix Biopharmaceutical, Ltd., Tel Hashomer Ramat Gan, Israel) are used to close the dead space. We use two drains in suction, and we ask the patient not to move the arm for 2 weeks. With this approach, patients have been evidenced a lower incidence of seroma. We consider acceptable the modest increase in operating time in exchange for the shorter hospitalization times and reduced drainage times. In no case was there an adverse reaction to the Patent Blue dye. It is our opinion that higher seroma rates could be due not only to the use of electric endothermy and radiation therapy, but also to the difficulty of performing a careful coagulation of lymphatic vessels that are hardly visible if not colored. The use of Patent Blue dye for lymphatic reverse mapping for ligation of damaged lymphatic vessels has proven to be an effective, economical, and reproducible practice. Prospective studies and more case studies are needed to confirm this hypothesis.Fig. 1.: Intraoperative view of the five injections of Patent Blue dye at the level of the dorsal region.Fig. 2.: Damaged lymphatic vessels previously marked with Patent Blue dye.DISCLOSURE The authors have no financial interests to disclose. No funding was received for this communication. Roberta Albanese, MDNicola Zingaretti, MDGlenda Giorgia Caputo, MDEmanuele Rampino Cordaro, MDPier Camillo Parodi, MDClinic of Plastic and Reconstructive SurgeryDepartment of Medical Area (DAME)Academic Hospital of UdineUniversity of Udine

A Generative Feature-to-Image Robotic Vision Framework for 6D Pose Measurement of Metal Parts

Six degrees of freedom (6D) pose estimation or measurement of target objects are important robotic vision techniques that are key aspects for achieving autonomously executed robot tasks. The existing techniques solve this problem well for ordinary textured or rough-surfaced objects; however, 6D pose estimation remains a challenge for textureless, shiny metal parts in industry. This article proposes both a new framework for performing 6D pose estimation and a practical method based on the proposed framework that outperforms the state-of-the-art methods. All the existing methods follow an image-to-feature framework: they first extract features from images and then use the features to infer object poses. In contrast, our idea is a novel generative feature-to-image framework based on generative models, whose pipeline is a reverse mapping from feature to image. In other words, given a feature representing a pose, our method generates an image of the object in the exact same pose. Based on this framework, we propose a specific algorithm to indirectly infer the pose, which enables an initially random answer to gradually be regressed to the correct result. The experimental results demonstrate that the proposed deep learning method possesses greater robustness and achieves higher accuracy than the traditional methods